VALIDITY AND RELIABILITY OF BODY COMPOSITION TECHNIQUES IN HEALTHY ADULTS

Transcription

1 VALIDITY AND RELIABILITY OF BODY COMPOSITION TECHNIQUES IN HEALTHY ADULTS A^> 3<o KiMET HGG A thesis submitted to the faculty of San Francisco State University In partial fulfillment of The requirements for The Degree Master of Science In Kinesiology: Exercise Physiology by Kelly Mae Hood San Francisco, California August 2016

2 Copyright by Kelly Mae Hood 2016

3 CERTIFICATION OF APPROVAL I certify that I have read Validity and Reliability o f Body Composition Techniques in Healthy Adults by Kelly Mae Hood, and that in my opinion this work meets the criteria for approving a thesis submitted in partial fulfillment of the requirement for the degree Master of Science in Kinesiology: Exercise Physiology at San Francisco State University. lam hce Kern, Ph.D. Professor of Kinesiology/Department Chair C. Matthew Lee, Ph.D. Professor of Kinesiology/Associate Chair James W. BagLey; Ph.D. Assistant Professor of Kinesiology

4 VALIDITY AND RELIABILITY OF BODY COMPOSITION TECHNIQUES IN HEALTHY ADULTS Kelly Mae Hood San Francisco, California 2016 The purpose of this investigation was to assess the day-to-day and week-to-week reliability of body fat (BF%) measurements using three different methods [air displacement plethysmography (Bod Pod), bioelectrical impedance analysis (Fitbit Aria ), and hydrostatic weighing (HW)] in the San Francisco State University Exercise Physiology Laboratory. Additionally, the validity of BF% measurements using the Bod Pod and Fitbit Aria were compared to the industry gold standard of HW. Twenty-two males and 21 females (age: 27.9 ± 5.6 years) participated in the three-day investigation. Each day, participants completed BF% measurements via Bod Pod, Aria scale [ Lean (A l) and Regular (A r) modes], and HW. The Bod Pod was found to be a valid method for measuring BF% in all participants (0.4±4.3%; SEE=2.2%); however when analyzed by sex, it was valid for females (-0.3±4.0%; SEE=2.0%) but significantly over estimated males (1.0±4.3%; SEE=2.2%). A r agreed with HW when analyzing BF% for all participants (-0.8±9.3%; SEE=4.4%) and females (0.4±10.8%; SEE=4.4%), but significantly underestimated males (-2.0±7.1%; SEE=3.7%). Al underestimated BF% by -5±9.1% (SEE=4.2%) for all participants (males: -7.9±6.9%; females: -2.6±8.0%; p<0.05), and this discrepancy was more pronounced in males. Overall, the mode chosen on the Aria1' scale greatly impacts validity of female participants, but was not valid for males using A l or A r. All methods were reliable when comparing day-to-day and week-to-week BF% measurements for all groups, suggesting the Fitbit Aria can be a reliable at-home body composition analysis scale. ertiiy that the Abstract is a correct representation of the content of this thesis. Date

5 ACKNOWLEDGEMENTS I would like to thank Dr. Marialice Kern, Dr. Matthew Lee, and Dr. James Bagley for their support and assistance in completing this thesis. Special thank you to my family, Terri, Alissa, and Erin, for their endless love and encouragement. To Morgan, thank you for your tech support, editing, and always believing in me. This thesis is dedicated to my father, Samuel Robert Hood II, for inspiring and teaching me to work hard and carry passion into everything I pursue. v

6 TABLE OF CONTENTS List of Tables...vii List of Figures... viii List of Appendices... ix Introduction...1 Method...3 Subjects...3 Design and Procedures... 4 Air Displacement Plethysmography...5 Bioelectrical Impedance Analysis...6 Hydrostatic Weighing...6 Statistical Analysis...7 Results...9 Physical Characteristics...9 Load Cell vs. Mechanical Scale Validity of Body Composition Measurements...10 Bod Pod Comparison...17 Reliability...20 Discussion References Appendices... 37

7 LIST OF TABLES Table Page 1. Physical Characteristics of All Participants Physical Characteristics of Participants by Sex Comparison of Body Fat Measurements from the Load Cell and the Mechanical Scale in Hydrostatic Weighing Validity of Body Composition Measurements using Hydrostatic Weighing (Load Cell as Validity Criterion) Comparison of Aria Body Composition Measurements to the Bod P o d Day-to-day Reliability of Total Body Water Measurements Week-to-week Reliability of Total Body Water Measurements Day-to-day Reliability of Body Composition Measurements Week-to-week Reliability of Body Composition Measurements... 22

8 LIST OF FIGURES Figures Page 1. Body Composition Methods Bland-Altman Plots with All Participants Bland-Altman Plots for Male and Female Participants Bland-Altman Plots Comparing A r Measurements for Males with <20% and >20% Body Fat Bland-Altman Plots Comparing A r Measurements for Females with <24% and >24% Body Fat Bland-Altman Plots Comparing Al Measurements for Males with <20% and >20% Body Fat Bland-Altman Plots Comparing Al Measurements for Females with <24% and >24% Body Fat Bland-Altman Plots for All Participants (Aria v. Bod Pod) Bland-Altman Plots for Male and Female Participants (Aria v. Bod Pod)... 19

9 LIST OF APPENDICES Appendix 1. Review of Literature Preparticipation Questionnaire

10 1 INTRODUCTION Evaluations of body fat percent and fat-free mass are necessary for monitoring obesity classification, training outcomes, and general health.1excess adipose tissue in obese individuals has been shown to have deleterious effects on multiple organ systems and is associated with increased risks of cardiovascular disease, diabetes mellitus, hypertension, and dyslipidemia.1,2 It follows that reducing excess body fat can decrease an individual s risk for chronic disease. Because estimations of body fat are used to quantify an individual s health risk, as well as identify weight loss intervention progress, 1 # it is important that they are accurate. Body composition is also useful for athletic trainers to create, optimize, and evaluate training programs, as well as for sports nutrition experts to develop individualized dietary interventions.4,5 In addition, analysis of body composition is also in the interest of endurance athletes, such as triathletes and marathoners, since a relatively low body fat percentage is desirable to optimize physical performance in these sports.6'9 Understanding the reliability of body composition measurements is essential for tracking the effectiveness of an intervention strategy or attaining optimal body composition for athletic performance. Because of its importance, many individuals purchase body composition measurement services at a local gym or exercise physiology laboratory. When providing health and fitness services, the ability to accurately and reliably measure body composition is vital. The Exercise Physiology Laboratory at San Francisco State University (SFSU) offers body composition testing using skin fold measurements,

11 2 hydrostatic weighing, and air displacement plethysmography via the Bod Pod. Between March 2015 and February 2016, 180 body composition measurement services were paid for and conducted in the lab. Out of those body composition measurements taken, 75% were performed using the Bod Pod. With a high volume of clients relying on the Bod Pod for body composition measurements, it is important to know the accuracy and validity of the machine; yet this has not been evaluated within the past 10 years. The lab has also installed a new load cell for measuring body weight in the hydrostatic tank, which has not yet been tested for validity or reliability. In addition, with the rise of home health electronics, many clients own a bioelectrical impedance analysis (BIA) scale, such as the Fitbit Aria, to monitor progress at home.10 Currently, no research exists evaluating the accuracy and reliability of the Aria scale compared to industry gold standards. The purpose of this investigation is threefold: (a) to assess the day-to-day and week-to-week reliability of body fat measurements using three different methods - air displacement plethysmography, BIA via the Fitbit Aria, and two measurements of hydrostatic weighing - in the SFSU Exercise Physiology Laboratory; (b) to evaluate the validity of body fat measurements using air displacement plethysmography and the Fitbit Aria compared to the industry gold standard of hydrostatic weighing using a load cell; (c) to compare hydrostatic weighing measurements of body fat percentage using both a mechanical scale and load cell.

12 3 METHODS Subjects Forty-seven healthy men (n = 24) and women (n = 23) aged volunteered to participate in this study. Subjects were recruited through personal contacts of the primary investigator and from classes in the Department of Kinesiology. All participants were classified as low-risk by the American College of Sports Medicine risk stratification system." Exclusion criteria included pregnancy, claustrophobia, and the use of medications that influenced hydration. Data from 22 males and 21 females were used in the final analysis. One male was disqualified due to inability to record a measured reading of Thoracic Gas Volume (V jg ) during testing in the BOD POD Body Composition System (Bod Pod). One female was disqualified due to an error with the Aria scale readings on the second laboratory visit. Additionally, one male and one female were disqualified for not following the pretest instructions prior to their third laboratory visit. Subjects were asked to list the ethnic group with which they most identified on a questionnaire. The subjects classified themselves as 63% Caucasian, 32% Asian, and 5% Hispanic. Some subjects had participated in class laboratory testing sessions that included hydrostatic weighing, whereas others had never performed a hydrostatic weighing assessment. The study was approved by the San Francisco State University Institutional Review Board for Human Subjects, and a written informed consent was obtained from each subject prior to testing.

13 4 Design and Procedures Using a repeated measures design, all participants reported to the Exercise Physiology Laboratory at the SFSU campus at the same time of day for three separate visits. The testing days were scheduled with visit two taking place 24 hours after visit one, and a third visit a week following either the first or second visit. Female participants were scheduled to start the first day of testing between days five and eleven of their menstrual cycle to avoid potential problems with water retention that can occur during the menstrual cycle.12 Each subject was asked to comply with the following pre-test instructions: no eating or drinking for three hours prior to testing, emptying bladder and bowels within 30 minutes of testing, no alcohol for 24 hours prior to testing, and no strenuous exercise at least 12 hours prior to testing. Female participants wore swimsuits or spandex shorts and sports bras. Male participants wore Speedo swimsuits, Lycra bike shorts (no padding), or boxer briefs. Each participant wore the same style of clothing for all three visits and for all body composition testing. During visit one, height was measured to the nearest centimeter on a wallmounted stadiometer (Seca 216 Mechanical Stadiometer, Seca Inc., Chino, CA, USA). Each subject was weighted wearing approved testing attire using a calibrated digital scale (BOD POD: Life Measurement, Inc., Concord, CA, USA) measured to the nearest kilogram. Residual volume (RV) was determined with the subject in a seated position using the oxygen dilution method of Wilmore via a metabolic cart (True One 2400, Parvo-Medics, Inc., Provo, UT, USA).13 Subjects completed a minimum of three trials

14 5 and the average of the closest two trials within 5% was used to represent RV. Hydration status, or total body water, was measured using 4-lead bioelectrical spectroscopy device (ImpediMed SFB7, ImpediMed Inc., Carlsbad, CA, USA). Body composition was measured in the order of Bodpod, Fitbit Aria, and hydrostatic weighing (Figure 1). For both the second and third visits, only weight, hydration status, and body composition were measured. Air Displacement Plethysmography Prior to each day of testing, the Bod Pod was warmed up, calibrated, and all quality checks were performed. Before each participant was tested, another two-point calibration was performed. While wearing approved attire, the subject was weighted on the calibrated Bod Pod scale. The participant was then given a swim cap to wear and asked to sit in the Bod Pod chamber for body volume measurement. The specific details of the Bod Pod procedures have been previously reported by Dempster et al.14 Once the volume measurements were complete, the subject was instructed on how to perform the proper breathing technique to measure V tg- The procedure for measuring V tg was repeated if the Bod Pod deemed the initial measurement unsatisfactory. The subject was given seven attempts at achieving a measured value for V tg- If the subject was unable to achieve a measured V tg, a predicted value was taken and the data from that subject was not used in final analysis. Once the test was complete, the Bod Pod software automatically calculated the body composition using the Siri equation.15 Siri Equation: Body Fat Percent = (4.95/Body Density) x 4.5

15 6 Bioelectrical Impedance Analysis The subject s height in feet and inches, weight in pounds, birth date, and sex were entered into an online Fitbit account synced with the Aria scale (Fitbit Inc., San Francisco, CA, USA). As published by the Fitbit Aria Instruction Manual, the subject was asked to stand on the scale with both feet completely on the scale surface, and weight evenly distributed. The subject was instructed not to move during the measurement until the percent body fat was displayed on the scale. The Aria has both a lean and regular mode. According to the Instruction Manual, the lean mode is intended for professional or high-level athletes, such as marathon runners or body builders, or individuals with very low body fat relative to their muscle mass.10 All participants were tested using both scale modes. For each mode, three body fat measurements were recorded and the average was used to represent scale body composition. The Aria uses proprietary equations to calculate the percent body fat for each mode and does not displace the impedance resistance values so the equations cannot be computed. Hydrostatic Weighing Underwater weight (UWW) was measured in a submersion tank in which a chair was suspended from a load cell in-line with a mechanical scale (Figure 1). A minimum of three trials were performed until an underwater weight plateau was observed. The primary investigator performed all UUW measurements for all three days. A damping technique, as previously described, was performed to reduce the size of mechanical scale arm oscillations.16 The UWW was calculated as the average of the heaviest three trials for

16 7 both the load cell and the mechanical scale. With both the chair and sinker attached, the load cell (Omega IN-USBH, Omega Engineering Inc., Stamford, CT, USA) was calibrated to zero using a two-point calibration with a 4.5 kilogram weight. Load cell output was converted to kilograms using a predetermined calibration equation in the Omega transducer software installed on a laboratory computer. UWW was simultaneously measured using the mechanical scale and load cell. Three load cell data points from each trial were recorded and averaged. Chair and sinker weight was recorded to subtract from the mechanical scale measurements. Water temperature was recorded to determine water density. Body volume was calculated by: Body Volume = (Dry weight - UWW) - RV (16) Water density Body density was calculated by dividing dry mass by body volume. Body fat percentage was calculated using the Siri equation.15 Statistical Analysis All statistical analysis was performed with IBM SPSS Statistics (version 24, SPSS Inc., Chicago, IL, USA). Bland-Altman plots were used to determine the 95% levels of agreement and mean bias among the Bod Pod, Aria in both lean and regular modes, and hydrostatic weighing using the load cell. The 95% levels of agreement are presented as +/ standard deviations. Pearson s correlation and standard error of estimate (SEE) were also determined for all methods compared to hydrostatic weighing. Load cell and mechanical scale measurements were compared using Pearson s correlation

17 8 coefficient. Intraclass correlation coefficients were used to compare measurement reliability between days and between weeks. Figure 1. Body composition methods located in the San Francisco State University Exercise Physiology Laboratory. Pictured from left to right: Bod Pod, Fitbit Aria, and Hydrostatic tank with mechanical scale and load cell.

18 9 RESULTS Physical Characteristics A total of 43 participants completed all aspects of the study. Physical characteristics of the participants can be found in Table 1 and 2. The majority of participants, 70% respectively, were aged years; the remaining 30% were aged between years. The average body mass index (BMI) for females fell within what is considered a normal range ( kg/m2), whereas male subjects fell within a range categorized as overweight ( kg/m2) (Table 2). Table 1. Physical Characteristics of All Participants All Participants (n=43) Mean ± SD Range Age (yr) 27.9 ± Height (cm) ± Mass (kg) 68.9 ± BMI (kg/m2) 23.7 ± RV (L) 1.2 ± Table 2. Physical Characteristics of Participants by Sex Female (n=21) Male (n=22) Mean ± SD Range Mean ± SD Range Age (yr) 28.2 ± ± Height (cm) ± ± Mass (kg) 59.5 ± ± BMI (kg/m2) 21.8 ± ± RV (L) 1.2 ± ±

19 10 Load Cell vs. Mechanical Scale Comparison of body fat percentage (BF%) measurements from the load cell (H W lc) and the mechanical scale (H W ms) used for hydrostatic weighting are presented in Table 3. All participants, females, and males had a Pearson s correlation of r =1.0, with standard error of estimate (SEE) of 0.2% between H W Lc and H W ms- Table 3. Comparison of Body Fat Measurements from the Load Cell and the Mechanical Scale in Hydrostatic Weighing Participants Load C ell Mechanical Scale ^ Pearson's Correlation (r) Standard Error of Estimate (%) All 22.3 ± ± Female 23.9 ± ± Male 20.8 ± ± \ / Values are given as mean ± SD of body fat (%) Validity o f Body Composition Measurements Bland-Altman plots (Mean Bias ± Limits of Agreement) comparing the Bod Pod and Fitbit Aria, in both lean (A l) and regular (A r) modes, to the validity criterion H W Lc during day one for all trials and for all participants are presented in Figure 2 and Table 4. Bland-Altman Plots comparing male and female participants separately are presented in Figure 3. The Bod Pod BF% measurements agreed with H W lc for all participants (0.4±4.3%; p=0.24) and females (-0.3±4.0%; p=0.56). The Bod Pod overestimated BF% by 1.0±4.3% for males (p<0.05) (Table 4). The A r BF% measurements agreed with HWlc for all participants (-0.8±9.3%; p=0.27) and females (0.4±10.8%; p=0.73), but

20 11 underestimated males by -2.0±7.1% (p<0.05) (Table 4). The Al significantly underestimated BF% for all participants (-5.3±9.1%), males (-7.9±6.9%), and females (-2.6± 8.0%) with p<0.05 (Table 4). The SEE and Pearson s Correlation coefficient for BF% are presented for each comparison in Table 4. Additionally, linear regressions revealed no significant Bland-Altman trends for any of the methods or groups (p>0.05). Based on H W lc measurements, male and female participants were further categorized into high and low BF% groups based on the median BF% for each sex. For males, low BF% was < 20% and high was > 20%. For female participants, low BF% was < 24% and high BF% was > 24%. Bland-Altman plots comparing A r and A l to the validity criterion H W lc during day one for male participants categorized by low and high BF% are presented in Figures 4 and 6. Female results are presented in Figures 5 and 7. The A r BF% measurements agreed with H W lc for males < 20% (-0.4±6.9%; p=0.73), but significantly underestimated BF% for males > 20% (-3.5±6.1%; p<0.05). The A r also agreed with H W lc for females with < 24% (-1.8±10.5%; p=0.30) and > 24% (- 1.1±10.9%; p=0.55). Al significantly underestimated BF% for males < 20% (-6.3±6.7%; p<0.05) and >20% (-9.46±5.9%; p<0.05). A L agreed with H W Lc for females < 24% (- 1.5±9.6%; p=0.33), but females > 24% were significantly underestimated (-3.8±5.5%; p<0.05).

21 12 Table 4. Validity of Body Composition Measurements using Hydrostatic Weighing with a Load Cell as the Criterion Body Composition Method Participants v Mean Bias (%) Limits of Agreement (%) Pearson's Correlation (r) Standard Error of Estimate (%) Bod Pod All Female * Male A r All Female Male * A l All * Female * Male - 7.9* Ar = Aria Regular Mode; Al = Aria Lean Mode \ / All (n=43), Female (n=21), Male (n=22) * p< mean difference significantly differed from HWlc

22 Mean BF of Device and HW (Vo) Figure 2. Bland-Altman plots for the Bod Pod (Panel A), Ar (Panel B), and AL (Panel C) showing mean biases (solid lines) and limits of agreement (dashed lines) for each device compared to HWlc for all participants (n=43). All comparisons are from the first day o f testing.

23 14 Female Male BF Difference (%) BF Difference (%) BF Difference (%) Mean BF of Device and HW (%) Mean BF of Device and HW (%) Figure 3. Bland-Altman plots for the Bod Pod (Panel A), AR (Panel B), and AL (Panel C) showing mean biases (solid lines) and limits of agreement (dashed lines) for each device compared to HWLc for female (n=21) and male (n=22) participants. All comparisons are from the first day of testing.

24 A B *.* Mean BF of Device and HW (%) Mean BF of Device and HW (%) Figure 4. Bland-Altman plots for Ar showing mean biases (solid lines) and limits of agreement (dashed lines) compared to HWLc for male (n=22) participants with (A) < 20% body fat (n=l 1) and (B) > 20% body fat (n=l 1). All comparisons are from the first day of testing B u flq "! ) Mean BF of Device and HW (%) Mean BF of Device and HW (%) Figure 5. Bland-Altman plots for A r showing mean biases (solid lines) and limits of agreement (dashed lines) compared to HWLc for female (n=21) participants (A) < 24% body fat (n=l 1) and (B) > 24% body fat (n=10). All comparisons are from the first day of testing.

25 B s CQ Mean BF of Device and HW (%) 35.0 s!o m o 15JD J Mean BF of Device and HW (%) 35.0 Figure 6. Bland-Altman plots for AL showing mean biases (solid lines) and limits of agreement (dashed lines) compared to HWLc for male (n=22) participants with (A) < 20% body fat (n=l 1) and (B) > 20% body fat (n=l 1). All comparisons are from the first day of testing B C.0- fc < j 10.0 J Mean BF of Device and HW (%) I 5.0 r Mean BF of Device and HW (%) i 30.0 j 35.0 Figure 7. Bland-Altman plots for AL showing mean biases (solid lines) and limits o f agreement (dashed lines) compared to HWLC for female (n=21) participants (A) < 24% body fat (n=l 1) and (B) > 24% body fat (n=10). All comparisons are from the first day of testing.

26 17 Bod Pod Comparison Bland-Altman plots comparing the Fitbit Aria, in both lean and regular modes, to the Bod Pod during day one for all trials and for all participants are presented in Figure 8 and Table 5. Bland-Altman Plots comparing male and female participants separately are presented in Figure 9. The A r BF% measurements agreed with the Bod Pod for all participants (-1.2 ±10.2%; p=0.14) and females (0.7±11.5%; p=0.60), but underestimated males by -3.0±7.3% (p<0.05) (Table 5). The Al significantly underestimated BF% for all participants (-5.7±10.6%), males (-8.9±7.6%), and females (-2.4± 9.3%) with p<0.05 (Table 5). The SEE and Pearson s Correlation coefficient for BF% are presented for each comparison in Table 5. Additionally, linear regressions revealed no significant Bland- Altman trends for any of the methods or groups (p>0.05). Table 5. Comparison of Aria Body Composition Measurements to the Bod Pod Body Composition Method Participants v Mean Bias (%) Limits of Agreement (%) Pearson's Correlation (r) Standard Error of Estimate (%) A r All Female * Male A l All - 5.7* Female -2.4* * Male Ar = Aria Regular Mode; AL = Aria Lean Mode \ / All (n=43), Female (n=21), Male (n=22) * p< mean difference significantly differed from Bod Pod

27 18 BF Difference (%) BF Difference (%) Mean BF of Device and Bod Pod (%) Figure 8. Bland-Altman plots for the Ar (Panel A), and AL (Panel B) showing mean biases (solid lines) and limits of agreement (dashed lines) for each device compared to the Bod Pod for all participants (n=43). All comparisons are from the first day of testing.

28 19 Female Male BF Difference (%) BF Difference (%) Figure 7. Bland-Altman plots for the AR (Panel A), and AL (Panel B) showing mean biases (solid lines) and limits of agreement (dashed lines) for each device compared to the Bod Pod for female (n=21) and male (n=22) participants. All comparisons are from the first day of testing.

29 20 Reliability Day-to-day and week-to-week reliability of BF% measurements for all devices are presented in Table 8 and 9, respectively. Results showed similar day-to-day and week-to-week reliability values (mean difference and intraclass correlations) between methods and groups (all participants, men, and women). All devices appear to produce reliable BF% measurements in men and women. As a control, hydration status, as measured by total body water, reliability is presented in Tables 6 and 7. Both day-to-day and week-to-week reliability values were similar among groups. The measurements of total body water appear to be reliable in both men and women. Table 6. Day-to-day Reliability of Total Body Water Measurements * Participants Day 1 v Day 2 ^ Mean difference ICC All 37.4 ± ± Female 31.9 ± ± Male 42.6 ± ± ICC: Intraclass Correlation Coefficient v)/ Values are given as mean ± SD of total body water (L) * All (n=43), Female (n=21), Male (n=22) Table 7. Week-to-week Reliability of Total Body Water Measurements * Participants Day 1 v Day 3 Mean difference ICC All 37.4 ± ± Female 31.9 ± ± Male 42.6 ± ± ICC: Intraclass Correlation Coefficient v / Values are given as mean ± SD of total body water (L) * All (n=43), Female (n=21), Male (n=22)

30 21 Table 8. Day-to-day Reliability of Body Composition Measurements All (n=43) Females (n=21) Males (n=22) Method Day 1 v Day 2 Mean difference ICC HWlc 22.3 ± ± HWms 22.4 ± ± Bod Pod 22.7 ± ± A r 21.5 ± ± A l 17.0 ± ± HWlc 23.9 ± ± HWms 24.0 ± ± Bod Pod 23.6 ± ± A r 24.3 ± ± A l 21.2 ± ± HWlc 20.8 ± ± HWms 20.8 ± ± Bod Pod 21.8 ± ± A r 18.8 ± ± A l 12.9 ± ± ICC: Intraclass Correlation Coefficient vy Values are given as mean ± SD of body fat (%)

31 22 Table 9. Week-to-week Reliability of Body Composition Measurements All (n=43) Females (n=21) Males (n=22) Method Day 1 ^ Day 3 v Mean difference ICC H W Lc 22.3 ± ± H W Ms 22.4 ± ± Bod Pod 22.7 ± ± A r 21.5 ± ± A l 17.0 ± ± H W lc 23.9 ± ± H W ms 24.0 ± ± Bod Pod 23.6 ± ± A r 24.3 ± ± A l 21.2 ± ± H W lc 20.8 ± ± H W ms 20.8 ± ± Bod Pod 21.8 ± ± A r 18.8 ± ± A l 12.9 ± ± ICC: Intraclass Correlation Coefficient \ / Values are given as mean ± SD of body fat (%)

32 23 DISCUSSION The aims of this investigation were to determine the reliability of body composition measurements from various methods, validate body fat percentage measurements using the SFSU Bod Pod and Fitbit Aria scale against the criterion method of H W lc, and compare body fat measurements from H W lc and H W ms- Based on a current review of the literature, this is the first investigation to evaluate the accuracy and reliability of the Aria scale compared to industry gold standards. Reliability In this group of healthy adults, all methods (H W lc, H W Ms, Bod Pod, A r, and A l) for all groups (all participants, males, and females) were reliable with ICC values >0.95 for both day-to-day and week-to-week measurements of body fat percentage (Table 8 and 9). Previous studies have found similar same day test-retest and between day reliability results for H W lc and H W ms-16,17 A review by Fields et al. reported similar within day and between day reliability results for air displacement plethysmography using the Bod Pod.17' 19 The Fitbit Aria proved to reliably track body fat percentage for both males and females in either lean or regular mode (Table 8 and 9). Similar between day reliability results have been found using foot-to-foot BIA scales.20,21 Utter et al. found that a footto-foot BIA scale was able to reliably track body fat loss over time in obese individuals with the same accuracy as hydrostatic weighing.21 When choosing an at home body fat measurement device to track weight loss or body composition changes over time, reliably is essential. With day-to-day ICC values >0.98 and week-to-week ICC values >0.96 for

33 24 all groups and modes, the Fitbit Aria is able to reliably track progress of body fat measures over time (Table 8 and 9). To ensure reliable results from any device over time, body composition measurements should be taken at the same time of day, in the fasted state, and with hydration status controlled. Another factor contributing to the reliability of all devices is that only one investigator performed all testing sessions. Interreliability errors between testers for all devices could be different from the intrareliability errors in this investigation. Of all body composition methods investigated in this study, measurements of underwater weight for hydrostatic weighing has the potential to be the most highly variable due to visual interpretation from the mechanical scale and deciding which load cell data points to use. To ensure reliable results from hydrostatic weighing, the same investigator should perform each session. Since hydration status of an individual can affect BIA measurements, total body water was measured each visit as a control. Measurements of total body water for all groups were reliable with day-to-day ICC values >0.89 and week-to-week ICC values >0.88 (Table 6 and 7). These findings agree with previous reliably research done on this device.20 Validity McCrory et al. were the first to evaluate the Bod Pod compared to hydrostatic weighing in adults, and their data showed a mean difference in body fat percent between the two methods to be 0.3% (p<0.05) and SEE = 1.8%. Their data concluded the Bod Pod was a valid instrument for determining body fat percent in men and women.22 Using

34 25 Bland-Altman plots, measurements of body fat percent from the SFSU Bod Pod agreed with the criterion method of H W lc and were highly correlated (r=0.93) for all participants with SEE = 2.2% (Figure 2 and Table 4). A review investigating the validity of the Bod Pod in comparison to hydrostatic weighing found similar SEE margins of % for the Bod Pod for both male and female participants.17 For females, the SFSU Bod Pod agreed with H W lc, with mean bias and limits of agreement -0.3±4.0% and SEE = 2.0% (Figure 3 and Table 4). Female Bod Pod measurements also highly correlated with H W lc (r=0.94). Fields et al. found similar SEE values of 2.3% for females in comparison to hydrostatic weighing in two separate investigations.17 In contrast, the SFSU Bod Pod measurements for male participants did not agree with H W lc, significantly overestimating body fat by 1.0±4.3% with SEE = 2.2% body fat (Figure 3 and Table 4). Previous studies have found opposite results, finding that the Bod Pod underestimates body fat in males likely because men tend to have more body hair due to facial hair and leg hair.17,23 A study done comparing Bod Pod body fat measurements in males with DEXA found that the Bod Pod overestimated body fat percent, although the two measures highly correlated.24 An explanation for this overestimation of body fat could be due to improper breathing during the Bod Pod body volume measurements or during the measurement of V tg- Tegenkamp et al. found that during body volume measurement in the Bod Pod, breathing more shallowly resulted in 9 S bod fat overestimation by 2.2%. Additionally, breathing deeper during the measurement 9 S of V tg overestimated body fat percent by 3.7%. Though all participants were given the

35 26 standardized instructions to breath normally throughout the entire test, it could be that males deviated from the instructions, causing the overestimation of body fat percent. Current research indicates that there is no consensus on accuracy of regional BIA devices for various populations. Depending on the specific equations used by each BIA scale, body fat results may not be as accurate for certain populations. Lazzer et al. and Goldfield et al. found that foot-to-foot BIA scales were not as accurate as DEXA in assessing body fat percent in obese adolescence and adults. Both studies concluded that though measurements of body fat percent correlated, the two methods should not be used interchangeably. In contrast, a study by Boneva-Asiova et al. on both obese and non-obese adults found that body fat percent, fat mass, and fat-free mass measured by DEXA and foot-to-foot BIA were not significantly different.28 They also found that the limits of agreement between BIA and DEXA decreased with the increasing BMI of the subjects, suggesting that BIA may not be as accurate at measuring body composition in obese individuals.28 Body fat measurements using the Aria scale support previous research indicating that segmental BIA correlates well with a criterion method, but under or overestimates individual body fat measures. In regular mode, the Aria agreed with H W lc for all participants with an r=0.70, but had a large 95% limit of agreement of ± 9.3% and SEE = 4.4% (Figure 2 and Table 4). Similarly for female participants, regular mode agreed with H W lc but had a wide limit of agreement at ± 10.8% and SEE of 4.7% (Figure 3 and Table 4). Female measurements also had a low Pearson s correlation of r=0.57. For male

36 27 participants, the Aria in regular mode significantly underestimated body fat percent by - 2 ± 7.1% with SEE = 3.7% (Figure 3 and Table 4). Though consistently underestimating, the SEE is lower for males than for females and all participants, and is close to a more acceptable error range. Male measurements also had a strong correlation to H W lc of r=0.82. In lean mode, the scale significantly underestimated body fat percent for all groups, with the discrepancy being more pronounced in males (Table 4 and Figures 2 and 3). Though body fat percentage was underestimated by a larger degree, the SEE for males in lean mode was 3.6% and closer to an acceptable range than females (SEE = 4.0%), and all participants (SEE = 4.2%). Males also had the strongest correlation to H W lc with r^o.82. According to the Fitbit Aria Instruction Manual, lean mode is intended for lean individuals or professional athletes, such a marathon runners and body builders.10 The population used in this study consisted of SFSU college students and recreational runners recruited through personal contacts of the primary investigator, some of which were incredibly lean and high-level athletes. In this study, activity level for each participant was not quantified. Linear regressions revealed no significant Bland-Altman trends for any of the methods or groups (p>0.05), though there was a wide range of body composition types. Without a quantifying activity level and using a sample of professional athletes to compare, it is hard to predict if lean mode will estimate body fat percentage better for certain body types. A study done by Swartz et al. investigated the effect of different activity levels on two different modes ( athlete and adult ) for a foot-

37 28 to-foot BIA device compared to hydrostatic weighing.29 The study found no difference in body fat percent in athlete mode for highly active and moderately active males compared to hydrostatic weighing, but the less active group did not agree and was underestimated. Opposite was true for Adult mode - there was no difference in body fat for less active males, but high and moderately active males did not agree and body fat 90 was over estimated. The study concluded that scale mode greatly impacted validity, and with the right mode for the right population, there was no difference between body fat percent compared to hydrostatic weighing; though the range of individual errors were high. In addition, male and female participants were further categorized into low and high body fat percent groups when analyzing the Fitbit Aria in both Regular and Lean modes. Previous studies have found that the accuracy of foot-to-foot BIA devices decreases as participant BMI increases.26"28 The findings in this study agree with the literature. In Regular mode, the Aria agreed with H W lc for males under 20% body fat, but significantly overestimated males greater than 20% body fat (Figure 4). The Regular mode was valid for female participants in both high and low body fat percent categories (Figure 5). In Lean mode, the Aria agreed with H W lc for females under 24% body fat, but significantly underestimated females over 24% body fat (Figure 7). For males, Lean mode significantly underestimated body fat percent in both categories (Figure 6).

38 29 For the Fitbit Aria, the mode used impacted validity of body fat measurements for both male and female participants; but body fat percent for male participants was more often significantly underestimated compared to H W lc in either mode. It may be possible that due to gender differences in fat distribution, with males more commonly having android fat distribution, the foot-to-foot BIA does not adequately register fat or the equations used in the scale to calculate body fat don t accurately account for it in males. Body fat measurements using the scale were also compared to the Bod Pod. Since the majority of body composition testing done by the SFSU Exercise Physiology Laboratory uses the Bod Pod, it is important to know how the two methods compare if the client also tracks their body composition at home using the Aria. Similarly to H W lc, the Aria regular mode agreed with the Bod Pod for all participants and females, but significantly underestimated males at -3.0±7.3% (Table 5). The Aria lean mode significantly underestimated body fat percent for all groups, with a larger discrepancy for males. Overall, results were similar to the criterion comparison. Load Cell vs. Mechanical Scale The load cell and mechanical scale measurements of body fat percentage had a Pearson s correlation of r=1.00 and a SEM of ± 0.2% for all groups (Table 3). A previous study done by Moon et al. found no difference between mechanical scale and load cell measurements of UWW and calculated body fat percentages (95% limits of agreement: 0.53%).16 The study concluded that either method can be used for hydrostatic weighing

39 30 with similar accuracy and reliability.16 Based on the findings from the present study, the Exercise Physiology Laboratory could use either the load cell or mechanical scale for hydrostatic weighing. Limitations There were multiple limitations to this study. Due to location of the Exercise Physiology Laboratory, all participants were from the San Francisco Bay Area. Though sex, body mass, and body fat did not influence the variations in scale body fat measurements, the current results only report the accuracy and reliability for a group of predominately Caucasian men and women from San Francisco, California. Future research investigating the impact of age and a wider range of body fat percentages on the accuracy of the scale is needed. Additionally, one cause of inaccuracy associated with BIA measurement is the limitation of the equations used for calculating body fat. Not all equations are the best fit for specific ethnic groups or body sizes. The equations used to calculate body fat percent in the Aria are property of Fitbit and are unknown to the investigator. Further research investigating a more diverse population is needed to see if the equations used in the scale are accurate for all ethnicities. Activity level of participants was not requested. This could be a contributing factor to help predict for which individuals the lean mode on the Aria scale was more accurate for. Future research investigating the impact of activity level on the accuracy of Aria modes is needed. When calculating body volume from hydrostatic weighing measurements, one cause of inaccuracy that must be corrected for is the air remaining within the body in both

40 31 the intestinal tract and lungs. In this study, the volume of air trapped in the intestinal tract was ignored. Conclusion Based on the findings from the present study, the Exercise Physiology Laboratory could use either the load cell or mechanical scale for hydrostatic weighing and achieve similar accuracy and reliably of body fat measurements. The SFSU Bod Pod was found to be a valid method for measuring body composition in females, but over estimates males by 1.0±4.3%. In regular mode, the Aria agreed with hydrostatic weighing when analyzing body fat percentage for all participants, females, and males less than 20% body fat, but significantly underestimated body fat for males over 20% body fat. In lean mode, the Aria agreed with hydrostatic weighing when analyzing body fat percentage for females under 24% body fat, but underestimated body fat percentage for all other groups, and this discrepancy was more pronounced in males. Overall, the mode chosen on the Aria scale greatly impacts validity for male and female participants, but was often invalid for males. In addition, individual errors were large for the Aria measurements for all groups. All methods were reliable when comparing day-to-day and week-to-week body fat percent measurements for all groups. This suggests the Fitbit Aria can be a reliable at-home body composition analysis scale when tested under the same conditions each measurement.

41 32 REFERENCES 1. Romero-Corral, A., Somers, V.K., Sierra-Johnson, J., Thomas, R.J., Collazo- Clavell, M.L., Korinek, J., Allison, T.G., Batsis, J.A., Sert-Kuniyoshi, F.H., & Lopez-Jimenez, F. (2008). Accuracy of body mass index in diagnosing obesity in the adult general population. International Journal o f Obesity, 32: Pi-Sunyer, F.X. (2002). The obesity epidemic: pathophysiology and consequences of obesity. Obesity Research, 10 (suppl 2): 97S-104S. 3. Lee, C. D., Blair, S. N., & Jackson, A. S. (1999). Cardiorespiratory fitness, body composition, and all-cause and cardiovascular disease mortality in men. American Journal o f Clinical Nutrition, 69 (3): Burke, L. M., Loucks A. B., & Broad N. (2006). Energy and carbohydrate for training and recovery. Journal o f Sports Science, 24: Nelson, K. M., Weinsier, R. L., Long, C. L., & Schutz, Y. (1992). Prediction of resting energy expenditure from fat-free mass and fat mass. American Journal o f Clinical Nutrition, 56: Barandun, U., Knechtle, B., Knechtle, P., Klipstein, A., Rust, C. A., Rosemann, T., & Lepers, R. (2012). Running speed during training and percent body fat predict race time in recreational male marathoners. Open Access Journal o f Sports Medicine, 3: Knechtle, B., Wirth, A., Baumann, B., Knechtle, P., & Rosemann, T. (2010). Personal best time, percent body fat, and training are differently associated with

42 33 race time for male and female Ironman triathletes. Research Quarterly for Exercise and Sport, 81(1): Bale, P., Rowell, S., & Colley, E. (1985). Anthropometric and training characteristics of female marathon runners as determinants of distance running performance. Journal o f Sports Sciences, 3(2): Rust, C. A., Knechtle, B., Knechtle, P., & Rosemann, T. (2012). Similarities and differences in anthropometry and training between recreational male 100-km ultra-marathoners and marathoners. Journal o f Sports Sciences, 30(12): Smarter scale. Better results. Retrieved March 31, 2016, from American College of Sports Medicine. Guidelines for Exercise Testing and Prescription. 9th ed. Lippincott, Williams, and Wilkins, Baltimore, Gleichauf, C. & Roe, D. (1989). The menstrual cycle s effect on the reliablity of bioimpedance measurements for assessing body composition. American Journal o f Clinical Nutrition, 50, Wilmore, J.H., Vodak, P.A., Parr, R.B., Girandola, R.N., and Billing, J.E. (1980). Further simplification of a method for determination of residual lung volume. Medicine and Science in Sports and Exercise, 12: Dempster P, & Aitkens, S. (1995). A new air displacement method for the determination of human body composition. Medicine and Science in Sports and

43 34 Exercise, 27: Siri, WE. (1961). Body composition from fluid spaces and density. Analysis of methods. In: Techniques for Measuring Body Composition. Brozek, J and Henschel, A, eds. Washington, DC: National Academy of Sciences, pp Moon, J.R., Stout, J.R., Walter, A.A., Smith, A.E., Stock, M.S., Herda, T.J., Sherk, V.D., Young, K.C., Lockwood, C.M., Kendall, K.L., Fukuda, D.H., Graef, J.L., Cramer, J.T., Beck, T.W., & Esposito, E.N. (2011). Mechanical scale and load cell underwater weighing: a comparison of simultaneous measurements and the reliability of methods. The Journal o f Strength and Conditioning Research, 25(3): Fields, D.A., Goran, M.I., & McCrory, M.A. (2002). Body-composition assessment via air-displacement plethysmography in adults and children: a review. American Journal o f Clinical Nutrition, 75: Tucker, L.A, Lecheminant, J.D., & Bailey, B.W. (2014) Test-restest reliability of the bod pod: the effect of multiple assessments. Perceptual and Motor Skills, 118(2): Anderson, D.E. (2007). Reliability of air displacement plethysmography. Journal o f Strength and Conditioning Research, 21(1): Nunez, C. Gallagher, D., Visser, M., Pi-Sunyer, F.X., Wang, Z., & Heymsfield, S.B. (1997). Bioimpedance analysis: evaluation of leg-to-leg system based on pressure contact foot-pad electrodes. Medicine and Science in Sports and

44 35 Exercise, 29 (4): Utter, A.C., Nieman, D.C., Ward, A.N., & Butterworth, D.E. (1999). Use of the leg-to-leg bioelectrical impedance method in assessing body-composition change in obese women. American Journal o f Clinical Nutrition, 69 (4): McCrory, M.A., Gomez, T.D., Bemauer, E.M., Mole, P.A. (1995). Evaluation of a new air displacement plethysmograph for measuring human body composition. Medicine and Science o f Sports and Exercise, 27: Biaggi, R.R., Vollman, M.W., Nies, M.A., Brener, C.E., Flakoll, P.J., Levenhagen, D.K., Sun, M., Karabulut, Z., & Chen, K.Y. (1999). Comparison of air-displacement plethysmography with hydrostatic weighing and bioelectrical impedance analysis for the assessment of body composition in healthy adults. The American Journal o f Clinical Nutrition, 69: Ball, S.D. & Altena, T.S. (2004). Comparison of the Bod Pod and dual energy x- ray absorptiometry in men. Physiological Measurement, 25(3). 25. Tegenkamp, M.H., Clark, R.R., Schoeller, D.A., & Landry, G.L. (2011). Effects of covert subject actions on percent body fat by air-displacement plethsymography. Journal o f Strength & Conditioning Research, 25(7): Lazzer, S., Boirie, Y., Meyer, M., & Vermorel, M. (2003). Evaluation of two foot-to-foot bioelectrical impedance analyzers to assess body composition in overweight and obese adolescents. British Journal o f Nutrition, 90:

45 Goldfield, G.S., Cloutier, P., Mallory, R., Prud homme, D., Parker, T., & Doucet, E. (2006). Validity of foot-to-foot bioelectrical impedance analysis in overweight and obese children and parents. Journal o f Sports Medicine and Physical Fitness, 46 (3): Boneva-Asiova, Z. & Boyanov, M.A. (2008). Body composition analysis by legto-leg bioelectrical impedance and dual-energy X-ray absorptiometry in nonobese and obese individuals. Diabetes, Obesity, and Metabolism, 10(11): Swartz, A.M., Evans, M.J., King, G.A., & Thompson, D.L. (2002). Evaluation of a foot-to-foot bioelectrical impedance analyzer in highly active, moderately active and less active young men. British Journal o f Nutrition, 88: Peterson, J.T., Repovich, W.E.S., & Parascand, C.R. (2011). Accuracy of consumer grade bioelectrical impedance analysis devices compared to air displacement plethysmography. International Journal o f Exercise Science, 4 (3):

46 37 APPENDIX I LITERATURE REVIEW Evaluations of body fat percent and fat-free mass are necessary to monitor obesity classification, training outcomes, and general health.1excess adipose tissue in obese individuals has been shown to have deleterious effects on multiple organ systems and is associated with an increased risk of cardiovascular disease, diabetes mellitus, hypertension, and dyslipidemia.1,2 It follows that reducing excess body fat can decrease an individual s risk for chronic disease. Because estimations of body fat are used to quantify an individual s health risk, as well as identify weight loss intervention progress, it is important that they are accurate.3 Body composition is also useful for athletic trainers to create, optimize, and evaluate training programs, as well as for sports nutrition experts to develop individualized dietary interventions.4,5 In addition, analysis of body composition is also in the interest of endurance athletes, such as triathletes and marathoners, since a relatively low body fat percentage is desirable to optimize physical performance in these sports.6'9 In order to track the effectiveness of an intervention strategy or attain optimal body composition for athletic performance, understanding the reliability of body composition measurements is essential. Because of its importance, many individuals purchase body composition measurement services at a local gym or exercise physiology laboratory. When providing health and fitness services, the ability to accurately and reliably measure body composition is vital. The Exercise Physiology Laboratory (EPL) at San Francisco State

47 38 University (SFSU) offers body composition testing using skin fold measurements, hydrostatic weighing, and air displacement plethysmography via the Bod Pod. Between March 2015 and February 2016, 180 body composition measurement services were paid for and conducted in the lab. Out of those body composition measurements taken, 75% were performed using the Bod Pod. With a high volume of clients relying on the Bod Pod for body composition measurements, it is important to know the accuracy and validity of the machine. The equipment in the EPL has been used not only to test the public, but also as teaching instruments for students. Over the years, and after extensive use, the reliability and accuracy of the body composition equipment in the laboratory has not been measured. Because ELP offers body composition measurements as a service, it is essential that the results are reliable over time, ensuring that clients receive the accurate body composition measurements that they paid for. With the rise of home health electronics, many clients own a bioelectrical impedance analysis (BIA) scale, such as the Fitbit Aria, to monitor progress at home. Thus, it is important to know how the methods compare to one another. The purpose of this investigation is to assess the day-to-day and week-to-week reliability of body fat measurements using three different methods - air displacement plethysmography, BIA, and two measurements of hydrostatic weighing - in the SFSU EPL. Recently, the EPL installed a new load cell for its hydrostatic tank that will be used to weigh subjects along with the mechanical scale. Additionally, the validity of body fat

48 39 measurements using air displacement plethysmography and BIA will be compared to the industry gold standard of hydrostatic weighing. Body Composition Components In order to measure body composition, the human body is broken down into its building blocks of water, protein, minerals, and fat. By independently measuring these components, precise measurements of total composition can be made. Depending on the method used, the body can be viewed as a two-component, three-component, fourcomponent or even six-component model. 11,12 The most common methods of assessing body composition, such as hydrostatic weighing, air displacement plethysmography, and BIA, are based on a two-component model.12 The two-component model divides the body simply into fat mass and fat-free mass, and equations derived from this model assume that the relative densities of these 1 ^ # two components are stable. Fat mass is defined as all non-essential lipids and has a relatively constant density of 0.9kg/L. Fat-free mass is comprised of all other mass, including essential non-fat lipids such as phospholipids and steroids that are crucial in various biochemical and physiological processes.11fat-free mass is estimated to be l.lkg/l, yet this density encompasses three major components (water, protein, and minerals), which can individually vary in density.12 While these values are representative of the majority of the population, there is some variability across different ethnic groups which needs to be taken into consideration.14 Based on the known densities of fat and fat- free mass, an equation was created by Siri in 1961 to estimate body fat percent from body

49 40 density.13 In 1963, Brozek et al. created another now commonly used equation to predict body fat percent based off predicted component densities.15 Despite the error created by the assumption of constant densities in these equations, they are the most commonly used and can be applied to the majority of the population. As technology has advanced over the years, more complex models of the human body have emerged and more accurate prediction equations have been derived based on additional components of the body other than fat mass and fat-free mass. The three, four, and six-compartment models are referred to as multi-component models and depending on the instrument used, can quantify the amount of water, protein, bone minerals, and body cell mass in the body.11 By measuring the different components of the body individually, more precise prediction equations can be developed that can account for body composition changes across ethnic groups and between males and females. These components are often measured by using dual x-ray absorptiometry (DEXA) or isotope dilution, both of which make multi-component models difficult to test outside of a research or clinical setting.12 Methods o f Measuring Body Composition Various methods are used to indirectly measure body fat, including hydrostatic weighing, air displacement plethysmography, BIA, DEXA, and skin fold measurements. The majority of these techniques use densitometry, which is the use of body density to determine total body composition. The focus of the current investigation is on hydrostatic weighing, air displacement plethysmography, and BIA.

50 41 Hydrostatic Weighing According to Archimedes principle, the volume of an object is equal to the object s loss of weight in water with appropriate correction for the density of the water.16 Hydrostatic weighting, first discussed by Behnke et al. in 1942, and is based on the relationship between total body density and body volume. Hydrostatic weighing measures the weight of an object underwater and uses this weight to calculate the object s volume. Because the density of an object is equal to the object s mass divided by the object s volume, body density can be calculated dividing dry body weight by body volume, as determined from hydrostatic weighing. The Siri and Brozek equations then use the calculated body density to predict body fat percent. Hydrostatic weighing measurements can be taken by reading weight directly from a mechanical scale or from a load cell. The load cell is a transducer that converts force into a measureable electric output. Consequently, the load cell provides a recording of the 90 underwater weight measurement in hertz that is then converted to kilograms. A study done by Moon et al. in 2011 found no significant differences for underwater weight or body fat percent between measurements taken by the load cell and mechanical scale. This study concluded that both the load cell and mechanical scale could be used to assess 90 underwater weight with a similar accuracy and reliability. One cause of inaccuracy in body volume measures that must be corrected for is the air remaining within the body in both the intestinal tract and lungs. This left over air increases buoyancy when being weighed underwater, which decreases underwater

51 42 weight. To correct for this, residual lung volume is directly measured using nitrogen washout or oxygen rebreathing techniques.17 The volume of air trapped in the intestinal tract is very small and can be either estimated or ignored, depending on lab protocol. Assuming hydrostatic weighing is performed correctly, and corrections are made for residual air within the body and water density, the resulting body density is quite accurate. However, it does have some limitations that can result in error when calculating body fat percent. Due to the inverse relationship of body density to body fat percent, if body density is underestimated it will lead to an overestimation of body fat percent. One way this manifests itself is when participants have trouble exhaling as much air as possible, their underwater weight will be lower than it should be, and body density will be underestimated. There are also limitations associated with using the Siri and Brozek equations, since they assume constant density of fat and fat-free mass. Despite these limitations, hydrostatic weighing is considered one of the gold standards for measuring body composition and is commonly used as a criterion method to compare against new body composition prediction methods. Air Displacement Plethysmography Air displacement plethysmography is a densitometry technique used to determine body composition by measuring body volume. Once body volume is known, body density and body fat percentage can be determined in a similar manner to hydrostatic weighting. Introduced in the mid-1990s, the Bod Pod is the apparatus used to perform this technique. The Bod Pod is an airtight chamber and the volume of air in the empty

52 43 chamber is known. When a person enters the airtight chamber, they displace their own volume of air. Body volume is then determined by taking the difference between the empty chamber air volume and the volume of air when the person is inside the chamber.18 As with hydrostatic weighing, corrections to body volume must be made. The behavior of gases under isothermal and adiabatic conditions are extremely important to the design of techniques used for measuring body volumes with plethysmography.18 Boyle s law states that at constant temperature (isothermal conditions) the product of pressure and volume is constant. Under adiabatic conditions, the temperature of air does not remain constant as its volume changes. Consequently, isothermic air is 40% more easily compressed than adiabatic air, leading to an over estimation of body density.18 Two contributors to isothermal conditions within the testing chamber are the subject s body surface area and air within the lungs. Air within the lungs, or thoracic gas volume, is measured while the subject is in the Bod Pod and is normalized to adiabatic conditions by dividing the measured thoracic gas volume by a correction factor of Thoracic gas volume can also be predicted using Bod Pod software, and these predictions were found to not differ significantly from measured thoracic volume.19 Additionally, there were no differences observed between body composition estimates using the predicted thoracic volume and actual measured volume.19 Clothing, hair, and skin are also at isothermal conditions and are corrected for in a calculation of surface area artifact automatically done by the Bod Pod software using the Dubois formula.18 Additional

53 44 clothing or exposure of hair will result in an overestimation of body volume, leading to an underestimation of body fat percent. Bioelectrical Impedance Analysis First described in the 1960s, BIA determines bioelectrical impedance, or the opposition of the flow of an electrical current through body tissues.21,22 This method is based on the principle that electrical conductivity of fat-free mass is greater than fat. Lean tissue contains large amounts of water and electrolytes, and is therefore highly conductive. In contrast, fat and bone are dielectric substances, making them poor conductors. BIA is based on Ohm s law, which states that the resistance of a substance is proportional to the voltage drop of an applied current as it passes through the resistive substance To measure this, a painless electrical signal is introduced via an electrode at one site on the body, and the signal is sensed by another electrode in a separate location. Because the input current is known ahead of time, and the voltage drop is recorded, resistance in the body can be calculated using Ohm s law. Once resistance is known, it can be used to calculate an estimation of total body water. From total body water, fat-free mass can be estimated, which then is used to determine body fat. BIA became commercially available in the mid 1980s and gained popularity due to its ease of use, portability of equipment, and low cost. There are several types of bioelectrical impedance equipment available. Whole-body BIA technology uses four electrodes, two attached to each right wrist and right ankle. Then, a constant 800(iA current at a fixed 50kHz frequency is introduced and the resistance is measured and used

54 45 to estimate total body water.24 The issue with this technique is that it assumes the body to be one cylinder, introducing some inaccuracy in its estimations. In reality, the body is better represented as a series of five cylinders - two for the arms, two for the legs, and one for the trunk. Because the limbs have a smaller cross-sectional area than the trunk, and there is an inverse relationship between resistance and cross-sectional area, the limbs will contribute more to whole body resistance than the trunk.23 Succeeding whole-body analysis, segmental body impedance devices that measure regional impedance were created.25 For example, hand held bioelectrical devices send a signal from arm-to-arm to determine upper body impedance. Another example are the currently popular BIA scales, like the Aria, which contain plate electrodes that send an impulse through a person s feet to measure lower body impedance. Once regional impedance is known, total body fatness is calculated using equations. One cause of inaccuracy associated with BIA measurement is the limitation of the equations used for calculating body fat. Not all equations are the best fit for specific ethnic groups or body sizes. Additionally, hydration status of the individual can effect the measurement. To account for this, fluid intake should be standardized prior to body composition measurement. Validity and Reliability o f Body Composition Methods Currently, both hydrostatic weighing and DEXA are considered the gold standards for measuring body composition and are used as the criterion to compare new body composition prediction methods against.20,24'31,33'37 First clinically available in the

55 s, DEXA is now considered one of the gold standards for measuring body composition. " Using low-energy x-ray beams and computer software, DEXA produces images of the body that can then be used to determine body composition.27 It is primarily used in clinical practice to measure bone mineral density, but also has been found to accurately measure body composition and fat content. This technique uses multi-component models to determine body composition, and it also determines regional body composition. DEXA is easy for subjects to comply with and is non-invasive. The procedure requires subjects to lie still in supine while a DEXA scanner moves above them. Though accurate, DEXA can be an expensive procedure due to the equipment needed and trained personnel required to operate the scanner and interpret the results. When the Bod Pod was first introduced, it was validated against both these gold standard measurements. In 1995, McCroy et al. published the first validation of the Bod Pod in comparison to hydrostatic weighing using human subjects. Measuring 68 adults, both male and female, of various ethnicities, fatness, and age (range years), the study found no significant difference in body fat estimates between the Bod Pod and hydrostatic weighing. The same study also measured same-day test-retest reliability in 16 subjects and found no significant difference between the first and second trials.30 The authors concluded that the study indicated excellent agreement between body fat percent as measured by the Bod Pod and hydrostatic weighting. A review by Fields et al. in 2002 investigated research findings published between 1995 and 2001 that compare the Bod Pod to hydrostatic weighing, DEXA, and

56 47 multicomponent models. On average, the review found that when compared, Bod Pod and hydrostatic weighing measurements of body fat percent are within 1% of body fat in both adults and children. Of the twelve validation studies reviewed investigating adults, five showed no significant difference between the Bod Pod and hydrostatic weighing. In the seven studies that did, the direction of differences was inconsistent - five showed lower body fat percent with Bod Pod than hydrostatic weighing and two studies showed the opposite.31 When compared, the Bod Pod and DEXA measurements of body fat percent were within 1% for adults and 2% for children. Of the nine studies, four found significantly lower body fat percent measurements by the Bod Pod compared to DEXA, and one found significantly higher. Compared to the multicomponent models, the Bod Pod underestimates body fat percent by 2-3% in both adults and children. Many of the studies also observed that hydrostatic weighing underestimated body fat percent by a similar margin when compared to multicomponent models. This underestimation could be explained by limitations in the assumption of the two-component model used by both the Bod Pod and hydrostatic weighing. In terms of Bod Pod reliability, seven studies reported within day and between day reliability of body fat percent of adults and found the measurements to be within range of the reliability of hydrostatic weighing and DEXA.31 The review by Fields et al. suggested that sources of error with the Bod Pod measurements could be due to testing conditions and inconsistencies across the different studies. Any additional clothing besides the required tight fitting swimsuit leads to

57 48 inaccurate measurements of body density and thus body fat percent.20 In some studies, subjects followed the manufacturer recommended guideline of wearing swimsuits, whereas others had subjects wear spandex shorts, or in some cases clothing worn during Bod Pod testing was unclear. Variation seen between hydrostatic weighing and the Bod Pod could also be attributed to different equipment used for hydrostatic weighing between labs and different methods for measuring residual volume.31 Another possible cause of error is interdevice variation between Bod Pods, but this is less likely since all are manufactured by the same company. A study investigated interdevice variability in two Bod Pods in the same laboratory and found no clinically significant differences between the two devices in measurement of body density and body fat percent.32 Many researchers have since replicated the previously mentioned McCrory Bod Pod validation study to determine body composition outcomes in various populations and age groups.33'37 Overall, the studies found the Bod Pod to be a valid tool for measuring body fat percentage for high school and college age men and women, as well as for collegiate athletes of both sexes. Other recent studies evaluated the test-retest reliability of the Bod Pod as well as reliability over three different days No significant differences were found for within day and between day body fat and body density measurements, and the studies concluded the Bod Pod to be highly reliable.38,39 Another study by Biagget et al. did a cross-validation of the Bod Pod, hydrostatic weighing, and whole body BIA. BIA was measured using four electrodes, two attached to the right foot and two to the right hand while the subject was in supine. There was no

58 49 significant difference between total group body fat percent determined by BIA (23.9 ± 7.7%), Bod Pod (25.0 ± 8.9%), or hydrostatic weighing (25.1 ± 7.7%).40 There was also a significant correlation between the body fat percentages measured by all three methods when compared to one another. Compared to hydrostatic weighing, the Bod Pod significantly underestimated (P < 0.05) body fat in men (by ± 3.12%) and overestimated body fat in women (1.02 ± 2.48%). This was not observed in comparing BIA to hydrostatic weighing or to the Bod Pod. The authors suggested that a possible reason for the difference in body fat estimation between the sexes in the Bod Pod could be the amount of body hair. Though the men did not have beards, they did have more hair on other areas of their body than women did, which could have led to the underestimation. Numerous studies have demonstrated that whole-body BIA is a reliable and valid way to measure body composition.24'25,41-42 Because this method requires a trained technician and the set-up of electrodes, regional BIA devices are used more prevalently today. A study done by Nunez et al. compared body fat measurements using regional foot-to-foot BIA scale to whole body BIA and found that the results were comparable, and that the scale offers the advantages of increased speed and ease of measurement.43 The study also found the between day reliability for the foot-to-foot BIA scale ranged from 1.0% to 3.6%. Another study found the estimation of fat-free mass by foot-to-foot BIA scale to be comparable to fat-free mass measured by hydrostatic weighing in obese women44 The scale was also able to track body fat loss over time in obese individuals

59 50 with the same accuracy as hydrostatic weighing 44 Additionally, a study by Boneva- Asiova et al. done on both obese and non-obese adults found that body fat percent, fat mass, and fat-free mass measured by DEXA and foot-to-foot BIA were not significantly different.45 In contrast to the previous findings, Boneva-Asiova et al. also found that the limits of agreement between BIA and DEXA decreased with the increasing BMI of the subjects.45 This suggests that BIA may not be as accurate at measuring body composition in obese individuals. Additionally, Lazzer et al. and Goldfield et al. found that foot-tofoot BIA scales were not as accurate as DEXA in assessing body fat percent in obese adolescence and adults. Both studies concluded that though measurements of body fat percent correlated, the two methods should not be used interchangeably.46,47 Their findings also suggest that BIA devices may not be reliable for estimating body fat in certain populations because of the specific equation used by the devices. In all of the studies discussed thus far, the foot-to-foot BIA scales used were expensive clinical grade scales. Currently there is limited research on the reliability and validity of the less expensive commercial scales that are available to the public, such as the Aria scale. Peterson et al. compared the accuracy of four consumer grade BIA devices (two being foot-to-foot scales) on eighty-two white female participants aged 19 to 67 years old. The study compared body fat percent estimates to skin folds and Bod Pod measurements. All body fat measurements by commercial BIA devices were significantly correlated to the Bod Pod measurements (Pearson r range from to 0.795), but

60 51 significantly over estimated body fat percentage.48 Overall, the study found variable accuracy and reliability between the different consumer scales. Future Research The current research shows that the validity and accuracy of various body composition measurement methods has been well established in the literature. In theory, the accuracy of these different methods should be universally applied to all devices in any laboratory, but there is always the possibility of interdevice variability. The body composition measuring devices in the EPL have not been tested for their reliability or accuracy. The lab has also installed a new load cell for measuring body weight in the hydrostatic tank, which has not yet been tested for its validity. Additionally, prior to this investigation, the lab estimated residual lung volume, needed to determine body fat via hydrostatic weighing, by using a formula rather than directly measuring it. Further research is needed to determine the accuracy and reliability of this specific laboratory s methods for measurement of body fat percent. In addition, there is no research on the accuracy and reliability of the Fitbit Aria scale compared to industry gold standards. 1. Reliability The first question raised is that although the Bod Pod and BIA scales have been found to be reliable methods for measuring body composition, does the equipment specifically used in the EPL agree with the research. The first aim of the study is to

61 52 determine the reliability of the body composition measurement methods and devices used in EPL. To investigate this, a repeated measures design will be used to collect data for both day-to-day and week-to-week reliability of body fat percent. The SFSU hydrostatic tank, with a mechanical scale and load cell, a Bod Pod, and an Aria scale will be used to measure body fat percent. The participants will be 60 apparently healthy men and women between 18 and 45 years of age. To be included in the study, participants must be classified as low-risk by the ACSM risk stratification system and are not considered to be a vulnerable population.49 Exclusion criteria will include pregnancy, claustrophobia, and regular consumption of medications that may influence hydration. Female participants will be scheduled for testing between day five and day eighteen of their menstrual cycle to avoid potential problems with water retention that can occur during the menstrual cycle.50 Prior to testing, all participants must abstain from food or drink for three hours, use the rest room within thirty minutes of testing, not consume alcohol twenty-four hours prior, and not exercise at least twelve hours prior. The participants will make three visits to the EPL. During the first visit, residual volume will be measured using the oxygen rebreathing technique via a metabolic cart. Next, participants will have their body fat measured, in order, using the Bod Pod, Aria scale, and hydrostatic weighing. The second visit will be 24 hours after visit one, and visit three will be scheduled one week after visit one. All visits will be scheduled at the same time of day. During visits two and three,

62 53 only body fat will be measured using the same three methods as taken on visit one. Intraclass correlation will be used to compare measurement reliability over time. 2. Validity The second question raised is whether the SFSU Bod Pod and Aria scale are valid body composition measurement methods in comparison to hydrostatic weighting. Also, if the load cell used for hydrostatic weighing is valid compared to the mechanical scale. Furthermore, to what degree do the different body fat measurements from the three methods agree with one another? For example, if a client chooses to purchase body composition measurement services at the exercise physiology laboratory and also use a scale at home, such as the Aria scale, to monitor progress, it is important to know how the methods compare. Thus, the second study aim to test the validity of these measurements, as well as compare the within-subject measurements of body fat from all three methods. To investigate this, data will be used from the previously described study design to evaluate the validity of the measurements. The hydrostatic tank will be used as the gold standard to compare the body fat measurements taken by the Bod Pod and the Aria scale. The load cell measurements will be compared to the mechanical scale measurements to investigate the accuracy. Data will be analyzed using Bland-Altman plots to determine the level of agreement and mean bias among the Bod Pod, BIA, and hydrostatic weighing. The comparison of the load cell and mechanical scale measurements will be compared using Pearson s correlation coefficient.

63 54 3. Residual Volume Measurement This study will be the first to measure residual volume using the oxygen rebreathing technique on the metabolic carts in the EPL. Another aim of this investigation is to provide a more accurate method for determining residual volume in the lab rather than estimating it using an equation. Step by step directions for the oxygen rebreathing technique will be provided for the lab for future research and student use. Significance The anticipated significance of this study is to replicate validity and reliability results from previous research done on these body composition methods. It will provide information regarding the accuracy of body composition measuring tools used in the lab, which will be useful to future researchers, clients, and students

64 55 References 1. Romero-Corral, A., Somers, V.K., Sierra-Johnson, J., Thomas, R.J., Collazo- Clavell, M.L., Korinek, J., Allison, T.G., Batsis, J.A., Sert-Kuniyoshi, F.H., & Lopez-Jimenez, F. (2008). Accuracy of body mass index in diagnosing obesity in the adult general population. International Journal o f Obesity, 32: Pi-Sunyer, F.X. (2002). The obesity epidemic: pathophysiology and consequences of obesity. Obesity Research, 10 (suppl 2): 97S-104S. 3. Lee, C. D., Blair, S. N., & Jackson, A. S. (1999). Cardiorespiratory fitness, body composition, and all-cause and cardiovascular disease mortality in men. American Journal o f Clinical Nutrition, 69 (3): Burke, L. M., Loucks A. B., & Broad N. (2006). Energy and carbohydrate for training and recovery. Journal o f Sports Science, 24: Nelson, K. M., Weinsier, R. L., Long, C. L., & Schutz, Y. (1992). Prediction of resting energy expenditure from fat-free mass and fat mass. American Journal o f Clinical Nutrition, 56: Barandun, U., Knechtle, B., Knechtle, P., Klipstein, A., Rust, C. A., Rosemann, T., & Lepers, R. (2012). Running speed during training and percent body fat predict race time in recreational male marathoners. Open Access Journal o f Sports Medicine, 3: Knechtle, B., Wirth, A., Baumann, B., Knechtle, P., & Rosemann, T. (2010). Personal best time, percent body fat, and training are differently associated with

65 56 race time for male and female Ironman triathletes. Research Quarterly for Exercise and Sport, 81(1): Bale, P., Rowell, S., & Colley, E. (1985). Anthropometric and training characteristics of female marathon runners as determinants of distance running performanc q. Journal o f Sports Sciences, 3(2): Rust, C. A., Knechtle, B., Knechtle, P., & Rosemann, T. (2012). Similarities and differences in anthropometry and training between recreational male 100-km ultra-marathoners and marathoners. Journal o f Sports Sciences, 30(12): Smarter scale. Better results. Retrieved March 31, 2016, from Heymsfield, S.B., Wang, Z., Baumgartner, R.N., & Ross, R. (1997). Human body composition: advances in models and methods. Annual Review o f Nutrition, 17: Pietrobelli, A., Heymsfield, S.B., Wang, Z.M., & Gallagher, D. (2001). Multicomponent body composition models: recent advances and future directions. European Journal of Clinical Nutrition, 55: Siri, WE. (1961). Body composition from fluid spaces and density. Analysis of methods. In: Techniques for Measuring Body Composition. Brozek, J and Henschel, A, eds. Washington, DC: National Academy of Sciences, pp Wang, Z., Heshka, S., Wang, J., et al. (2003). Magnitude and variation of fat-free

66 57 mass density: a cellular-level body composition modeling study. American Journal o f Physiology and Endocrine Metabolism, 284: E267-E Brozek, J., Grande, F., Anderson, J.T., & Keys, A. (1963). Densitometric analysis of body composition: revision of some quantitative assumptions. Annals o f the New York Academy o f Sciences, 110: Behnke, A.R., Feen, B.G., & Welham, W.C. (1942). The specific gravity of healthy men. Body weight and volume as an index of obesity. Journal o f the American Medical Association, 118: Wilmore, J.H., Vodak, P.A., Parr, R.B., Girandola, R.N., and Billing, J.E. (1980). Further simplification of a method for determination of residual lung volume. Medicine and Science in Sports and Exercise, 12: Dempster P, & Aitkens, S. (1995). A new air displacement method for the determination of human body composition. Medicine and Science in Sports and Exercise, 27: McCrory, M.A., Mole, P.A., Gomez, T. D., Dewey, K.G., & Bemauer, E.M. (1998). Body composition by air displacement plethysmography by using predicted and measured thoracic gas volumes. Journal o f Applied Physiology, 84: Fields, D.A., Hunter, G.R., & Goran, M.I. (2000). Validation of the BOD POD with hydrostatic weighing: influence of body clothing. International Journal o f Obesity, 24:

67 Thomasset, A. (1962). Bio-electrical properties of tissue impedance measurements. Lyon Medical, 207: Hoffer, E.C., Meador C.K., & Simpson, D.C. (1969). Correlation of whole body impedance with total body water volume. Journal o f Applied Physiology, 27: Kushner, R.F. (1992). Bioelectric impedance analysis: a review of principles and applications. Journal o f the American College o f Nutrition, 11(2): Segal, K.R., Van Loan, M., Fitzgerald, P.I., Hodgdon, J.A., & Van Itallie, T.B. (1988). Lean body mass estimation by bioelectrical impedance analysis: a foursite cross validation study. American Journal o f Clinical Nutrition, 47: Lukaski, H.C. & Siders, W.A. (2003). Validity and accuracy of regional bioelectrical impedance devices to determine whole-body fatness. Nutrition, 19: Pietrobelli, A., Formica, C., Wang, Z., & Heymsfield, S.B. (1996). Dual-energy X-ray absorptiometry body composition model: review of physical concepts. American Journal o f Physiology, 271: E941-E Kraemer, W. J., Fleck, S. J., & Deschenes, M. R. (2012). Understanding and improving body composition. In Exercise physiology: Integrating theory and application (pp ). Baltimore, MD: Lippincott Williams & Wilkins. 28. Haarbo, J., Gotfredsen, A., Hassager, C., & Christiansen, C. (1991). Validation of body composition by dual x-ray absorptiometry (DEXA). Clinical Physiology,

68 59 11(4): Moon, J.R., Stout, J.R., Walter, A.A., Smith, A.E., Stock, M.S., Herda, T.J., Sherk, V.D., Young, K.C., Lockwood, C.M., Kendall, K.L., Fukuda, D.H., Graef, J.L., Cramer, J.T., Beck, T.W., & Esposito, E.N. (2011). Mechanical scale and load cell underwater weighing: a comparison of simultaneous measurements and the reliability of methods. The Journal o f Strength and Conditioning Research, 25(3): McCrory, M.A., Gomez, T.D., Bemauer, E.M., & Mole, P.A. (1995). Evaluation of a new air displacement plethysmograph for measuring human body composition. Medicine and Science o f Sports and Exercise, 27: Fields, D.A., Goran, M.I., & McCrory, M.A. (2002). Body-composition assessment via air-displacement plethysmography in adults and children: a review. American Journal o f Clinical Nutrition, 75: Ball, S.D. (2005). Interdevice variability in percent fat estimate using the bod pod. European Journal o f Clinical Nutrition, 59(9): Utter, A.C., Goss, F.L., Swan, P.D., Harris, G.S., Robertson, R.J., & Trone, G.A. (2002). Evaluation of air displacement for assessing body composition of collegiate wrestlers. Medicine and Science in Sports and Exercise, Moon, J.R., Hull, H.R., Tobkin, S.E., Teramoto, M., Karabulut, M, Roberts, M.D., Ryan, E.D., Kim, S.J., Dalbo, V.J., Walter, A.A., Smith, A.T., Cramer, J.T., & Stout, J.R. (2007). Percentage body fat estimations in college women using

69 60 field and laboratory methods: a three-compartment model approach. Journal o f the International Society o f Sports Nutrition, 4: Moon, J.R., Tobkin, S.E., Smith, A.E., Roberts, M.D., Ryan, E.D., Dalbo, V.J., Lockwood, C.M., Walter, A.A., Cramer, J.T., Beck, T.W., & Stout, J.R. (2008). Percentage body fat estimations in college men using field and laboratory methods: a three-compartment model approach. Dynamic Medicine, 7: Moon, J.R., Tobkin, S.E., Costa, P.B., Smalls, M, Mieding, W.K, O Kroy, J.A, Zoeller, R.F., & Stout, J.R. (2008). Validity of the BOD POD for assessing body composition in athletic high school boys. Journal o f Strength and Conditioning Research, 22: Moon, J.R., Eckerson, J.M., Tobkin, S.E., Smith, A.E., Lockwood, C.M., Water, A.A., Cramer, J.T., Beck, T.W., & Stout, J.R. (2009). Estimating body fat in NCAA Division I female athletes: a five-compartment model validation of laboratory methods. European Journal o f Applied Physiology, 105: Tucker, L.A, Lecheminant, J.D., & Bailey, B.W. (2014) Test-restest reliability of the bod pod: the effect of multiple assessments. Perceptual and Motor Skills, 118(2): Anderson, D.E. (2007). Reliability of air displacement plethysmography. Journal o f Strength and Conditioning Research, 21(1): Biaggi, R.R., Vollman, M.W., Nies, M.A., Brener, C.E., Flakoll, P.J., Levenhagen, D.K., Sun, M., Karabulut, Z., & Chen, K.Y. (1999). Comparison of

70 61 air-displacement plethysmography with hydrostatic weighing and bioelectrical impedance analysis for the assessment of body composition in healthy adults. American Journal o f Clinical Nutrition, 69: Segal, K.R., Gutin, B. Presta, E., Wang, J. & Van Itallie, T.B. (1985). Estimation of human body composition by electrical impedance methods: a comparative study.journal o f Applied Physiology, 58 (5): Ross, R., Leger, L., Martin, P., & Roy, R. (1989). Sensitivity of bioelectrical impedance to detect changes in human body composition. Journal o f Applied Physiology, 61 (4): Nunez, C. Gallagher, D., Visser, M., Pi-Sunyer, F.X., Wang, Z., & Heymsfield, S.B. (1997). Bioimpedance analysis: evaluation of leg-to-leg system based on pressure contact foot-pad electrodes. Medicine and Science in Sports and Exercise, 29 (4): Utter, A.C., Nieman, D.C., Ward, A.N., & Butterworth, D.E. (1999). Use of the leg-to-leg bioelectrical impedance method in assessing body-composition change in obese women. American Journal o f Clinical Nutrition, 69 (4): Boneva-Asiova, Z. & Boyanov, M.A. (2008). Body composition analysis by legto-leg bioelectrical impedance and dual-energy X-ray absorptiometry in nonobese and obese individuals. Diabetes, Obesity, and Metabolism, 10 (11): Lazzer, S., Boirie, Y., Meyer, M., & Vermorel, M. (2003). Evaluation of two

71 62 foot-to-foot bioelectrical impedance analyzers to assess body composition in overweight and obese adolescents. British Journal o f Nutrition, 90: Goldfield, G.S., Cloutier, P., Mallory, R., Prud homme, D., Parker, T., & Doucet, E. (2006). Validitity of foot-to-foot bioelectrical impedance analysis in overweight and obese children and parents. Journal o f Sports Medicine and Physical Fitness, 46 (3): Peterson, J.T., Repovich, W.E.S., & Parascand, C.R. (2011). Accuracy of consumer grade bioelectrical impedance analysis devices compared to air displacement plethysmography. International Journal o f Exercise Science, 4 (3): American College of Sports Medicine. Guidelines for Exercise Testing and Prescription. 9th ed. Lippincott, Williams, and Wilkins, Baltimore, Gleichauf, C. & Roe, D. (1989). The menstrual cycle s effect on the reliablity of bioimpedance measurements for assessing body composition. American Journal o f Clinical Nutrition, 50:

72 63 APPENDIX II Preparticipation Screening Questionnaire Name: Age: Date: Ethnicity: Directions: Write Yes next to any true statements below. Otherwise, leave it blank. Have you ever had a heart attack, heart surgery, stroke or any other cardiovascular event, including abnormal heart rhythms? Have you ever been diagnosed with cardiovascular disease, such as heart disease, atherosclerosis, or peripheral vascular disease? Have you ever been diagnosed with pulmonary /respiratory disease, such as asthma, emphysema, bronchitis, or cystic fibrosis? Have you ever been diagnosed with metabolic disease, such as diabetes mellitus, thyroid disorders, renal disease, or liver disease? Have you ever experienced any abnormal events during physical exertion (example: fainting, chest pain, unreasonable breathlessness)? Do you have joint or musculoskeletal problems that limit your physical activity? Have you ever been told by a medical professional that you have high blood pressure? Have you ever been told by a medical professional that you have high cholesterol? Have you ever been prescribed heart or blood pressure medications? Are you physically inactive (i.e., you get less than 30 min. of physical activity on at least 3 days per week)? Do you have a close blood relative who had a heart attack before age 55 (father or brother) or age 65 (mother or sister)? Participant s name (print): Participant s signature: Researcher s name: Researcher s signature: