Egészségügy | Dietetika, táplálkozástudomány » Jayvaughn - T. Oliver - Body composition using air displacement plethysmography in obese adults, effect of estimated versus measured thoracic gas volume

BODY COMPOSITION USING AIR DISPLACEMENT PLETHYSMOGRAPHY IN OBESE ADULTS: EFFECT OF ESTIMATED VERSUS MEASURED THORACIC GAS VOLUME A Thesis by JAYVAUGHN T. OLIVER Submitted to the Graduate School at Appalachian State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE December 2019 Department of Health and Exercise Science BODY COMPOSITION USING AIR DISPLACEMENT PLETHYSMOGRAPHY IN OBESE ADULTS: EFFECT OF ESTIMATED VERSUS MEASURED THORACIC GAS VOLUME A Thesis by JAYVAUGHN T. OLIVER December 2019 APPROVED BY: Jonathon L. Stickford, PhD Chairperson, Thesis Committee Abigail S.L Stickford, PhD Member, Thesis Committee Jennifer J. Zwetsloot, PhD Member, Thesis Committee Kelly J. Cole, PhD Chairperson, Department of Health and Exercise Science Mike McKenzie, Ph.D Dean, Cratis D. Williams School of Graduate Studies Copyright by Jayvaughn T. Oliver 2019 All Rights Reserved Abstract BODY COMPOSITION USING AIR DISPLACEMENT PLETHYSMOGRAPHY

IN OBESE ADULTS: EFFECT OF ESTIMATED VERSUS MEASURED THORACIC GAS VOLUME Jayvaughn T. Oliver B.S, Appalachian State University Chairperson: Jonathon L. Stickford, PhD Introduction: The Bod Pod uses air displacement plethysmography (ADP) to measure body volume (Dempster, 1995), and, with the measurement of body mass, is able to calculate body density for the analysis of body composition. However, total body density will be incorrectly estimated if the gas volume within the lungs at the time of the body volume measurement, termed thoracic gas volume (VTG), is measured inaccurately. The Bod Pod can account for VTG by using a prediction equation based on age and height (VTGpred), or by direct plethysmographic measurement (VTGmeas). It is well established that obesity (OB) alters operational lung volumes at rest, which has the potential to increase the error associated with VTGpred and the corresponding estimation of body composition. The purpose of this study was to examine the effect of

VTGpred and VTGmeas on estimates of body fat percentage (%BF) using the Bod Pod (%BFVTGpred, and %BFVTGmeas, respectively) as compared to %BF from dual Xray absorptiometry (DXA) and a subcomponent estimation from DXA, trunk fat percentage, in normal weight (NW) and (OB) adults. Methods: Subjects came to the iv lab for a single visit and body composition testing was performed via Bod Pod and DXA. 15 NW (222 ± 17 kg·m-2) and 9 OB (321 ± 19 kg·m-2) adults (24 ± 6 yr) participated in the study. A mixed design analysis of variance was used to examine the effects of group and method on measurements of VTG and %BF. Results: The group by method interaction (F1,22 = 3.017, p = 0096, η2 = 011), the main effect for method (F1,22 = 2.330, p = 0141, η2 = 009), and the main effect for group (F1,22 = 3.685, p = 0068, η2 = 014), were not significant for VTG The differences between VTGpred and VTGmeas were not significantly related with body mass index (BMI) (r = 0.33, p = 011) but were

with trunk fat percentage (r = 047, p = 002) There was a significant group by method interaction for %BF (F2,44 = 10.060, p = 0.001, η2 = 046) Additionally, the main effect for group with %BF was significant (F1,22 = 10.944, p = 0003, η2 = 051) However, the main effect for method with %BF was not significant (F2,44 = 0.663, p = 0479, η2 = 003) The differences between VTGpred and VTGmeas were significantly related with the differences between %BFVTGpred and %BFVTGmeas (r = 0.92, p < 0001) In conclusion, although this study is underpowered, there appears to be a relationship between differences in VTG and error of %BF estimation. The differences of VTG is significantly related with the fat that is carried around the chest. DXA also appears to estimate %BF lower in normal weight adults but higher in obese adults compared to ADP. v Acknowledgments I would like to say thank you to my committee members: Dr. Abigail Stickford and Dr. Jennifer Zwetsloot, for assisting me through

this process I would like to especially say thank you to Dr. Jonathon Stickford for mentoring me throughout my graduate career He has guided me through very difficult circumstances, and I know that the skills and wisdom that he has shared with me will far exceed the scope of my academic career. I also would like to say thank you to the Exercise and Respiratory Physiology Lab for supporting me through my graduate career; the people I have worked with and the friends that I made have molded my passion for research and have furthered my inspiration to continue to move forward. I would like to say thank you to my friends and family for being there to support me and keep me from losing my mind. I will never forget the experiences that I have had here I believe it will truly mold me to be a better person. I have truly been inspired by Dr Stickford’s heart, and I won’t forget the kind of person he is. I know that as I move on to other things the experiences that I have had here will shape

my successful future. vi Table of Contents Abstract . iv Acknowledgments. vi Table of Contents. vii List of Abbreviations and Symbols.x List of Tables . xiii List of Figures . xiv Chapter 1– Introduction .1 Overview.1 Air Displacement Plethysmography .2 Dual X-ray absorptiometry .3 Summary.4 Statement of Problem .4 Purpose of the Study.4 Delimitations.4 Limitations.5 Research Questions.6 Hypotheses.6 Definition of Terms .7 Chapter 2- Literature Review.8 vii Obesity is an Epidemic .8 Respiratory Complications in Obesity.10 Respiratory Compliance.10 How is Body Composition Measured? .11 Average Thoracic Gas Volume.16 VTG Measurements .17 Dual Energy X-ray Absorptiometry.18 Chapter 3– Methods.22 Subjects.22 Study Design and Protocol .22 Body Composition with ADP using VTGpred .23 Body Composition with ADP using VTGmeas .24 Body Composition using DXA .25 Data Analysis.26 Chapter 4- Results.27 Subject Characteristics.27 Measured vs Predicted Thoracic Gas Volumes .28 Measures

of Body Fat using ADP and DXA.29 Chapter 5– Discussion .35 Main Findings.35 Subject Characteristics.35 viii VTG Differences .37 VTG is Not FRC .38 %BF Estimates.41 Error %BF Estimates .43 Conclusion .45 References.46 Appendix A.55 Raw Data.55 Screen Captures of Raw Data from Subject information.55 Screen Captures of Raw Data from VTGpred .56 Screen Captures of Raw Data from VTGmeas .60 Screen Captures of Raw Data from DXA.64 Appendix B .67 Institutional Review Board Approval .67 Appendix C .68 Informed Consent Statement Form .68 Appendix D.74 Telephone Screening Form .74 Appendix E .76 Medical History Form.76 Appendix F.79 ix 24-hour Health History Forms .79 Vita.81 x List of Abbreviations and Symbols ADP air displacement plethysmography BMI body mass index %BFVTGmeas body fat estimated air displacement plethysmography using measured thoracic gas volume. %BFVTGpred body fat estimates using air displacement plethysmography using predicted thoracic gas volume

%BFDXA total body fat estimates using dual X-ray absorptiometry DXA dual X-ray absorptiometry η2 Eta-squared BVraw raw measured body volume BVcorr corrected body volume cmH2O centimeters of water EELV end-expiratory lung volume EILV end-inspiratory lung volume ERV expiratory reserve volume FM fat mass FFM fat free mass FMVTGmeas fat mass from air displacement plethysmography using measured thoracic gas volume. FMVTGpred fat mass from air displacement plethysmography using predicted thoracic gas volume. xi FFMVTGmeas fat free mass from air displacement plethysmography using measured thoracic gas volume. FFMVTGpred fat free mass from air displacement plethysmography using predicted thoracic gas volume. FEV1 forced expiratory volume in one second FRC functional residual capacity FVC forced vital capacity Ht height IC inspiratory capacity IRV inspiratory reserve volume kg kilogram L liters min minutes NHANES National Health and

Nutrition Examination Survey NW normal weight OB obese ORa adjusted odds ratio r Pearson’s correlation RV residual volume s seconds SAA surface area artifact SD standard deviation SEE standard error of estimate xii TLC total lung capacity TBW total body water US United States VC vital capacity VTG thoracic gas volume VTGpred predicted thoracic gas volume VTGmeas measured thoracic gas volume VT tidal volume Wt weight yr years xiii List of Tables Table 1- Subject Characteristics .27 Table 2- Predicted and Measured VTG .28 Table 3- Measures of %BF using ADP and DXA .29 Table 4- Measures of FM using ADP and DXA.30 Table 5- Measures of FFM using ADP and DXA .30 xiv List of Figures Figure 1- The effect of obesity on the pressure-volume curve .11 Figure 2- Diagrammatic representation of the Bod Pod .14 Figure 3- Diagrammatic representation DXA.19 Figure 4- Thoracic gas volume difference (VTGpred – VTGmeas) as a function of VTGpred in

NW and OB adults .29 Figure 5- Difference in %BF (%BFVTGpred – %BFVTGmeas) as a function of %BFVTGpred in NW and OB adult.31 Figure 6- Difference in %BF (%BFVTGpred – %BFVTGmeas) as a function of the difference in VTG (VTGpred – VTGmeas) in NW and OB adults.32 Figure 7- %BF difference (%BFDXA – %BFVTGpred) as a function of %BFDXA the in NW and OB adults .33 Figure 8- %BF difference (%BFDXA – %BFVTGmeas) as a function of %BFDXA in NW and OB adults.34 Figure 9- Changes while lying supine at rest to tidal volume from magnetometer to respiratory apparatus .39 Figure 10- Effects of BMI on functional residual capacity .40 xv Introduction Overview Obesity is generally defined as an excess amount of adipose tissue (Gadde, 2018). A more phenotypical trait of obesity is the large variation of body fat distribution relative to the total body mass (Thomas, 2012). While not a direct measure of body fat, body mass index (BMI) provides an index of fatness by scaling body weight

relative to height. Adults with a BMI ≥30 kg·m-2 are considered obese, which is calculated using the following equation: = ( ) • ℎ ℎ( ) (1) The prevalence of obesity has increased substantially across the United States (US) over the past 20 years, with over 100 million adults currently classified as obese (Hales, 2017). The growing prevalence of obesity has reached epidemic status resulting in over 147 billion dollars annually in medical expenses (Finkelstein, 2009). The relationship between all-cause mortality and body weight is not entirely clear (Ades, 2010); however, those who are obese are known to be at higher risk for a variety of health conditions such as cardiovascular disease, type 2 diabetes, and respiratory complications (Bastien, 2014; Beuther, 2006; Hubert, 1983). Thus, it is imperative that obese individuals lose weight in order to reduce the potential negative health consequences and ease the substantial economic burden. A variety of methods exist to help

individuals lose weight, including: changes in dietary behaviors, engaging in regular exercise routine, and participating in pharmacological, and or surgical treatments (Santos, 2017). In 2017, nearly 44% of US adults engaged in at least one weight loss strategy (Santos, 2017). Measuring changes in body composition is a 1 useful method to track the effectiveness and progress in those trying to lose weight. However, obesity can sometimes prove to be an obstacle in the accurate estimation of body composition because equipment used for measurement cannot always accommodate larger body sizes, and some assumptions that these devices make based on normal populations do not apply to obese individuals. Common methods of estimating body composition aim to measure the amount of fat mass (FM) versus fat free mass (FFM) that make up the body (Fields, 2002; Lee, 2008). This two-part approach is known as the two-compartment model, and uses the densitometric method by categorizing body

composition based on the inherently different densities of FM and FFM. Air displacement plethysmography (ADP) is a favored method of body composition estimation in many populations due to its relative ease of use, and ability to comfortably accommodate larger individuals. Dual X-ray absorptiometry (DXA) further separates FFM into bone and lean tissue constituents while still accounting for FM. Thus, DXA is considered a more robust measure of estimating body composition compared with ADP because it can separate tissues into three, as opposed to two compartments. Air Displacement Plethysmography Use of ADP in obese individuals is practical because it requires little technical skill, and can accommodate larger individuals (Bernhard, 2016). By measuring body mass and volume, density can be determined. While mass is typically measured by a scale, ADP measures volume by the displacement of air. Subsequently, the calculated density is used to estimate percent body fat (%BF). To more precisely

estimate body composition based on volume, factors that have the potential to alter body volume measurements are important to consider. For air displacement devices, the volume of gas within the thoracic cavity, termed 2 thoracic gas volume (VTG), plays an important role in the accuracy of body volume measurements. The ADP device can predict or measure average lung volumes during tidal breathing within the chamber. In normal weight adults, the predicted and measured VTG (VTGpred and VTGmeas respectively) are similar to one another, along with the respective estimates of %BF using VTGpred and VTGmeas (D. Wagner, 2015) Yet, there still are gaps in knowledge with how these two methods compare in obese adults, whose lung volumes at rest are different than normal weight adults of the same height and age. Wagner (2015) analyzed the agreement of these methods in athletes and observed that the subjects with the smallest VTG had their VTG overestimated and those with a higher VTG had their

VTG underestimated. This may suggest that obese adults who demonstrate lower operational lung volumes at rest, may have less consistent findings between VTGpred and VTGmeas. Dual X-ray Absorptiometry DXA is a method of measuring body composition using photon absorptiometry. The device relies on the core concept that X-ray light will be attenuated as a function of the tissue it passes through (McCrory, 1998b; Pietrobelli, 1996). DXA is a popular tool that often can be found in many research and clinical settings, making it useful in comparing body composition in epidemiological studies (Cornier et al., 2011) While DXA can provide more robust measurements to estimate body composition, similar to ADP, it is still limited by the assumptions regarding the density of human tissue. The benefit of DXA in contrast to ADP is that measures for estimating %BF are independent of VTG. DXA cannot be substituted for a gold standard such as the four-compartment model, but its broadened use in clinical

and 3 research practice serves as an anchor to compare other accessible methods of body composition measurement. Summary Statement of the Problem It is unknown whether estimation VTG by VTGpred will be different in obese adults, and if those potential differences will contribute to greater error in the %BF estimations compared to VTGmeas in obese adults compared to normal weight adults. By understanding the impact that obesity may have on %BF estimates, more care can be taken by researchers and clinicians to ensure the most reliable techniques are being implemented for estimating %BF by ADP in an obese population. Purpose of the Study The primary purpose of the study was twofold: 1) to examine VTGpred and VTGmeas in obese (OB) and normal weight (NW) adults and 2) to examine the %BFVTGpred and %BFVTGmeas in OB and NW adults. A secondary purpose was to compare %BF estimates obtained via Bod Pod with an estimate obtained via DXA, a lung volume independent technique. Delimitations

The study was delimited by the following: 1. Males and females between the ages of 18 and 45 years participated 4 2. All doors to the room with Bod Pod remained closed during calibration and testing in an effort to minimize air flow (Lowry & Tomiyama, 2015). 3. The Bod Pod and DXA devices were calibrated the day of each visit 4. All subjects wore minimal skin tight garments along with a swim cap in an effort to minimize surface area artifact (SAA) for the Bod Pod. 5. All subjects wore the same garments for DXA as for the Bod Pod to maintain consistency across methods of measurement. 6. Height of the subjects was measured to the nearest centimeter 7. Weight of the subjects was measured to the nearest kilogram 8. All of the subjects voided their bladder before the test 9. All of the subjects completed tests back to back 10. All of the subjects refrained from exercise in the two hours prior to testing 11. All of the subjects fasted two hours before the visit Limitations

Interpretation of the results should consider the following limitations: 1. All of the subjects were from the same geographical area 2. Some subjects had facial hair and/or body hair not accounted for with skintight gear. 3. Skintight garments will make up some of the measured mass of the individual 4. The Bod Pod assumes uniform density of FFM. 5 Research Question The primary research question was to examine the potential differences in VTGpred, and VTGmeas, and the respective calculations of %BF in OB compared with NW adults. The secondary research question was to examine %BF via ADP (%BFVTGpred, %BFVTGmeas) with %BF from DXA (%BFDXA). The following research questions were addressed: 1. Are VTGpred and VTGmeas significantly different in OB and in NW adults? 2. Are the differences between VTGpred and VTGmeas significantly associated with BMI? 3. Are %BFVTGpred and %BFVTGmeas significantly different in OB and NW adults? 4. Are %BFVTGpred, %BFVTGmeas, and %BFDXA significantly

different in OB and NW adults? 5. Are the differences between VTGpred and VTGmeas significantly related with the differences between %BFVTGpred and %BFVTGmeas in OB and NW adults? Hypotheses The primary hypotheses of the study are: 1. VTGpred and VTGmeas will be significantly different in OB adults but not in NW adults. 2. The differences between VTGpred and VTGmeas will be significantly associated with BMI. 3. %BFVTGpred and %BFVTGmeas will be significantly different in OB adults but not in NW adults. 6 4. %BFVTGpred, %BFVTGmeas, and %BFDXA will be similar in NW adults; %BFVTGpred, %BFVTGmeas, and %BFDXA will be significantly different in OB adults, with %BFVTGmeas similar to %BFDXA in OB adults. 5. The differences between VTGpred and VTGmeas will be associated with the differences between %BFVTGpred and %BFVTGmeas in OB and NW adults. Definition of Terms Obesity- Excess amount of body weight for a given height (Wellens, 1994). Air Displacement Plethysmography- The measure of

volume via the displacement of air (Aitkens, 1995). DXA- Machine that measures the attenuation of high and low energies of X-rays passing through the body to evaluate body composition (Toombs, 2012). Body Mass Index- A ratio of one’s mass to their height squared (Wellens, 1994). Thoracic Gas Volume- Volume of air within the lungs at the end of a tidal breath (D. Wagner, 2015). Forced Vital capacity- Maximal volume of air that can be exhaled after a forced exhalation (Robert Crapo, 1994) Forced Expiratory Volume in 1 second- Maximal volume of air exhaled, after a maximal inhalation, in the first second of a forced exhalation (Robert Crapo, 1994). 7 Literature Review Obesity is an Epidemic Obesity is defined as having an excess accumulation of body mass in respect to one’s height. It is increasingly prevalent in affluent societies that are living in dietary excess (Kopelman, 2000). Within the US alone, over one-third of the population is now considered to be overweight. The

prevalence of obesity has increased drastically over the past 50 years (Kuczmarski, 1994; Ogden, 2015). The National Health and Nutrition Examination Survey (NHANES) reported in 2017, that the prevalence of obese adults over 20 yr has reached 39.6% That percentage applied to national health estimates in 2017 from the United States Census Bureau (2017 National Population Projections Datasets, 2018), projected 96 million adults 20 yr or older in the United States would be considered OB. That is not even considering that over 18% of the youth (ages 2-19 yr) are now OB with significantly increasing trends (Hales, 2017). Obesity has become so prevalent, that it is now affecting the economic health of the nation. The economic cost of obesity is a public health concern. There is a link between obesity, and medical spending. Those who are obese are at an increased risk for cardiovascular disease, type 2 Diabetes, along with various respiratory complications (Bastien, 2013; Chan, 1994; Zammit,

2010). As of 2008, aggregate medical cost of obesity was estimated to be up to 147 billion dollars, representing 9.1% of all annual medical spending (Finkelstein, 2009). In epidemiological studies the most common tool for measurement is BMI. It is a useful method to classify weight status amongst large populations and make valuable comparisons within and between populations. BMI classification is also advantageous in 8 identifying large groups who are at higher risk of morbidity and mortality. The idea behind the BMI formula is based on the assumption that the varying weight of people of the same height is generally due to changes in FM (Kopelman, 2000). The current standard of the cutoff points for the classification of those overweight were suggested by the world health organization (WHO) experts. They identified two different grades of being overweight These two levels are described as preobese, and obese, which can be subdivided into obese class I, II, and III in order of

least to most severe. The cut-off points for each are 250-299 kg∙m-2, 30.0-349 kg∙m-2 350-399 kg∙m-2, and ≥40 kg∙m-2 respectively (Wellens, 1994) While there are high associations between increases of BMI and increased risk for disease, the consequence of obesity is more directly related to fat tissue, and the overall distribution of that fat tissue in the body (Kopelman, 2000). For example, an increase in FM will increase the total amount of blood volume, and subsequent amount of oxygen that the body consumes increasing cardiac output, placing added stress on the heart (Bastien, 2013). A study done by Krotkiewski et. al, highlighted the differences in regional distribution of adipose tissue within males and females. Men predominately have more abdominal adiposity, while women have more peripheral distribution of fat (gluteal and femoral regions). Males were more likely to indicate signs of metabolic disease, such as higher levels of fasting glucose and triglycerides. Females

with regional adipose tissue similar to the male group showed similar increases in metabolic disruption (Krotkiewski, 1983). With increases in FM, there are uniform increases of visceral fat. The increase of this intra-abdominal visceral adipose tissue (upper body obesity) that is common in men, contributes to organ and hormone dysfunction. Respiratory complications arise from the distribution of fat that accumulates around the thoracic cage, and abdomen (Kopelman, 2000; Krotkiewski, 1983) 9 Respiratory Complications in Obesity Increases of BMI are associated with decreases in lung function and lung volumes (Koenig, 2001a; Mejbel, 2016; Zammit, 2010). A case control study recruiting 100 individuals ages 18-45 yr found significant spirometric reduction in the overweight males and females. Significant negative correlations were observed with %BF and forced vital capacity in 1 second (FEV1) (−0.772 p < 0001), and with %BF and forced vital capacity (FVC) (−0.869 p < 0001)

(Mejbel, 2016) This decrease in lung function and lung volume is, in part, due to the accumulation of fat within the anterior chest and abdominal wall (D'Angelo, 1999; Kopelman, 2000). A cross-sectional population based study was carried out with a sample of 121,454 men and women (45.7 ± 123 yr) in Paris to investigate the risk of lung function based on characteristics of metabolic syndrome. In their findings those with larger waist circumferences were at higher odds for impaired lung function (Leone, 2009). Respiratory Compliance Obesity contributes to a large load being placed on the respiratory muscles. The respiratory muscles have to compensate for the extra load contributed by excess fat in order for alveolar ventilation to be maintained (Sampson, 1983). A prevailing atypical lung volume measurement across multiple studies involving obese subjects is a decrease in expiratory reserve volume (ERV) (Koenig, 2001b; Littleton, 2012). These evident decreases in lung function can

be explained in part by the lengthened duration of respiratory muscle activation during exhalation, and the effect of upper adipose tissue on respiratory mechanics. Whereas adipose tissue will compress around the thoracic cage, diaphragm, and lungs, negatively affecting total respiratory compliance. Compliance can be defined as the ratio of change in 10 pressure to changes in volume (Suratt, 1984). A decreased compliance of the respiratory system would indicate that a given change in pressure would change the volume of gas in the lungs less (Suratt, 1984). Total respiratory compliance is equal to the sum of chest wall compliance and lung compliance (Harris, 2005). A decreased total respiratory compliance in obesity is thought to have dynamic contributions from each of these parts. A significant decrease in the pressure volume curve slop indicated in Figure 1, relates directly with a decrease in total respiratory compliance. Figure 1. The effect of obesity on the pressure volume

curve; Pst, static pressure of the total respiratory system; ∆V, change of volume (Harris, 2005). How is Body Composition Measured? The term body composition encapsulates multiple subunits of differentiated tissues and organs, such that the total body mass will equal the sum of these individual parts. Ideally, each constituent, or compartment, needs to be taken into consideration to accurately account for 11 body composition. Given the complexity of the human body, it proves difficult to itemize, and quantify each individual piece of this larger puzzle (Wang, 1999; Ward, 2018). With technological advances, more of these constituents can be quantified for application to better describe the total body composition. More refined methods are not cost effective and require more training to use. As a result, the two compartment model approach to measurement is popular. The methods to measure body composition have greatly changed over the years. There are multiple techniques used to

electronically estimate body fat: bio-electrical impedance (Bernhard, 2016), DXA, quantitative human tomography, ADP, magnetic resonance imaging, quantitative magnetic resonance, 3-dimensional photonic scanners, and positron emission tomography (Lee, 2008). A relatively more practical method of quantifying body composition is through ADP, this method is more mobile, and reduces subject and technician error (Dempster, 1995). The derived density of the whole body can be used to estimate a twocompartment model of body composition (FM and FFM) (Siri, 1961) The density of the human body can be derived by the relation between its’ mass and volume (2) = ( )/ ( ) (2) While mass is easily measured, the volume of the body is more difficult to determine. Body volume is not uniform throughout; cavities within the lungs and gastrointestinal tract are unable to be detected through superficial measurements of volume. Heat leaving the body also has potential to alter pressure measurements

during ADP. Not correcting for the volume of air within your body will greatly affect the subsequent calculations of density. Methods for controlling these variables usually are constringent, and can sometimes be a deterrent for subject participation, especially when measurements are conducted in water. New technology 12 has opened different avenues for collecting accurate measurements that also take less effort for the subject, and leave less room for technician error. The use of Bod Pod for plethysmography has grown in popularity because it can provide accurate measurement of density and is a convenient tool for technicians and patients to use. The Bod Pod utilizes ADP to indirectly measure body volume. When an individual sits inside a closed chamber, the amount of air within said chamber will be displaced because of the addition of a new volume inside the chamber. The volume of air displaced will be equal to the volume of the body entering the closed system. The Bod Pod

measures the pressure change initiated by a volume perturbing diaphragm while the subject is within the chamber (Aitkens, 1995). Past methods of ADP required isothermal conditions to measure volume by pressure, this applies the basic principles of Boyle’s law that states pressure and volume have an inverse relationship, such that as volume increases, pressure will decrease, given that temperature does not change. Keeping thermal conditions constant during body density measurement proves to be a laborious task (Fields, 2002). The Bod Pod makes use of both Boyle’s gas law and Poisson’s law, which allows for air to expand and compress within the closed chamber and still have volume and pressures accurately measured. This technique is useful to account for the increase in temperature that introducing a human subject to the chamber will cause. As a result, being able to compensate for changes in temperature, measurements can be assessed with less effort (Dempster, 1995; D. R Wagner,

2000) The Bod Pod consist of one structure with two coinciding chambers (front and rear) which sizes are about 450 L and 300 L respectively. The front chamber is where the subject is housed. The second chamber is separated by the molded seat in which the subject sits on during the testing. The rear chamber houses electronics, pressure transducers, breathing 13 circuits, valves and the diaphragm that initiates volume perturbations (Figure 1) (Aitkens, 1995). The relations of volume and pressure are applied to measurement when the subject has been placed in the front chamber, and the door has been sealed by multiple electromagnets. A diaphragm in the rear chamber oscillates in the positive and negative direction at a magnitude of about 350 mL inducing pressure changes of about 1 cmH2O within the system (Aitkens, 1995). Volume will have a linear relationship with these pressure changes. Figure 2. Diagrammatic representation of the main components of the Bod Pod system from the

Official Journal of American College of Sports Medicine (Aitkens, 1995). In order to accurately measure body volume, it is important to account for factors such as clothing, SAA, and lung volumes (Aitkens, 1995; Fields, 2002; Higgens, 2001; McCrory, 1998a). The raw body volume (BVraw) that is measured using pressure-volume 14 relationships is corrected taking into consideration SAA and VTG. Effects of clothing and hair are mitigated by the standard use of minimal skin-tight gear and a swim cap. Other bodily hair may be worth noting in error of measurements (Higgens, 2001). Body surface area, given a person’s height and weight is estimated using the Dubois formula (Bois, 1916). The estimated body surface area is then multiplied by a constant that defines the effect surface area has on volume measurement. The product of these factors gives a correction for SAA. VTG is either predicted with an estimation equation based on age, and height, or directly measured with plethysmographic

techniques. The formula to determine body volume includes these factors: = − + 40% (3) Where BVcorr is corrected body volume, BVraw is raw measurement of body volume based from Boyle’s law, and 40% of VTG is considered because air within the lungs is considered isothermal and is 40% more compressible than adiabatic air within the chamber. All values are expressed in liters (Dempster, 1995; McCrory, 1998a). Thoracic gas volume may be obtained from the Bod Pod by an estimation equation or through an actual lung volume measurement within the Bod Pod. VTGpred is calculated for the Bod Pod as: = + 0.5 (4) Where functional residual capacity (FRC) is the volume of air within the lungs at the end of a passive breath. During normal breathing, the amount of air moving in and out of the lungs is tidal volume (Vt). The mid-point of an exhalation is measured, the 50% of measured Vt the average volume of air being displaced during normal breathing. The following equations developed by (R.

Crapo, Morris, Clayton, & Nixon, 1982), are how FRC and VTG were 15 estimated accounting for age and height. In order to develop prediction equations, multiple linear regressions of each lung volume were generated against combinations of the independent variables height, age, and weight SAA. Regression equations were also calculated using transformations of both the independent and dependent variables. For each equation, the standard of the estimate and the correlation coefficient were calculated. For the equations reported, residuals (measured value minus predicted value) were graphically analyzed by comparing the residual values with the independent variables and the predicted dependent variables. Bod Pod is a type of body density measurement. There is a wide variations of body composition values dependent of the methods of measurement that is utlized, although some of this difference may be accounted for by biological variability and technical precision, it is widely

unknown as to why these values are different (Fields, 2002). Average Thoracic Gas Volume ADP can measure body volumes, and VTG. The value for VTG continuously changes during the act of breathing (inhalation, exhalation). FRC is described as the volume of gas in air at the end of a passive exhalation. The amount of volume in the lungs during resting, tidal breathing ranges from FRC to volume at the end of an inhalation, end inspiratory lung volume (EILV) (Wanger, 2005). Advanced body composition measurements devices such as ADP estimate VTG using a regression equation created from healthy, non-smoking adults (R. Crapo et al., 1982) Accounting for the lung volumes better depicts the density of an individual after pressure displacement (Aitkens, 1995). Individuals’ who’s lung volumes are lower relative to others that are their same sex, age, and height are inaccurately depicted by 16 these regression equations (Minderico, 2008; D. Wagner, 2015) For example, an obese individual

will have a smaller FRC and subsequent ERV; the estimated equation that is based on age and height (R. Crapo et al, 1982), will not account for smaller VTG due to added adiposity. With this overestimation of FRC in obese individuals, ADP may estimate the volume of during the measurement incorrectly, and therefore the measured %BF would potentially be different. VTG Measurement The technique the Bod Pod uses to measure thoracic gas volume is based on the relation between pressure and volume while temperature is constant (Dempster, 1995). Boyle’s law states that pressure and volume have an inverse relationship (5) = (5) where P1 is the pressure at FRC, V1 is FRC, and P2 is the pressure at the end of a pant and V2 is the acquired lung volumes (Dubois, 1956; West, 1999). When the subject initially comes onto the mouthpiece, lung volumes are unknown, without any flow the pressure of alveolar gas and atmospheric pressure are the same. This is only true if the glottis is open and the

cheeks are held rigid (so they do not puff) If the subject was to voluntarily expire, which would compress the gas, the difference in pressure would describe the changing lung volumes during panting at the time of measurement, according to Boyle's law. One way to measure lung volume is to have the subject inhale after the end of a normal expiration when the closed system has been occluded and perform a panting maneuver; this is the method the Bod Pod uses to measure VTG. This method is usually preferred because it allows for 17 retracing of the changes in volume and has less change in intrathoracic pressure (Dubois, 1956). Dual Energy X-ray Absorptiometry In the study of body composition, DXA is a common device utilized in research (Pietrobelli, 1996). It is often used to diagnose osteoporosis, osteopenia, and other bone diseases (Laskey, 1996; Sartoris, 1989; Toombs, 2012). Generally speaking, DXA machines measure the attenuation of high and low energies of X-rays passing

through the body. The Xrays are comprised of photon particles that are transmitted via electromagnetic energy Attenuation of the X-ray is dependent on the intensity of the photon particles, and the density of the substrate it is passing through. For example, bone mineral (higher density) will have larger decreases of photon intensity compared to soft tissue (lower density) as it passes through the body (Pietrobelli, 1996). To determine bone mineral density, DXA software assumes a compartment model where the body is divided into bone mineral, and soft tissue (skin, fat, muscles, fluids etc.) (Toombs, 2012) To differentiate between these two compartments, two intensities of X-rays are used. Low density material attenuates the X-ray less because more photon particles can pass through the body, the opposite is true for denser bone mineral. These relationships are used to differentiate between bone mineral density, fat mass, and fat free mass (Pietrobelli, 1996). The Hologic manufactured

DXA performs its measurements by scanning the body with X-rays that are rapidly switching from high and low intensities sourced from below the scanning table (Laskey, 1996). The attenuated photons are detected and measured above the subject being scanned (Figure 2). Although the main purpose of the DXA has been in quantifying bone density, due to advances in detecting 18 changes of photon intensity as it is attenuated through the body, resolution of images has improved (Toombs, 2012). With improved resolution DXA has also gained the ability to delineate between other subdivisions of body composition such as FM and FFM. Figure 3. DXA measures X-rays passing through the body at high and low energies The Xray source is located below the subject, and the attenuation is measured by the detector hovering over the table (Toombs, 2012). For the purpose of this study, DXA is appropriate to compare with %BFVTGpred and %BFVTGmeas. ADP is a two compartment model of estimating body

composition dividing body composition into FM and FFM based on measurements of density (Siri, 1961). Volume plays an important role in determining density. The assumptions made by the Bod Pod 19 software to account for lung volumes does not represent outliers well, especially if an outlying variable can change the Bod Pod’s software calculation for body volume (effect of SAA or VTG). As a result, the assumptions used by VTGpred have to be carefully considered before choosing whether it is appropriate. Measures can potentially be inaccurate for individuals who deviate from the constants that the devices are fundamentally based on (Kohrt, 1995; D. Wagner, 2015) This can potentially also be true in terms of accuracy of estimating lung volumes in an obese population, who tend to breathe at lower than normal operational lung volumes (Salome, 2010). A benefit of DXA in comparison to ADP is that estimates of body composition are independent from measures of lung volumes (Smith-Ryan,

2017), and it does not use density to predict body fat. Although the trueness of the measurement of body composition using DXA has promise in the future, it still is debated whether or not it can be considered a reference standard (Kohrt, 1995; Laskey, 1996; Pietrobelli, 1996; Shiel, 2018). Despite these disagreements, DXA is a commonly used tool in research that yields accurate and precise measurements of soft tissue (Svendsen, 1993). The body composition of pigs were measured using DXA, then with chemical analysis after postmortem homogenization, the respective r value for the comparison was > 0.97 with a SEE < 3% (Svendsen, 1993) ADP has often been compared to DXA and showed high correlations within several populations (Ballard, 2004; Levenhagen, 1999; Nunez, 1999; Radley, 2005). ADP is an attractive method to estimate body composition due to its ease of use, and its ability to accommodate larger body volumes; it is important to see how these two common tools of measuring body

composition compare with one another. 20 The state of obesity is a well-known complication for estimates of body composition with both ADP and DXA. Densitometry via ADP assumes a constant FFM hydration and density (Brozek, 1963; Siri, 1961). In an obese population these assumptions can be inaccurate due to unequal distribution of fluids and adiposity throughout the body (Brozek, 1963; Siri, 1956, 1961; Waki, 1991). The ratio of attenuation between a high energy photon beam and low intensity photon beam can be used to identify components within the body. Hydration status can skew the resulting r values of soft tissue, which can change the result of the subsequent FM. For example, an addition of 1 kg of extra cellular fluid to the reference man could result in a 0.6% underestimation of body fat (Pietrobelli, 1996) Ideally, the more compartments that are not assumed, the more accurate the resulting measurements will be (Smith-Ryan, 2017). However more detailed methods to account for

subdivisions of body composition such as total body water (TBW) are more expensive, and less broadly used in clinical and research settings (Das, 2003, 2005). Therefore, it is important to compare common tools of body composition assessment such as ADP and DXA in a variety of situations involving obese individuals to further validate this equipment in accurately estimating body composition. 21 Methods Subjects Subjects were recruited via email, posted flyers, and word of mouth within the community. To be included in the study, subjects had to be between the ages of 18 and 45 yr Subjects were apparently healthy (i.e, no signs or symptoms of disease) and were nonsmokers Subjects with a BMI of 185-249 kg·m-2 were classified as NW Subjects with a BMI of 30.0-399 kg·m-2 were classified as OB Subjects were excluded from the study if their BMI was not within the mentioned ranges. Subjects were also excluded for taking medication that effected hydration level (diuretics and/or

corticosteroids), if they had a history of smoking, had any lung dysfunction that could potentially change lung volumes, or if subjects had any type of metal plating within their body. The project was approved by the local Institutional Review Board (IRB# 18-0355), and all subjects voluntarily provided informed consent prior to participation. Study Design and Protocol All testing procedures were completed within a single laboratory visit. Prior to the study visit, subjects were emailed and asked to bring form fitting clothing. Upon arrival, subjects completed an informed consent, medical health history questionnaire, and a 24-hour health history questionnaire. Subsequently, body composition was estimated using ADP with VTGpred, and VTGmeas, and with the DXA protocol. Test by DXA or methods using ADP were selected in random order. When ADP was chosen, VTGpred, and VTGmeas were selected in random order. 22 Body Composition with ADP using VTGpred Steps to calibrate and measure the

Bod Pod were consistent with recommendations by the Bod Pod user’s manual. After the Bod Pod was powered on, the quality control calibration was used to calibrate the pressure transducers within the chamber. The chamber was calibrated using a capsule with a known volume (50.122 L) The Bod Pod weight scale also was calibrated using a standard 20 kg weight. The general population equation was used to predict VTG in all subjects. Before each subject entered the chamber, they were asked to remove all jewelry and other SAA other than skin tight gear. A swim cap was placed on each subject’s head to exclude isothermal air compression of trapped gas within the hair. Body mass was recorded using the Bod Pod’s scale. The body volume test was initiated once each subject remained motionless within the Bod Pod during the time of each body volume measurement. For one successful trial, body volume was measured at least two times If the two body volumes were more than 5% different, a third body

volume measurement was initiated. The average value from the two body volumes that were less than 5% different, was adjusted by a proprietary correction factor and then subsequently used as the volume component in the calculation of density. If all three body volumes were greater than 5% different from each other, the entire trial was repeated. Three successful trials were completed by each subject. Measurements reported from this portion of the visit included VTGpred, %BFVTGpred, FM from ADP using VTGpred (FMVTGpred) and FFM from ADP using VTGpred (FFMVTGpred). 23 Body composition with ADP using VTGmeas Calibrations for the Bod Pod using VTGmeas were similar to calibrations for VTGpred, except before calibration of the pressure transducers, a disposable tube and antimicrobial filter were added to a port inside the chamber, along with a nose clip that was clipped to the filter. These pieces of equipment were used during the panting maneuvers; calibrating the pressure transducers

with the equipment inside the chamber corrected for the added volume said equipment introduces during body volume measurement. Before the subject entered the Bod Pod, they were thoroughly instructed through the techniques of the test to measure VTG. Each subject was asked again to remove all jewelry or SAA other than form fitting clothing. Body mass was recorded using the Bod Pod’s scale. The body volume measurement was identical to the VTGpred method, except the disposable tube, antimicrobial filter, and nose clip were in the chamber during each measurement. When the body volume measurements met the same criteria as for ADP with VTGpred, the VTGmeas was initiated. Each subject was asked to place their hands on their cheeks and breathe through the internal chamber tube at a rate guided by the computer monitor while wearing a nose clip. After Vt was established, the Bod Pod instructed the subject to perform a soft panting maneuver. At the end of an exhalation, an occlusion occurred

during an inspiration of a pant. With the mouth occluded the pressure measured at the mouth during an inspiratory maneuver is equal to the pressure within the lungs and can be used to calculate lung volume using Boyle’s law (Dubois 1965). Following the occluded inspiratory effort, the airway was reopened and the subject came off of the mouthpiece. The VTGmeas was considered acceptable if the maneuver received a merit score below 10 and airway pressure below 30 cmH2O (the calculation for merit score was proprietary) as indicated by the Bod Pod software. If a maneuver was deemed unacceptable, 24 the manufacturer recommended the technician ensure the subject pant gentler and make a tight seal around the mouthpiece. The VTG was measured after each body volume measurement. The three body composition trials with three reproducible measures of VTG (error of 5%) were reported. Measurements reported from this portion of the visit included VTGmeas, %BFVTGmeas, FM from ADP using VTGmeas

(FMVTGmeas) and FFM from ADP using VTGmeas (FFMVTGmeas). Body Composition using DXA A standard whole body scan protocol was used to measure body composition via DXA. To calibrate the DXA machine, a phantom spine with a known (ie, standard) density was positioned between two laser cross hairs and the attenuation of X-ray light through the phantom spine was measured. The calibration passed if measures of density were similar to the actual density of the reference phantom. Before testing could commence, the subject’s information, including age, height, and weight were entered into the system software. Subjects were asked to lay in the supine position on the scanning table. An attempt to straighten/align the hips prior to the scan was made by the researcher by instructing subjects to relax their waist while the researcher gently pulled at the subject’s ankles. Subjects were then asked to sit straight up, take a big breath in, hold their chin to their chest, and lay back down. This was

to ensure that subjects’ spines were positioned properly for body composition analysis. After the subject was properly positioned, they were told to point their toes toward each other, then a harness fastened them in that fixed position. This was done so the full dimensions of the feet could be scanned 25 Then the two minute scan was initiated. Measurements reported from this portion of the visit included %BFDXA, percent of trunk fat from DXA, FM from DXA, and FFM from DXA. Data Analyses Independent t-test were used to test for group differences in age, weight, and height. A 2 x 2 mixed-design analysis of variance was used to examine the effects of group and method on measurements of VTG. A 2 x 3 mixed-design analysis of variance was used to examine the effects of group and method on measurements of %BF. Sphericity was tested using Mauchly’s test. When the assumption of sphericity was violated, a Geisser-Greenhouse correction factor was applied. Eta-squared (η2) was used to

quantify the effect size of the variance between measures. Pearson correlation coefficients (r) were used to assess the relationship between measured variables. Significance was set at α = 005 Data were reported as mean ± standard deviation (SD). 26 Results 4.1 Subject Characteristics A total of 38 subjects volunteered to participate in the study. Subjects did not qualify due to having a BMI outside of the qualifying range. Twenty-four (N=24) subjects qualified for the study and completed all study procedures. All subjects were non-smokers, were apparently healthy, and were deemed fit to participate in the study based on a brief medical history, and 24-hour health history questionnaire. Of the 24 subjects who participated in the study 15 were classified as normal weight (four males) and nine were classified as obese (nine males). Anthropometric data are provided in Table 1 Table 1. Subject Characteristics Age (yr) Wt (kg) Ht (cm) BMI (kg•m-2) NW (n=15) NW Range 25 ± 7

62.4 ± 69 167.4 ± 50 22.2 ± 17 18 - 41 52.2 - 718 161.8 - 1750 18.6 - 249 OB (n=9) 24 ± 7 103.5 ± 127* 179.4 ± 107* 32.1 ± 19* OB Range 21 - 27 91.3 – 1287 161.1 – 1975 30.3 - 359 Values are mean ± SD. NW, normal weight; OB, obese; Wt, weight; Ht, height; BMI, body mass index. * Significantly different compared with NW (p < 0.01) 27 Measured vs Predicted Thoracic Gas Volumes Table 2 Predicted and measured VTG VTGpred(L) VTGmeas(L) Mean ∆(L) NW (n=15) 3.326 ± 0232 3.353 ± 0755 -0.027 ± 0629 OB (n=9) 4.000 ± 0515 3.577 ± 0916 0.420 ± 0578 Values are mean ± SD. NW, normal weight; OB, obese; VTGpred, predicted thoracic gas volume; VTGmeas, measured thoracic gas volume; Mean ∆, mean difference of VTGpred and VTGmeas. Mean values for VTGpred and VTGmeas, along with the mean differences between the two measurements, are provided in Table 2. There was no group by method interaction (F1,22 = 3.017, p = 0096, η2 = 011) Additionally,

there was no main effect of method (F1,22 = 2.330, p = 0141, η2 = 009) or main effect for group (F1,22 = 3685, p = 0068, η2 = 0.14) The differences between VTGpred and VTGmeas were not significantly related with BMI (r = 0.33, p = 011) However, the differences between VTGpred and VTGmeas were significantly related with trunk fat percentage (r = 0.47, p = 002) Figure 4 depicts the individual differences between VTGpred and VTGmeas (i.e, residuals) plotted against the corresponding VTGpred for all subjects. In the NW group there were approximately equal numbers of positive and negative residuals. However, in the OB group there tended to be more positive than negative residuals. The differences between VTGpred and VTGmeas were not significantly related to VTGpred (r = −0.02, p = 0945) 28 VTGpred - VTGmeas(L) 2.000 1.500 1.000 0.500 0 -0.500 -1.000 -1.500 -2.000 0 3.000 4.000 5.000 VTGpred (L) Figure 4. Thoracic gas volume difference (VTGpred - VTGmeas) against the mean of

VTGpred in normal weight (•) and obese (□) subjects; VTGpred, predicted thoracic gas volume; VTG residuals; difference between VTGpred, and VTGmeas (r = −0.02, p = 0945) Measures of Body Fat using ADP and DXA Table 3 Measures of Body Fat using ADP and DXA %BFVTGpred(%) %BFVTGmeas(%) %BFDXA(%) NW (n=15) 24.7 ± 64 24.5 ± 53 26.1 ± 51 OB (n=9) 32.9 ± 43 32.2 ± 39 30.9 ± 30 Values are mean ± SD. NW, normal weight; OB, obese; %BFVTGpred, percent body fat from predicted thoracic gas volume; %BFVTGmeas, percent body fat from measured thoracic gas volume; %BFDXA, percent body fat from DXA. 29 Table 4 Measures of FM using ADP and DXA FMVTGpred(kg) FMVTGmeas(kg) FMDXA(kg) NW (n=15) 15.5 ± 48 15.4 ± 42 16.6 ± 43 OB (n=9) 34.0 ± 51 33.2 ± 52 32.6 ± 53 Values are mean ± SD. NW, normal weight; OB, obese; Values are mean ± SD; FMVTGpred, fat mass from predicted thoracic gas volume; FMVTGmeas, fat mass from measured thoracic gas volume. Table 5

Measures of FFM using ADP and DXA FFMVTGpred(kg) FFMVTGmeas(kg) FFMDXA(kg) NW (n=15) 46.9 ± 61 47.0 ± 55 46.7 ± 52 OB (n=9) 69.6 ± 104 70.3 ± 99 56.5 ± 146 Values are mean ± SD. NW, normal weight; OB, obese; Values are mean ± SD; FFMVTGpred, fat free mass from predicted thoracic gas volume; FFMVTGmeas, fat free mass from measured thoracic gas volume. Mean values for %BFVTGpred, %BFVTGmeas, and %BFDXA can be found in Table 3. There was a significant group by method interaction for the measure of %BF (F2,44 = 10.060, p = 0.001, η2 = 031) Additionally, there was a significant main effect for group in %BF (F1,22 = 10.944, p = 0003, η2 = 001), but not for method (F2,44 = 0663, p = 0479, η2 = 033) Mean values for FMVTGpred, FMVTGmeas, and FMDXA can be found in Table 4. There was a significant group by method interaction for the measures of FM (F2,44 = 9.944, p < 0001, η2 = 0.30) Additionally, there was a significant main effect for group in FM (F1,22 = 78616, p

< 0.001, η2 = 011) Mean values for FFMVTGpred, FFMVTGmeas, and FFMDXA can be found in Table 5. There were a significant group by method interaction for the measures of FFM 30 (F2,44 = 20.995, p < 0001, η2 = 036) Additionally, there were significant main effects for group (F1,22 = 58.936, p < 0001, η2 = 004) and method in FFM measures (F2,44 = 0998, p < 0.001, η2 = 027) The mean differences of %BFVTGpred, and %BFVTGmeas plotted against the measure of %BFVTGpred in the NW and OB groups are shown in Figure 5. At lower %BFVTGpred, there were large negative residuals, but the residuals were positive at higher %BFVTGpred. As a result, the differences between %BFVTGpred and %BFVTGmeas were significantly related to %BFVTGpred (r = 0.60, p = 0002) In the OB group, the majority of the %BFVTGpred - %BFVTGmeas (%) residuals were positive. 5.0 4.0 3.0 2.0 1.0 0.0 -1.0 -2.0 -3.0 -4.0 -5.0 0 10.0 20.0 30.0 40.0 50.0 %BFVTGpred (%) Figure 5. Percent body fat difference

(%BFVTGpred - %BFVTGmeas) across %BFVTGpred in normal weight (•) and obese (□) subjects; %BFVTGpred, percent body fat from predicted thoracic gas. volume; %BFVTGmeas, percent body fat from measured thoracic gas volume; %BF Residuals, the difference of %BFVTGpred, and %BFVTGmeas (r = 0.60, p = 0002) 31 The amount of error of estimating %BFVTGpred is shown in Figure 6. The differences between VTGpred and VTGmeas were significantly related with the differences between %BFVTGpred and %BFVTGmeas (r = 0.92, p < 0001) In the NW group, there was an even distribution of individuals who had their VTG either under or over predicted compared with VTGmeas. A large cluster of NW subjects had no large differences both in the estimation of VTG and estimation of %BF compared with respective measured parameters. The majority %BF residuals (%) of the obese subjects had both their VTG and %BF overestimated. 5.0 4.0 3.0 2.0 1.0 0.0 -1.0 -2.0 -3.0 -4.0 -5.0 -2.000 -1.000 0 1.000 2.000 VTG

residuals (L) Figure 6. Difference in %BF (%BFVTGpred - %BFVTGmeas) as a function of difference in VTG (VTGpred - VTGmeas) for normal weight (•) and obese (□) subjects; VTG residuals; difference between VTGpred, and VTGmeas; %BF Residuals, the difference of %BFVTGpred, and %BFVTGmeas (r = 0.92, p < 0001) The mean differences of measured %BFDXA and %BFVTGpred are plotted against %BFDXA in NW and OB subjects in Figure 7. The differences between %BFVTGpred and 32 %BFDXA were significantly related to %BFDXA (r = 0.92, p < 0001) In the NW group, there were more positive residuals; in the OB group, there were more negative residuals. Figure 8 depicts the mean differences of measured %BFDXA and %BFVTGpred plotted against %BFDXA in NW, and OB groups. In the NW group there were more positive residuals; in the OB group, there were more negative residuals. The differences between %BFVTGmeas and %BFDXA were significantly related to %BFDXA (r = 0.95, p < 0001) %BFDXA- %BFVTGpred

(%) 8.0 6.0 4.0 2.0 0.0 -2.0 -4.0 -6.0 -8.0 0 20.0 30.0 40.0 50.0 %BFDXA (%) Figure 7. Percent body fat difference (%BFDXA - %BFVTGpred) against the mean of %BFDXA in normal weight (•) and obese (□) subjects; %BFVTGpred, percent body fat from predicted thoracic gas volume; %BFDXA, percent body fat from the DXA (r = 0.92, p < 0001) 33 %BFDXA - %BFVTGmeas (%) 5.0 4.0 3.0 2.0 1.0 0.0 -1.0 -2.0 -3.0 -4.0 -5.0 0 15.0 20.0 25.0 30.0 35.0 40.0 %BFDXA(%) Figure 8. Percent body fat difference (%BFDXA - %BFVTGmeas) against the mean of %BF DXA in normal weight (•) and obese (□) subjects; %BFVTGmeas, percent body fat from measured thoracic gas volume; %BFDXA, percent body fat from the DXA (r = 0.95, p < 0001) 34 Discussion Main Findings The differences between VTGpred and VTGmeas were not significantly different within the OB and NW subjects, but the moderate effect size (η2) indicates differences may be observed with a larger sample size. Differences

between VTGpred and VTGmeas were not associated with BMI but were significantly related to trunk fat percentage. OB played a significant role into the error of %BF estimations. Within the OB group, %BF was reduced using DXA than with either ADP method. In contrast, %BF was greater using DXA than with either ADP method in the NW group. The differences between VTGpred and VTGmeas were strongly related to differences between %BFVTGpred and %BFVTGmeas. Consequently, because the OB group showed a trend of having their VTG overestimated (compared to when measured), OB individuals also had overestimated values of %BF. Although this study is underpowered, there appears to be an impact of body composition on estimates of %BF due to altered operational lung volumes; this calls for more attention to be focused on the method of measurement used in an obese population. Subject Characteristics All of the NW and OB subjects were apparently healthy, non-smokers. Each group displayed body composition

(%BF) typical of their BMI classification. The two groups differed greatly by sex, with 11 females in the NW group and no females in the OB group. Males tend to have more fat free mass, and females tend to have more fat mass (Wellens, 1994). While BMI is not directly related to %BF, the %BF of the NW group using either ADP or DXA was consistent with %BF that are typically observed in relation to BMI with both males and females in a NW population; males and females with a BMI of less than 25 kg∙m-2 usually have a %BF 36 that was below 25% and 35% respectively (Hanes, 2014; Lorenzo, 2003). This evidence is consistent with what this study found, with methods using ADP or DXA mean %BF ranged from 24% – 27%. Despite the OB group being entirely males, their higher BMI was not due to just a significant height difference, but also a larger %BF, males who were classified as obese had %BF greater than 30% using ADP or DXA. This finding is consistent with a typical %BF in this population

(%BF 30% or greater) (Lorenzo, 2003). Regardless of sex differences, decreased respiratory compliance and operational lung volumes are typical in obese adults (Harris, 2005; Norman, 1960). Thus, while the current study only observed obese males, obese females would be expected to have differences in VTG at rest due to decreases in FRC that are associated with a larger BMI similar to males. VTG Differences Being obese did not significantly over predict VTG compared to normal weight adults. There was also no relationship between BMI and difference between VTGpred and VTGmeas; however, there was a significant positive relationship between trunk fat percentage and differences between VTGpred and VTGmeas. BMI is known to be associated with decreases in operational lung volumes, primarily because of the increased adiposity around the chest wall and abdominal cavity (Koenig, 2001b; Littleton, 2012; Sampson, 1983). Although there were no significant differences observed between VTGpred and

VTGmeas in the OB adults, the current effect size may indicate that a larger sample size would result in significant differences observed between the methods in the OB but not the NW subjects. Yet, the lack of statistical significance could either be because the measured VTG was not related to resting FRC, or the excess fat of the OB group was not distributed in an area that could impede total respiratory compliance. The relationship that we found with trunk fat 37 percentage and VTG differences indicate that the small differences that we did see were in part, due to the location of fat. Based on the relationships described above regarding %BF and VTG, greater differences in VTG due to trunk fat percentage could result in further error on %BF estimations by ADP. VTG is not FRC The Bod Pod predicts lung volumes based on the estimation of the midpoint of tidal volume, plus the predicted FRC (Aitkens, 1995). Although VTG and FRC are closely related, they are not the same. VTG refers

to the amount of volume in the lungs at the time of measurement. During a measurement, a subject may exhale to FRC, but at the moment they inhale, lung volumes will no longer be at FRC. To take into consideration the net amount air in the lungs at any given point in the test, the midpoint best represents the average amount of air that is in the lungs. As such, predicted VTG is expected to be slightly larger than FRC Minor alterations in breathing patterns or positioning may alter the volume amount within the lungs at the time of measurement. In terms of the actual measurement of lung volumes, it is difficult to get true measures of tidal volume (Vt) using standard techniques. Typical methods to measure lung volumes usually involve a pneumatic device connected to the subject, along with a firmly fastened nose clip. These methods are often uncomfortable and could result in alterations to normal, resting breathing patterns. A study was done observing the differences in breathing patterns

with the use of pneumatic device and nose clip, versus the less invasive magnetometer in subjects while resting in bed (Figure 9). In nearly all cases the addition of the respiratory apparatus caused a subsequent increase in V t, (124 ± 80 ml) and a decrease in breathing frequency (Gilbert, 1972). In other words, when a nose clip and spirometric measuring device were added, the very values that were intended 38 on being measured were altered. Therefore it is important to note that due to measurement of VTG within the Bod Pod, lung volumes may have been altered. Figure 9. Changes while lying supine at rest to tidal volumes from magnetometer to respiratory apparatus; breathing frequency, and ventilation. M magnetomoter; RA respiratory apparatus (Gilbert, 1972). The under-prediction of NW VTG may be, in part, due to these altered breathing patterns to compensate for changes not usually experienced during uninterrupted breathing. 39 Subjects may breathe at higher lung volumes

compared with what is predicted according to age and height because they are breathing atypically. Mean differences in lung volumes observed in the OB group, in contrast to the normal weight group, averaged 816 ml less than what was predicted. Due to the increased adiposity around the thoracic cavity usually associated with those with higher BMI, lung volumes in this population are decreased (Jones, 2006), particularly in those with a BMI ≥ 30 kg∙m2 (Figure 10). Figure 10. Effects of BMI on functional residual capacity (FRC); NS, not significant (Jones, 2006). 40 Although VTG and FRC are different measures, if FRC decreases, VTG will also decrease. Measured VTG in the obese group was approximately 75% of predicted, while in the two groups combined, VTG was measured to be 86 ± 18% of predicted. This finding is consistent with other studies examining decreases in lung volumes attributed to obesity. While significant differences between groups were not found, the OB group had

lung volumes over-predicted by the Bod Pod, as a result, had an over-estimated %BF. While this study is under-powered, these trends have the potential to be significant with a larger sample of obese adults. If in fact these trends remain true, this would indicate that those with higher BMI will have their VTG, and perhaps the resulting %BF, over-estimated when not measuring VTG. %BF Estimates There were no significant differences in measures of %BF by ADP. However, BMI and/or body composition did affect %BFDXA differently than in normal weight adults. Specifically, %BFDXA in OB adults was lower than ADP by approximately 2%. In contrast, %BFDXA in NW adults was greater than ADP by approximately 2%. A strong correlation between VTG differences (VTGpred − VTGmeas) and %BF differences (%BFVTGpred − %BFVTGmeas) indicated that errors in VTG will result in errors in %BF. Low %BFVTGpred in the NW group resulted in larger differences in %BFVTGpred and %BFVTGmeas. Upon further analysis 8

normal weight individuals displayed measured lung volumes that averaged to be 113 % of the predicted VTG. These under estimated predictions of VTG 41 could have resulted in underestimation of %BF in the NW group. For large amounts of %BFVTGpred, typical in obesity differences were also greater. Being OB had a significant effect on the values of estimated %BF across the three methods (VTGpred, VTGmeas, and DXA). A significant main effect by group indicates that OB adults, in fact, had more %BF then their NW counterparts. Ultimately, being OB was not only related with greater %BF but larger differences between methods for estimating %BF. When the differences of VTGpred and VTGmeas were compared to the differences of %BFVTGpred, and %BFVTGpred, there was a strong positive correlation (r = 0.92, p < 0001), showing that the error in predicting VTG will affect the subsequent estimate of %BF from ADP. A large cluster of NW subjects did not have large differences in VTGpred and

VTGmeas, and therefore, the %BF estimates often agreed between the two methods. The large majority of OB subjects displayed an over estimated VTG, which resulted in an overestimation of %BF. When %BFDXA was compared to VTGpred and VTGmeas (Figure 7, Figure 8), the DXA estimation of %BF was lower in the OB group, but tended to estimate higher %BF than VTGpred and VTGmeas in the NW group. DXA has been shown to result in lower %BF estimates compared to ADP estimates of %BF in obese individuals (Sampson, 1983). For example, in 57 severely obese women, DXA estimated %BF to be 2.4% lower than ADP (Bedogni, 2013). In contrast, in normal weight adults, measures of %BFDXA have been found to be larger than ADP by 3% (Levenhagen, 1999). In females the difference in estimates from DXA and ADP appeared to be more substantial than in males. The results of our study are consistent with other previous findings, however there were some discrepancies. For example, a study including 109 participants, who

divided groups by BMI, reported %BF 42 from DXA in their NW and OB group to be approximately 2.5% higher than %BFVTGpred Yet, the severely OB group values for %BFDXA was 2.7% less than %BFVTGpred (Hanes, 2014). A study with 15 normal weight subjects, and 19 overweight/obese subjects reported %BFVTGpred to be 2.43% greater than %BFDXA and 146% less than %BFDXA in the overweight/obese group. Some of the differences observed in OB adults may have been mitigated by grouping together overweight and obese adults. Error in %BF Estimates Measuring true body composition is not yet possible in living humans. When the ADP and DXA devices estimate %BF, there are assumptions that are made of the composition of the body. For example, with ADP and DXA, a constant fat free mass hydration status is assumed (Aitkens, 1995; Pietrobelli, 1996; Siri, 1961). Hydration status that may deviate from what is normal has the potential to increase the error in %BF estimates. DXA uses a three-compartment model

to estimate body composition. Theoretically, by taking more compartments of the body into consideration, resultant measures of body fat should be more accurate. An added benefit of DXA, in contrast to ADP, is that the calculation of %BF is independent from the amount of gas in the lungs at any given time of measurement. Although it is impossible to get a direct measure of %BF in a living human, results from DXA should provide a closer estimation to the true body composition than the two-compartment model used in ADP. Errors in calculated %BF by DXA arise from factors that will affect the attenuation of the different energy level X-ray beams that pass through the body. Some of these factors include tissue thickness, hydration status, and body fat distribution all of which are altered 43 with obesity (Hanes, 2014; Jensen, 2019). Past studies have shown strong agreement in NW populations and measures of %BF from DXA and ADP (Ballard, 2004; Flakoll, 2004). Observed differences in %BF

in DXA compared with ADP could be due to the quantity and location of fat distribution in the NW versus OB population. Body composition can be greatly affected by confounding factors present in children and youth (≤18 years) along with older adults (≥ 40 years). Within these age groups, there are several body composition changes that could skew resultant values of FM and FFM independent of FRC, methodology used in determining %BF in OB individuals compared to their NW counterparts. In FFM of children and youth, there are changes in water and mineral content that tend to violate the soft tissue density assumptions for this population (Boileau, 1985; Lohman, 1984; Siri, 1961). With older groups, there are changes in bone mineralization and hydration of the fat free mass due to aging and factors such as menopause and disease states. Methods based on the two-compartment model to estimate FM and FFM may also be limited by these deleterious changes (Baumgartner, 1991; Clasey, 1999;

Fields, 2004; Heymsfield, 1989; Toth, 2000). Similarly in obese populations, hydration status and total body water (TBW) deviate from what is appraised as normal, and should be considered when analyzing body composition in obese adults. Future studies examining body composition in normal weight and obese individuals should consider a more detailed classification of fatness that considers the distribution of fat throughout the body. For example, values of waist and hip circumference could prove helpful in showing supporting evidence of %BF changes concurrent with different methods of body composition measurement. Further, because hydration status of fat and muscle cells can play 44 a key role in changing the assumptions that uniform density suggest, measuring hydration status of the body will help refine estimations of body composition. Conclusion The differences observed in %BF estimates between VTGpred, VTGmeas, and DXA in this study indicate that methods of measuring body

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VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Hisp Not Hisp Not Hisp Not Hisp Not Hisp Hisp Not Hisp Not Hisp Not Hisp Not Hisp Not Hisp Hisp Not Hisp Not Hisp Not Hisp Not Hisp Not Hisp Hisp Not Hisp Not Hisp Not Hisp Not Hisp Not Hisp Not Hisp 22 21 34 23 23 21 32 41 23 24 20 21 25 33 18 18 19 27 22 22 23 21 22 25 8/17/1996 . 2/19/1985 9/17/1995 4/5/1996 4/12/1998 12/5/1986 4/6/1978 8/27/1995 6/11/1995 12/7/1998 12/26/1997 3/25/1994 11/16/1985 12/17/2000 3/19/2001 4/17/2000 2/7/1991 3/3/1997 3/20/1996 4/14/1996 4/24/2019 3/17/1997 6/12/1994 M M F M F M M F M M F F M

F F F F M F M M F M M Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean 177.0 172.0 169.5 161.1 171.2 175.0 163.5 167.5 173.4 182.9 172.5 166.5 191.5 167.6 166.5 161.8 164.0 181.1 155.0 171.0 171.5 168.5 178.5 197.5 94.9 92.7 53.5 93.1 66.3 70.0 59.0 68.8 91.9 111.1 71.8 56.6 115.0 70.0 64.7 53.5 55.0 98.3 52.2 65.0 68.1 60.9 106.1 128.7 0.536 0.539 0.316 0.578 0.387 0.400 0.361 0.411 0.530 0.607 0.416 0.340 0.600 0.418 0.389 0.331 0.335 0.543 0.337 0.380 0.397 0.361 0.594 0.652 30.3 31.3 18.6 35.9 22.6 22.9 22.1 24.5 30.6 33.2 24.1 20.4 31.4 24.9 23.3 20.4 20.4 30.0 21.7 22.2 23.2 21.4 33.3 33.0 No No No No No No No No No No No No No . No No No No No No No No No . LN STUDY ID Asthma GRP Info Smoke STATUS Pks/day HX Ethnicity Years Sm Pks/yr AGE Ex DOB Type SEX Ex 1 2 3 6 7 8 9 10 11 12 14 15 17 18 19 20 21 22 23 24 25 26 28 29 VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG VTG

VTG VTG VTG VTG VTG VTG 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 N/A OB N/A OB N/A NW N/A OB N/A NW N/A NW N/A NW N/A NW N/A OB N/A OB N/A NW . NW N/A OB . NW N/A NW N/A NW N/A NW N/A OB N/A NW N/A NW N/A NW N/A NW N/A OB N/A OB NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted No . Completed NoCompleted0 . Completed NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 NoCompleted0 Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 Hisp . Not Hisp 0 Not Hisp . Not Hisp 0 Not Hisp 0 Not Hisp 0 Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 Not Hisp 0 0 22 0 21 0 34 0 23 0 23 0 21 0 32 0 41 0 23 0 24 0 20 . 21 0 25 . 33 0 18 0 18 0 19 0 27 0 22 0 22 0 23 0 21 0 22 0 25 CODE ExFreq HT (cm) (per/wk)

No 8/17/1996 Sedentary M Mean Yes . Cycling M Mean Yes 2/19/1985 Running F Mean Yes 9/17/1995 Walking M Mean Yes 4/5/1996 Running F Mean Yes 4/12/1998 M N/A Mean Yes 12/5/1986 Jump M Rope Mean .4/6/1978 Multiple F Mean Yes 8/27/1995 Running M Mean Yes 6/11/1995 Hiking M Mean Yes 12/7/1998 Cycling F Mean 12/26/1997 . F. Mean Yes 3/25/1994 Weightlifting M Mean 11/16/1985 . F. Mean Yes 12/17/2000 Soccer F Mean Yes 3/19/2001 Soccer F Mean Yes 4/17/2000 Soccer F Mean Yes 2/7/1991 Cycling M Mean Yes 3/3/1997 Dance F Mean Yes 3/20/1996 Running M Mean Yes 4/14/1996 Running M Mean Yes 4/24/2019 Cycling F Mean No 3/17/1997 M N/A Mean Yes 6/12/1994 M N/A Mean N/A 177.0 172.0 1 169.5 2 161.1 4 171.2 3 N/A 175.0 163.5 5 167.5 7 173.4 2 182.9 2 3.5 172.5 166.5 . N/A 191.5 167.6 . 166.5 5 161.8 5 164.0 7 181.1 3 155.0 3 171.0 3 171.5 3 168.5 3 N/A 178.5 N/A 197.5 55 ExDuratio WT (kg) WT:HT n (min) 94.9 N/A 92.7 30.0 53.5 30.0 93.1 30.0 66.3 20.0 70.0 N/A 59.0 15.0 68.8 90.0 91.9 20.0 111.1 120.0

71.8 20.0 56.6 . 115.0 N/A 70.0 . 64.7 90.0 53.5 90.0 55.0 60.0 98.3 30.0 52.2 30.0 65.0 180.0 68.1 30.0 60.9 30.0 106.1 N/A 128.7 N/A 0.536 0.539 0.316 0.578 0.387 0.400 0.361 0.411 0.530 0.607 0.416 0.340 0.600 0.418 0.389 0.331 0.335 0.543 0.337 0.380 0.397 0.361 0.594 0.652 BMI 30.3 31.3 18.6 35.9 22.6 22.9 22.1 24.5 30.6 33.2 24.1 20.4 31.4 24.9 23.3 20.4 20.4 30.0 21.7 22.2 23.2 21.4 33.3 33.0 HxDOE snoresnoreHx Asth subjective objective No Yes No No No No No No Yes Yes Yes . No . No No No Yes No Yes No No No Yes snoresnoreMeds Hx Asth subjective objective No Atarax; NoSingulair No No Yes None Yes No No None No No No Xyzal No No No None No No No None No No No None No No Synthroid; No Yaz; Zyrtec No No Yes None Yes No Yes None Yes No Concerta; Yes Zyrtec Yes No . . No No None No . . . No No None No No TriNo Previfem No No No Vienva No No Yes None Yes No No None No No Yes None Yes No No None No No Birth NoControl No No Ibuprofen No No Buspirone; . Lisinopril; Yes Trazodone

Yes None None None None None None None None None None None . None . None None None None None None None None None None No Yes No No No No No No Yes Yes Yes . No . No No No Yes No Yes No No No Yes None None None None None None None None None None None . None . None None None None None None None None None None Processing JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO Screen Captures of Raw Data from VTGpred: ΔVTG ID GRP Code TRIAL PB Temp RH Mass (kg) VTGp VTG (predmeas) VTGpp 014 014 014 014 015 015 015 015 016 016 016 016 019 019 019 019 020 020 020 020 021 021 021 021 022 022 022 022 023 023 023 023 024 024 024 024 025 025 025 025 027 027 027 027 028 028 028 028 030 030 030 030 OB OB OB OB OB OB OB OB NW NW NW NW OB OB OB OB NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB NW NW NW NW NW NW NW NW OB OB OB OB PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED

PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean . . . . 682.49 682.49 682.49 682.49 678.00 678.00 678.00 678.00 681.00 681.00 681.00 681.00 681.70 681.70 681.70 681.70 681.00 681.00 681.00 681.00 680.20 680.20 680.20 680.20 678.18 678.18 678.18 678.18 682.40 682.40 682.40 682.40 682.50 682.50 682.50 682.50 684.00 684.00 684.00 684.00 . . . #DIV/0! 682.50 682.50 682.50 682.50 . . . . 22.0 22.0 22.0 22.0 21.0 21.0 21.0 21.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 21.0 21.0 21.0 21.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 . . . #DIV/0! 21.0 21.0 21.0 21.0 . . . . 52.0 52.0 52.0 52.0 40.0 40.0 40.0 40.0 51.0 51.0 51.0 51.0 47.0 47.0 47.0 47.0 51.0 51.0 51.0 51.0 53.0 53.0 53.0 53.0

45.0 45.0 45.0 45.0 54.0 54.0 54.0 54.0 54.0 54.0 54.0 54.0 51.0 51.0 51.0 51.0 . . . #DIV/0! 34.0 34.0 34.0 34.0 94.9 94.9 . 94.86 92.7 92.7 . 92.71 53.5 53.5 53.5 53.47 93.3 93.1 93.1 93.17 66.3 66.3 66.3 66.35 70.0 70.0 70.0 70.03 59.1 59.1 59.1 59.12 68.8 68.8 68.8 68.82 202.7 202.7 202.7 202.70 111.1 111.1 111.1 111.07 71.8 71.8 71.8 71.82 56.6 56.7 56.7 56.67 114.9 115.0 115.0 114.97 3.869 3.869 3.869 3.869 3.624 3.624 3.624 3.624 3.376 3.376 3.376 3.376 3.127 3.127 3.127 3.127 3.403 3.403 3.403 3.403 3.760 3.760 3.760 3.760 3.320 3.320 3.320 3.320 3.326 3.326 3.326 3.326 3.709 3.709 3.709 3.709 4.159 4.159 4.159 4.159 3.442 3.442 3.442 3.442 3.229 3.229 3.229 3.229 4.577 4.577 4.577 4.577 3.869 3.869 3.869 3.869 3.624 3.624 3.624 3.624 3.376 3.376 3.376 3.376 3.127 3.127 3.127 3.127 3.403 3.403 3.403 3.403 3.760 3.760 3.760 3.760 3.320 3.320 3.320 3.320 3.326 3.326 3.326 3.326 3.709 3.709 3.709 3.709 4.159 4.159 4.159 4.159 3.442 3.442 3.442 3.442 3.229 3.229 3.229 3.229

4.577 4.577 4.577 4.577 0.000 0.000 0.000 0.000 0.000 0.000 . 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 100.0 100.0 100.0 100.0 100.0 100.0 . 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 56 ID GRP Code %BF Δ%BF (predTRIAL P%FFM B Temp FM (kg) .7220 .7170 . .7195 682.49 61.50 682.49 60.60 682.49 682.49 61.05 678.00 76.40 678.00 77.40 678.00 77.60 678.00 77.13 681.00 61.20 681.00 60.50 681.00 60.50 681.00 60.73 681.70 72.70 681.70 72.90 681.70 73.40 681.70 73.00 681.00 84.77 681.00 85.98 681.00 85.38 681.00 85.38 680.20 81.80

680.20 82.50 680.20 82.20 680.20 82.17 678.18 68.40 678.18 68.20 678.18 69.00 678.18 68.53 682.40 31.75 682.40 31.91 682.40 32.18 682.40 31.95 682.50 68.40 682.50 67.90 682.50 68.10 682.50 68.13 684.00 74.30 684.00 75.10 684.00 74.40 684.00 74.60 .7720 .7730 .7720 #DIV/0! 77.23 682.50 71.90 682.50 71.70 682.50 69.20 682.50 70.93 .264 .268 . 26.61 . 22.0 35.7 22.0 36.5 22.0 22.0 36.11 21.0 12.6 21.0 12.1 21.0 12.0 21.0 12.23 22.0 36.2 22.0 36.8 22.0 36.8 22.0 36.59 22.0 18.1 22.0 18.0 22.0 17.6 22.0 17.91 22.0 10.6 22.0 9.8 22.0 10.2 22.0 10.22 22.0 10.8 22.0 10.3 22.0 10.5 22.0 10.54 22.0 21.7 22.0 21.9 22.0 21.3 22.0 21.66 21.0 27.6 21.0 27.3 21.0 26.7 21.0 27.19 22.0 35.1 22.0 35.7 22.0 35.4 22.0 35.39 22.0 18.5 22.0 17.9 22.0 18.4 22.0 18.24 .129 .129 .129 #DIV/0! 12.90 21.0 32.3 21.0 32.5 21.0 35.4 21.0 33.42 meas) 014 014 014 014 015 015 015 015 016 016 016 016 019 019 019 019 020 020 020 020 021 021 021 021 022 022 022 022 023 023 023 023 024 024 024 024 025 025 025 025 027

027 027 027 028 028 028 028 030 030 030 030 OB OB OB OB OB OB OB OB NW NW NW NW OB OB OB OB NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB NW NW NW NW NW NW NW NW OB OB OB OB PRED 27.80 1 -0.70 PRED 28.30 2 -1.20 PRED. 3 . PRED 28.05 Mean -0.95 PRED 38.50 1 2.00 PRED 39.40 2 2.70 PRED. 3 . PRED 38.95 Mean 2.35 PRED 23.60 1 -0.90 PRED 22.60 2 -1.20 PRED 22.40 3 -1.50 22.86666667 PRED Mean -1.20 PRED 38.80 1 0.50 PRED 39.50 2 2.20 PRED 39.50 3 2.10 39.26666667 PRED Mean 1.60 PRED 27.30 1 0.80 PRED 27.10 2 0.40 PRED 26.60 3 0.30 PRED 27 Mean 0.50 PRED 15.20 1 -1.30 PRED 14.00 2 -5.00 PRED 14.60 3 -6.70 PRED 14.6 Mean -4.33 PRED 18.20 1 -2.10 PRED 17.50 2 -3.60 PRED 17.80 3 -2.00 17.83333333 PRED Mean -2.57 PRED 31.60 1 -1.30 PRED 31.80 2 -0.20 PRED 31.00 3 -0.60 31.46666667 PRED Mean -0.70 PRED 30.00 1 1.00 PRED 29.60 2 0.90 PRED 29.10 3 0.40 29.56666667 PRED Mean 0.77 PRED 31.60 1 0.60 PRED 32.10 2 1.80 PRED 31.90 3 1.10 31.86666667 PRED Mean 1.17 PRED 25.70 1

0.20 PRED 24.90 2 -0.70 PRED 25.60 3 0.40 PRED 25.4 Mean -0.03 PRED 22.80 1 1.20 PRED 22.70 2 0.30 PRED 22.80 3 1.20 22.76666667 PRED Mean 0.90 PRED 28.10 1 -0.30 PRED 28.30 2 -1.40 PRED 30.80 3 2.40 29.06666667 PRED Mean 0.23 1st 2nd ΔVTG 3rd Density Mass Body (kg) VolumeVTGp volume VTG volume (predvolume VTGpp Model mst. mst. meas) mst. 68.4933 . 91.567 3.869 89.109 3869 89.155 0000 100.0 Siri 94.9 68.0096 . 94.9 91.647 3.869 89.064 3869 88.950 0000 100.0 Siri . . 3.869 3.869 0.000 100.0 Siri 68.251 . 94.86 91.607 3.869 89.087 3869 89.052 0000 100.0 Siri 57.0165 52.0 91.494 3.624 89.101 3624 89.066 0000 100.0 Siri 92.7 56.1778 52.0 92.7 91.652 3.624 89.226 3624 89.257 0000 100.0 Siri 52.0 . . 3.624 3.624 . . Siri 56.59716337 52.0 92.71 91.573 3.624 89.164 3624 89.162 0000 #DIV/0! 100.0 Siri 40.8551 40.0 51.165 3.376 49.013 3376 49.118 0000 100.0 Siri 53.5 41.3861 40.0 53.5 51.054 3.376 48.718 3376 48.943 0000 48.961 1000 Siri 41.4914 40.0 53.5 51.029 3.376 48.915 3376

48.938 0000 100.0 Siri 41.24422131 40.0 51.08266667 53.47 3.376 48.88212 3376 48.9997 0000 48.96071 1000 Siri 57.1235 51.0 92.177 3.127 89.950 3127 90.065 0000 100.0 Siri 93.3 56.3211 51.0 93.1 92.064 3.127 89.826 3127 89.965 0000 100.0 Siri 56.3211 51.0 93.1 92.065 3.127 89.862 3127 89.931 0000 100.0 Siri 56.58856602 51.0 93.17 92.102 3.127 89.87954 3127 89.9872 0000 #DIV/0! 100.0 Siri 48.2358 47.0 66.3 63.981 3.403 61.788 3403 61.791 0000 100.0 Siri 48.3665 47.0 66.3 63.947 3.403 61.528 3403 61.715 0000 61.795 1000 Siri 48.6952 47.0 66.3 63.879 3.403 61.605 3403 61.770 0000 100.0 Siri 48.43247606 47.0 63.93566667 66.35 3.403 61.64008 3403 61.7589 0000 61.79542 1000 Siri 59.3410 51.0 70.0 65.788 3.760 63.417 3760 63.425 0000 100.0 Siri 60.2250 51.0 70.0 65.666 3.760 63.230 3760 63.367 0000 100.0 Siri 59.8000 51.0 70.0 65.742 3.760 63.319 3760 63.430 0000 100.0 Siri 59.78866667 51.0 70.03 65.732 3.760 63.32205 3760 63.40718 0000 #DIV/0! 100.0 Siri 48.3560 53.0 59.1 55.919

3.320 53.817 3320 53.835 0000 100.0 Siri 48.7726 53.0 59.1 55.833 3.320 53.711 3320 53.769 0000 100.0 Siri 48.5939 53.0 59.1 55.866 3.320 53.801 3320 53.746 0000 100.0 Siri 48.57416004 53.0 55.87266667 59.12 3.320 53.77644 3320 53.78349 0000 #DIV/0! 100.0 Siri 47.0746 45.0 68.8 66.962 3.326 64.723 3326 65.062 0000 64.880 1000 Siri 46.9355 45.0 68.8 66.986 3.326 64.834 3326 64.816 0000 100.0 Siri 47.4861 45.0 68.8 66.877 3.326 64.660 3326 64.774 0000 100.0 Siri 47.16539824 45.0 66.94166667 68.82 3.326 64.73892 3326 64.88397 0000 64.8802 1000 Siri 64.3640 54.0 202.7 89.168 3.709 86.767 3709 86.677 0000 100.0 Siri 64.6900 54.0 202.7 89.097 3.709 86.629 3709 86.673 0000 100.0 Siri 65.2090 54.0 202.7 89.168 3.709 86.538 3709 86.526 0000 100.0 Siri 64.75433333 54.0 89.14433333 202.70 3.709 86.64479 3709 86.62514 0000 #DIV/0! 100.0 Siri 75.9685 54.0 111.1 108.058 4159 105.212 4159 105.408 0000 100.0 Siri 75.4158 54.0 111.1 108.168 4159 105.407 4159 105.433 0000 100.0 Siri 75.6382

54.0 111.1 108.132 4159 105.465 4159 105.304 0000 100.0 Siri 75.67415194 54.0 108.1193333 111.07 4.159 105.3613 4159 105.3815 0000 #DIV/0! 100.0 Siri 53.3720 51.0 71.8 69.039 3.442 66.759 3442 66.838 0000 100.0 Siri 53.9405 51.0 71.8 68.908 3.442 66.569 3442 66.766 0000 100.0 Siri 53.4269 51.0 71.8 68.997 3.442 66.685 3442 66.829 0000 100.0 Siri 53.57979332 51.0 68.98133333 71.82 3.442 66.67115 3442 66.81077 0000 #DIV/0! 100.0 Siri 43.7292 . 56.6 54.102 3.229 52.009 3229 52.089 0000 100.0 Siri 43.8221 . 56.7 54.131 3.229 52.138 3229 52.019 0000 100.0 Siri 43.7602 . 56.7 54.142 3.229 52.155 3229 52.024 0000 100.0 Siri 43.77049002 #DIV/0! 56.67 54.125 3.229 52.10083 3229 52.04397 0000 #DIV/0! 100.0 Siri 82.6451 34.0 114.9 111.016 4577 108.186 4577 107.916 0000 100.0 Siri 82.4518 34.0 115.0 111.122 4577 108.165 4577 108.150 0000 100.0 Siri 79.5654 34.0 115.0 111.676 4577 108.859 4577 108.556 0000 100.0 Siri 81.55408979 34.0 111.2713333 114.97 4.577 108.4034 4577 108.2073 0000

#DIV/0! 100.0 Siri FFM RH(kg) 57 Body Density BSA Processi ng 1.036 1.035 . 1.0355 1.013 1.012 . 1.012 1.045 1.047 1.048 1.046733333 1.013 1.011 1.011 1.011666667 1.037 1.038 1.039 1.0377 1.064 1.067 1.064 1.064933333 1.057 1.059 1.058 1.0581 1.028 1.027 1.029 1.0281 1.031 1.032 1.033 1.032133333 1.028 1.027 1.027 1.027266667 1.041 1.042 1.041 1.0412 1.047 1.047 1.047 1.047066667 1.035 1.035 1.030 1.0333 21204.064 21202.851 . 21203.45757 20566.140 20564.470 . 20565.305 16105.696 16105.071 16104.803 16105.19006 19669.237 19647.162 19647.159 19654.51928 17780.187 17779.878 17779.406 17779.82375 18481.255 18486.949 18485.937 18484.7138 16373.366 16373.767 16373.565 16373.56602 17775.116 17774.894 17774.887 17774.96553 20615.535 20615.096 20613.854 20614.82848 23218.897 23219.243 23219.282 23219.14038 18491.676 18490.779 18489.198 18490.55099 16292.293 16298.026 16297.192 16295.83736 24358.252 24362.854 24361.350 24360.81845 JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO

JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO . . . . ID GRP Code TRIAL PB Temp RH Mass (kg) VTGp VTG ΔVTG (predmeas) VTGpp 031 031 031 031 032 032 032 032 033 033 033 033 034 034 034 034 035 035 035 035 036 036 036 036 037 037 037 037 038 038 038 038 039 039 039 039 041 041 041 041 042 042 042 042 NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED PRED 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean . . . #DIV/0! 683.00 683.00 683.00 683.00 683.00 683.00 683.00 683.00 684.00 684.00 684.00 684.00 680.20 680.20 680.20 680.20 680.30 680.30 680.30 680.30 . . .

#DIV/0! . . . #DIV/0! 688.00 688.00 688.00 688.00 697.45 697.45 697.45 697.45 679.45 679.45 679.45 679.45 . . . #DIV/0! 23.0 23.0 23.0 23.0 23.0 23.0 23.0 23.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 22.0 . . . #DIV/0! . . . #DIV/0! 22.00 22.00 22.00 22.0 22.0 22.0 22.0 22.0 21.0 21.0 21.0 21.0 . . . #DIV/0! 52.0 52.0 52.0 52.0 52.0 52.0 52.0 52.0 53.0 53.0 53.0 53.0 52.0 52.0 52.0 52.0 53.0 53.0 53.0 53.0 . . . #DIV/0! . . . #DIV/0! 53.0 53.0 53.0 53.0 46.0 46.0 46.0 46.0 51.0 51.0 51.0 51.0 69.9 69.9 69.9 69.93 64.7 64.7 64.7 64.73 53.5 53.5 53.5 53.49 55.0 55.0 55.0 54.96 98.4 98.4 98.3 98.35 52.2 52.1 52.1 52.15 65.0 65.0 65.0 64.99 68.1 68.1 68.0 68.06 60.9 60.9 60.9 60.90 106.2 106.1 106.1 106.14 128.7 128.7 128.7 128.69 3.310 3.310 3.310 3.310 3.220 3.220 3.220 3.220 3.050 3.050 3.050 3.050 3.132 3.132 3.132 3.132 4.115 4.115 4.115 4.115 2.818 2.818 2.818 2.818 3.592 3.592 3.592 3.592 3.615 3.615 3.615 3.615 3.300 3.300 3.300 3.300 3.938 3.938 3.938 3.938

4.860 4.860 4.860 4.860 3.310 3.310 3.310 3.310 3.220 3.220 3.220 3.220 3.050 3.050 3.050 3.050 3.132 3.132 3.132 3.132 4.115 4.115 4.115 4.115 2.818 2.818 2.818 2.818 3.592 3.592 3.592 3.592 3.615 3.615 3.615 3.615 3.300 3.300 3.300 3.300 3.938 3.938 3.938 3.938 4.860 4.860 4.860 4.860 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 58 ID GRP Code %BF Δ%BF (predTRIAL P%FFM B Temp FM (kg) .6710 .6730 .6740 #DIV/0! 67.27 683.00 79.80 683.00 79.20 683.00 79.70 683.00 79.57 683.00 72.63 683.00 73.36

683.00 72.44 683.00 72.81 684.00 79.60 684.00 81.10 684.00 80.20 684.00 80.30 680.20 69.70 680.20 69.20 680.20 69.80 680.20 69.57 680.30 74.90 680.30 75.70 680.30 76.10 680.30 75.57 .8310 .8470 .8400 #DIV/0! 83.93 .6790 .6770 .6830 #DIV/0! 67.97 688.00 64.30 688.00 63.30 688.00 64.10 688.00 63.90 697.45 63.90 697.45 62.60 697.45 62.90 697.45 63.13 679.45 67.70 679.45 67.90 679.45 68.00 679.45 67.87 23.0 . 22.9 . 22.8 . #DIV/0! 22.89 23.0 13.1 23.0 13.5 23.0 13.1 23.0 13.23 23.0 14.6 23.0 14.3 23.0 14.6 23.0 14.51 22.0 11.2 22.0 10.4 22.0 10.9 22.0 10.83 22.0 29.8 22.0 30.3 22.0 29.7 22.0 29.93 22.0 13.1 22.0 12.7 22.0 12.5 22.0 12.74 11.0 . .99 10.4 . #DIV/0! 10.44 21.8 . 22.0 . 21.6 . #DIV/0! 21.80 22.00 21.7 22.00 22.4 22.00 21.9 22.0 21.98 22.0 38.3 22.0 39.7 22.0 39.4 22.0 39.13 21.0 41.6 21.0 41.3 21.0 41.2 21.0 41.35 meas) 031 031 031 031 032 032 032 032 033 033 033 033 034 034 034 034 035 035 035 035 036 036 036 036 037 037 037 037 038 038 038 038 039 039 039 039 041 041 041

041 042 042 042 042 NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB PRED 32.90 1 1.00 PRED 32.70 2 -1.20 PRED 32.60 3 0.10 32.73333333 PRED Mean -0.03 PRED 20.20 1 0.60 PRED 20.80 2 0.20 PRED 20.30 3 -0.40 20.43333333 PRED Mean 0.13 PRED 27.40 1 0.20 PRED 26.60 2 1.20 PRED 27.60 3 1.00 PRED 27.2 Mean 0.80 PRED 20.40 1 0.60 PRED 18.90 2 -1.20 PRED 19.80 3 0.00 PRED 19.7 Mean -0.20 PRED 30.30 1 1.00 PRED 30.80 2 2.80 PRED 30.20 3 2.20 30.43333333 PRED Mean 2.00 PRED 25.10 1 0.70 PRED 24.30 2 1.80 PRED 23.90 3 0.50 24.43333333 PRED Mean 1.00 PRED 16.90 1 0.70 PRED 15.30 2 1.00 PRED 16.00 3 1.20 16.06666667 PRED Mean 0.97 PRED 32.10 1 3.20 PRED 32.30 2 4.20 PRED 31.70 3 3.20 32.03333333 PRED Mean 3.53 PRED 35.70 1 3.00 PRED 36.70 2 4.30 PRED 35.90 3 4.20 PRED 36.1 Mean 3.83 PRED 36.10 1 -1.80 PRED 37.40 2 0.40 PRED 37.10 3 0.70 36.86666667 PRED Mean -0.23 PRED 32.30 1 -0.70 PRED 32.10 2 -0.50 PRED 32.00 3

0.80 32.13333333 PRED Mean -0.13 1st 2nd ΔVTG 3rd Density Mass Body (kg) VolumeVTGp volume VTG volume (predvolume VTGpp Model mst. mst. meas) mst. 46.9223 . 69.9 68.221 3.310 66.100 3310 66.021 0000 100.0 Siri 47.0645 . 69.9 68.196 3.310 66.043 3310 66.028 0000 100.0 Siri 47.1353 . 69.9 68.187 3.310 66.019 3310 66.034 0000 100.0 Siri 47.0407023 #DIV/0! 68.20133333 69.93 3.310 66.05398 3310 66.02775 0000 #DIV/0! 100.0 Siri 51.6566 52.0 64.7 61.494 3.220 59.363 3220 59.437 0000 100.0 Siri 51.2664 52.0 64.7 61.565 3.220 59.435 3220 59.508 0000 100.0 Siri 51.5879 52.0 64.7 61.501 3.220 59.437 3220 59.380 0000 100.0 Siri 51.50361873 52.0 64.73 61.52 3.220 59.41162 3220 59.44196 0000 #DIV/0! 100.0 Siri 38.8490 52.0 53.5 1.037 3.050 49.594 3050 49.680 0000 100.0 Siri 39.2440 52.0 53.5 1.039 3.050 49.520 3050 49.607 0000 100.0 Siri 38.7470 52.0 53.5 1.037 3.050 49.663 3050 49.451 0000 49.662 1000 Siri 38.94666667 52.0 53.49 1.0373 3.050 49.59229 3050 49.57935 0000 49.66228 1000 Siri 43.7554

53.0 55.0 52.233 3.132 50.264 3132 50.211 0000 100.0 Siri 44.5707 53.0 55.0 52.057 3.132 50.044 3132 50.078 0000 100.0 Siri 44.0753 53.0 55.0 52.155 3.132 50.120 3132 50.199 0000 100.0 Siri 44.13379711 53.0 52.14833333 54.96 3.132 50.14274 3132 50.16244 0000 #DIV/0! 100.0 Siri 68.5572 52.0 98.4 95.441 4.115 92.782 4115 92.763 0000 100.0 Siri 68.0654 52.0 98.4 95.541 4.115 92.851 4115 92.895 0000 100.0 Siri 68.6406 52.0 98.3 95.407 4.115 92.862 4115 92.616 0000 100.0 Siri 68.42107583 52.0 98.35 95.463 4.115 92.83177 4115 92.75803 0000 #DIV/0! 100.0 Siri 39.0618 53.0 52.2 50.060 2.818 48.195 2818 48.276 0000 100.0 Siri 39.4743 53.0 52.1 49.970 2.818 48.124 2818 48.166 0000 100.0 Siri 39.6818 53.0 52.1 49.920 2.818 48.098 2818 48.511 0000 48.093 1000 Siri 39.40594732 53.0 49.98333333 52.15 2.818 48.13904 2818 48.31775 0000 48.09334 1000 Siri 53.9771 . 65.0 61.271 3.592 59.033 3592 58.991 0000 100.0 Siri 55.0621 . 65.0 61.108 3.592 58.937 3592 59.128 0000 58.761 1000 Siri 54.5997 . 65.0

61.186 3.592 58.751 3592 58.943 0000 58.910 1000 Siri 54.54628063 #DIV/0! 61.18833333 64.99 3.592 58.90701 3592 59.02101 0000 58.83583 1000 Siri 46.2071 . 68.1 66.283 3.615 64.003 3615 63.990 0000 100.0 Siri 46.0893 . 68.1 66.339 3.615 63.980 3615 64.124 0000 100.0 Siri 46.4751 . 68.0 66.219 3.615 63.673 3615 64.009 0000 63.856 1000 Siri 46.257156 #DIV/0! 66.28033333 68.06 3.615 63.8851 3615 64.04109 0000 63.85556 1000 Siri 39.1455 53.0 60.9 59.737 3.300 57.609 3300 57.807 0000 57.643 1000 Siri 38.5542 53.0 60.9 59.888 3.300 57.767 3300 57.785 0000 100.0 Siri 39.0377 53.0 60.9 59.778 3.300 57.639 3300 57.694 0000 100.0 Siri 38.91248605 53.0 60.90 59.801 3.300 57.67162 3300 57.76205 0000 57.64333 1000 Siri 67.8323 46.0 106.2 104.242 3938 101.512 3938 101.732 0000 100.0 Siri 66.4426 46.0 106.1 104.518 3938 101.982 3938 101.814 0000 100.0 Siri 66.7558 46.0 106.1 104.428 3938 101.790 3938 101.826 0000 100.0 Siri 67.01023101 46.0 106.14 104.396 3938 101.7614 3938 101.7906 0000 #DIV/0! 100.0

Siri 87.1264 51.0 128.7 125.404 4860 122.074 4860 122.405 0000 100.0 Siri 87.3809 51.0 128.7 125.340 4860 122.246 4860 122.105 0000 100.0 Siri 87.5021 51.0 128.7 125.297 4860 122.049 4860 122.217 0000 100.0 Siri 87.33644838 51.0 128.69 125.347 4860 122.123 4860 122.2425 0000 #DIV/0! 100.0 Siri FFM RH(kg) 59 Body Density BSA Processi ng 1.025 1.026 1.026 1.025366667 1.053 1.051 1.053 1.052266667 1.037 1.039 1.037 1.0373 1.052 1.056 1.054 1.053933333 1.031 1.030 1.031 1.030266667 1.042 1.044 1.045 1.0433 1.060 1.064 1.062 1.062066667 1.027 1.026 1.028 1.026833333 1.019 1.017 1.019 1.0183 1.018 1.016 1.016 1.0167 1.026 1.027 1.027 1.026633333 17911.499 17911.884 17912.012 17911.79819 17243.235 17242.987 17242.672 17242.96477 15573.620 15574.268 15574.144 15574.01072 15910.310 15908.902 15908.781 15909.33096 21893.034 21893.022 21891.003 21892.35306 14934.701 14933.945 14933.779 14934.14182 17605.447 17611.668 17610.655 17609.25696 17995.514 17998.564 17994.818 17996.29865 16945.381

16948.655 16947.967 16947.33433 22378.278 22376.890 22376.150 22377.10626 26134.599 26134.240 26133.284 26134.04079 JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO Screen Captures of Raw Data from VTGmeas: ΔVTG ID GRP Code Order TRIAL Mass (kg) VTGp VTG (predmeas) VTGpp 014 014 014 014 015 015 015 015 016 016 016 016 019 019 019 019 020 020 020 020 021 021 021 021 022 022 022 022 023 023 023 023 024 024 024 024 025 025 025 025 027 027 027 027 028 028 028 028 030 030 030 030 OB OB OB OB OB OB OB OB NW NW NW NW OB OB OB OB NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB NW NW NW NW NW NW NW NW OB OB OB OB MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS 2 2 2 2 1 1 1 1 2 2 2 2 2 2 2 2 . . . . . . . . 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1

2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 94.9 94.8 . 94.85 92.7 92.7 . 92.69 53.5 53.5 53.4 53.46 93.1 93.1 93.1 93.07 66.3 66.3 66.3 66.33 69.9 70.0 70.0 69.96 59.1 59.1 59.1 59.13 68.8 68.8 68.8 68.80 91.9 91.9 91.9 91.90 111.1 111.1 111.0 111.05 72.0 72.0 72.0 71.96 56.7 56.7 56.7 56.68 114.9 115.0 115.0 114.97 3.869 3.869 3.869 3.869 3.624 3.624 3.624 3.624 3.376 3.376 3.376 3.376 3.127 3.127 3.127 3.127 3.403 3.403 3.403 3.403 3.760 3.760 3.760 3.760 3.320 3.320 3.320 3.320 3.326 3.326 3.326 3.326 3.709 3.709 3.709 3.709 4.159 4.159 4.159 4.159 3.442 3.442 3.442 3.442 3.229 3.229 3.229 3.229 4.577 4.577 4.577 4.577 4.099 4.295 . 4.197 2.167 2.386 . 2.277 3.933 4.015 3.937 3.962 2.373 2.130 2.279 2.261 3.086 3.314 3.205 3.202 4.995 5.003 5.700 5.233 4.223 4.284 4.128 4.212 3.762 3.373 3.395 3.510 3.554 3.554 3.687 3.598 3.963 3.772 3.991 3.909 3.405 3.177 3.418 3.333 2.959 3.089

2.960 3.003 3.998 4.932 4.694 4.541 -0.230 -0.426 . -0.328 1.457 1.238 . 1.348 -0.557 -0.639 -0.561 -0.586 0.754 0.997 0.848 0.866 0.317 0.089 0.198 0.201 -1.235 -1.243 -1.940 -1.473 -0.903 -0.964 -0.808 -0.892 -0.436 -0.047 -0.069 -0.184 0.155 0.155 0.022 0.111 0.196 0.387 0.168 0.250 0.037 0.265 0.024 0.109 0.270 0.140 0.269 0.226 0.579 -0.355 -0.117 0.036 105.9 111.0 . 108.5 59.8 65.8 . 62.8 116.5 118.9 116.6 117.3 75.9 68.1 72.9 72.3 90.7 97.4 94.2 94.1 132.8 133.1 151.6 139.2 127.2 129.0 124.3 126.9 113.1 101.4 102.1 105.5 95.8 95.8 99.4 97.0 95.3 90.7 96.0 94.0 98.9 92.3 99.3 96.8 91.6 95.7 91.7 93.0 87.3 107.8 102.6 99.2 60 ID GRP Code %BF Δ%BF Order(pred- TRIAL %FFM Mass FM(kg) (kg) ΔVTG (predVTGp FFM (kg) VTG Body Volume meas) 014 014 014 014 015 015 015 015 016 016 016 016 019 019 019 019 020 020 020 020 021 021 021 021 022 022 022 022 023 023 023 023 024 024 024 024 025 025 025 025 027 027 027 027 028 028 028 028 030 030 030 030 OB OB OB OB OB OB OB OB NW NW

NW NW OB OB OB OB NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB NW NW NW NW NW NW NW NW OB OB OB OB MS 28.50 MS 29.50 MS . MS29 MS 36.50 MS 36.70 MS . MS 36.6 MS 24.50 MS 23.80 MS 23.90 24.06666667 MS MS 38.30 MS 37.30 MS 37.40 37.66666667 MS MS 26.50 MS 26.70 MS 26.30 MS 26.5 MS 16.50 MS 19.00 MS 21.30 18.93333333 MS MS 20.30 MS 21.10 MS 19.80 MS 20.4 MS 32.90 MS 32.00 MS 31.60 32.16666667 MS MS 29.00 MS 28.70 MS 28.70 MS 28.8 MS 31.00 MS 30.30 MS 30.80 MS 30.7 MS 25.50 MS 25.60 MS 25.20 25.43333333 MS MS 21.60 MS 22.40 MS 21.60 21.86666667 MS MS 28.40 MS 29.70 MS 28.40 28.83333333 MS 2 2 2 2 1 1 1 1 2 2 2 2 2 2 2 2 . . . . . . . . 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 -0.70 -1.20 . -0.95 2.00 2.70 . 2.35 -0.90 -1.20 -1.50 -1.20 0.50 2.20 2.10 1.60 0.80 0.40 0.30 0.50 -1.30 -5.00 -6.70 -4.33 -2.10 -3.60 -2.00 -2.57 -1.30 -0.20 -0.60 -0.70 1.00 0.90 0.40 0.77 0.60 1.80 1.10 1.17 0.20 -0.70 0.40 -0.03 1.20 0.30 1.20 0.90 -0.30 -1.40 2.40

0.23 meas) 1 71.50 2 70.50 3 . Mean 71.00 1 63.50 2 63.30 3 . Mean 63.40 1 75.50 2 76.20 3 76.10 Mean 75.93 1 61.70 2 62.70 3 62.60 Mean 62.33 1 73.50 2 73.30 3 73.70 Mean 73.50 1 83.48 2 81.00 3 78.70 Mean 81.06 1 79.70 2 78.90 3 80.20 Mean 79.60 1 67.10 2 68.00 3 68.40 Mean 67.83 1 71.05 2 71.33 3 71.30 Mean 71.23 1 69.00 2 69.70 3 69.20 Mean 69.30 1 74.50 2 74.40 3 74.80 Mean 74.57 1 78.40 2 77.60 3 78.40 Mean 78.13 1 71.60 2 70.30 3 71.60 Mean 71.17 27.0 94.9 94.8 28.0 . 94.85 27.51 33.8 92.7 92.7 34.0 . 92.69 33.93 13.1 53.5 53.5 12.7 53.4 12.8 53.46 12.87 35.6 93.1 93.1 34.7 93.1 34.8 93.07 35.05 66.3 17.6 66.3 17.7 66.3 17.4 66.33 17.58 69.9 11.5 70.0 13.3 70.0 14.9 69.96 13.25 59.1 12.0 59.1 12.5 59.1 11.7 59.13 12.06 68.8 22.6 68.8 22.0 68.8 21.7 68.80 22.13 91.9 26.7 91.9 26.4 91.9 26.4 91.90 26.47 111.1 34.4 111.1 33.6 111.0 34.2 111.05 34.09 72.0 18.4 72.0 18.4 72.0 18.1 71.96 18.30 56.7 12.2 56.7 12.7 56.7 12.2 56.68 12.39 114.9 32.6 115.0 34.2 115.0 32.6 114.97 33.15

3.869 67.8331 4099 91716 -0.230 3.869 66.8574 4295 91869 -0.426 3.869 . . 67.34521204 3.869 4.197 917925 -0.328 3.624 58.8622 2167 91101 1.457 3.624 58.6715 2386 91138 1.238 3.624 . . 58.76685027 3.624 2.277 911195 1.348 3.376 40.3675 3933 51249 -0.557 3.376 40.7360 4015 51172 -0.639 3.376 40.6747 3937 51175 -0.561 40.59277016 3.376 3.962 51.19866667 -0.586 3.127 57.4264 2373 91819 0.754 3.127 58.3532 2130 91613 0.997 3.127 58.2532 2279 91620 0.848 58.01091753 3.127 2.261 91684 0.866 3.403 48.7552 3086 63860 0.317 3.403 48.6206 3314 63878 0.089 3.403 48.8830 3205 63827 0.198 48.75294419 3.403 3.202 63855 0.201 3.760 58.3870 4995 65916 -1.235 3.760 56.6760 5003 66295 -1.243 3.760 55.0595 5700 66614 -1.940 56.70748188 3.760 5.233 66275 -1.473 3.320 47.1320 4223 56191 -0.903 3.320 46.6524 4284 56273 -0.964 3.320 47.4158 4128 56114 -0.808 47.06675138 3.320 4.212 56.19266667 -0.892 3.326 46.1686 3762 67130 -0.436 3.326 46.7868 3373 66999 -0.047 3.326 47.0573 3395 66939 -0.069

46.67090287 3.326 3.510 67.02266667 -0.184 3.709 65.3120 3554 88947 0.155 3.709 65.5460 3554 88860 0.155 3.709 65.5145 3687 88868 0.022 65.45749372 3.709 3.598 88.89166667 0.111 4.159 76.6263 3963 107913 0.196 4.159 77.4043 3772 107752 0.387 4.159 76.8400 3991 107846 0.168 76.95688713 4.159 3.909 107837 0.250 3.442 53.6185 3405 69133 0.037 3.442 53.5393 3177 69136 0.265 3.442 53.8244 3418 69076 0.024 53.66072741 3.442 3.333 69115 0.109 3.229 44.4410 2959 54008 0.270 3.229 43.9816 3089 54088 0.140 3.229 44.4386 2960 53999 0.269 44.28707758 3.229 3.003 54.03166667 0.226 4.577 82.2747 3998 111051 0.579 4.577 80.8622 4932 111460 -0.355 4.577 82.3135 4694 111103 -0.117 81.81676653 4.577 4.541 111.2046667 0.036 61 1st 2nd volume VTGpp volume mst. mst. 89.121 105.9 89052 89.135 111.0 89186 . . 89.12795 108.5 891189 88.868 59.8 89.261 88.886 65.8 89.178 . . 88.87697 62.8 8921948 48.912 116.5 48936 48.777 118.9 48851 48.868 116.6 48828 48.85212 117.3 4887194 89.709 75.9 90.020 89.857 68.1

89.831 89.790 72.9 89.792 89.78528 72.3 8988111 61.507 90.7 61.779 61.730 97.4 61.715 61.717 94.2 61.713 61.65128 94.1 6173556 62.978 132.8 63133 63.415 133.1 63646 63.457 151.6 63485 63.2831 139.2 6342117 53.791 127.2 53684 53.830 129.0 53759 53.664 124.3 53732 53.762 126.9 5372499 64.718 113.1 64873 64.790 101.4 64850 64.717 102.1 64785 64.74178 105.5 6483581 86.611 95.8 86.516 86.481 95.8 86.471 86.414 99.4 86.448 86.50178 97.0 8647821 105.222 95.3 105264 105.033 90.7 105284 105.183 96.0 105146 105.1462 94.0 1052317 66.986 98.9 66.828 66.998 92.3 67.003 66.920 99.3 66.768 66.96815 96.8 6686609 52.065 91.6 52.061 52.105 95.7 52.078 52.091 91.7 52.017 52.08695 93.0 5205217 108.399 87.3 108230 108.483 107.8 108216 107.980 102.6 108195 108.2874 99.2 1082136 3rd volume mst. . . . #DIV/0! 89.288 89.269 . 89.27818 . . . #DIV/0! 89.884 . . 89.88407 61.811 . . 61.81133 . 63.447 . 63.44747 . . . #DIV/0! . . . #DIV/0! . . . #DIV/0! . . . #DIV/0! . . . #DIV/0! . . . #DIV/0! . . . #DIV/0!

Density Model Body Density BSA Processi ng Siri Siri Siri Siri Siri Siri Siri #DIV/0! Siri Siri Siri #DIV/0! Siri Siri Siri #DIV/0! Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri 1.034 1.032 . 1.03335 1.018 1.017 . 1.01725 1.014 1.045 1.044 1.034466667 1.014 1.016 1.016 1.0151 1.039 1.038 1.039 1.038766667 1.061 1.055 1.050 1.055566667 1.052 1.051 1.054 1.052233333 1.025 1.027 1.028 1.026566667 1.034 1.034 1.034 1.033866667 1.029 1.031 1.030 1.029766667 1.041 1.041 1.042 1.041233333 1.050 1.048 1.050 1.049066667 1.035 1.032 1.035 1.0338 21204.569 21200.935 . 21202.75218 20564.876 20564.088 . 20564.48207 16104.624 16103.656 16102.337 16103.53895 19645.437 19644.884 19643.880 19644.73392 17778.429 17778.128 17777.676 17778.07774 18474.752 18478.103 18477.075 18476.64355 16375.934 16374.970 16374.200 16375.03469 17773.272 17773.095 17772.349

17772.90509 20612.990 20609.571 20609.014 20610.52538 23217.797 23217.879 23216.720 23217.46539 18506.779 18505.712 18505.306 18505.93208 16297.299 16296.361 16296.915 16296.85816 24355.035 24365.451 24359.916 24360.13401 JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO ΔVTG ID GRP Code Order TRIAL Mass (kg) VTGp VTG (predmeas) VTGpp 031 031 031 031 032 032 032 032 033 033 033 033 034 034 034 034 035 035 035 035 036 036 036 036 037 037 037 037 038 038 038 038 039 039 039 039 041 041 041 041 042 042 042 042 NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS MS 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 3

Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 1 2 3 Mean 70.0 69.9 69.9 69.95 64.7 64.7 64.7 64.75 53.5 53.5 53.5 53.52 55.0 54.9 54.9 54.94 98.3 98.3 98.3 98.31 52.2 52.2 52.2 52.16 65.0 65.0 65.0 64.98 68.0 68.1 68.0 68.04 61.0 61.0 61.0 60.99 106.1 106.1 106.1 106.12 128.7 128.7 128.6 128.65 3.310 3.310 3.310 3.310 3.220 3.220 3.220 3.220 3.050 3.050 3.050 3.050 3.132 3.132 3.132 3.132 4.115 4.115 4.115 4.115 2.818 2.818 2.818 2.818 3.592 3.592 3.592 3.592 3.615 3.615 3.615 3.615 3.300 3.300 3.300 3.300 3.938 3.938 3.938 3.938 4.860 4.860 4.860 4.86 3.220 3.637 3.264 3.374 3.267 3.284 3.227 3.259 2.802 2.657 2.723 2.727 3.320 3.424 3.311 3.352 3.143 2.683 2.878 2.901 2.364 2.096 2.385 2.282 3.852 3.457 3.784 3.698 3.013 2.950 2.911 2.958 2.225 2.163 2.204 2.197 3.956 3.627 3.699 3.761 5.300 4.986 3.963 4.750 0.090 -0.327 0.046 -0.064 -0.047 -0.064 -0.007 -0.039 0.248 0.393 0.327 0.323 -0.188 -0.292 -0.179 -0.220 0.972

1.432 1.237 1.214 0.454 0.722 0.433 0.536 -0.260 0.135 -0.192 -0.106 0.602 0.665 0.704 0.657 1.075 1.137 1.096 1.103 -0.018 0.311 0.239 0.177 -0.440 -0.126 0.897 0.110 97.3 109.9 98.6 101.9 101.5 102.0 100.2 101.2 91.9 87.1 89.3 89.4 106.0 109.3 105.7 107.0 76.4 65.2 69.9 70.5 83.9 74.4 84.6 81.0 107.2 96.2 105.3 102.9 83.3 81.6 80.5 81.8 67.4 65.5 66.8 66.6 100.5 92.1 93.9 95.5 109.1 102.6 81.5 97.7 62 ID GRP Code %BF Δ%BF (pred- TRIAL Order %FFM Mass FM(kg) (kg) meas) 031 031 031 031 032 032 032 032 033 033 033 033 034 034 034 034 035 035 035 035 036 036 036 036 037 037 037 037 038 038 038 038 039 039 039 039 041 041 041 041 042 042 042 042 NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW NW OB OB OB OB OB OB OB OB MS 31.90 MS 33.90 MS 32.50 32.76666667 MS MS 19.60 MS 20.60 MS 20.70 MS 20.3 MS 27.20 MS 25.40 MS 26.60 MS 26.4 MS 19.80 MS 20.10 MS 19.80 MS 19.9 MS 29.30 MS 28.00 MS 28.00 28.43333333 MS MS 24.40 MS

22.50 MS 23.40 23.43333333 MS MS 16.20 MS 14.30 MS 14.80 MS 15.1 MS 28.90 MS 28.10 MS 28.50 MS 28.5 MS 32.70 MS 32.40 MS 31.70 32.26666667 MS MS 37.90 MS 37.00 MS 36.40 MS 37.1 MS 33.00 MS 32.60 MS 31.20 32.26666667 MS 2 1.00 2 -1.20 2 0.10 2 -0.03 2 0.60 2 0.20 2 -0.40 2 0.13 2 0.20 2 1.20 2 1.00 2 0.80 2 0.60 2 -1.20 2 0.00 2 -0.20 2 1.00 2 2.80 2 2.20 2 2.00 2 0.70 2 1.80 2 0.50 2 1.00 2 0.70 2 1.00 2 1.20 2 0.97 2 3.20 2 4.20 2 3.20 2 3.53 2 3.00 2 4.30 2 4.20 2 3.83 2 -1.80 2 0.40 2 0.70 2 -0.23 2 -0.70 2 -0.50 2 0.80 2 -0.13 1st 2nd volume VTGpp volume mst. mst. 3.310 47.6418 3220 68107 0.090 66067 97.3 65.898 3.310 46.2333 3637 68374 -0.327 66061 109.9 66105 3.310 47.2123 3264 68177 0.046 66049 98.6 66.021 47.02915708 3.310 3.374 68.21933333 -0.064 6605884 101.9 6600826 3.220 52.0586 3267 61429 -0.047 59667 101.5 59290 3.220 51.4088 3284 61550 -0.064 59487 102.0 59375 3.220 51.3395 3227 61563 -0.007 59545 100.2 59389 51.6023208 3.220 3.259 61514 -0.039 5956633 101.2 593514

3.050 38.9720 2802 51606 0.248 49604 91.9 49.783 3.050 39.9291 2657 51400 0.393 49642 87.1 49.577 3.050 39.2801 2723 51524 0.327 49630 89.3 49.785 39.39372777 3.050 2.727 5151 0.323 4962534 89.4 4971488 3.132 44.0751 3320 52161 -0.188 49521 106.0 50023 3.132 43.8979 3424 52180 -0.292 50239 109.3 50026 3.132 44.0566 3311 52135 -0.179 50092 105.7 50044 44.00987879 3.132 3.352 52.15866667 -0.220 4995067 107.0 5003104 4.115 69.5170 3143 95207 0.972 92913 76.4 92.942 4.115 70.7813 2683 94932 1.432 92818 65.2 92.854 4.115 70.7676 2878 94921 1.237 92721 69.9 92.774 70.35528577 4.115 2.901 9502 1.214 928174 70.5 928567 2.818 39.4422 2364 49996 0.454 48420 83.9 48.287 2.818 40.4247 2096 49789 0.722 48469 74.4 48.278 2.818 39.9524 2385 49882 0.433 48306 84.6 48.155 39.93974011 2.818 2.282 49889 0.536 4839823 81.0 482399 3.592 54.4645 3852 61216 -0.260 58806 107.2 58901 3.592 55.6920 3457 60950 0.135 58699 96.2 58.952 3.592 55.3585 3784 61010 -0.192 58908 105.3 58643 55.17166703 3.592 3.698

61.05866667 -0.106 5880415 102.9 5883199 3.615 48.3757 3013 65829 0.602 63729 83.3 63.839 3.615 48.9314 2950 65736 0.665 63708 81.6 63.724 3.615 48.6444 2911 65762 0.704 63754 80.5 63.761 48.6505046 3.615 2.958 65.77566667 0.657 6373029 81.8 6377465 3.300 41.0249 2225 59449 1.075 57708 67.4 57.826 3.300 41.2460 2163 59460 1.137 57785 65.5 57.821 3.300 41.6702 2204 59371 1.096 57897 66.8 57.646 41.31369942 3.300 2.197 59.42666667 1.103 5779678 66.6 577641 3.938 65.8982 3956 104586 -0.018 101992 100.5 101925 3.938 66.8640 3627 104411 0.311 102032 92.1 101798 3.938 67.4871 3699 104271 0.239 101724 93.9 101769 66.74978533 3.938 3.761 104.4226667 0.177 1019159 95.5 1018306 4.860 86.2075 5300 125544 -0.440 122168 109.1 122240 4.860 86.7122 4986 125436 -0.126 122299 102.6 122145 4.860 88.5008 3963 125043 0.897 121895 81.5 122281 87.14017667 4.86 4.750 125341 0.110 1221205 97.7 1222217 ΔVTG (predVTGp FFM (kg) VTG Body Volume meas) 1 68.10 2 66.10 3 67.50 Mean 67.23 1 80.40 2 79.40 3 79.30

Mean 79.70 1 72.80 2 74.60 3 73.40 Mean 73.60 1 80.20 2 79.90 3 80.20 Mean 80.10 1 70.70 2 72.00 3 72.00 Mean 71.57 1 75.60 2 77.50 3 76.60 Mean 76.57 1 83.80 2 85.70 3 85.20 Mean 84.90 1 71.10 2 71.90 3 71.50 Mean 71.50 1 67.30 2 67.60 3 68.30 Mean 67.73 1 62.10 2 63.00 3 63.60 Mean 62.90 1 67.00 2 67.40 3 68.80 Mean 67.73 70.0 22.3 69.9 23.7 69.9 22.7 69.95 22.92 64.7 12.7 64.7 13.3 64.7 13.4 64.75 13.14 53.5 14.6 53.5 13.6 53.5 14.2 53.52 14.13 55.0 10.9 54.9 11.0 54.9 10.9 54.94 10.93 98.3 28.8 98.3 27.5 98.3 27.5 98.31 27.95 52.2 12.7 52.2 11.7 52.2 12.2 52.16 12.22 65.0 10.5 65.0 9.3 65.0 9.6 64.98 9.81 68.0 19.7 68.1 19.1 68.0 19.4 68.04 19.39 61.0 19.9 61.0 19.8 61.0 19.3 60.99 19.68 106.1 40.2 106.1 39.3 106.1 38.6 106.12 39.37 128.7 42.5 128.7 41.9 128.6 40.1 128.65 41.51 63 3rd volume mst. . . . #DIV/0! 59.344 . . 59.34392 49.732 . . 49.73238 50.158 50.110 . 50.1339 . . . #DIV/0! . 48.229 . 48.22876 . 58.791 58.705 58.74812 . . . #DIV/0! . . 57.748 57.74847 . . . #DIV/0!

. . 122.194 122.1941 Density Model Body Density BSA Processi ng Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri Siri 1.027 1.023 1.026 1.025366667 1.054 1.052 1.052 1.052533333 1.037 1.041 1.039 1.039066667 1.054 1.053 1.054 1.0534 1.033 1.036 1.036 1.034633333 48.420 48.469 48.306 48.39822795 1.062 1.662 1.065 1.2629 1.034 1.035 1.035 1.034466667 1.025 1.026 1.028 1.026366667 1.015 1.017 1.018 1.016266667 1.025 1.026 1.029 1.0264 17914.730 17913.201 17913.160 17913.69683 17245.159 17244.830 17244.182 17244.72338 15579.009 15577.935 15576.794 15577.91267 15908.758 15906.859 15905.913 15907.17669 21889.838 21888.006 21886.211 21888.01827 14937.169 14935.797 14935.343 14936.10331 17609.947 17608.955 17607.797 17608.89968 17994.086 17995.864 17993.550 17994.5002 16954.698 16961.376 16960.882 16958.98522 22374.915

22376.444 22374.517 22375.29232 26132.282 26131.010 26129.428 26130.9067 JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO JO Screen Captures of Raw Data from DXA: ID GRP Code Status Area (cm2) L arm Area (cm2) R arm Area (cm2) L Ribs Area (cm2) R Ribs 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA DXA Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed Completed 262.5 233.7 175.27 210.16 215.84 243.84 205.29 215.03 247.9 279.54 195.56 182.28 293.42 207.74 198.85 165.71 175.41 280.08 176.62 243.31 231.99

178.64 247.35 302.31 265.75 235.32 182.57 205.7 218.68 246.68 205.29 202.05 268.99 296.18 214.63 202.89 311.61 221.88 186.32 167.32 183.89 301.91 185.51 263.11 223.91 187.13 253.41 302.31 139.97 129.83 107.11 151.33 140.38 144.84 95.75 119.69 147.28 172.03 104.68 133.78 105.08 138.22 132.16 119.63 114.38 145.09 89.32 109.12 133.78 124.89 161.66 168.54 169.19 142.41 122.93 190.28 139.97 146.47 101.02 123.74 128.21 134.7 101.43 114.78 142.67 127.72 117.61 118.82 113.57 143.88 115.19 115.99 115.59 130.14 152.77 120.84 Area (cm2) T Area (cm2) L Spine Spine ID GRP BMC (g) L BMC (g) Area R (cm2) BMC L (g) Area L (cm2) BMC (g) Area R (cm2) BMC (g) Area T (cm2) BMC (g) Area L (cm2) BMC T Area (g) (cm2) BMC L (g) Area L (cm2) BMC (g) Area R (cm2) BMC L (g) Area (cm2) BMC (g) Area (cm2) BMC (g) Area (cm2) BMC MArea PP (cm2) BMC F PP Code Status arm arm arm Ribs R arm Ribs L Ribs Spine R Ribs Spine Spine Pelvis Spine Leg Pelvis leg Leg Subtotal R leg Head Subtotal Total Head (%) Total (%)

014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB DXA 230.89 Completed 235.53 2625 864 26575 10297 13997 12497 16919 6312 14363 36317 6126 55358 2698 53121 42804 22918540937 6229 21495129147527832 10775242783 13723 DXA 178.87 Completed 184.63 2337 7815 23532 8103 12983 9743 14241 4747 13835 25589 5274 4285 21584 44758 37286 17995537894 45935189999 22589 23532 8351 213531 10635 DXA 124.78 Completed 312.71 17527 5817 18257 6596 10711 10223 12293 3593 1278 26861 353 39504 23086 40955 35744 15930137448 50519171376 20982 25033 7616 196409 9638 DXA 214.99 Completed 154.31 21016 8162 2057 10945 15133 11958 19028 2784 14484 22527 3205 39882 17284 38256 34892 17144234324 4457 179937216014 2337 7986 203307 10170 DXA 160.89 Completed 170.66 21584 857 21868 893 14038 1226 13997 5008 13308 34417 4219 45467 23329 46242 39233 19404940045 6010419162225415323207 93.95674677 2148.29

11966 DXA 206.75 Completed 207.95 24384 9804 24668 9766 14484 12913 14647 5984 14363 36598 4788 50892 2836 55928 40393 223356 4388 65814209149 28917 27386 106.9020333 2365.35 13614 DXA 153.21 Completed 153.78 20529 5058 20529 5456 9575 9799 10102 3532 12172 17482 3854 35715 17608 35724 32742 14346532945 5307416005719653927792 275500187849 9028 DXA 163.79 Completed 152.67 21503 7712 20205 7622 11969 10626 12374 721 1278 32476 5883 49859 23816 47094 38949 194244 3903 65691 18651 25993524749 93.90715318 2112.59 11826 DXA 202.64 Completed 223.01 2479 9662 26899 8296 14728 14141 12821 5272 14687 36246 5274 5064 24668 51228 40978 21805142195 5683 207039 27488 2625 101.6192237 2332.89 12942 DXA 257.35 Completed 275.65 27954 13129 29618 10037 17203 15247 1347 8133 15417 44245 641 65937 29942 5967 49823 26969848443 65848 23828 33554625155 124.0465804 2634.35 15798 DXA 147.22 Completed 156.42 19556 6803 21463 5764 10468 1089 10143 4578 1274 29337 4341 38894 24992 3865 37773 16527937164 6697

17863923224930348 85.85914972 2089.87 10935 DXA 121.55 Completed 143.47 18228 7919 20289 6021 13378 8314 11478 3752 11599 26559 4001 36778 25098 36865 3496 15271136698 51243 17573 20395424573 75.39889094 2003.03 9602 DXA 289.38 Completed 316.21 29342 8667 31161 11022 10508 18742 14267 9431 1455 47005 7719 74957 28049 76487 51207 30687153956 6554624075937241726634 136.2168983 2673.93 17306 DXA 151.85 Completed 166.23 20774 9153 22188 8026 13822 11379 12772 5385 13459 28111 5214 39947 22188 41036 35647 17484336375 5800418243923284723886 275500206325 10696 DXA 152.54 Completed 138.89 19885 8764 18632 7858 13216 13011 11761 3997 13903 35589 3314 44093 24654 44321 36132 18677736415 6125617791224803225422 91.69390018 2033.34 11678 DXA 126.68 Completed 131.97 16571 688 16732 6587 11963 10602 11882 411 12044 29537 3516 37047 21259 37105 32899 15773331888 4575515875520348923765 75.22698706 1825.19 9580 DXA 123.42 Completed 133.2 17541 6515 18389 6483 11438 10071 11357 4142 11519 27762 4042

38742 25503 37425 33545 15680233101 6479916643422160126473 81.92273567 1929.06 10433 DXA 239.74 Completed 261.74 28008 10112 30191 9581 14509 12218 14388 4593 1362 28788 5092 51923 23482 51627 45872 218991 4567 5839522083427738626715 101.4579371 2475.49 12890 DXA 133.81 Completed 148.71 17662 5389 18551 6658 8932 10224 11519 4119 11802 21796 3718 2848 18672 31301 27887 13621929585 55597148327 13381 26149 4.94676525 1744.77 630 DXA 209.44 Completed 225.73 24331 7685 26311 7068 10912 1082 11599 5035 12125 31576 4688 45369 26479 4606 36819 19713137264 64199190522 26133 2729660998152 2177.22 12304 DXA 157.19 Completed 154.48 23199 8173 22391 6754 13378 9091 11559 4659 13418 22663 5012 37438 21784 34442 3783 15438835849 4949518441920388324977 75.37264325 2093.96 9599 DXA 130.65 Completed 135.75 17864 7012 18713 6828 12489 1005 13014 4013 12448 2318 4001 39013 18753 38342 34898 15507734798 5569 166919 2107 24533 77.89279113 1914.51 9920 DXA 211.74 Completed 224.18 24735 1046 25341 957 16166

12708 15277 492 14429 29759 4527 4279 21784 20109338234 5386 40861 25495320135325495325018 94.25249538 2263.71 12003 DXA 279.08 Completed 279.08 30231 11342 30231 7209 16854 14967 12084 6746 17824 36039 6911 75181 24654 66035 49429 27333448459 4603523667731936924411 116.8138259 2610.89 14841 ID GRP BMD (g/cm2) BMD (g/cm2) Area (cm2) BMDL(g/cm2) Area (cm2) BMD (g/cm2) Area (cm2) BMD (g/cm2) Area (cm2) BMD (g/cm2) Area (cm2) BMDT(g/cm2) Area (cm2) BMDL(g/cm2) Area (cm2) BMD (g/cm2) Area (cm2) BMDL(g/cm2) Area (cm2) BMD (g/cm2) Area (cm2) BMD (g/cm2) Area (cm2) BMD MArea PP (cm2) BMD F PP Code Status L arm R arm arm L Ribs R arm R Ribs L Ribs T SpineR RibsL Spine Spine Pelvis Spine L Leg Pelvis R leg Leg Subtotal R leg Head Subtotal Total Head (%) Total (%) 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB 143.63 138.35 127.8 144.84 133.08 143.63 121.72 127.8 146.87

154.17 127.4 115.99 145.5 134.59 139.03 120.44 115.19 136.2 118.02 121.25 134.18 124.48 144.29 178.24 DXA 0.88 Completed 0.886 2625 0617 26575 0609 13997 087 16919 103 14363 1346 DXA 0.765 Completed 0.785 2337 0602 23532 0569 12983 0704 14241 09 13835 1186 DXA 0.712 Completed 0.727 17527 0543 18257 0537 10711 08 12293 1018 1278 1164 DXA 1.023 Completed 0.75 21016 0539 2057 0575 15133 0826 19028 0869 14484 1303 DXA 0.745 Completed 0.78 21584 0611 21868 0638 14038 0921 13997 1187 13308 1475 DXA 0.848 Completed 0.843 24384 0677 24668 0667 14484 0667 14647 0899 14363 125 DXA 0.746 Completed 0.749 20529 0528 20529 054 9575 0805 10102 0916 12172 0993 DXA 0.762 Completed 0.756 21503 0644 20205 0616 11969 0831 12374 1225 1278 1364 DXA 0.817 Completed 0.829 2479 0656 26899 0647 14728 0963 12821 1 146.87 1469 DXA 0.921 Completed 0.931 27954 0763 29618 0745 17203 0989 1347 1269 15417 1478 DXA 0.753 Completed 0.729 19556 065 21463 0568 10468 0855 10143 1055 1274 1174 DXA 0.667 Completed 0.707

18228 0592 20289 0525 13378 0717 11478 0938 11599 1058 DXA 0.986 Completed 1.015 29342 0825 31161 0773 10508 1288 14267 1222 1455 1676 DXA 0.731 Completed 0.749 20774 0662 22188 0628 13822 0845 12772 1033 13459 1267 DXA 0.767 Completed 0.745 19885 0663 18632 0668 13216 0936 11761 1206 13903 1444 DXA 0.764 Completed 0.789 16571 0575 16732 0554 11963 088 11882 1169 12044 1389 DXA 0.704 Completed 0.724 17541 057 18389 0571 11438 0874 11357 1025 11519 1089 DXA 0.856 Completed 0.867 28008 0697 30191 0666 14509 0897 14388 0902 1362 1226 DXA 0.758 Completed 0.802 17662 0603 18551 0578 8932 0866 11519 1108 11802 1167 DXA 0.861 Completed 0.858 24331 0704 26311 0609 10912 0892 11599 1074 12125 1193 DXA 0.678 Completed 0.69 23199 0611 22391 0584 13378 0677 11559 093 13418 104 DXA 0.731 Completed 0.725 17864 0561 18713 0525 12489 0807 13014 1003 12448 1236 DXA 0.856 Completed 0.885 24735 0647 25341 0626 16166 0881 15277 1087 14429 1366 DXA 0.923 Completed 0.923 30231 0673 30231 0597 16854 084

12084 0976 17824 1462 64 61.26 52.74 35.3 32.05 42.19 47.88 38.54 58.83 52.74 64.1 43.41 40.01 77.19 52.14 33.14 35.16 40.42 50.92 37.18 46.88 50.12 40.01 45.27 69.11 61.26 52.74 35.3 32.05 42.19 47.88 38.54 58.83 52.74 64.1 43.41 40.01 77.19 52.14 33.14 35.16 40.42 50.92 37.18 46.88 50.12 40.01 45.27 69.11 Area (cm2) Pelvis Area (cm2) L Leg Area (cm2) R leg Area (cm2) Subtotal Area (cm2) Head Area (cm2) Total 269.8 215.84 230.86 172.84 233.29 283.6 176.08 238.16 246.68 299.42 249.92 250.98 280.49 221.88 246.54 212.59 255.03 234.82 186.72 264.79 217.84 187.53 217.84 246.54 428.04 372.86 357.44 348.92 392.33 403.93 327.42 389.49 409.78 498.23 377.73 349.6 512.07 356.47 361.32 328.99 335.45 458.72 278.87 368.19 378.3 348.98 382.34 494.29 409.37 378.94 374.48 343.24 400.45 43.88 329.45 390.3 421.95 484.43 371.64 366.98 539.56 363.75 364.15 318.88 331.01 456.7 295.85 372.64 358.49 347.98 408.61 484.59 2149.51 1899.99 1713.76 1799.37 1916.22 2091.49 1600.57 1865.1 2070.39

2382.8 1786.39 1757.3 2407.59 1824.39 1779.12 1587.55 1664.34 2208.34 1483.27 1905.22 1844.19 1669.19 2013.53 2366.77 278.32 235.32 250.33 233.7 232.07 273.86 277.92 247.49 262.5 251.55 303.48 245.73 266.34 238.86 254.22 237.65 264.73 267.15 261.49 272 249.77 245.33 250.18 244.11 2427.83 2135.31 1964.09 2033.07 2148.29 2365.35 1878.49 2112.59 2332.89 2634.35 2089.87 2003.03 2673.93 2063.25 2033.34 1825.19 1929.06 2475.49 1744.77 2177.22 2093.96 1914.51 2263.71 2610.89 1.293 2698 1298 42804 1066 40937 2238 214951 1201 27832 101.350211 2427.83 109.7806216 1.149 21584 1181 37286 0947 37894 1952 189999 1058 23532 89.28270042 2135.31 96.70932358 1.104 23086 1094 35744 093 37448 2018 171376 1068 25033 88.85191348 1964.09 95.78475336 1.143 17284 1115 34892 0953 34324 1907 179937 1063 2337 89.70464135 2033.07 97.16636197 1.159 23329 1155 39233 1013 40045 259 191622 1183 23207 99.83122363 2148.29 108.1352834 1.29 2836 1261 40393 1298 4388 1068 209149 1223 27386 103.2067511 2365.35

111.7915905 1.091 17608 1084 32742 0896 32945 191 160057 1046 27792 87.02163062 1878.49 93.81165919 1.28 23816 1207 38949 1041 3903 2654 18651 123 24749 102.6711185 2112.59 109.6256684 1.236 24668 1214 40978 1053 42195 2165 207039 1178 2625994092827 2332.89 107.678245 1.323 29942 1232 49823 1132 48443 2618 23828 1274 25155 107.5105485 2634.35 116.4533821 1.03 24992 104 37773 0925 37164 2207 178639 1111 30348 93.75527426 2089.87 101.5539305 1.052 25098 1005 3496 0869 36698 2085 17573 1018 2457385907173 2003.03 93.05301645 1.464 28049 1418 51207 1275 53956 2461 240759 1393 26634 116.4715719 2673.93 125.9493671 1.121 22188 1128 35647 0958 36375 2428 182439 1129 23886 93.92678869 2063.25 101.2556054 1.22 24654 1217 36132 105 36415 241 177912 122 25422 102.9535865 2033.34 111.5173675 1.126 21259 1164 32899 0994 31888 1925 158755 1115 2376594092827 1825.19 101.9195612 1.155 25503 1131 33545 0942 33101 2448 166434 1149 26473 96.96202532 1929.06 105.0274223 1.132 23482 113 45872 0992 4567 2186

220834 1121 26715 93.72909699 2475.49 101.3562387 1.021 18672 1058 27887 0918 29585 2126 148327 1099 26149 92.74261603 1744.77 100.4570384 1.232 26479 1236 36819 1035 37264 236 190522 12 272101.2658228 2177.22 109.6892139 0.99 21784 0961 3783 0837 35849 1982 184419 0974 24977 82.19409283 2093.96 89.03107861 1.12 18753 1102 34898 0929 34798 227 166919 1101 24533 92.91139241 1914.51 100.6398537 1.119 21784 1157 38234 0999 40861 2153 201353 1126 25018 95.02109705 2263.71 102.9250457 1.521 24654 1363 49429 1155 48459 1866 236677 1223 24411 102.2575251 2610.89 110.5786618 Fat Mass (g) Fat Mass Area (g)(cm2) Fat Mass L Area (g) (cm2) Fat Mass Area (g) (cm2) Fat Mass Area (g) (cm2) Fat Mass Area (g)(cm2) Fat Mass T Area (g)(cm2) Fat Mass L Area (g) (cm2) Fat Mass Area (g)(cm2) Fat Mass L Area (g) (cm2) Code Status L Arm R Arm arm Trunk R arm L Leg L Ribs R Leg R RibsSubtotalSpine Head Spine Total Pelvis Android Leg Gynoid R leg Area (cm2) Subtotal Are H 2149.51 1899.99 1713.76 1799.37

1916.22 2091.49 1600.57 1865.1 2070.39 2382.8 1786.39 1757.3 2407.59 1824.39 1779.12 1587.55 1664.34 2208.34 1483.27 1905.22 1844.19 1669.19 2013.53 2366.77 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 Area (cm2) Subtotal Are H 2149.51 1899.99 1713.76 1799.37 1916.22 2091.49 1600.57 1865.1 2070.39 2382.8 1786.39 1757.3 2407.59 1824.39 1779.12 1587.55 1664.34 2208.34 1483.27 1905.22 1844.19 1669.19 2013.53 2366.77 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 Total Mass Total Mass Area (cm2) Total L Mass Area (cm2) Total Mass Area (cm2) Total Mass Area (cm2) Total Mass Area (cm2) Total T Mass Area (cm2) Total L Mass Area (cm2) Total Mass Area (cm2) Total L Mass Area (cm2) Code Status (g) L Arm (g) R Arm arm (g) TrunkR arm(g) L LegL Ribs(g) R LegR Ribs (g) Subtotal Spine (g) HeadSpine (g) TotalPelvis (g) AndroidLeg(g) GynoidR leg Area (cm2) Subtotal Are H DXA 6460 Completed 6659 262.5 46132 26575 15493 13997 15154 16919 89888 14363 DXA 5656 Completed 5886 233.7 44534 23532 16283 12983 347

14241 88681 13835 DXA 2629 Completed 2731 175.27 24426 18257 9804 10711 10214 12293 49805 1278 DXA 5476 Completed 5795 210.16 48080 2057 14506 15133 15134 19028 88991 14484 DXA 3605 Completed 3739 215.84 30490 21868 11957 14038 12940 13997 62731 13308 DXA 4239 Completed 4226 243.84 32333 24668 12039 14484 12788 14647 65614 14363 DXA 3820 Completed 3816 205.29 26590 20529 9967 9575 10263 10102 54457 12172 DXA 3697 Completed 3702 215.03 32121 20205 12595 11969 12972 12374 65087 1278 DXA 5580 Completed 6101 247.9 45416 26899 14891 14728 15700 12821 87689 14687 DXA 6792 Completed 7546 279.54 52168 29618 20392 17203 20189 1347 107087 15417 DXA 3883 Completed 3979 195.56 31695 21463 13404 10468 13483 10143 66444 1274 DXA 2793 Completed 3301 182.28 26320 20289 10229 13378 10193 11478 52836 11599 DXA 8298 Completed 8729 293.42 54894 31161 18911 10508 19371 14267 110202 1455 DXA 3521 Completed 3795 207.74 35637 22188 11604 13822 12064 12772 66622 13459 DXA 3729 Completed 3473 198.85 30192 18632

11800 13216 12174 11761 61368 13903 DXA 3070 Completed 3298 165.71 25361 16732 9121 11963 9457 11882 50307 12044 DXA 3078 Completed 3248 175.41 23791 18389 10353 11438 10718 11357 51190 11519 DXA 6987 Completed 7323 280.08 47148 30191 16287 14509 16450 14388 94195 1362 DXA 3081 Completed 3403 176.62 22567 18551 9260 8932 9810 11519 48122 11802 DXA 4548 Completed 4976 243.31 29172 26311 10563 10912 11607 11599 60866 12125 DXA 3952 Completed 4077 231.99 31342 22391 12118 13378 12045 11559 63534 13418 DXA 3305 Completed 3506 178.64 29583 18713 101998 12489 10350 13014 56942 12448 DXA 7057 Completed 7727 247.35 51032 25341 16606 16166 17824 15277 100245 14429 DXA 8973 Completed 8973 302.31 63432 30231 22435 16854 21759 12084 125572 17824 2149.51 1899.99 1713.76 1799.37 1916.22 2091.49 1600.57 1865.1 2070.39 2382.8 1786.39 1757.3 2407.59 1824.39 1779.12 1587.55 1664.34 2208.34 1483.27 1905.22 1844.19 1669.19 2013.53 2366.77 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 ID GRP 014 015 016 019

020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB ID GRP 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB DXA 4733 Completed 4921 262.5 33561 26575 11146 13997 10887 16919 65247 14363 DXA 37.61 Completed 38.7 2337 30441 23532 10635 12983 10515 14241 59222 13835 DXA 1921 Completed 2057 175.27 20250 18257 6780 10711 6852 12293 37860 1278 DXA 3592 Completed 3840 210.16 29674 2057 9814 15133 10489 19028 57410 14484 DXA 2267 Completed 2439 215.84 23031 21868 7959 14038 8532 13997 44228 13308 DXA 3384 Completed 3362 243.84 25464 24668 9336 14484 9870 14647 51417 14363 DXA 2916 Completed 2970 205.29 22125 20529 7362 9575 7527 10102 42901 12172 DXA 2224 Completed 2337 215.03 22202 20205 7809 11969 7902 12374 42473 1278 DXA 3895 Completed 4419 247.9 32908 26899 10552

14728 11307 12821 63081 14687 DXA 4594 Completed 5251 279.54 36358 29618 14030 17203 13697 1347 73931 15417 DXA 2831 Completed 2951 195.56 25271 21463 9662 10468 9502 10143 50217 1274 DXA 1996 Completed 2437 182.28 22063 20289 7404 13378 7396 11478 41296 11599 DXA 5964 Completed 6366 293.42 38369 31161 13493 10508 14136 14267 78328 1455 DXA 2254 Completed 2500 207.74 23746 22188 7071 13822 7409 12772 42980 13459 DXA 2793 Completed 2631 198.85 24221 18632 8985 13216 9140 11761 47770 13903 DXA 2193 Completed 2401 165.71 18653 16732 6423 11963 6597 11882 36266 12044 DXA 2283 Completed 2516 175.41 19748 18389 7328 11438 7598 11357 39472 11519 DXA 5228 Completed 5537 280.08 34041 30191 11279 14509 11053 14388 67138 1362 DXA 2268 Completed 2502 176.62 18210 18551 6383 8932 6975 11519 36338 11802 DXA 3761 Completed 4039 243.31 24602 26311 8197 10912 8982 11599 49581 12125 DXA 2256 Completed 2381 231.99 23019 22391 7381 13378 7424 11559 42460 13418 DXA 2096 Completed 2342 178.64 20497 18713

6974 12489 6937 13014 38846 12448 DXA 4720 Completed 5199 247.35 32254 25341 10571 16166 11487 15277 65230 14429 DXA 5898 Completed 5898 302.31 43498 30231 15269 16854 14513 12084 85076 17824 ID GRP 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB DXA 1728 Completed 1728 262.5 12572 26575 DXA 1896 Completed 2016 233.7 14093 23532 DXA 708 Completed 674 175.27 4176 18257 DXA 1883 Completed 1955 210.16 18407 2057 DXA 1337 Completed 1300 215.84 7460 21868 DXA 854 Completed 864 243.84 6868 24668 DXA 904 Completed 846 205.29 4465 20529 DXA 1473 Completed 1365 215.03 9920 20205 DXA 1685 Completed 1682 247.9 12508 26899 DXA 2198 Completed 2295 279.54 15810 29618 DXA 1052 Completed 1028 195.56 6424 21463 DXA 796 Completed 864 182.28 4258 20289 DXA 2334 Completed 2362 293.42 16524 31161 DXA 1267 Completed 1295 207.74 11892 22188 DXA 936 Completed 842 198.85 5970 18632 DXA

878 Completed 897 165.71 6708 16732 DXA 795 Completed 733 175.41 4044 18389 DXA 1759 Completed 1786 280.08 13107 30191 DXA 814 Completed 901 176.62 4358 18551 DXA 787 Completed 937 243.31 4570 26311 DXA 1697 Completed 1696 231.99 8323 22391 DXA 1209 Completed 1164 178.64 9086 18713 DXA 2336 Completed 2528 247.35 187778 25341 DXA 3075 Completed 3075 302.31 19934 30231 4347 139.97 5648 129.83 3025 107.11 4692 151.33 3998 140.38 2702 144.84 2605 95.75 4786 119.69 4340 147.28 6363 172.03 3743 104.68 2825 133.78 5418 105.08 4533 138.22 2815 132.16 2699 119.63 3025 114.38 5009 145.09 2877 89.32 2366 109.12 4737 133.78 3223 124.89 6035 161.66 7166 168.54 4266 169.19 24640 14363 5806 142.41 29459 13835 3362 122.93 11944 1278 4644 190.28 31581 14484 4409 139.97 18503 13308 2909 146.47 14197 14363 2736 101.02 11557 12172 5070 123.74 22614 1278 4393 128.21 24608 14687 6492 134.7 33157 15417 3981 101.43 16228 1274 2797 114.78 11540 11599 5235 142.67 31874 1455 4654 127.72 23642 13459 3035 117.61

13598 13903 2859 118.82 14041 12044 2121 113.57 11718 11519 5397 143.88 27057 1362 2835 115.19 11784 11802 2625 115.99 11285 12125 4621 115.59 21074 13418 3413 130.14 18096 12448 6337 152.77 36014 14429 7246 120.84 40496 17824 1704 1300 1124 1456 1138 1307 1372 1149 1473 1569 1473 1143 1771 1074 1169 1047 1213 1453 1159 1297 1187 1225 1891 1430 61.26 52.74 35.3 32.05 42.19 47.88 38.54 58.83 52.74 64.1 43.41 40.01 77.19 52.14 33.14 35.16 40.42 50.92 37.18 46.88 50.12 40.01 45.27 69.11 26344 269.8 30759 215.84 13069 230.86 33037 172.84 19641 233.29 15504 283.6 12929 176.08 23764 238.16 26081 246.68 34756 299.42 17701 249.92 12684 250.98 33644 280.49 24716 221.88 14767 246.54 15087 212.59 12931 255.03 28510 234.82 12943 186.72 12582 264.79 22261 217.84 19320 187.53 37905 217.84 41926 246.54 2116 428.04 2659 372.86 615 357.44 2932 348.92 1172 392.33 1208 403.93 665 327.42 1573 389.49 2148 409.78 2930 498.23 1122 377.73 679 349.6 3105 512.07 2112 356.47 842 361.32 1014 328.99 636 335.45

2378 458.72 780 278.87 781 368.19 1218 378.3 1283 348.98 3170 382.34 3854 494.29 4239 409.37 5609 378.94 3026 374.48 4988 343.24 3971 400.45 3115 43.88 2212 329.45 4786 390.3 4575 421.95 5919 484.43 3961 371.64 3072 366.98 5155 539.56 5083 363.75 2958 364.15 2854 318.88 2974 331.01 4543 456.7 2728 295.85 2380 372.64 4341 358.49 3157 347.98 5607 408.61 6698 484.59 Lean+ BMC Lean+ Area BMC (cm2) Lean+ L BMC Area (cm2) Lean+ BMC Area (cm2) Lean+ BMC Area (cm2) Lean+ Area BMC (cm2) Lean+ T Area BMC (cm2) Lean+ L BMC Area (cm2) Lean+ Area BMC (cm2) Lean+ L BMC Area (cm2) Code Status (g) L Arm (g) R Arm arm (g) TrunkR arm(g) L LegL Ribs(g) R LegR Ribs (g) Subtotal Spine (g) HeadSpine (g) TotalPelvis (g) AndroidLeg(g) GynoidR leg 65 5163 3886 3489 4164 3586 4117 4207 3646 4449 4791 4592 3553 5268 3397 3688 3241 3839 4461 3648 4135 3644 3786 5270 4128 6867 5185 4613 5620 4724 5424 5580 4796 5921 6360 6065 4697 7039 4471 4858 4287 5052 5914 4807 5432 4830 5011 7161 5558 61.26 52.74 35.3

32.05 42.19 47.88 38.54 58.83 52.74 64.1 43.41 40.01 77.19 52.14 33.14 35.16 40.42 50.92 37.18 46.88 50.12 40.01 45.27 69.11 70410 269.8 63108 215.84 54418 230.86 61573 172.84 47814 233.29 55535 283.6 47108 176.08 46119 238.16 67530 246.68 78722 299.42 54808 249.92 44849 250.98 83597 280.49 46377 221.88 51458 246.54 39507 212.59 43311 255.03 71600 234.82 39986 186.72 53716 264.79 46104 217.84 42633 187.53 69501 217.84 89204 246.54 4143 428.04 9885 40937 4202 372.86 10387 37894 3349 357.44 9157 37448 4127 348.92 9956 34324 2914 392.33 7366 40045 3134 403.93 8433 4388 2679 327.42 6366 32945 2964 389.49 7221 3903 4798 409.78 9852 42195 5619 498.23 12262 48443 3165 377.73 8177 37164 3038 349.6 6954 36698 5146 512.07 11096 53956 3131 356.47 7282 36375 3058 361.32 8355 36415 2153 328.99 5943 31888 2591 335.45 6928 33101 4629 458.72 9845 4567 2174 278.87 5339 29585 3359 368.19 8129 37264 3015 378.3 7346 35849 2510 348.98 6033 34798 4446 382.34 10284 40861 7089 494.29 13721 48459 61.26

96754 2698 6259 42804 14124 40937 52.74 93866 21584 6861 37286 15996 37894 35.3 54418 23086 03349 35744 9157 37448 32.05 94610 17284 7059 34892 14944 34324 42.19 67455 23329 4086 39233 11337 40045 47.88 71039 2836 4342 40393 11549 4388 38.54 60037 17608 3345 32742 8578 32945 58.83 69883 23816 4537 38949 12008 3903 52.74 93611 24668 6946 40978 14428 42195 64.1 113448 29942 8548 49823 18181 48443 43.41 72509 24992 4287 37773 12138 37164 40.01 57532 25098 3716 3496 10026 36698 77.19 117241 28049 8251 51207 16250 53956 52.14 71092 22188 5244 35647 12365 36375 33.14 66226 24654 3900 36132 11313 36415 35.16 54594 21259 3167 32899 8797 31888 40.42 56241 25503 3227 33545 9902 33101 50.92 100110 23482 706 45872 14388 4567 37.18 52929 18672 2953 27887 8067 29585 46.88 66298 26479 4140 36819 10510 37264 50.12 68364 21784 4234 3783 11687 35849 40.01 61953 18753 3794 34898 9190 34798 45.27 107405 21784 7616 38234 15891 40861 69.11 131129 24654 10943 49429 20419 48459 2 2 2 2 2 2 2 2 2 2 2 2

ID GRP 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB ID GRP 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB ID GRP 014 015 016 019 020 021 022 023 024 025 027 028 030 031 032 033 034 035 036 037 038 039 041 042 OB OB NW OB NW NW NW NW OB OB NW NW OB NW NW NW NW OB NW NW NW NW OB OB Area (cm2) L Area (cm2) Area (cm2) Area (cm2) % Fat Area (cm2) T Area (cm2) L Area (cm2) Area (cm2) L Area (cm2) %Code Fat L ArmStatus % Fat R Arm % Fat Trunk % Fat L Leg % Fat R Leg % Fat Head % Fat Total % Fat M PP % Fat F PP arm R arm L Ribs R RibsSubtotalSpine Spine Pelvis Leg R leg DXA 26.7 DXA 33.5 DXA 26.9 DXA 34.4 DXA 37.1 DXA 20.2 DXA 23.7 DXA 39.9 DXA 30.2 DXA 32.4 DXA 27.1 DXA 28.5 DXA 28.1 DXA 36 DXA 25.1 DXA 28.6 DXA 25.8 DXA 25.2 DXA 26.4 DXA

17.3 DXA 42.9 DXA 36.6 DXA 33.1 DXA 34.3 Completed26 Completed 34.3 Completed 24.7 Completed 33.7 Completed 34.8 Completed 20.4 Completed 22.2 Completed 36.9 Completed 27.6 Completed 30.4 Completed 25.8 Completed 26.2 Completed 27.1 Completed 34.1 Completed 24.2 Completed 27.2 Completed 22.6 Completed 24.4 Completed 26.5 Completed 18.8 Completed 41.6 Completed 33.2 Completed 32.7 Completed 34.3 262.5 233.7 175.27 210.16 215.84 243.84 205.29 215.03 247.9 279.54 195.56 182.28 293.42 207.74 198.85 165.71 175.41 280.08 176.62 243.31 231.99 178.64 247.35 302.31 27.3 31.6 17.1 383 24.5 21.2 16.8 30.9 27.5 30.3 20.3 16.2 30.1 33.4 19.8 26.5 17 27.8 19.3 15.7 26.6 30.7 36.8 31.4 265.75 235.32 182.57 205.7 218.68 246.68 205.29 202.05 268.99 296.18 214.63 202.89 311.61 221.88 186.32 167.32 183.89 301.91 185.51 263.11 223.91 187.13 253.41 302.31 28.1 34.7 30.9 32.3 33.4 22.4 26.1 38 29.1 31.2 27.9 27.6 28.7 39.1 23.9 29.6 29.2 30.8 31.1 22.4 39.1 31.6 36.3 31.9 139.97 129.83 107.11 151.33

140.38 144.84 95.75 119.69 147.28 172.03 104.68 133.78 105.08 138.22 132.16 119.63 114.38 145.09 89.32 109.12 133.78 124.89 161.66 168.54 28.2 35.6 32.9 30.7 34.1 2.8 26.7 39.1 28 32.2 29.5 27.4 27 38.6 24.9 30.2 29.1 32.8 28.9 22.6 38.4 33 35.6 33.3 169.19 142.41 122.93 190.28 139.97 146.47 101.02 123.74 128.21 134.7 101.43 114.78 142.67 127.72 117.61 118.82 113.57 143.88 115.19 115.99 115.59 130.14 152.77 120.84 27.4 33.2 24 35.5 29.5 21.6 21.2 34.7 28.1 31 24.4 21.8 28.9 35.5 22.2 27.9 22.9 28.7 24.5 18.5 33.2 31.8 35.9 32.2 143.63 138.35 127.8 144.84 133.08 143.63 121.72 127.8 146.87 154.17 127.4 115.99 145.5 134.59 139.03 120.44 115.19 136.2 118.02 121.25 134.18 124.48 144.29 178.24 24.8 25.1 24.4 25.9 24.1 24.1 24.6 24 24.9 24.7 24.3 24.3 25.2 24 24.1 24.4 24 24.6 24.1 23.9 24.6 24.4 26.4 25.7 61.26 52.74 35.3 32.05 42.19 47.88 38.54 58.83 52.74 64.1 43.41 40.01 77.19 52.14 33.14 35.16 40.42 50.92 37.18 46.88 50.12 40.01 45.27 69.11 27.2 32.8 24 34.9 29.1 21.8 21.5 34 27.9

30.6 24.4 22 28.7 34.8 22.3 27.6 23 28.5 24.5 19 32.6 31.2 35.3 32 269.8 11624 42804 7749 40937 215.84 14017 37286 9345 37894 230.86 9339 35744 6486 37448 172.84 14915 34892 9943 34324 233.29 12436 39233 8291 40045 283.6 9316 40393 6211 4388 176.08 8366 32742 5811 32945 238.16 12364 38949 8740 3903 246.68 11923 40978 7949 42195 299.42 13077 49823 8718 48443 249.92 10427 37773 6952 37164 250.98 9402 3496 6268 36698 280.49 11667 51207 7972 53956 221.88 13541 35647 9405 36375 246.54 9530 36132 6353 36415 212.59 11795 32899 7863 31888 255.03 9829 33545 6553 33101 234.82 11585 45872 7917 4567 186.72 10470 27887 6980 29585 264.79 8120 36819 5413 37264 217.84 13932 3783 9288 35849 187.53 13333 34898 8889 34798 217.84 15085 38234 10057 40861 246.54 13008 49429 8889 48459 Fat Fat Fat %Fat %Fat %Fat Trunk/Limb Trunk/Limb Trunk/Limb % Fat Area (cm2) L Area (cm2) Area (cm2) Area (cm2) Android/Gyn Area (cm2) T Area (cm2) L Area (cm2) Area (cm2) L Area (cm2) Area (cm2) Area (cm2) Code Status % Fat

Gynoid Mass/Height Mass/Height Mass/Height Trunk/%Fat Trunk/%Fat Trunk/%Fat Fat Mass Fat Mass Fat Mass Android arm R arm L Ribs R Ribsoid RatioSpine Spine Pelvis Leg R leg Subtotal Head 2 (kg/m2) 2 M PP 2 F PP Legs Legs M PP Legs F PP Ratio Ratio M PP Ratio F PP DXA 33.8 Completed30 2625 841 26575 14134 13997 9917 16919 113 14363 097 6126 10985 2698 12780 42804 104 40937 11231214951 13960 27832 DXA 38.8 Completed 35.1 2337 103 23532 17311 12983 12146 14241 111 13835 09 5274 10193 21584 11858 37286 092 37894 9935 189999 12349 23532 DXA 18.4 Completed33 17527 455 18257 6711 10711 4866 12293 056 1278 1 35.3 10215 23086 12346 35744 054 37448 5080 171376 6421 25033 DXA 41.5 Completed33 21016 127 2057 21345 15133 14976 19028 124 14484 122 3205 13817 17284 16074 34892 14 34324 15119179937 18792 2337 DXA 28.7 Completed35 21584 67 21868 11261 14038 7901 13997 082 13308 072 4219 8154 23329 9486 39233 068 40045 7343 191622 9128 23207 DXA 27.8 Completed27 24384 506 24668 8504 14484 5967 14647 103

14363 094 4788 10646 2836 12385 40393 094 4388 10151209149 12617 27386 DXA 19.9 Completed 25.8 20529 483 20529 7124 9575 5166 10102 077 12172 064 3854 6537 17608 7901 32742 063 32945 5927 160057 7491 27792 DXA 34.7 Completed 39.9 21503 848 20205 11202 11969 8257 12374 087 1278 08 5883 7576 23816 9434 38949 078 3903 6593 18651 8696 24749 DXA 30.9 Completed 31.7 2479 867 26899 14571 14728 10224 12821 098 14687 096 5274 10872 24668 12648 40978 103 42195 11123207039 13826 2625 DXA 34.3 Completed 32.6 27954 104 29618 17479 17203 12264 1347 105 15417 096 641 10872 29942 12648 49823 091 48443 9827 23828 12215 25155 DXA 26.2 Completed 32.6 19556 595 21463 10000 10468 7017 10143 08 1274 071 4341 8041 24992 9354 37773 066 37164 7127 178639 8859 30348 DXA 18.3 Completed 30.6 18228 458 20289 7697 13378 5401 11478 06 11599 059 4001 6682 25098 7773 3496 058 36698 6263 17573 7785 24573 DXA 37.6 Completed 37.7 29342 917 31161 14396 10508 10303 14267 119 1455 108 7719 11576 28049 13740 51207 108 53956

10854240759 13568 26634 DXA 40.3 Completed 41.1 20774 879 22188 098 13822 086 12772 101 13459 086 5214 8784 22188 10617 35647 101 36375 9501 182439 12010 23886 DXA 21.6 Completed 26.1 19885 534 18632 8975 13216 6297 11761 083 13903 081 3314 9173 24654 10672 36132 078 36415 8423 177912 10470 25422 DXA 32 Completed 32.4 16571 576 16732 9681 11963 6792 11882 099 12044 088 3516 9966 21259 11594 32899 091 31888 9827 158755 12215 23765 DXA 19.7 Completed30 17541 48 18389 8067 11438 5660 11357 066 11519 058 4042 6569 25503 7642 33545 053 33101 5724 166434 7114 26473 DXA 33.9 Completed 31.6 28008 869 30191 13642 14509 9764 14388 107 1362 087 5092 9325 23482 11069 45872 094 4567 9447 220834 11809 26715 DXA 26.4 Completed 33.8 17662 539 18551 9059 8932 6356 11519 078 11802 064 3718 7248 18672 8432 27887 059 29585 6371 148327 7919 26149 DXA 18.9 Completed 22.6 24331 425 26311 7143 10912 5012 11599 083 12125 07 4688 7928 26479 9223 36819 068 37264 7343 190522 9128 272 DXA 28.8 Completed 37.1 23199

757 22391 12723 13378 8927 11559 077 13418 069 5012 7814 21784 9091 3783 065 35849 7019 184419 8725 24977 DXA 33.8 Completed 34.4 17864 681 18713 11445 12489 8031 13014 098 12448 095 4001 10759 18753 12516 34898 101 34798 10907166919 13557 24533 DXA 41.6 Completed 35.3 24735 119 25341 20000 16166 14033 15277 118 14429 102 4527 11552 21784 13439 38234 109 40861 11771201353 14631 25018 DXA 35.2 Completed 32.8 30231 107 30231 16797 16854 12022 12084 107 17824 096 6911 10289 24654 12214 49429 097 48459 9749 236677 12186 24411 Est. VAT Appen. Appen. Appen. Est. VAT Area (cm2) Est. L VAT Area (cm2) Lean/Height2 Area (cm2) Lean/Height2 Area (cm2) Lean/Height2 Area (cm2) T Area (cm2) L Area (cm2) Area (cm2) L Code Status Volume Lean/Height2 Lean/Height2 Lean/Height2 Mass (g) armArea (cm2) R arm (kg/m2)L Ribs (kg/m2) M R PPRibs (kg/m2) F PP Spine Spine Pelvis Leg (cm3) (kg/m2) (kg/m2) M PP (kg/m2) F PP DXA 515 Completed 557 262.5 107 26575 215 13997 11328 16919 13782 14363 961 6126 10834 2698

14112 42804 DXA 553 Completed 598 233.7 115 23532 204 12983 10748 14241 13077 13835 923 5274 10406 21584 13554 37286 DXA 218 Completed 236 175.27 453 18257 137 10711 6990 12293 8546 1278 577 353 6397 23086 8362 35744 DXA 491 Completed 531 210.16 102 2057 229 15133 12065 19028 14679 14484 103 3205 11612 17284 15125 34892 DXA 199 Completed 216 215.84 414 21868 154 14038 8114 13997 9872 13308 681 4219 7678 23329 10000 39233 DXA 275 Completed 297 243.84 57 24668 172 14484 9062 14647 11026 14363 799 4788 9008 2836 11733 40393 DXA 226 Completed 244 205.29 468 20529 169 9575 8622 10102 10543 12172 738 3854 8182 17608 10696 32742 DXA 290 Completed 314 215.03 602 20205 155 11969 7735 12374 9509 1278 678 5883 7434 23816 9755 38949 DXA 373 Completed 403 247.9 774 26899 215 14728 11328 12821 13782 14687 955 5274 10767 24668 14023 40978 DXA 492 Completed 531 279.54 102 29618 225 17203 11855 1347 14423 15417 107 641 12063 29942 15712 49823 DXA 206 Completed 222 195.56 427 21463 176 10468 9273 10143

11282 1274 802 4341 9042 24992 11777 37773 DXA 189 Completed 205 182.28 393 20289 155 13378 8166 11478 9936 11599 659 4001 7430 25098 9677 3496 DXA 486 Completed 525 293.42 101 31161 218 10508 11289 14267 13771 1455 103 7719 11521 28049 15015 51207 DXA 402 Completed 435 207.74 835 22188 157 13822 8010 12772 9794 13459 644 5214 7140 22188 9333 35647 DXA 173 Completed 187 198.85 358 18632 177 13216 9326 11761 11346 13903 808 3314 9109 24654 11865 36132 DXA 187 Completed 202 165.71 387 16732 143 11963 7534 11882 9167 12044 635 3516 7159 21259 9325 32899 DXA 162 Completed 175 175.41 337 18389 153 11438 8061 11357 9808 11519 695 4042 7835 25503 10206 33545 DXA 333 Completed 359 280.08 69 30191 21 14509 10875 14388 13266 1362 962 5092 10761 23482 14023 45872 DXA 132 Completed 143 176.62 274 18551 159 8932 8377 11519 10192 11802 718 3718 8095 18672 10543 27887 DXA 316 Completed 341 243.31 655 26311 173 10912 9115 11599 11090 12125 799 4688 9008 26479 11733 36819 DXA 262 Completed 283 231.99

544 22391 15 13378 7903 11559 9615 13418 626 5012 7057 21784 9192 3783 DXA 289 Completed 313 178.64 60 18713 143 12489 7534 13014 9167 12448 61 4001 6877 18753 8957 34898 DXA 694 Completed 751 247.35 144 25341 21 16166 11064 15277 13462 14429 961 4527 10834 21784 14112 38234 DXA 657 Completed 710 302.31 136 30231 22 16854 11393 12084 13898 17824 101 6911 11298 24654 14723 49429 66 Area (cm2) Subtotal Are H 2149.51 1899.99 1713.76 1799.37 1916.22 2091.49 1600.57 1865.1 2070.39 2382.8 1786.39 1757.3 2407.59 1824.39 1779.12 1587.55 1664.34 2208.34 1483.27 1905.22 1844.19 1669.19 2013.53 2366.77 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 2 2 Area (cm2) Total 2427.83 2135.31 1964.09 2033.07 2148.29 2365.35 1878.49 2112.59 2332.89 2634.35 2089.87 2003.03 2673.93 2063.25 2033.34 1825.19 1929.06 2475.49 1744.77 2177.22 2093.96 1914.51 2263.71 2610.89 Area (cm2) R leg 409.37 378.94 374.48 343.24 400.45 43.88 329.45 390.3 421.95 484.43 371.64 366.98 539.56 363.75 364.15 318.88 331.01

456.7 295.85 372.64 358.49 347.98 408.61 484.59 A Appendix B Institutional Review Board Approval: 67 Appendix C Informed Consent Statement Form: Appalachian State University Informed Consent for Participants in Research Projects Involving Human Subjects Title of Project: IRB Study #: Estimation of body composition via air displacement plethysmography using measured and predicted thoracic gas volumes in normal weight and obese adults 18-0355 Principal Investigator: Jonathon Stickford, Ph.D Research Assistants: Jayvaughn Oliver, B.S Erica Larson, M.S Dalton Fletcher, B.S John Cantu, B.S Email: stickfordjl@appstate.edu Email: oliverjt@appstate.edu Email: larsone@appstate.edu Email: fletcherds@appstate.edu Email: cantujw@appstate.edu This is to certify that I, have been given the following information with respect to my participation as a volunteer in a program of investigation under the supervision of Jonathon Stickford, Ph.D to which Jayvaughn Oliver, B.S, Erica

Larson, MS, Dalton Fletcher BS, and John Cantu may be assisting 1. Purpose of the study: Obesity has become a large issue in the US. Obesity-related conditions are the second leading cause of preventable death. Understanding more about obesity is important for the effective treatment of over 78 million people in the US. The main objective of this study is to investigate the measurement of body fat in an obese population using measured versus predicted values of lung volumes in the Bod Pod. The measurements will be compared to values of body fat using DXA The results from this study could provide further insight on how these measures may agree in an obese population. 2. Inclusion Criteria: You may participate in the study if the following apply to you:  Age: 18 – 45 years of age. The reason for the upper cut-off being that older adults are more likely to present with physical differences that could affect the outcomes of some measurements. 68  BMI between 18.5 and 249, or

between 30 and 40  Must be a non-smoker or smoked less than half a pack of cigarettes a day over the course of a year.  Have no known lung, heart, kidney disease or energy limitations, or exhibit any signs or symptoms of lung, heart, and kidney disease or energy limitations.  Interested in participating in the research study.  Understand written and oral instructions in English.  Provide informed consent.  Available during times the data collection are offered. Exclusion Criteria: You should not participate in this study if any of the following apply to you:  BMI between 25 and 29.9  Current smoker or previously smoked more than half a pack of cigarettes a day over the course of a year  Known lung, heart, kidney disease or energy limitation, or signs/symptoms suggestive of known lung, heart, kidney disease or energy limitation will exclude you from participation.  Pregnant  Unable to understand written and oral instructions in English. 3. Procedures:

Please read the descriptions of each step in the experiment and write your initials in the space provided. You could be asked to repeat a trial, procedure, or test. This could happen for many reasons such as equipment failure, power outage, inconclusive test results, etc. However, you do not have to repeat a trial, procedure, and/or test if you do not wish to do so. Below is a timeline showing all visits and experiments which you will complete in this study. Pre-Screen Visit 1 Screening Question (~10 minutes) Informed Consent & Questionnaires (~40 minutes) Bod Pod ( ~15 minutes) DXA ( ~15 minutes) 69 initial Prescreen: You may be telephoned by the Principle Investigator or a Research Assistant (see page 1) and asked screening questions to determine your eligibility for the study (~10 minutes). Visit 1: Initial Consent and Questionnaires: Potential participants who meet inclusion criteria will be invited to a screening interview within the laboratory

located off campus (Levine Hall). At this screening visit, the study will be explained in detail to you by the PI or a trained research assistant. You will have time to consider your options and get all questions answered - if you agree to participate, you will then provide your written informed consent. After you have provided consent (~15 minutes), you will be asked to complete questionnaires: 1) a medical history questionnaire (~15 minutes), and 2) a 24 hour health history questionnaire (~10 minutes). initial Bod Pod: After completing the questionnaires, we will measure your height, weight, and body composition. Your percent body fat will be measured using the Bod Pod. You will sit in a chamber and may hear some clicking while air pressure changes to measure your body volume. This piece of equipment estimates your body’s composition of fat and fat free mass by air movement. This is accomplished by measuring your mass and body volume which is then us to calculate fat mass

and fat free mass. This is an extremely accurate method and presents no risk. These procedures will take ~15 minutes total initial DXA: A DXA is a type of X-ray used to measure bone strength. During this test, X-ray pictures of your body will measure how much fat and muscle are present. You will lie flat on a table and a machine will take pictures of different areas of the body. This test will last about 15 minutes. 3. Discomforts and risks: There are minimal risks involved with measuring/monitoring/performing: questionnaires, physical characteristics, and body composition. DXA: The risks associated with a DXA scan include exposure to small amounts of radiation. DXA scanning uses radiation to obtain an image of your body. Everyone receives a small amount of unavoidable radiation from the environment each year. Some of this radiation comes from space and some from naturally-occurring forms of radioactive water and minerals. The DXA scan technique gives your body the equivalent

of about 4 extra days’ worth of this natural radiation. The radiation dose we have discussed is what you will receive from this study only and does not include any exposure you may have received or will receive from other tests. If you are pregnant or trying to get pregnant, you should not participate in a DXA scan 70 Loss of Confidentiality: Any time information is collected; there is a potential risk for loss of confidentiality. Every effort will be made to keep your information confidential; however, this cannot be guaranteed. Other Risks: There may possibly be other side effects that are unknown at this time. If you are concerned about other, unknown side effects, please discuss this with the researchers. How you can help reduce some of the risks: During your participation in this research, the researchers will closely observe your testing to determine whether there are problems that need medical care. It is your responsibility to do the following: • Ask questions about

anything you do not understand. • Keep appointments. • Follow the study researchers’ instructions. • Let the researchers know if your telephone number changes. • Tell the researchers before you take any new medication. • Tell your regular doctor about your participation in this research. • Talk to a family member or friend about your participation in this research. 4. a Benefits to me: You will receive a copy of your body composition These screenings are being performed only for research purposes and are not to be understood as a clinical screening intended for diagnostic or therapeutic purposes. The screening data will not be read for any health care or diagnostic purpose. Under no circumstance will the investigator, research staff or other University employee interpret your screening as normal or abnormal and they are unable to make any medical comments or interpretations based on your results. Please contact your health care provider if you have any questions regarding

this data. b. Potential benefits to society: The results of this study could alter the standard protocols used to measure body fat % using a Bod Pod. 5. Alternative procedures that could be utilized: Not participating in the study The procedures used in this study are frequently used in research and are the most appropriate methods to accomplish the goals of this research. 6. Time duration of the procedures and study: initial Pre-screening (about 10-15 min). You will need to visit the laboratory for the following: initial Visit 1 (about 1.5 hours) Approximately 2 hours Total 7. Statement of confidentiality: Volunteers are coded by an identification number for statistical analyses. All records are kept in a secure location All records associated with your participation in the study will be subject to the university confidentiality standards and in the event of any publication resulting from the research no personally identifiable information will be disclosed. The

Office of Human Research Protections in the US Department of Health and Human Services, the Office for Research Protections at 71 Appalachian State University and the Institutional Review Board may review records related to this project. 8. Right to ask questions: Please contact Jonathon Stickford, PhD (828-262-7471), with questions, complaints, or concerns about this research. If you have any questions about your rights as a research subject, please contact the IRB Administrator at the Appalachian State University Institutional Review Board Office at (828) 262-2692, irb@appstate.edu This study has been approved on February 23, 2019 by the Institutional Review Board (IRB) at Appalachian State University. This approval will expire on February 22, 2020 unless the IRB renews the approval of this research. 9. Injury Clause: In the unlikely event you become injured as a result of your participation in this study, standard emergency procedures will be followed. If you get hurt or sick

when you are not at the research site, you should call your doctor or call 911 in an emergency. If your illness or injury could be related to the research, tell the doctors or emergency room staff about the research study, the name of the Principal Investigator, and provide a copy of this consent form if possible. Please call the PI as soon as possible (Jonathon Stickford, Ph.D 828-262-7471) It is the policy of this institution to provide neither financial compensation nor free medical treatment for research-related injury. You will be responsible for any costs for medical care not paid by your insurance company. No other compensation is offered by Appalachian State University By signing this document, you are not waiving any legal rights that you have against Appalachian State University for injury resulting from negligence of the University or its investigators. 10. Voluntary participation: Your participation in this study is voluntary You may withdraw from this study at any time by

informing the research personnel. You may decline to answer certain questions and may decide not to comply with certain procedures. However, your being in the study may be contingent upon answering these questions or complying with the procedures. The researcher may end your role in the study without your consent if the researcher deems that your health or behavior adversely affects the study or increases risks to you beyond those approved by the Institutional Review Board and agreed upon by you in this document. You have been given an opportunity to ask any questions you may have, and all such questions or inquiries have been answered to your satisfaction. You must be 18 years of age or older to take part in this research study. If you agree to take part in this research study and have read the information outlined above, please sign your name and indicate the date below. You will be given a copy of this signed and dated consent form for your records.

Volunteer Date I, the undersigned, have defined and explained the studies involved to the above volunteer. 72 Person Obtaining Consent Date 73 Appendix D Telephone Screening Form: Initial Telephone Screening Form for Study VTG VTG We are conducting a study to examine the effect of lung volumes on measurements of body composition. We will do a series of measurements using the Bod Pod and DXA where we will analyze resultant measures of body composition. Effort for each of these tasks will be minimal. This screening is meant to determine if you are eligible to participate in the study. Basic demographic information will be asked along with a brief health history. If you choose not to participate, or do not qualify for the study, all of this information will be shredded. Are you interested in about learning more and potentially participating in this study? Great! Well to begin I would like to ask you some general

Information: What is your name, age, and year or birth? What Gender do you identify as? May I have your contact information to reach you when necessary, like your email and phone number? To the best of your knowledge what is your height and weight? Do you have any allergies to latex? Do you currently smoke tobacco or electronic cigarettes? Have you ever been diagnosed with a sleep disorder or use CPAP? Do you have a history of asthma, COPD, or any lung issues? Do you have a history of an irregular heartbeat or any heart condition? (Have you had an EKG performed?) Do you have any known health conditions? 74 High blood pressure? Diabetes? Thyroid issues? Are you pregnant? Thank you for taking the time to complete this screening questionnaire. Based on the information that you have provided we would like to invite you to the lab to potentially participate in this study. Upon arrival, you will be provide with further details of the study, and provided your consent we will continue to

move forward. Thank you for your time. Based on the information you have provided, you do not qualify for this study. I am sorry about this, but I encourage you to continue pursuing research. Thank you for your time and have a great day. 75 Appendix E Medical History Form: Appalachian State University – Integrative Human Physiology Laboratories 251 Industrial Park Dr. Boone, NC 28607 P h o n e : (828)262-7471 ASU Medical History Form Page 1 Study: Subject ID#: Highest Education Achieved: Ethnicity: Hispanic or Latino. A person of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin, regardless of race. The term "Spanish origin" can be used in addition to "Hispanic or Latino" Not Hispanic or Latino. Race: What race do you consider yourself to be? American Indian or Alaska Native. A person having origins in any of the original peoples of North, South, or Central America, and who maintains a tribal affiliation or

community attachment. Asian. A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. (Note: Individuals from the Phillippine Islands have been recorded as Pacific Islanders in previous data collection strategies.) Black or African American. A person having origins in any of the black racial groups of Africa Terms such as "Haitian" or "Negro" can be used in addition to "Black" or "African American". Native Hawaiian or Pacific Islander. A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific islands. White. A person having origins in any of the original peoples of Europe, the Middle East, or North Africa Check here if you do not wish to disclose any or all of the above information. Medications: include over the counter

drugs/oral contraceptives/dietary supplements Name/Dosage/How often taken: Allergies: Smoking History: Do you smoke? Yes No # packs per day Cigarettes? Pipe / Cigar? for Other? # of years Have you ever been exposed to second hand smoke? If you quit, what year did you quit What year did you start smoking? Home Work Other Alcohol Consumption History: Do you currently drink alcohol? If you drank alcohol previously, when did you stop? If you ever did drink alcohol, what is (was) the volume consumed? # ounces / day for # of years 76 Years ASU Medical History Form Page 2 Medical History: NO YES Please explain any "YES" answers below: high blood pressure swelling chest pain / history of heart attack extra heart beats, racing or fluttering abnormal electrocardiogram (ECG) other heart trouble (e.g murmur, valve problems) high cholesterol diabetes (e.g frequent urination and abnormal thirst) seizures stroke fainting or black-out spells, dizziness anxiety

(diagnosed) depression (diagnosed) recurrent fatigue (e.g feeling tired or extreme lack of energy) insomnia or poor sleeping thyroid problems difficulty breathing emphysema/ asthma/ chronic bronchitis cough, sputum (phlegm) tuberculosis chronic infection stomach/GI problems (e.g heart burn, nausea, vomiting, diarrhea, constipation, abdominal pain, gas pain, black stools, blood in stools) hepatitis bleeding disorder (e.g bleeding or bruising easily) kidney/ urinary problems (e.g frequent urination, burning when urinating, urine changing in color) joint injuries/ joint pain, back pain, or leg pain arthritis (rheumatoid or osteoarthritis) hearing problems (e.g impaired hearing or ringing in the ears) migraine headaches vision problems (exclude corrected near/far sightedness) surgical procedures (e.g c-sections, appendectomy, augmentations, knee and back surgeries, tonscillectomy, etc) Additional Notes: 77 ASU Medical History Form Page 3 Exercise History: Do you currently exercise

aerobically? Do you compete in endurance events? Any other types of exercise? If you are currently sedentary, when did you last exercise? Weight History: If overweight, how long have you been overweight? How many years? Types of Exercise: How many years? Duration: Frequency: Frequency: What events? How many years? Types of Exercise: How many years? Athlete in college? Yes No Duration: Frequency: Duration: Types of Exercise: Frequency: Were you overweight as a child? By how much? How many times has your weight changed? Any events that led up to your obesity? (E.g Pregnancy, injury) Yes No If yes, how may events? 1 2 3 4 5 >5 Sleep History: Have you ever been diagnosed with a sleep disorder? Yes No Do you use CPAP/BIPAP at night? Yes No Do you snore at night? Yes No Has someone ever told you that you snore at night? Yes No Do you have daytime sleepiness? Women Only: Yes No Menstrual history: Age begin □ Yes Regular? □ No □ Heavy □ Medium □

Light If your periods are irregular or associated with excessive bleeding or unusual discharge please elaborate: Number of days between periods: days Usual duration of period: days At what age did menopause occur, if applicable? Number of pregnancies? Are you currently Pregnant? Number of births? Explain any complications with pregnancy: Authorization to Release Information - Please check all that applies and sign/date. I authorize Appalachian State University to collect and save the above protected health information on me for purposes of research. I understand that all information is private and confidential I authorize Appalachian State University to keep this information and any information gained from my participation in their studies in a database so that they may contact me. The above information is correct and complete to the best of my knowledge. Signature Date 78 Appendix F 24-hour Health History Form: 24-HOUR HEALTH HISTORY Study: VTG YOB:

Height: Subject Number: Do you have: Head cold Nasal Congestion Headache Sore Throat Digestive Upset Intestinal Disorder General Fatigue Muscle Soreness Yes         Medicine taken in last 24 hours: No         Weight: Date: How do you feel? # of hours sleep Good How was your sleep? Fair Normal Not so good Wakeful Bad Restless Any leg cramps Since last activity? Physical activity in last 24 hours: Yes  No  Sex: # of hours since eating: What did you eat?

* Take weight with each visit. 79 Any unusual physical activity in last 24 hours? 24-HOUR HEALTH HISTORY Study: VTG YOB: Height: Subject Number: Do you have: Head cold Nasal Congestion Headache Sore Throat Digestive Upset Intestinal Disorder General Fatigue Muscle Soreness Yes         Medicine taken in last 24 hours: No         Weight: Date: How do you feel? # of hours sleep Good How was your sleep? Fair Normal Not so good Wakeful Bad Restless Any leg cramps Since last activity? Physical activity in last 24 hours: Yes  No  Sex:

# of hours since eating: What did you eat? * Take weight with each visit. Last Menstrual Period (LMP): (1st Day of LMP) 80 Any unusual physical activity in last 24 hours? Vita Jayvaughn Trujillo-Oliver was born in Longmont, Colorado, to Ricky Oliver and Stephanie Trujillo. He graduated from Athens Drive High school in August 2013 The following autumn, he was accepted to Appalachian State University to study Exercise Science. In May 2017, he was awarded a Bachelor of Exercise Science Degree For the next 2

years he worked under Dr. Jonathon Stickford as a graduate research assistant studying for his Masters of Exercise Science. The Masters of Exercise Science degree was awarded to him in December 2019. Mr. Oliver continues to follow his passion to serve underserved communities and is now striving to become a Doctor of Osteopathic Medicine. He resides in Clayton, NC, where he is actively pursuing his passion. 81