Medical knowledge | Dietetics, human nutrition » Maria Kotopoulea Nikolaidi - Blood flow restriction during resistance exercise, Impact on muscle strength, mass, mood and cognition

Blood flow restriction during resistance exercise: Impact on muscle strength, mass, mood and cognition Maria Kotopoulea Nikolaidi A thesis submitted in partial fulfilment of the requirements of the University of Brighton for the degree of Doctor of Philosophy July 2025 1 ABSTRACT Resistance exercise plays a critical role in promoting musculoskeletal health, enhancing cognitive function, and improving mood, making it a cornerstone of physical activity guidelines. This thesis adopts an integrative approach to assess the effects of a new progressively intermittent blood flow restriction (i-BFR) modality during low-load resistance exercise (30% of one-repetition maximum [1RM]) on perceptual responses, mood, cognitive function, and acute physiological markers related to muscle protein synthesis. The research was systematically structured, beginning with two meta-analysesone on chronic adaptations and one on acute physiological and perceptual responses. Meta-analysis 1 was conducted

to address methodological inconsistencies in the literature, such as variations in BFR pressure protocols, training duration, and participant populations. Meta-analysis 2 aimed to investigate the underlying physiological and perceptual responses to BFR compared to HL-RE. Although several mechanisms underlying BFR training have been proposed, they remain under investigation. Due to a lack of longterm studies on physiological and perceptual responses to BFR versus HL-RT in healthy adults, the second meta-analysis focused on acute studies. Specifically, Meta-analysis 1 demonstrated that BFR resistance training (BFR-RT) produces comparable increases in muscle mass and strength to HL-RT, particularly when applied to the lower body for at least eight weeks using personalised arterial occlusion pressure (AOP). While supporting the efficacy of BFR-RT under specific conditionsnamely, sufficient training duration and standardised pressure application using AOPthese findings also highlighted the

need to better understand its underlying physiological mechanisms and to evaluate perceptual responses and tolerability across different BFR modalities, such as continuous and intermittent application. Meta-analysis 2 showed that BFR resistance exercise (BFR-RE) elicited similar increases in growth hormone (GH) and cortisol compared to HL-RE, but lower responses in insulin-like growth factor-1 (IGF-1) and lactate. Data on other markers (i.e protein signalling) were limited, so the analysis focused on more consistently reported outcomes. It also revealed that intermittent BFR-RE was associated with lower ratings of perceived exertion (RPE) than HL-RE, whereas continuous BFR-RE produced similar RPE to HL-RE. These findings suggest that BFR-RE - particularly i- BFR, which remains less studied – may offer a viable, lower-exertion alternative to HL-RE, warranting further investigation into its acute physiological mechanisms compared to traditional c-BFR. Building on these insights, the

pilot study introduced a novel i-BFR protocol, consisting of progressively increased pressure throughout the sets. The findings demonstrated that this protocol was significantly more tolerable than c-BFR, with lower RPE and pain (p ≤ 0.05), and resulted in improvements in mood and cognitive function as measured by the Stroop test (p ≤ 0.05) These results highlight the potential of the new i-BFR protocol as a more tolerable and cognitively beneficial alternative to traditional BFR methods. Following the pilot, Acute Studies 1 and 2 expanded the acute investigation of this novel i-BFR protocol on mood, cognition, and hormonal responses to resistance exercise. Study 1 focused on perceptual responses, mood, cognition, and brain-derived neurotrophic factor (BDNF), revealing that iBFR was perceived as more tolerable based on semi-structured interviews, with BDNF levels showing similar increases 5’ post-exercise across all three experimental conditions (p ≤ 0.05) Acute Study 2

assessed metabolic responses, revealing marked increases in GH concentrations for both i-BFR and cBFR (182% and 734%, respectively; p ≤ 0.05), while IGF-1 only increased significantly in HL-RE (5%, p ≤ 0.05) In conclusion, this thesis confirms that i-BFR could be a feasible alternative to c-BFR and HL-RE, offering similar acute physiological responses with better tolerability and potential cognitive benefits. These metabolic responses suggest promising mechanisms that may support long-term muscle growth, but further research is needed to confirm this. Future research should also explore the long-term efficacy of i-BFR and its implications for cognitive and musculoskeletal health. 2 TABLE OF CONTENTS 1. Introduction 20 1.1 Research questions & Aims of the PhD project . 25 1.2 Chapters of the present thesis. 25 2. Literature Review 26 2.1 Introduction . 27 2.2 The Importance of Physical Activity on Health . 28 2.3 Health Benefits of Resistance Training: Physical,

Mental, and Cognitive Advantages. 30 2.4 Challenges to Resistance Training in frail populations. 40 2.5 Health Benefits of Resistance Exercise with Blood Flow Restriction . 42 2.51 Blood Flow Restriction during Low Load Resistance Training on Muscle Strength and Hypertrophy . 43 2.52 Blood Flow Restriction during Low Load Resistance Training on Mental Health.46 2.53 Blood Flow Restriction during Low Load Resistance Training on Cognitive Health.46 2.6 Methodological Challenges in Blood Flow Restriction Research . 49 2.61 Exercise protocols . 49 2.62 Cuff characteristics . 50 2.63 Blood Flow Restriction Pressure Application Protocols . 51 2.64 Blood Flow Restriction Pressures. 54 2.7 Enjoyability & Adherence in Blood Flow Restriction during Resistance Exercise.55 2.8 Continuous vs. Intermittent Pressure BFR modalities 56 2.9 Safety considerations of Blood Flow Restriction during Resistance Training . 59 2.10 Physiological Mechanisms & Adaptations to Resistance

Exercise with BFR . 61 2.101 Physiological Mechanisms of Blood Flow Restriction during Resistance Exercise.63 2.102 Impact of Blood Flow Restriction during Resistance Exercise on Growth Factors: Research Findings . 67 2.103 Impact of Blood Flow Restriction during Resistance Exercise on Cortisol: Research Findings . 70 2.11 Conclusions . 72 3. General Methodology 73 3.1 3.2 Phase A: Methodology for Systematic Reviews & Meta-Analyses. 76 3.11 Risk of Bias Assessment . 76 3.12 Statistical Analyses. 77 Phase B: Methodology for Experimental Studies . 78 3 3.21 Location, Ethics, Health & Safety . 78 3.22 Exercise Standardisation . 81 3.23 Baseline Measurements . 81 3.24 Reliability of Testing the KAATSU C3 Device . 85 3.25 Psychometric Assessments . 88 3.26 Resistance Exercise Protocol . 92 3.27 Phlebotomy & Biochemistry . 93 3.28 Statistical Analyses. 95 4. Meta-analysis 1: ‘Impact of blood flow restriction training duration, upper vs lower body

training, and pressure application protocols during resistance training on muscle strength and muscle mass adaptations in healthy adults: A Systematic Review & MetaAnalysis’ . 100 4.1 Abstract 101 4.2 Introduction 102 4.3 Methodology 105 4.31 Search Strategy & Study Selection 105 4.32 Eligibility Criteria 105 4.33 Type of Outcome Measures 106 4.34 Data Selection 106 4.35 Assessment of Quality & Risk of Bias 107 4.36 Statistical Analyses 107 4.4 Results 108 4.41 Search Results & Studies Characteristics 108 4.42 Muscle Strength Results 114 4.43 Muscle Mass Results 123 4.5 Discussion 127 4.6 Limitations 133 4.7 Conclusions 134 5. Meta-analysis 2: ‘The acute metabolic & perceptual responses to blood flow restriction resistance exercise versus high load resistance exercise in young healthy adults: A Systematic Review & Meta-Analysis’. 135 5.1 Abstract 136 5.2 Introduction 137 5.3 Methodology 141 5.31 Search Strategy & Study Selection 141

5.32 Eligibility Criteria 141 5.33 Type of Outcome Measures 142 5.34 Data Selection 142 4 5.35 Assessment of Quality and Risk of Bias 143 5.36 Statistical Analyses 143 5.4 Results 144 5.41 Search Results & Studies characteristics 144 5.42 Metabolic Responses 147 5.43 Ratings of Perceived Exertion 149 5.5 Discussion 153 5.6 Limitations 159 5.7 Conclusions 160 6. Pilot Study: ‘The acute effects of a new progressive intermittent BFR protocol on the perceptual, lactate, mood & cognitive responses to resistance exercise’ . 161 6.1 Abstract 162 6.2 Introduction 163 6.3 Methods 166 6.31 Participants 166 6.32 Experimental Procedures 167 6.33 Statistical Analyses 170 6.4 Results 171 6.41 Participants 171 6.42 Perceptual Responses 171 6.43 Lactate 172 6.44 Profile of Mood State (POMS) Questionnaire 173 6.45 Stroop Test 174 6.5 Discussion 176 6.6 Limitations 181 6.7 Conclusions 182 7. Acute Study 1: ‘High load resistance exercise vs Continuous &

Intermittent blood flow restriction: Effects on perceptual responses, brain derived neurotrophic factor (BDNF), mood & cognition’ . 183 7.1 Abstract 184 7.2 Introduction 185 7.3 Methods 187 7.31 Participants 187 7.32 Experimental Procedures 188 7.33 Semi-Structured Interviews 189 7.34 Statistical Analyses 190 7.4 Results 191 7.41 Perceptual Responses 191 7.42 Profile of Mood State (POMS)Questionnaire 194 5 7.43 Cognitive Function Tests 195 7.44 Brain-derived Neurotrophic Factor (BDNF) 199 7.45 Semi-structure Interviews 200 7.5 Discussion 202 7.6 Limitations 210 7.7 Conclusions 211 8. Acute Study 2: ‘Intermittent BFR with progressive pressure: A viable alternative to Continuous BFR & high-load resistance exercise on acute metabolic responses in healthy adults . 212 8.1 Abstract 213 8.2 Introduction 214 8.3 Methods 217 8.31 Participants 217 8.32 Experimental Procedures 217 8.33 Statistical Analyses 219 8.4 Results 220 8.41 Growth Hormone (GH) 220 8.42

Insulin-like Growth Factor-1 (IGF-1) 221 8.43 Cortisol 222 8.44 Lactate 223 8.5 Discussion 224 8.6 Limitations 228 8.7 Conclusions 229 9. General Discussion 230 9.1 Study Aims, Key Findings, and Contributions to Knowledge in Blood Flow Restriction with Resistance Exercise. 231 9.2 The new progressively increased pressure intermittent BFR modality: Physiological Responses, Participants Insights & Practical Applications. 236 9.21 Introduction of the New intermittent BFR Modality 236 9.22 Exploring Individual Variability in Perceptual and Metabolic Responses: Insights from the New Intermittent BFR Modality. 237 9.23 Implications of The New Intermittent BFR Modality 242 9.3 Future Directions 245 9.4 Challenges & Reflections 247 10. Conclusions 249 11. Reference List 252 12. Appendices 300 Appendix 1: Participants’ Information Sheet for Pilot Study . 301 Appendix 2: Participants’ Information Sheet for Acute Studies . 307 6 Appendix 3: Medical Questionnaire . 315

Appendix 4: Participant Consent Form for Pilot Study . 318 Appendix 5: Consent Form for Acute Studies. 319 Appendix 6: Short Medical Questionnaire . 320 Appendix 7: DXA Questionnaire . 321 Appendix 8: KAATSU Contraindications & Recommendations . 324 Appendix 9: KAATSU Certificate . 326 Appendix 10: Risk Assessment . 327 Appendix 11: Participants’ Dietary Diary . 332 Appendix 12: Participants’ General Instructions . 335 Appendix 13: POMS Questionnaire . 336 Appendix 14: POMS Scores Instructions . 337 Appendix 15: Full Search String Strategy for Meta-Analysis 1 . 339 Appendix 16: Full Search String Strategy for Meta-Analysis 2 . 340 Appendix 17: Muscle Soreness Questionnaire . 341 Appendix 18: Interview Questions Sample . 342 7 ABBREVIATIONS ~ Approximately a probability of Type I error in hypothesis test β probability of Type II error in hypothesis test Δ Delta Change η2 Partial eta square μL microlitre 2 Chi squared χ 1 RM 1 Repetition Maximum ANOVA

Analysis of Variance AOP Arterial Occlusion Pressure bDBP branchial Diastolic Blood Pressure BDNF Brain Derived Neurotrophic Factor BFR Blood Flow Restriction BFR-RE Resistance Exercise with Blood Flow Restriction BFR-RT Resistance Training with Blood Flow Restriction BIA Bioelectrical Impedance Analysis BMI Body Mass Index bSPB branchial Systolic Blood Pressure c-BFR Blood Flow Restriction with Continuous Pressure CI Confidence Intervals CREB cAMP-response element binding protein CSA Cross Sectional Area CV Coefficient of Variation DBP Diastolic Blood Pressure df degrees of freedom DOMS Delayed Onset of Muscle Soreness DXA Dual x-ray Absorptiometry ELISA Enzyme-linked Immunosorbent Assay GH Growth Hormone GLUT3 Glucose Transporter 3 h hour H+ Hydrogen ions HIF-1 Hypoxia-inducible Factor-1 HIF-1a Hypoxia-Inducible factor 1-alpha HL High Load 8 HL-RE High Load Resistance Exercise HL-RT High Load Resistance Training HPA

Hypothalamic Pituitary Adrenal HSP70 Heat Shock Protein 70 I2 heterogeneity i-BFR Blood Flow Restriction with Intermittent Pressure ICC Intraclass Correlation Coefficient ID identification IGF-1 Insulin Growth Factor-1 IL-10 Interleukin-10 IL-6 Interleukin-6 IQRs Interquartile Ranges KAATSU KA (additional in Japanese), AATSU (pressure in Japanese) La Lactate LL-RT Low Load Resistance Training MDC Minimal Detectable Change MDD Minimal Detection Dose MGF Mechano Growth Factor MOXY Muscle Oxygen Monitor MRI Magnetic Resonance Imaging mTOR mammalian target of rapamycin MVC Maximum Voluntary Isometric Contraction N sample size NIRS Near-Infrared Spectroscopy NO Nitric Oxide o C degrees Celsius p Probability pg.mL-1 picogram per millilitre PICOS Participants, Intervention, Comparators, Study Outcomes, and Study Design PO2 Partial Pressure of Oxygen POMS Profile of Mood States Questionnaire PRISMA Preferred Reporting Items for

Systematic Reviews and MetaAnalyses PROSPERO Prospective Register of Systematic Reviews Q1 First Quartile Q3 Third Quartile r Pearson Correlation Coefficient 9 Reps Repetitions ROS Reactive Oxygen Species RPE Ratings of Perceived Exertion RT Resistance Training SBP Systolic Blood Pressure SD Standard Deviation SMD Standardised Mean Difference SmO2 Muscle Oxygen Saturation SROC Spearman’s Rank-Order Correlation TE Typical Error TE(CV%) Coefficient of Variation for the Typical Error TMB Tetramethylbenzidine TMD Total Mood Disturbance TST testosterone VAS Visual Analogue Scale VEGF Vascular Endothelial Growth Factor vs. versus VTE venous thromboembolism 10 LIST OF FIGURES Figure 2.1 A schematic summarising the underlying proposed physiological interplay between resistance training and brain in BDNF-mediated redox regulation (Pinho et al., 2019) .38 Figure 2.2 A schematic summarising the physiological mechanisms underlying resistance

training (Ahtiainen,2018).62 Figure 2.3 A schematic summarising the physiological mechanisms underlying BFR during resistance exercise (Watson et al., 2022)63 Figure 2.4 A schematic summarising the hormonal mechanisms underlying BFR during resistance exercise (Watson et al., 2022)64 Figure 2.5 A schematic illustration of a) the basic principles of BFR, b) the application places of the cuffs for BFR and c) the possible neurobiological mechanisms of resistance training with BFR on cognitive adaptations (Torpel et al., 2018)66 Figure3.1 A schematic illustration of whole body DXA scan position 82 Figure 3.2 Bland-Altman plot between handheld doppler and ultrasound (Laurentino et al, 2020) .83 Figure 3.3 Picture of the main researcher and a research assistant performing the exercise protocol on the leg press machine.85 Figure 3.4 Schematic showing typical examples of the colour-word Stroop test.89 Figure 3.5 Schematic showing the ratings of perceived exertion scale used in the studies.92

Figure 3.6 Schematic showing the visual analogue scale for pain used in the studies.92 Figure 4.1 PRISMA diagram showing the search process of Meta-Analysis 1108 Figure 4.2 Effect sizes between HL-RT and BFR-RT on muscle strength on the upper and lower body .115 Figure 4.3 Effect sizes between HL-RT and BFR-RT on muscle strength for <8 weeks and ≥ 8 weeks training interventions.116 Figure 4.4 Effect sizes between HL-RT and BFR-RT on muscle strength on the upper body for <8 weeks and ≥ 8 weeks training interventions.117 11 Figure 4.5 Effect sizes between HL-RT and BFR-RT on muscle strength on the lower body for <8 weeks and ≥ 8 weeks training interventions.117 Figure 4.6 Effect sizes between HL-RT and BFR-RT on muscle strength based on a) other individualised BFR protocols, b) non-individualised BFR protocols, and c) percentage of AOP individualised BFR protocols.118 Figure 4.7 Effect sizes between HL-RT and BFR-RT on muscle strength based on a) >50 of AOP, and b)

≤50 of AOP.119 Figure 4.8 Effect sizes between HL-RT and BFR-RT on muscle mass on the upper and lower body.123 Figure 4.9 Effect sizes between HL-RT and BFR-RT on muscle mass for <8 weeks and ≥ 8 weeks training interventions.124 Figure 4.10 Effect sizes between HL-RT and BFR-RT on muscle mass on a) the upper body for <8 weeks, b) on the lower body for <8 weeks and c) for lower body for ≥ 8 weeks training intervention.125 Figure 4.11 Effect sizes between HL-RT and BFR-RT on muscle mass based on a) nonindividualised protocols, and b) AOP percentage individualised protocols126 Figure 4.12 Effect sizes between HL-RT and BFR-RT on muscle mass based on a)>50% of AOP, and b) ≤50 of AOP.126 Figure 5.1 PRISMA diagram showing the search process of Meta-Analysis 2145 Figure 5.2 Effect size between HL-RE and BFR-RE on Growth Hormone in Meta-Analysis 2147 Figure 5.3 Effect size between HL-RE and BFR-RE on Insulin-like Growth Factor-1147 Figure 5.4 Effect size between HL-RE and

BFR-RE on testosterone 148 Figure 5.5 Effect size between HL-RE and BFR-RE on cortisol148 Figure 5.6 Effect size between HL-RE and BFR-RE on lactate149 Figure 5.7 Effect sizes between HL-RE and BFR-RE on ratings of perceived exertion on a) continuous BFR and b) intermittent BFR .152 Figure 6.1 Schematic of the Pilot Study Design 169 Figure 6.2 A) Rating of Perceived Exertion (RPE) in Set 1, Set 2, Set 3 & Set 4 for continuous pressure BFR condition (c-BFR, white bars) and intermittent pressure BFR condition (i-BFR, black bars). The bar graphs capture the median and the white circles represent individual data points, with some on-top of each other. Values are reported as medians ± interquartile ranges (IQR) * Significant differences. B) Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR C) Individual data points in Set 1, Set 2, Set 3, & Set 4 for i-BFR.171 12 Figure 6.3 A) Visual Analogue Scale for Pain in Set 1, Set 2, Set 3 & Set 4 for continuous

pressure BFR during low load resistance exercise (c-BFR, white bars) and intermittent pressure during low load resistance exercise (i-BFR, black bars). The bar graphs capture the median and the white circles represent individual data points, with some on-top of each other. Values are reported as medians ± interquartile ranges (IQR). * Significant differences. B) Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR. C) Individual data points in Set 1, Set 2, Set 3, & Set 4 for i-BFR172 Figure 6.4 A) Bar graph of lactate concentrations pre and post exercise for continuous pressure BFR condition (c-BFR, white bars) and intermittent pressure BFR condition (i-BFR, black bars). The bar graphs capture the mean, and the white circles represent individual data points, with some on-top of each other. B) Individual data points from pre to post exercise for c-BFR C) Individual data points from pre to post exercise for i-BFR. Values are mean ± SD, * Significant differences. B)

Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR. C) Individual data points in Set 1, Set 2, Set 3, & Set 4 for i-BFR.173 Figure 6.5 A) POMS mood state scores in continuous pressure BFR (a; c-BFR, black lines) and in intermittent pressure BFR (b; i-BFR, black dashed lines) at pre-exercise B) POMS mood state scores in continuous pressure BFR (a; c-BFR, black lines) and in intermittent pressure BFR (b; i-BFR, black dashed lines) at post exercise Abbreviations; Tension (Ten), Anger (Ang), Fatigue (Fat), Depression (Dep),. Esteem (Est), Vigour (Vig), Confusion (Con) Values are mean ± SD, n = 14 * Significant differences between conditions post exercise, # Significant differences from pre to post exercise within conditions.174 Figure 6.6 A) Stroop test reaction time at pre and post exercise for continuous pressure BFR condition (c-BFR) and intermittent pressure BFR condition. The bar graphs capture the mean, and the white circles represent individual data points,

with some on-top of each other. B) Individual data points from pre to post exercise for c-BFR. C) Individual data points from pre to post exercise for i-BFR. Values are mean ± SD, * Significant differences.175 Figure 6.7 A) Stroop test correct answers at pre and post exercise for continuous pressure BFR condition (c-BFR) and intermittent pressure BFR condition. The bar graphs capture the mean, and the white circles represent individual data points, with some on-top of each other. B) Individual data points from pre to post exercise for c-BFR. C) Individual data points from pre to post exercise for i-BFR. Values are mean ± SD, * Significant differences between conditions post exercise, # Significant differences from pre to post exercise within conditions.175 Figure 7.1 Schematic of the Acute Study 1 design189 Figure 7.2 A) Rating of Perceived Exertion (RPE) in Set 1, Set 2, Set 3 & Set 4 for high load resistance exercise (HL-RE), continuous pressure BFR condition (c-BFR) and for

intermittent pressure BFR condition (i-BFR). The bar graphs capture the median and the white circles represent individual data points, with some on-top of each other. B) Individual data points in Set 1, Set 2, Set 3, & Set 4 for HL-RE. C) Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR D) Individual data points in Set 1, Set 2, Set 3, & Set 4 for i-BFR. Values are reported as medians ± interquartile ranges (IQR).192 Figure 7.3 A) Visual Analogue Scale for Pain in Set 1, Set 2, Set 3 & Set 4 for high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). The bar graphs capture the median and the white circles represent individual data points, with some on-top of each other. Values are reported as medians ± interquartile ranges (IQR). *Significant differences between conditions. B) Individual data points in Set 1, Set 2, Set 3, & Set 4 for

HL-RE. C) Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR. D) Individual data points in Set 1, Set 2, Set 3, & Set 4 for i-BFR193 Figure 7.4 A) Muscle Soreness Questionnaire data from baseline (before exercise), 24 hours post (Post24h) and 48 hours post (Post48h) for high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). The bar graphs capture the median and the white circles represent individual data 13 points, with some on-top of each other. Values are reported as medians ± interquartile ranges (IQR) B) Individual data points at baseline, Post24h, & Post48 for HL-RE. C) Individual data points at baseline, Post24h, & Post48 for c-BFR. D) Individual data points at baseline, Post24h, & Post48 for i-BFR.194 Figure 7.5 POMS mood state scores in intermittent pressure BFR (a i-BFR, black line with triangle markers), in continuous

pressure BFR (b. c-BFR, black dotted lines with diamond markers) and in high load resistance exercise (c. HL-RE, black dashed lines with cycle markers) Graph A shows the TMD scores at pre, 15 minutes and 60 minutes post exercise. Graph B shows the POMS subscales at pre-exercise across all three conditions. Graph C shows the POMS subscales at 15 minutes post exercise (Post15’) across all three conditions. Graph D shows the POMS subscales at 60 minutes post exercise (Post60’) across all three conditions. Abbreviations; Total Mood Disturbance (TMD), Tension (Ten), Anger (Ang), Fatigue (Fat), Depression (Dep), Esteem (Est), Vigour (Vig), Confusion (Con). Values are presented as medians, n = 21, * Significant differences within conditions.195 Figure 7.6 A) Reaction time in milliseconds (msec) in the Stroop test before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent

pressure BFR (i-BFR), followed by individual responses during i) HL-RE, ii) c-BFR, & iii) i-BFR. B) Correct Answers in the Stroop test before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR), followed by individual responses during i) HL-RE, ii) c-BFR, & iii) i-BFR. The bar graphs capture the mean (Graph A) and median (Graph B) and the white circles represent individual data points, with some on-top of each other. 1 Values in the bar graph A presented as mean ± SD Values in the bar graph B presented as median ± IQR.196 Figure 7.7 A) Reaction time in milliseconds (msec) in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HLRE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR), followed by individual responses during i) HL-RE, ii)

c-BFR, & iii) i-BFR. B) Correct Answers in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR), followed by individual responses during i) HL-RE, ii) c-BFR, & iii) i-BFR. The bar graphs capture the mean (Graph A) and median (Graph B) and the white circles represent individual data points, with some on-top of each other. Values in the bar graph A presented as mean ± SD Values in the bar graph B presented as median ± IQR197 Figure 7.8 A) Congruent rection time in milliseconds (msec) in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR). B) Incongruent reaction time in milliseconds (msec.) in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and

60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR). C) Congruent correct answers in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR). D) Incongruent correct answers in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR). The bar graphs capture the mean and the white circles represent individual data points, with some ontop of each other. Data presented as mean ± SD in graphs A & B Data presented as median ± IQR in graphs C & D.198 Figure 7.9 A) Brain-derived neurotrophic factor (BDNF) data before exercise (Pre), and five minutes post (Post5’) in high load

resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). B) Delta Percentage Changes (Δ%) in the HL-RE (black bar), c-BFR (white bar), and i-BFR (dark grey bar). The white circles in A & B bar graphs represent individual data points, with some on-top 14 of each other. C), D), & E) represent the individual data from Pre to Post5’ for HL-RE, c-BFR, & iBFR respectively Values presented as mean ± SD, * Significant differences199 Figure 8.1 Schematic of the Acute Study 2 design218 Figure 8.2 A) Growth Hormone (GH) data before exercise (Pre), and 5’ minutes post (Post5’) high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). The white circles represent individual data points, with some on-top of each other. B), C), & D), represent the individual data

from Pre and Post5’ for HL-RE, c-BFR, & i-BFR respectively. Values presented as mean ± SD * Significant differences.220 Figure 8.3 A) Insulin-like growth factor-1 (IGF-1) data before exercise (Pre), and five minutes post (Post5’) in high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). B Delta Percentage Changes (Δ%) in the HL-RE (black bar), c-BFR (white bar), and i-BFR (dark grey bar). The white circles in A & B bar graphs represent individual data points, with some on-top of each other. C), D), & E) represent the individual data from Pre to Post5’ for HL-RE, c-BFR, & i-BFR respectively. Values presented as mean ± SD. * Significant differences.221 Figure 8.4 A) Cortisol data before exercise (Pre), and 5’ minutes post (Post5’) high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent

pressure during low load resistance exercise (i-BFR). The white circles represent individual data points, with some on-top of each other. B) C), & D), represent the individual data from Pre and Post5’ for HL-RE, c-BFR, & i-BFR respectively. Values presented as mean ± SD * Significant differences.222 Figure 8.5 A) Lactate data before exercise (Pre), and 5’ minutes post (Post5’) high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). The white circles represent individual data points, with some on-top of each other. B), C), & D), represent the individual data from Pre and Post5’ for HL-RE, c-BFR, & i-BFR respectively. Values presented as mean ± SD * Significant differences.223 15 LIST OF TABLES Table 3.1 Reliability outcomes of SmO2 measurements using MOXY Device from previous studies.84 Table 3.2 Participants characteristics of the reliability

assessment of the KAATSU C3 device.86 Table 3.3 Reliability results of the KAATSU C3 device during rest86 Table 3.4 Reliability results of the KAATSU C3 device during exercise 87 Table 3.5 Minimal detection dose and intra/inter ELISA plate assay precision of the manufacturer’s reported accuracy for GH, IGF-1, BDNF, and cortisol.95 Table 4.1 Studies’ selection criteria for Meta-Analysis 1105 Table 4.2 Quality assessment scores of the 27 studies included in the Meta-Analysis 1109 Table 4.3 Summary of the 27 studies on muscle strength included in the Meta-Analysis 1110 Table 4.4 Summary of the 18 studies on muscle mass included in the Meta-Analysis 1120 Table 5.1 Studies’ selection criteria for Meta-Analysis 2141 Table 5.2 Quality assessment scores of the 17 studies included in the Meta-Analysis 2144 Table 5.3 Included studies’ variables for Met-Analysis 2145 Table 5.4 Summary of the studies investigating the hormonal and lactate responses in the MetaAnalysis 2146 Table 5.5

Summary of the studies investigating the ratings of perceived exertion in the MetaAnalysis 2150 Table 6.1 Participants’ characteristics in the Pilot Study, Values are presented as mean ± SD166 Table 6.2 1-RM protocol utilised in the Pilot Study (Clark et al, 2019)168 Table 7.1 Participants’ characteristics in the Acute Study 1, Values are presented as mean ± SD188 Table 7.2 Pairwise comparisons of RPE and pain between conditions191 Table 7.3 Presentation of the themes from the semi structure interviews 201 Table 9.1 Hypotheses for each study chapter presented in the thesis235 16 ACKNOWLEDGEMENTS This thesis would not have been possible without the unwavering support of my family and friends, who stood by me practically, mentally, and emotionally throughout this challenging journey. Their belief in me has been my source of strength, and I am deeply grateful for their love and encouragement. I am also immensely thankful to my lead supervisor and mentor of the last 12 years,

Dr. Ifigeneia Giannopoulou. Her guidance, and insightful feedback have shaped my academic growth, and her support both inside and outside the lab has been invaluable. I extend my sincere appreciation to the techniciansJames, Bill, and Annwho were always there to help me navigate the many technical and bureaucratic challenges I faced. Their dedication and problem-solving made an immense difference, and I cannot thank you enough for your support. To all my participants who volunteered their time, I could not have completed this research without their willingness to be part of this study. Their contribution is sincerely appreciated A heartfelt thank you goes out to my research assistantsHallum, Oli, Cristina, Salome, Kiana, and Jefferson, who spent countless hours in the lab with me. Their hard work and dedication were crucial in bringing this project to completion. Special thanks to Dr. Peter Watt, who generously shared his expertise and spent hours teaching me how to run and interpret

ELISA plates. His patience and insights were instrumental in my learning process. I am also grateful to my external supervisor Dr Borja Muniz Pardos for teaching me how to run meta-analyses and for guiding me through the statistical and methodological aspects of the process. His support was pivotal in this aspect of my research Thank you to KAATSU Ltd for funding part of my studentship, enabling this research to take place, and to Professor Yannis Pitsiladis, whose efforts in securing half of the funding and covering my expenses to attend the FIMS congress in Athens and Mexico were critical in advancing my academic career. Last but not least, a heartfelt thank you to Dr. Neil Maxwell, who joined my journey in my final year as my second supervisor. His input was remarkable and played a key role in the completion of my PhD. His support and guidance have been invaluable, and I am truly grateful This thesis is dedicated to my son Jason, my unconditional love and my greatest project! 17

AUTHOR’S DECLARATION I declare that the research contained in this thesis, unless otherwise formally indicated within the text, is the original work of the author. The thesis has not been previously submitted to this or any other university for a degree, and does not incorporate any material already submitted for a degree. Signed: - Dated: 27/11/2024 18 CONFERENCE PRECEEDINGS Kotopoulea-Nikolaidi, M. KAATSU the original blood flow restriction exercise & the latest developments for elite athletes, elderly and clinical populations. Oral Presentation at; 37th World Congress of Sport Medicine (FIMS), Guadalajara, Mexico, September 2022. Kotopoulea-Nikolaidi, M. The beneficial effects of KAATSU training: The past, the present and the future of Blood Flow Restriction (BFR). Oral presentation at; British Association of Sport and Exercise Medicine (BASEM) Conference, Brighton, UK, May 2022. Kotopoulea-Nikolaidi, M., Giannopoulou, I, Guppy, F, Comeras-Chueca, C, Collins, A,

Wright, G., Angeloudis, K, Muniz-Pardos, B, Pitsiladis, Y The effects of the new repeated progressive intermittent KAATSU-Cycle blood flow restriction protocol on the perceptual, mood and cognitive responses to resistance exercise. Oral presentation at; British Association of Sport and Exercise Medicine (BASEM) Conference, Brighton, UK, May 2022. Kotopoulea-Nikolaidi, M., Guppy, F, Muniz-Pardos, B, Pitsiladis, Y, Giannopoulou, I Effects of blood flow restriction during resistance exercise on muscle strength and metabolic, hormonal and perceptual responses in healthy adults: A systematic review and meta-analysis. Oral presentation at; 36th World Congress of Sport Medicine (FIMS), Athens, Greece, September 2021. UNDER PREPARATION FOR SUBMISSION Kotopoulea-Nikolaidi, M., Guppy, F, Muniz-Pardos, B, Comeras-Chueca, C, Pitsiladis, Y, Giannopoulou, I., (2025) Impact of blood flow restriction training duration, upper vs lower body training, and pressure application protocols during resistance

training on muscle strength and muscle mass adaptations in healthy adults: A Systematic Review & Meta-Analysis. Sports Medicine. Kotopoulea-Nikolaidi, M., Guppy, F, Muniz-Pardos, B, Comeras-Chueca, C, Pitsiladis, Y, Giannopoulou, I., (2025) The acute metabolic & perceptual responses to blood flow restriction resistance exercise vs. high load resistance exercise in young healthy adults: A Systematic Review & Meta-Analysis. Sports Medicine Kotopoulea-Nikolaidi, M., Comeras-Chueca, C, Muniz-Pardos, B, Pitsiladis, Y, Giannopoulou, I., (2025) The acute effects of a new progressive intermittent BFR protocol on the perceptual, lactate, mood & cognitive responses to resistance exercise. Strength & Conditioning Kotopoulea-Nikolaidi, M., Georgiou, O, Cousins, H, Muniz-Pardos, B, Pitsiladis, Y, Giannopoulou, I., (2025) High load resistance exercise vs Continuous & Intermittent blood flow restriction: Effects on perceptual responses, brain derived neurotrophic factor

(BDNF), mood & cognition. Endocrinology Letters Kotopoulea-Nikolaidi, M., Cousins, H, Georgiou, O, Muniz-Pardos, B, Pitsiladis, Y, Giannopoulou, I., (2025) Intermittent BFR with progressive pressure: A viable alternative to Continuous BFR & high-load resistance exercise on acute metabolic responses in healthy adults. Strength & Conditioning. 19 1. Introduction 20 Health is one of the most important attributes that all human beings aspire to, yet lifestyle choices such as physical inactivity and poor nutrition can jeopardize physical and mental health, well-being, and quality of life (Kuneš, 2014). Despite widespread recognition of the benefits of physical activity, a significant portion of the global population remains inactive (WHO, 2018). This physical inactivity is linked to an increased risk of over twenty chronic health conditions, including metabolic disorders, obesity, type 2 diabetes, cardiorespiratory diseases, coronary artery disease, certain types of

cancer, musculoskeletal conditions, along with mental health and cognitive disturbances (NIDDKD, 2015; WHO, 2023). The impact of physical inactivity becomes even more pronounced with aging, as it accelerates age-related declines in muscle mass, strength, and cognitive function, further compounding these health risks (WHO, 2023). According to the World Health Organisation (WHO), approximately 27% of adults (approximately 1 in 4) and 81% of adolescents (approximately 5 in 6) worldwide do not meet the recommended levels of physical activity (WHO, 2022a; WHO, 2022b; WHO, 2023). Physical inactivity ranks as the fourth leading cause of morbidity and mortality globally, contributing to 3.2 million deaths annually (Kohl et al, 2012; Woods et al., 2020) In the UK, around 25% of adults and nearly 80% of adolescents are physically inactive, with significant implications for health and healthcare costs (WHO, 2022a; WHO, 2022b; WHO, 2023). Increased physical activity has been shown to reduce

mortality risk significantly, with studies indicating that meeting the WHO guidelines could potentially prevent 46% of deaths associated with physical inactivity in the UK (Mok et al., 2019) Beyond personal health, physical inactivity imposes a substantial economic burden on healthcare systems, with global costs exceeding $50 billion annually. In the UK, including broader societal costs such as lost productivity and premature mortality, the financial burden rises to approximately £7.4 billion each year (NICE, 2018; Santos et al., 2023; Woods et al, 2020) One of the main barriers to exercise participation is adherence to an exercise routine (Lees et al., 2005; Morgan et al., 2016) Various factors contribute to this challenge, including lack of motivation, time constraints, high costs, and inadequate support systems (Lee et al., 2005; Morgan et al., 2016) In clinical and elderly populations, adherence to exercise is further complicated by physical limitations and fear of injury (Lee et

al., 2005) A recent review highlighted key factors affecting exercise adherence, such as low confidence in using gym equipment and an intimidating gym environment (Collado-Mateo et al., 2021) Despite the WHO’s guidelines recommending 150300 minutes of moderate intensity aerobic activity or 75-150 minutes of vigorous activity per week, along with resistance training involving major muscle groups on at least two or more days a week (WHO, 2020), many individuals struggle to meet these targets. This widespread difficulty in adhering to physical activity recommendations underscores a significant public health challenge, as physical inactivity has profound negative implications for both physical and mental health (Belvederi et al., 2020; Sudo & Ando, 2020) 21 Mental health benefits from regular physical activity are profound and well-documented (Mahindru et al., 2023) Aerobic exercise, such as walking, running, cycling, and swimming, are known for enhancing mood, reducing symptoms

of depression and anxiety, and improving cognitive function (Mersy, 1991; Wilmore & Knuttgen, 2003). While the benefits of aerobic exercise are wellestablished, there is a growing body of evidence highlighting the positive impact of resistance training on mental health outcomes (Cavarretta et al., 2019; Li et al, 2018) Resistance training not only improves strength, and muscle mass, but also positively affects mood and cognitive function (Cavarretta et al., 2019; Li et al, 2018; Lopez et al, 2018; O'Connor et al, 2010) Even a single session of resistance exercise has been demonstrated to reduce anxiety and depression symptoms and improve cognitive function (Fernandes et al., 2016; Nosrat et al, 2017; Strickland & Smith, 2014). However, traditional resistance training protocols often involve high loads, which can be challenging, poorly tolerated, or potentially unsafe, particularly for clinical populations, the elderly, and individuals with injuries (Pollock et al., 1991)

These high load resistance exercise protocols, typically involving 70-85% of one’s one repetition maximum (1-RM), can increase the risk of injury (Hass et al., 2001) Therefore, adaptations in resistance training protocols are necessary to enhance safety and adherence, especially among vulnerable cohorts (Refalo et al., 2022) One research area of increasing focus in is blood flow restriction during low load resistance training (BFR-RT), also known as occlusion or KAATSU training (Loenneke et al., 2011; Vanwye et al., 2017) BFR-RT offers an alternative modality to the gold standard high load resistance training for improving muscle strength and hypertrophy, having gained significant attention over the past decades for its benefits, especially in frail populations (Kong et al., 2022) This resistance training modality involves the application of pneumatic equipment, such as tourniquet cuffs, to restrict blood flow proximally to the muscle being trained (Loenneke et al., 2011) The

technique aims to induce physiological adaptations akin to those seen with high load resistance training but at significantly lower loads. This characteristic makes BFR-RT particularly applicable for clinically symptomatic and/or elderly populations who cannot tolerate high loading due to high mechanical effort to the joints and bones as well as individuals with injuries (Centner et al., 2019; Sato, 2005) Studies have shown significant improvements in muscle strength, hypertrophy, and overall exercise capacity, highlighting the potential of BFR-RT as an effective exercise modality for these populations (Centner et al., 2019; Loenneke et al, 2012; Sato, 2005; Vanwye et al, 2017; Yasuda et al., 2015) Specifically, BFR-RT has been reported to achieve comparable strength gains and muscle hypertrophy to traditionally prescribed high load training, in clinical populations such as women with rheumatoid arthritis (Rodrigues et al., 2020), patients undergoing rehabilitations after anterior

cruciate ligament surgery (Hughes et al., 2019), older individuals with sarcopenia (Kong et al., 2022), patients with musculoskeletal disorders (Jorgensen et al, 2023) and patients with sporadic inclusion body myositis (Jorgensen et al., 2022) Additionally, BFR-RT has been associated with significant improvements in quality of life, reductions in pain, and enhanced physical function (Hughes et al., 2019; Rodrigues et al, 2020) 22 Recent research also suggests that BFR-RT might enhance cognitive function and mood regulation, potentially through mechanisms involving the brain-derived neurotrophic factor (BDNF), a newly investigated biomarker associated with improved neuroplasticity and psychological outcomes such as reduced anxiety and depression symptoms, enhanced memory and better executive functioning (Du et al., 2021; Torpel et al, 2018) However, the evidence is limited and inconsistent. To date, only three studies to the authors’ knowledge, have examined the effects of BFR in

combination with low load resistance exercise on cognitive function, each utilizing different methodologies and reporting varied results (Du et al., 2021; Sardeli et al, 2018; Yamada et al., 2021) Specifically, Yamada et al, (2021) found no significant changes in cognitive function following low-load handgrip exercise with BFR in a sample of 60 healthy young adults. In contrast, Sardeli et al., (2018) observed cognitive improvements in healthy older adults following BFR with low load resistance exercise in the lower limbs. Regarding mood effects, only three studies -to the authors’ knowledge- also reported conflicting outcomes. Silva et al, (2018) noted an acute negative impact on mood states after low load lower body exercises with BFR compared to high load resistance exercises in basketball players. Conversely, Ruaro et al, (2020) reported significant mood improvements following low load BFR exercises. Yamada et al, (2021) found no significant differences in mood states between the

BFR group and the control group without BFR. The literature on BDNF responses to BFR resistance training is even more sparse. To the authors' knowledge, only one study by Du et al. (2021) investigated the effects of BFR-RT on BDNF responses This study reported significant increases in BDNF levels following both low-load lower body resistance exercises with BFR (~52% increase) and high-load lower body resistance exercises without BFR (~57% increase) in stroke patients with depression. This finding suggests that BFR-RT significantly elevates BDNF concentrations, in a pattern similar to the traditional resistance training without BFR. However, due to the limited evidence it remains unclear whether the specific addition of BFR confers additional benefits over standard resistance training regarding BDNF-related cognitive and mood improvements. Further research is needed to clarify the distinct impacts of BFR-RT on BDNF levels and the subsequent effects on neuroplasticity and

psychological outcomes. The tolerability of BFR-RT has been under scrutiny in recent years, particularly as an alternative to high-load resistance training due to the lower loads utilized. Despite its potential benefits, inconsistencies in its tolerability persist. Some studies have reported that BFR-RT can result in similar or even higher levels of perceived exertion and discomfort compared to high load resistance training, despite the lower resistance (Bell et al., 2018; Brandner et al, 2017; Dankel et al, 2019) This discomfort is often attributed to the constant application of BFR pressure during exercise and rest periods (Freitas et al., 2019; Loenneke et al, 2014) Such continuous pressure has been linked to increased ratings of perceived exertion (RPE) and discomfort, potentially hindering long term adherence to the training regimen (Neto et al., 2017) In response to these challenges, researchers have explored alternative BFR modalities, such as intermittent BFR-RT (Brandner et

al., 2017; Freitas et al., 2019; Neto et al, 2017) This modality involves applying pressure only during the 23 exercise phase and releasing it during resting periods (Freitas et al., 2019) Preliminary findings suggest that intermittent BFR-RT may offer better tolerability compared to continuous BFR-RT (Freitas et al., 2019; Neto et al, 2017) However, most research has focused on perceptual responses and discomfort rather than comparing the physiological effects of intermittent BFR-RT with those of high load resistance exercise. To date, only two studies -to the authors’ knowledge- have investigated pivotal key biomarkers related to muscle protein synthesis, such as growth hormone, insulin-like growth factor-1, in the context of intermittent BFR-RT (Kalantari & Siahkohian, 2020; Vilaca-Alves et al., 2022) These studies have reported similar advantageous responses between intermittent BFR-RT and high load RT without BFR (Kalantari & Siahkohian, 2020; Vilaca-Alves et al.,

2022) Additionally, research on lactate levels -a proposed driver of positive physiological adaptations such as hypertrophy, strength gains, and hormonal responses - has yielded mixed results. Some studies show lower lactate increases with intermittent BFR compared to high load resistance (Freitas et al., 2020), while others report similar lactate responses compared to high load resistance exercise (Laurentino et al., 2022) Therefore, further research is needed to clarify the physiological effects of intermittent BFR-RT to ensure it produces comparable benefits to high load resistance exercise for the musculoskeletal system. There is a paucity of research investigating the effects of intermittent BFR-RT on mood and cognition. Investigating these aspects could provide valuable insights into optimizing BFR-RT protocols to enhance resistance training adaptations with a focus on physical, mental and cognitive health as well as exercise adherence, across diverse populations. 24 1.1

Research questions & Aims of the PhD project The primary purpose of this PhD project was to evaluate the feasibility and effectiveness of a novel intermittent Blood Flow Restriction (i-BFR) training modality that progressively increases pressure in combination with brief intervals of non-occlusion. This investigation aimed to determine whether i-BFR could offer a more tolerable alternative to continuous Blood Flow Restriction (cBFR), without compromising the musculoskeletal benefits of high-load resistance exercise (HLRE). The research was systemically structured, beginning with two meta-analyses -one on chronic adaptations and one on acute physiological and perceptual responses- to address methodological inconsistencies in the literature and guide the design on the experimental studies. The primary research question was to assess the tolerability of i-BFR compared to both c-BFR and HL-RE. The secondary aim was to explore the potential effects of i-BFR on mood, cognitive function,

and metabolic responses, to determine whether this new modality offers similar physiological benefits while being more tolerable. 1.2 Chapters of the present thesis This thesis presents the following chapters: - Chapter 2: Literature review, with particular focus given to musculoskeletal adaptations and the underlying physiology of resistance training and resistance training with BFR. - Chapter 3: Methodological approaches and experimental designs employed in this PhD thesis - Chapter 4 (Study 1): Systematic Review & Meta-analysis on the chronic musculoskeletal adaptations between BFR-RT and HL-RT. - Chapter 5 (Study 2): Systematic Review & Meta-analysis on the acute metabolic and ratings of perceived exertion responses between BFR-RE and HL-RE. - Chapter 6 (Study 3): A Pilot study was conducted to investigate; a) the reliability of the KAATSU equipment, b) the effects of the new intermittent BFR-RE (KAATSU-Cycle) modality compared to the traditionally prescribed continuous

BFR-RE on lactate, perceptual responses, mood and cognition. - Chapter 7 (Study 4): An Acute study 1 was conducted to investigate a) perceptual responses, tolerability, and adherence, b) mood, c) cognitive function of the new intermittent BFR-RE (KAATSU-Cycle) modality compared to the traditional continuous BFR, and the gold standard high load resistance exercise. - Chapter 8 (Study 5): An Acute study 2 was conducted to investigate the metabolic responses of the new intermittent BFR-RT (KAATSU-Cycle) compared to the traditional continuous BFR, and the gold standard high load resistance exercise. - Chapter 9: General Discussion of the overall findings of this PhD thesis - Chapter 10: Conclusions 25 2. Literature Review 26 2.1 Introduction This chapter will begin by highlighting the critical role of physical activity in promoting health and well-being, particularly in managing chronic diseases and enhancing cognitive function and mental health. Initially, a short

introduction will be provided on aerobic exercise, as it is the primary form of exercise traditionally used to improve overall health, cognition, and mental health. However, the main emphasis of this chapter will be on resistance training (RT), and particularly its benefits on enhancements of muscle strength, muscle hypertrophy, and overall physical function, benefiting various populations, including elderly and clinical cohorts. The second part of this literature review will explore the potential of BFR training, with a particular focus on its implications for general populations and individuals who cannot tolerate high load resistance exercise. Although BFR is generally considered safe, it is crucial to address the safety considerations to ensure its ethical and safe implementation; these considerations will be thoroughly discussed in this literature review. Finally, this review will delve into the acute and chronic physiological responses to BFR, exploring the underlying

physiological mechanisms that drive these adaptations during low-load resistance exercise. In addition, the review will examine the beneficial effects of RT with and without BFR on cognition and mental health and present the scarce evidence of the literature in this area. 27 2.2 The Importance of Physical Activity on Health Physical activity is a cornerstone of healthy lifestyle, playing a crucial role in promoting overall health and well-being (Reiner et al., 2013) Among various forms of exercise, cardiorespiratory or cardiovascular endurance exercise, often referred to as aerobic exercise, is the primary and most accessible method to enhance overall health (van Baak et al., 2021) Aerobic exercise has been described as ‘requiring the use of large muscle groups and being performed continuously over a prolonged period’ (McArdle, 2015). This type of exercise relies on the aerobic energy system to meet the energy demands of the activity and improves the efficiency of the heart,

lungs, and blood vessels in delivering oxygen to working muscles during sustained physical activity (McArdle, 2015). Research evidence has demonstrated that regular aerobic exercise is linked with numerous physiological and psychological benefits, including strengthening the myocardium, enhancing blood circulation, maintaining healthy blood pressure levels, managing weight, reducing visceral fat, improving metabolic health, enhancing respiratory efficiency, improving sleep quality, cognition and mood (Ruegsegger & Booth, 2018). More specifically, the cardiovascular improvements achieved with aerobic exercise has been shown to significantly decrease the risk of heart disease, stroke and hypertension (Fuchs & Whelton, 2020). Additionally, research has demonstrated that aerobic exercise plays a pivotal role in weight management by increasing energy expenditure, enhancing metabolic rate, and reducing visceral adiposity (Vissers et al., 2013) This reduction in visceral fat is

particularly important as it is associated with various metabolic disorders such as type 2 diabetes, insulin resistance, dyslipidaemia, and hypertension (Gastaldelli et al., 2002) Consequently, improved metabolic health resulting from regular aerobic activity also enhances insulin sensitivity and aids in the regulation of blood glucose levels, thereby providing an effective strategy for the prevention and management of type 2 diabetes and metabolic syndrome (Yaribeygi et al., 2019) Moreover, evidence indicates that aerobic exercise improves respiratory health by strengthening the respiratory muscles and increasing oxygen uptake, thereby augmenting overall stamina and endurance (Jones & Carter, 2000; Mohamed & Alawna, 2020). Furthermore, studies have shown that, in addition to physical benefits, aerobic exercise positively influences cognitive function and mental health, such as improving memory, enhancing executive function, reducing symptoms of anxiety and depression, and

boosting overall mood (Guiney & Machado, 2013; Morres et al., 2019) In addition to the substantial benefits provided by regular aerobic exercise, incorporating resistance exercise plays a pivotal role and further enhances physical fitness and overall health (WHO, 2022a, WHO, 2023). Resistance exercise, also referred to as strength exercise or weightlifting, is a type of physical activity that involves the use of resistance, such as free weights, 28 resistance bands, or body weight, to induce muscular contraction (Fleck & Kraemer, 2014). It typically involves performing exercises targeting major muscle groups, with the resistance gradually increased over time to promote adaptation and progress (Fleck & Kraemer, 2014). Resistance exercise primarily utilizes the anaerobic energy system to meet the energy demands of the activity, on the contrary to aerobic exercise, which primarily relies on the aerobic energy system (Fleck & Kraemer, 2014). Research evidence has shown

that regular resistance exercise is associated with numerous physiological and psychological benefits (Westcott, 2012). These benefits include enhancing muscular strength, endurance, and hypertrophy, promoting bone density, improving metabolic health, and aiding in weight management (Strasser & Schobersberger, 2011; Westcott, 2012). Additionally, resistance exercise has been linked to improvements in functional capacity, joint stability, cognitive function, mental health, and overall quality of life (Fleck & Kraemer, 2014; Gordon et al., 2018) More details regarding the beneficial effects of resistance training will be provided in the following sections of this chapter, with a particular focus on muscle strength, muscle hypertrophy, cognitive function, and mental health. 29 2.3 Health Benefits of Resistance Training: Physical, Mental, and Cognitive Advantages Physical Health Benefits of Resistance Training: Ageing is a multifaceted process influenced by various factors,

including lifestyle choices, genetic predisposition, and the development of chronic diseases, all of which interact to shape an individual's health (Hass et al., 2001) Several physiological changes associated with aging, such as the reduction in muscle strength (known as dynapenia), muscle mass (known as sarcopenia), muscle power, bone density (known as osteopenia), elasticity, connective tissue balance, and flexibility, contribute to an increased risk of chronic diseases and injuries, with falls being a prominent cause of morbidity and mortality in the elderly population (Bell & Hoshizaki, 1981; Campbell et al., 1989; Hass et al, 2001; Lindle et al, 1997; Metter et al., 1997) It is worth mentioning that on average, muscle mass declines by 3% to 8% per decade after the age of 30, with this rate accelerating to 5% to 10% per decade after reaching the fifth decade of life (Flack et al., 2011; Marcell, 2003; Westcott, 2012) Skeletal muscle, accounting for up to 40% of total body

weight, exerts significant influence on various metabolic risk factors including obesity, dyslipidaemia, type 2 diabetes, and cardiovascular diseases (Strasser & Schobersberger, 2011; Westcott, 2012). Its pivotal role in glucose and triglyceride disposal underscores the critical impact of muscle loss on glucose intolerance and related health conditions (Dutta & Hadley, 1995; Flack et al., 2011; Strasser & Schobersberger, 2011; Westcott, 2012) An extensive body of research evidence has established that RT can be used as an effective intervention to counteract age-related challenges in body composition (ASCM, 1998; Hass et al., 2001; Hunter et al., 2004; Fahlman et al, 2011; Fragala et al, 2019; Lopez et al, 2018; Seguin & Nelson, 2003). Several studies have shown that even short, regular sessions of RT can enhance muscle strength and mass in adults of all ages (Westcott, 2012). In a recent meta-analysis conducted by Benito et al. (2020), it was documented that RT

significantly promotes muscle hypertrophy, regardless of the participants' age or training experience. Furthermore, a comprehensive metaanalysis by Currier et al (2023), which included 178 studies (n=5097; 45% women) focusing on muscle strength and 119 studies (n=3364; 47% women) targeting muscle hypertrophy, concluded that diverse RT approaches resulted in significant improvements in both muscle strength and hypertrophy for healthy adults compared to non-exercising control groups (Currier et al., 2023) Moreover, in a recent overview of systematic reviews conducted by El-Kotob et al. in 2020, the benefits of RT on health outcomes in adults aged 18 or older were investigated. This extensive analysis included eleven reviews representing 34 primary studies and a total of 382,627 participants (El-Kotob et al., 2020) El-Kotob and their team concluded that RT was strongly associated with a reduction in all-cause mortality and a decreased incidence of cardiovascular diseases. Recent

studies provide further support for the benefits of RT in older adults and clinical populations. Specifically, a meta-analysis conducted by Grgic et al in 2020, focused on very elderly 30 adults (≥75 years old), revealed that RT efficiently enhances muscle strength and size in this population (Grgic et al., 2020) This analysis also demonstrated that even the oldest participants can derive benefits from RT, effectively increasing their muscle strength and size (Grgic et al., 2020) Moreover, evidence suggests that RT significantly reduces the risk factors associated with falls, a predominant factor in increased risk for morbidity and mortality in elderly individuals (Fragala et al., 2019) Additionally, in clinical populations who cannot tolerate traditionally prescribed high intensity aerobic exercise, evidence suggests that RT offers significant health benefits (Strasser & Schobersberger, 2011). More specifically, RT has been shown to benefit individuals with obesity, type 2

diabetes, high blood pressure, cardiovascular diseases, autoimmune diseases, and specific cancers (Liu et al., 2022; Luo et al, 2024; Paluch et al, 2024; Strasser et al, 2013; Strasser & Pesta, 2013). Studies have demonstrated that increasing muscle mass through RT enhances metabolic rate and insulin sensitivity by improving muscle glucose uptake and increasing mitochondrial density (Dutta & Hadley, 1995; Flack et al., 2011; Strasser & Schobersberger, 2011; Westcott, 2012) Visceral fat is strongly linked to adverse health conditions such as metabolic syndrome, type 2 diabetes, high blood pressure, and cardiovascular diseases (Hills et al., 2010; Westcott, 2012) This improvement in insulin sensitivity from RT contributes to the reduction of visceral fat through enhanced glucose uptake by muscles, reduced insulin levels, and decreased lipogenesis, thereby lowering the accumulation of fat in visceral regions (Strasser & Pesta, 2013). Furthermore, RT induced increases in

muscle mass have been shown to improve glucose and lipid metabolism, which helps reduce the storage of excess fat, particularly in the abdominal cavity, and mitigates associated health risks (Strasser & Schobersberger, 2011; Westcott, 2012). The increase in lean body mass from RT also has been shown to lead to a reduction in body fat percentage and improved bone density, contributing to enhanced metabolic health and reduced systemic inflammation (Shin et al., 2019). This reduction in systemic inflammation, characterized by decreased pro-inflammatory markers and increased anti-inflammatory cytokines, is crucial in managing chronic diseases (Calle & Fernandez, 2010). Furthermore, RT has also been linked to favourable effects on specific types of cancer, stroke patients, and individuals coping with autoimmune diseases including Parkinson’s disease, multiple sclerosis, and rheumatoid arthritis, primarily due to improvements in muscle strength, enhanced immune function, and better

managements of chronic inflammation, and oxidative stress (Hills et al., 2010; Hunter et al, 2002; Kamada et al, 2017; Kim et al, 2019; Lemmey et al., 2009; Ryan et al, 1995; Saeidifard et al, 2019; Treuth et al, 1995) Mental Health Benefits of Resistance Training: Mental health is linked with affective states, including emotions, stress responses, impulses, and moods, which collectively influence thoughts, feelings, and behaviours (Gross et al., 2019) An imbalance of these emotional states can result in a range of psychological conditions, such as depression, anxiety, and fatigue, each significantly impacting an individual’s overall well-being, daily functioning, motivation, and overall quality of life (Gross et al., 2019) Mental health is a significant global health concern Specifically, in 2019, approximately 1 in every 8 people (970 million individuals worldwide), were living with a mental 31 disorder, with anxiety and depressive disorders being the most common (WHO, 2022).

In the UK, approximately 1 in 6 adults experience a common mental health symptom such as depression or anxiety on a weekly basis (Mental Health Foundation Statistics, 2021). Resistance training has emerged as an important intervention for improving mood and mental health, complementing the traditional role of aerobic exercise in these domains (Cavarretta et al., 2019; Strickland & Smith, 2014). While aerobic exercise has long been prescribed for its mood enhancing effects, recent studies have increasingly recognised RT’s potential to positively influence mood (Strickland & Smith, 2014; Xie et al., 2021) Specifically, the existing literature suggest that RT offers a range of mental health benefits for adults, including reductions in symptoms of fatigue, anxiety, and depression (Cavarretta et al., 2019; El-Kotob et al, 2020; O’Connor et al, 2010; Smith et al., 2022; Westcott, 2012) For example, Bartholomew & Linder (1998) found that both males and females experienced

significantly lower anxiety levels following low load RT (40-50% of 1RM), while anxiety levels significantly increased 20 minutes following high load RT (75-85% of 1RM) (Bartholomew & Linder, 1998). Similarly, Focht & Koltyn (1999) conducted a study involving 84 participants, who were randomly assigned to one of the three conditions: 50% of 1RM, 80% of 1RM, or control condition. Mood states were assessed using profile of mood states questionnaire (POMS) before and at 1, 20-, 60-, 120-, and 180-minutes post-exercise. Low-intensity exercise (50% 1RM) resulted in significant reductions in vigour immediately and at 20 minutes post exercise, in depression at 60-, 120-, and 180-minutes post exercise, in anger at 20-, 60-, and 180minutes post exercise, in confusion at 120- and 180-minutes post exercise, and in anxiety at 180minutes post exercise. High intensity exercise (80% of 1RM) led to a reduction solely in the anger at 180-minutes post exercise. Both intensity groups experienced

an increase in fatigue immediately after exercise, but this returned to baseline levels by 120- and 180-minutes post exercise. On the contrary, Herring & O’Connor (2009) reported no significant differences in total mood disturbance between high intensity resistance exercise (70% of 1RM) and very low intensity resistance exercise (15% of 1RM) on mood state in sedentary college women. There were no significant differences in the total mood disturbance on the POMS questionnaire between the two conditions; however, vigour scores were significantly higher from pre to post high intensity resistance exercise, but there were no significant differences between the conditions. Additionally, fatigue scores were significantly lower for the low intensity compared to high intensity resistance exercise (Herring & O’Connor, 2009). Positive mood improvements also have been documented in the literature in older and clinical populations following RT (Alves et al., 2017; McLafferty et al,

2004) Specifically, McLafferty et al., (2004) conducted a chronic study examining the impact of RT (target weights were increased between strength testing sessions whenever the participant reached 10 repetitions of both upper and lower body exercise) on mood in 28 sedentary older adults (60-77 years old) over a 24-week intervention. The study revealed significant improvements in various subscales of POMS among both female and male participants. Specifically, significant decreases were reported in confusion (females; -23.44%, males; -5161%), tension (females; -3529%, males: 4375%), anger 32 (females; -51.61%, males; -9333%) and Total Mood Disturbance (females; -12647%, males; 120.55%) scores Additionally, no significant changes were observed in the subscales for fatigue, vigour, and depression and there were no significant gender differences or differences between high and low intensity RT regimens in terms of mood improvement (McLafferty Jr et al., 2004) Moreover, Alves et al.,

(2017) investigated the acute affective responses to RT sessions (3 sets x 5 repetitions for upper and lower body exercises) in 14 obese women. They found significant immediate positive affective valence during workouts, highlighting the immediate mood benefits that RT, even at self-selected intensities can offer (Alves et al., 2017) These findings highlight the differential impacts of low and high intensity RT on various feelings and mood states and emphasize the potential of low intensity exercise to alleviate negative feelings and mood states subscales more effectively over time. A recent review by Cavarretta et al, (2019) aligns with these results, suggesting that lower training volumes performed at low to moderate intensities (50-70% of 1RM) with longer inter-set intervals could potentially be beneficial for reducing anxiety and enhancing depressive symptoms and mood states in various populations (Cavaretta et al., 2019) The review also reported that several factors including

volume, intensity exercise selection, order, inter-set interval, contraction type, and duration, can influence acute psychological responses. While these factors may individually affect outcomes, it is also plausible that interactions between them contribute to the psychological effects observed. This variability complicates the identification of the most effective RT regimen, reinforcing the need for more targeted research into how specific combinations and interactions of training variables can best support mental health outcomes. Several physiological mechanisms have been proposed to explain the positive mood changes observed following RT regimens (Strickland & Smith, 2014; Xie et al., 2021) These mechanisms include neurobiological effects, hormonal changes, modulation of the endocrine system, and neuroinflammatory pathways, all of which collectively contribute to the therapeutic benefits of RT (Strickland & Smith, 2014; Xie et al., 2021) RT impacts neurobiological systems

relevant to mood regulation, such as the hypothalamic-pituitary-adrenal (HPA), axis, albeit to a lesser extent compared to aerobic exercise (Strickland & Smith, 2014). The modulation of cortisol levels and HPA axis activity by RT may also contribute to mitigate symptoms associated with anxiety disorders, highlighting its potential as an anxiolytic intervention (Strickland & Smith, 2014). In addition to neurobiological effects, RT has been reported to induce changes in neurotransmitters and hormones including endorphins, serotonin, dopamine and cortisol, which are pertinent to mood stabilization (Dietrich & McDaniel, 2004; Meeusen & De Meirleir, 1995; Strickland & Smith, 2014). Moreover, RT influences other endocrine factors such as IGF-1, which has been suggested to play a pivotal role in neuroplasticity and cognitive function, further supporting its moodregulating effects (Xie et al., 2021) Furthermore, RT has been suggested to exert modulatory effects on

neuroinflammatory pathways, akin to those observed with aerobic exercise, by reducing pro33 inflammatory cytokines and enhancing anti-inflammatory markers such as interleukin-10 (IL-10), promoting a neurochemically favourable environment that supports mood stability and alleviates depressive symptoms (Xie et al., 2021) Chronic inflammation, which is increasingly recognised as a factor in the development of depression, is reduced through exercise, as it promotes the production of anti-inflammatory cytokines and decreases the levels of pro-inflammatory cytokines (Frank et al., 2021; Rose et al, 2021) The reduction in systemic inflammation has been suggested to alleviate depressive symptoms, as chronic inflammation has been linked to the disruption of neurotransmitter metabolism and neuroplasticity (Hassamal, 2023). Among the various physiological mechanisms implicated in RT’s effects on mood, brain-derived neurotrophic factor (BDNF) has been suggested to play a crucial role

(Murawska-Cialowicz et al., 2021). BDNF, a member or the neurotrophin family is essential for supporting synaptic plasticity, neuronal survival, development, and differentiation within the central nervous system (Huang & Reichardt, 2001). This protein is particularly crucial for neurogenesis in brain regions like hippocampus, which play a key role in mood regulation and emotional well-being (De Sousa, 2021; Xie et al., 2021) As a neurotrophin, BDNF modulates neuroplasticity in the brain and is extensively studied in the context of psychiatric disorders (Lin & Huang, 2020). Elevated levels of BDNF have been associated with reduced symptoms of depression and anxiety, particularly following antidepressive treatments, suggesting its significant role in mood regulation (Polyakova et al., 2015). Emerging evidence indicates that exercise-induced increases in BDNF can enhance mood by promoting synaptic plasticity, improving neurogenesis, and maintaining a healthy neural environment,

thereby contributing to better mental health and resilience against mood disorders (Szuhany et al., 2015) Recently, BDNF has been proposed to act as a myokine- produced by skeletal muscle cells in response to exercise (Yang et al., 2019) This dual role enables BDNF to exert effects both locally within muscle tissue and systemically, influencing processes such as energy metabolism and adaptation to metabolic challenges (Murawska-Cialowicz, et al., 2021; Yang et al, 2019). Additionally, by acting as a myokine, BDNF has been suggested to support the communication and coordination between skeletal muscle and other organs, including the nervous system, thereby potentially contributing to improvements in mood observed with exercise (De Sousa, 2021; Xie et al., 2021) However, it is important to note the complexity and incomplete understanding of BDNF’s responses to resistance exercise, with contradictory findings reported in the literature. More specifically, Church et al., (2016) reported

that BDNF levels increased following an acute bout of RT, regardless of the training paradigm (90% of 1RM vs. 70% of 1RM) and continued to rise after a seven-week training program in experienced lifters. Additionally, Yarrow et al, (2010) also reported significantly higher BDNF levels following a five-week progressive high load RT (50120% 1-RM) in healthy untrained young adults. Similar BDNF improvements have also been reported following RT regimens in clinical (Deus et al., 2021), overweight (Dominguez-Sanchez et 34 al., 2018), and elderly populations (Eidukaite et al, 2023) Indicatively, in a study by Deus et al, (2021), 157 haemodialysis patients with depressive symptoms were randomly assigned to a control group (n=76) or a RT (full body exercises with progressively increasing repetitions to failure) group (n=81). The RT group engaged in RT three times a week for six months BDNF levels in the RT group increased by approximately 70% after the intervention, whereas BDNF levels in

the control group decreased by approximately 21.4% (Deus et al, 2021) Exploratory analyses showed that BDNF levels were associated with improved quality of life and reduced depressive symptoms, suggesting that RT is an effective non-pharmacological tool for enhancing mental health in haemodialysis patients (Deus et al., 2021) However, some studies have reported no significant changes in BDNF levels following RT. For example, Sharifi et al, (2018) investigated the acute effects of anaerobic, aerobic, and resistance exercise (65-85% of 1RM, 8-12 repetitions until failure) on BDNF and hormones related to happiness in 32 young healthy men. Although beta-endorphin levels significantly increased after acute RT and aerobic exercise sessions, serotonin and BDNF levels did not show significant changes (Sharifi et al., 2018) Moreover, a recent review by Babiarz et al. (2022) examined the effects of RT on BDNF levels in healthy young adults and found the results to be inconclusive. This was

largely attributed to significant variability in study designs, including differences in intervention duration (ranging from 5 to 24 weeks), training intensity (from 15% to 120% of 1RM), and the muscle groups targeted (upper body, lower body, or both). These findings highlight the need for further research to clarify the relationship between different RT modalities, BDNF, and mood regulation in healthy populations, as current evidence for improving mental health through mechanisms involving BDNF remains inconsistent. It is important to note that there is no universal consensus regarding the percentage of 1RM that defines low-, moderate-, or high-load resistance training. Therefore, this thesis reflects the terminology used in individual studies when describing loading intensities, which may vary depending on study design, population characteristics, and training goals. Where necessary, the %1RM used in each study is reported to provide clarity, even when the classification (i.e,

‘moderate load’) differs between studies. For the purposes of this thesis, low-load resistance exercise is defined as <40% 1RM, moderate-load as 40–65% 1RM, and high-load as ≥70% 1RM, in line with general guidelines (ACSM, 2009; NSCA, 2016), while acknowledging that variations exist in the literature. Cognitive Health Benefits of Resistance Training: Cognitive health is critically important for maintaining quality of life and independence, particularly as individuals age (Park et al., 2003) Cognitive function encompasses a range of mental processes involved in perceiving, processing, understanding, and responding to the environment, such as attention, working memory, cognitive flexibility, and inhibitory control (APA, 2018; Morley et al., 2015; Wilke et al, 2019) These processes are integral to executive function, which enables individuals to plan, organise, execute, and regulate goal-directed behaviour (Miyake et al., 2000) Executive function specifically included key

components like planning, problem-solving, and self-regulation, in addition to working 35 memory, inhibition, and cognitive flexibility (Diamond, 2013). Aging is a primary risk factor for cognitive decline, with processes such as neurodegeneration, vascular changes, and the accumulation of brain pathology contributing to diminish cognitive function (Mattson & Magnus, 2006). These age-related changes can affect various cognitive domains, including memory, attention, executive function, and processing speed (Harada et al., 2013) The public health impact of cognitive decline and dementia is increasing as the population ages (Park et al., 2003) According to the World Health Organization, approximately 50 million people globally were living with dementia in 2019, with projections indicating this number will triple by 2050. Nearly one-third of individuals over the age of 85 experience some form of cognitive impairment (Alzheimer’s Association, 2020). Exercise, primarily in the form

of aerobic training as mentioned above, has been shown to be beneficial in maintaining and improving cognitive function, potentially delaying cognitive decline (Smith et al., 2010) In recent years, RT has increasingly been shown to improve cognitive function, despite the traditional emphasis on aerobic exercise as the primary recommended regimen (Smith et al., 2013, Wilke et al, 2019) Specifically, Alves et al, (2012) observed significantly lower reaction times in completing the Stroop Test immediately after both aerobic and strength exercise, relative to pre-exercise values, in a cohort of healthy women (average age; 52 ± 7 years). Similarly, Chang et al., (2014) investigating the acute effects of resistance exercise in cognitive function using the Stroop Test, reported enhanced performance across various Stroop conditions compared to a control group, suggesting that acute resistance exercise facilitates general cognition, particularly executive control. Furthermore, Hsieh et al,

(2016) examined the acute effects of resistance exercise on cognitive function in both young (average age; 24 ± 2 years) and older (average age; 67.2 ± 2 years) healthy adults, revealing significantly lower reaction times post exercise in both age groups (young; -7.73% in the in-set-probes and -849% in the out-of-set-probes Older; -741% in the inset-probes and -596% in the out-of-set-probes) These findings underscore the potential of resistance exercise to enhance cognitive function across different age demographics. Systematic reviews and meta-analyses have further strengthened the case for RT’s positive impact on cognitive function. El-Kotob et al, (2020) conducted an overview of 11 systematic reviews, revealing notable improvements across various age groups. Similarly, Wilke et al (2019) conducted a systematic review with multilevel meta-analysis, concluding that resistance exercise can rapidly enhance cognitive function, particularly in areas such as attention, working memory,

cognitive flexibility, and inhibitory control among healthy adults. In the context of older adults, Li et al, (2018) reported positive effects on executive cognitive ability and global cognitive function resulting from triweekly RT. However, memory benefits were not consistently observed Numerous interconnected physiological mechanisms have been proposed to explain how RT can positively affect cognitive function (Pinho et al., 2019) These mechanisms include the modulation of oxidative stress, enhancement of synaptic plasticity, upregulation of neurogenesis, and improved 36 metabolic function (Pinho et al., 2019) Central to these processes are neurotrophic factors such as BDNF, IGF-1, and Vascular Endothelial Growth Factor (VEGF) (Cassilhas et al., 2012; Pinho et al., 2019) BDNF, as mentioned earlier, is crucial for neuronal survival, differentiation, and synaptic transmission (Huang & Reichardt, 2001). Additionally, BDNF mediates the proliferation of satellite cells, which are

vital for neuronal repair and regeneration (Cotman & Berchtold, 2002). BDNF is produced not only in the brain but also in other tissues such as skeletal muscles, where it aids in muscle development and repair (Yang et al., 2019) Increased BDNF levels have been reported in response to RT, potentially enhancing glucose uptake to meet the energy demands of neuronal differentiation and synaptic activity (Burkhalter et al., 2003; Church et al, 2016; Yarrow et al, 2010). Furthermore, BDNF stimulates the expression of glucose transporter 3 (GLUT3), facilitating increased glucose uptake to support protein synthesis and neuronal function (Marosi & Mattson, 2014). The brain, however, is highly vulnerable to oxidative stress due to its high levels of phospholipids and polyunsaturated fatty acids, which are prone to oxidation and generate reactive oxygen species (ROS) in large quantities (Hwang, 2013; Radak et al., 2016) Additionally, the brain has low levels of antioxidant enzymes, and

certain areas like the striatum have high iron content, further promoting ROS formation (Hwang, 2013). Oxidative stress can decrease BDNF levels, as BDNF is sensitive to changes in the brain’s redox oxidation reduction state (Siamilis et al., 2009) While aerobic exercise has been well-documented to reduce oxidative stress and increase BDNF levels in both humans (Zhang et al., 2018) and animals (Tuon et al, 2014), the role of RT in this context is not fully understood (Chow et al., 2021; Pinho et al, 2019; Torpel et al, 2018) It is speculated that RT may upregulate antioxidant mechanisms and brain redox regulation through proteins and pathways such as the mammalian target of rapamycin (mTOR) and cAMP-response element-binding protein (CREB) (LiCausi & Hartman, 2018; Pinho et al., 2019) These pathways are crucial for cell growth, proliferation, and survival, and they enhance muscle and brain BDNF expression and activation (Pinho et al., 2019) The complex interplay between muscle and

brain in BDNF-mediated redox regulation is presented in the following schematic in Figure 2.1 of Pinho et al., (2019) 37 Figure 2.1: This Schematic described by Pinho et al, (2019) depicts the interplay between muscle and brain in BDNFmediated redox regulation Resistance exercise induces BDNF generation from CREB and mTor phosphorylation by the Pi3K/AKT signaling pathway. The BDNF release from muscle contraction reaches the brain and binds the TrkB receptor to induce the phosphorylation of different cascades of signaling pathways, which results in the additional secretion of BDNF. Brain BDNF leads to the activation of Nrf2, which regulates the expression of antioxidants molecules BDNF =brain-derived neurotrophic factor; IGF1 = insulin-like growth factor 1; IGF1R = insulin-like growth factor 1 receptor; Pi3K = phosphatidylinositol 3-kinase; IRS1 = Insulin receptor substrate 1; pAKT = protein kinase B phosphorylated; MEK = mitogen-activated protein kinase; ERK = extracellular

signal–regulated kinase; CREB = cAMP-response elementbinding protein phosphorylated; mTORC1 = mammalian target of rapamycin complex 1; p70s6k = ribosomal protein S6 kinase beta-1; TrkB = Tropomyosin receptor kinase B; PLCγ = phospholipase C gamma; CamKII = calcium/calmodulindependent protein kinase II; ARE = antioxidant response element; pKeap1 = Kelch-like ECH-associated protein 1 phosphorylated; Nrf2 = nuclear factor erythroid 2-related factor 2. However, the evidence on the impact of RT on circulating BDNF levels in humans is mixed, with studies showing both increases (Arazi et al., 2021; Church et al, 2016; Marston et al, 2017; Yarrow et al., 2010) and no changes (Correia et al, 2010; Goekint et al, 2010) For instance, Church et al, (2016) observed increased BDNF concentrations after acute bouts of resistance exercise, regardless of training paradigm (high intensity-low volume RT; 3-5 repetitions at 90% of 1RM versus low intensity-high volume RT; 10-12 repetitions at 70% of

1RM), with further increases observed after a 7-week training program in twenty resistance-trained men. Arazi et al (2021) found significant post exercise increases in BDNF following both resistance and endurance exercise regimens in older men, without significant differences between the two groups. Marston et al, (2017) compared two resistance exercise protocols (strength related resistance exercise protocol; 5 x 5 reps, 180 seconds recovery versus hypertrophy related resistance exercise protocol; 3 x 10 reps, 60 seconds recovery) on BDNF and found that hypertrophy-based protocol led to significant post-exercise increases in 38 BDNF compared to strength-based protocol. In contrast, Correia et al, (2010) reported no significant alterations in BDNF following acute resistance exercise in sixteen healthy, young adults. Similarly, Goekint et al., (2010) reported no significant acute or chronic BDNF changes following RT (50-80% of 1RM, 3 x 10 repetitions) in untrained, young, healthy

adults. Babiarz et al, (2022) conducted a review study on the effects of RT on BDNF in healthy young adults, highlighting inconclusive results due to variations in study interventions, including study duration, intensity, and musculature trained. They suggested further research to draw clearer conclusions regarding BDNF responses to RT in this population (Babiarz et al., 2022) These findings collectively demonstrate the potential of resistance exercise as a valuable strategy for enhancing cognitive function across different age groups. They also emphasize the need for further research to elucidate the physiological mechanisms underlying these effects and to investigate the impact of various resistance exercise modalities on cognition in various populations. As noted earlier, there is no universal consensus in the literature regarding what constitutes low-, moderate-, or high-load resistance training in terms of %1RM, as these classifications often vary depending on study design,

training status, and population characteristics. In this thesis, low-load RT generally refers to intensities <40% of 1RM, moderate-load RT to 40–65% of 1RM, and highload RT to ≥70% of 1RM (ASCM, 2009), unless otherwise stated. These definitions have been applied consistently throughout, while also reporting the specific intensities used in each cited study to maintain transparency. 39 2.4 Challenges to Resistance Training in frail populations High load resistance training is the gold standard for achieving muscle strength and hypertrophy. For muscle strength, high intensity RT is essential, involving heavy loads that allow for fewer repetitions (1-5 per set) at 80% to 100% of 1RM (Schoenfeld et al., 2015; Schoenfeld et al, 2021) These RT protocols promote neuromuscular adaptations and require longer rest intervals (2-5 minutes) between sets for optimal recovery and performance (Schoenfeld et al., 2015; Wernborm et al., 2007) In contrast, muscle hypertrophy focuses on

moderate to high intensity with greater training volume, typically involving 8-12 repetitions per set at 60 to 80% of 1RM with multiple sets (3-5) and shorter rest intervals (30 seconds to 1.5 minutes) (Schoenfeld et al, 2021) Even though, as mentioned in section 2.31, RT offers numerous benefits for frail populations, including improvements in muscle strength and muscle hypertrophy, implementing RT in these populations presents several challenges. Frail individuals often face mobility limitations, chronic health conditions, and a higher risk of injury, complicating the initiation and progression of RT programs. High mechanical effort on the joints due to heavy loading poses a significant risk, particularly for individuals with osteoporosis, dynapenia, sarcopenia, and/or obesity, who are susceptible to injuries from such stress (Hurst et al., 2023) Additionally, populations with a history of musculoskeletal injuries -such as those affecting shoulders, lower back, hips, knees, toes, or

other joints- may be at risk of exacerbating their conditions when engaging in traditionally prescribed high load RT (Von Rosen et al., 2018) Moreover, fear of falling is prevalent among older adults, and can serve as a significant psychological barrier to initiate and maintain a resistance training regimen (Rhodes et al., 1999) This concern often stems from the perception that engaging in certain resistance training exercises – particularly those involving upright or dynamic movements – may increase the risk of falls and/or injury (Rhodes et al., 1999) These challenges could negatively affect adherence to RT programs, which is another major concern, as frail individuals may have low motivation, fear of injury, and lack of confidence and access to appropriate facilities or trained professionals (Yardley et al., 2006) In recent years, there has been a notable research focus on the relationship between resistance training and adherence to the training programs, particularly within

frail populations. This emphasis on frail populations reflects a growing interest in understanding how resistance training can be effectively utilized as an intervention in healthcare and rehabilitation settings, and by exercise practitioners and exercise physiologists. More specifically, Rivera-Torres et al (2019) highlighted the multifactorial challenges older adults face in adhering to RT. These challenges include factors such as education level, socioeconomic status, and depression. They emphasized the importance of tailoring RT programs to the individual's needs, suggesting that starting with lower loads and high movement speeds can be beneficial. This approach allows older adults to gradually acclimate to the 40 demands of RT before progressing to higher loads, underscoring the necessity of individualized RT programs for this population (Rivera-Torres et al., 2019) Additionally, Millen & Bray, (2009) emphasized the importance of resistance training for cardiac

patients' clinical and functional benefits. They addressed the challenge of exercise adherence after cardiac rehabilitation, and their intervention targeting self-efficacy and outcome expectations for upper-body resistance exercise led to improved adherence. Their findings underlined the role of self-efficacy in enhancing adherence to resistance training in clinical populations (Millen & Bray, 2009). Additionally, Lund et al (2019) explored long-term progressive resistance training for breast cancer patients during adjuvant treatment, providing valuable insights into adherence strategies within a clinical context. One of their main findings is that home-based resistance training was associated with lower adherence specifically to obese participants and participants with average or below-average lower body muscle strength at baseline (Lund et al., 2019) Another study conducted by Coletta et al (2019) also reviewed factors associated with adherence to physical activity in cancer

patients and survivors. Their findings indicated poor adherence to physical activity guidelines, stressing the need to integrate physical activity discussions into clinical care settings to improve adherence. Specifically, they reported that adherence to guideline-based physical activity -including both aerobic and resistance training regimens- was low, with only 9% of patients adhering to these guidelines. The adherence to resistance training specifically was only 12%, while overweight or obesity was associated with not meeting guideline-based physical activity in both cancer prevention patients and cancer survivors (Coletta et al., 2019) These findings, although derived from different clinical and vulnerable populations, collectively highlight a broader concern: high load RT may not be a viable or sustainable option for many individuals due to physical, psychological, or contextual barriers. This underlines the importance of developing and investigating alternative RT approaches that

can enhance adherence while still offering physiological benefits across various populations. Given these challenges, alternative modalities of RT have been suggested for populations who cannot tolerate traditionally prescribed high load resistance exercise (Gronfeldt et al., 2020) These alternatives include methods such as low load RT (Rivera-Torres et al., 2019), elastic band exercises (Yamamoto et al., 2021), isometric training (ie pilates, yoga) (Bergamin et al, 2015; Shin, 2021), and low load RT with BFR (Loenneke et al., 2012) These approaches are designed to cater to individuals who may have limitations due to age, medical conditions, or physical frailty, thereby promoting greater adherence and reducing the risk of injury. However, more research is needed to explore these alternative modalities to traditionally prescribed high-load RT in healthy populations initially, ensuring they do not compromise the beneficial effects of traditional RT on musculoskeletal health, mood, and

cognitive function while achieving better adherence. 41 2.5 Health Benefits of Resistance Exercise with Blood Flow Restriction BFR training is an exercise modality that involves applying a specific pressure to the proximal portion of a limb using pneumatic equipment, such as tourniquet cuffs, and elastic bands to induce partial arterial occlusion and complete venous occlusion during exercise (Loenneke et al., 2011) This method aims to enhance the training stimulus by reducing blood flow and inducing local hypoxia to the muscles while allowing exercise to be performed at lower intensities (Loenneke et al., 2011) Initially, BFR training was applied exclusively to resistance exercises, where it was found to induce similar, and in some cases greater, adaptations compared to traditional high-load resistance training (Gronfeldt et al., 2020; Hughes et al, 2017; Kong et al, 2022) The first form of BFR training, known as KAATSU, was invented in Japan by Dr. Yoshiaki Sato in the 1960s

(Vanwye et al., 2017) Dr Sato reportedly conceptualised BFR training in 1966 during a Buddhist ceremony where he experiences a sensation of tightness in his legs form sitting in a certain posture (Sato, 2005). He hypothesized that restricting blood flow could replicate the effects of heavy weightlifting (Sato, 2005). Initially, Dr Sato experimented with rudimentary methods, such as wrapping limbs with belts, bands, and ropes to restrict blood flow (Sato, 2005). Through these experiments, he discovered that exercising with these wraps led to significant muscle improvements even with low load resistance exercises (Sato, 2005). Dr Sato refined his techniques over the years, eventually developing what he called “KAATSU", which is derived from Japanese, meaning “additional pressure,” with "KA" representing "additional" and "ATSU" denoting "pressure." Early KAATSU training involved the use of simple elastic bands to achieve both partial

arterial and complete venous occlusion during resistance exercises (Vanwye et al., 2017) This early approach applied a constant mode of pressure to the limbs, effectively restricted blood flow (Vanwye et al., 2017). As the field of BFR training advanced, the equipment evolved from these basic elastic bands to more sophisticated pneumatic cuffs (Scott et al., 2015) These modern devices provide precise control over pressure, allowing for more accurate and effective blood flow restriction, which enhances the overall efficacy and safety of the training method (Scott et al., 2015) Modern BFR training techniques have been shown to induce substantial improvements in muscle protein synthesis, muscle hypertrophy, and strength, across various populations, including athletes (Scott et al., 2015; Wortman, 2020), healthy young and older adults (Gronfeldt et al, 2020), individuals with musculoskeletal conditions (Hughes et al., 2017), sarcopenia (Kong et al, 2022), and cardiometabolic diseases

(Kambic et al., 2023) This evolution of equipment and methodology has enhanced the ability of BFR training to provide effective exercise adaptations while reducing the load and strain typically associated with high-intensity resistance training. It has been suggested particularly beneficial for individuals who cannot engage in high load resistance exercise due to injury, age, or other health conditions as it allows muscle growth and strength improvements using much lighter weights than traditionally required. 42 2.51 Blood Flow Restriction during Low Load Resistance Training on Muscle Strength and Hypertrophy The existing body of evidence in the literature has documented the potential beneficial effects of BFR during RT (BFR-RT) on muscle strength and muscle mass in various populations (Centner et al., 2019a; Gronfeldt et al, 2020; Hughes et al, 2017; Kong et al, 2022; Vinolo-Gil et al, 2023) Specifically, increased muscle strength and muscle mass gains have been documented

following low load BFR-RT in healthy adults compared to the traditionally prescribed high load RT (Gronfeldt et al., 2020) Similarly, comparable muscle strength and muscle mass increases following BFR-RT have also been documented in athletic populations when compared to traditional high load resistance training (HL-RT) (Bagley et al., 2015), the elderly (Centner et al, 2019; Vechin et al, 2015), and postmenopausal women (Linero & Choi, 2021). Furthermore, preliminary findings have shown improvements in muscle function following BFR-RT among injured populations (Hughes et al., 2017; Li et al, 2021), as well as clinical populations such as individuals with lung disease (Thiebaud et al., 2014), those living with Acquired Immune Deficiency Syndrome (AIDS) (Alves et al., 2021) (Alves et al, 2021), patients with chronic kidney disease (Corrêa et al, 2021), heart failure and heart disease (Cahalin et al., 2022), diabetes (Saatmann et al, 2021), and women with rheumatoid arthritis

(Rodrigues et al., 2020) Recently BFR-RT has gathered attention as a potential intervention for cancer patients, who often suffer from muscle weakness and fatigue due to their treatments (Vinolo-Gil et al., 2023) Despite promising findings regarding the beneficial effects of BFR-RT, inconsistencies in the reported outcomes have been identified, highlighting the need for further investigation and critical evaluation of existing evidence. While many studies have demonstrated positive muscle adaptations with BFR-RT at low loads compared to low load RT without BFR (de Castro et al., 2019; Fujita et al., 2008), others have reported conflicting results (Gavanda et al, 2020; Pignanelli & Burr, 2019; Pignanelli et al., 2020) De Castro et al, (2019) compared two groups performing single-leg knee extension exercises at low loads (20% of 1RM) over six weeksone group with BFR and the other without. They reported significant muscle strength increases of 31% only in the BFR group, while no

significant changes were observed in the non-BFR group. In contrast, Gavanda et al, (2020) reported similar increases in 1-RM between BFR-RT at 30% of 1RM and no BFR at the same load. Similarly, Pignanelli & Burr (2019) found comparable muscle strength and hypertrophy gains following six weeks of training with single-leg squats at 30% of 1RM, with and without BFR. They documented that low load training to failure, both with and without BFR, resulted in similar muscle strength (BFR: 79±13 to 95±13 kg vs. no-BFR: 82±13 to 100±13 kg, p<0002) and hypertrophy (BFR: 2.7±01 to 3±01 vs no-BFR: 28±02 to 3±01 cm, p<0016), with significantly higher pain levels in the BFR group (Pignanelli & Burr, 2019). Interestingly, Sieljacks et al, (2019) compared low load RT with BFR until volitional failure versus non-failure on changes in muscle size, function, and perceptual responses in fourteen young untrained males. Participants performed single leg knee 43 extension with

BFR-RT until volitional failure, while the contralateral leg performed non-volitional failure BFR-RT at the same load (25% of 1RM). Both BFR conditions led to similar increases in muscle cross sectional area (CSA) and muscle strength; however, the non-volitional failure condition was associated with lower perceived exertion, discomfort and delayed onset of muscle soreness (DOMS) (Sieljacks et al., 2019) These findings suggest that variations in exercise protocols, such as load and the inclusion of volitional failure, could potentially contribute to the conflicting outcomes observed in muscle strength, muscle hypertrophy, and perceived effort with BFR-RT. This highlights the importance of optimizing BFR-RT protocols to balance effectiveness and tolerability. Establishing standardized protocols could lead to more consistent results, thereby improving the method’s applicability and adherence. To further elucidate the efficacy of BFR-RT, it is imperative to examine findings from studies

that have compared the chronic effects of low load BFR-RT to high load RT without BFR (HL-RT), which is the traditionally prescribed exercise method for optimizing muscle strength and hypertrophy. Notably, there are also inconsistent findings in the literature regarding muscle strength and hypertrophy outcomes in these comparisons, with some studies demonstrating similar positive musculoskeletal adaptations between BFR-RT and HL-RT (Bemben et al., 2022; Centner et al, 2022; Clark et al., 2011) while other studies showing significantly greater muscle strength and muscle mass gains following HL-RT compared to BFR-RT (Barbieri et al., 2020; Cook et al, 2018; DeLemos et al., 2019) Centner et al, (2022) reported similar gains in muscle strength and mass between low load BFR-RT and HL-RT for the lower body. The study involved participants performing BFR-RT which consisted of 4 sets with repetitions structured as 30-15-15-15 at 20-35% of 1RM and pressure of 50% based on the individualised BFR

pressure. In comparison, participants in the HL-RT group completed 3 sets of 6-12 repetitions, depending on the exercise at 70-85% of 1RM. After 14 weeks, muscle mass increased by approximately 5% with HL-RT and 10% with BFR-RT, while strength gains were 38% for HL-RT and 34% for the BFR-RT group (Centner et al., 2022) Clark et al, (2011) similarly found that muscle strength gains in the lower body were comparable between BFR-RT and HL-RT. Over a four-week intervention, participants performed BFR-RT, which entailed 3 sets until failure at 30% of 1RM, with a pressure of 1.3 times the systolic blood pressure (SBP). The HL-RT group performed 3 sets to failure at 80% of 1RM The resulting strength gains were 8% and 13% for BFR-RT and HL-RT respectively (Clark et al., 2011) Conversely, Cook et al., (2018) observed that HL-RT induced greater muscle strength gains in the lower body compared to BFR-RT. The study protocol included 2 sets of 25 repetitions followed by 1 set to failure at 20% of

1RM with a pressure set at 180mmHg for the BFR-RT. The HL-RT group performed 2 sets of 10 repetitions followed by 1 set until failure. Over a six-week intervention, both BFR and no BFR groups showed significant increases in muscle strength and hypertrophy. However, HL-RT group led to a 34 ± 20% increase in muscle strength and 6% increase in muscle mass compared to control group, while BFR-RT showed 14 ± 5% increase on muscle strength and 44 3% increase in muscle mass compared to control group. Furthermore, Barbieri et al, (2020) documented greater muscle strength gains in the HL-RT group compared to BFR-RT in the biceps and triceps. Participants performed 3 sets of 15 repetitions at 70-80% of 1RM for the HL-RT, while the BFR-RT protocol involved the same sets and repetitions at 30% of 1RM with a pressure at 80% of SBP. Over five weeks, the biceps muscle strength increased by 28% with HL-RT and 5% with BFR-RT, and the triceps strength increased by 21% with HL-RT and 8% with

BFR-RT. However, muscle mass gains were greater for the BFR-RT with a 4% increase compared to no increase for HL-RT (Barbieri et al., 2020) Sugiarto et al (2017) found that muscle mass gains were similar between BFR-RT and HL-RT in the upper, body whereas muscle strength gains were significantly greater with BFR-RT. This study’s protocol included 4 sets with repetitions structured as 30-15-1515 at 30% of 1RM with a pressure set at 50mmHg for BFR-RT group, and 3 sets of 12 repetitions at 70% of 1RM for the HL-RT group. Over a five-week period, BFR-RT induced significantly greater increases in peak torque at various angular velocities compared to HL-RT. Specifically, BFR-RT resulted in increases of 50% at 60o/s, 80% at 120o/s, and 63% at 180o/s, compared to HLRT increases of 30%, 38%, and 30% respectively. Muscle mass gains were comparable between groups, with both BFR-RT and HL-RT achieving approximately 7% increases (Sugiarto et al., 2017). In summary, these studies highlight the

variability in outcomes between BFR and no BFR conditions. Although there is a body of evidence suggesting the potential beneficial effects of BFRRT on muscle strength and muscle mass, particularly for individuals seeking to enhance muscle strength and hypertrophy with lower mechanical loads, inconsistencies in the studies’ outcomes are apparent. These inconsistencies are also reflected across multiple meta-analyses Supporting this diversity in findings, two meta-analyses conducted by Lixandrao et al. in 2017 and Gronfeldt et al in 2020 have reported equivocal results when comparing muscle strength adaptations between HLRT and BFR-RT. Specifically, Lixandrao et al, (2017) observed significant muscle strength gains favouring HL-RT across various populations, while Gronfeldt et al., (2020) noted similar muscle strength improvements between interventions among healthy individuals aged 20 to 80. These mixed findings underscore the necessity for a more nuanced understanding of BFR’s

role within RT, highlighting the importance of further research to clarify its benefits and limitations. By critically examining these meta-analyses and other key studies, it is possible to identify the factors contributing to these discrepancies – such as differences in study designs, BFR pressures, cuff widths, training loads, exercise selection, and participant characteristics- and work towards optimizing BFR-RT protocols for various populations and training goals. This approach aims to ensure that the potential advantages of BFR-RT are fully realized, while also addressing any concerns related to its application and effectiveness. 45 2.52 Blood Flow Restriction during Low Load Resistance Training on Mental Health The available studies on the impact of BFR during low load resistance exercise on mood are very limited and equivocal. To the authors’ knowledge, only two studies have investigated the acute effects of BFR during low load resistance exercise on mood, and no

studies have investigated the chronic effects. Specifically, Silva et al (2018) compared the acute effects of BFR-RE versus HighLoad Resistance Exercise (HL-RE) in eleven basketball players Participants performed, in random order, four exercise sets (30-15-15-15 repetitions) at 30% of 1RM at 80% of individualised BFR pressure and three sets (10 repetitions) at 75% of 1RM without BFR. Mood state was measured before and after each session with the Brunel Mood Scale. Fatigue levels significantly increased from pre to post only in the BFR condition (~170%) but not in the HL-RE condition (~11%). However, total mood disturbance significantly decreased only in the BFR condition by approximately 8%. The authors suggested that BFR-RE might not be advisable shortly before sports competitions due to increased fatigue levels and possibly due to a higher decrease -though not significant- in tension post HL-RE (~45%) (Silva et al., 2018) Ruaro et al (2020) examined the effects of low load resistance

exercise (20% of 1RM) with BFR on mood in fourteen healthy, recreationally active male adults and found significant enhancements in mood state from pre- to post-exercise. Specifically, Ruaro et al investigated the acute effects of strength exercise with different BFR cuffs (short cuffs; 7 cm width for the upper body and 12 cm width for the lower body versus large cuffs; 12 cm width for the upper body and 20 cm for the lower body) on mood. Mood state was assessed before and after each session via POMS questionnaire. Short cuffs yielded significantly better responses in tension, depression, anger, and mental confusion compared to the large cuff. Additionally, they reported that both protocols improved overall mood state, but short cuff was more effective compared to the large cuff (Ruaro et al., 2020) The limited number of studies examining the effects of BFR-RE on mood and the somewhat equivocal findings emphasize the necessity for further investigation. More research is needed to

determine how and whether BFR-RE can promote positive or negative mood in various populations. Such studies can provide valuable insights into the psychological aspects of BFR-RE and its potential applications for different individuals and training scenarios. 2.53 Blood Flow Restriction during Low Load Resistance Training on Cognitive Health There is growing evidence, that RT induces brain changes, which could potentially contribute to improved cognitive functions (Wilke et al., 2019) While RT with BFR is widely studied in the context of muscular performance, preliminary findings suggest that this training strategy could potentially induce activation of signalling pathways associated with neuroplasticity and cognitive functions (Sardeli et al., 2018; Torpel et al, 2018) The hypothesis that BFR-RT could enhance 46 cognitive function is supported by several plausible mechanisms (Torpel et al., 2018) Specifically, Torpel et al., (2018) provide a compelling rationale for the

potential cognitive benefits of BFR-RT They suggest that BFR-RT is a promising new strategy to boost the effectiveness of RT interventions regarding cognitive performance, especially in aging populations, where cognitive decline is prevalent. This hypothesis is based on the potential ability of BFR-RT to induce neuroplasticity through several mechanisms that will be further discussed in the following section (2.10) Despite these promising theoretical foundations there are very limited studies on the effects of BFR-RT on cognition; to the authors’ knowledge, only three have been published in recent years (Du et al., 2021; Sardeli et al, 2018; Yamada et al, 2021b) Sardeli et al, (2018) investigated and compared the acute effects between HL-RE (80% of 1RM), low load resistance exercise (30% of 1RM) and BFR-RE (30% of 1RM and 50% of individualised BFR pressure) in twenty-four older adults (64 ± 5 years). They reported significant reductions in rection time measured by Stroop test only

in the low load resistance exercise condition from pre to post exercise compared to high load resistance exercise but not compared to BFR condition. They concluded that even though low load resistance exercise was the most effective resistance exercise protocol to improve cognitive function in older adults, possibly through exercise-induced optimal autonomic modulation changes, they identified a potential beneficial effect (non-significant) of low load resistance exercise with BFR on cognitive function (Sardeli et al., 2018) Yamada et al., (2021) examined the impact of isometric handgrip exercise, with and without BFR, on 65 healthy young (15-35 years) adults. Participants performed three experimental conditions in randomised counterbalanced order: a) isometric handgrip exercise at 30% of 1RM without BFR, b) isometric handgrip exercise at 30% of 1RM with BFR at 50% of individualised BFR pressure, and c) a time-matched non-exercise control condition. Cognitive function was assessed

using the Exercise-Induced Feeling Inventory and the Stroop Test before and after each exercise condition. Yamada et al., (2021) reported no significant difference in interference control and cognitive function in either BFR or no BFR condition, indicating that participants' decision-making abilities remained intact. Finally, a study conducted by Du et al., (2021) investigated the acute effects of low load resistance exercise (40% of 1RM) with and without BFR (pressure set at 120-160 mmHg) and HL-RE (80% of 1RM) on BDNF, and vascular endothelial growth factor (VEGF) in 24 post-stroke patients (48 ± 5 years) with diagnosed depression (PSD). The concentrations of both BDNF, and VEGF were significantly higher post exercise relative to pre-exercise values in the BFR-RE and HL-RE groups (BDNF: 52% and 61%, VEGF: 39% and 33% respectively), but not in low load resistance exercise without BFR (BDNF: 11%, VEGF: 6%). However, the perceived effort during exercise was notably lower in the

BFR-RE group. This finding suggests that BFR during low load resistance exercise 47 might be an effective and more comfortable alternative for PSD patients looking to harness the benefits of RT without the usual physical strain. The current evidence, although promising, is limited and presents mixed results regarding the effects of BFR-RT on cognitive health. This highlights the need for more research to determine how BFR-RT can be optimally applied across different populations, including healthy adults, older adults, and clinical groups. Future studies should aim to refine BFR-RT protocols and explore the mechanisms through which they might impact cognitive functions. Such research is essential for developing targeted interventions that could harness the potential cognitive benefits of BFR-RT, potentially enhancing cognitive health across a range of individuals. However, it is important to note that much of the current literature focuses on acute responses, and it remains unclear

how these short-term changes relate to long-term adaptations in cognitive function. Therefore, chronic studies are necessary to determine whether acute improvements following BFR-RT translate into sustained cognitive benefits over time. 48 2.6 Methodological Challenges in Blood Flow Restriction Research Noticeable methodological heterogeneity in studies examining BFR during resistance training have been reported in the literature, limiting the understanding of BFR and its effects during low load resistance training. Specifically, various BFR modalities have been introduced, resulting in differences related to the application of pressure, whether continuously or intermittently (Bartolomei et al., 2022; Mouser et al, 2019; Sinclair et al, 2022; Soligon et al, 2018) Moreover, this heterogeneity extends to the exercise protocols themselves, encompassing variations in the number of repetitions, sets, and rest periods between sets, as well as the use of different percentages of

one's one-repetition maximum (1RM) (Alvarez et al., 2020; Barbieri et al, 2020; Bemben et al, 2022; Bergamasco et al., 2022; Biazon et al, 2019; Biazon et al, 2021; Ellefsen et al, 2015; Fernandes et al., 2020; Lixandrao et al, 2015) The diversity also includes the width and materials of BFR equipment (Buckner et al., 2017; Loenneke et al, 2012), the BFR pressure application protocols (Loenneke et al., 2013), which may be individualized or non-individualized, and the specific BFR pressure levels (Mouser et al., 2018), ranging from high pressures to low pressures (Laurentino et al., 2016a; Laurentino et al, 2016b) This variability highlights the evolving nature of BFR research and the exploration of its optimal applications in resistance training. In the following subsections, the differences in exercise BFR protocols, the differences in cuff BFR characteristics, the different BFR application protocols, the different pressures applied, and the different modalities of pressure

application, such as continuous and intermittent BFR, will be discussed as presented in the literature. 2.61 Exercise protocols A variety of exercise protocols have been investigated in the BFR literature. These variations in exercise design, including the selection of different one-repetition maximum (1RM) percentages (ranging from 20-55% 1RM), repetitions (ranging from 8-30 or/and until failure), sets (ranging from 2-5), and resting periods between sets (ranging from 30 seconds to 2 minutes), play a crucial role in determining the outcomes of BFR training (Barbieri et al., 2020; Bemben et al, 2022; de Lemos Muller et al., 2019; Fernandes et al, 2020; Laswati et al, 2018; Ozaki et al, 2013; Sharifi et al, 2020; Texeira et al., 2022; Yasuda et al, 2011a, Yasuda et al, 2011b) The different choices of 1RM percentage, the number of repetitions and sets could potentially influence the level of muscle stress and metabolic perturbation experienced during resistance training with BFR,

ultimately impacting muscle adaptation (Ciccolo & Kraemer, 2013; Cuthbert et al., 2021; Grgric et al, 2020; Hass et al., 2001; Roberts et al, 2020; Stone et al, 1979; Stone et al, 1998; Stone et al, 1999a; Stone et al., 1999b; Stone et al, 2000) Previous literature studies on resistance training prescription have shown that different 1RM percentages may elicit varying degrees of muscle hypertrophy, while the selection of repetitions, sets, and rest intervals can shape the balance between muscle 49 strength and endurance (Bernandez-Vazquez et al., 2022; Campos et al, 2002; Ralston et al, 2017; Schoenfeld et al., 2015; Schoenfeld et al, 2017; Wernbom et al, 2007) Specifically, some studies have reported and suggested that higher loads with lower number of sets promote greater hypertrophic effects compared to strength-oriented regimens where greater strength adaptations are achieved with even higher loads but fewer sets and longer resting intervals (Bernandez-Vazquez et al., 2022;

Campos et al, 2002; Ralston et al, 2017; Schoenfeld et al, 2015; Schoenfeld et al, 2017; Wernbom et al., 2007) However, a recent meta-analysis conducted by Schoenfeld et al (2017) investigated the strength and hypertrophy adaptations between low versus high load resistance training, reporting changes in measures of muscle hypertrophy were similar between conditions irrespectively of the loads. In contrast, maximal strength benefits were obtained from the use of heavy loads (Schoenfeld et al., 2017) The field needs further research to determine how varying load conditions interact with BFR to influence muscle strength and hypertrophy adaptations, as well as to establish optimal BFR protocols tailored to different populations and training goals. 2.62 Cuff characteristics Numerous studies have investigated the influence of cuff width, cuff material, and related factors in BFR exercise (Buckner et al., 2017; Patterson et al, 2019) One of the main differentiators, apart from the width,

among BFR equipment is the material used in the cuffs. Specifically, wider cuffs are generally considered those measuring approximately 13.5cm or more in width and are typically made from rigid materials such as nylon and often require less pressure to achieve the same level of occlusion compared to narrower cuffs (Buckner et al., 2017) Narrow cuffs, usually 5 or less cm wide, are often constructed from more elastic materials, providing greater flexibility and better adaptability to the user’s limb size (Buckner et al., 2017) Buckner et al (2017) also noted that wider cuffs, particularly in the upper body resulted in lower arterial occlusion pressure (AOP) compared to narrower cuffs. Patterson et al (2019) emphasized the importance of considering limb characteristics and recommended using cuff widths ranging from approximately 5 cm to 13.5 cm, with appropriate pressure adjustments based on limb circumference and cuff width to ensure effective BFR. Jessee et al (2016) explored AOP

variations with different cuff widths, emphasizing how factors like arm circumference, sex, and race can impact the effectiveness of BFR training Similarly, Mattocks et al (2016) observed significant influences of cuff material on resting AOP in the upper body, underlining the need for tailored considerations based on material choice. There are inconsistencies in the evidence concerning discomfort linked to different cuff widths and materials. Buckner et al (2017) reported increased discomfort with elastic cuffs in later sets compared to nylon cuffs, while Spitz et al (2019) observed greater discomfort with wide nylon cuffs during BFR exercise, matched to narrow elastic cuffs at the same relative pressure. Conversely, Spitz et al (2021) found no compelling evidence for discomfort differences, suggesting a preference 50 among participants for narrow elastic cuffs at recommended relative pressures. Stray-Gundersen (2020) recommended narrow elastic bands over wide rigid-nylon cuffs

for at-risk individuals during light-intensity exercise due to their lower discomfort impact. Moreover, studies such as Mouser et al (2017) suggested that relative pressures, when factoring in cuff width and participant characteristics, yield similar blood flow restriction across cuffs of varying widths. These findings collectively emphasize the need for personalized approaches in BFR, accommodating individual characteristics, cuff width, and material selection, while highlighting the ongoing need for research to clarify the role of cuff material and dimensions in discomfort during BFR exercises. In conclusion, the influence of cuff width and material on BFR exercise demonstrates the necessity for personalised approaches, considering individual characteristics and appropriate pressure adjustments. While there is some evidence suggesting different levels of discomfort based on cuff material and width, the findings highlight the importance of further research to clarify these effects, as

discomfort could play a pivotal role in adherence to BFR-RT. 2.63 Blood Flow Restriction Pressure Application Protocols The application of pressure in BFR training is a critical aspect of this exercise modality (Loenneke et al., 2013; Patterson et al, 2019) Various BFR pressure application protocols have been explored in the literature, offering insight into the nuances of this method (Loenneke et al., 2013; Patterson et al., 2019) These BFR pressure application protocols can be broadly categorized into two groups: a) non-individualised pressure application, referred to as absolute or arbitrary pressures and b) individualised pressure application, also known as relative pressures (Loenneke et al., 2013; Patterson et al., 2019) The distinction between these categories has played a significant role in the development of BFR training protocols. Non-individualised pressure application protocols involve applying the same BFR pressure uniformly to all participants, regardless of their

individual characteristics and differences (Fahs et al., 2012; Loenneke et al, 2013a; Patterson et al, 2019) In the early stages of BFR research, it was suggested that pressure should be determined based on the width of the cuff used and the size of the trained limb (Fahs et al., 2012; Loenneke et al, 2013a; Patterson et al, 2019) However, as the field of BFR research expanded, it became evident that ignoring individual characteristics not only diminished the effectiveness of the intervention but also raised safety concerns (Fahs et al., 2012; Loenneke et al., 2013a; Patterson et al, 2019) Many early studies applied the same absolute pressure to all participants, independent of cuff width and limb circumference, resulting in a wide range of absolute pressures ranging from 50mmHg to 350mmHg (Cook et al., 2007; Early et al, 2020; Fahs et al., 2012; Kubota et al, 2011; Loenneke et al, 2013a; Patterson et al, 2019) While some of these studies demonstrated favourable muscular adaptations

with uniform absolute 51 pressures, others revealed that higher BFR pressures could augment cardiovascular responses and frequently lead to discomfort (Early et al., 2020; Ellefsen et al, 2015; Jessee et al, 2017; Laswati et al., 2018; Mattocks et al, 2017) Conversely, individualised BFR pressure application protocols aim to determine the pressure relative to an individual’s specific characteristics. These protocols may employ various methods, including relative calculations of an individual’s branchial systolic blood pressure (bSBP) or consideration of thigh circumference and cuff characteristics (Clark et al., 2011; Dong-il et al, 2016; Kim et al., 2009) However, despite its seeming utility as a relative method, there is scant evidence supporting the use of bSBP as an accurate estimate for BFR in the lower limbs. This divergence is not unexpected due to the substantial differences in limb sizes between the upper and lower body (Loenneke et al., 2012) Research has demonstrated

that bSBP does not significantly contribute to the variance in prediction models used for determining lower limb AOP (Loenneke et al., 2012; Loenneke et al., 2013) Instead, the thigh circumference appears to be the primary predictor of AOP (Cirilo-Sousa et al., 2019; Jessee et al, 2016: Loenneke et al, 2013) Considering the substantial body of scientific research in the field of BFR training, it becomes apparent that the most reliable and secure approach to pressure application protocol involves the determination of the AOP specific to the limb targeted for training (Loenneke et al., 2013; Patterson et al, 2019) This can be achieved by gradually inflating the cuff used until the point of complete cessation of arterial blood flow, which corresponds to 100% of the arterial occlusion pressure (Freitas et al., 2019) The measurement of AOP can be accurately performed using specialised equipment such as a handheld Doppler or ultrasound, which ensures precise detection of the point at which

arterial blood flow is completely occluded (Loenneke et al., 2013; Patterson et al, 2019) Subsequently, practitioners can apply a selected percentage of that pressure, typically ranging from 40% to 80% of the AOP, throughout the exercise session (Patterson et al., 2019) This approach allows for precise and tailored pressure application, ensuring that BFR remains both effective and safe. Although the method utilizing ultrasound or handheld Doppler to attain 100% of AOP, from which practitioners can prescribe the percentage of AOP for individuals exercising at low loads, is the most valid and accurate, it poses certain challenges (Loenneke et al., 2013; Patterson et al, 2019) These include the need for specific equipment such as ultrasound and handheld Doppler, as well as the requisite training to use these devices and efficiently assess AOP. To address these challenges several attempts have been made to develop predictive equation methods for both the upper and lower limbs.

Specifically, Loenneke et al, (2015) attempted to determine what factors should be accounted for when setting the BFR cuff pressure for the upper and lower body. They suggested that individual factors independent of bSBP and branchial diastolic blood pressure (DBP), such as arm circumference or tissue composition (muscle; MTH, fat thickness; FTH) , are important and may need to be considered in future BFR training (Loenneke et al., 2015) For the lower body, they reported that thigh circumference is the biggest predictor of arterial occlusion, noting that larger 52 thighs require greater pressures, whereas smaller thighs require less. They documented the following formulas for the upper and lower body respectively: For the upper body: Arterial occlusion (mmHg) = 0.514 (SBP) + 0339 (DBP) + 1461 (Arm circumference) + 17236 Arterial occlusion (mmHg) = 0.667 (SBP) + 0210 (DBP) + 0331 (MTH) + 0446 (FTH) + 26275 For the lower body: Arterial occlusion (mmHg) = 5.893 (Thigh circumference) +

0734 (DBP) + 0912 (SBP) – 220046 Additionally, Jessee et al., (2016) aimed to examine differences in upper body (arms) AOP between three different cuff widths and how individual characteristics influence this. They highlighted that the AOP is dependent upon cuff width as well as factors such as arm circumference, sex and race (Jessee et al., 2016a) They suggested the following equations for each cuff width to predict the AOP in the upper body: For a 5cm cuff width: Arterial occlusion (mmHg) = 2.926 (arm circumference) + 1002 (bSBP) – 0428 (arm length) + 0.213 (bDBP) + 12668 (sex; males = 0, females =1) -68493 For a 10cm cuff width: Arterial occlusion (mmHg) = 1.545 (arm circumference) + 0.722 (bSBP) − 0.235 (arm length) + 0.205 (bDBP) + 6378 (sex; males = 0, females =1) − 15918 For a 12cm cuff width: Arterial occlusion (mmHg) = = 1.393 (arm circumference) + 0710 (bSBP) − 0294 (arm length) + 0.164 (bDBP) + 6419 (sex; males = 0, females =1) − 8752 Furthermore, Sousa et

al., (2019) investigated predictive equations for application of BFR training using a cuff with a width of 18cm for lower limbs and included age, sex, thigh circumference (TC), and SBP as predictor variables. They suggested the following predictive equation for lower limbs when using BFR cuffs with a width of 18cm (Cirilo-Sousa et al., 2019): AOP (mmHg) = 65.290 + 1110 (TC in cm) + 0178 (SBP in mmHg) + 1153 (age in years) – 7984 (sex, males =1, females= 2). 53 2.64 Blood Flow Restriction Pressures The literature has explored a variety of occlusion pressures during BFR exercises, contributing to the methodological heterogeneity present in the field (Loenneke et al., 2013; Patterson et al, 2019) Some studies follow non-individualized protocols, while others use individualized pressure levels based on limb occlusion or AOP as mentioned above. The fundamental question is: how much pressure is necessary and safe? Currently, there is no clear consensus on the ideal pressures, even

when employing individualized methods (Clarkson et al., 2020; Loenneke et al, 2013; Patterson et al., 2019) Studies that utilize individualized AOP-based pressure application protocols are easier to quantify, as they specify percentages of AOP. However, there is no straightforward relationship between pressure and exercise outcomes. The choice of cuff material, width, and pressure are pivotal variables in BFR. The width and material of the cuff can significantly change the percentage of the individualised BFR pressure. Some studies have reported that wider cuffs made from nylon materials require less pressure to achieve specific individualised BFR pressures, whereas narrow elastic cuffs might need more pressure to achieve the same individualised BFR pressures (Loenneke et al., 2011) Nevertheless, researchers often apply pressure inconsistently, using arbitrary values, percentages of occlusion pressures, and different cuff types without clear rationale. Despite recent preferences

leaning towards individualized pressures, consensus remains elusive. In a 2020 systematic review by Clarkson et al., questions were raised about the rationale behind the chosen cuff pressures for BFR exercises. The study suggests that individualized cuff pressures can help reduce variability and account for equipment differences. Nevertheless, this approach lacks consistency in the literature, and many studies lack clear justifications for their chosen BFR pressures (Clarkson et al., 2020) 54 2.7 Enjoyability & Adherence in Blood Flow Restriction during Resistance Exercise Perceptual responses during exercise, encompassing factors like rating of perceived exertion, and discomfort levels are vital indicators of individuals’ affective states and can significantly influence exercise adherence and mood (Ekkekakis & Petruzzello, 1999; Hall et al., 2002; Lind et al, 2009; Welch et al., 2007) These responses become particularly important when considering exercise

interventions with BFR-RT, which has emerged as an alternative to traditional high load RT, especially for populations unable to tolerate high mechanical stress on joints and muscles (Rossi et al., 2018) However, research into the effects of BFR-RT on perceptual responses presents conflicting findings (Aniceto et al., 2021; Dankel et al, 2019; Eonho et al, 2014) Some studies indicated that low-load resistance training with BFR may lead to increased RPE and discomfort in comparison to high-load resistance training without BFR (Brandner et al., 2017; Dankel et al, 2019). Conversely, other studies have reported inconsistent results, with no clear consensus on which exercise mode is less taxing in terms of perceived effort (Lixandrao et al., 2019; Miller et al, 2020). Recent systematic reviews and meta-analyses have attempted to synthesize these findings but have also encountered challenges due to methodological heterogeneity and varied exercise protocols (De Queiros et al., 2023) While

some studies suggest that RPE during BFR-RT may be similar to non-BFR exercises when performed to voluntary failure, others indicate higher RPE during fixed repetitions schemes with BFR-RT compared to low load resistance exercise with no BFR, but lower than high load resistance exercise without BFR (De Queiros et al., 2023) Moreover, discomfort levels during BFR-RT appear to vary depending on the exercise protocol, with some studies suggesting similar discomfort between BFR and non-BFR conditions in sets performed to failure, while others reported greater discomfort during BFR-RT compared to high load resistance exercise (De Queiros et al., 2023) Methodological inconsistencies and individual variability may contribute to these conflicting results. Understanding perceptual responses during BFR-RT is critical, as they can influence exercise tolerability and adherence, particularly among sedentary, clinical, and elderly populations (Hall et al., 2002) Although, BFR shows promising

evidence regarding adherence and tolerability, the findings are equivocal (De Queiros et al., 2023) 55 2.8 Continuous vs. Intermittent Pressure BFR modalities The majority of the studies investigating BFR-RT fall under the categorization of continuous BFR training (Bemben et al., 2022; Satoh, 2011; Takarada et al, 2000; Tanimoto et al, 2005; Vechin et al., 2015; Yasuda et al, 2006; Yasuda et al, 2010; Yasuda et al, 2011b; Yasuda et al, 2015) Blood flow restriction with continuous pressure means that blood flow is continuously restricted during the entirety of the exercise session including the resting periods between sets. These studies, although demonstrating significantly greater adaptations in muscle strength and hypertrophy when training with equivalent loads compared without BFR, and similar adaptations compared to the traditional higher intensities resistance training without BFR, also report higher levels of perceived exertion and pain perception and greater delayed onset

muscle soreness in young and older individuals (Centner et al., 2019a; De Queiros et al, 2023; Fitschen et al, 2014; Gronfeldt et al, 2000; Lixandrao et al., 2018b; Neto et al, 2017; Slysz et al, 2015; Teixeira et al, 2022; Weatherholt et al., 2013) As a result, some BFR research has focused on an intermittent type of BFR training that appears to not affect pain perception and perceived effort in its participants in the same manner as continuous BFR training. Evidence from a limited number of studies, demonstrated an advantageous effect of the intermittent BFR-RT protocols by inducing similar physiological (Freitas et al., 2000; Kalantari et al, 2019; Neto et al, 2017) and musculoskeletal adaptations (Davids et al, 2021; Stone et al., 2022) as continuous BFR-RT, but with significantly less pain and discomfort (Fitschen et al., 2014; Neto et al, 2017) To date, research comparing continuous and intermittent BFR has primarily focused on acute physiological responses. The acute studies

demonstrate similar outcomes across both BFR modalities in parameters such as hemodynamic (Neto et al., 2017), growth factor biomarkers such as GH, IGF-1 (Kalantari et al., 2019), and lactate (Freitas et al, 2020) Specifically, Neto et al, (2017) reported similar heart rate and lactate responses following low load RT (20% of 1RM) with continuous and intermittent BFR (1.3 x SBP) in young healthy adults However, growth hormone responses, crucial for muscle protein synthesis are understudied within intermittent BFR. According to the authors' knowledge, only a single study has investigated the GH and IGF-1 responses across continuous BFR, and intermittent BFR. Kalantari et al (2019) observed that low load resistance exercise (20% of 1RM) with both continuous and intermittent BFR, led to comparable increases in GH levels in young healthy adults, with no significant alterations in IGF-1 among these conditions (Kalantari & Siahkohian, 2020). Additionally, the majority of the limited

studies comparing continuous and intermittent BFR have mainly focused on the lactate responses (Freitas et al., 2020; Neto et al., 2017) Specifically, Freitas et al, (2020) documented no significant differences in the lactate increases following both low load RT (20% of 1RM) with continuous and intermittent BFR (50% of AOP) in young untrained adults. Similarly, Neto et al, (2017) reported similar lactate increases following low load RT (20% of 1RM) with intermittent BFR (1.3 x SBP) compared to continuous BFR (1.3 x SBP) in young, trained adults 56 Beneficial and similar effects have been reported in the BFR literature on musculoskeletal adaptations following the traditionally prescribed continuous BFR and intermittent BFR. Specifically, Davids et al. (2021) reported similar musculoskeletal adaptations following 21 sessions over seven weeks with low load RT (30% of 1RM) with continuous and intermittent BFR (60% of AOP) in young healthy adults. They reported muscle cross-sectional

area increases from pre- to post-training in both continuous (1%) and intermittent BFR (2%), with strength gains of 14% for continuous and 19% for intermittent BFR, showing no significant differences between the two BFR modalities. Similarly, Neto et al (2019) reported that young healthy adults with RT experience who participated in 12 sessions over 6 weeks with low load (20% of 1RM) using continuous BFR (80% of AOP) and intermittent BFR (80% of AOP) exhibited similar muscle activations in the biceps and triceps during various exercises. Notably, intermittent BFR improved the muscle activation of the biceps brachii during the front pull-down exercise compared to continuous BFR (Neto et al., 2019) Additionally, Stone et al. (2022) investigated healthy astronauts (average age 36 ± 10 years) and found that low load RT (20% of 1RM for the upper extremity and 30% of 1RM for the lower extremity) with intermittent BFR (40% of AOP) improved muscular strength and function, with no synergistic

effects observed from leucine/protein supplementation combined with BFR exercise. The majority of studies favour intermittent BFR in terms of pain and discomfort compared to traditionally prescribed continuous BFR (Fitschen et al., 2014; Freitas et al, 2019; Yasuda et al, 2013), although there are some studies reporting no significant differences (Sinclair et al., 2022) and one study reporting higher RPE in intermittent compared to continuous (Brandner et al., 2017) Specifically, Fitschen et al. (2014) reported significantly higher pain scores in the last two sets in continuous BFR compared to intermittent BFR (30% of 1RM, set pressure at 160 mmHg) in young healthy adults. Similarly, Freitas et al (2019) also documented significantly higher pain scores in continuous BFR compared to intermittent BFR in sets 3 and 4 during low load RT (20% of 1RM) in young healthy adults. Furthermore, Yasuda et al (2013) reported significantly higher ratings of perceived exertion (RPE) in the last set

during low load resistance exercise (20% of 1RM) with continuous compared to intermittent BFR (set at 160 mmHg) in young healthy adults. Moreover, Neto et al. (2017) found higher RPE scores in continuous BFR during low load resistance exercise (20% of 1RM) compared to intermittent BFR (1.3 x SBP) in military men, although this difference did not reach statistical significance. In a more recent study, Schwiete et al, (2021) explored the long-term perceptual responses to a six-week training program comparing an alternative intermittent BFR (20% of 1RM), where cuffs were inflated during rest periods (80% of AOP) and deflated during exercise sets, with the traditional continuous BFR. They observed that mid-intervention, participants experienced higher pain levels with continuous BFR (20% of 1RM at 80% of AOP) compared to intermittent BFR (20% of 1RM at 80% of AOP). However, by the end of the six-week period, the difference in pain perception and RPE was no longer significant in

recreationally trained healthy young males. Furthermore, Sinclair et al (2022) conducted a recent meta-analysis which concluded that there was no significant difference in perceived discomfort ratings between 57 continuous and intermittent BFR protocols. On the contrary, a study conducted by Brandner et al, (2017) is the only study to the authors’ knowledge, reporting significantly higher RPE following low load resistance exercise (20% of 1RM) with intermittent BFR (130% of SBP) compared to continuous (80% of SBP) in untrained young males. However, it should be noted that this study was the only study, using different BFR pressures between continuous and intermittent modalities. Further research is necessary to fully understand the physiological mechanisms and long-term effects of intermittent BFR training. Future studies should focus on standardizing pressure protocols and exploring the impact on key biomarkers and muscle adaptation processes. 58 2.9 Safety considerations

of Blood Flow Restriction during Resistance Training A comprehensive evaluation of the existing literature and research is essential to gain a deeper understanding of the safety, effectiveness, and practical applications of BFR-RT in various populations. In this discussion, the safety considerations associated with BFR in exercise will be explored and review key findings from relevant studies to provide a well-rounded perspective on its utilization. The study by Patterson et al. (2019) provides an in-depth analysis of Blood Flow Restriction Resistance Exercise (BFR-RE), primarily focusing on its methodology, application, and safety considerations. The authors offer a comprehensive model for prescribing BFR-RE exercises, covering various aspects, including frequency, load, restriction time, muscle groups targeted, sets, cuff sizes, repetition schemes, rest intervals, restriction forms, and execution speed. Furthermore, the research explores the cardiovascular responses associated with

BFR-RE, distinguishing between central and peripheral vascular responses and elucidating how these responses are influenced by BFR levels, exercise modes, and application methods. Notably, the study emphasizes that BFR-RE induces unique effects on central and peripheral vascular responses, with varying outcomes depending on specific factors. Moreover, it investigates the potential risk of venous thromboembolism (VTE) associated with BFR-RE. The authors scrutinize both acute and chronic VTE measures and associated blood coagulation markers, ultimately concluding that the available evidence does not indicate an increased risk of VTE due to BFR-RE (Patterson et al., 2019) The study also delves into the impact of BFR-RE on the fibrinolytic system, reinforcing the need for further research to comprehend fully its effects in this context. In addition, the authors discuss muscle damage, distinguishing between the eccentric and inflammatory phases of muscle damage and examining various markers

such as muscle soreness, reduced torque production, and muscle oedema. Overall, the study concludes that the risk of adverse events -specifically VTE and muscle damage – is not significantly higher with BFR-RE compared to conventional RT methods (Patterson et al., 2019) A comprehensive systematic review conducted by Minniti et al. (2020) reinforces the importance of gaining a more comprehensive understanding of BFR-RT, particularly its applications, limitations, and safety aspects particularly for patients with musculoskeletal disorder. As BFR-RT gains broader acceptance, there has been an emerging consensus within the clinical community regarding the need for a more comprehensive appraisal of the current applications, constraints, and safety considerations of BFR-RT to ensure its effective utilization with appropriate patient groups. Their findings indicate that BFR-RT demonstrates a considerable degree of safety, especially when applied in adherence to evidence-based guidelines,

particularly in patients with knee-related musculoskeletal disorders. Nevertheless, it is prudent to approach these findings with a degree of 59 caution, given the constraints posed by the limited number of studies, small, pooled sample size, and relative uniformity in the patient populations under investigation (Minniti et al., 2020) Moreover, in another comprehensive review conducted by Christina-Oliveira et al. (2019), the clinical safety of BFR-RT in patients with cardiovascular disease was examined. Their findings echo the concern regarding the potential induction of abnormal reflex-mediated cardiovascular responses by BFR-RT. Of particular interest is the muscle metaboreflex, an ischemia-induced pressor reflex originating in skeletal muscle. As elucidated by Christina-Oliveira et al (2020), their review synthesizes available evidence that suggests BFR-RT may indeed elicit abnormal cardiovascular responses due to heightened metaboreflex activation. It is noteworthy that these

abnormal cardiovascular responses appear to be more pronounced in individuals with elevated cardiovascular risk, such as the elderly and those with pre-existing cardiovascular conditions. Notwithstanding, this emphasizes the importance of thorough research and evaluation of the cardiovascular safety of BFR-RT, especially in clinical populations. Addressing these concerns is essential for making informed decisions regarding the implementation of BFR-RT as an exercise modality in clinical practice (Christina-Oliveira et al., 2020) 60 2.10 Physiological Mechanisms & Adaptations to Resistance Exercise with BFR Resistance training, as mentioned earlier, leads to significant gains in muscle function, size, and strength. The underlying physiological mechanisms responsible for these adaptations are complex and involve the interplay of various systems such as the muscular, nervous, endocrine, cardiovascular, skeletal, metabolic, and immune systems (Ahtiainen, 2018) (Fig. 21) This

interplay subsequently stimulates signalling pathways, intracellular pathways, hormonal secretions, increased metabolites, protein synthesis, gene expression, muscle fibre recruitment, and cellular hypertrophy (Ahtiainen, 2018; Kraemer & Ratamess, 2004) (Fig. 21) The exact mechanisms remain under investigation and are not yet fully understood, particularly in terms of the complex interplay among these systems, hormones, gene expression, signalling pathways and metabolites involved. The extent to which these mechanisms are stimulated highly depends on the resistance exercise program variables such as the choice and order of the exercises performed, muscle contraction type, velocity, intensity, volume, rest periods between sets, and training frequency, as well as the nutrition (Ahtiainen et al., 2005; Schoenfeld et al, 2021) The schematic 22, of Ahtiainen (2018), shows the physiological complexity of the aforementioned factors. It is recommended that high load resistance exercise

(≥70% of 1RM) leads to greater musculoskeletal adaptations such as muscle strength and hypertrophy compared to lower resistance exercise loads (<70% of 1RM), potentially due to the better stimulation and interplay of these underlying mechanisms (ACSM, 1998) (ACSM, 1998). Interestingly, evidence has shown that even with lower loads (20-40% of 1RM) with BFR can induce similar musculoskeletal adaptations to high load RT (Gronfeldt et al., 2020) The underlying physiological mechanisms of BFR during RT are still under investigation, but potential mechanisms have been proposed in the literature (Hwang & Willoughby, 2019; Pearson & Hussain, 2015a; Rossi et al., 2018) The purpose of this section is to review the proposed underlying physiology of BFR during resistance exercise. Additionally, this section will also discuss the potential underlying physiological mechanisms of resistance exercise with and without BFR that are still under investigation, particularly concerning mood and

cognitive function, which have garnered significant research interest in recent years. 61 Figure 2.2 Physiological Mechanisms underlying Resistance Training: This schematic overview from Ahtiainen (2018) illustrates the physiological stimuli induced by resistance exercise, leading to adaptive responses. Depending on the program variables, resistance exercise creates a unique environment of mechanical and metabolic stimuli within the contracting muscle, along with both systemic and local release of signalling molecules. This results in the activation of signalling pathways and changes in the activity of cellular enzymes. These exercise-induced stimuli, combined with nutrient availability, promote protein synthesis and tissue regeneration post exercise. Over time, chronic resistance training results in a positive net protein synthesis, leading to muscle hypertrophy and muscle strength. 62 2.101 Physiological Mechanisms of Blood Flow Restriction during Resistance Exercise

Various mechanisms underpin the physiological effects of BFR-RT on muscle hypertrophy and muscle strength gains, including metabolic stress, mechanical tension, muscle cell swelling, anabolic signalling, inflammatory responses, and satellite cell and immunity activation (Hughes & Patterson, 2020; Pearson & Hussain, 2015a; Rossi et al., 2018; Watson et al, 2022) Among these, hypoxia- whether induced by BFR, exercise, or both plays a pivotal role in enhancing muscle adaptations (Watson et al., 2022) Furthermore, BFR has been hypothesized to exacerbate local hypoxia and acidity in the musculature further enhancing these physiological mechanisms crucial for muscle strength and hypertrophy (Hughes & Patterson, 2020; Pearson & Hussain, 2015a; Rossi et al., 2018) As shown in the schematic graph of Watson et al, (2022), local hypoxia due to BFR could lead to muscle cell swelling and increased metabolites such as lactate and hydrogen ions (H+) (Figure 2.3) These factors, in

turn, could initiate anabolic signalling and elevate anabolic hormones such as growth hormone (GH), insulin growth factor-1 (IGF-1), and testosterone. Muscle fibre excitability may increase due to heightened motor unit recruitment, metabolic stress, and the preferential activation of type II muscle fibres (Watson et al., 2022) Furthermore, stimulation and activation of myogenic stem cells under local hypoxia could be responsible for enhancing the regenerative response, including satellite cell activation, proliferation, and differentiation, crucial for muscle repair and growth. Figure 2.3 Proposed Physiological Mechanisms underlying BFR as described by Watson et al, (2022) 63 Additionally, as depicted in the schematic graph of Watson et al., (2022), local hypoxia and the acidic environment due to BFR-RT are proposed to induce afferent neural activity (Figure 2.4) This increased afferent activity enhances sensory feedback from muscles to the central nervous system, primarily

through the accumulation of metabolites such as lactate, H+, and inorganic phosphates. This heightened neural input may stimulate a neuroendocrine response, triggering the release of anabolic hormones such as GH, IGF-1 and testosterone, possibly further contributing to muscle strength development and muscle hypertrophy on a chronic basis (Watson et al., 2022) The interplay of these proposed physiological mechanisms in BFR-RT is complex and synergistic, with ongoing investigation into their interactions. Current research places primary emphasis on metabolic stress and mechanical tension as pivotal drivers of the adaptations observed with BFRRT. Figure 2.4 Hormonal Mechanisms underlying BFR training Hydrogen (H+), Growth Hormone (GH), Insulin Growth Factor 1 (IGF-1), Mechano Growth Factor (MGF) as described by Watson et al., (2022) Metabolic stress in BFR-RT triggers essential mechanisms for muscle adaptations (Freitas et al., 2017). During resistance exercise, heightened energy

demands deplete ATP reserves, resulting in the accumulation of metabolites such as lactate and H+ within muscle cells (Freitas et al., 2017) This metabolic milieu not only creates an acidic environment conducive to muscle fibre stimulation but also serves as a signalling molecule that triggers pathways upregulating the production of GH and IGF-1 (Brooks, 2018; Ferguson et al., 2018; Lee, 2021) It has been hypothesized that there is an additive effect with BFR, inducing local hypoxia, which could potentially stimulate greater increases in GH and IGF-1 (Rossi et al., 2018) This additive effect arises from the combination of the metabolic stress factors such as metabolite accumulation and the reduced oxygen supply due to the blood flow occlusion, enhancing the secretion of GH and IGF-1 in promoting muscle protein synthesis (Pearson & Hussain, 2015a; Rossi et al., 2018) Metabolic stress also activates cellular stress pathways, including the hypoxia-inducible factor 1-alpha (HIF-1a)

pathway (Rossi et al., 2018). HIF-1a enhances gene transcription related to angiogenesis, glucose metabolism, and erythropoiesis, supporting muscle cell adaptations under low-oxygen conditions (Pearson & Hussain, 2015). 64 Mechanical tension is another fundamental physiological mechanism implicated in BFR-RT, crucial for enhancing muscle hypertrophy and adaptive responses (Pearson & Hussain, 2015a; Rossi et al., 2018) As mentioned above, by applying external pressure to the limbs, BFR induces a unique vascular occlusion, which intensifies the mechanical tension experienced by muscle fibres during resistance exercises, thereby initiating mechanotransduction pathways (Pearson & Hussain, 2015; Rossi et al., 2018) Mechanotransduction involves cells converting mechanical stimuli into biochemical signals, triggering cascades that promote muscle growth and repair (Amani-Shalamzari et al., 2019; Hwang & Willoughby, 2019; Pearson & Hussain, 2015a; Rossi et al, 2018)

While the level of mechanical tension in BFR-RT may appear low compared to traditional resistance exercise, research suggests that even subtle tension can activate pathways essential for hypertrophy (Pearson & Hussain, 2015). These mechanisms include increased localised hormone production, muscle damage, reactive oxygen species (ROS) production, and enhanced recruitment of fast-twitch fibres, all of which stimulate protein synthesis, signalling pathway activation, and satellite cell proliferation for muscle growth (Pearson & Hussain, 2015). Moreover, mechanical tension in BFR-RT works synergistically with metabolic stress, enhancing the secretion and effectiveness of anabolic hormones such as GH and IGF-1 (Pearson & Hussain, 2015). This synergy contributes significantly to muscle adaptation and hypertrophy. While the primary focus of BFR-RT research has been on muscle adaptations, emerging evidence suggest that the physiological mechanisms activated by BFR-RT also have

significant implications for cognitive function (Törpel et al., 2018) As already mentioned in previous subsections, during BFR-RT, the restriction of blood flow to muscles induces localized hypoxia, triggering metabolic stress and the accumulation of metabolites (Törpel et al., 2018) This hypoxic environment stimulates the release of hormones such as GH, IGF-1, and VEGF, which have neuroprotective and neurotrophic effects (Pearson & Hussain, 2015). Elevated levels of neurochemical substances associated with BFR-RT are believed to play pivotal roles in synaptic functioning and neuroplasticity, thus influencing cognitive performance (Hwang et al., 2016; Nyberg & Hallberg, 2013; Torpel et al., 2018; Van Dam et al, 2000; Yamada et al, 2021) Moreover, BFR-RT, may induce both systemic and localized hypoxia, activating hypoxia-inducible factor 1α (HIF-1α), a regulator of oxygen homeostasis, potentially exerting neuroprotective effects and influencing neurotrophic factor

expression, thereby positively influencing neurocognitive adaptations (Correira & Moreira, 2010; Laurentino et al., 2018; Ratcliffe & Schofield, 2004; Semenza, 1998) (Figure 2.5) 65 Figure 2.5: Schematic illustration of (A) the basic principles of BFR, (B) the application places of the cuffs for BFR and (C) the possible neurobiological mechanisms of resistance training with blood flow restriction that are likely to contribute to improve cognitive functions; blood flow restriction (BFR), growth hormone (GH), hypoxia-inducible factor (HIF), insulin-like growth factor 1 (IGF-1), resistance training (RE), vascular endothelial growth factor (VEGF), as described by Torpel et al., (2018) 66 Some studies have been shown that BFR-RT leads to higher post exercise blood lactate concentrations compared to traditional resistance exercises, which has been linked to acute improvements in cognitive functions such as short-term memory and executive functions (Brooks, 2018; Takano et

al., 2005; Takarada et al, 2000; Törpel et al, 2018) Lactate, capable of crossing the blood-brain barrier, may serve as a fuel for cognitive processes and is associated with changes in BDNF, a key player in neuroplasticity (Coco et al., 2020; Ferris et al, 2007; Schiffer et al, 2011; Xue et al., 2022) However, research on the cognitive effects of BFR-RT compared to HL-RT remains limited. To the authors’ knowledge, only one study by Du et al (2021) explored the effects of BFR-RT versus HL-RT on BDNF and VEGF in stroke patients, reporting increases post BFR, along with higher exercise compliance and subjective physical strength compared to traditional HLRT. Further research is needed to investigate at a greater depth the potential cognitive benefits of BFR-RT and the associated BDNF responses. 2.102 Impact of Blood Flow Restriction during Resistance Exercise on Growth Factors: Research Findings Research employing BFR-RT consistently demonstrates notable enhancements in GH levels

across various demographics, including both young, trained and untrained men, older men, and postmenopausal women (Chen et al., 2022; Dong-il et al, 2016; Eonho et al, 2014; Laurentino et al., 2022; Manini et al, 2012; Patterson et al, 2013; Sharifi et al, 2020; Takano et al, 2005; Takarada et al., 2000; Tanimoto et al, 2005; Vilaca-Alves et al, 2022) Indicatively, Laurentino et al., (2022) investigated the effects of low load resistance exercise with BFR (20% of 1RM, 4 sets x 15 repetitions) with BFR (80% pressure to complete blood flow in a resting condition) versus high load resistance exercise (80% of 1RM, 4 sets x 8 repetitions) on GH in 29 active young males. They reported similar GH increases following both exercise conditions without significant differences between the two (BFR; 0.9 ± 06 to 84 ± 55, no BFR; 07 ± 07 to 122 ± 98 ng/ml) Similarly, Patterson et al., (2013), studied seven older healthy men (71 ± 65 years) performing 5 sets of unilateral knee extension until

failure at 20% 1RM with and without BFR (set at 110 mmHg) in a counterbalanced order. They found significant increases in GH only in the BFR condition with a rise of 229% from pre to 30 minutes post exercise. In contrast, the no BFR condition showed only a 3% increase from pre to 30 minutes post exercise. Chen et al., (2022) examined the acute effects following low load resistance exercise (30% of 1RM, 6 sets x 15 repetitions with 1’ rest) with and without BFR (70% of individualised BFR) versus high load resistance exercise (70% of 1RM, 6 sets x 15 repetitions with 1’ rest) in 18 postmenopausal women with mild to moderate unilateral knee osteoarthritis. They measured lactate and GH at four time points via cannula: before exercise, immediately after, 15- and 30-minute post exercise. Lactate was significantly higher in both BFR and high load resistance exercise from pre to immediately post 67 and 15-minute post exercise and compared to low load resistance exercise without BFR,

whereas GH was also significantly higher in BFR and high load resistance exercise from pre to 30-minutes post and compared to low load resistance exercise without BFR. Notably, a sole study, to the authors’ knowledge, by Reeves et al. (2006) reported significantly greater post-exercise GH increases in the BFR-RT condition compared to traditionally prescribed HL-RT. In this study, eight young healthy adults performed, in random order, 3 sets of single-arm biceps curls and single leg calf presses until failure with 1 minute interest rest period at low load resistance exercise (30% of 1RM) with and without BFR (arm occlusion time 341 ± 5 seconds, leg occlusion time 387 ± 13 seconds) and high load resistance exercise (70% of 1RM). Blood samples were taken pre-exercise, immediately after and 15 minutes post exercise for each experimental condition. GH significantly increased by fourfold from pre to immediately post exercise in the BFR condition but did not change significantly during

this time period in the high or low load resistance exercise without BFR. Studies investigating the effects of BFR during low load resistance exercise on IGF-1 are limited and yield inconsistent results (Abe et al., 2005; Bemben et al, 2022; Dong-il et al, 2016; Karabulut et al., 2013; Laurentino et al, 2022; Manini et al, 2012; Patterson et al, 2013) Specifically, investigations into the impact of BFR-RT on IGF-1 levels post-exercise have produced varying outcomes, contributing to the complexity of understanding its hormonal response. For instance, Dong-il et al. (2016) investigated the effects following a 12-week resistance training programme in middle aged women (52.7 ± 78 years) Forty-four participants were randomly assigned to five groups: control group (no exercise, CG), low load resistance exercise (40% of 1RM, LL-RE) group, high load resistance exercise (70% of 1RM, HL-RE) group, low load resistance exercise (20% of 1RM) with 5% reduction in cuff circumference for BFR

(BFR-RE-5%), and low intensity (20% of 1RM) with a 3% reduction in cuff circumference (BFR-RE-3%). Significant increases in IGF-1 concentrations were observed in the HL-RE (47% higher), the BFR-RE-5% (35% higher) and the BFR-RE-3% (27% higher) groups compared to the LL-RE group (3% higher) (Dong-il et al., 2016) Bemben et al. (2022) compared the acute and chronic response to a 6-week programme of low intensity (20% of 1RM) with BFR (initial pressure set at 40-60mmHg, incrementally increased up to 160mmHg), high intensity (70% of 1RM) and moderate intensity (45% of 1RM) without BFR in young men (18-35 years). High intensity produced significant increases in IGF-1, both at weeks 1 and 6, while moderate intensity exercise produced significant increases at week 6. The BFR condition showed significant IGF-1 increases only at the end of the training intervention (week 6) (Bemben et al., 2022) Notably, a study by Abe et al (2004) stands out, reporting significantly higher IGF-1 concentrations

post-training exclusively in the BFR condition compared to low-load resistance training without BFR. Abe et al, (2004) investigated the chronic effects of twice daily sessions of low intensity resistance training (20% of 1RM) with (set at 160mmHg, incrementally increased daily by 10mmHg, until reaching 240mmHg) and without BFR for two weeks (twice daily, six days per week for two weeks) using 3 sets of two dynamic lower body exercises on resting IGF-1 concentrations. Resting serum IGF-1 concentrations were measured via venous blood 68 sampling at baseline, week 1 and 2 post training. Significant increases in resting IGF-1 were observed only in the BFR condition compared to baseline measurements (week 1: 15%, week 2: 24%), whereas there were no significant changes in the no-BFR group (week 1: -7%, week 2: 2%). However, the majority of studies exploring the effects of BFR during resistance exercise on IGF-1 post-exercise have reported no significant alterations in hormonal response

from pre- to postexercise across all groups (Karabulut et al., 2013; Laurentino et al, 2022; Manini et al, 2012; Patterson et al., 2013) Testosterone is a primary anabolic hormone responsible for regulating muscle protein synthesis and skeletal muscle mass (Kraemer et al., 2020) While the direct effects of BFR-RT on testosterone levels are not fully elucidated, resistance exercise in general has been shown to acutely elevate testosterone levels (Kraemer et al., 2020) BFR-RT likely potentiates this response due to the heightened metabolic stress and hormonal milieu induced by BFR, as already mentioned above, thereby facilitating muscle hypertrophy and recovery (Kraemer et al., 2020; Pearson et al, 2015; Rossi et al., 2018) Studies examining the impact of BFR resistance exercise on testosterone levels have also yielded inconclusive findings, highlighting the complexity of hormonal responses to this training modality (Bemben et al., 2022; Karabulut et al, 2013; Laurentino et al, 2022;

Reeves et al., 2006; Sharifi et al, 2020; Vilaca-Alves et al, 2022) For instance, Bemben et al (2022) compared the acute and chronic testosterone responses following 6 weeks of BFR (20% of 1RM, set pressure at 40mmHg incrementally increased to 160mmHg), traditional high-load resistance exercise (70% of 1RM), and moderate-intensity resistance exercise (45% of 1RM) in young men. They found significant increases in testosterone levels at both weeks 1 and 6 in both HL-RT and BFR-RT groups (HL-RT: 13% at week 1 and 11.20% at week 6, BFR-RT; 856% at week 1 and 6.45% at week 6), with moderate-intensity exercise showing acute increases only at week 1 (919% at week 1 and 0.59% at week 6) In contrast, Sharifi et al (2020) investigated testosterone concentrations across four different training modalities did not observe significant increases compared to pre-tests and the control group. Forty healthy and untrained young males (18-25 years) were randomly divided into five groups: one session per

day of low load RT (20-30% of 1RM) with BFR (set at 110 and 180mmHg for upper and lower body pressure respectively), or two sessions per day of low load RT with BFR, or one session per day of high load resistance exercise (70-80% of 1RM), or two sessions per day of high load resistance exercise, or control group (no exercise). The mean changes in testosterone were determined by ELISA technique, before, after the first training session and the end of the last training session at the end of the 6-week intervention. They reported no significant increases in testosterone levels in each of the four training groups. Conversely, Laurentino et al. (2022) reported a non-significant decrease in testosterone levels from pre to 15 minutes in all three experimental conditions. Specifically, testosterone levels decreased by 6.29% from pre to 15 minutes post high load resistance exercise (80% of 1RM), in low-load resistance exercise (20% of 1RM) without BFR by 26.95%, and in low load resistance

exercise (20% of 1RM) with BFR (80% of AOP) by 24.48% Testosterone was significantly lower in high 69 load condition compared to low load without BFR, but no other significant differences were observed (Laurentino et al., 2022) Finally, several studies have reported unchanged testosterone concentrations from pre- to post-exercise across BFR-RT, HL-RT, and low-load resistance exercise without BFR (Karabulut et al., 2013; Reeves et al, 2006; Vilaca-Alves et al, 2022) 2.103 Findings Impact of Blood Flow Restriction during Resistance Exercise on Cortisol: Research Despite its association with stress and catabolism, cortisol has been suggested to play a role in muscle protein synthesis and repair (Kraemer & Ratamess, 2005). Released by the adrenal cortex in response to stress, cortisol is often viewed as catabolic due to its role in protein breakdown. However, it also facilitates the mobilization of amino acids for protein synthesis in tissues involved in inflammation and healing

(Pedersen & Febbraio, 2012). Cortisol has been proposed to regulate the inflammatory response induced by resistance exercise, preventing excessive tissue damage and aiding in recovery (Hackney & Walz, 2013). Moderate increases in cortisol during and after resistance exercise are suggested to contribute to muscle remodelling by breaking down damaged proteins and clearing cellular debris, thereby promoting muscle protein synthesis (Kraemer & Mazzetti, 2003). While chronic elevations in cortisol could be detrimental, short-term increases following exercise are part of the body’s adaptive response, essential for muscle repair and growth (Kraemer et al., 2020) However, studies examining the impact of BFR during low load resistance exercise on cortisol levels have produced conflicting findings (Bemben et al., 2022; Eonho et al, 2014; Laurentino et al., 2022; Patterson et al, 2013; Reeves et al, 2006; Vilaca-Alves et al, 2022) For instance, Eonho et al. (2014) and Laurentino et

al (2022) observed significant increases in cortisol levels post-exercise in both high-load resistance exercise and BFR, with no notable differences between the two exercise conditions (Eonho et al., 2014; Laurentino et al, 2022) Indicatively, Eonho et al., (2014) investigated the acute effects following high load resistance exercise (80% 1RM, 3 sets of 10 repetitions) and low load resistance exercise (20% of 1RM, 1 set of 30 repetitions and 2 sets of 15 repetitions) on cortisol levels. Fasting serum cortisol was measured in the morning before and immediately after exercise sessions. Cortisol levels significantly increased in both experimental conditions with no significant differences between the two exercise modalities (Change: BFR: 8.10 ± 230; no-BFR: 634 ± 172 ugdL-1) Conversely, the majority of studies have reported unchanged cortisol concentrations from pre- to post-exercise in both BFR and no BFR conditions, with no significant differences between the two exercise modalities

(Bemben et al., 2022; Patterson et al, 2013; Reeves et al, 2006; Vilaça-Alves et al, 2022) Indicatively, Vilaca-Alves et al., (2022) investigated the acute effects of multi-joint resistance exercises on cortisol levels following low load protocol (20% of 1RM, 4 sets x 30-15-15-15 repetitions with 30 seconds resting periods between sets) with intermittent pressure BFR (120% of SBP) and high load 70 protocol (75% of 1RM, 4 sets of 8-8-8-20 repetitions with 90 seconds resting periods between sets). Venous blood samples were collected before, immediately after and 15 minutes after each experimental condition. They reported no significant changes in cortisol concentrations immediately and 15 minutes post exercise in both BFR and no BFR conditions. In summary, BFR-RT engages several physiological mechanisms, primarily metabolic stress and mechanical tension via hypoxia-induced stimulation. These mechanisms synergistically stimulate hormone secretion crucial for muscle protein synthesis

and adaptations to resistance training with BFR (Kraemer et al., 2005; Rossi et al, 2018) Key among these responses is heightened GH secretion, that could potentially influence on IGF-1 levels, and the modulation of testosterone and cortisol, all contributing to enhanced muscle hypertrophy and strength. Despite these insights, the optimal application of BFR-RT still remains underexplored in both chronic and acute studies. Methodological heterogeneity across current research, including differences in demographics, exercise protocols, BFR pressures, and control groups, complicates outcome comparisons. Establishing standardized research methodologies is essential to derive robust conclusions regarding the efficacy of BFR-RT, particularly during low-load resistance exercise. 71 2.11 Conclusions In conclusion, there is strong evidence supporting the benefits of BFR-RT on muscle strength and hypertrophy, positioning it as a promising alternative to HL-RT, particularly for populations

who may not tolerate high loads. While some studies suggest that BFR-RT may be perceived as more tolerable than HL-RT due to the lower mechanical load involved, findings on discomfort and exertion remain mixed, and long-term adherence advantages have yet to be clearly established. Additionally, various physiological mechanisms have been proposed for BFR-RT, with local hypoxia-induced metabolic stress and mechanical tension driving hormonal adaptations. Emerging evidence also highlights potential benefits of resistance training on mood and cognition, with BDNF identified as a pivotal mediator. However, literature specifically examining the effects of BFR-RT on mood and cognition, including its impact on BDNF responses, remains scarce. Despite these promising findings, conflicting results in literature may stem from significant methodological heterogeneity across studies. Further research is essential, particularly on the roles of key hormones such as GH, IGF-1, testosterone, and

cortisol in muscle protein synthesis. Identifying the optimal BFR-RT modality that maximizes benefits for musculoskeletal health, mood, and cognition while improving tolerability and adherence should be a priority in future investigations. 72 3. General Methodology 73 This chapter outlines the overall methodological approach adopted throughout the research to address the primary objectives of the PhD. The main aim of this thesis was to evaluate the feasibility and effectiveness of a novel intermittent blood flow restriction (i-BFR) training modality that progressively increases pressure in combination with brief intervals of non-occlusion. The thesis also explored the underlying physiological mechanisms of i-BFR during low load resistance exercise (BFR-RE), in comparison to traditional high-load resistance exercise (HL-RE) and continuous BFR (c-BFR). To achieve these objectives, the research was systematically divided into two phases: Phase A (meta-analyses) and Phase B

(experimental studies) each with a distinct methodological focus. Phase A consisted of two meta-analyses, each conducted to address specific research questions that would help advance the BFR resistance training (BFR-RT) literature and directly inform the design of the experimental work in Phase B. The first meta-analysis (Chapter 4) examined the chronic effects of BFR-RT compared to high load resistance training (HL-RT) on muscle strength and muscle mass in healthy adults. To address key sources of heterogeneity observed in the literature, subgroup analyses were conducted based on training duration, targeted musculature, BFR application methods, and applied pressures related to arterial occlusion pressure (AOP). These analyses helped clarify under which conditions BFR-RT can produce positive adaptations comparable to HL-RT, supporting the use of continuous BFR (c-BFR) as a suitable comparator in subsequent experimental studies. Furthermore, the findings highlighted the importance of

standardising pressure application, reinforcing AOP as the most reliable and individualised method to guide pressure prescription in the experimental designs. The second meta-analysis (Chapter 5) focused on the acute metabolic and perceptual responses to low load BFR resistance exercise (BFR-RE) versus high load resistance exercise (HL-RE) in young healthy adults. Given the influence of age on metabolic responses, older, clinical, and athletic populations were excluded. Subgroup analysis was conducted to explore whether intermittent BFR (i-BFR) is more tolerable than HL-RE and c-BFR protocols. The findings from this analysis supported the investigation of a novel i-BFR protocol -originally developed by the KAATSU company but not yet evaluated in the peer reviewed literature – within Phase B. These findings provided a rationale for comparing i-BFR versus both HL-RE and c-BFR in terms of acute responses, feasibility, and individual tolerance. Phase B involved a mixed method

experimental study conducted in healthy, resistance-trained adults, designed to evaluate the acute effects of a novel i-BFR modality in comparison to the more traditionally prescribed c-BFR and HL-RE. A preliminary pilot study (Chapter 6) was first undertaken to assess the feasibility and tolerability of the new i-BFR protocol. This study provided initial data on perceptual responses, blood lactate, mood, and cognitive function, which informed key refinements in the subsequent experimental procedures. 74 The main study, reported in Chapters 7 and 8, adopted a randomized crossover design in which all outcome measures were collected from the same group of participants. Chapter 7 focused on acute perceptual and psychological responses, including ratings of perceived exertion (RPE), pain, delay muscle soreness, mood, and cognitive function. In addition, brain-derived neurotrophic factor (BDNF) was measured as a biomarker associated with mood and cognitive performance. A qualitative

component involving semi-structured interviews was also conducted to gain deeper insight into participants’ subjective experiences and preferences across the three modalities, thereby enhancing understanding of the intervention’s feasibility and acceptability. Chapter 8 examined acute metabolic responses relevant to muscle hypertrophy and strength development. These included growth hormone (GH), insulin-like growth factor-1 (IGF-1), cortisol, and blood lactate concentrations. Taken together, this mixed-methods approach allowed for a comprehensive evaluation of the iBFR modalitycharacterised by progressively increasing pressure with intermittent reliefacross physiological, psychological, and experiential domains. The inclusion of acute hormonal and metabolic markers such as GH, IGF-1, and lactate was intended to provide mechanistic insights into the potential for muscle hypertrophy and strength gains typically observed over longer-term training. As acute responses to resistance

exerciseparticularly elevations in GH and lactatehave been associated with the stimulation of anabolic pathways and subsequent training adaptations, these findings offer a basis for predicting the long-term efficacy of i-BFR. Additionally, the inclusion of perceptual and qualitative data helps assess tolerability and feasibility, which are critical for adherence and successful implementation in practice. 75 3.1 Phase A: Methodology for Systematic Reviews & Meta-Analyses Both meta-analyses presented in Chapters 4 and 5 were designed to adhere to the PRISMA guidelines, and their protocol have been published online at the International Prospective Register of Systematic Reviews, PROSPERO with the code CRD42021246633 (Moher et al., 2009) Initially, the design aimed to investigate the acute and chronic effects of BFR during low load resistance exercise versus the traditionally prescribed high load resistance exercise. However, given the substantial number of identified studies,

particularly for the chronic adaptations and the multitude of outcome measures under investigation, the meta-analysis registered with the above code was bifurcated into two distinct analyses, each with a specific research focus: one concentrating on the chronic a priori outcome measures (chronic muscle adaptations: muscle strength, muscle mass), and the second one concentrating on the acute a priori outcome measures (acute responses; hormonal and lactate responses and ratings of perceived exertion). 3.11 Risk of Bias Assessment The risk of bias was assessed for all the studies included in this article, as proposed in the PRISMA 2020 statement (Page et al., 2021, Sterne et al, 2019) To evaluate the methodological quality of the included randomised controlled trials (RCTs), the updated version of the Risk of Bias 2 (RoB 2) tool developed by Sterne et al. (2019) was employed This tool assesses five specific domains of potential bias: bias arising from the randomisation process,

deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. Each domain was rated as ‘low risk’, ‘some concerns’, or ‘high risk’, and an overall risk of bias judgement was derived for each study based on these domain-level ratings. No studies were excluded from the analysis based on risk of bias assessment. The primary, and a second reviewer independently undertook the risk of bias assessment prior to a meeting to resolve any discrepancies by consensus, with input from a third reviewer when required. In the first meta-analysis, the primary reviewer was Maria Kotopoulea-Nikolaidi, who led the process under the guidance of Dr. Fergus Guppy (second reviewer) and Dr. Ifigeneia Giannopoulou (third reviewer) Dr Guppy has extensive experience in conducting meta-analyses, having published multiple meta-analytical studies. Dr Giannopoulou, despite her expertise in research and supervision, was relatively new to the

specific methodologies involved in meta-analyses at the time. Maria Kotopoulea-Nikolaidi, as a PhD candidate, undertook the assessment process as part of her broader methodological training, gaining experience under the supervision of more experienced researchers. In the second meta-analysis, Maria KotopouleaNikolaidi again served as the primary reviewer, with Dr Ifigeneia Giannopoulou acting as the second reviewer and Dr. Borja Muniz-Pardos as the third reviewer Dr Muniz-Pardos brings significant expertise in conducting meta-analyses, with several published works in this area. The 76 complementary combination of different levels of experience among the reviewers ensured a thorough and balanced assessment process. 3.12 Statistical Analyses All analyses were performed using the Open Meta [Analyst] software (Windows 10, Rhode Island, RI, USA) (Wallace et al., 2012) The Hedge’s g for each group was calculated as the change score difference (pre to post values) in the BFR groups

minus the change score difference (pre to post values) for the control group (HL), divided by the pooled standard deviation. When studies reported multiple post-intervention time points, the g calculation was made based on baseline and the final time point closest to the end of the intervention. This approach was applied consistently across both meta-analyses: in the chronic studies included in Meta-analysis 1, the final point reflected the end of the training intervention; in the acute studies of Meta-analysis 2, it corresponded to the latest post-exercise time point reported. A continuous random-effects model employing the DerSimonian– Laird method was used to determine the effect size for all outcome measures, and all variables were calculated using the standardised mean difference (SMD) with 95% CI (DerSimonian and Laird, 1986). The selection of the continuous random-effects model was predicated upon its ability to account for variability between studies while simultaneously

estimating the overall effect size (Borenstein, 2009). This model was deemed appropriate due to the inherent heterogeneity expected among the included studies, stemming from variations in methodological approaches. The SMD effect sizes were interpreted as a small effect (0.2–04), moderate effect (05–07) and large effect (>0.8) and significance was set at p≤005 (Cohen, 1988) The heterogeneity of the studies was tested using the I2 statistic, where it is interpreted as follows: I2 = 0–25% no heterogeneity, I2 = 25–50% moderate heterogeneity, I2 = 50–75% high heterogeneity, and I2 = 75–100% very high heterogeneity (Higgins et al., 2011) 77 3.2 Phase B: Methodology for Experimental Studies The experimental phase consisted of three studies: a Pilot study (Chapter 6), Acute Study 1 (Chapter 7), and Acute Study 2 (Chapter 8). While each study had specific objectives, the methods and testing protocols were consistent across all studies where applicable. The following

summary highlights the shared protocols and measurements: • BFR Pressure Application Protocol: The BFR pressure application protocols were identical across all three studies, ensuring consistency in both the intermittent and continuous BFR conditions. • BFR Pressures: The pressures applied during both intermittent and continuous BFR conditions were standardized and consistent across all three studies. • Cognitive Function Tests & POMS Questionnaire: The same cognitive tests and Profile of Mood States (POMS) questionnaire were employed in Pilot Study and Acute Study 1 to assess cognitive function and mood states, although Mixed Stroop Task was used only in the acute study 1. • Venous Blood Sampling Protocol: The protocol for venous blood sampling and analysis was consistent in Acute Studies 1 and 2, although this method was not used in the Pilot Study. • Lactate Measurement: Lactate levels were consistently measured using the same methodology across all three studies.

• Body Composition Assessment: Body composition was assessed using Dual x-ray Absorptiometry (DXA) in Acute Studies 1 and 2. Bioelectrical Impedance Analysis (BIA) was used in the Pilot Study due to its more preliminary focus. While these acute studies did not investigate changes in body composition as an outcome, these assessments were conducted to comprehensively describe the participant characteristics and ensure sample homogeneity with respect to muscle mass and body fat. The use of BIA in the Pilot Study reflected its preliminary nature and practical considerations, whereas DXA was employed in the subsequent acute studies to provide more precise baseline characterization. 3.21 Location, Ethics, Health & Safety Location: The experimental studies were conducted primarily at Welkin Sport and Exercise Science Laboratories (Pilot Study, Acute studies 1 & 2) on the Eastbourne Campus of the University of Brighton, where all testing and measurements took place (including

cognitive function tests, POMS questionnaire, lactate and venous blood sampling, BFR pressure application, and exercise protocols). The DXA scans for body composition assessment, however, were conducted in the Mithras building on Moulsecoomb Campus (Acute Studies 1 & 2) of the University of Brighton. Participants’ Criteria: In all three experimental studies (Chapters 6 - 8) stringent inclusion and exclusion criteria were implemented to ensure the safety and integrity of both participants and 78 research outcomes. Participants eligible for inclusion were required to be over 18 years old, in good health, and have prior experience in resistance training. However, individuals with a body mass index (BMI) outside the range of 20 to 29.9 kg/m2, elevated resting blood pressure, diabetes, heartrelated conditions necessitating medication such as blood thinners, recent acute illnesses, orthopaedic or neurological limitations, or a medical history of deep vein thrombosis were excluded.

Notably, participants who had contracted COVID-19 within the past three months, received a COVID-19 vaccine within the last six weeks, or planned to do so during the study period, were also excluded. This decision was made in consultation with the ethics committee of the University of Brighton due to reported incidents of thrombosis associated with the COVID-19 vaccine during the pandemic. Given the potential additive pressure of BFR during resistance exercise on thrombotic events, it was crucial to mitigate any potential risk or complications from the interaction between the vaccine and the exercise protocol. Therefore, these exclusions were implemented to uphold participant safety and ensure the reliability of the study findings. Participants were provided with a participant information sheet and had at least 48 hours to reflect on the information before they consented to participate in the studies (Pilot Study; Appendix 1, Acute Studies; Appendix 2). They had the opportunity to ask

any questions before, during, and after their participation in the studies. During their initial visit, participants filled out a medical questionnaire to rule out any medical conditions that could affect their health (Appendix 3). If the participants met the inclusion criteria, an informed consent form was provided for them to sign (Pilot Study; Appendix 4, Acute Studies; Appendix 5). In subsequent visits, a short medical questionnaire (Appendix 6) was also provided to ensure they were still in good health, had abstained from exercise for a minimum of 24 hours and eaten a light meal 2.5 hours before sessions (Dankel et al.,2019), abstained from alcohol for minimum of 48 hours (de Araujo et al, 2017) and caffeine for a minimum of 6 hours (Bell et al., 2018), and kept their usual hours of sleep and daily activities (Aniceto et al., 2021) Additionally, participants in acute studies 1 and 2 during their second visit for DXA scan, completed another questionnaire to determine eligibility

before proceeding with the scan (Appendix 7). These measures were implemented to ensure both participants’ safety and adherence to study protocols and to minimize potential confounding factors on study outcomes. Blood Flow Restriction Safety Considerations: The literature on BFR during exercise underscores its safety when applied appropriately (Anderson et al., 2022, Patterson et al, 2019, Brandner et al, 2018). Evidence suggests that BFR does not induce a muscle damage response in resistance exercise protocols, particularly with single exercise sessions up to 5 sets to volitional failure (Patterson et al., 2019) Overall, the literature indicates that with proper application and supervision, BFR is a safe and effective modality for exercise rehabilitation and training (Anderson, et al., 2022) Nevertheless, precautions taken in this project on BFR safety during exercise, are provided. In this project all the experimental exercise protocols did not exceed a single exercise or four

sets. Additionally, adherence to guidelines and warnings provided by the manufacturer of the BFR 79 equipment used, KAATSU Global Inc., was paramount (Appendix 8) Further safety measures included administering a detailed medical questionnaire (see Appendix 3) to participants to identify any issues such as a history of blood clots, heart problems, or chronic respiratory conditions. During testing sessions, participants' capillary refill time throughout their KAATSU exercise was monitored, ensuring it remained under three seconds, indicative of good blood flow. Additionally, the main experimenter completed specialised training in KAATSU techniques to guide participants through their BFR training sessions safely (Appendix 9). These measures were implemented to safeguard the well-being of participants while exploring the benefits of BFR during resistance exercise. Risk Assessments: A comprehensive risk assessment was conducted to ensure the health and safety of both experimenters

and participants during the experimental sessions (Appendix 10). This assessment encompassed several key procedures, including blood sampling, BFR during exercise, COVID-19 measures, lone working in the labs, Profile of Mood States (POMS) questionnaire, and exercise testing. Initially, it was planned to take venous blood samples at five timepoints during each experimental visit via cannula. However, following a revision in study design, blood samples were collected only before and after exercise using classic phlebotomy processes through a needle (Eonho et al., 2014) Strict measures were implemented for COVID-19, including the mandatory wearing of face masks, gloves, and lab coats by experimenters, as well as regular cleaning and sterilization of equipment as per university regulations. As per updated university regulations, face mask and lab coat requirements were adjusted; however, the main experimenter continued to wear gloves consistently during testing procedures. Aseptic touch

techniques were employed during blood sampling to minimize infection risk, and participants were briefed on the procedure to alleviate anxiety, with measures taken to accommodate those with needle phobia. Additionally, participants with needle phobia were seated in a reclined position to prevent fainting. Training in sharps handling was provided to phlebotomists and their assistants, and a sharp disposal box was readily available. Exercise sessions were closely monitored for participant discomfort, with warm-up and cool-down periods included to mitigate injury risk. Ratings of perceived exertion, pain, and discomfort were assessed regularly during exercise. Additionally, the main experimenter verbally ‘checked in’ with participants at regular intervals to ensure their well-being and assess how they were feeling. Screening using the POMS questionnaire was also conducted before participants engaged in the main experimental conditions to identify any individuals experiencing stress,

anxiety, or other negative emotions. Participants reporting prior mental health conditions were excluded from participation based on the results of this screening process. 80 3.22 Exercise Standardisation Pre-study and exercise standardizations were implemented to control for potential confounding variables and ensure consistency across participants. Dietary control measures were employed to minimize the influence of macronutrient percentages on study outcomes (Bemben et al., 2022; Chryssanthopoulos et al., 2004; Williams et al, 2002) Participants were provided with a 3-day dietary diary during their initial visit and instructed to replicate the exact same meals, quantities, and timings for three days preceding each of their final three visits (see Appendix 11) (Burke, 2007; Kang, 2018; Maughan & Shirreffs, 2013). Additionally, the last three visits were separated by at least five days each and scheduled in the morning between 8:00am and 10:00 am (±1 h) to minimize

variation due to the circadian rhythm (Eonho et al., 2014; Freitas et al, 2020) Participants were instructed to consume a very light breakfast, identical for each of the last three visits, 2.5 hours before their scheduled arrival at the laboratory (Dankel et al.,2019) Participants were also instructed to abstain from heavy exercise during their participation and were strictly prohibited from engaging in exercise at least 24 hours before each of the last three visits (Dankel et al., 2019) Furthermore, participants were instructed to refrain from alcohol consumption 48 hours before testing (de Araujo et al., 2017) and to avoid caffeine or other beverages for 6 hours prior to their arrival for testing during the last three visits (Bell et al., 2018) These precautions aimed to prevent alterations in exercise-sensitive biomarkers such as GH, IGF-1, cortisol, and BDNF, and exercise performance, thus maintaining experimental control (Cano et al., 2008) General instructions were provided to

participants during their initial visit (see Appendix 12) to facilitate adherence to study protocols, with encouragement for participants to seek clarification from the main experimenter if needed throughout their participation. These standardized procedures were critical for minimizing potential confounds and optimizing the reliability and validity of study findings. 3.23 Baseline Measurements Anthropometric Data: Participants were instructed to remove their shoes and wear minimal clothing before stepping onto the scales with a stadiometer attached (SECA 704, Birmingham, UK). They were asked to stand in the Frankfurt plane anatomical position, vertically upright. Subsequently, the stadiometer was adjusted to a horizontal position, aligning with the participants' heads as they faced forward. Measurements were recorded to the nearest 05 cm, and weight was displayed on the screen of the electronic scales in kilograms to the nearest 0.1 kg Dual x-ray Absorptiometry (DXA):

Participants in acute studies 1 and 2 (Chapter 7 and Chapter 8) underwent a gold standard dual x-ray absorptiometry scan (DXA scan) using the Horizon-Bone Densitometry System (Horizon W, Hologic, Massachusetts, USA) to assess body composition, including lean mass and fat mass distribution (Shepherd et al., 2017) The DXA scan was conducted according to the manufacturer's guidelines by trained personnel and daily calibration ensured optimal performance, adhering meticulously to manufacturer’s instructions. Upon arrival, 81 participants underwent an eligibility assessment, including a review of criteria outlined in Appendix 7. Notably, a contraindication for proceeding with the DXA scan was a cumulative radiation dose exceeding 1mSv in the last 12 months. Prior to the scan, participants were instructed to remove any metal objects and to wear light clothing without any metal components to minimize interference with the scan results. Participants were provided with a gown for the

examination when necessary Anthropometric measurements of height and weight were recorded before participants assumed a supine position on the DXA table. Each participant was positioned on the DXA table in accordance with standardized protocols, ensuring proper alignment and stability throughout the procedure. Participants were instructed to maintain stillness and relaxation during the approximately 5-minute whole-body scan (Figure 3.1) The experimenter input participant data, including height, weight, age, gender, and ethnicity, into the software before commencing the scan. The scan captured detailed images of the body, utilizing low-dose X-ray technology to differentiate between bone, lean tissue, and fat mass. Following the DXA scan, participants received feedback on their body composition results, and any questions or concerns were addressed by the research team. All DXA scan data were securely stored and analysed in accordance with established protocols to ensure participant

confidentiality and data integrity. Figure 3.1: Whole Body DXA scan position Individualised BFR pressure application protocol: For the individualized BFR pressure application protocol, a methodology widely established in the literature was adopted (Freitas et al., 2019, Loenneke et al., 2012) Initially, participants assumed a supine position for a minimum of 10 minutes. Subsequently, three measurements of brachial blood pressure were obtained using an electronic blood pressure monitor (Boso Medicus, Bosch + Sohn, Jungingen, Germany), with the average of these measurements calculated to ensure consistency within a 5-mmHg range. Thigh 82 circumference was assessed using an anthropometric tape to select appropriately sized KAATSU elastic bands (5 cm width). Participants were then instructed to position these bands at the most proximal portion of each leg, ensuring a snug fit that permitted the passage of an index finger between the band and the thigh without impeding circulation.

Arterial blood flow was detected at the ankle using a handheld doppler probe placed on the posterior tibial artery by the main experimenter. The validity of the handheld doppler used for arterial flow detection was assessed by comparing its measurements with those obtained using doppler ultrasound (US), which is considered the gold standard for determining arterial occlusion pressure in healthy individuals (Laurentino et al., 2020) The study found no significant differences in arterial occlusion pressure levels between the handheld doppler and doppler ultrasound (133 [±18] vs. 135 [±17] mmHg, p = 0168) Additionally, there was a significant correlation (r = 0938, p = 0.168), reasonable agreement, and a total error of the estimate of 60 mmHg between the two measurement methods (Figure 3.2) This validation process ensured accuracy of the handheld doppler for arterial flow detection in our study. Figure 3.2: Bland-Altman plot between handheld doppler and ultrasound The middle solid line

represents mean of the 2 methods and 2 dotted lines at the top and bottom represent 1.96 SDs from the mean Dotted lines represent 5mmHg above and below the mean (Laurentino et al., 2020) The KAATSU C3 device was employed to automatically adjust band pressure, with actual pressures confirmed on the device's digital display. Bands were initially inflated to approximately 50 mmHg for 30 seconds, followed by deflation for 10 seconds. Subsequently, bands were inflated to the participant's brachial systolic blood pressure for 30 seconds, followed by deflation for 10 seconds. Pressure was incrementally increased by 40 mmHg until arterial flow was no longer detected during inflation. Once arterial flow cessation was observed, pressure was reduced in 10 mmHg increments until arterial flow resumed, with the lowest recorded band pressure at which arterial flow ceased documented as the arterial occlusion pressure. This value represented the 100% 83 individualized BFR pressure, from

which the 50% pressure was calculated to apply in the BFR conditions. In instances where occlusion pressure exceeded the upper limit of the KAATSU C3 device (400 mmHg), the Zimmer ATS 3000 Tourniquet System (Zimmer Biomet, Indiana, USA) was utilized, with a maximum pressure capacity of 500 mmHg. For participants exceeding this threshold, realtime monitoring of muscle oxygen concentrations using a Near-Infrared Spectroscopy (NIRS) device (MOXY Muscle Oxygen Monitor, Hutchinson, MO, USA) during exercise was implemented. This device calculates the percentage of saturated haemoglobin in relation to total haemoglobin in the muscle, providing insights into tissue oxygenation levels (Bartolomei et al., 2022, Guardado et al., 2021) Placement of the MOXY device on the vastus lateralis muscle enabled continuous monitoring throughout each set of leg press exercises. The data collected was analysed using software provided by the device manufacturer. Previous studies have assessed the reliability

of MOXY device and demonstrated good to excellent test-retest reliability for muscle oxygen saturation (SmO2) across different intensities (Yogev et al., 2023, Crum et al, 2017) (Table 31) Participants performed up to 4 sets of leg press until failure at 30% of 1 repetition maximum (1RM), with pressure initially set at 400 mmHg. Subsequent adjustments were made based on mean SmO2 measured by the NIRS device. Pressure was decreased in 50 mmHg increments until SmO2 fell within the desired range of 18-28%. It is worth noting that the target range of 18-28% SmO2 was determined based on a previous study utilizing similar pressure level and resistance exercise load (Bartolomei et al., 2022) Table 3.1: Reliability outcomes of SmO2 measurements using MOXY Device from previous studies ICC CV (%) MDC SROC Yogev et al. (2023) 0.90-081 11-43.8% 12-18% - Crum et al. (2017) 0.773-0992 - - 0.834-0980 Intraclass correlation coefficient (ICC), Coefficient of variation (CV) units are in

percentage, minimal detectable change (MDC), Spearman’s Rank-Order correlation (SROC) 1 Repetition Maximum (1-RM): Participants underwent a standardized warm-up protocol prior to testing, consisting of 5 minutes of cycling on a stationary cycle ergometer at a self-paced intensity (Monark Exercise AB, VANSBRO, Sweden). Subsequently, participants were carefully positioned in the leg press machine with their knees and feet placed hip-width apart to ensure proper alignment. Their knees were flexed at a 90-degree angle, maintaining a neutral spine with firm contact against the backrest. Participants stabilized themselves by holding handles adjacent to the hips with their hands. Following a one-minute rest period, participants were acquainted with the leg press machine (Signature Series Linear Leg Press, Life Fitness, Cambridgeshire, UK) (Figure 3.3) by performing 84 8-10 repetitions with a light load (~50% of predicted 1RM), as per the protocol outlined by Seo et al. (2012) Initial

loads were estimated based on researcher experience and participant feedback regarding training history, with subsequent adjustments informed by established estimations from past research (Reynolds et al., 2006, Seo et al, 2012) Following another one-minute rest period, participants performed repetitions with a load set at approximately 80% of the estimated 1-RM through the full range of motion. Load increments were applied after successful performance until participants reached their maximal effort or experienced a failed attempt. One-minute rest intervals were provided between each attempt, and the 1-RM was determined within a maximum of five attempts, with five minutes of rest separating each test. This 1-RM protocol demonstrated high reliability and precision, supported by significant intraclass correlation coefficients (ICC > 0.91, p < 0.027) as reported by Seo et al (2012) Figure 3.3: Leg press machine 3.24 Reliability of Testing the KAATSU C3 Device To assess the

reliability of the KAATSU C3 device in maintaining consistent pressure settings over extended periods, a test-retest study was undertaken at rest and during exercise. Specifically, ten healthy young participants, comprising both males and females aged 18 to 35 years old and with a BMI range of 19 to 29.9 kg/m2, volunteered for the study (Table 32) 85 Table 3.2: Participant characteristics Variable Total (n=10) Age (yrs) 23.70 ± 490 Height (m) 1.72 ± 009 Weight (kg) 65.03 ± 1118 BMI (kg/m2) 21.90 ± 220 The primary objective was to ascertain the device's capability to sustain specified pressure consistently during periods of rest. Upon arrival at the laboratory, participants assumed a supine position for 20 minutes. Brachial blood pressure was measured three times using an electronic blood pressure device, and the mean values were used to determine the individualised BFR pressure for the legs (Freitas et al., 2019) Following this, KAATSU bands were applied

bilaterally to the thighs, inflated to 50% of the individualized BFR pressure, and participants remained supine for an additional 30 minutes. Throughout this interval, the pressure displayed on the KAATSU C3 screen was monitored every 5 minutes to ensure alignment with the preset pressure. Participants returned for a second visit, where the identical protocol was replicated, enabling a thorough evaluation of the device's capacity to maintain consistent pressure levels over time. The two visits were separated by 3-7 days and were conducted at the same time of day to account for potential variations in blood pressure due to time of day (Parati, 2007). Following data collection, intraclass correlation coefficient (ICC), typical error (TE), coefficient of variation for the typical error (TE [CV%]), and Pearson correlation coefficient was conducted to examine the relationship between the recorded pressure values displayed on the KAATSU C3 screen and the preset pressure settings. The

results indicated a strong positive correlation, suggesting that the device effectively maintained consistent pressure levels as programmed across both test and retest sessions (Table 3.3) 86 To further assess the KAATSU C3 device’s ability to maintain preset pressure levels during exercise, a test-retest study was conducted with the same participants. During the initial visit, participants performed a one-repetition maximum (1-RM) leg press exercise between 8-10 am (±1 h) to minimize variation due to the circadian rhythm (Eonho et al., 2014; Freitas et al, 2020) Following a rest period of at least 5 hours, participants returned to the lab to complete four sets of leg press exercise until failure. Participants returned for a final visit 48-72 hours later to repeat the exercise protocol and data collection process. By incorporating NIRS technology, this modified approach allowed for a comprehensive assessment of the KAATSU C3 device's performance in maintaining preset

pressure levels during exercise. The findings from the test-retest study revealed that the KAATSU C3 device effectively maintained the preset pressures during exercise, as evidenced by consistent oxygen levels within the muscle observed across repeated measurements. Specifically, the oxygen levels within the vastus lateralis during the test and retest sessions exhibited notable similarity, indicating the device’s capacity to sustain consistent pressure settings throughout the exercise protocol. The observed consistency in muscle oxygen levels during the test-retest sessions aligns with findings from previous studies employing similar individualized BFR pressures and employing comparable resistance exercise protocols (Bartolomei et al., 2022) Detailed results of the ICC, TE, (TE [CV%]), and Pearson correlation analyses are provided in Table 3.4 for further reference and analysis. 87 3.25 Psychometric Assessments Profile of Mood States Questionnaire (POMS): The POMS

questionnaire is a widely recognized psychometric assessment for evaluating psychological distress, encompassing various mood states such as tension, anger, fatigue, depression, vigour, and confusion in diverse populations (Curran et al., 1995; de Andres-Teran et al, 2019; Grulke et al, 2006; Kienast et al, 2022; Konuma et al, 2015; Kuesten et al., 2017; Martin et al, 2000; Martínez-Soto et al, 2022; Petrowski et al, 2021; Shacham, 1983). In this study, mood states were assessed using a 40-item mood adjective checklist, derived from the POMS, and categorized into six subscales (tension, anger, fatigue, depression, esteem-related affect, vigour, and confusion) (Grove and Prapavessis, 1992). Participants were instructed to rate their current feelings on a scale ranging from "Not at all = 0" to "Extremely = 4" based on a list of descriptive words associated with different mood states (Appendix 13). For clarity and ease of interpretation, an appendix (Appendix 14) is

included to provide an explanation of the scoring method for the POMS questionnaire. This appendix offers detailed instructions on how to score the questionnaire, including the calculation of subscale scores and total mood disturbance scores. Additionally, it provides guidance on interpreting the scores and understanding their implications for mood states. This resource enhances transparency and facilitates replication of the study's methodology by providing readers with comprehensive information on the scoring process for the POMS questionnaire. While the original 65-item POMS scale is comprehensive, its length may present challenges in certain populations or research designs. Consequently, shorter versions of the POMS have been developed and evaluated for validity and reliability. Curran et al, (1995) introduced a 37-item Short Form of the POMS, which demonstrated comparable internal consistency to the original POMS across all subscales, with correlations exceeding 0.95 between

total mood disturbance and subscale scores (Curran et al., 1995) Furthermore, Petrowski et al, (2021) assessed the validity and reliability of an even shorter version of the POMS questionnaire comprising 16 items. Their findings revealed excellent reliability across all POMS subscales, with coefficients ranging from 0.86 to 091 (Petrowski et al., 2021) The development and validation of shorter versions of the POMS questionnaire offer researchers practical, time-efficient alternatives for assessing mood states while maintaining high levels of reliability. These abbreviated versions address the challenges posed by the original 65-item scale, making the assessment of psychological distress more accessible and feasible in various research designs (Curran et al., 1995; Grove and Prapavessis, 1992; Petrowski et al., 2021) The POMS questionnaire’s score is often used as an indicator of overall psychological distress, calculated by summing the scores of the negative mood subscales such as

depression and anger and subtracting the score of positive subscales such as vigour (Curran et al., 1995; Shacham, 1983). Higher TMD scores indicate greater mood disturbance (Curran et al, 1995) Although 88 thresholds can vary, scores above 100 are frequently considered indicative of significant mood disturbance in various clinical and research settings (Curran et al., 1995; Grove & Prapavessis, 1992). For depression, elevated scores on the depression-dejection subscale often warrant further assessment (Petrowski et al., 2021) While specific cut-offs are context-dependent, scores above 10 are commonly associated with heightened depressive symptoms in some versions of the POMS scale (Grove & Prapavessis, 1992; Holden et al., 2019; Lane et al, 2001) Cognitive function Assessments (Stroop test & Mixed Stroop task): The Stroop Test and the Mixed Stroop Test are valid (r=0.84) (Siegrist, 1997), widely used cognitive tasks designed to measure cognitive processing speed,

selective attention, and executive functioning (MacLeod, 1991; Stroop, 1935). In the traditional Stroop Test, participants are presented with a four colour words (red, blue, green, yellow) printed in incongruent ink colours (e.g, the word "red" printed in blue ink) and asked to name the ink colour while ignoring the word meaning (Figure 3.4) The interference between the word meaning and ink colour creates a conflict, requiring participants to inhibit the automatic response of reading the word and instead focus on identifying the ink colour, thus assessing their ability to selectively attend to relevant information while suppressing irrelevant information (MacLeod, 1991; Stroop, 1935). Figure 3.4: Typical examples of the colour-word Stroop test Building upon the traditional Stroop paradigm, the Mixed Stroop Test incorporates additional cognitive demands by interspersing congruent trials (where the word meaning and ink colour match) among incongruent trials. This task

variation introduces greater cognitive flexibility requirements, as participants must rapidly switch between reading the word and identifying the ink colour depending on the trial type (Wright, 2017). The Mixed Stroop Test provides a more ecologically valid measure of cognitive control and executive functioning by simulating the dynamic cognitive demands of real-world situations where conflicting information must be processed and managed efficiently (Wright, 2017). In this study, both the traditional Stroop Test and the Mixed Stroop Test were employed to assess participants' cognitive functioning in response to cognitive challenge following three different resistance exercise regimens. Both cognitive function tests were performed using PsychoPy3, a computerised software (Peirce et al., 2019) To minimise the familiarisation error, participants in their initial visit familiarised themselves with both cognitive function tests and they answered at least three sets of 40 responses for

both Stroop test and Mixed Stroop task (Yamada et al., 2021) 89 Additionally, in order to further minimise the familiarisation error for each experimental visit, participants performed one set of 20 and 40 responses for the Stroop test and the Mixed Stroop task respectively before the pretest. During the pretest, post-test, and 60 minutes post-test, participants completed a set of 50 responses for Stroop test and 80 responses for the Mixed Stroop task (Li et al., 2019; Stroop, 1935; Yamada et al, 2021) Once the word appeared on the screen, participants were instructed to respond as quickly as possible regardless of the test or the condition. Participants responded by pressing the arrow keys on the keyboard that corresponded to the colour of their answer. They were instructed to memorise which key represented each colour, as the keys themselves were not colour coded. Prior to the task, participants were given clear instructions and time to familiarise themselves with the key-colour

associations (e.g the left arrow corresponds to red, the up arrow corresponds to blue, etc) Participants were instructed to respond as quickly and accurately as possible to each trial, and their performance on both tasks was recorded and analysed. The Stroop Test and the Mixed Stroop Test provide valuable insights into individuals' cognitive abilities and are commonly utilized in research settings across various fields, including psychology, neuroscience, and clinical assessments (Bush et al., 2000; Carter et al, 1998; MacLeod, 1991; Miyake et al., 2000) The outcome measures for the Stroop test included: 1) Reaction time [in milliseconds (ms)] of correct answers: This metric indicates the time taken by participants to correctly respond to Stroop stimuli. 2) Number of the correct answers: This metric represents the total count of correct responses given by participants during the Stroop test. Specifically, the mean of the correct answers for the Stroop test was calculated by

assigning a value of 1 to each correct response and a value of 0 to each incorrect response in the collected data. Subsequently, the mean and standard deviation of these values were computed to characterize participants’ performance in terms of correct answers. A higher mean value, closer to 1, indicated that participants responded more accurately during the Stoop test. 3) Percentage of correct answers: This metric reflects the accuracy of participants’ responses, ����� ������ �� ������� ������� calculated using the formula: 0⁄0 ������� ������� = ( ����� ������ �� ��������� ) × 100 (Gómez et al., 2015) The outcome measures for the Mixed Stroop task included four main metrics: 1) Overall Reaction Time (in ms) of correct answers for both congruent and incongruent stimuli: This metric indicated the time taken by participants to respond to both congruent

and incongruent stimuli correctly. 90 2) Reaction Time of correct incongruent responses (in ms): This metric specifically measures the time taken by participants to respond to incongruent stimuli correctly. 3) Reaction Time of the correct congruent responses (in ms): This metric specifically measures the time taken by participants to respond to congruent stimuli correctly. 4) Overall number of the correct answers: This metric represents the total count of correct responses given by participants during the Mixed Stroop task for both congruent and incongruent responses. Similar to Stroop test, the mean of the correct answers was calculated by assigning a value of 1 to each correct response and a value of 0 to each incorrect response in the collected data. Subsequently, the mean and standard deviation of these values were computed to characterize participants’ performance in terms of correct answers. A higher mean value, closer to 1, indicated that participants responded more

accurately during the Stoop test. 5) Overall percentage of correct answers: This metric, calculated using the same formula as for the Stroop test, reflects the accuracy of participants’ responses. 6) Number of congruent correct answers: This metric represents the total count of correct responses given by participants during the Mixed Stroop task for only congruent responses. 7) Number of incongruent correct answers: This metric represents the total count of correct responses given by participants during the Mixed Stroop task for only incongruent responses. 8) Percentage of correct congruent answers: This metric, calculated using the same formula as for the Stroop test, reflects the accuracy of participants’ congruent responses. 9) Percentage of correct incongruent answers: This metric, calculated using the same formula as for the Stroop test, reflects the accuracy of participants’ incongruent responses. Perceptual Scales: At the end of each set during resistance exercise in all

trials, two perceptual scales were evaluated: ratings of perceived exertion (RPE), and Visual analogue scale for pain (VAS), as depicted in Figure 3.5 and Figure 36 respectively Participants received standardised guidance outlining precise instructions for reporting the scales. RPE assessed perceived exertion on a scale ranging from 0 to10, where 0 represents rest, 7 indicates a sensation of exertion described as ‘very hard’, and 10 signifies maximal exertion (Borg, 1998). Similarly, pain intensity was measured via VAS on a scale ranging from 0 to 10, with 0 indicating the absence of pain and 10 denoting the worst possible pain (Delgado et al., 2018) 91 Figure 3.5: Rating of Perceived Exertion scale Figure 3.6: Visual Analogue Scale for pain 3.26 Resistance Exercise Protocol In visits three to five of acute studies 1 and 2 (Chapter 7 & Chapter 8), participants were randomly assigned to perform 4 sets of leg press until failure, with 30-second resting periods, under the

following conditions: a) at 70% of 1RM without BFR (HL-RE), b) at 30% of 1RM with continuous 92 BFR (c-BFR), and c) at 30% of 1RM with intermittent BFR (i-BFR) (Clael et al., 2021, Freitas, 2020). Although single-joint exercises such as knee extensions are often preferred in BFR protocols due to the more direct isolation of quadriceps (the primary target of occlusion), leg press was selected in this study due to the unavailability of a knee extension machine at the time of data collection. While the leg press does activate additional musculature such as the gluteus maximus which is not directly occluded it still produces significant quadriceps engagement and has been widely used in BFR research as a functional multi-joint alternative (Hughes et al., 2017; Lixandrão et al., 2018) During the c-BFR condition, pressure was maintained continuously at 50% of the individualised BFR pressure throughout the entire exercise session, including the resting periods. In the i-BFR condition,

pressure incrementally increased by 10 mmHg in each set until reaching 50% of the individualised BFR pressure in the final set, with deflation of elastic pneumatic cuffs during resting periods. To ensure standardization, a tempo of 1 second eccentric and 1 second concentric phases was maintained across all three experimental conditions, facilitated by a digital metronome (Wilk et al., 2021) 3.27 Phlebotomy & Biochemistry Venous blood sampling was performed by a trained phlebotomist. Blood samples were acquired after participants completed medical questionnaires and received thorough explanations of the procedures, including any associated risks and discomforts as outlined in the above risk assessment section. Venipuncture Blood Sampling: Participants were instructed to assume a comfortable seated position, and a trained phlebotomist selected the arm for blood collection. Prior to insertion, the chosen site underwent cleansing using alcohol wipes (STERETS® Alcowipe®, Molnlycke

Healthcare LTD., UK) to mitigate the risk of infection. A tourniquet was then applied to temporarily occlude blood flow, facilitating vein visualisation and accessibility. Following vein identification, a sterile, singleuse needed (BD Vacutainer® Eclipse™ Signal™ Needle 22G, 1 in), affixed to single-use holder (BD Vacutainer® Holder) was inserted into the vein. Blood was collected directly into a 10ml tube (BD Vacutainer® Plastic Serum Tube). Upon completion, the tourniquet was released, and the needle, secured within a safety cap, was promptly discarded in a designated yellow sharp bin. Gentle pressure was applied to the puncture site to achieve haemostasis, with the application of a plaster reserved for cases where participants did not have allergies. Whole blood & serum separation: The vacutainer containing the blood was gently shaken after collection, and the samples were subsequently incubated at room temperature (20-25oC) in an upright position for 60 minutes to

facilitate clotting. Following this, the blood samples underwent centrifugation at 4.500 rpm at 4oC for 10 minutes (Eppendorf Centrifuge, Eppendorf Refrigerated 93 Centrifuge Model 5804R). In instances where immediate centrifugation was not feasible after clotting, the vacutainers were refrigerated at 4oC for a maximum duration of 4 hours, adhering to the manufacturer’s guidelines. Serum samples were then aliquoted into 5-7 cryovials (ep0030119401 Eppendorf Tube® capacity 5mL, Eppendorf QualityTM) and subsequently stored in -86oC freezer until analysis (Sanyo Ultra Low, VIP Series freezer). ELISA Plate Analysis: The serum concentrations of Growth Hormone (GH), Insulin-like Growth Factor-1 (IGF-1), cortisol, and Brain-Derived Neurotrophic Factor (BDNF) were investigated due to their involvement in muscle protein synthesis, mood, and cognitive function following resistance training protocols. Enzyme-linked immunosorbent assay (ELISA) techniques were employed to assess these

markers. The ELISA kits were provided by Abcam Solutions (Cambridge Biomedical Campus, UK) and were utilized following the manufacturer’s instructions, with detailed protocols included in the booklet. All sandwich ELISA assays involved 96-well microplates requiring coating with the capture antibody. Samples and standards were analysed in duplicate A manual multi-channel pipette (EppendorfTM ResearchTM plus mechanical multi-channel pipette) with 12 x 300μL disposable pipette tips (Fisherbrand™ SureOne™ Micropoint - X1000, Fisher Scientific UK Ltd, Loughborough, UK) was utilized during whole-plate procedures, while a single-channel pipette (Eppendorf Research 200-1000 μL, Eppendorf, UK) with a 300 μL disposable pipette tip was used during standard and serum sample procedures. All materials and prepared reagents were equilibrated to room temperature prior to use. Reagents, working standards, and samples were prepared according to the manufacturer's protocols before adding

them to the ELISA plates. The standard curve was constructed using kit-provided standards unless expected values deviated significantly based on literature, in which case, the main investigator contacted the company for further clarification to prepare the standards accordingly. Standards and samples were then added to the ELISA plates and incubated either in a dark room, shaker, or oven at specific temperatures as per the manufacturer's instructions and ELISA kit specifics. Following incubation, the wells were washed, and tetramethylbenzidine (TMB), also known as the detection antibody, was added to the wells and further incubated for a specified period according to the ELISA kit instructions. After the final incubation, a stop solution was added to the wells. The plates were then read at the appropriate wavelength on a plate reader (BioTek Universal Microplate Reader ELX 800, BioTek UK, Bedfordshire, UK). The sensitivity (mean minimal detection dose [MDD]), detection range and

the intra-assay and inter-assay precision for each marker are presented in Table 3.5 However, it is noted that the manufacturer did not provide MDD, intra-assay and inter-assay precision data for the cortisol ELISA kit. 94 Capillary Blood Lactate Sampling (La): La levels were measured using a portable blood lactate analyser (Lactate Pro 2, Arkray Inc, Japan) paired with lactate test strips (Lactate Pro 2 Test Strips, Arkray Inc, Japan). Fingertip samples were obtained from either the index or middle fingers using disposable lancets. Before collecting samples, the fingers were sanitized with an alcohol wipe, and the initial blood drop was discarded. The subsequent blood droplet was then placed onto the test strip for analysis. 3.28 Statistical Analyses The data in the experimental studies (Chapters 6,7 and 8) underwent analysis utilizing IBM SPSS Statistics version 29.010 (171) software and were presented as the mean accompanied by the standard deviation (SD), unless specified

otherwise. A significance level of p ≤ 005 was employed consistently across the thesis to control for the Type I error rate. This alpha level was chosen to ensure a 95% confidence interval, signifying that there is a 5% probability of incorrectly rejecting a true null hypothesis (Type I error). Detailed statistical analyses for each experimental chapter can be found within the respective sections. Data Analysis Framework: The studies of this PhD employed Null Hypothesis Significance Testing (NHST) as the primary statistical framework to evaluate differences between experimental conditions. NHST is a widely used approach in research that assesses whether observed data provide sufficient evidence to reject a null hypothesis (H₀), which typically states that there is no effect or difference between groups (Nickerson, 2000). The alternative hypothesis (Hₐ) represents the presence of an effect. This approach involves calculating a p-value, which quantifies the probability of obtaining

results at least as extreme as those observed, assuming the null hypothesis is true (Wasserstein & Lazar, 2016). A p-value below a predetermined alpha level (commonly 005) leads researchers to reject H₀ in favour of Hₐ, indicating a statistically significant result. 95 NHST was selected in this thesis due to its established use and interpretability within exercise science and biomedical research, providing a structured and familiar method for testing group-level effects. For normally distributed data, repeated measures ANOVA was used, followed by Bonferroni-corrected post hoc comparisons. For non-normally distributed data, the Friedman test was applied, with Wilcoxon signed-rank tests and Bonferroni correction for post hoc analysis. However, despite its practicality, NHST has important limitations. P-values do not reflect the probability that either the null or alternative hypothesis is true, and they can be strongly influenced by sample sizepotentially leading to false

positives or negatives (Gelman & Stern, 2006). Moreover, NHST does not provide estimates of effect size or practical significance, which are crucial for interpreting real-world impact (Cumming, 2014). In contrast, Bayesian statistics offer a different perspective by estimating the probability of hypotheses given the observed data and by incorporating prior knowledge into the analysis (Kass & Raftery, 1995). This allows for a more nuanced understanding of evidence but requires careful selection of prior distributions and is less commonly used in applied exercise science to date. Given these considerations, NHST was deemed an appropriate and accessible statistical approach for this thesis. Nonetheless, its limitations were acknowledged and addressed through the reporting of descriptive statistics, effect sizes, and corrected post hoc tests to enhance transparency and interpretability of the findings. Power Analyses: Before commencing the experiments, G*Power software version 3.1

was utilized to determine the sample size necessary for both the pilot and acute studies detailed in Chapters 6, 7, and 8. This determination adhered to established guidelines for a priori sample size calculation (Prajapati, 2010). The effect size utilized for the primary dependent variables, such as RPE and pain in the pilot study, and blood biomarkers including BDNF and GH in acute studies 1 and 2, was derived from published mean and standard deviation (SD) data obtained from similar experimental designs (Bell et al., 2018; Brandner and Warmington, 2017; Dankel et al, 2019; Du et al, 2021; Freitas et al., 2019; Laurentino et al, 2022; Manini et al, 2012; Vilaça-Alves et al, 2022) The required number of participants was determined based on predefined alpha (α: 0.05) and beta (β: 0.80) levels, ensuring adequate statistical power A total of 14 participants was enough to reach the statistical power of 80% for pilot study (Chapter 6) and a total number of 19 participants was required

for acute studies 1 & 2 (Chapter 7 & 8). Hypotheses testing: Throughout the present thesis, a variety of statistical methods were employed to assess the acceptance or rejection of the predetermined null or alternative hypotheses outlined at the outset of each experimental study. Normality: Before proceeding with additional analyses, the data underwent assessment for normality through the Shapiro-Wilk test, as well as examination of skewness and kurtosis (Cohen, 96 2013). Skewness and kurtosis were evaluated to provide additional insights into the distributional characteristics of the data (Tabachnick, 2013). Specifically, skewness measures the symmetry of the distribution, with values closer to zero indicating greater symmetry, while kurtosis measures the peakedness or flatness of the distribution, with values closer to zero indicating a more Gaussian shape. Additionally, the absolute values of skewness and kurtosis were assessed to determine if they fell within the range

of approximately +-2, a commonly used threshold to consider the data as approximately normally distributed (Tabachnick, 2013). These assessments were employed to evaluate the appropriateness of assuming a normal distribution for the data and to ascertain the likelihood of random error impeding normal distribution. Sphericity: Mauchly’s test for sphericity was used to assess whether the assumption of sphericity was met. When the p-value >005, the assumption was considered violated In cases where the test indicated significant sphericity with an estimate of ≤0.75, the Greenhouse-Geisser correction was applied to adjust the interpretation of the ANOVA results. Conversely, when the sphericity estimate was >0.75, the Huynh-Feldt correction was employed Both correction methods modify the degrees of freedom used in evaluating the F-ratio, in line with the recommendations provided by Field (2013). Parametric data: Following the normality assessment, if the data were found to adhere

to a normal distribution, descriptive statistics were utilized to summarize the data in the present thesis. Data in that case presented as means and standard deviations. The mean, calculated as the sum of all data points divided by the total number of data points, provides a measure of central tendency, representing the average value of the data set. Meanwhile, the standard deviation quantifies the dispersion or spread of the data around the mean, offering insights into the variability within the data set (Field, 2013). Non-parametric data: When data were found to deviate from normality, as determined by a ShapiroWilk test, non-parametric statistics were employed. In such cases, descriptive statistics were presented as medians, interquartile ranges (IQRs), and percentile ranks. The median, representing the middle value of the dataset when ordered, provided a robust measure of central tendency less susceptible to the influence of outliers compared to the mean. The IQR, calculated as the

difference between the third quartile (Q3) and the first quartile (Q1), captured the spread of the middle 50% of the data (Field, 2013). Additionally, percentile ranks were utilized to indicate the percentage of data points falling below a specified value, facilitating comparisons across datasets regardless of their distributional properties. These non-parametric descriptive statistics served as valuable tools for summarizing and interpreting data in instances where parametric assumptions were not met (Field, 2013). Reliability: The reliability of the KAATSU equipment was evaluated using a test-retest approach. Reliability was assessed through Pearson correlation coefficients (r), which measure the strength 97 and direction of the linear relationship between scores obtained from the same participants on two different occasions (Carmines, 1981). A Pearson correlation coefficient of 1 indicates perfect positive correlation, meaning the scores are fully consistent across both

sessions. In contrast, a coefficient of -1 signifies perfect negative correlation, indicating a complete inverse relationship between scores. A coefficient of 0 suggests no correlation, implying no consistent relationship between the two sets of scores. The p-value was set at ≤005 for determining significance Additionally, intraclass correlation coefficients (ICC) were calculated to provide a more robust measure of reliability by considering both within- and between-subject variability (Gwet, 2008). When the p-value for the ICC was >0.05, this indicated poor reliability Furthermore, the typical error (TE) and the coefficient of variation for the typical error (TE [CV%]) were also analysed to quantify measurement precision and consistency across repeated measures (Hopkins, 2000). Parametric Data Analysis: A two-way repeated measures ANOVA was conducted with two factors (condition × time) to analyse differences in variation within groups, across the pilot study and both acute

studies, each of which employed a crossover design. This analysis was used to determine the effects of different conditions over time within subjects, with a significance level set at p ≤ 0.05 (Field, 2013). When a significant F value was obtained, post hoc comparisons were adjusted using Bonferroni’s correction, maintaining a significant level of p ≤0.05, ensuring that the Type I error rate during follow-up tests remained at 5%. This correction was implemented to mitigate the familywise error rate associated with multiple comparisons. Additionally, a one-way ANOVA was conducted to investigate delta changes as the interaction effect within condition. Only variables that showed significant differences in delta changes between conditions are reported in the experimental study chapters, while non-significant findings were omitted for clarity and brevity. This approach ensures that the focus remains on the most relevant and impactful outcomes. For the pilot study, exploratory

statistical analysis was performed using paired t-tests to evaluate the isolated effect of each BFR modality (continuous BFR versus intermittent BFR). This approach allowed for the comparison of mean differences within the same group under different conditions, helping to identify the unique impact of each modality. Non-Parametric Data Analyses: A Friedman test was conducted to analyse the non-parametric data, with a significance level set at p≤0.05 The Friedman test is a non-parametric test, commonly used, for analysing repeated measures data, particularly when the assumptions of parametric tests like ANOVA are not met (Conover, 1999). Following a significant effect of interaction within the Friedman test, pairwise comparisons using the Wilcoxon singed-rank test was conducted to examine specific differences between pairs (Gibbons and Chakraborti, 2014). A correction to control the familywise error rate in multiple comparisons was also applying manually to maintain the overall Type I

error rate at predetermined level (Holm, 1979). This correction involved dividing the significance level (0.05) by the number of pairwise comparisons conducted To investigate delta 98 changes as the interaction effect within conditions, Kruskal-Wallis analysis was also conducted (Siegel, 1957). Parametric vs. Non-Parametric Data Analyses: Subjective measures such as the RPE, VAS for pain, POMS, and muscle soreness scales were included in this thesis to capture perceptual and affective responses. These outcomes are inherently ordinal in nature, meaning the values indicate order but not necessarily equal intervals between them (Norman, 2010; Dankel et al., 2019) In such cases, non-parametric statistical tests (e.g, Wilcoxon signed-rank, Friedman tests) were used when the data violated normality assumptions, as they are more appropriate and robust for analysing skewed or ordinal datasets without assuming equal variance or interval spacing (Altman, 1990; Bell et al., 2018) Conversely,

when the data were normally distributed, as in the case of POMS scores in the Pilot Study, parametric tests were applied, in line with the assumption that treating ordinal data as interval can be justifiable under specific conditions (Streiner, 1995; Brandner & Warmington, 2017). For blood biomarkers (BDNF, GH, IGF-1, cortisol), a different approach was taken. These variables are ratio-scale data, not ordinal, meaning they possess a true zero and equal intervals, which justifies the use of parametric tests under appropriate distributional assumptions. However, due to biological variability and individual differences, these data are often right skewed and did not meet normality assumptions in their raw form. Instead of applying non-parametric testswhich are less powerful and less commonly used for biochemical datalog₁₀ transformation was employed to normalise the distributions (Wilcox, 2017). This is a standard and widely accepted method in the field of exercise endocrinology

and physiology (e.g, Manetta et al, 2002), particularly when the goal is to analyse relative changes in concentrations and interpret interaction effects across time and condition. Importantly, while the analyses were performed on log-transformed data, the presentation of results (e.g, figures and descriptive statistics) used the original, untransformed mean ± SD values This was done deliberately to enhance the interpretability of findings and facilitate comparison with previous studies, which typically report raw hormone concentrations. In summary, subjective data were analysed using non-parametric or parametric tests depending on normality and measurement level, whereas objective biomarker data (ratio-level) were logtransformed when non-normal to enable valid parametric testing, in keeping with established best practices in the physiological literature. This mixed analytical strategy ensured both statistical rigour and practical relevance, respecting the nature of each variable type

while aligning with disciplinespecific conventions. 99 4. Meta-analysis 1: ‘Impact of blood flow restriction training duration, upper vs. lower body training, and pressure application protocols during resistance training on muscle strength and muscle mass adaptations in healthy adults: A Systematic Review & Meta-Analysis’ 100 4.1 Abstract Introduction: High load resistance training (HL-RT) is the gold standard for increasing muscle strength and mass. However, HL-RT is often not viable for frail populations due to its high mechanical impact on joints and bones. Low load resistance training with blood flow restriction (BFR-RT) is suggested as an alternative, though studies show conflicting results, possibly due to methodological heterogeneity. This study aims to compare the effects of BFR-RT and HL-RT on muscle strength and mass, considering factors such as body region (upper versus lower body), intervention duration (<8 weeks versus ≥8 weeks), and BFR pressure

protocols (individualised versus non-individualised). PROSPERO registration ID (CRD42021246633) Methods: A systematic search was conducted in four electronic databases and reference lists. Analyses focused on post-intervention changes in maximal muscle strength and muscle mass. A continuous randomeffects model determined the effect size using standardised mean difference (SMD) with 95% CI Results: Of 1142 studies, 27 met the inclusion criteria, totalling 538 participants. Muscle strength adaptations did not differ between BFR-RT and HL-RT for lower body lasting ≥ 8 weeks (SMD=0.157 [95%CI: -0322, -0009]) Strength gains were also similar when personalised arterial occlusion pressure (AOP) was applied (SMD=-0.148, [95%CI: -0339,0043]) Muscle strength improvements in the upper body were similarly effective following both BFR-RT and HL-RE, regardless of training duration (<8 weeks: SMD = -0.218 [95% CI: -0486, 0050]; ≥8 weeks: SMD = -0.235 [95% CI: -0518, 0047]) Muscle mass

increases were comparable between BFR-RT and HL-RT, regardless of training duration, targeted musculature, or BFR pressure application protocols (SMD=-0.017 [95%CI: -0109, -0143]) Conclusion: BFR-RT appears as effective as HL-RT for increasing lower body muscle strength when interventions last ≥8 weeks in healthy adults aged 1864 years. Additionally, when using individualised AOP, muscle strength gains from BFR-RT are comparable to those from HL-RT. Both training methods result in similar muscle mass gains 101 4.2 Introduction Muscular strength and muscle mass play a pivotal role in functional capacity and overall health, determining the future risk of chronic diseases and mortality (Artero et al., 2012, McLeod et al, 2016). However, poor lifestyle choices such as physical inactivity, and poor nutrition, in addition to ageing and its comorbidities, can lead to decreased muscle strength (dynapenia) and muscle mass (sarcopenia) exacerbating the risk of disease and musculoskeletal

injuries (Chen et al., 2013; Hartard et al., 1996; Lang et al, 2010,) Particularly, sarcopenia is an independent predictor of chronic disease and mental illness, negatively impacting exercise capacity, quality of life and overall well-being (Evans, 2010; Hartard et al., 1996; Lambert & Evans, 2002; Lang et al, 2010) Resistance training is an established key component of exercise training to combat dynapenia and sarcopenia and potentially slow down the adverse effects of ageing and physical inactivity (American College of Sports, 2009). Specifically, high intensity resistance training ranging between 60% to 100% of 1 Repetition Maximum (1-RM) is a validated standardized exercise regime promoting muscle protein synthesis and hypertrophy, leading to muscle strength, and overall exercise capacity improvements in healthy adults (Rossi et al., 2018; Schoenfeld et al, 2019; Schoenfeld et al., 2021) However, these recommended resistance training intensities, while effective, may not always

be tolerable or safe for clinical, elderly, and injured populations (Rossi et al., 2018) Additionally, the induced high mechanical stress imposed on the joints and bones can lead to increased feelings of soreness and localized pain, potentially compromising exercise adherence and overall enjoyment of exercise. Various training modalities have been explored in the literature to counter the limitations of high intensity resistance training in populations that cannot tolerate resistance training at high intensities (de Oliveira et al., 2015; Lasevicius et al, 2022; Kim et al, 2012; Schoenfeld et al, 2016) Blood flow restriction (BFR) training is an alternative modality to high intensity resistance training that has been studied in the literature since the 1990s with numerous evidence demonstrating its efficacy (Cerqueira et al., 2021; Freitas et al, 2021; Patterson et al, 2019) BFR, also known as occlusion or KAATSU training, employs the application of a tourniquet, or elastic band

proximally to the muscle being trained inducing partial arterial blood restriction and local hypoxia leading to advantageous mechanical stress and stimulation of key metabolic and growth factor pathways (Iida et al., 2011) In the last three decades, numerous studies have investigated the use of BFR during low load resistance training (BFR-RT) (20%-50% of 1-RM) as an alternative to the traditionally prescribed high load resistance training (HL-RT). The majority of these studies have found significant improvements in muscle strength, muscle mass, sprint performance and neuromuscular function in various populations such as healthy adults, elderly and clinical individuals as well as athletes, demonstrating the potential effectiveness of BFR as a fitness and rehabilitation modality (Bagley et al., 2015; Bemben et al, 2010; Gronfeldt et al, 2020; Libardi et al, 2014; Lixandrão et al., 2018; Rolnick & Schoenfeld, 2020; Vanwye et al, 2017) However, there is still contradictory 102

evidence in the literature questioning the application and effectiveness of BFR particularly in frail, elderly and clinical populations and in some cases demonstrating negative perceptual responses such as increased pain and soreness in the local musculature where occlusion is applied (Gronfeldt et al., 2020; Lixandrão et al, 2018) The contradictory evidence on the use of BFR-RT is partly attributed to methodological heterogeneity in the BFR literature. This heterogeneity is evident in the large variations in methodological approaches employed, including different BFR exercise training regimes, pressure application protocols, and the use of BFR equipment. Such diversity may complicate and limit our understanding of how BFR-RT compares to the golden standard HL-RT in terms of muscle strength and muscle hypertrophy (Chang et al., 2023; Clarkson et al, 2020; Mattocks et al, 2017) Moreover, there is considerable variability in the literature regarding training duration, targeted muscle

groups (upper body vs. lower body), and populations studied (healthy adults, elderly, athletes vs nonathletes) (Centner & Lauber, 2020; Chang et al, 2023; Clarkson et al, 2020; da Cunha Nascimento et al., 2019; Domingos & Polito, 2018; Fabero-Garrido et al, 2022; Gronfeldt et al, 2020; Lixandrão et al., 2018; Loenneke et al, 2012; Mattocks et al, 2017; Slysz et al, 2015) This diversity, often treated as a homogenous group, adds to the complexity and conflicts in our understanding of the effects of BFR-RT on these diverse populations. Recent meta-analyses have sought to differentiate and isolate the impact of age and/or the different methodological protocols for BFR pressure application on the muscle strength and muscle mass adaptations to training (Fabero-Garrido et al., 2022; Kong et al, 2022) In a recent systematic review and meta-analysis conducted by Kong et al. (2022), the authors controlled for the effect of ageing, comparing muscle strength and muscle mass adaptations

of BFR-RT versus HL-RT in elderly with sarcopenia, it was found that BFR-RT led to greater improvements in muscle strength but lower improvements in muscle mass compared to HL-RT (Kong et al., 2022) The findings of this metaanalysis demonstrated that elderly with sarcopenia could experience similar benefits to younger individuals without sarcopenia in muscle strength, but not in muscle mass, as per previous studies (Bemben et al., 2022, Biazon et al, 2019, Shiromaru et al, 2019) Furthermore, a systematic review and meta-analysis by Fabero-Garrido et al. (2022), in an attempt to isolate the effect of older age, investigated the effects of BFR-RT versus HL-RT in healthy adults aged over 60, and reported lower muscle strength gains, but similar muscle hypertrophic gains in BFR-RT compared to HL-RT (Fabero-Garrido et al., 2022) Previous meta-analyses have also attempted to control the methodological difference in BFR approaches. In a comprehensive systematic review and metaanalysis by

Lixandrao et al (2018), a range of studies involving subjects of diverse age groups and physical activity levels were analysed and controlled for factors such as occlusion pressure and cuff width (Lixandrão et al., 2018) They found that HL-RT resulted in greater muscle strength gains compared to BFR-RT, regardless of the occlusion pressure and cuff width, demonstrating the effectiveness of BFR-RT as an alternative modality (Lixandrão et al., 2018) However, the authors did not control the effect of ageing and physical activity, potentially partly confounding their 103 findings. Finally, a recent meta-analysis conducted by Chang et al (2023) investigated the effects of BFR cuff pressure characteristics by analysing the impact of applying different BFR pressure application protocols such as individualised versus non-individualised, and cuff inflation patterns on muscle strength adaptations following BFR-RT compared to HL-RT. They reported similar muscle strength gains between BFR-RT

and HL-RT only when applying individualised, incremental, and intermittent pressure exercise protocols in BFR-RT (Chang et al., 2023) This finding highlights the importance of considering that BFR protocols, such as the method by which a specific pressure is applied during exercise with BFR, can alter the results when comparing muscle strength adaptations between BFR-RT and HL-RT. Despite the extensive research and growing number of meta-analyses on BFR-RT published between 2019 and 2022, there remains a need for further clarification due to the continued heterogeneity in study populations and training protocols. Previous meta-analyses have often included mixed populations such as elderly, clinical, or athletic individuals, which can confound interpretations related to healthy adults (aged 18–64). To our knowledge, no previous meta-analysis has exclusively focused on healthy non-athletic adults while simultaneously investigating how training musculature (upper vs. lower body),

training duration (<8 vs ≥8 weeks), and pressure application protocol (individualised vs. non-individualised) might independently or jointly affect the efficacy of BFR-RT compared to HL-RT. These subgroup comparisons were selected based on recurring methodological inconsistencies identified in the literature. First, the training musculature (upper vs. lower body) may differentially influence strength and hypertrophy responses due to anatomical and physiological differences in muscle groups and their responses to blood flow restriction (Candow & Chilibeck, 2005; Haizlip et al., 2015; Jung et al, 2023; Kern et al, 2001; Mansour et al., 2021; Miller et al, 1993; Plotkin et al, 2021; Roberts et al, 2020; Schoenfeld et al, 2021; Stowers et al., 1983; Willough, 1993) Second, training duration is a critical variable in resistance training adaptations, and short versus long interventions may yield different outcomes, for both muscle strength and muscle hypertrophy (Enoka, 1988;

Fernandes et al., 2020; Kim et al, 2009; Sale, 1988; Shiromaru et al., 2019) Third, the protocols used for pressure application (eg, individualised vs. fixed pressures) are known to affect perceptual and physiological responses during BFR-RT and may be a key determinant of its effectiveness (Loenneke et al., 2012; 2015) Investigating these factors together, in a controlled population, can help isolate their individual and combined effects on muscle strength and mass adaptations, providing more precise and generalisable conclusions for practice. Therefore, the primary aim of this meta-analysis was to investigate the sole and combined effects of: a) BFR protocols targeting different musculature (i.e upper versus lower body training), b) varying durations of BFR training intervention (i.e <8 weeks versus ≥8 weeks), and c) different BFR pressure application protocols (i.e individualised versus non-individualised pressure application protocols) on muscle strength and muscle mass in

healthy adults aged 18–64 years. 104 4.3 Methodology This is the first part of the meta-analysis that was designed to adhere to the PRISMA guidelines (Section 3.1) 4.31 Search Strategy & Study Selection All studies were identified by searching four electronic databases. The articles were identified by searching the following four electronic databases from inception to 1st of February 2023: MEDLINE via PubMed, EmbaseMBASE via Ovid, Web of Science, and SportDiscus via EBSCO. No restrictions were made for language and publication year. Cross-referencing searching by backtracking relevant publications, scanning reference lists of relevant articles was conducted The following search terms were included to search in all the databases: “resistance training”, “weightlifting”, “multi-joint resistant exercise”, “hypertrophy”, “muscle strength”, “intermittent pneumatic compression devices”, “blood flow restriction”, “blood flow occlusion”, “occluded

blood flow”, “restricted blood flow”, “vascular occlusion”, “vascular restriction”, and “Kaatsu”. See Appendix 15 for full search string. 4.32 Eligibility Criteria A PICOS (participants, intervention, comparators, study outcomes, and study design) format was used for the inclusion and exclusion criteria to rate the studies for eligibility (Table 4.1) (Moher et al., 2009) Table 4.1 Selection Criteria Category Inclusion Criteria Exclusion Criteria Population Healthy adults, ≥18 and ≤64 years old Elderly, Clinical population, Athletes Low-load resistance training with BFR* combined with electrical stimulation and Absence of resistance training or BFR Intervention vibration training Comparators High-Load resistance training without BFR Absence of high-load resistance training without BFR Study outcomes Study design See 2.3 Type of Outcome Measures Randomised controlled trials *BFR; Blood flow restriction 105 Non-randomised controlled trials 4.33

Type of Outcome Measures Included studies for muscle strength and muscle hypertrophy involved a training intervention protocol with intervention groups performing high-intensity resistance training (60%-99% of 1RM) versus a group performing low-intensity resistance training (20%-50% of 1-RM) with BFR. Participants who performed a low load resistance training with BFR were compared to participants who performed a high load resistance training without BFR. Additionally, the same exercise protocol should be followed between the groups (i.e leg press, handgrip, biceps, etc) with and without BFR. A priori primary outcome measures included changes in muscle strength and muscle hypertrophy measured by dynamic, isometric or isokinetic test (e.g 1 maximum repetition, 1-RM) and magnetic resonance imaging, ultrasound, measurement of upper/lower circumference (i.e for muscle cross sectional area, CSA, anthropometric tape). All included studies in this systematic review report at least one of the

aforementioned measurements for muscle strength and muscle hypertrophy respectively. 4.34 Data Selection All studies were imported into EndNote (EndNote X9.31, Clarivate Analytics, USA) and Microsoft Excel (Excel 365, Microsoft Corporation, USA). Duplicates were removed by the main reviewer. Two independent reviewers evaluated the results of the initial search using a successive three-step screening procedure: (a) title screening, (b) abstract screening, and (c) full-text reading. The screeners were not blinded to either the journal titles or to the study authors/affiliations. Reasons for exclusion were coded based on one or more of the following: (i) inappropriate comparison(s) (n=58), (ii) congress presentations and posters, thesis and abstracts, (n=23), (iii) other than English language (n=3), (iv) review papers (n=5), (v) inappropriate population (n=6), (vi) inappropriate outcome(s) & study designs (n=30). The screeners met to discuss their selections and reconciled any

discrepancies by consensus with input from the author (IG). Missing data items were sought by e-mail to the corresponding study author(s). If no response was received within one week, two additional follow-up attempts were made within the following month. Studies were excluded from the meta-analysis if the necessary data could not be obtained after these efforts. Data extracted are available in Figure 4.1 For the assessment of quality and risk of bias please see Chapter 3 106 4.35 Assessment of Quality & Risk of Bias The risk of bias was assessed for all the studies following the PRISMA 2020 guidelines (Section 3.11) 4.36 Statistical Analyses Statistical analyses on the global effects of BFR-RT versus HL-RT on muscle strength and muscle mass were calculated (Section 3.12) Exploratory meta-analyses were also conducted for parameters such as a) upper versus lower body exercise, b) intervention length (<8 weeks versus ≥8 weeks), c) individualised versus non-individualised

blood flow pressures, and d) ≥50% of the individualised blood flow pressure versus <50% of the individualised blood flow pressure. 107 4.4 Results 4.41 Search Results & Studies Characteristics The search from four electronic databases returned 5918 studies. From these 2325 were excluded as they were identified as duplicates from EndNote 20 and Microsoft Excel 365. The first and the second authors read the titles and the abstracts and after consensus they decided to exclude 3361 based on the data selection criteria. The remaining studies were fully read and 27 were included for this meta-analysis (1 study was identified through cross referencing) (Figure 4.1) (Kim et al, 2009) The risk of bias for randomised controlled trials is summarized in Table 4.2 Figure 4.1 Diagram showing the search process 108 Overall, 27 studies investigating the effects of HL-RT versus BFR-RT on muscle strength were included in this systematic review and meta-analysis. A total of five

hundred and thirty-eight (n=538) participants took part in 59 interventions comprising 502 males and 36 females (Table 4.3) Additionally, 18 studies were included comparing the HL-RT vs BFR-RT adaptations on muscle hypertrophy, with a total of three hundred and seventy-eight (n=378) participants taking part in 42 interventions, comprising 358 males and 20 females (Table 4.4) 109 110 111 112 113 4.42 Muscle Strength Results Overall, the findings from the global data analysis showed that HL-RT led to significantly greater increases in muscle strength compared to BFR-RT (SMD = -0.227, with a p <0001, 95% CI: -0340, -0.113 and I2 = 0%, df=57, p=0999) Similarly, in the sub-analysis investigating the sole effect of the musculature trained (upper vs. lower body) on muscle strength, HL-RT was found to induce greater muscle strength adaptations to BFR-RT in both upper and lower body exercises (SMD= 0.235, with a p=0013, 95% CI: -0420, -0049, I2 = 0%, with a p=0802

versus SMD= -0222, with a p=0.002, 95% CI: -0365, -0079 and I2=0%, with a p=0999 for the upper and lower body respectively) (Figure 4.2) Moreover, in the sub-analysis investigating the sole effect of the intervention duration (<8 weeks vs. ≥8 weeks), HL-RT yielded greater muscle strength gains compared to the BFR-RT condition, independent of the duration of training (SMD= -0.311, p=0001, 95% CI -0497, -0125; I2 = 0%, p=0780 versus SMD= -0177, p=0015, 95% CI -0320, 0034; I2 = 0%, p=1 for <8 weeks training length and for ≥8 weeks training respectively) (Figure 4.3) BFR-RT was found to lead to similar improvements in muscle strength to HL-RT when we analysed for the combined effect of the intervention duration (<8 weeks vs. ≥8 weeks) and the musculature trained (upper vs. lower body) Specifically, in the upper body BFR-RT demonstrated similar muscle strength increases to HL-RT both in interventions lasting <8 weeks and ≥8 weeks (<8 weeks: SMD= -0.218 with a p=0111,

95% CI: -0486, 0050 and a I2 = 1064%, with a p=0339 versus ≥8 weeks: SMD= -0.235, with a p = 0102, 95% CI: -0518, 0047 and a I2 = 0%, with a p=0.982) (Figure 44) In the lower body, BFR-RT produced similar muscle strength gains to HLRT, when the training duration was 8 weeks or longer (SMD= -0157, p=0064, 95% CI: -0322, 0009 and a I2 = 0%, with a p=0998) In contrast, when the training lasted less than 8 weeks, HLRT resulted in significantly greater strength improvements compared to BFR-RT (SMD= -0415 with a p=0.004, 95% CI: -0700, -0131, and I2 = 0%, with a p=0984) (Figure 45) In the sub-analysis examining the sole effect of the various BFR pressure application protocols, BFR-RT was found to induce similar muscle strength gains to HL-RT only when the percentage individualised protocol was applied (SMD= -0.148, with a p= 0128, 95% CI: -0339, 0043, I2 = 0%, p=0.993) (Figure 46) In contrast, the studies that employed the non-individualised pressure application protocols and other

individualised pressure protocols demonstrated greater improvements in muscle strength with the HL-RT compared to BFR-RT (non-individualised protocols: SMD = -0.212, with a p-value of 0010, 95% CI: -0374, -0050, I2 = 0%, with a p=0959, versus other individualised pressure application protocols: SMD= -0.448, with a p=0002, 95% CI: -0.733, -0163, I2 = 0%, with a p=0953) (Figure 46) In the final exploratory sub analysis on the sole effect of the BFR pressures (≤50% vs. >50%) of individualised pressure, no statistically significant differences were found between HL-RT and 114 BFR-RT in muscle strength adaptations, with BFR-RT producing similar muscle strength gains to HL-RT, regardless of the percentage of the BFR pressures being applied. However, it is important to note here, that the effect size was lower in studies employing ≤50% compared to those using >50% pressure (>50% pressure: SMD=-0.232, with a p=0051, 95% CI: -0465, 0001, I2= 0%, p=0.998, versus ≤50% pressure:

SMD=0021, p=0901, 95% CI -0310, 0352, I2= 0%, p=0820) (Figure 4.7) Figure 4.2 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle strength on the upper body and the lower body 115 Figure 4.3 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on lower body muscle strength following training interventions of <8 weeks and ≥ 8 weeks duration. 116 Figure 4.4 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on upper body muscle strength following training interventions of <8 weeks and ≥8 weeks duration. Figure 4.5 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle strength on the Lower Body for<8 weeks and ≥8 weeks training interventions 117 . Figure 4.6

Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle strength based on a) Other individualised protocols, b) non-individualised protocols and c) percentage individualised protocols. 118 Figure 4.7 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle strength based on a) >50 of blood flow restriction (BFR) pressure applications, b) ≤50 of blood flow restriction (BFR) pressure applications. 119 120 121 122 4.43 Muscle Mass Results The global effect analysis comparing the effect of BFR-RT vs. HL-RT on muscle mass revealed similar hypertrophic improvements between the two conditions (SMD= -0.017, with a p =0790, 95% CI: -0.109, -0143, I2 = 0%, with df=35 and a p=1) Similarly, all further sub-analyses conducted found similar improvements in muscle mass between HL-RT and BFR-RT. Specifically, in the

sub-analysis investigating the sole effect of the musculature trained (upper vs. lower body), HL-RT and BFR-RT led to similar improvements in muscle mass (upper body: SMD= 0.006, with a p=0.962, 95% CI: -0225, -0237, and a I2 = 0%, with a p=0808, versus lower body: SMD= 0022, with a p=0775, 95% CI: -0129, -0173 and a I2 = 0% with a p=1) (Figure 48) Figure 4.8 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle mass on the upper body and the lower body 123 Moreover, the sub-group analysis investigating the duration of the intervention (≥8 weeks vs. <8 weeks) on muscle mass, BFR-RT induced similar hypertrophic adaptations to HL-RT independent of the training duration (<8 weeks: SMD= 0.044, with a p=-0587, 95% CI: -0115, -0203, and I2 = 0% with a p=0.996, versus ≥8 weeks: SMD= -0028, with a p=0788, 95% CI: -0235, -0179, and I2 = 0% with a p=1) (Figure 4.9) Similarly, in the combined

sub-analysis of intervention duration and musculature trained, BFR-RT resulted in similar increases in muscle mass to HL-RT in the lower body (lower body, <8 weeks: SMD = 0.079, with a p= 0481, 95% CI: -0141, 0299 and I2 = 0%, p=1, versus lower body, ≥8 weeks: SMD= -0.028, with a p=0788, 95% CI: -0235, 0179 and I2 = 0% with a p=1) (Fig.410) No studies included in the present meta-analysis investigated the effects of muscle mass between the two modalities in the upper body for ≥8 weeks. Therefore, the combined effect of training duration and the upper body focused on interventions lasting <8 weeks, revealing similar muscle mass gains between BFR-RT and HL-RT (SMD=0.006, p=0962, 95% CI: -0.225, 0237, I2 = 0%, p=0808) (Figure 410) Figure 4.9 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle mass for a) <8 weeks and b) ≥ 8 weeks training interventions. 124 Figure 4.10 Effects of high load

resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle mass on the Upper Body for <8 weeks and on the Lower Body for <8 weeks and for ≥8 weeks training interventions. Similarly, the sub-analysis exploring the sole effect of the different pressure application protocols employed (non-individualised BFR pressure application protocols vs. percentage individualised BFR pressure protocols) demonstrated BFR-RT and HL-RT to induce similar improvements (nonindividualised protocols: SMD= -0.021, with a p= 0833, 95% CI: -0215, 0173, and a I2 = 0% with a p=0.959, versus percentage individualised protocols: SMD= 0043, with a p= 0613, 95% CI: 0125, 0211 and a I2 = 0% with a p=1) (Figure 411) It is worth noting that the present sub-analysis specifically focused on non-individualised and percentage individualised protocols, as only one of the included studies employed other individualised pressure protocols (Barbieri et al., 2020)

Finally, the sub-analysis on the percentages of the individualised pressure protocols (≤50% vs, >50% of the AOP) found no significant differences between BFR-RT and HL-RT in the increases seen in muscle mass post training, regardless of the percentage of the pressure being applied (>50% pressure: SMD=-0.020, with a p= 0859, 95% CI: -0204, 0245 and a I2= 0%, with a p=1, versus ≤50% pressure: SMD=-0.073, with a p= 0574, 95% CI: -0180, -0326 and I2= 0%, with a p=099) (Figure 4.12) 125 Figure 4.11 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle mass based on a) Non-individualised protocols and b) Percentage individualised protocols. Figure 4.12 Effects of high load resistance training (HL-RT) versus low load resistance training with blood flow restriction (BFR-RT) on muscle mass based on a) >50% of individualised pressures, b) ≤50% of individualised pressure. 126 4.5 Discussion BFR

during low load resistance training has been suggested in the literature as an effective, alternative exercise modality to the traditional prescribed resistance training programs for muscle strength and muscle hypertrophy in young and older individuals as well as athletic individuals (Bagley et al., 2015; Bemben et al, 2010; Gronfeldt et al, 2020; Libardi et al, 2014; Lixandrão et al., 2018; Rolnick & Schoenfeld, 2020; Vanwye et al, 2017) However, there are contradictory findings in the literature regarding the efficacy of BFR in muscle strength and muscle mass adaptations to resistance training (Gronfeldt et al., 2020; Lixandrão et al, 2018) This may be partly attributed to the significant heterogeneity evident in the BFR literature, encompassing various methodological approaches and populations. Hence, the primary purpose of this meta-analysis was to control for and investigate the sole and combined effects of the confounding parameters: training duration, upper vs. lower body

training and different BFR pressure protocols, on the muscle strength and muscle mass responses to BFR versus the traditionally prescribed HL-RT. Additionally, the secondary purpose of the study was to investigate the effect of BFR-RT exclusively on healthy adults aged 18-64 years old, excluding athletic, elderly and clinical populations, hence minimizing the potential error that might arise due to age, disease and/or athletic status on our understanding of the effects of BFR-RT. One of the main findings of the present meta-analysis was that BFR-RT, when performed for at least 8 weeks led to increases in lower body muscle strength comparable to those achieved with HL-RT, which supports the hypothesis of the present study. Additionally, comparable strength increases between BFR-RT and HL-RT were also observed in the upper body regardless of the training duration. Regarding muscle mass, similar positive adaptations were observed between BFR-RT and HL-RT, regardless of training duration,

targeted musculature, or BFR pressure protocols, further supporting the initial hypothesis. To the authors’ knowledge, this is the first attempt in the literature to control and investigate the sole and combined effects of training duration, trained musculature (upper vs. lower body), and different BFR pressure protocols on muscle strength and muscle mass adaptations, with the aim of gaining a clearer and deeper understanding of the adaptations to BFR-RT and its effectiveness as an alternative modality to HL-RT. Interestingly, in the present study, when none of the confounding methodological parameters were taken into account, BFR-RT appeared to induce lower muscle strength gains compared to the traditionally prescribed HL-RT in healthy adults. This aligns with part of the recent research literature suggesting the relative ineffectiveness of BFR-RT compared to HL-RT in muscle strength development regardless of age or prior training experience (Chang et al., 2023; Fabero-Garrido et

al., 2022; Lixandrão et al, 2018) However, when the effects of trained musculature and training duration were controlled, it was evident that BFR-RT was equally effective to HL-RT in promoting lower body muscle strength gains -but only when training lasted beyond 8 weeks. In contrast, for interventions shorter than 8 weeks, BFR-RT appears less effective than HLRT These findings align with studies in healthy adults (Gronfeldt et al, 2020) and older individuals 127 with sarcopenia (Kong et al., 2022), which also reported similar strength improvements between BFR-RT and HL-RT when interventions were 8 or more weeks. The influence of training durations on strength outcomes can be partially explained by the temporal interplay between neural and muscular adaptations (Fernandes et al., 2020; Sale, 1988) Traditionally, it has been well-documented that neuromuscular improvements, such as increased mort unit recruitment, enhanced firing frequency, and improved coordination, dominate the

early phases of resistance training (typically within the first 6-8 weeks) and account for initial gains in strength (Enoka, 1988; Fernandes et al., 2020; Kim et al, 2009; Sale, 1988; Shiromaru et al, 2019) However, these neurological adaptations do not act in isolation. Structural changes such as hypertrophy may begin within this early phase but may not contribute substantially to measurable strength increases until later stages of the training programme (Loenneke et al., 2019; Reggiani & Schiaffino, 2020). Thus, while neural adaptations are crucial early on, hypertrophic adaptations likely accumulate over time and become more influential as training progresses beyond 8 weeks. This integrated view suggests that meaningful comparisons between BFR-RT and HL-RT should prioritise training durations of 8 weeks or more, to adequately capture the contribution of both neural and morphological changes to strength gains. No differences were found in the upper body muscle strength

adaptations to BFR-RT versus HLRT interventions during resistance training when the effect of intervention duration was assessed. Interestingly, when examining the upper body strength adaptations, the training duration did not affect the effectiveness of the BFR. All BFR interventions, whether lasting less or longer than 8 weeks, found that BFR-RT was effective in producing significant similar muscle strength improvements compared to HL-RT, suggesting that BFR during low load resistances training could be as effective as high load resistance training for upper body strength improvements. The contradictory findings between upper and lower body strength adaptations to BFR could be attributed to previously documented variations in strength adaptation mechanisms across different muscle groups (Candow & Chilibeck, 2005; Haizlip et al., 2015; Jung et al, 2023; Kern et al, 2001; Mansour et al., 2021; Miller et al, 1993; Plotkin et al, 2021; Schoenfeld et al, 2021; Stowers et al, 1983;

Willough, 1993). These variations can be influenced by joint complexity, muscle fibre proposition, hormonal responses, and individual factors such as genetics, sex, body composition, nutrition, and recovery practices (Candow & Chilibeck, 2005; Haizlip et al., 2015; Jung et al, 2023; Kern et al., 2001; Mansour et al, 2021; Miller et al, 1993; Plotkin et al, 2021; Roberts et al, 2020; Schoenfeld et al., 2021; Stowers et al, 1983; Willough, 1993) Training parameters such as volume, frequency, and intensity further modulate these responses and influence the dose-response relationship between muscle strength and hypertrophy (Hughes et al., 2018; Jung et al, 2023; Stowers et al., 1983; Wernbom et al, 2007; Willough, 1993) Upon closer examination of the included studies in the present meta-analysis comparing BFR-RT and HL-RT for upper body muscle strength, noticeable variation was found in training volume and 128 intensity. HL-RT protocols ranged from 60-85% 1RM, while BFR-RT ranged

from 20-55% 1RM, with differing set/rep structures and rest intervals (HL-RT: 3-4 sets, 8-15 repetitions/ and or until failure, with rest periods between sets ranging from 30 seconds to 3 minutes; BFR-RT: 3-4 sets, 830 repetitions/ and or until failure, with rest periods between sets ranging from 30 seconds to 2 minutes). Furthermore, some muscles may be inherently more responsive to resistance training due to their pre-existing usage in daily activity (Wernbom et al., 2007) For example, the soleus muscle is less responsive compared to the vastus lateralis or biceps brachii (Trappe et al., 2004) Studies comparing quadriceps and elbow flexor hypertrophy have consistently reported greater hypertrophic adaptations in the upper body (Abe et al., 2000; Housh et al, 1992; Turner et al, 1997; Welle et al., 1996; Wernbom et al, 2007) Abe et al (2000) observed that relative increases in muscle thickness were significantly higher and occurred earlier in upper-body musculature. Similarly, Wernbom

et al. (2007) quantified the daily rate of hypertrophy and found that elbow flexors responded faster (0.20% per day) than quadriceps (011% per day) These differences underscore the importance of evaluating upper and lower body BFR adaptations separately, particularly for interventions exceeding 8 weeks, in order to tailor BFR training protocols to musclespecific needs. To the authors’ knowledge, this study represents one of the first attempts to isolate and assess the impact of BFR pressure application protocols on the muscle strength and muscle mass adaptations to BFR-RT versus HL-RT. Notably, when we analysed the studies employing the protocol of an individualised percentage of the arterial occlusion pressure (100% AOP), muscle strength gains were found to be similar between BFR-RT and HL-RT. Conversely, when non-individualised or other than %AOP individualised pressure application protocols are employed, HL-RT demonstrated higher muscle strength gains to BFR-RT. These findings

align with a recent meta-analysis conducted by Chang et al. (2023) where BFR-RT, using individualised percentage pressure protocols based on the 100%AOP calculations, showed muscle strength gains comparable to those seen with HL-RT (Chang et al., 2023) However, a meta-analysis by Lixandrao et al (2018) reported significantly greater muscle strength gains with HL-RT compared to BFR-RT, irrespectively of the BFR pressure application protocols used in the studies (Lixandrão et al., 2018) These inconsistencies identified in the literature, concerning the optimal BFR pressure application protocol, may stem from the challenges associated with achieving a consistent pressure stimulus using non-individualised BFR pressure protocols. The literature underscores concern about the limited ability of nonindividualised BFR pressure application methods to deliver a consistent stimulus across diverse populations, encompassing both clinical and non-clinical (McEwen et al., 2019, McEwen & Hughes,

2020). This not only raises safety concerns due to uncertainty about the degree of blood restriction but also diminishes the efficacy of BFR-RT (McEwen et al., 2019, McEwen & Hughes, 2020). While a more accurate BFR pressure application protocol based on the percentage of AOP has been suggested, this method may not always be practical, requiring specific equipment such as 129 ultrasound or handheld doppler and expertise from the practitioner to identify an individual’s 100%AOP (Lima-Soares et al., 2022) Consequently, several studies have sought to determine relative pressures for BFR in the lower limbs based on brachial systolic blood pressure (bSBP) (Cook et al., 2010, Cook et al, 2007, Manini et al, 2011, Rossow et al, 2012, Loenneke et al, 2013). However, previous research has raised concerns about individualised BFR pressure protocols delivered from bSBP calculations, particularly emphasizing their impact on the consistency and safety of the stimulus across various

populations, especially clinical populations (McEwen et al., 2019, Loenneke et al., 2013) Despite the common practice of applying BFR pressure for the lower body based on a percentage of an individual’s bSBP (i.e 130% of bSBP) in BFR literature, limited evidence supports bSBP as an accurate estimate for BFR to the lower limbs (Loenneke et al., 2013) An investigation by Loenneke et al. (2013), utilizing datasets from their laboratory, found that bSBP did not significantly contribute to variance in prediction models for lower limb arterial occlusion pressure (Loenneke et al., 2013) Additionally, the literature emphasizes the pivotal role of cuff width, with wider cuffs requiring less pressure to occlude the limb, and smaller cuffs necessitating higher pressures for occlusion (Loenneke et al., 2013) Consequently, as one study applies lower limb pressure based on individuals' bSBP with smaller cuffs, and another study utilizes the same pressure but with wider cuffs, the

comparability of results becomes compromised. This lack of standardization in pressure settings methods, coupled with wide variations in BFR methodological diversity (including variations in BFR pressure application protocols and equipment, pressure levels, and targeted muscle groups), threatens the internal validity of past research and could contribute to the confounding and inconsistent results observed in the existing literature on BFRRT. One interesting finding of our study was that BFR pressure percentages (>50 versus ≤50% of AOP) had no significant effect on muscle strength gains between BFR-RT and HL-RT in interventions targeting the lower body musculature. This suggests that both high (>50% of AOP) and low (≤50% of AOP) pressures yielded similar advantageous muscle strength adaptations in both BFR-RT and HL-RT. These results align with a recent meta-analysis by Cerqueira et al, (2021), investigating the effects of high (≥50% AOP) versus low (<50% AOP) BFR

pressures during low load resistance training on muscle strength and muscle mass adaptations, which reported no significant differences between the high and low BFR pressures on both muscle strength and muscle mass adaptations (Cerqueira et al., 2021) However, in a recent review by Das and Patons, (2022), it was suggested that BFR pressures below 50% or exceeding 80% of AOP did not result in significant muscle strength gains when compared to HL-RT (Das and Paton, 2022). On the other hand, when BFR pressures were maintained between 50-80% of AOP during low-load resistance training, similar muscle strength adaptations were observed compared to conventional high-load resistance training (Das and Paton, 2022). While our analysis has shed light on the comparable effects of BFR-RT and HL-RT in the lower body, it is essential to recognize critical gaps in our understanding, and the need for further research. The existence of these knowledge gaps, 130 particularly regarding the optimal

percentage of AOP during BFR-RT, emphasizes the imperative for further research to unravel intricacies and refine the most effective BFR-RT percentages for diverse populations and the involved muscle groups. In contrast to the muscle strength adaptations observed in the present study, the muscle mass gains with BFR-RT were comparable to those with HL-RT, irrespective of training duration, targeted muscle group, and BFR pressure application protocols. To the authors' knowledge, this systematic review and meta-analysis are the first to explore the effects of muscle mass between BFR-RT and HL-RT in healthy adults aged 18-64 years. The aim was to examine both the sole and combined effects of confounding parameters, including training duration, targeted musculature, and BFR pressure application protocols. Our findings align with the previous literature, particularly with meta-analyses conducted by Gronfeldt et al, (2020), Fabero-Garrido et al, (2022), and Lixadrao et al., (2018)

Specifically, Gronfeldt et al, (2020), reported that BFR-RT was as effective as HL-RT in young and healthy adults (Gronfeldt et al., 2020) Similarly, Fabero-Garrido et al, (2022), found comparable hypertrophy enhancements in older adults (older than 60 years old) with BFR-RT versus HL-RT, with no additional benefit observed when applying pressures near or above the occlusion threshold (Fabero-Garrido et al., 2022) Consistent findings were also noted by Lixandrao et al, (2018), demonstrating similar hypertrophic responses between HL-RT and BFR-RT in physically active adults, regardless of factors such as the occlusion pressure, cuff width, and occlusion pressure prescription method (Lixandrão et al., 2018) However, Kong et al, (2022) found significantly greater muscle mass adaptations in HL-RT compared to BFR-RT in older adults (>50 years old) with sarcopenia (Kong et al., 2022) This observation emphasizes the need for more research on this population, investigating optimal BFR

pressure stimuli for comparable muscle mass gains to HLRT. It also underscores the importance of distinguishing populations, as evidenced by the differences in hypertrophic gains between healthy adults and those with conditions like sarcopenia and potentially dynapenia or even osteopenia when applying BFR-RT. It is essential to note that we could not explore the sole and combined effects of the upper body, training duration equal to or more than 8 weeks, and the percentage individualized BFR pressure protocol due to the absence of studies meeting the criteria for inclusion in this meta-analysis. In our study, the observed outcomes regarding muscle mass did not directly mirror the results of muscle strength gains. While strength gains are typically influenced by both neural and morphological adaptations (Staron et al., 1994; Wernbom et al, 2007), their relative contributions can vary over time. It is well documented that neural adaptations dominated the initial 6–8 weeks of training,

with hypertrophy playing a more delayed role (Enoka, 1988; Fernandes et al., 2020; Sale, 1988). However, accumulating evidence suggests that morphological changes such as hypertrophy can emerge far earlier than previously thoughtsometimes as early as two weeks into a resistance training programme (Abe et al., 2005; Mayhew et al, 1995; Rafeei, 1999; Sale et al, 2003; Seynnes et al., 2007; Staron et al, 1994; Wernbom et al, 2007) Specifically, studies by Abe et al. (2005), Sale et al (2003), and Staron et al (1994) reported increases in fibre cross-sectional 131 area (CSA) and muscle volume within 2–3 weeks of training. Likewise, Mayhew et al (1995) and Rafeei et al. (1999) documented significant hypertrophic adaptations after just 4 weeks of concentric resistance training, with further gains observed by week 6. Nevertheless, despite these early morphological adaptations, such changes do not always appear to correspond with equivalent improvements in muscle strength. This potential

dissociation suggests that early hypertrophy may not necessarily translate into measurable strength gains, which could still be predominantly influenced by neural adaptations during the initial phases of training. As such, increases in muscle size and increases in muscular strength may follow partially overlapping but not entirely identical timelines. This highlights the importance of assessing both parameters independently and in combination when evaluating the potential effectiveness of BFR-RT versus HL-RT. 132 4.6 Limitations While this meta-analysis has contributed valuable insights into the comparison of BFR-RT and HL-RT in muscle strength and muscle mass adaptations in healthy adults aged 18-64 years, particularly in reference to the specific confounding parameters that were controlled for, several limitations should be acknowledged. In the present systematic review and meta-analysis, no differentiation was made between trained and untrained individuals, although athletes

were excluded, which limits a deeper understanding of how fitness status influences the responses to the investigated resistance training modalities (Ahtiainen et al., 2003, Vikmoen et al, 2020, Lacio et al., 2021) Additionally, we did not control the effect of the resistance training protocol due to the broad methodological heterogeneity in exercise resistance training designs present in the literature. The analysis highlights challenges arising from variability in parameters such as the % 1RM (HLRT: 60-85% 1RM, BFR-RT: 20-55% 1RM), the number of sets, repetitions, and resting periods (HL-RT: 3-4 sets, 8-15 repetitions, and/or until failure, with rest periods between sets ranging from 30 seconds to 3 minutes; BFR-RT: 3-4 sets, 8-30 repetitions, and/or until failure, with rest periods between sets ranging from 30 seconds to 2 minutes). Additionally, variations in cuff width characteristics (ranging between 3 cm to 15 cm) further complicate the categorization and comparison of these

variables. This variability represents a distinct point that necessitates attention, separate from the discussion of resistance training protocols. Another limitation of this metaanalysis is that studies using different muscle size assessment methods (eg MRI, ultrasound, thigh circumference) were weighted equally in the analysis, despite known differences in measurements accuracy and validity, with MRI being considered the gold standard (Stokes et al., 2021) This variation in measurement quality may have introduced heterogeneity into the muscle mass outcomes and should be considered when interpreting the findings. Lastly, it's important to note that a limitation in the existing literature is the insufficient number of studies employing the individualized % AOP protocol to investigate muscle strength and muscle mass adaptations for durations exceeding 8 weeks in the upper body of healthy adults aged 18-64 years old. The lack of data in this specific context restricts our ability to

draw comprehensive conclusions about the effectiveness of the optimal BFR-RT protocol for the upper body muscle strength and muscle mass adaptations and compare them with the traditionally prescribed HL-RT. Future research is warranted to investigate the effects of BFR-RT on muscle strength and muscle mass adaptations in interventions lasting more than 8 weeks, particularly when applying the individualised %AOP protocol. 133 4.7 Conclusions The primary aim of this meta-analysis was to investigate and single out the impact of a series of key confounding parameters such as training duration, specific musculature trained, and different BFR pressure application protocols in the assessment of the effectiveness of BFR-RT on muscle strength and muscle mass compared to HL-RT without BFR. Moreover, we aimed to control for the effect of age, clinical conditions and training status on the evaluation of the effects of BFR-RT on muscle strength and muscle hypertrophy, by focusing exclusively

on a homogeneous cohort of healthy adults aged 18-64, excluding athletes, elderly individuals, and clinical populations. To the authors' knowledge, in the BFR literature, this is the first attempt to mitigate substantial methodological heterogeneity by considering all the aforementioned parameters. The principal insight from this systematic review and meta-analysis is that by carefully considering parameters that play a pivotal role in physiological adaptations to exercise, we can refine our understanding of the effectiveness of BFR-RT and its comparison to HL-RT. Particularly, our findings revealed several key insights. Firstly, the intervention duration and the targeted upper and lower body muscles demonstrated distinct outcomes. Interventions lasting longer than 8 weeks resulted in similar muscle strength gains between BFR-RT and HL-RT in the lower body, rendering BFR-RT an effective modality for muscle strength in healthy adults. Secondly, our findings indicate that the BFR

pressure application protocol significantly influences the muscle strength outcomes in the lower musculature. Specifically, when BFR pressure is applied via the individualized protocol based on the 100% AOP, which is a widely validated methodological approach in BFR literature, we observed comparable muscle strength adaptations in the lower body between BFR and HL-RT. This underscores the significance of personalized pressure protocols in designing effective BFR-RT intervention programs aimed at enhancing muscle strength. Finally, regarding muscle mass adaptations to BFR-RT, we found that BFR-RT led to similar levels of muscle hypertrophy compared to HL-RT, irrespective of training duration, the specific muscle group targeted, and the BFR pressure application protocols. The optimal BFR-RT protocol for muscle strength adaptations remains uncertain, particularly in the upper body, with previous studies lacking the use of percentage individualized BFR pressure protocols, and interventions

did not exceed 8 weeks. This study offers valuable insights for future research and practitioners, specifically in tailoring BFR-RT programs for healthy adults. Anticipating muscle strength adaptations after 8 weeks of BFR-RT and employing individualised percentage BFR pressure application protocols based on the %AOP, could potentially optimize lower body training adaptations. However, further research is required to ascertain the applicability of these recommendations to the upper body. Additionally, future studies should compare various BFR-RT protocols, considering exercise designs (i.e, number of sets, repetitions, duration of resting periods) for both upper and lower body in specific populations. 134 5. Meta-analysis 2: ‘The acute metabolic & perceptual responses to blood flow restriction resistance exercise versus high load resistance exercise in young healthy adults: A Systematic Review & Meta-Analysis’ 135 5.1 Abstract Introduction: Numerous studies have

demonstrated the positive effects of low load resistance exercise with blood flow restriction (BFR-RE) on muscle strength and muscle hypertrophy; however, the underlying mechanisms responsible for these musculoskeletal adaptations remain under investigation. Moreover, BFR-RE is proposed as a more tolerable alternative to high load resistance exercise (HL-RE); however, conflicting findings exist in the literature, particularly regarding perceptual responses, which necessitate further investigation. This study had two main aims: a) to assess the acute effects of BFR-RE on growth hormone (GH), insulin-like growth factor1 (IGF-1), testosterone, cortisol, lactate and b) to investigate the acute effects of BFR-RE on the ratings of perceived exertion (RPE) compared to HL-RE. Additionally, the acute effects of intermittent and continuous BFR modalities compared to HL-RE on RPE were also evaluated. Methods: A systematic search of MEDLINE, EmbaseMBASE, Web of Science and SportDiscus databases

was conducted for eligible studies. A continuous random-effects model was employed to determine effect sizes using standardised mean difference (SMD) with 95% confidence intervals (CI). Results: Among 5918 studies, 17 met the inclusion criteria Post-exercise GH, testosterone, and cortisol responses were similar between BFR-RE and HL-RE (GH; SMD=-0.221, 95%CI: 1308, -0866, I2= 8644%, Testosterone; SMD= -0021, 95%CI: -0379, 0355, I2=0%, cortisol; SMD=0.212, 95%CI: -0291, 0716, I2=2954%) However, HL-RE resulted in significantly higher post-exercise IGF-1 (SMD=-0.893, 95%CI: -1757, -0028, I2=6259%), and lactate concentrations compared to BFR-RE (SMD=-1.490, 95%CI: -2608, -03725, I2=8926%) Overall, RPE was significantly lower in BFR-RE compared to HL-RE (SMD=-0.463, 95%CI:-0822, -0105, I2=86.66%) Subgroup analysis revealed that RPE was lower in intermittent BFR-RE compared to HL-RE (SMD=-0.958, 95%CI: -1294, -0623, I2=3644%), while in continuous BFR-RE, RPE was similar to HL-RE (SMD=

-0.233, 95% CI:-0696, 023, I2=8949%) Conclusion: BFR-RE induces similar acute GH, testosterone, and cortisol responses but lower IGF-1, and lactate concentrations compared to HL-RE in young health adults. These findings suggest that BFR-RE may stimulate comparable physiological mechanisms for muscle strength and hypertrophy biomarkers as HL-RE. However, due to the limited number of studies and high overall heterogeneity observed, further research is warranted. Intermittent BFR-RE appears more tolerable compared to HL-RE as evidence by the lower RPE responses, but additional research is needed to determine optimal BFR modalities for frail individuals while maintaining the beneficial effects of HL-RE. 136 5.2 Introduction Blood flow restriction during low load resistance training has been suggested as an alternative exercise modality to the traditionally prescribed high load resistance training due to its comparable muscle mass and muscle strength adaptations (Chang et al., 2022;

Fabero-Garrido et al, 2022; Gronfeldt et al., 2020; Kong et al, 2022; Lixandrão et al, 2018) This exercise modality has been suggested to be particularly advantageous for clinical populations, individuals with musculoskeletal injuries, and older individuals with sarcopenia and osteoporosis who often cannot tolerate the high mechanical effort on the joints and bones associated with high load resistance training (Bemben et al., 2010; Chang et al, 2022; Kong et al, 2022) Nevertheless, despite the numerous evidence demonstrating the positive effects of BFR on muscle strength and muscle hypertrophy, the underlying mechanisms responsible for these musculoskeletal adaptations are still under investigation. Hypoxia, induced by the occlusion during BFR-RE, serves as the primary driver of the physiological adaptations observed in this training modality (Amani-Shalamzari et al., 2019; Hwang & Willoughby, 2019; Rossi et al., 2018) The localized reduction in oxygen availability creates a

hypoxic environment in the occluded limb, which initiates a cascade of metabolic and cellular responses aimed at maintaining homeostasis (Rossi et al., 2018) This hypoxia-driven state leads to increased metabolic stress, cellular swelling, and hormonal responses, as well as the activation of satellite cells and reactive oxygen species (ROS) production (Amani-Shalamzari et al., 2019; Hwang & Willoughby, 2019; Rossi et al., 2018) Metabolic stress, in particular, is evident from the accumulation of by-products such as lactate, which is heightened under hypoxic conditions (AmaniShalamzari et al., 2019; Hwang & Willoughby, 2019; Rossi et al, 2018) Lactate acts as a signaling molecule, stimulating the secretion of anabolic hormones like growth hormone, insulin-like growth factor-1, and testosterone (Hwang & Willoughby, 2019; Pearson & Hussain, 2015; Rossi et al., 2018). Although a large body of research has explored the role of lactate in driving the beneficial adaptations of

BFR-RE, the findings remain inconsistent (Bemben et al., 2022; Eonho et al, 2014; Freitas et al., 2020; Laurentino et al, 2022; Manini et al, 2012; Valério et al, 2018) Specifically, Laurentino et al., (2022), reported significant, similar lactate increases 15 minutes post knee extension exercise (Δ 1.7 ± 03) with both BFR (4 sets x 15 repetitions at 20% of 1 RM with 80% of BFR individualised pressure) and no BFR (4 sets x 8-10 repetitions at 80% of 1 RM) protocols (Δ: 1.4 ± 06 mmolL-1), while previous studies have reported significantly lower lactate concentrations in response to BFR compared to no-BFR resistance protocols (Bemben et al., 2010; Eonho et al., 2014; Freitas et al, 2020; Valério et al, 2018) Indicatively, Freitas et al, (2020) reported approximately a 273% higher increase in lactate concentrations from pre to post leg press exercise (4 sets x 10 repetitions at 70% of 1RM) without BFR compared to approximately a 192% increase following BFR (4 sets x 30-15-15-15

repetitions at 20% of 1 RM with 50% of individualised BFR pressure). Moreover, a study conducted by Valerio et al, (2018) comparing no 137 BFR (3 sets x 10 repetitions at 80% of 1RM) to BFR (3 sets x 15 repetitions at 20% of 1RM with 80% of individualized BFR pressure) found significantly higher lactate concentrations post leg press exercise by a 6.85-fold with no BFR compared to a 316-fold increase in lactate concentrations with BFR (Valério et al., 2018) One potential explanation for the aforementioned conflicting lactate responses following BFR resistance exercise compared to no BFR resistance protocols could be the considerable variability in the study designs employed, including various BFR pressures, exercise intensities, and number of sets and repetitions. This methodological heterogeneity underscores the need for a systematic synthesis and meta-analysis to clarify overall trends and better understand the comparative effects of BFR versus no BFR protocols on lactate

responses. Hormonal responses to BFR during resistance exercise exhibit varied outcomes, potentially due to the substantial methodological diversity observed among studies, similar to the literature on lactate. In regard to the growth hormone (GH) responses to BFR, the majority of the research studies have shown similar post exercise growth hormone (GH) increases between BFR during low load resistance exercise and no BFR during high load resistance exercise show (Dong-il et al., 2016; Eonho et al., 2014; Laurentino et al, 2022; Manini et al, 2012; Reeves et al, 2006; Sharifi et al, 2020; Tanimoto et al., 2005; Vilaça-Alves et al, 2022) Only one study, to the authors’ knowledge, by Reeves et al., (2006) has demonstrated a fourfold increase in GH following single-arm biceps curls and single-leg presses with BFR, with no changes in GH levels without BFR. Conversely, the limited number of studies on IGF-1 responses present conflicting findings, with some studies reporting significant

increases following a BFR resistance exercise protocol (Bemben et al., 2022; Dong-il et al., 2016), while other studies report unaltered responses to BFR (Karabulut et al, 2013; Laurentino et al., 2022; Manini et al, 2012; Patterson et al, 2013) Indicatively, Dong-il et al (2016) reported significant IGF-1 increases of 47.5%, 355% and 26% for no-BFR, BFR with 5% reduction of blood flow and BFR with 3% reduction of blood flow, respectively. On the contrary, Karabulut et al (2013) reported no significant changes in IGF-1 following both BFR and no BFR resistance training protocols. Inconsistences also pertain the testosterone reported outcomes in the BFR literature (Bemben et al., 2022; Karabulut et al, 2013; Laurentino et al, 2022; Reeves et al, 2006; Sharifi et al., 2020; Vilaça-Alves et al, 2022) Bemben et al (2022) compared the acute and chronic testosterone responses after 6 weeks of low intensity (20% 1RM) with BFR resistance training to traditional resistance training (70% 1RM).

Testosterone levels significantly increased at both weeks 1 and 6 for both no BFR (12.77% and 919% for weeks 1 and 6, respectively) and BFR (1120% and 5.9% for weeks 1 and 6, respectively) (Bemben et al, 2022) Conversely, Laurentino et al (2022) reported a decrease in testosterone levels by -6.25% following high load resistance exercise and -24.47% following BFR Other BFR studies found unchanged testosterone levels pre to post resistance exercise (Karabulut et al., 2013; Reeves et al, 2006; Vilaça-Alves et al, 2022) Several investigations have reported significant increases in cortisol levels following both BFR and no-BFR resistance training protocols (Eonho et al., 2014; Eslami et al, 2019; Laurentino et al, 2022). In contrast, the majority of studies have observed unchanged cortisol levels from pre- to 138 post-exercise across both protocols (Bemben et al., 2022; Patterson et al, 2013; Reeves et al, 2006; Vilaça-Alves et al., 2022) Indicatively, Eonho et al (2014) and

Laurentino et al (2022) found significant post-exercise cortisol increases in both no BFR and BFR resistance exercise conditions, with no significant differences between the two modalities (12.7% for no BFR and 232% for BFR, and 34.2% for no BFR and 204% for BFR, respectively) Further research is needed to explore the effects of BFR during low load resistance exercise on key hormonal responses related to muscle hypertrophy and strength adaptations more thoroughly. One of the limiting factors in the use of BFR is its potential negative effect on perception of effort and pain. Although BFR-RE has been introduced as an alternative modality to HL-RE, particularly due to the lower loads applied, the effects of BFR on perceptual variables such as RPE and pain remain inconsistent in the literature. Several studies have reported higher RPE responses in BFR compared to no-BFR conditions (Dankel et al., 2019; Suga et al, 2021), while others have found the opposite, with higher RPE reported in

no-BFR compared to BFR (Miller et al., 2020; Neto et al., 2017) Additionally, some studies have shown that RPE was elevated when higher pressures were applied during BFR compared to no-BFR conditions (Bell et al., 2018; Brandner et al, 2017) Indicatively, a study conducted by Dankel et al., (2019) found that the RPE was significantly higher in the BFR condition (183% increase from first to last set) compared to high load resistance exercise without BFR (167% increase from first to last set). In contrast another study, conducted by De Araujo et al., (2016), reported higher RPE responses throughout the five sets in the no BFR compared to the BFR condition. Additionally, a study by Bell et al, (2018), found higher RPE responses to BFR compared to the no BFR condition only when the pressure applied was high (80% of individualised pressure) and lower when the pressure applied was low (40% of individualised pressure). This variation may be due to significant methodological differences in

exercise prescription, such as BFR loads (i.e 15% to 40% of 1RM), number of sets (ie 3 to 4), repetitions (6-30 or until failure), BFR pressure (i.e 25% to 80% of arterial occlusion pressure), as well as differences in targeted musculature (upper versus lower body) (Aniceto et al., 2021; Bell et al, 2018; Brandner & Warmington, 2017; Dankel et al., 2019; de Araújo et al, 2017; Eonho et al, 2014; Freitas et al., 2019; Lixandrao et al, 2019; Miller et al, 2020; Neto et al, 2017) To optimize the comfort, tolerability, and potentially the adherence to BFR-RE protocols, researchers have introduced the intermittent BFR-RE modality, where blood flow is allowed during rest periods by deflating the cuff or releasing the elastic band (Brandner & Warmington, 2017; Freitas et al., 2019; Neto et al, 2017) Emerging evidence suggests that intermittent BFR may be more tolerable than traditional continuous BFR, which keeps the cuffs inflated throughout the entire exercise session, leading to

greater discomfort and higher RPE (Freitas et al., 2019; Neto et al, 2017). For instance, Fitschen et al (2014) and Freitas et al (2019) found that continuous BFR resulted in significantly higher pain scores in the later sets of low-load resistance exercises compared to intermittent BFR. Similarly, Yasuda et al (2013) documented higher RPE during continuous BFR in the final sets compared to intermittent BFR. On the other hand, a recent meta139 analysis reported no significant differences in perceptual responses between the two BFR modalities (Sinclair et al., 2022), and only one study -to the authors’ knowledge- by Brandner et al (2017) even reported higher RPE in intermittent BFR compared to continuous BFR. Overall, while the evidence indicates that intermittent BFR tends to be more tolerable, the findings are inconsistent, highlighting the need for further research to establish the most effective BFR protocol. Given that optimizing BFR-RE protocols is crucial for improving

adherence and long-term outcomes, more indepth investigations are needed to determine the most effective intermittent BFR configurations. The primary purpose of this meta-analysis was to investigate systematically the acute effects of BFR-RE on key metabolic responses related to muscle protein synthesis, namely lactate, GH, IGF1, testosterone, and cortisol and to compare them to the traditional HL-RE. A secondary objective was to examine the ratings of perceived exertion in response to BFR-RE and HL-RE, and to further compare the acute RPE responses between the continuous and intermittent BFR-RE protocols versus HL-RE to evaluate tolerability. The study focused exclusively on young, healthy adults aged 18-35 years, to control and minimize variability in the metabolic and perceptual responses potentially influenced by ageing and/or clinical conditions. It was hypothesized that the acute post exercise responses of GH, IGF-1, testosterone, cortisol, and lactate would be similar between

BFRRE and HL-RE. Additionally, it was hypothesized that BFR-RE would elicit similar RPE compared to HL-RE. 140 5.3 Methodology The design of the present study adheres to the PRISMA guidelines (Section 3.1) 5.31 Search Strategy & Study Selection The studies included in the present meta-analysis were identified by searching four electronic databases from inception to 1st of February 2023: MEDLINE via PubMed, EmbaseMBASE via Ovid, Web of Science, and SportDiscus via EBSCO. No restrictions were made for language and publication year. The following search terms were included to search in all the databases: “resistance training”, “exercise”, “weightlifting”, “multi-joint resistance exercise”, “hypertrophy”, “muscle strength”, “intermittent pneumatic compression devices”, “blood flow restriction”, “blood flow occlusion”, “occluded blood flow”, “restricted blood flow”, “vascular occlusion”, “vascular restriction”, and “Kaatsu”,

“hormonal responses”, “ratings of perceived exertion”, “perceptual responses”, “growth changes”, “growth factor changes”, “lactate”, “cortisol”, “testosterone”. See Appendix 16 for full search string. 5.32 Eligibility Criteria A PICOS (participants, exercise type, comparators, study outcomes, and study design) format was used for the inclusion and exclusion criteria to rate the studies for eligibility (Table 5.1) (Moher et al., 2009) Table 5.1 Selection Criteria Category Inclusion Criteria Population Healthy adults, ≥18 and ≤35 years old Exercise type Low-load resistance exercise with BFR* Comparators Study outcomes Study design Exclusion Criteria Elderly, Clinical population, Athletes Absence of resistance exercise or BFR combined with electrical stimulation and vibration training Absence of high-load resistance exercise without BFR High-Load resistance exercise without BFR See 2.3 Type of Outcome Measures Acute random order trials Or Acute

random order cross-over trials Chronic non-random order trials or Case studies *BFR; Blood flow restriction 141 5.33 Type of Outcome Measures The included studies investigating growth hormone (GH), insulin-like growth factor-1 (IGF-1), testosterone, cortisol, lactate concentrations, and ratings of perceived exertion followed acute randomized order design protocols. The groups performed high-intensity resistance exercise (60%90% of 1-RM) and low-intensity resistance exercise (20%-30% of 1-RM) with BFR Furthermore, the same exercise protocol was maintained between conditions (e.g, leg press, handgrip, biceps, etc.), both with and without BFR The a priori primary outcome measures encompassed changes in GH, IGF-1, testosterone, cortisol, and lactate, measured through venous blood sampling analysis or/and capillary blood sampling for lactate. The secondary outcome measures included ratings of perceived exertion assessed via perceptual response assessments (e.g, Borg Scale, OMNI

scale) Studies were required to report at least one of the following: growth hormone, insulin-like growth factor-1, testosterone, cortisol, lactate, or ratings of perceived exertion. 5.34 Data Selection Results from the search strategies were imported into EndNote (EndNote X9.31, Clarivate Analytics, USA) and Microsoft Excel (Excel 365, Microsoft Corporation, USA) and duplicates were removed by the first author (MKN). The results from the search were evaluated by two independent reviewers (MKN and IG) using a successive three-step screening procedure: (a) title screening, (b) abstract screening, and (c) full-text reading. The screeners were not blinded to either the journal titles or to the study authors/affiliations and met to discuss their selections and reconciled any discrepancies by consensus. When outcome data of interest were not readily accessible in the published articles, attempts were made to retrieve the missing information by contacting the corresponding authors via

email. An initial email was sent, followed by two further reminders over the course of one month if no reply was received. If the authors did not respond after these three attempts, the study was excluded from the meta-analysis due to insufficient data availability. The exclusion criteria were coded determined by one or more of the following: (i) inappropriate comparison(s) (n=58), (ii) congress presentations and posters, thesis and abstracts, (n=23), (iii) other than English language (n=3), (iv) review papers (n=5), (v) inappropriate population (n=6), (vi) inappropriate outcome(s) and study designs (n=30), (vii) chronic intervention designs (n=10). More details of the extracted data process are available in Figure 5.1 For the assessment of quality and risk of bias please see Chapter 3. 142 5.35 Assessment of Quality and Risk of Bias The risk of bias was assessed for the studies included in the present systematic review and metaanalysis following the PRISMA 2020 guidelines

(Section 3.11) 5.36 Statistical Analyses Statistical analyses on the global effects of BFR-RE versus HL-RE on GH, IGF-1, cortisol, testosterone, lactate and RPE were calculated (Section 3.12) Exploratory meta-analysis was also conducted for RPE measurements stratified by the type of the BFR modality which involved the continuous BFR versus intermittent BFR. 143 5.4 Results 5.41 Search Results & Studies characteristics The flow chart presented in Fig. 1 depicts the search process used for the identification of the studies that have been included in this systematic review and meta-analysis. Our systematic literature search returned 5918 studies (PubMed; 1142, SPORTDiscus; 987, Web of Science; 1803 and Embase; 1986). EndNote20 and Microsoft Excel 365 identified 2012 and 313 duplicates respectively. The first and the second authors read the titles and the abstracts and after consensus they decided to exclude 3361 studies. The remaining 152 studies were fully read and 17 were

included for the present systematic review and meta-analysis. The risk of bias for randomised controlled trials is summarized in Table 5.2 Eight studies investigating the acute effects of BFR-RE versus HL-RE on metabolic responses were included in the present systematic review and meta-analysis. Specifically, five studies investigated and compared the acute effects following BFR-RE versus HL-RE on GH, three studies on IGF-1, four studies on cortisol, four studies on testosterone and six studies on lactate (Table 5.3 & Table 5.4) Finally, ten studies were also included in the present systematic review and metaanalysis (n=160 participants, experimental conditions = 26) investigating the acute effects on ratings of perceived exertion between HL-RE and BFR-RE (Table 5.3 & Table 55) 144 Figure 5.1 Flow-chart depicts the search process 145 146 5.42 Metabolic Responses There were no significant differences in GH levels from pre to post exercise between BFR-RE and HL-RE

(SMD = -0.221, p =0690, 95% CI: -1308, -0866 and I2 = 8644%, df=5, p<0001) (Figure 5.2) Figure 5.2 Effects of high load resistance exercise (HL-RE) versus low load resistance exercise with blood flow restriction (BFR-RE) on Growth Hormone concentrations. On the contrary, significant differences in IGF-1 concentrations from pre to post exercise were observed between the two conditions, favouring HL-RE (SMD= -0.893, p=0043, 95% CI: -1757, -0.028, I2 = 6259%, df=5347, p=0069) (Figure 53) Figure 5.3 Effects of high load resistance exercise (HL-RE) versus low load resistance exercise with blood flow restriction (BFR-RE) on Insulin Growth Factor-1 concentrations. 147 Additionally, testosterone and cortisol levels did not show significant differences between BFRRE and HL-RE (SMD= -0.021, p =0948, 95% CI: -0379, 0355, I2 = 0%, df=5, p=0922 and SMD= 0.212, p =0408, 95% CI: -0291, 0716 and I2 = 2954%, df=3, p=0235 for testosterone and cortisol respectively) (Figure 5.4 & Figure

55) Figure 5.4 Effects of high load resistance exercise (HL-RE) versus low load resistance exercise with blood flow restriction (BFR-RE) on testosterone concentrations. Figure 5.5 Effects of high load resistance exercise (HL-RE) versus low load resistance exercise with blood flow restriction (BFR-RE) on Cortisol concentrations. Finally, lactate concentrations were significantly different between BFR-RE and HL-RE, favouring the HL-RE condition (SMD = -1.490, p =0009, 95% CI: -2608, -0373, I2 = 8926%, df=6, p<0.001) (Figure 56) 148 Figure 5.6 Effects of high load resistance exercise (HL-RE) versus low load resistance exercise with blood flow restriction (BFR-RE) on lactate concentrations. 5.43 Ratings of Perceived Exertion The overall effect size indicated a significant difference between BFR-RE and HL-RE in RPE values, with RPE being significantly higher in HL-RE compared to BFR-RE (SMD = -0.463, p =0.011, 95% CI: -0822, -0105, and I2 = 8666%, df=37, p<0001) (Figure 7) In

the final exploratory sub-group meta-analysis on the effect of the BFR modalities (continuous pressure versus intermittent pressure), RPE responses were significantly lower in the intermittent BFR-RE modality compared to HL-RE (SMD= -0.958, p<0001, 95% CI: -1294, -0623, I2= 3644%, p=0108) On the contrary, the effect size showed no significant difference in RPE values between continuous BFR-RE and HL-RE (SMD= -0.233, p= 0323, 95% CI: -0696, 0230 and I2= 8949%, p<0001) (Figure 5.7) 149 150 151 Figure 5.7 Effects of high load resistance exercise (HL-RE) versus low load resistance exercise with blood flow restriction (BFR-RE) on ratings of perceived exertion (RPE) on either a) continuous Pressure or b) Intermittent Pressure. 152 5.5 Discussion The exploration and understanding of the physiological and perceptual effects of BFR during lowload resistance exercise offer promising insights into its potential as an alternative modality for individuals unable to follow a

high-load resistance training regime. However, research in this area remains limited, highlighting the need for further investigation into the pivotal role of metabolic stress and adaptations in activating muscle hypertrophy cellular pathways (Fabero-Garrido et al., 2022; Gronfeldt et al., 2020; Hwang & Willoughby, 2019; Pearson & Hussain, 2015; Rossi et al, 2018). This involves the local hypoxia induced by BFR-RE, which drives the accumulation of lactate and activation of hormonal responses crucial for muscle protein synthesis (Hwang & Willoughby, 2019; Loenneke et al., 2012; Pearson & Hussain, 2015; Rossi et al, 2018) However, the literature in this research area is limited, with a small number of studies comparing acute metabolic responses between BFR-RE and HL-RE, and inconsistent findings (Abe et al., 2005; Bemben et al., 2022; Dong-il et al, 2016; Eonho et al, 2014; Karabulut et al, 2013; Laurentino et al., 2022; Manini et al, 2012; Patterson et al, 2013; Reeves

et al, 2006; Rossi et al, 2018; Sharifi et al., 2020; Takano et al, 2005; Takarada et al, 2000; Vilaça-Alves et al, 2022) Hence, the primary purpose of the present systematic review and meta-analysis was to investigate and compare the acute effects of metabolic responses crucial for muscle protein synthesis between BFR-RE and HL-RE in only young health adults aged 18-35 years old, excluding athletic, elderly and clinical populations to minimise potential errors arising from age, disease, and athletic status. A novel finding in this meta-analysis was that GH, testosterone, and cortisol concentrations following exercise were comparable between BFR-RE and HL-RE, supporting the initial hypothesis. However, post-exercise levels of IGF-1 and lactate differed between conditions, favouring HL-RE, thereby rejecting the null hypothesis and demonstrating the need for future research to better understand these contradictory physiological responses. The secondary purpose of this study was to

investigate and compare RPE during BFR-RE versus HL-RE, and to further explore potential differences in RPE findings between continuous BFR-RE versus HL-RE and intermittent BFR-RE versus HL-RE. The overall RPE was significantly lower in BFR-RE (both continuous and intermittent) compared to HL-RE, thereby rejecting the null hypothesis. A key finding in the exploratory analysis revealed no significant RPE differences between the continuous BFR-RE and HL-RE, whereas RPE was significantly lower in intermittent BFR-RE compared to HL-RE. To authors’ knowledge, this is the first systematic review and meta-analysis investigating the acute metabolic responses, crucial for muscle protein synthesis, following BFR-RE compared to HL-RE, in young, healthy adults aged 18-35 years. One of the main findings of the present study was the similar, post exercise increases in GH concentrations between BFR-RE and HL-RE, indicating the potential for BFR during resistance exercise as an alternative modality.

This result aligns with the majority of the included studies that reported similar GH increases between BFR and no BFR 153 conditions (Eonho et al., 2014; Laurentino et al, 2022; Sharifi et al, 2020; Vilaça-Alves et al, 2022), with the exception of one study showing higher GH concentrations after BFR-RE compared to HL-RE (Manini et al., 2012) The observed similarities in metabolic responses between BFR-RE and no BFR resistance exercises have been suggested to be linked to the localized hypoxia induced by blood flow restriction, initiating anaerobic metabolism and leading to elevated lactate production (Amani-Shalamzari et al., 2019; Gladden, 2004; Hwang & Willoughby, 2019; Rossi et al, 2018) Research indicates that the reduction in oxygen availability during low-load BFR exercise induces metabolic stress, which is crucial for stimulating hormone release, including GH (AmaniShalamzari et al., 2019; Gladden, 2004; Hwang & Willoughby, 2019; Rossi et al, 2018; Schoenfeld,

2013). Studies also suggest a dose-response relationship, where the extent of GH release increases with greater metabolic stress, though a critical threshold may also exist (Fahs et al., 2012; Goto et al., 2005; Kraemer & Ratamess, 2005; Takarada et al, 2000) Research indicates that this relationship is evident in various exercise regimens, including BFR exercise, where reduced oxygen availability induces further metabolic stress (Fahs et al., 2012; Goto et al, 2005; Kraemer & Ratamess, 2005; Takarada et al., 2000) However, further investigation is needed to delineate the precise mechanisms involved in this dose-response relationship, particularly concerning metabolic stress during BFR. Additionally, local acidosis, resulting from BFR induced hypoxia, and cell swelling due to restricted venous blood flow are also proposed mechanisms influencing hormonal responses (Amani-Shalamzari et al., 2019; Freitas et al, 2017; Gladden, 2004; Hwang & Willoughby, 2019; Loenneke et al.,

2012; Miller et al, 2021; Rossi et al, 2018; Schoenfeld, 2013) Despite these proposed mechanisms, the synergistic interplay remains unclear, emphasizing the need for ongoing research to fully understand the metabolic responses to BFR-RE under different dose-response stimuli. Furthermore, more research is needed to assess the acute GH responses following BFR-RE versus HL-RE with homogeneous methodological approaches, acknowledging the high heterogeneity (I2 = 86.44%) observed in the GH study outcomes in the present study The varied outcomes in the included studies could be attributed to factors such as varied blood sample collection timing, diverse exercise protocols, and methodological differences in BFR equipment and pressure application protocols being applied (Eonho et al., 2014; Khalid et al, 2020; Kraemer & Ratamess, 2005; Laurentino et al., 2022; Manini et al, 2012; Sharifi et al, 2020; Vilaça-Alves et al., 2022; Wackerhage et al, 2019) The findings of the present

meta-analysis revealed no significant effect of BFR-RE on IGF-1 concentrations, in contrast to its pronounced impact on GH levels following low-load resistance exercise. This result aligns with the majority of included studies, which reported unchanged IGF-1 levels post-exercise in BFR-RE compared to HL-RE (Laurentino et al., 2022; Manini et al, 2012) However, one study observed significantly higher IGF-1 concentrations post-HL-RE than BFR-RE (Bemben et al., 2022), suggesting that the lack of a consistent effect might stem from conflicting outcomes and the small number of studies available. The limited number of studies included in the 154 present meta-analysis highlights the need for further research to elucidate the acute effect of BFR on IGF-1 responses. GH, produced by the pituitary gland, is acknowledged for its role in growth, cell regeneration, and recovery processes, elevated in response to resistance exercise (Kraemer et al., 2020) One mechanism involves the stimulation of

the liver and other tissues to produce IGF-1 (Kraemer et al., 2020) However, the translation of increased GH levels into higher IGF-1 levels has been proposed to be subjected to individuals’ variations influenced by genetics, hormonal regulation, dietary habits, age, sleep patterns, overall health status, and the nature of the exercise (Khalid et al., 2020; Kraemer et al, 2020; Sharma et al, 2020) The heterogeneity observed in IGF1 outcomes was high (I2=6259%), similar to the GH findings mentioned above As discussed previously, this heterogeneity likely stem from various factors such as differences in exercise protocols, blood sample collection timing, and methodological variations in BFR equipment and pressure application (Eonho et al., 2014; Khalid et al, 2020; Kraemer & Ratamess, 2005; Laurentino et al., 2022; Manini et al, 2012; Sharifi et al, 2020; Vilaça-Alves et al, 2022; Wackerhage et al., 2019) While these findings contribute valuable insights, the limited number of

studies emphasizes the necessity for more research to establish a comprehensive understanding of the interplay between BFR-RE, HL-RE, and IGF-1 responses. Addressing these limitations and employing standardized methodologies will enhance the reliability and applicability of future studies in this area and lead to a better understanding of the underlying physiology. A novel finding of the present meta-analysis was the similar effect of BFR-RE and HL-RE on testosterone levels. Specifically, three out of four studies reported no significant changes in testosterone concentrations from pre- to post-exercise in both BFR-RE and HL-RE (Laurentino et al., 2022; Sharifi et al, 2020; Vilaça-Alves et al, 2022), while Bemben et al (2022) observed significantly higher post-exercise testosterone levels in the HL-RE condition. Several factors might explain this discrepancy. Firstly, the incremental cuff pressure protocol employed in Bemben et al's study could have played a role. In their

protocol, cuff pressure was gradually increased from 40–60 mmHg to a final training pressure of 160 mmHg, with intermittent inflation (30 seconds) and deflation (10 seconds) intervals before exercise commenced. This warm-up phase may have triggered physiological mechanisms promoting testosterone release, potentially through enhanced vascular dynamics and localized hypoxia. In contrast, the other studies used distinct pressure-setting protocols that may not have elicited the same preparatory effects. For instance, Sharifi et al (2020) applied a wide range of pressures (110–230 mmHg), while Vilaça-Alves et al. (2022) used a pressure equivalent to 120% of resting systolic blood pressure, and Laurentino et al. (2022) employed a high pressure set at 80% of arterial occlusion pressure (AOP). Nevertheless, despite testosterone’s recognized role in muscle hypertrophy and strength enhancements, the intricate relationship between resistance training intensity, volume, and the effect of

BFR and local hypoxia on testosterone levels remains a subject of ongoing research and scientific inquiry (Vingren et al., 2010). Additional research is needed to comprehensively explore testosterone levels following BFR-RE versus the traditionally prescribed for muscle strength and muscle hypertrophy, HL-RE. 155 The present meta-analysis showed similar effects of BFR-RE and HL-RE on cortisol concentrations in young healthy adults. Specifically, Bemben et al, (2022), Laurentino et al, (2022), and Vilaca-Alves et al., (2022) reported unaltered cortisol concentrations from to pre to post exercise in both exercise modalities (Bemben et al., 2022; Laurentino et al, 2022; Vilaça-Alves et al., 2022), however, Eonho et al, (2014) presented significant, similar cortisol increases postexercise in both BFR-RE and HL-RE While cortisol is commonly associated with stress and its catabolic consequences, its crucial to acknowledge its pivotal role in the body’s response to resistance exercise

and muscle development (Kraemer et al., 2020, Kraemer & Ratamess, 2005) Post-resistance exercise cortisol elevation has been correlated with enhanced muscle growth and protein synthesis (Kraemer et al., 2020; Kraemer & Ratamess, 2005; O'Leary & Hackney, 2014) However, cortisol secretion in response to resistance exercise arises also from other complex mechanisms such as inflammation regulation, tissue remodelling, hormonal equilibrium, gluconeogenesis regulation, and adaptations (Kraemer & Ratamess, 2005; O'Leary & Hackney, 2014). These intricate physiological factors may contribute to variations in cortisol responses to exercise in various studies (Eonho et al., 2014; Laurentino et al, 2022) Most importantly, the studies on cortisol responses to BFR-RE and HL-RE are limited, emphasizing the need for further research to identify the underlying cortisol physiological mechanism specific to BFR-RE and local hypoxia. Additionally, more comprehensive

investigations are required to determine the optimal BFR modality and adaptations. To the authors’ knowledge, this systematic review and meta-analysis is the first to investigate the acute effects of BFR-RE versus HL-RE on lactate concentrations in young, healthy adults. A key finding revealed that lactate levels favoured HL-RE over BFR-RE, potentially suggesting that HLRE could elicit greater metabolic stress, as indicated by higher lactate accumulation. However, while some of the included studies demonstrated higher lactate levels in HL-RE compared to BFRRE, others did not find a significant difference. Specifically, three out of six studies reported no significant differences in post exercise lactate increases between BFR-RE and HL-RE (Bemben et al., 2022; Eohno et al, 2014; Laurentino et al, 2022), whereas the remaining three studies observed significantly higher lactate concentrations favouring HL-RE (Freitas et al., 2020; Manini et al, 2012; Valerio et al., 2018) Lactate, a

metabolic byproduct arising from anaerobic processes during intense physical activity, tends to accumulate within muscles (Siegler & Robergs, 2005). Formerly, considered a fatigue-associated waste product, contemporary research has demonstrated a positive, broader role for lactate, including its potential impact on muscle protein synthesis (Lee, 2021). Recent investigations portray lactate as a signalling molecule influencing diverse cellular reactions, such as gene expression, energy metabolism and muscle protein synthesis (Brooks, 2018; Ferguson et al., 2018; Lee, 2021) Although the precise mechanisms underpinning lactate’s signalling role are intricate and not fully comprehended, it is suggested to contribute to metabolic adaptations and exercise-induced responses (Brooks, 2018; Ferguson et al., 2018; Lee, 2021) A prevailing hypothesis suggests that lactate might engage mechanistic target of rapamycin complex 1 156 (mTORC1) signalling, a pivotal regulator of muscle protein

synthesis (Brooks, 2018; Ferguson et al., 2018; Lee, 2021; Shirai et al, 2021) This could occur via lactate’s influence on energy status, cellular redox equilibrium, and nutrient availability (Shirai et al., 2021) It is essential to acknowledge that while the association between lactate and mTOR signalling is of interest, further investigation is required to clarify its role in exercise-induced adaptations. However, lactate responses to exercise can be dependent on the exercise stimuli such intensity, duration, resting intervals, BFR equipment, application of BFR pressures, and the exercise protocols employed in BFR-RE versus HL-RE (Jessee et al., 2016; Khalid et al, 2020; Kraemer & Ratamess, 2005; Loenneke et al., 2012; McEwen et al, 2019; Murray et al, 2021; Patterson et al, 2019; Wackerhage et al., 2019) Additionally, the method of lactate sampling, including the timing of sample collection, the site of blood draw (i.e arterial versus venous), and the equipment used, can also

influence the observed lactate concentrations (Bonaventura, 2015; Goodwin et al., 2007; Robergs et al., 1990) There is a notable variability in the included studies investigating the effects BFR-RE versus HL-RE on lactate post exercise concentrations, and that could potentially explain the high heterogeneity observed (I2 = 89.26%) Hence, more research studies are needed to control the methodological heterogeneity in order to accurately assess the effect of BFR on lactate levels and the subsequent metabolic pathways. An interesting finding of the present meta-analysis showed that the overall RPE was significantly lower in the BFR-RE (including continuous and intermittent BFR modalities) compared to HL-RE in young healthy adults aged 18-35 years old (SMD = -0.46, p=001) These results did not align with a recent meta-analysis conducted by de Queiros et al. (2023), which reported no significant differences in the overall RPE between BFR-RE and HL-RE. However, their sensitivity analyses

indicated that RPE was higher in the HL-RE compared to BFR-RE under fixed repetition schemes, while discomfort was greater in the BR-RE when sets were performed to voluntary failure (SMD = 0.95, p<001) The discrepancies in RPE findings between the present meta-analysis and that of de Queiros et al., (2023) may be attributed to heterogeneity in exercise designs across studies Variations in protocols, such as repetition schemes, training intensity, and set configurations, likely contribute to these differences in perceptual responses. Moreover, the broader demographic diversity in de Queiros et al.'s analyses, which included both healthy and clinical populations like hypertensive individuals, young and elderly participants, might have influenced the RPE outcomes differently than in included studies focusing exclusively on young, healthy adults. To further address and control the methodological heterogeneity present in the BFR literature, an exploratory analysis was conducted

comparing RPE responses between continuous BFR-RE and intermittent BFR-RE against HL-RE. This analysis revealed that RPE was similar between continuous BFR-RE and HL-RE, whereas intermittent BFR-RE resulted in significantly lower RPE compared to HL-RE. This suggests that while continuous BFR-RE may offer similar perceived exertion to HL-RE, intermittent BFR-RE could be more tolerable, highlighting the need to explore 157 different BFR protocols to better understand their effects on exercise perception. These findings diverge from a recent meta-analysis conducted by Sinclair et al., (2022), which focused solely on comparing intermittent versus continuous BFR resistance exercise without including HL-RE. Sinclair and colleagues reported that intermittent cuff deflations during resting periods did not improve tolerance compared to continuous BFR-RE. This divergence in findings underscores the complexity of evaluating BFR-RE and suggests that understanding the hypoalgesic effects of

BFRRE is also crucial. The hypoalgesic effect of BFR may be attributed to several mechanisms, including the modulation of neurophysiological responses, which may influence pain perception and transmission (Cervini et al., 2023; Hughes et al, 2021, Hughes & Patterson, 2019; Hughes & Patterson, 2020; Karanasios et al., 2023; Li et al, 2021; Song et al, 2021) Additionally, BFR has been suggested to induce the release of endogenous opioids, which act as natural pain-relieving substances in the body (Hughes et al., 2021, Hughes & Patterson, 2020) and contribute to the reduction of inflammatory markers and promote the release of growth factors, thereby creating a favourable environment for pain relief and tissue pair (Rossi et al., 2018) The variability in findings likely reflects methodological heterogeneity in BFR research, emphasizing the need for standardized protocols to clarify these complex mechanisms (Aniceto et al., 2021; Bell et al, 2018; Brandner & Warmington,

2017; Dankel et al., 2019; de Araújo et al, 2017; Eonho et al, 2014; Freitas et al., 2019; Lixandrao et al, 2019; Miller et al, 2020; Neto et al, 2017) This variability could contribute to the high overall heterogeneity observed in the RPE in the present meta-analysis and the different BFR protocols (I2 = 86.66%) Given these discrepancies and the complexity of the underlying physiology regarding the hypoalgesic effect of BFR-RE, more research is needed to comprehensively identify the optimal BFR exercise protocols. Such research should aim to control for methodological variations and assess their impact on perceived exertion and exercise tolerance, ensuring that the musculoskeletal benefits of BFR-RE are not compromised. 158 5.6 Limitations Despite the novelty of this systematic review and meta-analysis focusing on acute hormonal and metabolic responses to BFR-RE in young, healthy adults, several limitations should be acknowledged. Firstly, although GH and IGF-1 are commonly

used markers of anabolic responses, there is growing evidence suggesting that acute post-exercise elevations in systemic anabolic hormones do not necessarily predict or drive long-term hypertrophy or strength gains. Multiple studies (eg, West et al, 2009; 2010; 2012; Morton et al., 2016; Wilkinson et al, 2006) have shown that increases in hormones such as GH, testosterone, and cortisol measured immediately post-exercise are weakly or not at all associated with changes in muscle protein synthesis or muscle growth following training. These findings suggest that local muscular factors and intracellular signalling pathways may play a more significant role than systemic hormonal responses. However, other studies have reported associations between acute hormonal responses and muscle protein synthesis or hypertrophy, indicating that the relationship may be context-dependent (Fryburg et al., 1993; Gharahdaghi et al, 2020) While this metaanalysis did not investigate long-term outcomes, its

primary aim was to evaluate whether the acute metabolic and hormonal responses to BFR-RE are comparable to those of HL-RE. As such, this analysis offers a foundation for understanding how BFR-RE challenges the body acutely, which may guide future research exploring chronic adaptations. Second, the exclusive focus on acute studies is a notable limitation. However, given the currently limited number of high-quality chronic BFR-RE studies, it was not feasible to include them in this review. Importantly, acute studies offer initial and critical insights into the immediate metabolic and perceptual responses to BFR-RE, which are necessary before long-term effects can be meaningfully investigated. Third, considerable methodological heterogeneity among the included studies presented challenges for interpretation. Variations in training protocolsincluding exercise intensities, number of sets and repetitions, timing of sample collection, inter-set rest periods, and differences in BFR application

methods and occlusion pressuresintroduced substantial variability. Although efforts were made to control for some of these variables, full standardization was not possible due to the limited number of eligible studies and the diversity in experimental designs. Lastly, the relatively small number of studies available for inclusion underscores the need for further research in this area, both acute and chronic. While the current meta-analysis consolidates available data to provide an important preliminary overview, future studies employing more standardized methodologies are essential to clarify the acute responses to BFR-RE and to determine their relevance for long-term training outcomes. 159 5.7 Conclusions In conclusion, this systematic review and meta-analysis represents the first comprehensive exploration of acute metabolic responses to BFR-RE compared to HL-RE exclusively in young, healthy adults aged 18-35 years. Focusing on this specific age group allowed for greater

homogeneity across studies and may be particularly important when examining acute hormonal responses, as hormones such as GH, IGF-1, testosterone, and cortisol can vary substantially with age (Arazi et al., 2013) A key finding was that post-exercise GH levels increased comparably between BFR-RE and HL-RE, suggesting similar anabolic stimulation, but with a lower RPE during BFR-RE. This indicates that BFR-RE may offer comparable benefits to high-load resistance exercise while reducing the perception of effort. Notably, this study also provides novel insights into the effect of intermittent BFR-RE on RPE. It was found that intermittent BFR-RE led to significantly lower RPE compared to HL-RE, suggesting potential advantages in exercise tolerability. In contrast, continuous BFR-RE produced similar RPE responses to HL-RE, highlighting potential benefits of the intermittent modality in enhancing adherence and comfort during resistance training. However, the results for testosterone and

cortisol concentrations were inconclusive. Additionally, distinct contrasts were observed in post-exercise IGF-1 and lactate levels, both of which favoured HL-RE over BFR-RE, underscoring the need for further investigation to understand these differences and their implications for training adaptations. The inconsistent findings on lactate concentrations also emphasize the need for more research to clarify the underlying metabolic mechanisms. Overall, while current evidence suggests that BFR-RE elicits comparable metabolic responses to HLRE, this study highlights the importance of optimizing BFR-RE protocols, particularly by investigating the benefits of intermittent versus continuous BFR. Furthermore, a more detailed exploration of perceptual responses such as RPE is crucial for understanding exercise tolerability and adherence across diverse populations. 160 6. Pilot Study: ‘The acute effects of a new progressive intermittent BFR protocol on the perceptual, lactate, mood

& cognitive responses to resistance exercise’ 161 6.1 Abstract Introduction: Blood flow restriction (BFR) during low-load resistance exercise has demonstrated promise in enhancing muscle strength and hypertrophy, particularly in frail populations who cannot tolerate traditionally prescribed high-load resistance exercise. However, conflicting findings regarding the tolerability of the continuous BFR (c-BFR) during low-load resistance exercise exist, while the newer intermittent BFR (i-BFR) has shown some promising results, with lower perceptions of effort observed. This pilot study aims to compare the effects of a new progressively increased pressure i-BFR to c-BFR on perceptual responses, mood, cognitive function and blood lactate concentration [La], in young healthy adults. Methods: Fourteen healthy males and females (age: 231 ± 48 years, BMI: 236 ± 2.3) performed two resistance training protocols in random order with i-BFR and c-BFR During the experimental sessions,

participants performed four single-leg press sets of 30-15-15-15 repetitions, separated by 30-second resting periods at 30% of 1RM. In the c-BFR condition, pressure was continuous at 50% of individualized arterial blood flow (%AOP) throughout the exercise session. In the i-BFR condition, pressure incrementally increased from 30mmHg below each participant’s individual 50% AOP, increasing by 10mmHg during each set until the target 50% AOP was reached in the last set. During the resting periods, the BFR bands were completely deflated in the i-BFR. Capillary [La], profile of mood states (POMS) questionnaire, and Stroop test were measured before (Pre) and after exercise (Post). Ratings of perceived exertion (RPE) and pain were measured at the end of each set Results: RPE was significantly lower in i-BFR compared to c-BFR in Set 2 (p=0.005) Set 3 (p=0006) and Set 4 (p=0.004) with pain also being significantly lower in the i-BFR compared to c-BFR in Set 3 (p=0005) and Set 4 (p=0.003) [La]

significantly increased post-exercise in both c-BFR (p<0001) and i-BFR (p<0.001), with no significant differences between the two modalities (15 ± 02 to 50 ± 14 mmolL-1 and 1.2 ± 02 to 49 ± 11 mmolL-1, respectively, p=0877) No significant differences were observed between the two BFR modalities on Total Mood Disturbance (p=0.431), with the exception of tension subscale that was significantly lower in i-BFR post-exercise (p=0.01), and the fatigue subscale that was significantly higher in c-BFR post-exercise (p=0.034) Reaction time (p=0014) and correct answers (p=0.043) significantly improved only in the i-BFR, post-exercise (p≤005) Conclusions: These results indicate that an acute bout of the new progressively increased pressure i-BFR during single-leg press exercise is better tolerated than c-BFR and could potentially improve cognitive performance, as evidenced by enhanced reaction time and accuracy on the Stroop test post-exercise. However, given the preliminary nature of

this study, further research is warranted to confirm these findings in larger samples and to examine the long-term effects and underlying mechanisms of i-BFR on perceptual, physiological, and cognitive outcomes. 162 6.2 Introduction Exercise adherence is critical for the efficacy of training programmes, with tolerability and enjoyment playing key roles in sustaining engagement, particularly among individuals unable to tolerate traditional high load and high intensity protocols (ASCM, 2000; Dishman & Buckworth, 2013; Riebe et al., 2018; Rhodes & Kates, 2015; Ryan & Deci, 2000). Populations for whom alternative, more tolerable exercise options are essential for maintaining physical function and overall health includes sedentary and clinically symptomatic, injured individuals, and the elderly and/or frail. Perceptual responses, including ratings of perceived exertion (RPE) and discomfort, as well as assessments of pain, are among the primary measurements utilized in the

literature to gauge individual’s subjective experiences during exercise (Hardy & Rejeski, 1989; Robertson & Noble, 1997). These outcome measures serve as potential indicators of exercise tolerability and may influence future compliance to exercise regimens. Beyond perceptual responses, exercise compliance is influenced by various psychological and physiological factors, including mood, cognitive function and central and peripheral fatigue (Bhattacharya et al., 2023; Lee et al, 2016; Prasad & Cerny, 2002; Tornero-Aguilera et al, 2022) These factors play interconnected roles in shaping positive experiences and outcomes during exercise (Bhattacharya et al., 2023; Lee et al, 2016; Prasad & Cerny, 2002; Tornero-Aguilera et al, 2022) Mood and cognitive function are critical determinants of exercise adherence, as they impact the decision to participate, and influence the selection of exercise intensity and type, which in turn affect motivation, enjoyment, and overall

engagement in exercise (Basso & Suzuki, 2017; Ekkekakis, 2003; Rhodes & Kates, 2015). Lactate on the other hand, a metabolic indicator and signalling molecule of gene expression, energy metabolism, and muscle protein synthesis, has been recently recognised for its role as an alternative energy source for the brain during exercise, thereby potentially playing a distinct role in cognitive function and mood (Brooks, 2018; Coco et al., 2020; Ferguson et al, 2018; Lee, 2021; Schurr, 2006; Van Hall, 2000; Xue et al., 2022) Emerging evidence suggests lactate could also be utilized by neurons and may be linked to the brain-derived neurotrophic factor (BDNF) release, impacting neuronal growth and cognitive function (Coco et al., 2020; Xue et al, 2022) These benefits, particularly through their positive effects on mood and cognition, may enhance exercise adherence by promoting a more rewarding and tolerable experience. Building on the recognition of mood, cognitive function, and

perceptual responses as critical determinants of exercise adherence, researchers have been investigating alternative exercise modalities to address the challenges of tolerability and perceptual discomfort associated with traditional high-load resistance exercise (HL-RE) (De Oliveira et al., 2015; Rossi et al, 2018) Blood Flow Restriction (BFR) during low load resistance exercise has emerged as a promising alternative to traditional high load 163 resistance training, offering a more tolerable option for individuals unable to withstand the load of the latter for muscle strength and hypertrophy (Kong et al., 2022; Rodrigo-Mallorca et al, 2021) Traditionally, BFR is applied with continuous pressure throughout the exercise, including resting periods between sets. However, while continuous pressure BFR during low load resistance exercise (cBFR) has been proposed as a viable alternative to HL-RE, particularly for individuals unable to tolerate heavy loading, its tolerability remains a

subject of debate (Dankel et al., 2017; Hughes & Patterson, 2020; Song et al., 2022; Teixeira et al, 2022) Specifically, the constant pressure applied throughout the exercise may contribute to elevated perceptual responses, such as increased RPE, pain and discomfort compared to high load resistance exercise (Dankel et al., 2017; Hughes & Patterson, 2020; Song et al., 2022; Teixeira et al, 2022) In responses to these challenges, the intermittent BFR (i-BFR) protocol has been introduced in the literature over the last decade as an alternative to c-BFR (Fitschen et al., 2014; Freitas et al, 2019; Neto et al, 2017) This BFR modality is characterized by periods of inflation during exercise sets and deflation during rest periods, which are intended to improve perceptual responses by allowing for recovery during the deflation phases (Fitschen et al., 2014; Freitas et al., 2019; Neto et al, 2017) Studies suggest that i-BFR may offer a more tolerable approach, with lower RPE and pain

compared to continuous BFR (Fitschen et al., 2014; Freitas et al, 2019; Neto et al., 2017) Nevertheless, a recent meta-analysis by Sinclair et al, (2022) found no significant differences in RPE between i-BFR and c-BFR (SMD=-0.06, p=073), suggesting that intermittent deflations did not improve exercise tolerance during BFR training. The authors highlighted that these findings might be due to the very limited number of studies investigating the perceptual responses between the two BFR modalities (Sinclair et al., 2022) Additionally, they mentioned that the lack of significance might also stem from high methodological heterogeneity across studies, including variations in applied pressures, differences in BFR equipment (i.e cuff widths and materials), and inconsistent pressure application protocols. To address these limitations, the present study introduces a novel progressively intermittent pressure BFR protocol, in which the cuff pressure increases incrementally across successive sets of

low load resistance exercise. In this protocol, pressure starts at 30mmHg below the target and increases by 10mmHg per set until the final set reaches the prescribed occlusion pressure. This stepwise progression is designed to improve tolerability by gradually increasing the vascular occlusion stimulus, thereby reducing discomfort while maintaining a sufficient physiological stimulus for adaptation. The concept aligns with the origins of KAATSU training, where Dr. Sato first introduced both intermittent and progressively increasing pressure BFR to reduce pain, while still promoting musculoskeletal gains (KAATSU Global Ltd, 2024). However, empirical research examining this has been lacking Given these challenges, Sinclair et al., (2022) highlighted the importance of further research exploring individual responses and tolerability during BFR training, as this could be crucial in improving 164 adherence and exercise compliance. To the authors’ knowledge, this pilot study is the

first to investigate the acute effects of this progressively intermittent pressure i-BFR protocol. The aim of the present pilot study was to investigate and compare the effects of a new intermittent progressive BFR modality during low-load resistance exercise on RPE, and pain, mood, cognition, and blood lactate concentrations, to the traditionally prescribed continuous BFR. The null hypothesis was tested, where no significant perceptual differences would exist between the two BFR modalities. 165 6.3 Methods 6.31 Participants Following appropriate ethical procedures (Section 3.21) and in line with the Declaration Helsinki (2013), fourteen participants (seven males and seven females) aged 18-32 years old (see Table 6.1) with no prior health conditions (Section 3.212) volunteered to take part in this study Participants attended the laboratory on three separate occasions, separated by at least 48hours. The visits for female participants were scheduled during the mid-follicular phase

of the menstrual cycle, specifically between days 5 and 10 (Monis & Tetrokalshvili, 2019). This period was chosen to ensure consistence in hormonal profiles across study sessions (Monis & Tetrokalshvili, 2019). Specifically, the mid-follicular phase is characterised by relatively stable and lower hormone levels following menstruation and before ovulation, which helps minimise potential confounding effects on study outcomes (Carmichael et al., 2019). This timing avoids the extremes of the menstrual cycle, such as the early follicular phase, which can still have residual hormonal fluctuations, and the late luteal phase, characterised by higher progesterone levels and potential physical symptoms (Carmichael et al., 2021; McNulty, et al, 2020) By selecting this phase, the study aims to reduce variability caused by hormonal fluctuations and improve the reliability of the results. This approach is commonly used in research to standardise testing conditions and enhance outcome

consistency (McNulty, et al., 2020) In the initial visit participants were provided with a 3-day dietary diary during their initial visit and were instructed to replicate the dietary intake on the last three days of the trials (Section 3.22) Table 6.1: Participants’ characteristics Variable Total (n=14) Age (yrs) 23.07 ± 483 Height (m) 1.72 ± 007 Weight (kg) 71.18 ± 694 BMI (kg/m2) 23.57 ± 235 SBP (mmHg) 113.69 ± 641 DBP (mmHg) 61.48 ± 563 1 RM (kg) 149.86 ± 4049 100% BFR (mmHg) 451.43 ± 12347 Values are mean ± SD 166 6.32 Experimental Procedures Preliminary testing: During the initial visit, medical questionnaires and consent forms were completed, followed by anthropometric measurements (height, weight), and BMI calculations (Section 3.212 & Section 3.231), and the single leg press 1 repetition maximum (1RM) test, the identification of individualised BFR pressures (Section 3.233), familiarisation with profile of mood states questionnaire (POMS)

(Section 3.251), the Stroop cognitive function test (Section 3252), and determination of the ratings of perceived exertion (RPE) and visual analogue scale of pain (Section 3.253) Body composition was measured via a non-invasive bioelectrical impedance analysis (BIA) technique widely employed to estimate body fat percentage and other pertinent body composition metrics across diverse populations (Sullivan et al., 2019, Hillier et al, 2014, Evans et al, 2018, Achamrah et al, 2018) BIA involves the passage of a low-level electrical current through the body, with the impedance to this current's flow being measured. This method capitalizes on the fact that lean tissue, such as muscle, possesses greater water and electrolyte content, thereby exhibiting superior electrical conductivity compared to adipose tissue. During the BIA procedure, participants assumed a supine position, and two electrodes were affixed to their right hand and right foot following meticulous cleansing of the areas

with alcohol wipes, ensuring optimal contact. The participants’ relevant data, including height, weight, waist and hip circumference, age, gender, ethnicity, and fitness level, were inputted into the touchscreen interface of the BIA device (BodyStat 1500, BodyStat Ltd., Isle of Man, UK) Subsequently, clips were secured to the metal tab strip of the electrodes. Participants were instructed to maintain a relaxed state and minimal movement for a duration of 4 minutes until the results were displayed on the device's screen. The single leg press 1 Repetition Maximum (1RM) was conducted using a linear leg press machine (Signature Series Linear Leg Press, Life Fitness, Cambridgeshire, UK), as described by Clark et al. (2019) (Table 6.2) Participants were asked to identify their dominant leg, often based on their experience in resistance training. In cases where participants were unsure of their dominant leg, 1-RM assessments were performed for both legs, and the leg with the higher

1-RM was selected as dominant. Participants were carefully positioned in the leg press machine, with their knees and feet positioned hipwidth apart, ensuring proper alignment. Their knees were flexed at a 90- angle (with full knee extension defined as O0), maintaining a neutral spine with firm contact against the backrest. Participants held handles adjacent to the hips with their hands for stability. The non-dominant limb was removed from the footplate and actively held in approximately 90 hip and knee flexion. This position ensured isolation of the targeted lower limb muscles and facilitated accurate assessment of strength without 167 interference from the non-tested limb (Clark et al., 2019; Freitas, 2020) The 1-RM was determined once the participants failed to complete a repetition or failed to execute the leg press technique correctly. The 1-RM for all participants was determined within 3-5 attempts, ensuring a balance between exhaustive effort and minimizing

fatigue-induced performance variability. The process of the 1-RM protocol for a single leg is detailed in Table 3.5 This approach ensured standardized assessment while accommodating individual differences in limb dominance and strength. The chosen 1-RM protocol provided a reliable and precise method for assessing lower single limb strength, supported by significant correlations between single-leg leg press and knee flexion/knee extension tests (r = 0.60-059, p < 001), validating its efficacy for capturing overall lower limb strength (Clark et al., 2019) Participants were asked to rest for at least 1 hour after their 1-RM completion assessment. Following their recovery, participants were required to conduct 4 sets (30 x 15 x 15 x 15 repetitions) of single-leg leg press exercise with their dominant leg at 30% 1-RM for familiarisation purposes. Table 6.2: 1-RM Protocol by Clark et al (2019) Warm-up set 10 repetitions, 50% BW Rest 120 second Trial 1 1 repetition, 100% BW Rest

120 seconds Trial 2 1 repetition, trial 1 + 30% BW (M) / 25% BW (F) Rest 120 seconds Trial 3 1 repetition, Trial 2 + 30% BW (M) / 25% BW (F) Rest 120 seconds Trial 4 1 repetition, Trial 3 + 30% BW (M) / 25% BW (F) Abbreviations; Body Weight (BW, Male (M), Female (F). Main experimental trials: In the following two visits, participants were required to conduct a single-leg leg press exercise under two different conditions in a random order. Specifically, in the present crossover design pilot study, participants were randomly assigned to perform leg press exercise using their dominant leg under two different BFR conditions: continuous BFR (c-BFR) and intermittent (i-BFR). For the c-BFR condition, participants exercised at 30% of their 1RM with BFR pressure at 50% of their individualised arterial occlusion pressure (50% of AOP). This pressure was maintained throughout the entire exercise session, including both exercise sets and the resting periods between sets. For the i-BFR

condition, participants also exercised at 30% of their 1RM, but the BFR pressure was progressively increased by 10mmHg with each set until it reached 50% of their individualised AOP by 168 the final set. During the rest periods between sets, the elastic pneumatic cuffs were deflated, allowing for temporary relief from the pressure. The exercise consisted of 1 set of 30 repetitions followed by 3 sets of 15 repetitions in both conditions, separated by 30 seconds resting periods (Figure 6.1) The load utilized for the single leg press exercise corresponded to 30% of participants' 1RM. This intensity was chosen to ensure a manageable intensity, minimizing undue strain while still eliciting a meaningful physiological response, as supported by existing literature (Barbieri et al., 2020; Clark et al, 2011; Ramis et al, 2020) To ensure standardization, a tempo of 1 second eccentric and 1 second concentric was maintained during both BFR conditions. An electronic metronome guided

participants to adhere to the prescribed tempo throughout the exercise regimen (Wilk et al., 2021) RPE and pain were recorded at the end of each set (Laborda et al., 2013, Schwiete et al, 2021) Capillary blood sample [La] concentrations were analysed pre-exercise as a baseline measurement and immediately following exercise cessation (Section 3.274) The POMS questionnaire and Stroop test were measured also before and after exercise (Figure 6.1) Figure 6.1: Study Design Schematic Abbreviation: Ratings of Perceived Exertion (RPE), Profile of Mood States (POMS), Blood flow restriction with intermittent pressure (i-BFR), Blood flow restriction with continuous pressure (c-BFR), Repetitions (reps), 1 Repetition Maximum (1RM). Note: Percentages (%) refer to individualised arterial occlusion pressure (AOP). 169 6.33 Statistical Analyses Prior to the pilot study a priori sample size was determined using G* Power software (version 3.1) (Section 3.28) All data were first checked for

normality using Shapiro-Wilk test (Section 328) To identify differences between conditions and time, a two-way repeated measures analysis of variance (ANOVA) was performed, considering the within-subject factors of condition and time (Section 3.28) In cases where the data deviated from a normal distribution, the non-parametric equivalent to ANOVA analysis was employed (Section 3.28) Where appropriatesuch as when only two levels were being compared (e.g, pre- vs post-exercise within a condition, or post-exercise between i-BFR and c-BFR) paired-sample t-tests were conducted to further explore specific within- and between-condition differences, in line with the exploratory nature of the pilot study. 170 6.4 Results All variables, except for RPE and pain were normally distributed. Therefore, parametric statistical tests were applied to normally distributed variables, while non-parametric tests were used for RPE and pain. 6.41 Participants There were no observed differences in

participants’ baseline characteristics (p > 0.05, Table 61) 6.42 Perceptual Responses A significant difference was found in RPE, as indicated by the Friedman test (p<0.001, χ2 =48412, df=7). Post hoc pairwise comparisons with Bonferroni correction revealed that RPE was significantly lower in the i-BFR modality at sets 2, 3, and 4 compared to the c-BFR modality (Set 1; p=0.154, Set2; p=0.005, z=-2667, Set3; p=0006, z=-2751, Set4; p=0004, z=-2842) (Figure 62) A significant difference was also found in the pain, as indicated by the Friedman test (p<0.001, χ2 =59.130, df=7) Post hoc pairwise comparisons with Bonferroni correction revealed that pain was significantly lower in i-BFR modality compared to c-BFR in sets 3 and 4 (Set 1; p=0.011, Set 2; p=0.009, Set3; p=0005, z=-2777, and Set4; p=0003, z=-2956) (Figure 63) Figure 6.2 A) Rating of Perceived Exertion (RPE) in Set 1, Set 2, Set 3 & Set 4 for continuous pressure BFR condition (cBFR, white bars) and intermittent

pressure BFR condition (i-BFR, black bars) The bar graphs capture the median and the white circles represent individual data points, with some on-top of each other. 1 Values are reported as medians ± interquartile ranges (IQR). 2 * Significant differences. B) Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR. C) Individual data points in Set 1, Set 2, Set 3, & Set 4 for i-BFR. 171 Figure 6.3 A) Visual Analogue Scale for Pain in Set 1, Set 2, Set 3 & Set 4 for continuous pressure BFR during low load resistance exercise (c-BFR, white bars) and intermittent pressure during low load resistance exercise (i-BFR, black bars). The bar graphs capture the median and the white circles represent individual data points, with some on-top of each other. 1 Values are reported as medians ± interquartile ranges (IQR). 2 * Significant differences. B) Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR. C) Individual data points in Set 1, Set 2, Set 3,

& Set 4 for i-BFR. 6.43 Lactate No significant interaction effect was identified in lactate (p=0.877) Exploratory statistical analyses (Section 3.28) revealed that lactate concentrations changed significantly from pre to post exercise in both c-BFR (t(13) = -12.6, p≤0001) and i-BFR (t(13) = -119, p≤0001) (Figure 64) Baseline lactate measurements were similar between conditions (p=0.199) 172 Figure 6.4 A) Bar graph of lactate concentrations pre and post exercise for continuous pressure BFR condition (c-BFR, white bars) and intermittent pressure BFR condition (i-BFR, black bars). The bar graphs capture the mean, and the white circles represent individual data points, with some on-top of each other. B) Individual data points from pre to post exercise for c-BFR. C) Individual data points from pre to post exercise for i-BFR. 1 Values are mean ± SD, 2 * Significant differences. B) Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR. C) Individual data points

in Set 1, Set 2, Set 3, & Set 4 for i-BFR. 6.44 Profile of Mood State (POMS) Questionnaire No significant differences were identified in total mood disturbance (TMD) (p=0.431), and the subscales of tension (p=0.793), anger (p=0068), depression (p=0793), esteem (p=0743), vigour (p=0.186), fatigue (p=0136), and confusion (p=0512) However, a significant effect of time identified on tension (F(1,13)=13.542, p=0003, η²=0510) and a significant effect of condition on fatigue scores (F(1,13)=13.937, p=0002, η²=0517) The exploratory statistical analysis using pairwise t-tests (Section 3.28) revealed that tension was significantly lower post exercise only in the i-BFR condition (t(13)=3.015, p=001) and fatigue was significantly higher post exercise compared to pre-exercise only in the c-BFR condition (t(13)=-2.375, p=0034) Additionally, fatigue was significantly higher post exercise in the c-BFR compared to the i-BFR (t(13)=4.163, p=002) (Figure 65) 173 Figure 6.5 A) POMS mood

state scores in continuous pressure BFR (a; c-BFR, black lines) and in intermittent pressure BFR (b; i-BFR, black dashed lines) at pre-exercise B) POMS mood state scores in continuous pressure BFR (a; c-BFR, black lines) and in intermittent pressure BFR (b; i-BFR, black dashed lines) at post exercise Abbreviations; Tension (Ten), Anger (Ang), Fatigue (Fat), Depression (Dep), Esteem (Est), Vigour (Vig), Confusion (Con). 1 Values are mean ± SD, n = 14 2 * Significant differences between conditions post exercise 3 # Significant differences from pre to post exercise within conditions 6.45 Stroop Test No significant condition by time interactions were identified in reaction time (p=0.130) Exploratory pairwise t-tests comparisons (Section 3.28) revealed that reaction time was significantly lower post exercise compared to the pre values only in i-BFR (t(13) = 2.839, p=0014), while no significant difference observed from pre to post values in c-BFR condition or between conditions (p=0.783)

(Figure 6.6) A significant condition by time effect was identified following repeated measures ANOVA on correct answers (F(1,13)=7.076, p=002, η2= 0352) Post-hoc pairwise t tests comparisons revealed that post exercise correct answers were significantly more in the i-BFR condition compared to the c-BFR (t(13)=3.297, p=002) Additionally, correct answers were more from pre to post exercise only in the i-BFR condition (t(13)=-2.244, p=0043) (Figure 67) 174 Figure 6.6 A) Stroop test reaction time at pre and post exercise for continuous pressure BFR condition (c-BFR) and intermittent pressure BFR condition. The bar graphs capture the mean, and the white circles represent individual data points, with some on-top of each other. B) Individual data points from pre to post exercise for c-BFR. C) Individual data points from pre to post exercise for i-BFR. 1 Values are mean ± SD, 2 * Significant differences. Figure 6.7 A) Stroop test correct answers at pre and post exercise for continuous

pressure BFR condition (c-BFR) and intermittent pressure BFR condition. The bar graphs capture the mean, and the white circles represent individual data points, with some on-top of each other. B) Individual data points from pre to post exercise for c-BFR. C) Individual data points from pre to post exercise for i-BFR. 1 Values are mean ± SD, 2 * Significant differences between conditions post exercise 3 # Significant differences from pre to post exercise within conditions 175 6.5 Discussion BFR during low-load resistance training is an increasingly explored alternative mode of exercise to traditional high load resistance exercise, offering comparable muscle strength and hypertrophy positive adaptations (Kong et al., 2022; Rodrigo-Mallorca et al, 2021) Given its potential benefits for individuals unable to tolerate high intensity loading, such as those with musculoskeletal limitations, evaluating the tolerability and effectiveness of different BFR modalities becomes essential

(Jørgensen et al., 2023; Rodrigo-Mallorca et al, 2021; Zhang et al, 2022) Therefore, the purpose of this pilot study was to investigate a new i-BFR modality, characterised by progressively increasing pressure in addition to intervals of deflation, and to compare it with the traditionally prescribed c-BFR during low load resistance exercise. The primary focus was to evaluate perceptual responses, and pain, hence assessing the tolerability of the new i-BFR relative to c-BFR. A secondary aim was to examine potential differences in mood, cognitive function, and blood lactate concentrations between the two modalities, to explore the effectiveness of the new intermittent protocol in these factors. The key preliminary finding of this pilot study was that the new i-BFR modality resulted in lower RPE and pain during exercise compared to c-BFR. Notably, these benefits were observed without compromising the acute metabolic response, as lactate concentration increases were similar between the two

BFR modalities, suggesting potentially comparable stimulation of the muscle hypertrophy cascade. The null hypothesis was rejected as the new i-BFR resulted in significantly lower perceptual responses compared to c-BFR. A noteworthy finding in the present pilot study was that RPE and pain were significantly lower with the new i-BFR modality compared to c-BFR, demonstrating the potential impact that this protocol may have on the participants’ overall exercise experience and adherence to BFR training programmes. It is important to highlight that, to the best of the authors’ knowledge, no previous studies have compared this specific progressively increasing intermittent BFR modality and compared it to the traditional continuous BFR. This distinction is crucial, as the new i-BFR protocol used in this study differs from the intermittent BFR modalities explored in the existing literature, which utilise the same pressure from the start of the BFR application. Despite this novelty, the

observed reductions in RPE and pain align with the majority of the current literature comparing intermittent and continuous BFR modalities (Fitschen et al., 2014; Freitas et al, 2019; Neto et al, 2017; Yasuda et al, 2013) Specifically, Fitschen et al. (2014) observed significantly greater acute muscle pain with c-BFR during unilateral leg extensions compared to i-BFR, while Yasuda et al., (2013) reported a progressive increase in RPE that reached significance in the third and fourth sets during c-BFR compared to i-BFR. Neto et al, (2017), similarly found higher RPE with c-BFR compared to i-BFR during upper body resistance exercises. However, findings regarding perceptual responses between continuous and intermittent BFR during low load resistance exercise are not entirely consistent. Some studies, like Davids et al, (2021), reported 176 initially higher pain with c-BFR, but these differences diminished as participants adapted to the training over time. Specifically, participants

completed 21 sessions over seven weeks, with significantly higher ratings of pain reported in c-BFR compared to i-BFR during initial sessions. However, by the final session, there were no significant differences in pain between the two BFR modalities (Davids et al., 2021) Additionally, Brandner & Warmingthon (2017) investigated perceived exertion after low load elbow-flexion exercise with low pressure c-BFR (80% of Systolic Blood Pressure; SBP), high pressure intermittent BFR (130% of SBP), and high load resistance exercise without BFR. They found higher RPE for both high load resistance exercise and high pressure i-BFR compared to low pressure c-BFR (Brandner & Warmington, 2017). However, it is important to note that both the pressures used in their study and the methods for identifying individualised BFR pressures differ substantially from those in the present pilot study. The inconclusive results regarding perceptual responses between continuous and intermittent BFR during

low load resistance exercise, may be attributed not only to the variability in methodological approaches, such as exercise protocol design, BFR modalities, BFR pressures, and different musculature trained (upper versus lower body), but also to several limitations. These could include the lack of standardized pressure application and measurement protocols (i.e pressure determination protocols, application methods, BFR equipment, assessment techniques), potential differences in participants’ baseline fitness levels or pain thresholds, and the varying adaptation times to different BFR modalities. Addressing these limitations could help elucidate the mechanistic drivers behind perceptual responses and highlight the need for more targeted research to better understand and optimize BFR training protocols. An interesting finding of the present pilot study was that the exploratory analysis revealed significantly lower tension and fatigue scores in the i-BFR condition post-exercise compared

to the cBFR. Given that mood has been considered a crucial factor influencing exercise adherence (Lee et, 2016; Rhodes & Kates, 2015), the findings suggest that the new i-BFR modality could potentially improve mood and enhance tolerability compared to the c-BFR modality. These results contribute to the ongoing debate regarding the effects of BFR on mood (Du et al., 2021; Silva et al, 2019), and exercise tolerance (Brandner & Warmingthon, 2017; Freitas et al., 2019) While a limited number of studies have reported benefits of BFR on mood (Du et al., 2021; Ruaro et al, 2020), others have found no significant differences (Yamada et al., 2021), or even negative effects (Silva et al, 2019) Specifically, Du et al., (2021) reported significantly increased serum levels of BDNF and vascular endothelial growth factor (VEGF), -both known biomarkers associated with mood regulation post-BFR resistance exercise in stroke patients with post stroke depression (Du et al., 2021) Ruaro et al,

(2020), investigated the effects of short and large BFR cuff application during low load resistance exercise and found that both BFR conditions improved mood state, but the short cuff significantly decreased tension, depression, anger and mental confusion compared to large cuff (Ruaro et al., 2020) 177 Additionally, Yamada et al. (2021) reported no significant differences in feelings of tranquillity or physical exhaustion between BFR and no BFR resistance exercise conditions (Yamada et al., 2021).Conversely, Silva et al (2019) reported negative effects on mood following BFR during lowload resistance exercise compared to high-load resistance exercise, noting acute negative effects on mood state, decharacterization of the iceberg profile, increased total mood disturbance, and greater participant fatigue, suggesting that BFR resistance training should be avoided before sports competitions in athletes (Silva et al., 2019) Furthermore, limited studies investigating the effects of BFR

during low-load aerobic exercise have also shown inconsistent results, with some reporting negative effects on mood and exercise adherence (Mok et al., 2020; Silva et al, 2019), while others, such as Kargaran et al. (2021), highlight improvements in mood and sleep quality In summary, while the present pilot study provides promising insights into the potential mood benefits of the new i-BFR modality, the broader literature indicates that more research is necessary to fully understand and optimize BFR protocols for improving mood and exercise adherence. The present pilot study is the first exploratory investigation, to the authors' knowledge, comparing the acute effects of i-BFR versus c-BFR modalities on cognition, and finding significant improvements in cognitive function with the new i-BFR modality compared to the c-BFR during low load resistance exercise. Specifically, only i-BFR led to a significant increase of 65% in correct answers post exercise in the Stroop test, exceeding

the absolute total error of the mean (TEM%) of 3.8%, indicating a meaningful change. Moreover, reaction time decreased by 55% post-exercise only in the i-BFR condition, which is also greater than the absolute TEM% of 4.8%, confirming the significant of this reduction, while reaction time remained unchanged in the c-BFR condition from pre to post. As no previous studies have explored the acute effects of intermittent versus continuous BFR on cognitive function, the present results lack direct comparison. However, these results are consistent with previous findings in the literature suggesting that BFR can have positive effects on cognitive function (Kagaran et al., 2021; Sardeli et al, 2018; Sugimoto et al, 2021) Sardeli et al (2018) reported lower reaction times post-exercise in both BFR and non-BFR conditions compared to high-load resistance exercise in older adults. Additionally, studies examining BFR during low load aerobic exercise have shown enhanced cognitive function compared to

no BFR conditions, as evidenced by biomarker changes related to cognition and mood, such as BDNF (Karagan et al., 2021) Specifically, Kargaran et al (2021) demonstrated significant improvements in cognitive function in older women during BFR walking on a treadmill at low intensity compared to no BFR walking. Similarly, Sugimoto et al (2021) reported improved executive function, reflected by shortened reaction times and decreased Stroop interference scores, during BFR walking compared to no BFR walking. In contrast, Yamada et al. (2021) found no significant changes or differences on reaction time and correct answers in Stroop test in BFR conditions compared to no BFR resistance protocols (Yamada et 178 al., 2021) In summary, the present pilot study provides initial evidence that i-BFR may enhance cognitive function more effectively than c-BFR during low load resistance exercise. One possible explanation for this difference could lie in the district physiological and psychological

responses elicited by i-BFR compared to c-BFR (Boulares et al., 2024; Snuggs et al, 2023) It has been suggested that intermittent hypoxia, as induced by i-BFR, may enhance oxygen utilization and metabolic efficiency (Boulares et al., 2024), potentially stimulating the production of neuroprotective factors such as BDNF and promoting vascular adaptations that support cognitive performance and alertness (Ruber & Schwarz, 1999; Snuggs et al., 2023) Finally, another notable finding of this pilot study was the significant post exercise increase in lactate responses observed in both i-BFR and c-BFR, with no significant differences between them. These preliminary results indicate that both the new i-BFR and the traditional c-BFR could potentially induce similar metabolic responses, as reflected by lactate concentrations, suggesting that they may activate similar physiological pathways. To the authors’ knowledge, no other studies have used a progressively increased pressure intermittent

protocol in BFR, hence no direct comparisons with the existing BFR literature can be conducted. However, the present findings align with the findings of previous studies on other intermittent BFR protocols. Freitas et al (2020), who reported comparable blood lactate concentrations between low load resistance exercises (20% of 1RM, 4 sets x 30-15-15-15 reps) with iBFR and c-BFR (50% of AOP) in young untrained individuals (Freitas et al., 2020) Similarly, Neto et al., (2017) found comparable lactate increases following low load resistance exercise protocols (20% of 1RM, 4 sets x 30-15-15-15 repetitions) with both i-BFR and c-BFR (1.3 x SBP) in young, trained individuals. The limited number of existing studies highlights the need for further research to identify the optimal BFR modality and delve deeper into the underlying physiology. This is particularly noteworthy given lactate’s proposed role as a mediator molecule that stimulates other biomarkers such as GH, and IGF-1, both of which

play a pivotal role in muscle protein synthesis (Brooks, 2018; Lee, 2021; Rossi et al., 2018; Sharifi et al, 2020) Additionally, lactate has been implicated in cognitive function and mood enhancement through its potential influence on BDNF (Brooks, 2018; Coco et al., 2020; Ferguson et al, 2018; Lee, 2021; Schurr, 2006; Van Hall, 2000; Xue et al., 2022) The similarity in lactate increases between i-BFR and c-BFR could potentially suggest that the new intermittent modality might stimulate similar physiological responses to the traditional cBFR with improved tolerance. However, while these preliminary findings are promising, further research is necessary to comprehensively understand the mechanism by which BFR and lactate impact both muscle protein synthesis and cognitive function. An additional aspect of this pilot study worth noting is the individual variability in responses to the new i-BFR modality compared to c-BFR. The most notable individual variability was seen in RPE, and 179

pain, responses, with less variability in lactate and cognitive outcomes like Stroop correct answers and reaction times. This variability in RPE and pain could stem from factors such as personal pain thresholds and individual adaptation to BFR protocols (Davids et al., 2021; Terarz et al, 2012) Such differences highlight the need for personalized approaches in evaluating BFR modalities. Qualitative data, such as interviews, could provide clearer insights into these variations and a better understanding of the user’s experiences during BFR training, which could be key to improving adherence and exercise compliance (Sinclair et al., 2022) In the case of lactate responses, some individuals may respond better to i-BFR, while for others, the modality may make little difference in how pressure is applied. To further explore these differences in metabolic responses, measuring biomarkers that are crucial for muscle protein synthesis, such as growth hormone (GH) and insulin-like growth

factor-1 (IGF-1), could potentially provide more information on the variability in lactate responses under different BFR modalities, as lactate alone may not fully capture the underlying metabolic processes. Conversely, cognitive improvements were more consistent, suggesting that i-BFR’s effects on cognitive performance may be less impacted by individual differences. However, incorporating additional biomarkers related to cognitive function and mood, such as BDNF, could enhance our understanding of how BFR during resistance exercise influences these aspects. 180 6.6 Limitations Despite the novelty of this pilot study investigating a new intermittent BFR modality with progressively increased pressure throughout the sets, several limitations should be noted. First, the study did not include a no-BFR control condition for direct comparison. However, the inclusion of the c-BFR modality as a comparator addressed this to some extent, as c-BFR has been extensively studied in the

literature, providing a well-established reference point for evaluating the novel intermittent BFR approach. This allowed for meaningful comparisons and insights into the differences between these two BFR modalities. Additionally, while the study utilized RPE and VAS for pain to gauge participants' experiences, qualitative data such as interviews could have offered richer insights into participants' preferences and perceptions regarding the new intermittent BFR modality. This would help better understand whether the intermittent approach is more favourable compared to traditional methods. Finally, the study focused on lactate concentrations as the primary metabolic marker. Including a broader range of biomarkers, such as GH and IGF-1 for muscle strength and hypertrophy, as well as BDNF for cognitive function and mood, could provide a more comprehensive understanding of the physiological and psychological mechanisms and impacts of BFR. 181 6.7 Conclusions In conclusion,

this pilot study highlights the acute effects of the new i-BFR modality compared to cBFR during low-load resistance exercise. Notably, i-BFR significantly reduced RPE and pain, indicating potentially better tolerance during exercise, without compromising lactate responses compared to c-BFR. Additionally, the new i-BFR showed potential cognitive benefits, suggesting that it could enhance cognitive function alongside physical performance. These findings add valuable insights to the ongoing discussion about i-BFR’s benefits despite some inconsistencies in the literature due to varied methodological approaches. However, individual responses to the new i-BFR exhibited considerable variability compared to traditionally prescribed c-BFR, particularly in RPE, and pain. This variability highlights the importance of adopting personalized approaches when evaluating and implementing BFR exercise modalities, particularly regarding occlusion pressure and its application, such as through

incremental adjustments or extended deflation periods during rest. Further research could benefit from exploring these individual differences more deeply through qualitative methods and additional biomarker analysis. 182 7. Acute Study 1: ‘High load resistance exercise vs. Continuous & Intermittent blood flow restriction: Effects on perceptual responses, brain derived neurotrophic factor (BDNF), mood & cognition’ 183 7.1 Abstract Introduction: Mental and cognitive health conditions significantly impact quality of life. While the benefits of aerobic exercise on mood and cognition are well documented, the effects of resistance training regimenssuch as high-load resistance exercise (HL-RE) and low-load resistance exercise with continuous blood flow restriction (c-BFR)on these parameters remain under investigation. Current evidence is insufficient to establish conclusively that c-BFR consistently improves mental and cognitive health. Additionally, the perceived

exertion and discomfort associated with HL-RE, as well as c-BFR, can hinder adherence to these exercise regimens. This study aims to address these issues by investigating the acute effects of HL-RE and two BFR modalitiesc-BFR and a novel intermittent pressure BFR (i-BFR)on perceptual responses, brain derived neurotrophic factor (BDNF), mood, and cognitive function. Methods: Twenty-one healthy, resistance-trained males (age: 18-38 years) performed four sets of leg press to failure under three conditions: HL-RE at 70% of 1RM, c-BFR at 30% of 1RM with constant pressure at 50% of arterial occlusion pressure (AOP), and i-BFR at 30% of 1RM with pressure increased to 50% of AOP by the last set, with cuffs deflated during rest periods. Ratings of perceived exertion (RPE) and pain were measured at the end of each set. Muscle soreness was assessed before, 24 and 48 hours post each trial. Cognitive function was assessed using the Stroop test and Mixed Stroop task before, 10-, and 60- minutes

after exercise. The Profile of Mood States (POMS) was measured before, 15-, and 60- minutes after exercise. Venous blood samples for brainderived neurotrophic factor (BDNF) were collected pre- and post-exercise Semi-structured interviews with a focus subgroup (n=14) explored preferences and adherence. Results: Pain was significantly higher in c-BFR compared to HL-RE during sets 1 (p=0.002), 3 (p=0003), and 4 (p=0004) RPE and muscle soreness responses did not differ significantly between conditions across all four exercise sets. Participants preferred HL-RE due to familiarity but found i-BFR more tolerable and less painful compared to both HL-RE and c-BFR, as reported in the semi-structured interviews. No significant differences in mood state or cognitive function were observed between the three conditions at any time point (p > 0.004) BDNF significantly increased from pre-to-post exercise in all three conditions (HLRE; p<0001, c-BFR; p=0004, i-BFR; p = 001) Conclusions: i-BFR may

stimulate BDNF increases, which have been associated with improvements in cognitive function and mood in previous research. Despite no observed enhancements in these outcomes in the current study, i-BFR was better tolerated, with lower perceived discomfort compared to both HL-RE and c-BFR. Future research should explore the chronic effects of i-BFR on psychological outcomes to optime training protocols and support adherence. 184 7.2 Introduction Mental and cognitive health conditions are critical for maintaining quality of life, mental health and independence (Gross et al., 2019; Park et al, 2003) In 2019, approximately one in eight people globally had a mental health condition, with anxiety and depressive disorders being the most common (WHO, 2022). Cognitive health issues, such as dementia, affected around 50 million people in 2019, with projections suggesting a tripling of this number by 2050 (Alzheimer’s Association, 2020). Ageing impacts cognitive domains like memory,

attention, and executive function due to neurodegeneration and vascular changes (Harada et al., 2013; Mattson & Magnus, 2006) While aerobic exercise is well established as beneficial for mood and cognition (Herring et al., 2016; Smith et al, 2010), emerging evidence supports resistance training as an effective alternative for emotional well-being and cognitive enhancement (Cavarretta et al., 2019; Herold et al, 2019) Resistance training has been shown to improve mood and cognitive function across various populations (Bartholomew & Linder, 1998; El-Kotob et al., 2020) Even low-load resistance exercise has been found to reduce anxiety and improve mood in both males and females (Bartholomew & Linder, 1998; Focht & Koltyn, 1999). Additionally, resistance training has been associated with enhanced cognitive performance, including faster reaction times and improved executive function (Alves et al., 2012; Chang et al., 2014; El-Kotob et al, 2020; Li et al, 2018; Wilke et al,

2019) These beneficial effects are believed to be mediated by complex neurobiological mechanisms, including increases in neurotransmitters such as endorphins, serotonin, and dopamine (Dietrich & McDaniel, 2004; Meeusen & De Meirleir, 1995), and neurotrophic factors such as brain-derived neurotrophic factor (BDNF), which plays a key role in neuroplasticity and mood regulation (Cotman & Berchtold, 2002; Kim et al., 2019; Lu et al., 2014; Marston et al, 2017; Murawska-Ciałowicz et al, 2021) Despite the benefits of high-load resistance exercise, its feasibility may be limited in certain populations, including older adults, and adults with joint or cardiovascular limitations. Low-load resistance exercise with blood flow restriction (BFR-RE) has emerged as an alternative that elicits similar musculoskeletal adaptations to high-load resistance exercise (HL-RE) at lower mechanical loads (Cook et al., 2018; Laurentino et al, 2012; Ozaki et al, 2013) However, traditional continuous

BFR (c-BFR), where pressure is maintained throughout the exercise and rest periods, has been associated with elevated ratings of perceived exertion (RPE), discomfort, and pain -potential barriers to adherence (Bell et al., 2018; Dankel et al, 2019; Kilpatrick et al, 2020) To address these limitations, intermittent BFR (i-BFR), which applies occlusion only during the active exercise phases and deflates during rest intervals, has been explored (Fitschen et al., 2013; Neto et al, 185 2017). This method has been shown to improve tolerability compared to c-BFR (Fitschen et al, 2013; Neto et al., 2017) However, a recent meta-analysis by Sinclair et al (2022) reported no significant differences in RPE between i-BFR and c-BFR and highlighted a limited number of studies and methodological variability as important factors. The authors also recommended future studies incorporating qualitative methods to better understand individual responses and identify strategies for improving adherence.

Building upon this, a novel progressively incremental intermittent BFR protocol has been developed (KAATSU Ltd, 2024). This approach gradually increases cuff pressure across sets (rather than maintaining a fixed pressure per set), starting below the target and reaching full occlusion pressure by the final set, with deflation between sets. Though it has been informally used in practice since the work of Dr. Yoshiaki Sato, its acute effects have not been formally studied Practically, this approach may reduce the abrupt vascular and perceptual stress of traditional protocols while still achieving sufficient occlusion to stimulate physiological adaptations. Physiologically, the gradual pressure increase may reduce afferent nerve activation and pain perception, potentially improving adherence without sacrificing efficacy. The need for such an approach is supported by previous findings that highlight perceptual discomfort (e.g, elevated RPE and pain) as key deterrents to long-term adherence

(Bell et al., 2018; Dankel et al, 2019; Kilpatrick et al, 2020) Additionally, while BFR training has been shown promise in promoting musculoskeletal adaptations (Gronfeldt et al., 2020; Kong et al, 2025), its effects on mood and cognition remain relatively unexplored. Existing findings are mixed with some studies reporting increased fatigue without significant cognitive improvements (Silva et al., 2021; Yamada et al, 2021), while others suggest increased BDNF and mood benefits (Du et al., 2021), including reductions in tension, depression, anger, and confusion (Ruaro et al., 2020) As such, further investigation is needed to elucidate the mechanisms underlying these effects and to determine whether novel BFR strategies can optimise both efficacy and tolerability. To the authors’ knowledge, no study has yet compared a progressively incremental i-BFR protocol to both c-BFR and HL-RE in terms of perceptual responses and tolerability, as well as mood and cognitive outcomes. Given the

potential of BFR-RE as a more accessible alternative to HL-RE, it is important to evaluate protocols that maximise comfort and adherence while also preserving or enhancing psychological and cognitive benefits. This is the first study to integrate quantitative and qualitative methodologies to assess physiological, perceptual, and cognitive responses to a novel i-BFR modality. It was hypothesised that the new i-BFR would be more tolerable than both HL-RE and c-BFR, while still eliciting improvements in mood and cognitive performance. 186 7.3 Methods This study employed a mixed-methods design incorporating both quantitative and qualitative approaches to evaluate the research question comprehensively. Utilizing a crossover experimental design, participants were assigned to three experimental conditions and conducted in a random order: high load resistance exercise (HL-RE), low load resistance exercise with continuous pressure BFR (cBFR), and low load resistance exercise with

intermittent pressure BFR (i-BFR) (Section 3.7) 7.31 Participants Twenty-seven healthy young males aged 19 to 38 years (Table 7.1) and who were currently engaged in resistance training (at least 2 days/week for the last 6 months) volunteered for this study (Section 3.21) From the twenty-seven participants, six dropped out of the study due to personal reasons Additionally, one participant did not undergo venepuncture for venous blood sampling but completed all other measurements. Twenty participants were recruited for this study, with 19 being sufficient to achieve a statistical power of 80% (Section 3.91) The participants paid five visits to the laboratories, one in the Moulsecoomb campus and four in the Welkin laboratories in the Eastbourne campus. The first two visits were for preliminary data collection and familiarisation purposes (Section 3.5) During their initial visit, participants were provided with nutrition and exercise guidance for pre study and exercise standardization

(Section 3.4) The initial visit was separated from the third experimental visit by at least 48 hours. The subsequent three experimental visits were spaced at least five days apart 187 7.32 Experimental Procedures Preliminary testing & Familiarisations: During the initial visit, consent forms and medical questionnaires were collected (Section 3.21), followed by measurements of anthropometric data (Section 3.51), the identification of individualised BFR pressures (Section 353) and the assessment of leg press 1 Repetition Maximum (1-RM) (Section 3.54) Participants were then instructed to rest for a minimum of one hour after completing their bilateral leg press 1-RM assessment. During this rest period, they were also asked to familiarize themselves with the profile of mood states questionnaire (POMS) (Section 3.61), the cognitive function assessments (Section 362), and the ratings of perceived exertion (RPE), and visual analogue scale of pain (Section 3.63) After the resting

period, participants were guided through the exercise protocol for familiarisation purposes. Participants performed four sets of bilateral leg press exercise to failure, with the load set at 30% of their 1-RM, while wearing the KAATSU bands inflated to 50% of their individualised BFR pressure. At the end of each set, participants rated their discomfort and pain via the Borg Scale (0-10) and a visual analogue scale (0-10) for pain. The POMS questionnaire and the two cognitive function assessments were completed before and after the exercise. In the second visit, participants underwent a Dual x-ray Absorptiometry scan (DXA) to assess body composition, including lean mass and fat mass distribution (Section 3.52) Main Experimental trials: In the following three visits, participants performed a bilateral leg press exercise under three different conditions in a randomised order (Section 3.7) Following a 30-minute resting period in a supine position, capillary blood samples were collected

before and immediately after each exercise session (Section 3.84) and venous blood samples were taken both before the exercise 188 and 5 minutes after its completion (Section 3.81) During each visit cognitive function assessments were conducted before exercise and at 10- and 60- minutes after exercise, while POMS questionnaire was administered before exercise and 15- and 60-minutes post exercise. RPE and pain were assessed at the end of each set. Figure 71 illustrates the study design Muscle soreness was assessed 24 hours and 48 hours post each exercise session using the 7-point Likert scale of muscle soreness (Appendix 17) (Impellizzeri & Maffiuletti, 2007). Figure 7.1: Study Design Schematic Abbreviations: Ratings of Perceived Exertion (RPE), Capillary blood lactate (BLa), Profile of Mood States (POMS), Blood flow restriction with intermittent pressure (i-BFR), Blood flow restriction with continuous pressure (c-BFR), Repetitions (reps), 1 Repetition Maximum (1RM). 7.33

Semi-Structured Interviews Out of the twenty-one participants, a subsample of fourteen participants were randomly selected in the focus group interviews. The focus group interviews were arranged in the last week of the last experimental condition and were conducted in an undisturbed room in the Welkin Laboratories. The semi-structured interview protocol included questions regarding their preference among the three experimental exercise protocols, reasons for their preference, perceived adherence to each exercise protocols, and overall experience. Examples of questions were ‘Which exercise protocol did you prefer and why?’, ‘Which exercise protocol was more tolerable and why?’ (Appendix 18). Interviews were 189 audio-recorded with participant consent, and detailed notes were taken during the interviews to capture key points and responses. 7.34 Statistical Analyses All quantitative data were assessed for normality using Shapiro-Wilk test (Section 3.28), while differences

across conditions and time were investigated using a two-way (condition x time) repeated measures analysis of variance (ANOVA) (Section 3.28) In instances of non-normally distributed data, the Friedman test was applied (Section 3.28) For normally distributed data, means ± standard deviations (SD) are presented, while for non-parametric data, medians and interquartile ranges (IQR, Q3-Q1) are provided (Section 3.28) Statistical significance was set at a p-value of 005 Semi-structured interview data were analysed using thematic analysis (Braun & Clarke, 2006, Clarke & Braun, 2013). The analysis process involved six-phases; familiarization with the data, coding, generating themes, reviewing themes, defining and naming themes, and interpretation (Braun & Clarke, 2006; Nowell et al., 2017) Themes were identified based on recurring patterns and significant statements related to participants’ preferences, adherence, and experiences with the exercise protocols. The research

questions, outlined as the primary questions in the interview guide, directed the analysis. A theme was identified as a recurring pattern or significant meaning related to the research questions within the data. Individual statements were examined for their relevance to determine whether they represented a singular viewpoint or a common opinion among the focus group. Strongly positive or negative comments were recognized as indicators of shared opinions within the group (Krueger, 2014). Thematic analysis allowed for a comprehensive exploration of participants' perspectives, providing valuable insights into factors influencing adherence to different exercise protocols (Fereday & MuirCochrane, 2006). By systematically analysing qualitative data, this approach enhanced the understanding of participants' experiences and preferences, complementing the quantitative findings obtained from the cross-over randomized trial (Creswell & Plano Clark, 2018). 190 7.4 Results

7.41 Perceptual Responses A Friedman test revealed a significant difference in RPE across the three conditions (p<0.001, χ2 =130.744, df=11) over the four sets Subsequent post hoc comparisons with Bonferroni correction showed no significant RPE differences between the three conditions across all four sets (p>0.004) (Table 7.2, Figure 72) Furthermore, a significant difference was observed in pain, as indicated by the Friedman test (p<0.001, χ2 =117539, df=11) Post hoc pairwise comparisons with Bonferroni correction demonstrated that pain was significantly lower in the HL-RE condition in sets 1,3, and 4 compared to c-BFR (Set 1; p=0.002, z=-3055, Set 2; p=0008, z=-2656, Set 3; p=0003, z=-2936, Set 4; p=0004, z=-2.889) No significant pain differences were identified between i-BFR and HL-RE or c-BFR across all four sets (p>0.004) (Table 72, Figure 73) Finally, Friedman test revealed a significant muscle soreness difference across the three conditions over the four sets

(p<0.001, χ2 =53487, df=8) (Figure 74) Post hoc pairwise comparisons with Bonferroni correction showed no significant differences between conditions (24 hours post; HL-RE vs c-BFR, p=0.284, HL-RE vs i-BFR, p=0089, c-BFR vs i-BFR, p=0184, & 48 hours post; HL-RE vs cBFR, p=0299, HL-RE vs i-BFR, p=0300, c-BFR vs i-BFR, p=0115) Table 7.2 Pairwise comparisons of RPE and pain between conditions Set Comparison RPE (p) Pain (p) 1 HL-RE vs c-BFR 0.334 *0.002 HL-RE vs i-BFR 0.439 0.018 c-BFR vs i-BFR 0.73 0.446 HL-RE vs c-BFR 0.723 0.008 HL-RE vs i-BFR 0.459 0.118 c-BFR vs i-BFR 0.496 0.142 HL-RE vs c-BFR 0.927 *0.003 HL-RE vs i-BFR 0.793 0.35 c-BFR vs i-BFR 0.493 0.113 HL-RE vs c-BFR 0.253 *0.004 HL-RE vs i-BFR 0.131 0.010 c-BFR vs i-BFR 0.952 0.268 2 3 4 Abbreviations; HL-RE: high load resistance exercise, c-BFR: continuous Blood Flow Restriction, i-BFR: intermittent Blood Flow Restriction. 1 Data are non-parametric. Bonferroni-adjusted alpha

for 12 comparisons (3 conditions x 4 sets) for RPE and pain 2 Significance set at *p ≤0.004 191 Figure 7.2: A. Rating of Perceived Exertion (RPE) in Set 1, Set 2, Set 3 & Set 4 for high load resistance exercise (HL-RE), continuous pressure BFR condition (c-BFR) and for intermittent pressure BFR condition (i-BFR). The bar graphs capture the median and the white circles represent individual data points, with some on-top of each other. B. Individual data points in Set 1, Set 2, Set 3, & Set 4 for HL-RE C. Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR D. Individual data points in Set 1, Set 2, Set 3, & Set 4 for i-BFR 1 Values are reported as medians ± interquartile ranges (IQR). 192 Figure 7.3: A. Visual Analogue Scale for Pain in Set 1, Set 2, Set 3 & Set 4 for high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). The bar

graphs capture the median and the white circles represent individual data points, with some on-top of each other. 1 Values are reported as medians ± interquartile ranges (IQR). 2 Significant differences between conditions. B. Individual data points in Set 1, Set 2, Set 3, & Set 4 for HL-RE C. Individual data points in Set 1, Set 2, Set 3, & Set 4 for c-BFR D. Individual data points in Set 1, Set 2, Set 3, & Set 4 for i-BFR 193 Figure 7.4: A. Muscle Soreness Questionnaire data from baseline (before exercise), 24 hours post (Post24h) and 48 hours post (Post48h) for high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). The bar graphs capture the median and the white circles represent individual data points, with some on-top of each other. 1 Values are reported as medians ± interquartile ranges (IQR). B. Individual data points at baseline, Post24h, &

Post48 for HL-RE C. Individual data points at baseline, Post24h, & Post48 for c-BFR D. Individual data points at baseline, Post24h, & Post48 for i-BFR 7.42 Profile of Mood State (POMS)Questionnaire Friedman’s test revealed significant differences in total mood disturbance (TMD) (p=0.037, χ2 =16.400, df=8), anger (p=0007, χ2 =20953, df=8), tension (p<0001, χ2 =37204, df=8), and fatigue (p<0.001, χ2 =67346, df=8) subscales of POMS, whereas no significance was observed in depression (p=0.441), esteem (p=0580), vigour (p=0345), and confusion (p=0052) Follow up post hoc comparisons with Bonferroni correction identified no significant differences between conditions in TMD and anger scores (p>0.004) Tension significantly decreased only in the HL-RE from baseline to 60’ minutes post exercise (p=0.001), whereas fatigue significantly increased from baseline to 15 minutes post exercise in all three experimental conditions (HL-RE; p=0.003, c-BFR; p<0001, i-BFR;

p<0.001) (Figure 75) 194 Figure 7.5 POMS mood state scores in intermittent pressure BFR (a i-BFR, black line with triangle markers), in continuous pressure BFR (b. c-BFR, black dotted lines with diamond markers) and in high load resistance exercise (c HL-RE, black dashed lines with cycle markers). A. shows the TMD scores at pre, 15 minutes and 60 minutes post exercise B. shows the POMS subscales at pre-exercise across all three conditions C. shows the POMS subscales at 15 minutes post exercise (Post15’) across all three conditions D. shows the POMS subscales at 60 minutes post exercise (Post60’) across all three conditions Abbreviations; Total Mood Disturbance (TMD), Tension (Ten), Anger (Ang), Fatigue (Fat), Depression (Dep), Esteem (Est), Vigour (Vig), Confusion (Con). 1 Values are presented as medians, n = 21 2 * Significant differences within conditions 7.43 Cognitive Function Tests Stroop Test: No significant differences were observed between conditions at any time

point in reaction times (p=0.472) or correct answers (p=0273) as measured by the Stroop test before exercise, 10 minutes post exercise, and 60 minutes post exercise (Figure 7.6) 195 Figure 7.6 A. Reaction time in milliseconds (msec) in the Stroop test before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR), followed by individual responses during i) HL-RE, ii) c-BFR, & iii) i-BFR. B. Correct Answers in the Stroop test before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR), followed by individual responses during i) HL-RE, ii) c-BFR, & iii) i-BFR. The bar graphs capture the mean (Graph A) and median (Graph B) and the white circles represent individual data points, with some on-top of each other. 1 Values

in the bar graph A presented as mean ± SD 2 Values in the bar graph B presented as median ± IQR Mixed Stroop Task: No significant differences between conditions were identified in overall reaction times (p=0.780) (Figure 77), congruent (p=0665) and incongruent reaction times (p=0793) as measured by the Mixed Stroop task before exercise, 10 minutes post exercise, and 60 minutes post exercise (Figure 7.8) No significant differences between conditions were identified in the overall (p=0.515), congruent (p=0.129), or incongruent correct answers (p=0340) as measured by the Mixed Stroop task before exercise, 10 minutes post exercise, and 60 minutes post exercise (Figure 7.7, Figure 78) 196 Figure 7.7 A. Reaction time in milliseconds (msec) in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR), followed by individual

responses during i) HL-RE, ii) c-BFR, & iii) i-BFR. B. Correct Answers in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR), followed by individual responses during i) HL-RE, ii) c-BFR, & iii) i-BFR. The bar graphs capture the mean (Graph A) and median (Graph B) and the white circles represent individual data points, with some on-top of each other. 1 Values in the bar graph A presented as mean ± SD 2 Values in the bar graph B presented as median ± IQR 197 Figure 7.8 A. Congruent rection time in milliseconds (msec) in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR). B. Incongruent reaction time in milliseconds (msec) in the Mixed Stroop Task

before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR). C. Congruent correct answers in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR). D. Incongruent correct answers in the Mixed Stroop Task before (Pre), 10 minutes after (Post10), and 60 minutes after exercise (Post60) for high load resistance exercise (HL-RE), continuous pressure BFR (c-BFR) and intermittent pressure BFR (i-BFR). 1 The bar graphs capture the mean and the white circles represent individual data points, with some on-top of each other. 2 Data presented as mean ± SD in graphs A & B. 3 Data presented as median ± IQR in graphs C & D. 198 7.44 Brain-derived Neurotrophic Factor (BDNF) A repeated measures

ANOVA (condition x time) identified a significant interaction effect (F (2,18) = 3.875, p=004, η2=0301), and significant main effect of time F(1,19) = 22120, p≤0001, η2=0538), but the main effect of condition did not reach significance F(2,18) = 3.344, p=0058, η2=0271) Follow up post hoc comparisons with Bonferroni correction revealed that BDNF levels significantly increased from pre to post exercise in all three experimental conditions (HL-RE; p<0.001, c-BFR; p=0004, iBFR; p=001) Additionally, a significant difference was identified in the delta percentage changes (Δ%) between conditions, (F(2,18) = 6.952, p≤0001) Follow up comparisons with Bonferroni correction revealed that Δ% was significantly higher in c-BFR compared to both HL-RE (p = 0.04) and i-BFR (p=0.03) (Figure 79) Figure 7.9: A. Brain-derived neurotrophic factor (BDNF) data before exercise (Pre), and five minutes post (Post5’) in high load resistance (HL-RE), continuous pressure BFR during low load

resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). B. Delta Percentage Changes (Δ%) in the HL-RE (black bar), c-BFR (white bar), and i-BFR (dark grey bar) The white circles in A & B bar graphs represent individual data points, with some on-top of each other. C., D, & E represent the individual data from Pre to Post5’ for HL-RE, c-BFR, & i-BFR respectively 1 Values presented as mean ± SD 2 * Significant differences 199 7.45 Semi-structure Interviews Four themes were identified from the semi-structure interviews (Table 7.2) The four themes were ‘familiarity’, ‘tolerance’, ‘enjoyability’, and ‘pain’. Familiarity: The majority of participants (9 out of 14) expressed a clear preference for the HL-RE protocol. This preference was primarily due to their prior resistance training experience of at least 2 years, as they had not encountered BFR before participating in this study. Participant A stated, “I

preferred the high load because I have always been into heavy lifting, and it felt like I was really challenging myself.” This sentiment was echoed by several others, who emphasized the perceived effectiveness and familiarity of traditional resistance training methods. A smaller subset of participants (3 out of 14) preferred the i-BFR protocol because it was less challenging, while only one participant favoured the c-BFR for being the most challenging. Tolerance: When asked which of the three resistance exercise modalities they preferred (HL-RE, cBFR, or i-BFR), 9 out of 14 participants found the HL-RE more tolerable, mainly due to their familiarity with this type of exercise. Participant B mentioned, “I found HL-RE more tolerable mainly because I am more used to this type of exercise. I found the BFR modalities more challenging because the feeling of the pressure was not as nice.” Participants who preferred i-BFR noted that it was more tolerable and could foresee themselves

adhering to this type of exercise in the future. For example, Participant D said, “I prefer the i-BFR because it was more bearable, and I could see myself adhering to this type of exercise.” Enjoyability: Most participants (9 out of 14) found the HL-RE more enjoyable compared to the two BFR modalities due to their familiarity with this type of resistance exercise. Participant E stated, “I enjoy high load resistance training, especially when it is until failure because I feel I am doing a lot of work, and my muscles are working to the maximum.” However, when asked which of the two BFR modalities they preferred, the majority (13 out of 14) found i-BFR more enjoyable. Participant F commented, “I liked the intermittent BFR because it was more fun. It was nice to expect this deflation feeling during resting periods.” Pain: All participants found c-BFR the most painful of the three resistance exercise modalities and iBFR the least painful. Participant G remarked, “i-BFR was not

as painful as the continuous pressure BFR and high load resistance exercise. I could see myself adhering to intermittent BFR low load resistance training.” Another participant stated, “I definitely prefer the i-BFR compared to c-BFR because it was not so painful. I could still feel the pump without feeling like my limbs were going to explode with c-BFR.” 200 In conclusion, although the majority of participants preferred the HL-RE, this preference was mainly due to their familiarity with this type of exercise and their belief that it would lead to more positive musculoskeletal adaptations. Additionally, the majority of participants agreed that i-BFR was more tolerable, enjoyable, and less painful compared to both c-BFR and HL-RE. Table 7.3: Presentation of the themes Themes Frequency of occurrence Familiarity 9 Sample participant narratives ‘I am more used to it’ ‘It felt more familiar’ ‘I am heavy lifting for years and the feeling of the pressure in my legs was

very new to me’ Tolerance 10 ‘It was more tolerable because I am more used to it’ ‘I prefer i-BFR because it was more manageable’ ‘I found it more bearable’ Enjoyability 8 ‘I enjoyed it more because I was waiting for the breaks in between sets’ ‘It was more fun’ ‘I found it more pleasant’ Pain 14 ‘It was the most painful’ ‘I found it unbearable at some point’ ‘It was really uncomfortable’ 201 7.5 Discussion The aim of the present study was to investigate the acute effects of a novel, progressively intermittent pressure BFR protocol versus the traditionally prescribed continuous pressure BFR protocol and high load resistance exercise on perceptual responses, and adherence, mood, cognitive function, and BDNF levels. To the best of the authors’ knowledge, this is the first mixed methods study to examine these outcomes in a single investigation in the BFR literature. The findings suggest that the new intermittent BFR modality could be

more tolerable compared to both HL-RE and the traditionally prescribed cBFR, as although the majority of the focus group (9 out 14) preferred HL-RE due to their familiarity, 13 out of 14 participants reported that i-BFR was more tolerable than both HL-RE and c-BFR. This finding may suggest that additional familiarization sessions are beneficial for individuals who are accustomed to high load resistance training. Thus, the hypothesis that the new i-BFR would be more tolerable compared to both HL-RE and c-BFR was accepted. One of the key findings in the present study was that pain scores were significantly higher in c-BFR compared to HL-RE in Sets 1, 3, and 4 by approximately 20%, 33%, and 28%, respectively. These findings align with other studies in literature (Bell et al., 2018; Dankel et al, 2019) Specifically, a study conducted by Bell et al. (2018) reported significantly higher ratings of discomfort across all sets with low-load resistance exercise (15% of 1RM) with both 40% of AOP

and 80% of AOP compared to no BFR high-load resistance exercise (70% of 1RM). Similarly, Dankel et al (2019) found that ratings of discomfort were significantly lower in high-load resistance exercise (70% of 1RM) by 50% compared to BFR with 40% of AOP, and 100% compared to BFR condition with 80% of AOP. In the present study, it is worth noting that i-BFR pain scores were lower compared to c-BFR by approximately 12.5% and 11% in Sets 2 and 4, respectively, although this did not reach statistical significance. Studies investigating the pain and discomfort between i-BFR and c-BFR also reported higher pain and discomfort in the last sets with c-BFR. Specifically, Fitschen et al (2014) reported significantly higher pain scores in the last two sets in c-BFR compared to i-BFR (30% of 1RM, 4 sets of 30-15-15-15 with set pressure at 160 mmHg) by 21% and 26%, respectively, in young healthy adults. Additionally, Freitas et al. (2019) found significantly higher pain scores in c-BFR compared to

i-BFR (20% of 1RM) in sets 3 and 4 during leg press and knee extension exercises (4 sets of 30-15-15-15 repetitions). In contrast, pain in BFR conditions was not different from HL-RE (70% of 1RM) across all sets in fourteen young healthy males. A more recent study by Schwiete et al (2021) investigated the chronic effects of a sixweek intervention on perceptual responses between an alternative i-BFR (20% of 1RM), where the cuffs were inflated during resting periods (80% of AOP) and deflated during exercise sets, and the traditionally prescribed c-BFR. The study reported higher pain mid-intervention in the c-BFR (20% of 1RM at 80% of AOP), but not at the end of the intervention (3 weeks; c-BFR: 48.5 ± 146 vs i-BFR: 202 28.3 ± 145, p<005, 6 weeks; c-BFR: 442 ± 103 vs i-BFR: 28 ± 100, p>005) (Schwiete et al, 2021) These findings suggest that to the new i-BFR indeces less pain compared to c-BFR and HL-RE, particularly in the later sets. Future research should further explore

whether the reduced pain associated with intermittent BFR could improve long-term adherence to resistance training programs Another important finding of the present study was that there was no difference in RPE between the three conditions. These RPE findings align with those of Hollander et al (2010), who reported no significant differences in RPE scores between low-load resistance exercise (30% 1RM) with BFR at 100% of AOP and high-load resistance exercise (70% 1RM). Similarly, Schwiete et al (2021) found similar RPE responses between low-load resistance exercise (20% of 1RM) with continuous and intermittent BFR (80% of AOP) after a six-week training intervention (c-BFR: 14 ± 1.2, i-BFR: 139 ± 1.4, p>005) in recreationally trained healthy young males Contrary to these findings, other studies have reported significantly higher RPE responses following HL-RE protocols compared to low-load resistance exercise with BFR. For instance, Eonho et al (2014) observed significantly higher

RPE responses after knee extension and leg press exercises in HL-RE (70% 1RM, 2 sets x 10 + 1 set x failure) compared to low-load (20% 1RM, 3 sets x 30-15-15) with BFR (200 mmHg) in untrained young females. De Araujo et al (2017) also reported higher RPE responses following knee extension in HLRE (80% 1RM, 4 sets x 8 + 1 set x failure) compared to low-load (40% 1RM, 4 sets x 16 + 1 set x failure, 100 mmHg) in young, trained males. Similarly, Lixandrao et al (2019) noted higher RPE responses after HL-RE (80% 1RM, 4 sets to failure) compared to low-load (30% 1RM, 4 sets x 15) with BFR (50% AOP). Bell et al (2018) found higher RPE responses following biceps curls in HL-RE (70% 1RM, 4 sets to failure) compared to low-load (15% 1RM, 4 sets to failure) with BFR (40% AOP), but not with 80% AOP. In contrast, some studies have reported lower RPE responses in HL-RE compared to low-load BFR-RE. Brandner et al (2017) observed lower RPE following upper body exercises with HL-RE (80% 1RM, 4 sets x

6-8) compared to low-load (20% 1RM, 4 sets x 30-15-15-15) with intermittent BFR (130% SBP). However, they found no significant differences between HL-RE and continuous BFR (80% SBP) in untrained young males. Notably, Brandner et al. (2017) was the only study reporting significantly higher RPE responses in iBFR compared to c-BFR In contrast, Yasuda et al (2013) found significantly higher RPE scores in the last set (4 sets x 30-15-15-15) in c-BFR (160 mmHg) compared to i-BFR (160 mmHg). Neto et al (2017) also reported greater local and general RPE responses following upper and lower body exercises in HL-RE (80% 1RM, 3 sets x 8) compared to both low-load (20% 1RM, 4 sets x 30-15-15-15) with continuous BFR (1.3x SBP) and intermittent BFR (13x SBP) While the present study found no differences in RPE between the three conditions, the literature presents a range of findings, with some studies reporting higher RPE in high-load resistance exercise compared to BFR, and others showing no

significant differences. This variability across studies suggests that further research is needed to 203 determine the conditions under which different BFR protocols may influence perceived exertion and exercise adherence. The effects of BFR on muscle soreness emerged as a notable finding in this study. Although statistical significance was not reached between conditions, the i-BFR modality exhibited greater reductions in muscle soreness compared to both HL-RE and c-BFR 24 hours post exercise, and compared to c-BFR 48 hours post exercise, with reductions of approximately 10%. These findings align with Nielsen et al (2017), who reported no significant differences in muscle soreness between HL-RE (70% of 1RM, 4 sets to failure) and low-load (20% of 1RM, 4 sets to failure) with BFR (100 mmHg) in healthy recreationally active males. Similarly, Alvarez et al (2019) reported significantly higher muscle soreness 24- and 48-hours post-exercise in low-load (20% of 1RM) unilateral knee

extension with BFR (50% of AOP) from baseline, but no significant differences between BFR and HL-RE (70% of 1RM). In contrast, Shiromaru et al. (2019) reported significantly greater muscle soreness from baseline to postexercise in low-load (30% of 1RM, 3 sets x 15) with BFR (80% of AOP) but no significant difference from baseline to post HL-RE (80% of 1RM, 3 sets x 10). However, they found no significant differences between the two conditions. Brandner et al (2017) also found that both low-load (20% of 1RM, 4 sets x 30-15-15-15) BFR-RE modalities (continuous at 80% of SBP and intermittent at 130% of SBP) significantly increased muscle soreness 24-, 48-, and 72-hours post-exercise compared to HL-RE (80% of 1RM, 4 sets x 6-8). The findings on perceptual responses in the present study (RPE, pain, muscle soreness) and their comparisons with existing BFR literature are inconclusive due to high methodological heterogeneity. Variations in the study protocols include differences in resistance

exercise parameters such as the number of sets (2-4), repetitions (8-30 or to failure), resting periods (30-160 seconds), and loads (20-40% of 1RM for BFR and 60-80% of 1RM for HL-RE). Additional factors include BFR pressure application protocols (individualised versus non-individualised), BFR pressures (50-80% of AOP, 0.8-13 x SBP), and body musculature targeted (upper versus lower body Familiarisation with BFR-RE also varies. Neto et al (2017) reported that different exercises on the same body part can stimulate different perceptual responses and Schwiete et al. (2021) showed that chronic adaptation might change perception during BFR-RE. Additionally, it has recently been reported by systematic review, involving 21 studies with 352 healthy participants, that the use of sets until failure during low load resistance exercise with BFR compared to predefined repetition schemes can negatively impact perceptual responses, muscle damage markers, delayed muscle soreness scores, and

subsequently adherence (Queiros et al., 2021) Qualitative data from semi-structured interviews, included in this study for the first time sheds light on the participants' preferences and the reasons for these preferences. Experienced resistance-trained individuals in the present study, having trained for more than two years, mentioned that their familiarity with high-load resistance exercise played a pivotal role in their preference for traditionally prescribed 204 high loading compared to the novelty of BFR modalities. They also attributed their high pain scores in BFR modalities not to discomfort per se but to unfamiliarity. Additionally, they found the new intermittent BFR modality more tolerable, enjoyable, and adherable compared to continuous BFR. This mixed-method design, integrating qualitative and quantitative data, provides valuable insights into participant preferences. Nonetheless, further research is necessary to determine if the new intermittent BFR modality is

the optimal choice for individuals unable to tolerate high-load resistance exercise regimens. Incorporating both quantitative and qualitative data strengthens our understanding of perceptual responses and participants’ preferences in resistance exercise modalities. It also clarifies the inconsistency of the results in the literature. Moreover, it may offer insights into identifying the optimal BFR modality that would elicit similar physiological responses to traditional exercise regimens. An interesting novel finding of the present study was that BDNF levels significantly increased from baseline to 5 minutes post-exercise across all three resistance exercise protocols: 9% for i-BFR, 31% for c-BFR, and 11% for HL-RE. To the best of the authors’ knowledge, this is the first study investigating the acute effects of i-BFR compared to c-BFR and HL-RE on BDNF levels. The observed increases in BDNF align with several previous studies. For example, Marston et al (2017) reported a 12%

increase in BDNF following HL-RE in untrained young adults, while Arazi et al. (2021) documented a 17% increase in older adults. Church et al (2016) observed BDNF increases of 57% and 132% following high-intensity and low-intensity resistance training protocols, respectively. Yarrow et al. (2010) noted a 32% acute BDNF elevation and a 77% increase after a 5-week intervention Lira et al. (2020) reported BDNF increases ranging from 38% to 98% depending on the exercise protocol However, some studies have reported no significant BDNF changes. Schiffer et al (2009) found no significant BDNF alterations after high-load resistance training or endurance training. Similarly, Correia et al. (2010) and Goekint et al (2010) found no significant changes following resistance exercise protocols. Lodo et al (2020) and Quiles et al (2020) also reported no significant differences in BDNF levels across various resistance exercise conditions. Notably, the study by Du et al (2021) is the only one study -to

the authors’ knowledge- that specifically investigated BDNF responses during low-load resistance exercise with BFR. Their findings of BDNF increases of 60% and 53% following high-load without BFR and low-load resistance with continuous BFR exercises, respectively, in poststroke patients, highlight the limited exploration of intermittent BFR’s effects on BDNF. It is important to note here, the great variability in BDNF responses observed in the present studyparticularly the higher Δ% increases (~69%) in some participants under the c-BFR condition compared to others (~312%) which suggests the potential existence of 'responders' and 'non-responders' to BFR modalities (Pickering & Kiely, 2019), or the potential for a BFR response continuum existing. This variability highlights the need for a deeper understanding of the factors influencing these differential responses. Genetic differences, such as variations in genes related to muscle hypertrophy, angiogenesis,

and 205 metabolic pathways, could lead to different adaptive responses (Viecelli & Ewald, 2022). Additionally, individual differences in vascular endothelial growth factor (VEGF) expression, which is linked to BDNF production, might explain some of the variability observed (Du et al., 2021; Li et al, 2022; Ruggiero et al., 2011) Overall, while this study provides novel insights into BDNF responses to intermittent BFR, it also highlights the complexity of individual variability and the need for further research to elucidate the underlying physiological mechanisms. The impact of resistance exercise on mood remains a topic of considerable interest, with varying results reported across studies (Ferreira et al., 2013; Focht, 2002; Strickland & Smith, 2014; Xie et al, 2021). In the present study, total mood disturbance did not reach significance change from pre- to postexercise across any of the three experimental conditions However, tension significantly decreased from pre to 60

minutes post-exercise only in HL-RE. Similar findings have been reported in the literature (Ferreira et al., 2013; Focht, 2002; Focht & Koltyn, 1999; Focht & Koltyn, 2009, Garwin et al, 1997) Specifically, studies investigating the effects of resistance exercise on mood have reported no significant differences in mood and anxiety levels. Focht & Koltyn (2009) documented no significant difference in anxiety levels from pre to post high-load resistance exercise (75% of 1RM) in young resistance-trained males. Garvin et al (1997) similarly found no significant anxiety changes following resistance exercise (70% of 1RM) in sedentary young males. Ferreira et al (2013) found no significant differences in affective responses from pre to post eccentric exercise condition (90% of 1RM), concentric exercise condition (70% of 1RM), or dynamic exercise condition (70% of 1RM) in elderly untrained women. Additionally, Focht et al (2015) also found no significant differences in young females

between self-paced intensity resistance exercise and high-load resistance exercise (75% of 1RM). However, they reported that anxiety significantly decreased only in participants who reported high anxiety levels at baseline, independently of the resistance exercise protocol's intensity (high or self-paced loads). On the contrary, the results of the present study did not align with the majority of the existing literature demonstrating positive effects of resistance exercise on mood (Cavarretta et al., 2019; Gordon et al., 2018) Bartholomew and Linder (1998) found that low-load resistance exercise (40-50% of 1RM) reduced anxiety by 8.8% in males and 15% in females, whereas high-load resistance exercise (75-85% of 1RM) increased anxiety by 21.6% in males and 75% in females Herring and O’Connor (2009) observed a 17.5% increase in vigor scores after high-intensity exercise (70% of 1RM) and 147% after low-load exercise (15% of 1RM), with only the former reaching significance. Fatigue

was significantly reduced by 44.7% after low-intensity exercise compared to 20% after high-intensity exercise. McLafferty et al (2004) reported significant mood improvements over 24 weeks in older adults (60-77 years), with reductions in confusion (females: -23.44%, males: -5161%), tension (females: -35.29%, males: -4375%), anger (females: -5161%, males: -9333%), and total mood disturbance (females: -126.47%, males: -12055%) Chase and Hutchinson (2015) found significant and 206 similar improvements in tension, depression, confusion, and vigor in young adults after resistance exercise (3x12 at 30% of 1RM) and low-intensity aerobic exercise. Singh et al (1997) noted a 44% decrease in depressive symptoms after a 10-week high-load resistance exercise intervention in depressed elderly (60-84 years). Similarly, other studies investigating the effects of resistance exercise in clinical populations with diagnosed mood-related health conditions have shown that resistance exercise improves

mood state, anxiety, and depression (Aidar et al., 2014; Dalgas et al, 2010; Levinger et al., 2011; Penninx et al, 2002; Singh et al, 1997; Van Der Kooi et al, 2007) Only two studies to the authors’ knowledge have investigated the effects of BFR during low load resistance exercise on mood, yielding inconclusive results. Specifically, Ruaro et al (2020) investigated the effects of low-load resistance exercise (20% of 1RM) with short cuff BFR (7 cm arm, 12 cm legs) versus long cuff BFR (12 cm arm, 20 cm legs) on mood in active young males. They found that short cuff BFR significantly improved mood by reducing tension (-50%), depression (-50%), anger (-47%), and confusion (-42%). In contrast, long cuff BFR increased tension (29%) and confusion (31%) Vigor decreased in both short cuff (-22%) and long cuff BFR (-34%) conditions, while fatigue increased with short cuff (144%) and long cuff BFR (234%). Silva et al (2021) observed significantly higher fatigue scores post-exercise with

low-load (30% of 1RM, 4 x 30-15-15-15) and BFR (80% of AOP) by 169.2% compared to high-load (75% of 1RM, 3 x 10) without BFR, which increased fatigue by only 28.5% in athletes. The results of the present study, along with the existing literature, demonstrate inconsistencies in the effects of resistance exercise on mood, potentially due to methodological heterogeneity. Variations in exercise intensity (20-85% of 1RM), volume (different numbers of sets and repetitions), populations (trained, untrained, young, older, healthy, clinical), individual BFR response variability, BFR pressures, and BFR equipment (long vs. short cuffs) likely contribute to these discrepancies Furthermore, the semi-structured interviews revealed that participants preferred HL-RE, possibly because they were more familiar with this exercise modality as resistance-trained individuals. This preference might influence their mood responses. Another possible explanation for the lack of significant mood improvements in

the BFR modalities or in other subscales of POMS in HL-RE could be the low baseline scores of POMS subscales such as depression, confusion, anger, and total mood disturbances, leaving little room for improvement post-exercise. Notably, tension decreased in all three experimental conditions: HL-RE pre 2.64 to post 1 (-62%), c-BFR pre 236 to post 155 (-34%), and i-BFR pre 164 to post 1.09 (-33%), with lower mean tension scores observed in both c-BFR and i-BFR compared to HL-RE. These findings suggest that while certain mood subscales may not reach significance, individual components such as tension could potentially show meaningful changes, highlighting the complex nature of mood responses to different exercise protocols and BFR applications. Further 207 research is necessary to elucidate the specific factors contributing to these varied outcomes and to optimize the BFR resistance exercise protocols for mood enhancement. Interestingly, despite the varied intensity and nature of the

resistance exercise modalities employed in this study, cognitive function remained unchanged from pre to post exercise across all three conditions. These results align with those reported by Yamada et al. (2021), who found no significant differences in Stroop Test reaction times from pre to 11 minutes post-exercise with low load resistance exercise (30% of 1RM, 4 handgrip sets for 2 minutes with 1 minute rest between sets) with BFR (50% of AOP) or without BFR in young healthy adults. However, the results of the present study do not agree with those of Sardeli et al., (2018), who reported significantly lower reaction times post low load resistance exercise (30% of 1RM) with (50% of AOP, 4 sets x 30-15-15-15) and without BFR (4 sets x failure) compared to high load resistance exercise (80% of 1RM, 4 leg press sets x failure) in healthy untrained older adults (Sardeli et al., 2018) Although there were no significant differences in cognitive function between the three experimental

conditions, reaction times decreased in the Stroop test from pre to 60 minutes post exercise in all three conditions (HL-RE; -9%, c-BFR; -4, i-BFR; -4), and in the Mixed Stroop task (congruent reaction times: HL-RE; -5%, c-BFR; -11%, i-BFR; -9%, incongruent reaction times: HL-RE; -7%, c-BFR; -7%, i-BFR; -10%). Similar significant percentages have been reported in previous studies. More specifically, Chang & Etnier (2009) reported that an acute bout of six upper body exercises (2x10) at 75% of 1RM significantly improved the speed of processing by approximately 5% post exercise and showed a trend toward improved performance on an executive function task (mixed Stroop task) that requires shifting of the habitual response (~4%) in healthy adults aged 35-65 years (Chang & Etnier, 2009). Another study found that low load (40% of 1RM, 6 lower body exercises, 6x10) and high load (80% of 1RM, 6 lower body exercises, 6x10) resistance exercise resulted in significant decreases in

incongruent reaction times by 8% and 17% respectively, and in neutral reaction times by 5% and 10% respectively (Tsukamoto et al., 2017) Similarly, Alves et al (2012) observed a significant decrease in Stroop Test reaction times among older women following both aerobic (19% reduction) and resistance exercise (15% reduction). Chang et al (2014) found that acute resistance exercise at 70% of 1RM led to improved Stroop Test performance. Hsieh et al (2016) reported notable decreases in reaction times post-exercise for both young (-7.73% for in-set probes, -849% for out-ofset probes) and older adults (-741% for in-set probes, -596% for out-of-set probes), highlighting cognitive benefits of resistance exercise across age groups. Additionally, systematic reviews and metaanalyses have validated the cognitive benefits of resistance training, with improvements observed in attention, working memory, and cognitive flexibility (El-Kotob et al., 2020; Wilke et al, 2019) The Stroop test and mixed

Stroop task assess different aspects of cognitive function and engage distinct brain regions (Egner, 2011; MacLeod, 1991; Milham et al., 2003; West, 1996) The Stroop test primarily evaluates selective attention, cognitive flexibility, and response inhibition, engaging areas 208 such as the prefrontal cortex (Egner, 2011; MacLeod, 1991; Milham et al., 2003; West, 1996) Meanwhile, the mixed Stroop task adds additional cognitive demands like task switching and interference resolution, potentially involving a broader network of brain regions (Egner, 2011; Milham et al., 2003) The findings of the present study suggest that the new intermittent BFR modality could potentially be beneficial for specific brain regions, while high load resistance exercise or continuous BFR during low load resistance exercise might be advantageous for others. However, the limited existing literature on BFR during low load resistance exercise versus high load resistance exercise on cognitive function has

produced inconsistent results (Sardeli et al., 2018; Yamada et al, 2021) Moreover, meta-analyses investigating resistance exercise on cognition in various populations have shown variable effects (Coelho-Junior et al., 2022; Landrigan et al, 2020; Wilke et al, 2019; Zhang et al., 2020) Landrigan et al, (2020) noted positive effects on cognition but highlighted the need for further investigation into the variability. Similarly, Coelho-Junior et al, (2022) found improvements in overall cognitive function with resistance training in older adults but varied effects on specific cognitive domains such as short-term memory. Additionally, Wilke et al, (2019) reported acute cognitive enhancements post resistance exercise in healthy adults but emphasized the need for further exploration of factors influencing these effects such as age and training intensity. In conclusion, while resistance exercise, including BFR, shows promise in improving cognitive function, more research is needed to

understand the impact of different modalities on cognition and their impact on diverse populations. Systematic reviews like those by Li et al., (2018) and Herold et al, (2019) highlight the need for larger scale studies to elucidate the complexity of the underlying neurobiological mechanisms and optimize resistance exercise protocols for cognitive benefits (Herold et al., 2019; Li et al, 2018) 209 7.6 Limitations This study's generalizability is limited due to the homogeneous sample of young, resistance-trained males. This approach was intentionally chosen to minimize inter-individual variability and ensure consistent physiological responses, as including a more diverse population could have introduced heterogeneity, potentially confounding the findings. Future research should validate these results across broader populations, including females, older adults, and clinical groups. The crossover design, selected for its statistical robustness in facilitating within-subject

comparisons, inherently carries a risk of residual effects between conditions. To mitigate this, experimental sessions were separated by at least five days, a period exceeding the recovery durations reported in similar studies. While this interval minimized the likelihood of carry-over effects, subtle residual influences cannot be entirely excluded. Lastly, the study focused on acute responses to evaluate the novel i-BFR protocol, which has not been previously investigated. This allowed for direct comparisons with c-BFR and HL-RE Long-term adaptations, such as strength and hypertrophy, were not assessed, as establishing acute responses was a necessary first step before progressing to chronic research. These limitations reflect methodological decisions made to enhance the precision and relevance of the findings while acknowledging areas for future exploration. 210 7.7 Conclusions In conclusion, the findings of the present study highlight the potential of the new i-BFR modality

with progressively intermittent pressure to offer similar cognitive and mood benefits as both HL-RE and cBFR, while potentially improving adherence due to its lower pain and discomfort. In the present study, pain scores were significantly higher in c-BFR compared to HL-RE, while RPE and muscle soreness increased in a similar manner across all three conditions, with no significant differences between them. Participants preferred HL-RE due to familiarity yet found i-BFR more tolerable and less painful than both HL-RE and c-BFR. Moreover, BDNF levels increased significantly across all conditions, suggesting that i-BFR may stimulate beneficial responses related to mood and cognition, with reduced perceived exertion and discomfort. Future research should explore the long-term effects of i-BFR on cognitive, psychological, and physical adaptations across diverse populations. Furthermore, exploring the impact of familiarization sessions on the new intermittent BFR modality could further inform

exercise prescription and improve adherence in both clinical and healthy populations. Finally, future research is needed to investigate the underlying physiological mechanisms of the new intermittent BFR modality regarding muscle strength and hypertrophy adaptations, as this study primarily focused on perception, mood, and cognition. 211 8. Acute Study 2: ‘Intermittent BFR with progressive pressure: A viable alternative to Continuous BFR & high-load resistance exercise on acute metabolic responses in healthy adults’ 212 8.1 Abstract Introduction: Low-load resistance exercise with blood flow restriction (BFR) has gained attention as a viable alternative for enhancing muscle strength and hypertrophy, especially for individuals unable to tolerate high-load exercises. Continuous BFR has shown efficacy comparable to high-load resistance training, but it is often observed to cause discomfort and pain due to the sustained cuff pressure. Intermittent BFR, which alternates

pressure application with periods of release, may offer a more tolerable and adherable option, yet its underlying physiological mechanisms remain under-researched. This study aimed to investigate and compare a new, progressively increased intermittent BFR modality to the high load, resistance exercise and traditionally prescribed continuous pressure BFR on growth hormone (GH), insulin-like growth factor 1 (IGF-1), cortisol, and lactate responses. Methods: Twentyone healthy, resistance-trained males (ages 18-38 years) completed four sets of leg press to failure under three different conditions: high-load resistance exercise (HL-RE) at 70% of 1RM, continuous BFR (cBFR) at 30% of 1RM with a constant pressure of 50% of arterial occlusion pressure (AOP), and intermittent BFR (i-BFR) at 30% of 1RM with pressure gradually increased to 50% of AOP by the final set, while the cuffs were deflated during rest intervals. Venous blood samples for GH, IGF-1, and cortisol concentrations were collected

pre and five minutes post exercise. Capillary blood samples for lactate concentrations were measured pre and immediately post exercise. Results: GH concentrations increased significantly post-exercise in both BFR modalities, as indicated by repeated measures ANOVA (p =0.005) Bonferroni-adjusted post hoc comparisons showed significant increases in GH following i-BFR (p = 0.04) and c-BFR (p < 0001), with no significant change observed in the HL-RE condition (p = 0.623) Post-exercise GH levels were significantly higher in i-BFR compared to HL-RE (p = 0.004), with no other significant differences between conditions (p > 005) IGF-1 significantly increased in HL-RE (p = 0.018) and significantly decreased in c-BFR (p = 0021) post-exercise, while no significant change was observed in i-BFR (p = 0.126) Post hoc tests revealed significantly lower IGF-1 levels in c-BFR compared to both i-BFR (p=0.03) and HL-RE (p= 001) Although IGF-1 increased by 4.6% in the i-BFR, this change did not reach

statistical significance (p = 0061) Cortisol concentrations remained unchanged post-exercise across all conditions (p =0.129) Lactate concentrations significantly increased from pre- to post-exercise in all three modalities (p < 0.001), with no significant differences observed between them (p =0.830) Conclusion: Both i-BFR and c-BFR significantly increased GH, with a more moderate increase in i-BFR. IGF-1 increased significantly only in the HL-RE condition, while c-BFR resulted in a significant decrease. No significant differences in cortisol or lactate were observed between conditions. These findings highlight the distinct acute metabolic responses elicited by i-BFR and suggest its potential as a novel approach warranting further investigation to determine its long-term efficacy and adaptability. 213 8.2 Introduction Low-load resistance exercise with blood flow restriction (BFR) has emerged as a promising alternative modality for enhancing muscle strength and hypertrophy,

particularly for populations unable to tolerate high loading, such as clinical, elderly, and injured individuals (Chang et al., 2022; Fabero-Garrido et al., 2022; Kong et al, 2022) Traditionally, BFR has been prescribed using continuous pressure, which has demonstrated comparable positive musculoskeletal adaptations compared to the gold standard highload resistance exercise in various populations (Gronfeldt et al., 2020; Lixandrão et al, 2018) However, despite its efficacy, continuous BFR has been associated with discomfort and pain amongst young and healthy individuals as well as older and clinical populations, both trained and untrained, due to the constant pressure applied throughout exercise sessions, including rest periods (Bell et al., 2018; Brandner & Warmington, 2017; Parkington et al., 2022) In response to these challenges, intermittent BFR has been proposed as a more tolerable and adherable exercise regimen (Fitschen et al., 2014; Freitas et al., 2019; Neto et al, 2017)

Intermittent BFR involves periods of pressure application during sets with periods of complete release during resting periods, providing intermittent blood flow to the muscle being trained. Despite the potential perceptual and adherence-related advantages of intermittent BFR, research into its underlying physiological mechanisms remains limited, hindering a comprehensive understanding of its potential efficacy relative to continuous BFR. Building on conventional intermittent BFR, this study investigates a novel progressively incremental intermittent BFR (i-BFR) protocol, where cuff pressure gradually increases across sets instead of remaining constant. Inspired by Dr Yoshiaki Sato, the founder of BFR training, this stepwise pressure approach aims to reduce abrupt vascular and sensory stress, potentially lowering pain and afferent nerve activation. This gradual increase may improve tolerability and adherence while maintaining effective occlusion for muscle adaptations. To date, no

published research has explored the acute effects of this novel method, highlighting the need for further investigation into its physiological and perceptual benefits. Several underlying physiological mechanisms have been proposed to explain the efficacy of BFR during low load resistance exercise in promoting muscle adaptations, with metabolic stress, and mechanical tension suggested to play a primary role (Hughes & Patterson, 2020; Pearson & Hussain, 2015; Rossi et al., 2018) Specifically, the restriction of blood flow leads to localised hypoxia, resulting in the accumulation of metabolites that stimulate several physiological responses, such as hormonal secretions, crucial for muscle protein synthesis (Rossi et al., 2018) The buildup of metabolites, such as lactate, has been proposed to synergistically promote the secretion of growth hormone (GH) and insulin like growth factor-1 (IGF-1), which play a pivotal role in muscle strength and muscle mass adaptations 214 (Brooks,

2018; Lee, 2021; Rossi et al., 2018; Sharifi et al, 2020) These growth factor responses, particularly in GH and IGF-1, have been shown to be comparable between low-load resistance exercise with BFR and high-load resistance exercise without BFR (Bemben et al., 2022; Dong-il et al, 2016; Eonho et al., 2014; Sharifi et al, 2020) GH increases have been reported in the literature with a typical range of 68% to 86% for BFR conditions and 75% to 91% for high-load resistance exercise with noBFR (Eonho et al., 2014; Sharifi et al, 2020) Similarly, IGF-1 increases have been observed within a range of 14% to 26% in BFR conditions and 6% to 32% in high-load resistance exercise (Bemben et al., 2022; Dong-il et al, 2016; Laurentino et al, 2022) However, evidence from a limited number of studies investigating the effects of BFR and high-load resistance exercise with no-BFR on GH and IGF1 suggests that while BFR can elicit hormonal adaptations similar to those achieved with traditional high-load

resistance exercise, further research is needed to understand fully these responses. Nonetheless, BFR offers a practical alternative for promoting muscle growth and strength in populations unable to lift heavy loads (Gronfeldt et al., 2020; Lixandrao et al, 2018) In addition to GH and IGF-1, research has also focused on cortisol responses to resistance exercise, exploring comparisons between BFR and high-load resistance exercise (Bemben et al., 2022; Eslami et al., 2019) Cortisol, a hormone released in response to stress, plays a key role in muscle protein metabolism, such as modulating protein breakdown, influencing muscle repair processes, and potentially affecting overall muscle adaptation (Kraemer & Ratamess, 2005; Pedersen & Febbraio, 2012). Due to the multifaceted, complex nature of cortisol's effects, findings in the literature are more conflicting when investigating and comparing the effects of low load resistance exercise with BFR versus high-load resistance

exercise. Some studies report significant cortisol increases following both BFR and no BFR resistance exercise with no significant differences between the two modalities (Eonho et al., 2014; Eslami et al, 2019) Cortisol increases have been observed ranging from 11% to 32% in BFR and 19% to 36% in high load resistance exercise with no BFR (Eonho et al., 2014; Eslami et al, 2019; Laurentino et al., 2022) Conversely, other research has found no significant changes in cortisol levels following either BFR or no BFR modalities (Bemben et al., 2022; Vilaça-Alves et al, 2022) The conflicting evidence regarding cortisol responses in BFR literature underscores the need for further investigation to better understand the acute hormonal dynamics associated with these resistance exercise modalities and their potential implications for muscle adaptations. The majority of research on BFR during low load resistance exercise has concentrated on continuous pressure BFR protocols, with limited

investigation into intermittent BFR and its comparison to highload resistance exercise. Notably, Kalantari et al (2019) and Vilaca-Alves et al (2022) provided insights into the effects of intermittent BFR on growth factors. Kalantari et al (2019) found similar post exercise GH increases with continuous and intermittent BFR compared to high-load resistance exercise, although IGF-1 responses did not significantly differ across these conditions. Conversely, Vilaca-Alves 215 et al. (2022) observed significant GH increases of 2279% and 2073% for BFR and no-BFR conditions, respectively, with no significant differences between modalities. IGFPB-3 also increased similarly across conditions, while cortisol levels remained unchanged. In terms of lactate responses, studies show varied results. Freitas et al (2020) reported higher lactate increases following high-load resistance exercise (81%) compared to continuous (66%) and intermittent BFR (73%) conditions, with significant differences

between no-BFR and BFR modalities but no notable differences between the BFR conditions. Neto et al (2017) found significantly lower lactate concentrations with intermittent BFR (4.4% increase) compared to no-BFR (52% increase), but no significant differences between continuous BFR (5% increase) and the other conditions. Overall, while BFR, both continuous and intermittent, appears to elicit similar growth factor responses to high-load resistance exercise, with differing impacts on lactate concentrations, further research is needed to clarify the physiological mechanisms in order to optimize future BFR protocols. The aim of the present study was to compare the acute responses of key metabolic biomarkers lactate, GH, IGF-1, and cortisolto high-load resistance exercise, during the continuous BFR and a new intermittent BFR modality during low-load resistance exercise to enhance our understanding of the underlying physiology of BFR responses during resistance training. It was hypothesized

that there would be no significant metabolic differences following the three resistance exercise modalities. 216 8.3 Methods This study utilized a crossover experimental design, with participants being randomly allocated to one of three experimental conditions: high-load resistance exercise (HL-RE), low-load resistance exercise with continuous pressure blood flow restriction (c-BFR), and low-load resistance exercise with intermittent pressure blood flow restriction (i-BFR) (Section 3.7) 8.31 Participants Twenty-seven males, ranging from 19 to 38 years old (Table 7.1), all with prior resistance training experience, initially volunteered for the study (Section 3.21) A sample size of 19 participants was sufficient to achieve an 80% of statistical power (Section 3.91) Of the initial 27 participants, six withdrew due to personal reasons, leaving 21 participants who completed the study. However, one participant did not undergo venepuncture for venous blood sampling but provided

capillary lactate data and completed all the other assessments. Therefore, a total of 20 participants provided data for GH, IGF-1 and lactate concentrations. Among these 20 participants, data for the determination of cortisol levels was available for a sample of 13 participants. Participants attended the laboratories on five different occasions: one visit at the Moulsecoomb campus and four visits at the Welkin laboratories on the Eastbourne campus. The initial two visits were dedicated to preliminary data collection and familiarisation (Section 3.5) During the initial visit, participants received guidance on nutrition and exercise to ensure pre study and exercise standardisation (Section 3.4) There was a minimum interval of 48 hours between the initial preliminary visit and the third experimental visit. The experimental visits (3-5 visits) were scheduled with at least five days between each. 8.32 Experimental Procedures Preliminary testing & Familiarisation: During the initial

visit, participants completed medical questionnaires and consent forms (Section 3.21), followed by measurements of anthropometric data (Section 3.51) Individualised BFR pressures were determined (Section 353), and bilateral leg press 1 repetition maximum (1RM) was assessed (Section 3.54) After one hour rest period following the 1RM assessment, participants performed four sets of leg press to failure with a load at 30% of their 1RM, while wearing KAATSU bands inflated to 50% of their individualised BFR pressure for 217 familiarisation purposes. In the second visit, participants underwent a Dual X-ray Absorptiometry (DXA) scan to evaluate body composition, including lean mass and fat mass distribution (Section 3.52) Main Experimental trials: In the subsequent three visits, participants engaged in bilateral leg press exercises under three different conditions in a randomized order (Section 3.7) Following a 30-minute rest period in a supine position, capillary blood samples were

collected both before and immediately after each exercise session (Section 3.84) Venous blood samples were taken prior to the exercise and again five minutes after its completion (Section 3.81) Figure 81 illustrates the study design Figure 8.1: Study Design Schematic Abbreviations: Ratings of Perceived Exertion (RPE), Capillary blood lactate (BLa), Blood flow restriction with intermittent pressure (i-BFR), Blood flow restriction with continuous pressure (c-BFR), 1 Repetition Maximum (1RM). Immediately post exercise (IP). 218 8.33 Statistical Analyses Normality of the data was assessed with the Shapiro-Wilk test, while differences between conditions and time were evaluated using a two-way repeated measures analysis of variance (ANOVA) (Section 3.28) All GH, IGF-1, and cortisol data met the homogeneity of variance assumption, but were nonnormally distributed, hence data were log-transformed and subsequently met the normality assumption for parametric analyses described above

(Section 3.28) Statistical differences were investigated using log-transformed data but means ± SD of the non-log-transformed data were presented in figures to facilitate comparisons with existing literature. Pearson’s correlation coefficients were calculated to investigate the potential relationship between blood lactate concentrations on the GH responses and GH concentrations on the IGF-1 responses during the exercise conditions. 219 8.4 Results 8.41 Growth Hormone (GH) A repeated measures ANOVA (condition x time) identified a significant interaction effect for GH concentrations (F(2,18)= 7.370, p=0005, η2= 0450) Main effects were also significant for condition (F(2,18)= 4.033, p=0036, η2= 0309) and time (F(2,18)= 12246, p=0002, η2= 0392) Post hoc analyses with Bonferroni corrections revealed that GH concentrations significantly increased from pre-exercise to 5 minutes post exercise only in the two BFR modalities (c-BFR; p<0.001, i-BFR; p=0.04), but not in the HL-RE

(p=0623) (Figure 82) Additionally, GH levels were significantly higher five minutes post exercise in the i-BFR condition compared to the HL-RE (p=0.04) Figure 8.2: A. Growth Hormone (GH) data before exercise (Pre), and 5’ minutes post (Post5’) high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (iBFR). The white circles represent individual data points, with some on-top of each other B, C, & D, represent the individual data from Pre and Post5’ for HL-RE, c-BFR, & i-BFR respectively 1 Values presented as mean ± SD 2 * Significant differences. 220 8.42 Insulin-like Growth Factor-1 (IGF-1) A repeated measures ANOVA (condition x time) identified a significant interaction effect (F (2,18)= 6.249, p=0009, η2= 0410) Main effects were not significant for condition (F(2,18)= 1183, p=0329, η2= 0.116) and time (F(2,18)= 0271, p=0608, η2= 0014) Post hoc analyses with

Bonferroni correction showed that IGF-1 levels were significantly higher from pre-exercise to five minutes post exercise only in the HL-RE condition (p=0.018), significantly lower from pre to five minutes post exercise in the c-BFR condition (p=0.021), while no significant changes were observed in the i-BFR from pre to post exercise (p=0.126) (Figure 83) Additionally, post exercise IGF concentrations in the c-BFR were significantly lower compared to both HL-RE (p=0.01) and iBFR (p=003) post exercise Furthermore, a significant difference was identified in the delta (Δ%) between conditions (F(2,18)= 7.151, p=0007) Follow up comparisons revealed that Δ% was significantly lower in the c-BFR compared to both HL-RE (p=0.01) and i-BFR (p=003) (Figure 83) Figure 8.3: A. Insulin-like growth factor-1 (IGF-1) data before exercise (Pre), and five minutes post (Post5’) in high load resistance (HLRE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure

during low load resistance exercise (i-BFR). B. Delta Percentage Changes (Δ%) in the HL-RE (black bar), c-BFR (white bar), and i-BFR (dark grey bar) The white circles in A & B bar graphs represent individual data points, with some on-top of each other. C., D, & E represent the individual data from Pre to Post5’ for HL-RE, c-BFR, & i-BFR respectively 1 Values presented as mean ± SD 2 * Significant differences 221 8.43 Cortisol Repeated measures ANOVA revealed no significant main effects for condition (F(2,11)= 3.397, p=0071, η2= 0.382), or time (F(1,12)= 1855, p=0198, η2= 0134), and no significant interaction effect (F(2,11)= 2.485, p=0129, η2= 0311) (Figure 84) Figure 8.4: A. Cortisol data before exercise (Pre), and 5’ minutes post (Post5’) high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). The white circles represent individual data points,

with some on-top of each other. B, C, & D, represent the individual data from Pre and Post5’ for HL-RE, c-BFR, & i-BFR respectively 1 Values presented as mean ± SD 2 * Significant differences. 222 8.44 Lactate No significant interaction effect was identified in the two-way repeated measures ANOVA (condition × time) for lactate concentrations (F(2,19) = 0.188, p =0830, η² = 0019) Main effects were found for time (F(1,20) = 265.906, p < 0001, η² = 0930), but no significant main effect for condition (F(2,19) = 0.103, p =0903, η² = 0011) (Figure 85) Figure 8.5 A. Lactate data before exercise (Pre), and 5’ minutes post (Post5’) high load resistance (HL-RE), continuous pressure BFR during low load resistance exercise (c-BFR) and intermittent pressure during low load resistance exercise (i-BFR). The white circles represent individual data points, with some on-top of each other. B, C, & D, represent the individual data from Pre and Post5’ for HL-RE, c-BFR,

& i-BFR respectively 1 Values presented as mean ± SD 2 * Significant differences. 223 8.5 Discussion This study is the first study to the author’s knowledge to investigate the acute metabolic effects of a new progressively intermittent pressure BFR modality during low-load resistance exercise (i-BFR), comparing it to the traditionally prescribed continuous BFR (c-BFR) and high-load resistance exercise modality without BFR (HL-RE). The null hypothesis was partially accepted Specifically, GH levels significantly increased only in the BFR modalities, while remaining unchanged following HL-RE. Additionally, IGF-1 increased significantly only in HL-RE and decreased significantly in c-BFR, with no significant changes observed in i-BFR. No significant differences were found between the resistance exercise conditions in terms of cortisol and lactate concentrations following the three experimental conditions. One of the key findings in the present study was that GH significantly

increased only following the BFR modalities, by 182% (Δ% change) and 734% (Δ% change) for the new intermittent BFR and continuous BFR, respectively, while GH concentrations remained unaltered (5%) in the no BFR condition. This increase in GH with BFR is consistent with previous research, which has shown greater GH responses with BFR compared to no-BFR conditions during both high-load (Manini et al., 2012; Reeves et al., 2006) and low-load resistance exercise (Takarada et al, 2000; Patterson et al, 2013) One explanation for the greater GH increases observed with BFR compared to HL-RE could be that BFR enhances metabolic stress and muscle hypoxia during resistance exercise, thereby stimulating a more substantial GH release (Rossi et al., 2018) Resistance training without BFR is suggested to induce less metabolic stress compared to BFR (Rossi et al., 2018), which may account for the lack of significant GH increase in the HL-RE condition. Studies by Reeves et al (2006) and Manini et al

(2012) support these findings, demonstrating that BFR-induced metabolic stress results in a greater GH release compared to conventional resistance exercises. Additionally, the significant variability in GH responses within the BFR conditions, compared to the more consistent responses observed in HL-RE, highlights how individual factors such as muscle fibre composition, baseline hormonal status, and tolerance to metabolic stress can influence hormonal outcomes (Chikani & Ho, 2014; Qaisar et al., 2016) This variability suggests that BFR modalities create a distinct metabolic and hormonal environment, primarily driven by the hypoxic conditions that amplify metabolic stress and subsequent physiological responses (Rossi et al., 2018) While HL-RE induces GH secretion through mechanical stress and muscle fibre recruitment, the hypoxia associated with BFR triggers a cascade of physiological effects, including elevated lactate accumulation, intramuscular acidosis, and increased sympathetic

nervous system activation, all of which are potent stimulators of GH secretion (Chikani & Ho, 2014; Qaisar et al., 2016; Rossi et al, 2018) These additional metabolic stimuli likely contribute to the heightened and more variable GH response observed in BFR conditions. 224 Several physiological factors have been implicated in exercise-induced GH responses, including neural input, catecholamine stimulation, lactate, nitric oxide, and changes in acid-base balance (Godfrey et al., 2003) Among these, afferent stimulation, nitric oxide release, and lactate accumulation are considered key drivers of GH release during exercise (Chikani & Ho, 2014; Godfrey et al., 2003; Qaisar et al., 2016) In BFR modalities, where metabolic stress is heightened by restricted blood flow, the resulting local hypoxia may further amplify the accumulation of these metabolites compared to HL-RE (Rossi et al., 2018) During BFR, the partial pressure of oxygen (PO₂) in the restricted muscle decreases,

creating a hypoxic environment that potentially stimulates peripheral chemoreceptors (Freitas et al., 2021). These chemoreceptors, in conjunction with afferent sensory nerves, relay signals of metabolic stress to the central nervous system, promoting hormonal adaptations such as GH release (Freitas et al., 2021). The hypoxic conditions induced by BFR could also be further compounded by the Bohr effect, wherein the acidic environment caused by lactate accumulation reduces hemoglobin's oxygen affinity (Benner et al., 2018) This facilitates oxygen unloading and signals heightened metabolic demand (Benner et al., 2018) Although lactate increases in post-exercise were similar across all three experimental conditions, the unique metabolic environment created by BFR likely amplified the GH response (Brooks, 2018; Lee, 2021). In contrast, the absence of a significant GH response in the HLRE condition may suggest that, for these resistance-trained participants, the high-load protocol (70%

of 1RM) did not elicit sufficient hypoxia or metabolic stress to stimulate a robust hormonal release (Cadore et al., 2008) A notable finding in the present study was the differential response of IGF-1 across the experimental conditions. Specifically, IGF-1 increased significantly only after HL-RE by 5%, while it decreased by 11% following c-BFR. Although IGF-1 levels increased after i-BFR, this change did not achieve statistical significance. The literature presents conflicting reports regarding IGF-1 responses to resistance exercise protocols. Some studies report significant IGF-1 increases following resistance exercise (Abe et al., 2005; Bemben et al, 2010; Dong-il et al, 2016; Gregory et al, 2013; Yinghao et al., 2021), while others indicate significant IGF-1 decreases (Kraemer et al, 2017; Mitchell et al, 2013; Nindl et al., 2004; Nindl & Pierce, 2010; Tomeleri et al, 2020), or no significant IGF-1 changes (Kraemer et al., 1995; Laurentino et al, 2022; Manini et al, 2012;

Patterson et al, 2013) The variability in IGF-1 responses observed in all conditions contrasts with the more pronounced variability in GH responses within the BFR modalities. This discrepancy can be partially explained by the distinct physiological roles and regulatory mechanisms of GH and IGF-1. IGF-1 is primarily involved in promoting protein synthesis and muscle repair, with its secretion influenced by the availability of GH and other metabolic factors such as lactate accumulation, nitric oxide levels, and changes in acid-base balance (Chikani & Ho, 2014; Godfrey et al., 2003; Qaisar et al, 2016) These factors interact in complex ways to regulate IGF-1 release during and after exercise. 225 The timing of GH and IGF-1 responses also plays a crucial role in understanding their interaction. GH is released in pulses, typically peaking shortly after exercise, which stimulates the liver and other tissues to produce IGF-1. However, IGF-1 levels often peak several hours later,

reflecting the delayed effect of GH on IGF-1 production (Isley et al., 1983; Kraemer & Ratamess, 2005) Immediate post-exercise samples may show elevated GH but not yet elevated IGF-1 due to the time required for the liver to synthesize and release IGF-1 (Zhao et al., 2007) In contrast, samples taken several hours after exercise are more likely to show elevated IGF-1 levels, highlighting the sequential nature of these hormonal responses (Houghton et al., 1998; Reinecke et al, 2012) The significant increase in GH observed in the c-BFR condition, with a 734% rise, might indicate heightened metabolic stress that could influence IGF-1 dynamics. This, combined with the timing of blood sampling, could explain the observed variability in IGF-1 responses across conditions. Despite GH being a strong stimulant for IGF-1 release, the relationship between these hormones can be inconsistent (Amiri et al., 2021; Tsai et al, 2015) This inconsistency may be attributed to IGF-1’s multifaceted

roles in metabolism and recovery, which could be influenced by factors beyond GH alone, such as exercise intensity, metabolic stress, and individual physiological differences (Godfrey et al., 2003) The variability in IGF-1 responses observed in this study underscores the complexity of hormonal responses to different exercise modalities and highlights the need to consider both GH and IGF-1 interactions in understanding exercise-induced physiological adaptations. Given the use of validated assays and consistent sampling protocols, it is unlikely that the observed variability can be attributed to measurement error, further supporting the role of physiological and individual differences as contributing factors. Cortisol levels remained unchanged across all three resistance exercise protocols, aligning with the findings from the majority of studies on the acute effects of resistance exercise without BFR, as discussed in a recent systematic review by Anderson & Wideman (2017). They

highlighted the need for further research to understand fully the influence of exercise on cortisol and addressed several gaps in the literature, including the need to control exercise load and standardize sample collection and analysis methods. Additionally, the cortisol findings of the present study align with a study conducted by Vilaca-Alves et al., (2022), which reported no effect of high load (80% 1RM) multi-joint resistance exercise without BFR or low load (20% of 1RM) multi-joint resistance exercise with BFR (120% of SBPr) on cortisol concentrations post exercise regimens. However, our results differ from other BFR studies investigating the acute effects of high load resistance exercise compared to low load resistance exercise with BFR on cortisol responses (Bemben et al., 2022; Eonho et al, 2014; Laurentino et al, 2022). Specifically, Eonho et al, (2014) reported significantly higher cortisol concentrations following both BFR (20% of 1RM, set at 200mmHg) and no-BFR (80% of

1RM) resistance protocols by 19% and 12.5% respectively Laurentino et al, (2022) observed a time effect for increased cortisol concentrations in both BFR (20% of 1RM, 80% of AOP) and no-BFR (80% of 1RM) resistance 226 protocols by 17% and 19% respectively. Conversely, Bemben et al, (2022) reported decreases in cortisol concentrations immediately post exercise in BFR (20% of 1RM, 40-60mmHg) condition. Several hypotheses have been proposed in the literature to explain the reasons of unaltered cortisol levels following resistance exercise. These include factors such as exercise intensity, volume and the individual’s fitness level (Tremblay et al., 2005) Individual variability in hormonal responses to exercise, influenced by factors such as age, sex, and baseline cortisol levels can also affect how an individual’s cortisol levels may respond to exercise (Anderson & Wideman, 2017; Segerstrom et al., 2017). Additionally, some studies suggest that psychological stress and

perceived effort during exercise can influence cortisol responses (Rudolph & McAuley, 1998). Future studies should aim to address these variables, standardize protocols, and explore the effects of different exercise intensities and modalities on cortisol levels to provide a clearer understanding of these complex interactions. 227 8.6 Limitations The study has several limitations that should be considered, although these are balanced by deliberate methodological choices. Firstly, while the study focused on acute responses of GH, IGF-1, and cortisol, hormones widely used in resistance training literature, emerging evidence indicates that acute increases in these systemic hormones may not be causally linked to muscle hypertrophy or strength gains. Research by West et al., (2009, 2010, 2012), Morton et al, (2016), and Wilkinson et al, (2006) has demonstrated that muscle protein synthesis and hypertrophic adaptations can occur independently of systemic hormonal elevations,

highlighting the predominance of local mechanisms in driving these outcomes. Consequently, although the acute hormonal responses reported here provide insight into the physiological load imposed by each exercise modality, their relevance to long-term adaptation remains uncertain and should be interpreted with caution. Secondly, the study did not include other potentially informative biomarkers, such as testosterone and inflammatory markers (e.g, interleukin-6), which could provide further insights into the physiological responses. However, this is the first study investigating the acute physiological responses to muscle protein synthesis following the new i-BFR protocol, and the decision was made to focus on hormones commonly used in the literature to assess muscle protein processes, such as GH, IGF-1, and cortisol. Finally, the specific BFR pressure application method used may limit generalizability, although it served the purpose of evaluating the novel intermittent protocol in a

controlled and replicable way. Future research should explore variations in intermittent BFR modalities to further assess their impact on metabolic responses and examine chronic training outcomes alongside acute responses and incorporate molecular and local muscle markers to better understand the mechanistic pathways involved. 228 8.7 Conclusions In conclusion, the findings of this study offer valuable insights into the acute metabolic responses elicited by the novel intermittent BFR modality during low-load resistance exercise, high-load resistance exercise, and continuous pressure BFR. Notably, the new progressively increasing pressure, i-BFR modality resulted in similar increases in GH and lactate compared to continuous BFR, and a comparable, though not statistically significant, increase in IGF-1 to that observed with high-load resistance exercise. These findings suggest that the new i-BFR modality could serve as a viable alternative, especially for populations who cannot

tolerate high-load exercises or sustained BFR pressures, potentially optimizing exercise programming for individuals with exercise capacity limitations. However, further research is necessary to understand further the underlying mechanisms driving these responses and to refine the application of intermittent BFR protocols. 229 9. General Discussion 230 9.1 Study Aims, Key Findings, and Contributions to Knowledge in Blood Flow Restriction with Resistance Exercise Blood flow restriction (BFR) during low-load resistance training has garnered significant attention as an alternative exercise modality for enhancing muscle strength and hypertrophy, particularly for populations unable to tolerate high-load resistance training (HL-RT) (Gronfeldt et al., 2020; Lixandrao et al., 2018) Numerous studies have suggested that BFR combined with low-load resistance exercise can yield muscle strength and hypertrophy gains comparable to those achieved through traditional HLRT, but with much

lower mechanical stress on the joints and tissues (Rodrigo-Mallorca et al., 2021; Kong et al., 2022) This makes BFR particularly appealing for individuals such as older adults or those recovering from injury and clinical populations, who may be at risk of injury or discomfort from highload exercises (Zhang et al., 2022; Jørgensen et al, 2023) Despite these promising outcomes, the literature presents conflicting findings regarding the effectiveness of BFR for muscle adaptations. Some studies report similar muscle strength and hypertrophy gains between BFR and HL-RT, while others suggest that these gains may be lower with BFR (Gronfeldt et al., 2020; Lixandrão et al, 2018) One potential explanation for the variability in study outcomes regarding muscle adaptations and physiological responses is the methodological heterogeneity across studies, including variations in BFR application protocols, training duration, targeted muscle groups, populations, and individual responses to the BFR

stimulus. Moreover, the underlying physiological mechanisms driving muscle adaptation during BFR, although partly understood, still require further clarification. The primary mechanisms proposed during BFR resistance exercise include hypoxia-induced metabolic stress and mechanical tension, which synergistically stimulate the accumulation of metabolites such as lactate (Rossi et al., 2018) Hypoxia reduces the partial pressure of oxygen (PO₂) in the restricted muscles, triggering afferent sensory signals and activating peripheral chemoreceptors (Freitas et al., 2021) These mechanisms, combined with the Bohr effectwhere the acidic environment caused by lactate accumulation enhances oxygen unloading amplify metabolic stress and promote hormonal responses, including the release of growth hormone (GH), insulin-like growth factor 1 (IGF-1), cortisol, and testosterone, all of which play crucial roles in muscle protein synthesis and hypertrophy (Benner et al., 2018; Chikani & Ho, 2014;

Hwang & Willoughby, 2019; Rossi et al., 2018)Given these complexities, it was crucial in this PhD to explore further the efficacy and understanding of the underlying physiological mechanisms of BFR during resistance exercise, while controlling key methodological variables, and compare them to HL-RT. Recognizing the great variability in the studies outcomes, the first meta-analysis presented in this thesis (Chapter 4) aimed to control and systematically investigate these factors such as body musculature trained (upper versus lower body), training duration, BFR pressure application protocols (individualised 231 versus non-individualised) and BFR pressures based on the arterial occlusion pressure (AOP%) to provide a clearer understanding of the muscle strength and hypertrophy adaptations resulting from BFRRT compared to HL-RT. This meta-analysis was the first, to the authors’ knowledge, to control for the sole and combined effects of the aforementioned factors. It offers a

significant contribution by revealing that BFR-RT is as effective as HL-RT for increasing lower body muscle strength, particularly when interventions last eight weeks or longer in healthy adults aged 18–64 years. Moreover, when using individualized AOP, BFR-RT produced muscle strength gains comparable to those from HL-RT, with both methods leading to similar muscle mass increases. In addition to the long-term adaptations, understanding the acute physiological and perceptual responses to BFR is vital because these immediate responses, such as hormone secretion (i.e GH, IGF1, testosterone, cortisol) and metabolic byproducts like lactate, offer key insights into the mechanisms that drive muscle growth and adaptation over time (Ahtiainen et al., 2018; Rossi et al, 2018; Watson et al., 2022) Furthermore, acute responses such as perceived exertion and discomfort are critical in determining the tolerability and feasibility of BFR for different populations, as they directly influence

adherence to training protocols and the potential for injury prevention (De Queiros et al., 2023) By understanding these short-term effects, researchers and practitioners can optimize BFR protocols to ensure both efficacy and safety, particularly in settings where traditional high-load training may not be feasible. The second meta-analysis (Chapter 5) focused on the acute metabolic responses, such as GH, IGF-1, cortisol, and lactate levels, as well as ratings of perceived exertion (RPE), comparing BFR-RE to HL-RE. This analysis was particularly impactful because it intentionally excluded athletic, elderly, and clinical populations to minimize confounding variables related to age, disease, and training status. By focusing exclusively on young, healthy adults aged 18-35 years, it was aimed to control for these potential confounders and ensure that the observed effects were more attributable to the BFR-RE and HL-RE conditions rather than other factors. Notably, this was the first

systematic review and metaanalysis to investigate the acute effects of BFR-RE versus HL-RE on lactate concentrations and metabolic responses crucial for muscle protein synthesis in young, healthy adults. The results showed that BFR-RE induces similar acute hormonal responses as HL-RE, though with lower IGF-1 and lactate concentrations. Additionally, intermittent BFR-RE (i-BFR) appeared more tolerable than HL-RE, as evidenced by lower RPE responses, suggesting its potential as a more comfortable alternative for frail individuals while still maintaining the benefits of traditional resistance training. In continuance to the aforementioned work and promising findings on the effectiveness of BFR-RE, and based on the findings of the two meta-analysis it became evident that there was a need to investigate and optimise the BFR training with modalities that are potentially more tolerable and as effective to HL-RE. Hence, the experimental part of the thesis investigated the development of a new

intermittent BFR protocol. Unlike traditional BFR protocols, which maintain a constant pressure throughout the 232 exercise or intermittently deflate the pressure bands during rest periods, this novel protocol progressively increased the pressure during the exercise sets. The pressure was incrementally raised by 10 mmHg across four sets, starting at a lower level and reaching the target arterial occlusion pressure (AOP) of 50% by the final set. This progressive approach aimed to optimize the metabolic stimulus while improving tolerability, offering a more comfortable alternative to the constant or intermittent deflation methods commonly used in BFR protocols. To address these questions an exploratory pilot study was first conducted to compare the effects of the new, progressively increased pressure BFR (iBFR) with the traditional continuous BFR (c-BFR) on perceptual responses, mood, cognitive function, and blood lactate concentration and gain some early insights that would later be

investigated to a greater depth and with a more complete research design. The originality of this pilot study lay in the exploration of the perceptual, mood, and cognitive effects of a novel i-BFR modality, making it one of the first studies to investigate the potential cognitive benefits. Using an exploratory approach, participants completed perception measurements (RPE and pain scales) at the end of each set, followed by mood assessments using the POMS questionnaire before and after exercise. Cognitive function was evaluated through the Stroop test conducted before exercise, and post-exercise. Additionally, lactate levels were measured before and after exercise. The preliminary findings suggested that i-BFR could be more tolerable than c-BFR, with potential additional benefits for mood and cognitive function. This shows potential for broader applicability in populations that may struggle with traditional high-load or continuous BFR protocols, such as frail individuals, while

potentially enhancing cognitive function without compromising the musculoskeletal benefits observed with c-BFR. However, as this was a pilot study, further research was warranted to explore the new i-BFR modality, especially through the inclusion of qualitative data, which can provide deeper insights into participants’ experiences, behaviours and perceptions beyond the limitations of the RPE and pain scales. Additionally, measuring biomarkers of cognitive function, such as brain-derived neurotrophic factor (BDNF), in conjunction with computerized cognitive function tests, as well as GH, IGF-1, cortisol for the investigation of the underlying physiology of musculoskeletal adaptations should be included, along with comparisons to HL-RE. In light of these findings, subsequent studies were designed and included in this PhD to build on this first experimental pilot research study, (Chapter 6) and provide more robust evidence on the effectiveness, tolerability, cognitive benefits, and

mood-enhancing effects of the new i-BFR protocol with a larger population sample. The first acute experimental study (Chapter 7) aimed to investigate the new i-BFR modality versus c-BFR and HL-RE on perception, mood, and cognition, using both qualitative and quantitative measures, including measuring the BDNF responses to i-BFR, c-BFR, and HL-RE protocols. To the best of the authors’ knowledge, this was the first mixed-methods study to combine subjective and objective measures to evaluate the psychological and cognitive impacts of BFR modalities, and particularly, the new intermittent protocol, providing a more holistic understanding of 233 their effects. The findings indicated that the new i-BFR could be a more tolerable and adherable option compared to both HL-RE and c-BFR. Additionally, i-BFR could potentially stimulate BDNF increases and its related beneficial effects on cognitive function and mood at similar levels to both HL-RE and cBFR, but with lower perceived pain and

discomfort, further supporting its promise as a more comfortable alternative. Building on the foundational research from previous studies, the second acute study (Chapter 8) aimed to compare the physiological responses of the new i-BFR protocol with those of c-BFR and HLRE. This phase of the PhD focused on assessing whether i-BFR would stimulate similar acute physiological responsesspecifically GH, IGF-1, cortisol, and lactaterelated to muscle protein synthesis as observed in HL-RE and c-BFR. By exploring these comparisons, this study sought to evaluate further the efficacy of the new i-BFR protocol while contributing to a deeper understanding of its potential benefits in resistance training. The results indicated that both i-BFR and c-BFR significantly increased GH levels, suggesting that i-BFR may effectively stimulate hormonal responses associated with muscle growth, similar to c-BFR, although using a more progressive occlusion pressure that might be more comfortable for the

participants. However, IGF-1 levels increased only in the HLRE condition, while i-BFR demonstrated a meaningful increase, and c-BFR led to a decrease These variations highlight a critical difference in how each modality influences IGF-1, a key factor in muscle protein synthesis, thereby demonstrating the need for further research to better understand the underlying mechanisms and potential implications for resistance training protocols. Table 9.1 presents a summary of all the research hypotheses tested within the thesis and indicates whether they were accepted or rejected. While the table provides a detailed overview, key findings are discussed below to contextualize the results. Collectively, these findings advance our understanding of BFR-RE, particularly in terms of perceptual responses and hormonal adaptations. The new i-BFR modality shows promise as a lower-load alternative, with lower acute perceptual responses compared to c-BFR and HL-RE. However, further research is required to

explore its full potential and optimize its application across diverse populations. Table 9.1 presents a summary of all the research hypotheses tested within the thesis and indicates whether they were accepted or rejected. While the table provides a detailed overview, key findings are discussed below to contextualize the results. Collectively, these findings contribute to the understanding of BFR-RE, particularly in terms of acute perceptual and hormonal adaptations. The new i-BFR modality shows promise as a lower-load alternative, with lower acute perceptual responses compared to c-BFR and HL-RE. In conclusion, this thesis provides evidence that i-BFR could be a feasible alternative to c-BFR and HL-RE, offering comparable physiological responses with better tolerability and potential cognitive benefits. Future research should investigate the long-term efficacy of i-BFR and its broader implications for cognitive and musculoskeletal health. 234 235 9.2 The new progressively

increased pressure intermittent BFR modality: Physiological Responses, Participants Insights & Practical Applications This section explores the utility, advantages, and potential limitations of the new i-BFR protocol, highlighting the unique characteristics of this modality in comparison to the traditional c-BFR approach. By analysing the distinct features of the progressively increased pressure used in i-BFR, this section aims to provide a comprehensive understanding of the physiological and perceptual responses elicited during exercise under controlled conditions, its efficacy, and its practical applications. 9.21 Introduction of the New intermittent BFR Modality The majority of studies investigating the chronic and acute effects of BFR on muscle adaptations (Gronfeldt et al., 2020), physiological responses (Bemben et al, 2022; Freitas et al, 2020), and perception (Aniceto et al., 2021; Bell et al, 2018) have predominantly focused on continuous pressure BFR. Although BFR has

been shown to be a more tolerable and viable option for frail populations unable to handle high loads (Miller et al., 2020; Neto et al, 2018), it can still induce beneficial musculoskeletal adaptations similar to those observed with traditional high-load resistance training (7095% of 1RM) but at much lower loads (20-30% of 1RM). However, due to the constant pressure applied during BFR-RE, it has been reported that perceived exertion and discomfort can be higher (Bell et al., 2018) or similar to HL-RE in some sets (Aniceto et al., 2021) To mitigate these challenges, researchers have explored alternative BFR modalities, such as applying pressure intermittently (Freitas et al., 2019; Brandner & Warninghton, 2017). Most studies investigating intermittent BFR have used protocols where pressure is applied during exercise sets and released during rest periods (Sinclair et al., 2022), with one notable exceptionwhere pressure is inflated during rest and deflated during exercise (Schwiete et

al., 2021) To the authors' knowledge, the experimental studies conducted as part of this PhD are the first to investigate the acute effects of a new progressively intermittent pressure BFR. In this novel i-BFR modality, the cuff pressure is progressively increased in a stepwise manner across four sets of resistance exercise. The pressure begins 30 mmHg below the target level and is increased by 10 mmHg after each set. For example, if 50% of a participant's arterial occlusion pressure (AOP) is 200 mmHg, the first set starts at 170 mmHg, the second at 180 mmHg, and the third at 190 mmHg, with the final set reaching 200 mmHg, corresponding to 50% of AOP. This incremental approach is designed to enhance tolerability while ensuring sufficient occlusion for musculoskeletal adaptations, in contrast to the fixed pressure used in continuous BFR. The rationale for this approach is rooted in the historical development of KAATSU training, first envisioned by the founder of BFR training

Dr. Yoshaki Sato in Tokyo in 236 1966 (KAATSU Global Ltd, 2024). Dr Sato introduced the KAATSU progressively increased pressure i-BFR in 1973, claiming that this new BFR modality could induce similar and advantageous musculoskeletal adaptations compared to continuous BFR, but with less pain and discomfort (KAATSU Global Ltd, 2024). However, there is currently no formal research supporting these claims Therefore, the current PhD experimental studies aimed to address this gap by evaluating the efficacy and tolerability of this novel protocol. 9.22 Exploring Individual Variability in Perceptual and Metabolic Responses: Insights from the New Intermittent BFR Modality Individual variability plays a crucial role in the effectiveness of novel exercise protocols, and the new intermittent BFR (i-BFR) protocol, with its progressive pressure application, likely induces diverse physiological and perceptual responses across individuals, as demonstrated in this PhD project. This section delves

into the variability observed in perceptual measures, cognitive function, mood, biochemical markers like lactate, and hormonal responses, and offers potential physiological explanations for these differences. By examining these factors, a clearer understanding can be gained of how i-BFR impacts individuals differently, as demonstrated throughout the experimental chapters of this thesis. Perceptual Responses: Individual variability in RPE and pain perception was significant in the new iBFR protocol, providing valuable insights into how progressive pressure influences these responses. In the Pilot Study, where resistance-untrained participants performed controlled repetitions, the IQR for RPE ranged from 1 to 1.75 across four sets, indicating relatively consistent perceived exertion despite gradual pressure increments. However, pain perception exhibited greater variability The IQR for pain was notably higher, particularly in the later sets, with values reaching 2.75 in Sets 2 and 4 This

suggests that discomfort increased as the protocol progressed, likely due to the rising pressure levels, and highlights the heterogeneous pain experiences among participants. The mean IQR for pain across all sets was 2.3, further illustrating the diversity in responses within the small sample These findings align with previous studies showing increased variability in perceptual responses with intermittent BFR compared to continuous BFR (Freitas et al., 2019; Neto et al, 2017) In contrast, in Acute Study 1, where resistance-trained participants performed leg presses to failure, the IQR for RPE remained more consistent at 2 across all sets. The failure-based protocol likely led to more uniform exertion levels across participants, reducing variability. Pain perception also showed less fluctuation compared to the Pilot Study, with values peaking at 3 in all four sets, suggesting that resistance-trained participants may have been better equipped to handle discomfort due to their training

237 experience. This reduced variability indicates that the progressive pressure in i-BFR might have become more tolerable with repeated exposure, allowing participants to adapt to the discomfort. The variability in perceptual responses observed in both studies can be explained by several physiological and psychological factors. Physiologically, variations in muscle perfusion, nerve compression, and ischemia due to progressive pressure likely contributed to differing pain responses, modulated by individual pain tolerance (Burtscher et al., 2023; Joyner & Casey, 2017; Patterson et al, 2019). The intermittent pressure increases in i-BFR could have caused dynamic fluctuations in muscle oxygenation and neural feedback, which would result in a broad range of perceptual responses. Some participants might have experienced discomfort earlier or later depending on their sensitivity to ischemia (Freitas et al., 2020; Neto et al, 2017) Additionally, the intermittent deflation and

restriction might have induced varying levels of peripheral fatigue, affecting the onset of discomfort (Marcora, 2009; Norbury et al., 2022) Psychological factors likely also played a role in the variability of pain perception. Unfamiliarity with the i-BFR protocol could have amplified discomfort anticipation or induced psychological stress, particularly in untrained participants, who may have experienced the protocol differently than resistance-trained individuals (Teixeira et al., 2022) Insights from semi-structured interviews revealed that while participants favoured HL-RE due to its familiarity, both HL-RE and c-BFR were perceived as more painful than i-BFR. This suggests that the progressive nature of i-BFR, with its intermittent pressure, may have helped mitigate discomfort over time, offering a psychological reprieve compared to the constant pressure in c-BFR or the higher intensity of HL-RE. This aligns with research indicating that individualized arterial occlusion pressure

(AOP) does not always create consistent stimuli across participants (Stanford et al., 2022) The variability in perceptual responses in these studies underscores the complex interaction between physiological stressors and psychological factors, particularly in protocols like i-BFR that involve progressive pressure. Understanding this variability is key to optimizing BFR protocols for different individuals, thus enhancing both performance and adherence. Mood, Cognitive Function, and BDNF: Individual variability was also observed in mood and cognitive function across the Pilot Study and Acute Study 1, though the differences were not as pronounced. Total Mood Disturbance (TMD) scores were relatively consistent, with SDs of 7 and 8, respectively, suggesting that mood responses were not significantly influenced by the resistance exercise protocols used. Previous research has shown that different resistance exercise protocols can affect mood in varying ways (Ferreira et al., 2013; Focht,

2002; Strickland & Smith, 2014; Xie et al, 2021), but the findings here suggest that keeping exercise intensity, resting periods, and BFR modality constant may not substantially alter mood outcomes. The variability in TMD scores, however, suggests that mood 238 responses to i-BFR can still differ between individuals, highlighting the need for personalized approaches to optimize mood benefits. In cognitive function, the variability in Stroop test performance was minimal between the two studies (SDs of 120 ms vs. 130 ms), with a 10 ms difference Studies like those by Yamada et al (2021) and Sardeli et al. (2018) suggest that cognitive responses to resistance training modalities can vary, although the overall impact on cognitive function remains small. Differences in mood and cognitive function may reflect baseline individual differences, such as anxiety levels, which can significantly influence exercise outcomes (Focht et al., 2015) The consistency in variability between the two

studies (using fixed repetitions in untrained individuals vs. failure-based protocols in trained individuals) implies that factors like pressure progression and modality, rather than training experience or repetition schemes, may play a more significant role in determining mood and cognitive responses. Despite limited research on mood and cognitive outcomes during BFR, these results suggest that the intermittent nature of iBFR may provide a more tolerable and mood-stabilizing alternative, possibly contributing to more consistent cognitive performance post-exercise, potentially due to enhanced cerebral oxygenation (Burtscher et al., 2023) BDNF concentrations also exhibited individual variability, with post-i-BFR values averaging 15 ng/ml (SD = 3 ng/ml). This variability is consistent with previous studies investigating BDNF responses to both BFR and non-BFR resistance exercise modalities. For instance, Du et al (2021), the only study to investigate BDNF during low-load resistance

exercise with BFR, reported similar BDNF concentrations (13 ng/ml, SD = 3 ng/ml). Other studies in resistance exercise without BFR showed lower BDNF values (4–5 ng/ml, SDs = 2 ng/ml), while studies by Yarrow et al. (2010) and Lira et al (2020) reported greater variability (18–37 ng/ml, SDs from 6 to 13 ng/ml). These findings suggest that while the variability in BDNF responses to i-BFR mirrors the broader literature, the degree of variability remains within a typical range for resistance exercise. The variability observed in BDNF responses likely reflects diverse physiological responses to intermittent hypoxia, which modulates BDNF production (Meng et al., 2020) This variability could explain the differences in mood and cognitive outcomes across participants, highlighting the varying degrees of adaptation to the novel i-BFR protocol. Factors such as training status, familiarity with the protocol, and psychological responses may influence individual outcomes (Bird et al., 2005)

Physiologically, intermittent hypoxia can activate neuroendocrine responses that overlap with mental stress pathways, stimulating the sympatho-adrenomedullary system and the HPA axis (Burtscher et al., 2023). This could explain why some participants experienced mood improvements post-i-BFR, while others showed minimal changes, particularly during failure-based protocols. Additionally, intermittent hypoxia may affect cognitive function by enhancing cerebral blood flow and oxygen delivery (Burtscher et al., 2023; Hoiland et al, 2016), which could contribute to the stable cognitive performance observed 239 after i-BFR. The greater variability in BDNF responses following i-BFR compared to c-BFR (15 ng/ml, SD = 2 ng/ml) and HL-RE (15 ng/ml, SD = 2 ng/ml) might reflect individual differences in sensitivity to hypoxia. Biomarkers such as hypoxia-inducible factor-1 (HIF-1), heat shock protein 70 (HSP70), and nitric oxide (NO) are key regulators of hypoxic responses and could influence how

individuals adapt to the localized hypoxia induced by BFR (Dzhalilova & Makarova, 2020). Participants with higher hypoxic tolerance, indicated by elevated levels of HIF-1 or HSP70, may show more consistent BDNF and mood responses, while those with lower tolerance might experience greater fluctuations. This variability in physiological markers, combined with individual differences in neuroendocrine responses, highlights the complexity of how intermittent BFR impacts cognitive and mood outcomes. These findings underscore the interplay between hypoxia, stress responses, and individual physiology in shaping cognitive and mood outcomes with i-BFR. While variability in BDNF responses highlights the need for tailored approaches, the tolerability and stable mood and cognitive performance suggest that the new i-BFR is a promising and more accessible alternative to c-BFR or HL-RE. Further research is needed to optimize this protocol for personalized benefits. Metabolic Responses: The

variability in individual metabolic and hormonal responses observed in this PhD project highlights the complexity of physiological reactions to different exercise modalities. Factors such as genetic predisposition (Bouchard et al., 2011), training status (Kraemer & Ratamess, 2005), and environmental influences like circadian rhythms (Hackney, 2006) and psychological stress (Hill et al., 2008) contribute to this diversity This study revealed notable variability in growth hormone (GH), insulin-like growth factor-1 (IGF-1), and cortisol levels, emphasizing the influence of individual differences on metabolic regulation, muscle recovery, and adaptation, whereas lactate responses showed less variability than hormonal markers, reflecting potentially their close association with metabolic demand and muscle recruitment (Brooks, 2020). In both the Pilot and Acute Study 2, lactate responses were consistent, averaging approximately 8±3 mmol/L for both i-BFR and c-BFR and 9±2 mmol/L for

HL-RE, reflecting potentially consistent metabolic stress across conditions. This consistency aligns with findings from other studies (Bemben et al., 2022; Eonho et al, 2014; Manini et al, 2012; Valerio et al, 2018), although Freitas et al (2019) reported greater variability in i-BFR compared to c-BFR. The standardized 1RM percentages and rest intervals used in both the Pilot and Acute Study 2 likely contributed to the stable lactate responses observed (Brooks et al., 2020) In contrast, hormonal responses displayed substantial individual variability. For GH, participants using in the i-BFR had a mean response of 0.4 ng/mL (SD: 034), with some experiencing significant increases while others did not. This variability exceeds that reported in traditional c-BFR studies, which documented more consistent post-exercise GH levels (Eonho et al., 2014; Manini et al, 2012; Sharifi 240 et al., 2020) IGF-1 responses in the i-BFR participants were similarly variable, with a mean of 46 ng/mL (SD:

13), but lower than the averages reported in other studies using c-BFR (Bemben et al., 2022). Cortisol levels also displayed moderate variability in the i-BFR modality (mean 182 ng/mL, SD: 122), considerably higher than those reported by the literature (Eohno et al., 2014; Reeves et al, 2006) Notably, all studies in the literature investigating these hormones employed continuous BFR, whereas the present study utilized the novel progressively intermittent BFR modality, complicating direct comparisons. The variability in hormonal responses observed with the novel i-BFR protocol can be attributed to a combination of physiological, psychological, and methodological factors. Individual sensitivity to exercise-induced stress, influenced by factors such as metabolic adaptations from prior training (Godfrey et al., 2003), perceived exertion, and discomfort during exercise, plays a significant role (Morton et al., 2009) The pulsatile nature of hormonal secretion, particularly for GH, adds to

this variability, as GH levels fluctuate naturally throughout the day and in response to exercise stimuli (Jenkins, 2001; Stanley et al., 2011) The alternating hypoxia and reperfusion cycles characteristic of iBFR likely stimulate GH release by inducing hypoxic stress, yet individual differences in tolerance to hypoxia and muscle engagement during exercise may amplify variability (Takarada et al., 2000; Rossi et al., 2018; Dzhalilova & Makarova, 2020) For IGF-1, the intermittent nature of i-BFR appears to mitigate the potential catabolic effects of continuous ischemia seen in c-BFR, which may impair IGF1 production due to sustained hypoxia (Takarada et al., 2000; Yasuda et al, 2010) By providing recovery periods during exercise, i-BFR may enhance anabolic potential, although differences in participants' metabolic health and physiological responses contribute to the observed variability (Burtscher et al., 2023) Similarly, cortisol responses reflect the distinct stress

mechanisms of the two BFR modalities. The fluctuating stress levels induced by i-BFR’s cyclical hypoxia likely led to moderate variability in cortisol secretion, whereas the continuous hypoxia of c-BFR elicits more stable responses due to prolonged metabolic stress (Wernbom et al., 2008; Hart et al, 2023) Collectively, these findings underline the unique physiological responses elicited by the novel i-BFR modality, emphasizing the need for further research to clarify its impact on hormonal regulation and its potential implications for optimizing exercise programming. In conclusion, this PhD project highlights the novel physiological responses elicited by the innovative i-BFR modality, offering valuable insights into its impact on hormonal regulation and metabolic stress. While the variability in GH, IGF-1, and cortisol responses underscores the complexity of individual physiological reactions to intermittent hypoxic stress, the consistency in lactate responses suggests a robust

metabolic demand across exercise conditions. These findings expand the understanding of iBFR’s unique mechanisms and emphasize its potential for tailored exercise programming Further 241 research is warranted to refine its application and explore its broader implications for health and performance. 9.23 Implications of The New Intermittent BFR Modality The application of the new i-BFR modality extends beyond academic research and holds significant potential across various sectors. The following recommendations aim to facilitate the integration of this approach into broader societal contexts: Policy: Advocacy for the integration of i-BFR into Government Health Initiatives: There exists a considerable opportunity to advocate for the incorporation of i-BFR exercise into government-funded health programs. Specifically, policymakers in the UK should consider a growing body of evidence that may recommend integrating this modality into rehabilitation protocols within healthcare

settings for clinical populations. While further studies are needed to fully establish its effectiveness, patients recovering from prolonged hospitalization, surgical procedures, or chronic conditions (such as severe COPD or obesity) may greatly benefit from i-BFR's potential to enhance muscle strength and mass without necessitating high-load resistance training. Moreover, i-BFR is potentially more tolerable and carries a reduced risk of injury compared to traditional high-load resistance exercise. This modality requires less equipment, minimizing the need for heavy weights that could contribute to health and safety concerns, thereby making it a safer alternative for vulnerable populations. Product Development: Enhancements to existing KAATSU C3 Devices: Manufacturers should consider increasing the maximum pressure of KAATSU devices from 400 mmHg to 800 mmHg. This adjustment would enable practitioners to determine more accurately an individual's AOP and prescribe exercise

based on precise percentages of AOP, thus enhancing both safety and effectiveness. Higher pressure thresholds could facilitate more tailored and effective applications of blood flow restriction training, particularly for individuals with varying fitness levels and rehabilitation needs. However, to ensure safety, such devices should be designed for use exclusively by qualified practitioners or individuals who have received proper training from the KAATSU company. This precaution is essential, as applying higher pressures without adequate knowledge of the implications could pose risks to the general population. By offering a specialized version of the device for trained professionals much like how selfautomated defibrillators work, the potential for safer implementation of higher-pressure protocols could be maximized, thereby minimizing associated risks while optimizing the therapeutic benefits of i-BFR training. Additionally, the integration of embedded sensors to monitor muscle oxygen

saturation in the KAATSU C3 device would provide significant advantages. Firstly, real-time monitoring would enable 242 practitioners to make immediate adjustments to the exercise intensity and pressure settings, ensuring that users remain within safe physiological parameters. This capability would enhance user safety and optimize training outcomes by minimizing the risk of over-restriction or inadequate blood flow. Secondly, the data collected from these sensors would facilitate the individualization of BFR protocols. By analysing the physiological responses of users during training, practitioners could tailor exercise regimens to better align with each individual's unique needs and capacities. This personalization would not only improve the effectiveness of the BFR training but also promote adherence by ensuring a more comfortable and engaging experience for the user. Overall, the incorporation of these advanced monitoring features would enhance the functionality,

applicability, and utility of the KAATSU C3 device across diverse populations. Practice/Practitioners: Guidelines for Occupational Therapists, Physiotherapist, Sports Therapist, Personal Trainers, Sports Scientists, and Coaches: Acknowledging that more research is needed before what is currently known can be translated into practice, practitioners should adhere to evidence-based guidelines to maximize the benefits and minimize the risks associated with implementing the new iBFR modality. In accordance with the first meta-analysis conducted in this PhD, which enhanced the existing BFR literature by confirming the efficacy of BFR training in promoting muscle strength and hypertrophy across various populations, these guidelines can be tailored to ensure both effectiveness and safety in practice. By integrating these findings, practitioners can better meet the unique needs of their clients while optimizing the application of the i-BFR modality. Specifically, practitioners should aim to

achieve 30-50% of AOP in the final set, as this pressure range has been demonstrated to be more tolerable while providing effectiveness comparable to high-load resistance training without BFR. Moreover, when designing exercise regimens for clinical and elderly populations, it is crucial to avoid training to failure, as this approach can lead to increased discomfort and may hinder adherence to the program. Instead, maintaining a focus on manageable exertion levels can enhance both tolerance and adherence, ensuring a more positive exercise experience for these populations. Practitioners should also set realistic expectations for strength adaptations, recognizing that lower body exercises may yield noticeable improvements after eight or more weeks, whereas adaptations for upper body exercises are likely to occur in less than eight weeks. By incorporating these considerations, practitioners can effectively implement the i-BFR modality to optimize outcomes for their clients. People (Users):

Users of i-BFR training should seek guidance from qualified and trained practitioners, as proper instruction and supervision are critical to ensuring that the exercise is both safe and effective. To maximize the benefits of i-BFR and minimize the risk of adverse effects, educational initiatives should be implemented to inform users about the technique and its applications. Incorporating i-BFR training into public gym programs can also enhance accessibility, allowing a broader segment of the population to experience its advantages. Furthermore, training programs for fitness professionals and 243 gym staff should emphasize the importance of evidence-based practices related to i-BFR, fostering a supportive environment for users. By promoting awareness and knowledge about i-BFR, its integration into fitness regimens can significantly impact overall health and fitness outcomes in the general population. Feedback from Participants: Participants reported that the progressive pressure

increments enhanced the tolerability of the protocol. This observation is significant for the overall utility of BFR in practice, as improved user comfort and compliance may facilitate greater adherence to the training regimen without compromising the acute physiological effects associated with the method. Further, participants noted that the protocol's appeal could make it more likely for others to recommend it, especially those seeking a low-load alternative to traditional high-load resistance training that offers similar benefits. Specifically, participants noted that the equipment was user-friendly, allowing for easy adjustment of settings. However, participants also expressed a desire for extended resting periods if they were to use the protocol independently. They indicated that the process of returning to the main menu to select the lower body option, followed by manual settings to adjust the pressure, was time-consuming. The initial pressure setting started at 20 mmHg and

increased by increments of 10 mmHg, which could extend the time required to reach higher pressures. Consequently, the necessity to prepare the pressure for the next set within a 30-second resting period posed a challenge, as participants felt this timeframe was insufficient for optimal recovery and adjustment. The new i-BFR modality holds immense promise for application across a range of sectors. In healthcare, its inclusion in rehabilitation programs could offer a safe, effective alternative to high-load resistance training, particularly for vulnerable populations. This, however, requires further empirical evidence specific to these populations. The data from this PhD study provides a foundation for future research to explore its potential. Future product developments, such as increasing pressure thresholds and incorporating advanced monitoring technologies, will enhance both the safety and effectiveness of BFR training. Practitioners and policymakers alike should prioritize the

integration of i-BFR into clinical settings, public health initiatives, and fitness programs, while ensuring adequate training and supervision for users. Continued collaboration between researchers, manufacturers, and healthcare providers will ensure that i-BFR training reaches its full potential, positively impacting both individual health outcomes and broader societal well-being. However, more research is needed to establish the long-term effects and optimal protocols of this new method in order to effectively promote its widespread use and integration into clinical practice and community-based health programs. 244 9.3 Future Directions The novel and promising findings of this PhD, particularly regarding the new progressively increased pressure i-BFR modality, contribute to the evolving landscape of BFR resistance training and present several avenues for future research. The following directions are recommended: Comparative Intervention Studies: Chronic studies should be

conducted to evaluate the chronic effects of the new i-BFR modality against traditional continuous BFR (c-BFR), high-load resistance training (HL-RT) and typically used consistent pressure i-BFR approach. These studies should focus on musculoskeletal adaptations, such as strength gains and muscle hypertrophy, to determine the efficacy and potential advantages of the i-BFR modality. Additionally, it will be essential to explore the underlying physiological mechanisms driving these adaptations, as understanding these factors is a core objective of this research. Given the methodological limitations of the current PhD, which primarily focused on acute studies, the strength of the conclusions drawn is inherently restricted. This highlights the necessity for further investigation into the chronic effects of i-BFR, as this first step lays the groundwork for more robust future research while acknowledging the limitations of the initial findings. Perceptual Response Studies: Both acute and

chronic studies are needed to investigate perceptual responses, such as discomfort, perceived exertion, and overall experience, when using the i-BFR modality. To gain a more comprehensive understanding, future research should incorporate a variety of methodologies, including validated questionnaires targeted on adherence and user experience, as well as qualitative interviews and focussed groups to capture nuanced perceptions. These interviews could benefit from a broader range of questions compared to those included in Acute Study 1 of the present thesis, particularly concerning psychological aspects such as anticipation of discomfort and participants’ familiarity with the i-BFR protocol and exploring the impact of using i-BFR on markers of quality of life. Exploring whether participants feel they require additional time to acclimate to the new modality could provide valuable insights into their perceptual experiences. Comparisons should also be made with other intermittent BFR

modalities that deflate pressure only during resting periods and do not progressively increase pressure as the sets advance. This multifaceted approach will help create a clearer picture of the perceptual responses associated with this new i-BFR modality, as well as its efficacy in both acute and long-term applications, particularly in comparison with continuous BFR, traditional intermittent BFR, and HL-RE. Cognitive and Mood Adaptations: There is a need for research into the cognitive and mood effects of both the new i-BFR and c-BFR training across a broader range of populations, including healthy adults, elderly individuals, and clinical groups. Both acute and chronic studies should assess whether the novel i-BFR can provide cognitive benefits or mood enhancements, and how these effects compare with cBFR and non-BFR protocols. Research on brain-derived neurotrophic factor (BDNF) is particularly 245 crucial in resistance training, as it may mediate the potentially beneficial

effects on cognition and mood. This is a relatively new field, and there is an even greater need to investigate BDNF changes during low-load resistance training with BFR, especially given that there are currently no studies examining the effects of i-BFR on BDNF levels, aside from this novel investigation. Focusing on elderly and clinical populations is especially important, as these groups may benefit from integrating i-BFR into their health interventions to enhance cognitive function and emotional well-being. By exploring these dimensions, researchers can gain insights into the mechanisms underlying the perceived benefits of iBFR, ultimately enhancing its applicability in various settings and contributing to the understanding of its role in cognitive function and emotional health. Qualitative Studies in Elderly and Clinical Populations: Future research should include acute studies that compare the new i-BFR modality with traditional i-BFR (without incremental pressure increases) and

with non-BFR conditions. These studies should incorporate qualitative methods, such as semistructured interviews, to gain insights into the experiences of elderly and clinical populations, focusing on their perceptual responses and tolerance to the i-BFR modality. Moreover, exploring behavioural aspects, such as motivation, adherence, and the psychosocial factors influencing engagement with iBFR training, could provide valuable insights into how these populations respond to and integrate BFR training into their routines. Investigating the barriers and facilitators of adopting i-BFR in rehabilitation or fitness contexts could enhance understanding of its practical application. Additionally, examining the role of social support and environmental factors in promoting adherence to BFR training could be beneficial. By delving into these nuanced areas, researchers can identify specific needs and preferences of diverse populations, ultimately contributing to the development of tailored

interventions that maximize the benefits of i-BFR training while fostering a supportive environment for users. This comprehensive approach can fill existing gaps in literature and lead to innovative applications of BFR training in clinical and community settings. 246 9.4 Challenges & Reflections The findings and challenges of this study highlight several key considerations that are likely to shape future research directions. First, the use of narrow elastic bands compared to wider nylon cuffs in assessing AOP has shown a notable difference. Narrower bands may result in significantly higher AOP values than those reported in the literature using wider cuffs. This discrepancy should be anticipated and adjusted for in future studies, especially when aiming for accurate cross-comparisons with existing data. If researchers opt to use narrow elastic bands that do not achieve the higher pressures required for full arterial occlusion, ultrasound technology offers a promising solution.

By providing real-time data on arterial saturation levels during occlusion, ultrasound could help determine the exact percentage of AOP using lower pressures with these bands. This approach would eliminate the need for more complex processes, such as using Near-Infrared Spectroscopy (NIRS) during exercise to assess muscle oxygen saturation and then calculating the 50% AOP from those findings. Ultrasound's ability to streamline the identification of AOP percentages with less invasive methods would make it a valuable tool in future research. Physiological differences, such as muscle mass, should also be a key consideration in future studies. The more muscular the lower limbs, the more pressure is required to achieve full arterial occlusion. This suggests that future research should stratify participants based on their physiological characteristics to ensure consistent and meaningful results. Moreover, when determining the most appropriate exercise modality, pilot studies are

essential for elucidating the nuances of various protocols. It has been shown that resistance exercise protocols that involve training to failure with blood flow restriction (BFR) can lead to increased exertion and discomfort, without necessarily resulting in more advantageous adaptations compared to BFR protocols that do not train to failure. For example, structured repetition schemes, such as 30-15-15-15, can yield similar benefits while promoting greater tolerability. Understanding these distinctions is crucial, particularly in diverse populations where individual responses to exercise may vary significantly. The findings from the present PhD will contribute to a better understanding of these approaches and their potential implications for different groups, including clinical and elderly populations. This knowledge can guide practitioners in designing exercise programs that consider individual tolerability and adherence, ultimately improving the likelihood of successful long-term

health outcomes. By focusing on pilot studies, future research can further refine these protocols to meet the specific needs of the populations being tested. Finally, securing sufficient funding, research assistance, and the necessary equipment is essential before the project’s initiation. Having these resources in place will not only ensure the smooth progression of the research but also help maintain the integrity and scope of the project. 247 By addressing these challenges and considerations, future research can build on the foundation established here, advancing the field while ensuring methodological robustness. 248 10. Conclusions 249 This thesis employed multiple methodological approaches, integrating both meta-analytic reviews and experimental studies, including a mixed-methods study that combined both quantitative and qualitative data, to explore the physiological, perceptual, and cognitive effects of blood flow restriction (BFR) during low-load resistance

exercise (BFR-RE). Two meta-analyses form the foundation of this thesis, assessing the efficacy of BFR-RE for musculoskeletal adaptations, as well as the acute metabolic and perceptual responses associated with this modality. Building on these findings, experimental studies were designed to further investigate the acute effects of a novel progressively intermittent pressure BFR (i-BFR), with a particular focus on its tolerability, metabolic impact, and potential influence on cognitive function and mood. The two meta-analyses examined both the chronic musculoskeletal adaptations of low-load resistance training with blood flow restriction (BFR-RT) and the acute metabolic and perceptual responses to BFR during low-load resistance exercise (BFR-RE). These analyses found that BFR-RT, particularly when utilizing individualized arterial occlusion pressure (AOP), is comparable to high-load resistance training (HL-RT) in promoting muscle strength and hypertrophy, especially in interventions

lasting eight weeks or more. Additionally, the meta-analyses revealed that BFR-RE can induce acute metabolic responses similar to those of high load resistance exercise (HL-RE). Importantly, the intermittent pressure BFR was found to be more tolerable than HL-RE, with lower perceived exertion, thus offering a promising alternative for individuals who experience difficulty with the discomfort associated with traditional high-load training. A pilot study and two acute studies further investigated the novel i-BFR’s effects. The pilot study suggested greater tolerability and potential cognitive benefits of i-BFR compared to c-BFR. The first acute study, the first mixed-methods assessment of BFR modalities' psychological and cognitive impacts, found that i-BFR was more tolerable than both HL-RE and c-BFR, with potential improvements in mood and cognitive function, likely through brain-derived neurotrophic factor (BDNF) stimulation. The second acute study highlighted key physiological

differences, showing that while both BFR modalities increased growth hormone (GH), i-BFR had a less pronounced effect on insulin-like growth factor 1 (IGF-1) compared to HL-RE. In conclusion, the novel i-BFR modality shows potential as a more tolerable alternative to c-BFR and HL-RE, offering comparable metabolic benefits and possibly similar musculoskeletal adaptations. Its potential to positively influence mood and cognitive function further extends its applicability, particularly for individuals who cannot tolerate high-load training. Integrating the new i-BFR into healthcare, rehabilitation, and public health programs could provide valuable benefits for clinical populations. Key areas for successful implementation include policy advocacy, product development (e.g, higher pressure thresholds and advanced monitoring technologies), and adherence to evidencebased guidelines by practitioners Proper training and supervision are essential to ensure safety and 250 maximize benefits.

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Restriction on Muscle Size and Arterial Stiffness in Older Adults’, The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 70 (8), pp 950-958. doi: 101093/gerona/glu084 Yasuda, T., Ogasawara, R, Sakamaki, M, Bemben, M G & Abe, T (2011), ‘Relationship between limb and trunk muscle hypertrophy following high-intensity resistance training and blood flowrestricted low-intensity resistance training’, Clinical Physiology and Functional Imaging, 31 (5), 347351. doi: 101111/j1475-097X201101022x Yasuda, T., Ogasawara, R, Sakamaki, M, Ozaki, H, Sato, Y & Abe, T (2011), ‘Combined effects of low-intensity blood flow restriction training and high-intensity resistance training on muscle strength and size’, European journal of applied physiology, 111 (10), pp 2525-2533. doi: 101007/s00421-0111873-8 Yasuda, T., Shirakawa, J, Fujita, T, Beekley, M D, Sato, Y & Abe, T (2006), ‘Comparison of EMG activity among Low-intensity Exercise with and without

KAATSU and Ischemic Conditions’, Medicine and Science in Sports and Exercise, 38 (5), S520-S521. doi: 101249/00005768-200605001-03048 Yinghao, L., Jing, Y, Yongqi, W, Jianming, Z, Zeng, G, Yiting, T & Shuoqi, L (2021), ‘Effects of a blood flow restriction exercise under different pressures on testosterone, growth hormone, and insulinlike growth factor levels’, Journal of International Medical Research, 49 (9). doi: 10.1177/03000605211039564 Yogev, A., Arnold, J, Nelson, H, Clarke, D C, Guenette, J A, Sporer, B C & Koehle, M S (2023), ‘Comparing the reliability of muscle oxygen saturation with common performance and physiological markers across cycling exercise intensity’, Frontiers in Sports and Active Living, 5, 1143393. doi: 10.3389/fspor20231143393 Zhang, K., Zhang, Q, Jiang, H, Du, J, Zhou, C, Yu, S, Hashimoto, K & Zhao, M (2018) ‘Impact of aerobic exercise on cognitive impairment and oxidative stress markers in methamphetamine-dependent patients’,

Psychiatry research, 266, pp 328-333. doi: 101016/jpsychres201803032 Zhang, L., Li, B, Yang, J, Wang, F, Tang, Q & Wang, S (2020), ‘Meta-analysis: Resistance Training Improves Cognition in Mild Cognitive Impairment’, International journal of sports medicine, 41, pp 815-823. Zhao, W., & Smith, R G (2007), ‘The role of insulin-like growth factor-1 in the regulation of growth hormone release’, Endocrinology, 148(8), pp 3970-3979. 299 12. Appendices 300 Appendix 1: Participants’ Information Sheet for Pilot Study Participation Information Sheet University of Brighton School of Sport and Service Management ‘The acute effects of the new repeated progressive intermittent KAATSU-Cycle blood flow restriction protocol on the perceptual, mood, cognitive and lactate responses to resistance exercise’ Experimenter: Maria Kotopoulea Nikolaidi Or mob: +447852663846 Contact details: M.KotopouleaNikolaidi@brightonacuk Supervisors: Prof. Yannis Pitsiladis

Y.Pitsiladis@brightonacuk Dr Fergus Guppy F.Guppy@brightonacuk Dr Ifigeneia Giannopoulou I.Giannopoulou@brightonacuk This study is partly funded by the University of Brighton and partly funded by the American company “KAATSU Global Inc.” KAATSU Global Inc will also provide the blood flow restriction equipment that will be used in this project. This information sheet will inform you about the aim of the study, the requirements needed for you to participate, the benefits, the risks and discomforts. If you have any questions, please do not hesitate to contact us. The participation is voluntary, and you are free to withdraw at any time without giving a reason. Regarding participants who are students or know the team personally, it must be clear that your decision not to take part in the study will not have any negative consequences in terms of your studies, work, or other activities. It must also be underlined those expenses such as travel, meals, loss of earnings etc are not

going to be covered. Aim: The aim of this study is to investigate the acute psychophysiological effects of continuous blood flow restriction (BFR) during low intensity resistance exercise and intermittent BFR during low intensity resistance exercise versus high intensity resistance exercise without BFR. Rationale: Health is the most important attribute to which all human beings aspire. However, poor lifestyle choices such as physical inactivity and unbalanced nutrition, can jeopardize the population’s health and quality of life. High intensity resistance training is associated with improvements in muscle strength and tone, flexibility and balance as well as weight management and enhancements in mood state and cognition. However, in order to gain these benefits, the prescribed intensity is high (70-85% of 1 repetition maximum), which can be quite difficult, uncomfortable and not appropriate for everyone 301 such as older individuals or individuals with injuries. Low intensity

resistance exercise (20-30% of 1 repetition maximum) with blood flow restriction (KAATSU) has been suggested as an alternative and safe method of inducing similar or even greater physiological and psychological responses compared to the traditional high intensity resistance exercise without KAATSU. Particularly, KAATSU exercise is the first form of blood flow restriction training reported in the literature with significant improvements in exercise capacity, muscle strength, muscle hypertrophy, mood and cognition in young, older, clinical and athletic populations. KAATSU training involves the use of narrow, elastic, stretchable pneumatic bands that inflate and deflate at set pressures (individualised) while you are exercising, whereas other blood flow restriction equipment uses modified or normal blood pressure cuffs or tourniquets (please follow the link for more information: https://www.kaatsucom/) The underlying physiological mechanisms are still poorly understood, and more research

is needed. A number of different modalities have been used and reported significant improvements in muscle strength, mood, cognition and perceptual responses such as pain and discomfort. It has been reported that the deflation of the pneumatic bands during resting periods between sets while exercising with resistance exercise causes less pain and discomfort but it induces similar physiological benefits compared to continuous KAATSU resistance exercise (eg. constant inflation during the whole exercise session) and high intensity resistance exercise without KAATSU. The purpose of this study is to investigate the most appropriate modality of KAATSU exercise (continuous inflation while exercising versus intermittent inflation while exercising), regarding the pain, discomfort, mood, cognition and lactate responses. Participant requirements: Inclusion Criteria: >18 years old Healthy Have experience in resistance training Exclusion Criteria: <18 years old BMI <20 and >29.9 Resting

Systolic Blood Pressure >139 mmHg & Resting Diastolic Blood Pressure >89 mmHg Have Diabetes (Type 1 or Type 2) Have heart related conditions and taking medication (i.e blood thinners) Had an acute illness within the last 3 months Have orthopedic or neurological limitations Have a medical history of deep vein thrombosis Exercise regularly (resistance exercise more than 3 times a week) Had COVID-19 the last 3 months Had the COVID-19 vaccine the last 6 weeks or are planning to get a COVID-19 vaccine during the period of their participation in this study Methodology: Prior to all trials you will be asked to complete a medical questionnaire and informed consent form. This is to ensure that you meet the inclusion criteria and understand what is required from you. You will be required to visit Eastbourne campus Labs (WardHall) three times separated by at least 302 48 hours. The order or the experimental trials will be assigned randomly All testing will be taking place at a

predetermined time of the day. That time will be discussed in advance so that it fits with your schedule. As it is important to control your physical activity and diet for 3 days before your last two visits, during your first visit you will be provided with a 3-Day Dietary Sheet and you will be asked to report all your meals and replicate that every 3 days prior to each visit (for the last 2 visits). You will also be asked to refrain from strenuous exercise during your participation in this study and you will be required to refrain from alcohol or caffeine 48 hours and 6 hours respectively prior visiting the labs. Visit 1: Preliminary testing (2 hours max, most of the time they will be rested and sit): 1: Medical questionnaires & screening and Consent forms 2: Anthropometric & Body composition via BIA (BODYSTAT) This testing is to identify your body composition. You will be asked to lie down, and 4 electrodes will be placed on y o u r foot and hand. 3: Blood pressure

(systolic/diastolic) – 3 measurements after 10 minutes rest in supine position 4: Thigh circumference measurement via tape 5: Individualised Blood flow restriction pressure It is important to identify and individualise your blood flow restriction pressure that we will apply when you are exercising, in order to avoid your limb being fully occluded. You will be asked to lie down and rest for 10 minutes and then we will check your branchial arterial pressure. After that cuffs connected to an inflator system will be placed in your thighs and inflated to 40 mmHg for 30 seconds while a handheld doppler probe coated with gel will be positioned in your thigh to detect the pulse. Then the cuff will be inflated to your systolic blood pressure that we measured in your arm previously. After 10 seconds the cuffs will be deflated and cycles of inflation and deflation will be performed in intervals of 10mmHg, until the pulse is completely interrupted. Once the pulse is no longer detected by the

Doppler, the pressure will slowly be released until we can detect it again. The final pressure will be your individualised 100% of BFR pressure and then we will calculate the 50% restrictive pressure to be used during the two KAATSU experimental trials. 6: 1-RM for the dominant leg only in the leg press machine. 303 A general 5’ warm up will be performed in the bike. You will be introduced to the proper technique and complete 8-10 repetitions with a moderate to light load, following a load increment. You will be asked to complete 4-5 repetitions, then the load will be increased once again and you will have to complete 23 repetitions. The load will progressively increased until you will be unable to complete a repetition using proper form or/and technique. 7: Familiarization with the Cognitive function test (Stroop test) 8: Familiarization with the Mood questionnaire (Profile of Mood State questionnaire) 9: You will get rest for approximately 30 minutes. We will calculate the 30%

of the 1-RM for the dominant leg and after resting you will be asked to perform 4 sets of 30-15-15-15 repetitions at 30% of the 1-RM for the dominant leg with the cuffs inflated at your personal 50% of BFR pressure. Visit 2-3: Main experimental trials Continuous BFR & KAATSU cycle (Random-order) (approximately ~30’) 1: Short medical questionnaire and consent form 2: Capillary finger pick blood samples (for Lactate), Cognitive function test (Stroop test) and Mood questionnaire (Profile of Mood State (POMS) questionnaire) will be performed before exercise and immediately after exercise. 3: Ratings of Perceived exertion and visual analogue scales for pain and discomfort will be measured before and at the end of each set. Benefits of Participation: By participating in this study, you will gain valuable understanding and knowledge of physiological mechanisms and how the human body reacts to different conditions. On completion of the study, you will be provided with important

information related to your health profile and how you can improve your health by following specific exercise and dietary strategies. More specifically, at the completion of testing each participant will receive a comprehensive, reporting the results and according prescription and recommendations on the following: Body Composition (BODYSTAT) and Anthropometric testing (Body weight, BMI, %muscle mass etc) 1-RM of the dominant leg Cognitive function and mood state results under different conditions 304 Finally, by participating in this study you will have an insight of the use of the equipment and your current strength fitness (1-RM) and how this can be improved with training. Risks, Discomfort and Safety Precautions: The tests can be physically demanding. If you experience a level of discomfort during the tests as a result of the high intensities or due to the pressures of the blood flow restriction, you can stop the trials. Within the experimental procedures, there are measures

that reduce the risks, the experimenters will always be on hand and will monitor signs of discomfort. Procedures within the laboratories undergo regular risk assessments and the current study has been given approval from the University of Brighton Ethics Committee and has been reviewed by the Life, Health and Physical Science Cross School Research Ethics Committee. You have the right to terminate any test at any point should you feel in significant discomfort or distress. Each test will be preceded with a supervised warm up and cool down after each session. Participants with underlying health problems will be excluded from the study as a safety precaution; if you have any queries about this, feel free to discuss this with the principal investigator. Informed Consent: You will be asked to complete a consent form prior to any testing along with a medical questionnaire. At this point you will be able to talk to the principal investigator about any queries that you have before indicating

your consent. Your participation in the study is strictly voluntary and you are free to withdraw at any point and are under no obligation to give reasons for your withdrawal. General Guidelines: Participants should be well rested and hydrated to ensure that the responses to exercise are not influenced by acute changes in physiological status. More information and advice will be given regarding your hydration. Participants should wear appropriate athletic clothing and training shoes. Participants should refrain from strenuous exercise during the study. The Day of Testing: No exercise should be undertaken. Stay hydrated. Ensure you drink ~ 500 mL water Eat your breakfast 2 h before your arrival at the laboratories Adequate fluids should be taken (water), but no caffeine or other drinks should be consumed in the 6 hours prior to testing. No alcohol in the last 48 hours before your arrival at the labs Confidentiality: Personal details will be treated as strictly confidential at all times

and you will only be identified by a personal identification number; which only yourself and the principal investigators will know. Any data collected will be anonymised and kept secure in a computer, locked by passwords only known to the investigators. All data will be kept for a period of 10 years for future research that has ethical approval from the University of Brighton and will not be released without prior permission unless required by law. The data collected may be published in the form of a journal/report, however subjects will be anonymised, and all personal information will be treated with the strictest confidence. You may withdraw your data from the study at any point up until data-analysis has been conducted; at this point and beyond it will be impossible to remove your data from the study. Please follow the below link to the University of Brighton privacy notice: https://unibrightonac.sharepointcom/:b:/r/sites/public/docs/Legal%20and%20Governance/Resea rch Privacy

Notice.pdf?csf=1&web=1&e=6BdMtW 305 Withdrawal: If you wish to withdraw from this study you can do so at any time with no prejudice and without a reason. If you wish to make a complaint about this study then please contact my supervisors Y.Pitsiladis@brightonacuk, FGuppy@brightonacuk, IGiannopoulou@brightonacuk and the Chair of the Life, Health and Physical Science Cross School Research Ethics Committee (CREC), Dr Lucy Redhead (L.Redhead@brightonacuk) 306 Appendix 2: Participants’ Information Sheet for Acute Studies Participation Information Sheet V5 University of Brighton School of Sport and Service Management The acute effects of blood flow restriction Kaatsu resistance exercise on growth factors, cognition, mood and perceptual responses in healthy adults. Experimenter: Contact details: Maria Kotopoulea Nikolaidi M.KotopouleaNikolaidi@brightonacuk Or mob: +447852663846 Supervisors: Prof. Yannis Pitsiladis Y.Pitsiladis@brightonacuk Dr Ifigeneia Giannopoulou

I.Giannopoulou@brightonacuk 307 This study is partly funded by the University of Brighton and partly funded by the American company “KAATSU Global Inc.” KAATSU Global Inc will also provide the blood flow restriction equipment that will be used in this project. This information sheet will inform you about the aim of the study, the requirements needed for you to participate, the benefits, the risks and discomforts. If you have any questions, please do not hesitate to contact us. The participation is voluntary, and you are free to withdraw at any time without giving a reason. Regarding participants who are students or know the team personally, it must be clear that your decision not to take part in the study will not have any negative consequences in terms of your studies, work, or other activities. It must also be underlined those expenses such as travel, meals, loss of earnings etc are not going to be covered. Aim: The aim of this study is to investigate the acute

psychophysiological effects of continuous blood flow restriction (BFR) during low intensity resistance exercise and intermittent BFR during low intensity resistance exercise versus high intensity resistance exercise without BFR. Rationale: Health is the most important attribute to which all human beings aspire. However, poor lifestyle choices such as physical inactivity and unbalanced nutrition, can jeopardize the population’s health and quality of life. High intensity resistance training is associated with improvements in muscle strength and tone, flexibility and balance as well as weight management and enhancements in mood state and cognition. However, in order to gain these benefits, the prescribed intensity is high (70-85% of 1 repetition maximum), which can be quite difficult, uncomfortable and not appropriate for everyone such as older individuals or individuals with injuries. Low intensity resistance exercise (20-30% of 1 repetition maximum) with blood flow restriction

(KAATSU) has been suggested as an alternative and safe method of inducing similar or even greater physiological and psychological responses compared to the traditional high intensity resistance exercise without KAATSU. Particularly, KAATSU exercise is the first form of blood flow restriction training reported in the literature with significant improvements in exercise capacity, muscle strength, muscle hypertrophy, mood and cognition in young, older, clinical and athletic populations. KAATSU training involves the use of narrow, elastic, stretchable pneumatic bands that inflate and deflate at set pressures (individualised) while you are exercising, whereas other blood flow restriction equipment uses modified or normal blood pressure cuffs or tourniquets (please follow the link for more information: https://www.kaatsucom/) The underlying physiological mechanisms are still poorly understood, and more research is needed. A number of different modalities have been used and reported

significant improvements in muscle strength, mood, cognition and perceptual responses such as pain and discomfort. It has been reported that the deflation of the pneumatic bands during resting periods between sets while exercising with resistance exercise causes less pain and discomfort but it induces similar physiological benefits compared to continuous KAATSU resistance exercise (eg. constant inflation during the whole exercise session) and high intensity resistance exercise without KAATSU. The purpose of this study is firstly to examine the underlying physiology and secondly to investigate the most appropriate modality of KAATSU exercise (continuous inflation while exercising versus intermittent inflation while exercising), regarding the pain, discomfort, mood and cognition. Participant requirements: 308 Inclusion Criteria: >18 years old & <40 years old Males Healthy Have experience in resistance training and do resistance training at least 2 days/week the last 6

months Exclusion Criteria: <18 years old & >40 years old BMI <20 and >29.9 Resting Systolic Blood Pressure >139 mmHg & Resting Diastolic Blood Pressure >89 mmHg Have Diabetes (Type 1 or Type 2) Have heart related conditions and taking medication (i.e blood thinners) Had an acute illness within the last 3 months Have orthopedic or neurological limitations Have a medical history of deep vein thrombosis Exercise regularly (resistance exercise more than 3 times a week) Had COVID-19 the last 3 months Had the COVID-19 vaccine the last 6 weeks or are planning to get a COVID-19 vaccine during the period of their participation in this study Methodology Prior to all trials you will be asked to complete a medical questionnaire and informed consent form. This is to ensure that you meet the inclusion criteria and understand what is required from you. You will be required to visit Welkin Labs four times and the last 3 visits will be separated by one week. Also, you will be

required to pay one visit at Moulsecoomb campus in Brighton (please see Figure 1 below). The order or the experimental trials will be assigned randomly. Specifically, you will pick a random number from a bowl from 1 to 3 until the numbers run out. The order you pick the numbers with will be your assignment to the equivalent group (trial). All testing will be taking place at a predetermined time of the day. That time will be discussed in advance so that it fits with your schedule As it is important to control your physical activity and diet for 3 days before your last four visits, during your first visit you will be provided with a 3-Day Dietary Sheet and you will be asked to report all your meals and replicate that every 3 days prior to each visit (for the last 3 visits). You will also be asked to refrain from strenuous exercise during your participation in this study and you will be required to refrain from alcohol or caffeine 48 hours and 24 hours respectively prior visiting the

labs. 309 Figure 1. indicates the preliminary testing at the first visit and then the completion of the main experimental trials in a randomised order. Visits from 3-5 will have to be separated by a week Measurements Body composition via DXA This testing is to identify your body composition (lean and bone mass). You will be asked to lie down, and relax 4 for approximately 15 minutes. Picture 1: DXA scan machine Maximum Dynamic Strength Test You will be asked to assess your maximum strength using bilateral 1 Repetition Maximum tests for leg press exercise following the National Strength and Conditioning Association’s guidelines. You will be introduced to the proper technique, complete a warm-up and then incrementally we will increase the load until you are unable to complete a repetition using proper form and technique. This test will be carried out in the leg press machine as you see below in the picture. 310 Picture 2: Leg Press Machine Assessment of Total Blood Flow

Restriction Pressure It is important to identify and individualise your blood flow restriction pressure that we will apply when you are exercising, in order to avoid your limb being fully occluded. You will be asked to lie down and rest for 10 minutes and then we will check your branchial arterial pressure. We will place nylon cuffs to your thighs. These cuffs are connected to an inflator system we will set the inflation to 50 mmHg for 30 seconds. We will check regularly your arterial pulse with a handheld doppler probe coated with gel Then the cuff will be inflated to your systolic blood pressure that we measured in your arm previously. After 10 seconds the cuff will be deflated and cycles of inflation and deflation will be performed in intervals of 10mmHg, until the pulse is completely interrupted. Once the pulse is no longer detected by the Doppler, the pressure will slowly be released until we can detect your pulse again. That will be considered to be your 100% of blood flow

occlusion and then we will calculate the 50% in order to use this pressure during the two KAATSU trials. Resistance Exercise Protocols You will be required to randomly complete each one of the exercise trials (Figure 1) consisting of four sets until failure (until you will no longer be able to complete another repetition) of the leg press machine (Picture 2). Mood questionnaires One mood related questionnaire (Profile of Mood States) will be provided to you to complete before exercise, immediately after exercise and 1 hour after exercise. We will give you the opportunity to familiarise yourself with the questionnaire and ask any questions you might have in your first visit. Physical Activity Enjoyment Scale Questionnaire One questionnaire related to how enjoyable the exercise protocol is will be provided to you to complete before exercise, immediately after exercise and 1 hour after exercise. We will give you the opportunity to familiarise yourself with the questionnaire and ask any

questions you might have in your first visit. 311 Cognitive Function Tests Two cognitive function tests (Stroop test, Shift Stroop) will be provided to you on a laptop to complete before exercise, immediately after exercise and 1 hour after exercise. These cognitive function tests are assessing your working memory and you will have the opportunity to familiarise yourself and ask any questions you might have during your first visit. Capillary Blood Sampling A small capillary blood sample will be taken from your fingertip before exercise and immediately after exercise for blood lactate analysis. Venous Blood Sampling Venous blood will also be taken to measure inflammatory factors, and growth factors at two timepoints (before exercise, approximately 5’ post exercise). Venous samples will be collected via a needle in the antecubital veins of the forearm by a trained certified person. It must be underlined that only trained phlebotomists will perform the blood sampling and their

certificates have been submitted to the Human Tissues Governance Manager. It is important to understand how data collected about you will be used, stored and who will have access to it. It is also very important to understand that your personal information may be viewed for audit purposes by those governing or supporting governance under the University’s Human Tissue Authority licence. For the above reasons it is important to read the below: Your blood samples will be centrifuged within a few hours of collection to remove the cell-free part of your blood which, is called serum and this will be frozen and stored in the Welkin laboratories until analysis at a later date. The remaining blood which, contains cells will be discarded as per SSHS guidelines and in adherence with the Human Tissue Act 2004 and the Human Tissue Authority's standards. By agreeing to participate in this project you are agreeing that your serum samples can be stored for the ethically approved duration of

this project and can be used for the research described in this information sheet. There will not be any DNA or RNA analysis carried out on your samples If you chose to withdraw from the study at any time we can arrange for your stored serum to be discarded and no further work will be carried out. Visual analogue Scales: You will be asked at the end of each exercise set, to assess from 0-10 how motivate, exhausted, vigoured or how tolerated the exercise set was. 0 equals to “Not Feeling that at all” and 10 equals to “I feel that extremely”. Structured Interview: You will be asked, once you finish all the visits to participate in a structured interview, which will last approximately 5-10 minutes. The content of the questions will be related only to the exercise protocols that you have undergo. A sample of the question is “Which exercise protocol did you prefer?, Which exercise protocol was more tolerable/or painful?” The interview will be recorded either online via Teams or

it can be arranged face-to-face and will be recorded via a recording machine. We will give you the opportunity to ask any questions you might have in your first visit. Benefits of Participation: By participating in this study, you will gain valuable understanding and knowledge of physiological mechanisms and how the human body reacts to different conditions. On completion of the study, you 312 will be provided with important information related to your health profile and how you can improve your health by following specific exercise and dietary strategies. More specifically, at the completion of testing each participant will receive a comprehensive handout by email, reporting the results and according prescription and recommendations on the following: Body Composition by the golden standard (DXA) and Anthropometric testing (Body weight, BMI, %muscle mass etc) Dietary and nutritional analysis from your 3-Day Dietary Information Sheet Exercise capacity and muscle strength Finally, by

participating in this study you will have an insight of the use of the equipment and your current strength fitness (1-RM) and how this can be improved with training. Risks, Discomfort and Safety Precautions: The tests can be physically demanding. If you experience a level of discomfort during the tests as a result of the high intensities or due to the pressures of the blood flow restriction, you can stop the trials. Within the experimental procedures, there are measures that reduce the risks, the experimenters will always be on hand and will monitor signs of discomfort. Procedures within the laboratories undergo regular risk assessments and the current study has been given approval from the University of Brighton Ethics Committee and has been reviewed by the Life, Health and Physical Science Cross School Research Ethics Committee. You have the right to terminate any test at any point should you feel in significant discomfort or distress. Each test will be preceded with a supervised

warm up and cool down after each session. Participants with underlying health problems will be excluded from the study as a safety precaution; if you have any queries about this, feel free to discuss this with the principal investigator. There are no anticipated risks with high intensity resistance exercise or low intensity resistance exercise with blood flow restriction (KAATSU) other than possible anxiety and discomfort. The sensation is unusual, however it is not painful and only low levels of discomfort are likely to be experienced. The blood taking procedures present a low risk of infection and discomfort and all the risk assessments have been carried out. Additionally, all phlebotomists are accredited, and their certificates have been sent to the Human Tissues Governance Manager. Finally, all equipment will be sterilised and strict hygiene regulations are followed. Due to the ongoing COVID-19 pandemic the following additional safety measures will be taken; a) all researchers will

be wearing lab coats, masks and gloves, b) all participants will also wear masks during their staying in the laboratories, and c) a questionnaire related to COVID-19 protocols will be provided for you to complete every time you are admitted to the laboratory area. Informed Consent: You will be asked to complete a consent form prior to any testing along with a medical questionnaire. At this point you will be able to talk to the principal investigator about any queries that you have before indicating your consent. Your participation in the study is strictly voluntary and you are free to withdraw at any point and are under no obligation to give reasons for your withdrawal. General Guidelines: 313 Participants should be well rested and hydrated to ensure that the responses to exercise are not influenced by acute changes in physiological status. More information and advice will be given regarding your hydration. Participants should wear appropriate athletic clothing and training shoes.

Participants should bring their own bottle of water. Participants should refrain from strenuous exercise during the study. The Day of Testing: No exercise should be undertaken. Stay hydrated. Ensure you drink ~ 500 mL water Eat your breakfast 2 h before your arrival at the laboratories Adequate fluids should be taken (water), but no caffeine or other drinks should be consumed in the 6 hours prior to testing. No alcohol in the last 48 hours before your arrival at the labs Confidentiality: Personal details will be treated as strictly confidential at all times and you will only be identified by a personal identification number; which only yourself and the principal investigators will know. Any data collected will be anonymised and kept secure in a computer, locked by passwords only known to the investigators. All data will be kept for a period of 10 years for future research that has ethical approval from the University of Brighton and will not be released without prior permission unless

required by law. The data collected may be published in the form of a journal/report, however subjects will be anonymised, and all personal information will be treated with the strictest confidence. You may withdraw your data from the study at any point up until data-analysis has been conducted; at this point and beyond it will be impossible to remove your data from the study. Please follow the below link to the University of Brighton privacy notice: https://unibrightonac.sharepointcom/:b:/r/sites/public/docs/Legal%20and%20Governance/Research Priv acy Notice.pdf?csf=1&web=1&e=6BdMtW Withdrawal: If you wish to withdraw from this study you can do so at any time with no prejudice and without a reason. If you wish to make a complaint about this study then please contact my supervisors Y.Pitsiladis@brightonacuk, FGuppy@brightonacuk, IGiannopoulou@brightonacuk and the Chair of the Life, Health and Physical Science Cross School Research Ethics Committee (CREC), Dr Lucy Redhead

(L.Redhead@brightonacuk) 314 Appendix 3: Medical Questionnaire 315 316 317 Appendix 4: Participant Consent Form for Pilot Study 318 Appendix 5: Consent Form for Acute Studies 319 Appendix 6: Short Medical Questionnaire 320 Appendix 7: DXA Questionnaire 321 322 323 325 Appendix 9: KAATSU Certificate 326 Appendix 10: Risk Assessment 327 328 329 330 331 Appendix 11: Participants’ Dietary Diary 332 333 334 Appendix 12: Participants’ General Instructions 335 Appendix 13: POMS Questionnaire 336 Appendix 14: POMS Scores Instructions 337 338 Appendix 16: Full Search String Strategy for Meta-Analysis 2 340 Appendix 17: Muscle Soreness Questionnaire 341 Appendix 18: Interview Questions Sample 342