Secondary Logo

Journal Logo

Effects of Acute and 2-Hour Postphysical Activity on the Estimation of Body Fat Made by the Bod Pod

Harrop, Bradley J.; Woodruff, Sarah J.

Journal of Strength and Conditioning Research: June 2015 - Volume 29 - Issue 6 - p 1527–1533
doi: 10.1519/JSC.0000000000000715
Original Research

Harrop, BJ and Woodruff, SJ. Effects of acute and 2-hour postphysical activity on the estimation of body fat made by the Bod Pod. J Strength Cond Res 29(6): 1527–1533, 2015—The Bod Pod has been found to be reliable/valid against several criterion methods, including hydrostatic weighing and dual-energy x-ray absorptiometry, and under different conditions, such as clothing, dehydrated states, and body temperature changes. However, questions remain regarding the effects of an acute bout of exercise. Therefore, the purpose was to determine the effects of an acute bout of exercise on the estimations made by the Bod Pod. Participants (15 men and 22 women) were of age 18–27 years and were currently exercising. Baseline Bod Pod measures were completed followed by a 30-minute cycling trial at 75% of maximum heart rate. Bod Pod measures were taken immediately after exercise and 2 hours after exercise. Differences between men and women were found at baseline between height (p < 0.001), weight (p < 0.001), body volume (BV; p < 0.001), and body density (Db; p < 0.001). Among men, body mass (p < 0.001), body fat percentage (%BF; p < 0.001), and BV (p < 0.001) decreased, whereas Db (p < 0.001) and body temperature (p < 0.001) increased directly after exercise; body mass (p < 0.001) and BV (p < 0.001) remained lower after 2 hours. Among women, body mass (p < 0.001) and BV (p < 0.001) decreased, whereas thoracic gas volume (p = 0.014) and temperature (p < 0.001) increased directly after exercise; body mass (p < 0.001) and BV (p < 0.001) remained lower, whereas %BF (p < 0.001) and Db (p = 0.006) remained higher 2 hours after exercise. These results suggest that a single bout of exercise immediately before Bod Pod testing seems to alter the estimate of %BF, and continues to affect the prediction 2 hours after exercise in women.

Department of Kinesiology, University of Windsor, Windsor, Ontario, Canada

Address correspondence to Sarah J. Woodruff,

Back to Top | Article Outline


The study of modern human body composition is over 100 years old, spanning several disciplines such as clinical nutrition, sport and exercise science, and medicine (17). Body composition research is divided into 3 interconnected areas: the organizational rules that guide the different levels of body composition, their measurement techniques, and biological factors that influence body composition (39). Body composition can be used to assess disease status (35), nutrition and its effects on disease (23), athletic performance (1), weight-sensitive sports (1,8), malnutrition (18), the administration of drug dosages (41), and muscle and bone atrophy during prolonged periods of immobilization or bed rest. Several techniques exist to estimate body fat percentage (%BF), including dual-energy x-ray absorptiometry (DXA; 29,38), skinfold measurements (17), near-infrared interactance (2), and hydrodensitometry (HD; 36,40). Developed in the 1990s, the Bod Pod (27) is very similar to HD except it uses air displacement to make an estimation of body density (Db) in lieu of water displacement (12).

The manufacturer of the Bod Pod currently recommends that individuals not eat, drink, or participate in any physical activity 2 hours before undergoing Bod Pod testing. This is an attempt to ensure that all individuals undergoing testing are at a normal and rested state before testing, as deviation in both body temperature and hydration status may affect the measurement made by the Bod Pod. Previous research (14) examined the effects of body temperature and moisture between Bod Pod trials (using HD) and reported that Db (0.01 g·cm−3) and body weight (0.8 kg) significantly increased, whereas corrected body volume (BV; 0.2 L) and %BF (1.79%) significantly decreased after an increase in body temperature (∼0.6° C). However, because of high-end athletes' training regiments, the likelihood of finding time in their busy schedule to meet the requirements of the Bod Pod's testing system is not likely. Furthermore, athletes may want to adjust their %BF to meet training or competition guidelines that may allow for a competitive edge against competitors.

Although the Bod Pod has been used to determine the effects of an exercise intervention in several studies (11,24,30), multiple clothing types and their effects on the estimations made by the Bod Pod (20) and covert body positions are assumed by participants in the Bod Pod (33). To the best of the authors' knowledge, the effects of an acute bout of exercise on the Bod Pod's ability to estimate %BF have not been examined. Therefore, the purpose of this study was to determine the effects of an acute bout of exercise on the Bod Pod's ability to estimate %BF. It is hypothesized that this single bout of moderate physical activity will affect the outcome measures (i.e., %BF).

Back to Top | Article Outline


Experimental Approach to Problem

No such research has questioned the effect of an acute bout of exercise on the Bod Pod's ability to measure %BF. A full description of the Bod Pod (7) can be found in Refs. 12,13,27. Furthermore, before data collection, a technician from COSMED ensured that the Bod Pod was functioning within normal parameters.

Before each testing session, environmental conditions were assessed, and there was no variation in these conditions through the testing procedures. As a short summary (Figure 1), before entering the Bod Pod, participants were asked to change into Bod Pod–specific clothing either spandex compression type shorts or speedo (men) or compression and a sports bra (no padding) or a bathing suit (women), and body weight is taken by the electric scale. Participants then entered the Bod Pod for 2 separate BV measures. If the 2 test measures differ by more than 150 ml, a third measurement occurs. At the end of this stage, a raw BV (Vbraw) is determined. However, because air in the lungs behaves isothermally (i.e., air in the lungs is 40% more compressible than air under adiabatic conditions), a measure of thoracic gas volume (TGV) is needed. After several cycles of normal breathing, participants are instructed to breathe normally through the breathing tube in accordance with a progression bar on the screen (i.e., to measure tidal volume), followed by instructions to huff (e.g., gentle puff) 3 times (i.e., to measure functional residual capacity). Using a proprietary formula, TGV is estimated using half of the tidal volume plus the functional residual capacity. Once completed, TGV is then used as a correction factor to determine a corrected BV. This is then used, along surface area artifact (i.e., a correction factor to account for the warm air nearest the skin), to determine Db. Once Db is calculated, Siri's (1961) equation was used to estimate %BF.

Figure 1

Figure 1

In the past, the Bod Pod's ability to estimate %BF has been validated against several criterion methods including DXA (5,6) and HD (24,37) showing good to excellent correlation of 0.89–0.91 and 0.88–0.92, respectively (6,22,28,37). The Bod Pod has also shown good validity in female Division II collegiate athletes (n = 12) and controls (n = 10) compared with DXA, reporting no significant differences in %BF between 2 consecutive trials (5). Similar results were also observed among collegiate football players (9) and in adults of various ethnicities (26,31).

This study used a pre-/posttest repeated-measures design under controlled conditions. Additionally, because of observed difficulties in obtaining a measured TGV using the Bod Pod in the Physical Activity and Cardiovascular Research (PACR) Lab at the University of Windsor and the known difficulties reported in the literature (3), a confirmatory methodology was performed to assess the stability of the TGV measure (i.e., to determine whether to measure TGV in this study).

Back to Top | Article Outline


The University of Windsor Research Ethics Board approved all procedures (REB #12–171), and informed consent was given before testing. Male (n = 18) and female (n = 27) participants were recruited from the University of Windsor through classroom visits, word of mouth, and a mass email sent throughout the Department of Kinesiology. Participants (n = 45) were determined to be current exercisers (exercising between 3 and 5 times a week), between the ages of 18 and 27 years, who have not competed in varsity sports in the past 2 years. Exercise frequency and intensity were established using a Demographic, Health, and Physical Activity Questionnaire, and physical activity was then validated using the Bodymedia SenseWear Mini Armband (BSA; Pittsburgh, PA).

Of the 18 male participants, 2 were unable to produce a valid TGV measurement(s) and did not complete the study. Of the 27 female participants, 4 individuals voluntarily withdrew, 1 was deemed not physically active, and 1 was removed from the exercise portion of the study as they were unable to produce a valid TGV measurement after exercise.

Back to Top | Article Outline


All participants were asked to report to the PACR Lab located in the Human Kinetics building at the University of Windsor for an initial meeting. Informed consent was obtained, and the Demographic, Health, and Physical Activity Questionnaire and the Physical Activity Readiness Questionnaire were filled out. Height and weight were measured using a wall-mounted tape measure (height) and the electronic scale from the Bod Pod (weight), and participants were asked to undergo a familiarization trial in the Bod Pod before being fitted with a BSA. The BSA was worn at all times with the exception of showering and swimming for the subsequent 7 days.

More specifically, the BSA was used to validate physical activity responses collected by the Demographic, Health, and Physical Activity Questionnaire. The BSA has been validated among several populations including adults between the ages of 18 and 60 years (16,19) and children between the ages of 11 and 15 years (4). In 1 study of 30 adults over 14 days, the armbands measured total energy expenditure to within 22 kcal[BULLET OPERATOR]d−1 compared with doubly labeled water, the current gold standard for measuring energy expenditure (19). The BSA has been shown to be valid at low- to moderate-intensity activities (16,21) and is well suited for evaluating activity levels in the general public. The BSA device (similar to a pedometer/accelerometer yet more sophisticated) is a small monitor that is worn on the upper left arm (over the triceps) and measures biaxial accelerometry, body heat loss, and galvanic skin response, which automatically calculates minute by minute total energy expenditure and metabolic equivalents (METs). There is no discomfort associated with wearing the BSA, and it can easily be worn under clothing. Participants were deemed active if they exceeded 3 METs for more than 30 minutes a day. This device was not able to collect data from 3 participants (e.g., time on body was less than 20 h·d−1), so the questionnaire was used to determine suitability in this study.

Participants were then asked to return to the PACR Lab at a later date to complete data collection. All participants were instructed to refrain from eating/drinking and participating in physical activity for 2 hours before testing (as per the manufacturer's specifications; 7). As female participants were included in this study, it was prudent to standardize the phase of menstrual cycles (15,27,33). All female participants were asked to return to the PACR Lab 3–5 days after completion of menses; thus, ensuring all female participants were within the same phase (follicular phase) of their menstrual cycle. On entering the PACR Lab, participants were asked to change into Bod Pod–specific clothing (i.e., compression spandex/lycra shorts or speedo for men and compression spandex/lycra shorts and sports bra without padding or bathing suit for women) and then underwent 5 consecutive Bod Pod tests (i.e., BV and TGV measurements) to confirm the stability of the TGV measurement. The final trial (trial 5) was used as the baseline trial for this study under the basic assumption that as participants became more comfortable with the testing protocol (i.e., TGV measurement), their results would be more accurate. Baseline body temperature was taken before the first Bod Pod test.

Before beginning exercise, participants were asked to change into exercise attire, including undergarments. Each participant was asked to exercise at 75% of heart rate maximum (220-age) for 30 minutes on a cycle ergometer. Heart rate was monitored using the Polar heart rate system (model E40), which includes a transducer that wraps around the participant's thorax and a display watch so that both the participant and researcher could monitor the heart rate. On completion, body temperature was taken, and participants were immediately instructed to change into their original Bod Pod clothing (i.e., to eliminate any error caused by sweat collected in clothing that would have been worn in the Bod Pod) and wipe away any sweat on the body.

Once the postexercise Bod Pod testing was completed, the participants were given a mouthful of water. Participants were instructed not to consume any additional water or food and were asked to return to the PACR Lab after 2 hours. On the return of the participant to the PACR Lab, a third body temperature measurement was taken, followed by a final Bod Pod.

Back to Top | Article Outline

Statistical Analyses

Data collected during this study were analyzed using SPSS software for Windows (v21.0; Armonk, NY). All analyses were completed separately for men and women, and the level of significance was set at p ≤ 0.05. Basic demographics were assessed using independent t tests. For the confirmatory analysis, individual within-subject repeated-measures analyses of variance (ANOVAs) were used to assess %BF, BV, body mass, and TGV over the 5 trials.

The effect of exercise on the Bod Pods ability to estimate %BF (dependent variable) was analyzed using separate within-subjects repeated-measures ANOVAs to determine the differences between the following independent variables: body mass, %BF, Db, TGV, BV, and body temperature over time. Trial 5 (from the confirmation portion of this study) was used as the baseline measurement to determine the effects of exercise on the estimations produced by the Bod Pod. Within-subject post hoc contrasts were used to determine differences among the 3 trials.

Back to Top | Article Outline


Basic demographics and measurements taken from baseline (trial 5) are presented in Table 1. Age ranged from 18 to 27 years (men: 18–27 years and women: 19–23 years). Significant differences between men and women were found in relation to height (p < 0.001), body mass (p < 0.001), TGV (p < 0.001), and BV (p < 0.001). No significant differences between men and women in reference to %BF and fat-free mass (percent) were observed. Men and women wore the BSA devices for an average of 22 hours, suggesting good compliance with this methodology.

Table 1

Table 1

Based on the confirmation analysis as reported in Table 2, TGV was not statistically significant between the trials for either sex. Therefore, the results supported Anderson's (2007) work and the use of measuring TGV during subsequent trials.

Table 2

Table 2

Among men and women, significant differences were found across baseline, postexercise, and 2-hour postexercise (Table 3) for body mass (p < 0.001), %BF (p = 0.001 men and p = 0.006 for women), Db (p < 0.001 men and p = 0.006 women), BV (p < 0.001), and temperature (p < 0.001). Additional differences were also seen in TGV (p < 0.001) for women only.

Table 3

Table 3

Back to Top | Article Outline


Although the Bod Pod has been widely used for research purposes to determine the effects of exercise interventions (11,25,30), no such research has questioned the effect of an acute bout of exercise on the Bod Pod's ability to measure %BF. The purpose of this study was, therefore, to determine the effects of an acute bout of physical activity on the ability of the Bod Pod to estimate %BF.

Several significant differences were found between baseline, postexercise, and 2-hour postexercise. The changes observed in body mass, in both men and women, could be due to the loss of water as a by-product of exercise (sweating; 32). It is generally accepted that for every kilogram lost from a preexercise weight that the body's hydration status decreases by 1–2% (10). Water is typically lost through sweat and during respiration. This may explain the decreased body mass seen immediately after exercise in both men and women (i.e., −0.39 and −0.26 kg, respectively), which in turn could affect the %BF measurement. In a study by Utter et al. (34), a decrease in hydration of 2–3% resulted in a decrease in total body mass of 2 kg or 2.6% body weight. This study did not replace water lost (e.g., only gave each participant a small mouthful of water), which may explain why body mass did not return to normal even 2 hours later. In fact, body mass was −0.55 kg (men) and −0.38 kg (women) lower 2 hours after exercise. A limitation of this study is a lack of valid/reliable measure of hydration status, which would be recommended to measure in future research. A possible explanation for this may have been the time between the subject's last meal (e.g., may have also decreased the subject's weight). Although all subjects were given the same instructions, some participants may have been in a fasted state for longer than others, depending on the time of testing during the day.

Significant changes were also observed for BV in both men and women. A potential explanation for these differences might be the changes in body temperature during the testing period (e.g., body temperature increased with the exercise protocol). The current results are similar to a study (14) that reported a decrease in BV after an increase in body temperature of ∼0.6° C. Furthermore, changes in body temperature may have been too rapid (i.e., half a degree in 30 minutes) for the correction factors used by the Bod Pod to take effect (14).

Finally, there were also several significant changes in %BF for both men and women (although the pattern differed). The immediate decrease in %BF observed among men could be a by-product of the increased temperature changes (discussed earlier). An earlier study (14) reported a decrease in both %BF and BV (corrected), whereas Db and body mass increased when the participant was warmed. As Db is a function of body mass and BV, changes in these variables would inevitably affect %BF. Once temperature returned to normal (2 hours after exercise), %BF returned to baseline values. However, among women, %BF significantly increased 2 hours after exercise. The increase in %BF among women may be a function of the higher TGV values observed. Once again, Fields et al. (14) also measured TGV but did not report a significant difference between TGV trials. As TGV was the only variable that was different between the patterns observed between men and women, it is plausible that the increase in TGV may have caused the %BF to be higher in women 2 hours after exercise. Although the results of this study have some practical implications, the results fall within the error rates of the Bod Pod (as reported in literature; 27). Therefore, it cannot be stated with certainty that these results are due to exercise alone and not caused by the error associated with the Bod Pod.

Back to Top | Article Outline

Practical Applications

The main objective of this study was to determine the effects of an acute bout of exercise on the Bod Pod's ability to estimate %BF. When examining the data, it is clear that the current recommendation put forth by COSMED (refraining from any physical activity for 2 hours) is not enough time for the Bod Pod to measure an individual under resting conditions. If an individual wished to manipulate their %BF measurement to gain a competitive advantage (i.e., weight-specific sports), a moderate bout of exercise lasting only 30 minutes would be sufficient to influence the %BF. Therefore, it is suggested that future research examine the necessary time needed for the body to return to resting levels so that accurate measurements of %BF are taken. Also, it may also be prudent to have a supervised rest period before testing to ensure that the subjects are in a rested state.

The Bod Pod is a quick (∼5 minutes per test) tool to estimate %BF that requires little technical expertise to operate it and is more comfortable for participants (compared with HD and DXA). The current findings suggest that moderate bout of exercise is enough to alter %BF readings made by the Bod Pod. Although the differences did not exceed the current error rates of the Bod Pod, practically speaking, if an individual wanted to alter their %BF, a single bout of moderate-intensity exercise would alter the results.

When considering the TGV measurement made by the Bod Pod, this study confirms findings reported by Anderson (3) implying that the TGV measure is stable. However, given the financial cost associated with the TGV measure (i.e., purchasing the breathing tubes), the difficulties reported in Anderson (3), and the significant difference observed by women in this study, it is suggested that predicted values be used in future estimations to decrease variability with test-retest situations. This will decrease testing time, frustration on the part of the participant, and the cost of future research.

Back to Top | Article Outline


The authors report that there is no conflict of interest in regard to this study. To the best of the authors' knowledge, there is no professional relationship with COSMED (manufacturers of the Bod Pod). This research project was supported by the Department of Kinesiology at the University of Windsor, and the results of this study do not constitute endorsement of the product by the authors or the NSCA.

Back to Top | Article Outline


1. Ackland TR, Lohman TG, Sundgot-Borgen J, Maughan RJ, Meyer NL, Stewart AD, Muller W. Current status of body composition assessment in sports: Review and position statement on behalf of the ad hoc research working group on body composition health and performance. Sports Med 42: 227–249, 2012.
2. American College of Sports Medicine. Health-Related Physical Fitness Testing and Interpretation, ACSM's Guidelines for Exercise Testing and Prescription. Baltimore, MD: Lippincott Williams & Wilkins, 2010. pp. 60–102.
3. Anderson D. Reliability of air displacement plethysmography. J Strength Cond Res 21: 169–172, 2007.
4. Arviddson D, Slinde F, Hulthen L. Free-living energy expenditure in children using multi-sensor activity monitors. Clin Nutr 28: 305–312, 2009.
5. Ballard TP, Fafara L, Vukovich MD. Comparison of Bod Pod and DXA in female collegiate athletes. Med Sci Sports Exerc 36: 731–735, 2004.
6. Bentzur KM, Kravitz L, Lockner DW. Evaluation of the Bod Pod for estimating percent body fat in collegiate track and field female athletes: A comparison of four methods. J Strength Cond Res 22: 1985–1991, 2008.
7. BOD POD. Gold Standard Operator's Manual. Concord, CA: Life Measurement, Inc, 2010.
8. Brito CK, Martins-Roas F, Brito I, Marins J, Cordova C, Franchini E. Methods of body-mass reduction by combat sport athletes. Int J Sport Nutr Exerc Metab 22: 89–97, 2012.
9. Collins MA, Millard-Shafford ML, Sparling PB, Snow TK, Rosskopf LB, Webb SA, Omer J. Evaluation of the BOD POD for assessing body fat in collegiate football players. Med Sci Sports Exerc 31: 1350–1356, 1999.
10. Coyle EF. Substrate utilization during exercise in active people. Am J Clin Nutr 61: 968S–979S, 1995.
11. de Silva PL, de Mello MT, Cheik NC, Sanches PL, Piano A, Corgosinho F, Damaso AR. The role of pro-inflamatory and anti-inflamatory adipokines on exercise-induced bronchospasm in obese adolescents undergoing treatment. Respir Care 57: 572–582, 2011.
12. Dempster P, Aitkens S. A new air displacement method for the determination of human body composition. Med Sci Sports Exerc 27: 1692–1697, 1995.
13. Fields DA, Goran MI, McCrory MA. Body composition assessment via air-displacement plethysmography in adults and children: A review. Am J Clin Nutr 75: 453–467, 2002.
14. Fields DA, Higgins PB, Hunter GR. Assessment of body composition by air-displacement plethysmography: Influence of body temperature and moisture. Dyn Med 3: 3–10, 2004.
15. Francek B. Influence of the Menstrual Cycle on Body Composition Determined by Air Displacement Plethysmography (Bod Pod) [Master's thesis]. Arcata, CA: Humboldt State University; 2008.
16. Fruin ML, Rankin JW. Validity of a multi-sensor armband in estimating rest and exercise energy expenditure. Med Sci Sports Exerc 36: 1063–1069, 2004.
17. Heymsfield SB, Lohman TG, Wang Z, Going SB, eds. Human Body Composition (2nd ed.). Champaign, IL: Human Kinetics Publishers, 2005.
18. Heymsfield SB, McManus C, Stevens V, Smith J. Muscle mass: Reliable indicator of protein-energy malnutrition severity and outcomes. Am J Clin Nutr 35: 1192–1199, 1982.
19. Johannsen DL, Calabro MA, Stewart J, Franke W, Rood JC, Welk GJ. Accuracy of armband monitors for measuring daily energy expenditure in healthy adults. Med Sci Sports Exerc 42: 2134–2140, 2010.
20. King GA, Fulkerson B, Evans MJ, Moreau KL, McLaughlin JE, Thompson DL. Effects of clothing type on validity of air-displacement plethysmography. J Strength Cond Res 20: 95–102, 2006.
21. King GA, Torres N, Potter C, Brooks TJ, Coleman KJ. Comparison of activity monitors to estimate energy cost of treadmill exercise. Med Sci Sports Exerc 36: 1244–1251, 2004.
22. Koda M, Tsuzuku S, Nino N, Shimokata H. Body composition by air displacement plethysmography in middle-aged and elderly Japanese. Comparison with dual-energy X-ray absorptiometry. Ann N Y Acad Sci 904: 484–488, 2000.
23. Lane JS, Magnon CP, Lane KT, Chan T, Hoyt DB, Greenfield S. Nutrition impacts the prevalence of peripheral arterial disease in the United States. J Vasc Surg 48: 897–904, 2008.
24. Levenhagen DK, Borel MJ, Welch DC, Piasecki JH, Piasecki DP, Chen KY, Flakoll PJ. A comparison of air displacement plethysmography with three other techniques to determine body fat in healthy adults. JPEN J Parenter Enteral Nutr 23: 293–299, 1999.
25. Malavolti M, Battistini NC, Dugoni M, Bagni B, Bagni I, Pietrobelli A. Effect of intense military training on body composition. J Strength Cond Res 22: 503–508, 2008.
26. McCrory MA, Gomez TD, Bernauer EM, Mole PA. Evaluation of a new air displacement plethysmograph for measuring human body composition. Med Sci Sports Exerc 27: 1686–1691, 1995.
27. Meijer GA, Westerterp KR, Saris WHM, ten Hoor F. Sleeping metabolic rate in relation to body composition and the menstrual cycle. Am J Clin Nutr 55: 637–640, 1992.
28. Miyatake N, Nonaka K, Fujii M. A new air displacement plethysmograph for the determination of Japanese body composition. Diabetes Obes Metab 1: 347–351, 1999.
29. Pietrobelli A, Formica C, Wang Z, Heymsfield SB. Dual-energy X-ray absorptiometry body composition model: Review of physical concepts. Am J Physiol 271: E941–E951, 1996.
30. Plasqui G, Soenen S, Westerterp-Plantenga MS, Westerterp KR. Measurement of longitudinal changes in body composition during weight loss and maintenance in overweight and obese subjects using air-displacement plethysmography in comparison with the deuterium dilution technique. Int J Obes (Lond) 35: 1124–1130, 2011.
31. Sardinha LB, Lohman TG, Teixeira PJ, Guedes DP, Going SB. Comparison of air displacement plethysmography with dual-energy X-ray absorptiometry and 3 field methods for estimating body composition in middle-aged men. Am J Clin Nutr 68: 786–793, 1998.
32. Sawka MN, Burke LM, Eichner ER, Maughan RJ, Montain SJ, Stachenfeld NS. American college of sports medicine position stand. Exercise and fluid replacement. Med Sci Sports Exerc 39: 377–390, 2007.
33. Symons JP, Sowers MF, Harlow SD. Relationship of body composition measures and menstrual cycle length. Ann Hum Biol 24: 107–116, 1997.
34. Utter AC, Goss FL, Swan PD, Harris GS, Robertson RJ, Trone GA. Evaluation of air displacement for assessing body composition of collegiate wrestlers. Med Sci Sports Exerc 35: 500–505, 2003.
35. Valerio CM, Zajdenverg L, de Oliveira JE, Mory PB, Moyses RS, Godoy-Matos AF. Body composition study by dual-energy x-ray absorptiometry in familial partial lipodystrophy: Finding new tools for an objective evaluation. Diabetol Metab Syndr 4: 40–46, 2012.
36. Wagner DR, Heyward VH. Validity of two-component models for estimating body fat of black men. J Appl Physiol (1985) 90: 649–686, 2001.
37. Wagner DR, Heyward VH, Gibson AL. Validation of air displacement plethysmography for assessing body composition. Med Sci Sports Exerc 32: 1339–1344, 2000.
38. Wang Z, Heymsfield SB, Chen Z, Zhu S, Pierson RN. Estimation of percentage body fat by dual-energy X-ray absorptiometry: Evaluation by in vivo human elemental composition. Phys Med Biol 55: 2619–2635, 2010.
39. Wang ZM, Heshka S, Pierson RN Jr, Heymsfield SB. Systematic organization of body-composition methodology: An overview with emphasis on component-based methods. Am J Clin Nutr 61: 457–465, 1995.
40. Ward A, Pollock ML, Jackson AS, Ayres JJ, Pape G. A comparison of body fat determined by underwater weighing and volume displacement. J Appl Physiol (1985) 234: E94–E96, 1978.
41. Wulfsohn NL, Joshi CW. Thopentone dosage based on lean body mass. Br J Anaesth 41: 516–521, 1969.

air displacement plethysmography; exercise; Bod Pod; body fat

Copyright © 2015 by the National Strength & Conditioning Association.