Perceptions of Body Composition Measurement Instruments: A Pilot Study Original Research
Main Article Content
Keywords
body analysis, fat-free measurement, qualitative analysis
Abstract
Introduction: The purpose of this study was to explore collegiate student-athletes’ perceptions of undergoing three common body composition assessments: bioelectrical impedance (BIA; Tanita), digital anthropometry (DA; Fit3D), and hydrostatic weighing (HW).
Methods: Twenty male (n=8) and female (n=12) NCAA Division I collegiate athletes (age: 19.6 ± 1.6 yrs.) underwent three body composition assessments in the following order: BIA, followed by DA, and HW. Following the three body composition assessments, participants completed questionnaires regarding their demographic and perceptions towards the various body composition assessments. Data was analyzed for themes using a phenomenological qualitative design.
Results: Ten (50%) of the participants selected the BIA as their preferred method while 8 (40%) chose HW. Only 2 (10%) participants selected DA. Four themes emerged from the qualitative data analysis. Theme 1 - Ease of use and timely measurements; Theme 2 - Accuracy is important; Theme 3 - Body composition instruments are fun to use; Theme 4 - Sense of curiosity and novelty. Participants reported a positive experience undergoing these three body composition assessments.
Conclusions: The emergent themes revealed participants are genuinely concerned with their data/scores while placing importance on accuracy and ease of use. Study results show the importance of considering participant experiences in body composition measurement protocols.
References
2. A'Naja MN, Reed R, Sansone J, Batrakoulis A, McAvoy C & Parrott MW. 2024 ACSM worldwide fitness trends: future directions of the health and fitness industry. ACSM's Health Fit J. 2024;28(1):14-26.
3. National Heart Lung and Blood Institute. Study reveals wearable device trends among U.S. adults. 2023. Available at: https://www.nhlbi.nih.gov/news/2023/study-reveals-wearable-device-trends-among-us-adults.
4. Statista. Most used eHealth tracker/smart watches by brand in the U.S. 2024. 2025. Available at: https://www.statista.com/forecasts/997195/most-used-ehealth-tracker-smart-watches-by-brand-in-the-us.
5. Best Buy. Apple Watch. 2025. Available at: https://www.google.com/search?q=https://www.bestbuy.com/site/wearable-technology/apple-watch-device-accessories.
6. Kuriyan R. Body composition techniques. Indian J Med Res. 2018;148(5):648-658.
7. Wells JCK & Fewtrell MS. Measuring body composition. Arch Dis Child. 2006;91(7):612-617.
8. Dexa Plus. Dexa Plus. 2025. Available at: https://dexaplus.com/.
9. Block Imaging. Block Imaging. 2025. Available at: https://www.blockimaging.com.
10. Duren DL, Sherwood RJ, Czerwinski SA et al. Body composition methods: comparisons and interpretation. J Diabetes Sci Technol. 2008;2(6):1139-1146.
11. López-Taylor JR, González-Mendoza RG, Gaytán-González A et al. Accuracy of anthropometric equations for estimating body fat in professional male soccer players compared with DXA. J Sports Med. 2018;2018(1):6843792.
12. Williams DM, Rhodes RE & Conner MT. Psychological hedonism, hedonic motivation, and health behavior. Affect Determinants Health Behav. 2018;204:205-234.
13. Anderson LJ, Erceg DN & Schroeder ET. Utility of multifrequency bioelectrical impedance compared with dual-energy x-ray absorptiometry for assessment of total and regional body composition varies between men and women. Nutr Res. 2012;32(7):479-485.
14. Moon JR, Stout JR, Smith-Ryan AE et al. Tracking fat-free mass changes in elderly men and women using single-frequency bioimpedance and dual-energy X-ray absorptiometry: a four-compartment model comparison. Eur J Clin Nutr. 2013;67(1):S40-S46.
15. Stone TM, Wingo JE, Nickerson BS & Esco MR. Comparison of bioelectrical impedance analysis and dual-energy x-ray absorptiometry for estimating bone mineral content. Int J Sport Nutr Exerc Metab. 2018;28(5):542-546.
16. LaForgia J, Gunn SM & Withers RT. Body composition: validity of segmental bioelectrical impedance analysis. Asia Pac J Clin Nutr. 2008;17(4).
17. Ling CH, de Craen AJ, Slagboom PE et al. Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adult population. Clin Nutr. 2011;30(5):610-615.
18. Mocini E, Cammarota C, Frigerio F et al. Digital anthropometry: A systematic review on precision, reliability and accuracy of most popular existing technologies. Nutrients. 2023;15(2):302.
19. Ng BK, Hinton BJ, Fan B, Kanaya AM & Shepherd JA. Clinical anthropometrics and body composition from 3D whole-body surface scans. Eur J Clin Nutr. 2016;70(11):1265-1270.
20. Minetto MA, Pietrobelli A, Busso C, Bennett JP, Ferraris A, Shepherd JA, Heymsfield SB. Digital Anthropometry for Body Circumference Measurements: European Phenotypic Variations throughout the Decades. Journal of Personalized Medicine. 2022; 12(6):906. https://doi.org/10.3390/jpm12060906
21. Lohman T & Milliken LA. ACSM's Body Composition Assessment. Human Kinetics; 2019.
22. Creswell JW. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 3rd ed. Sage Publications, Inc; 2009.
23. Patton MQ. Qualitative Research & Evaluation Methods: Integrating Theory and Practice. Sage Publications; 2014.
24. Kim Y & Lee O. Exploring the phenomenological meanings of assessment in physical education through primary teachers’ lived experiences. Phys Educ Sport Pedagogy. 2021;27(6):578–590.
25. Pridgeon L & Grogan S. Understanding exercise adherence and dropout: An interpretative phenomenological analysis of men and women’s accounts of gym attendance and non-attendance. Qual Res Sport Exerc Health. 2012;4(3):382-399.
26. Rossman GB, Rallis SF. An Introduction to Qualitative Research: Learning in the Field. 4th ed. SAGE Publications; 2016.
27. Denzin NK. The Research Act: A Theoretical Introduction to Sociological Methods. McGraw-Hill; 1978.
28. Fit3D. Fit3D overview - 3D body scanning technology. Fit3D. Published 2025. Accessed December 31, 2025. https://www.fit3d.com/Fit3D.
29. Bose D, Saha S, Saxena U et al. Factors influencing recruitment and retention of participants in clinical studies conducted at a tertiary referral center: a five-year audit. Perspect Clin Res. 2020;11(2):81-85.
30. Ceniccola GD, Castro MG, Piovacari SMF et al. Current technologies in body composition assessment: advantages and disadvantages. Nutrition. 2019;62:25-31.
31. Emmerich SD, Fryar CD, Stierman B & Ogden CL. Obesity and severe obesity prevalence in adults: United States, August 2021–August 2023. NCHS Data Brief No. 508. Hyattsville, MD: National Center for Health Statistics. 2024.
32. Ng M, Dai X, Cogen RM et al. National-level and state-level prevalence of overweight and obesity among children, adolescents, and adults in the USA, 1990–2021, and forecasts up to 2050. Lancet. 2024;404(10469):2278-2298.
33. Attia P. Outlive: The Science and Art of Longevity. Harmony; 2023.
34. Kim Y, White T, Wijndaele K et al. The combination of cardiorespiratory fitness and muscle strength, and mortality risk. Eur J Epidemiol. 2018;33:953-964.
35. Metter EJ, Talbot LA, Schrager M & Conwit R. Skeletal muscle strength as a predictor of all-cause mortality in healthy men. J Gerontol A Biol Sci Med Sci. 2002;57(10):B359-B365.
36. Strasser B & Burtscher M. Survival of the fittest: VO2max, a key predictor of longevity. Front Biosci (Landmark Ed). 2018;23(8):1505-1516.
Article Sidebar
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright, 2026 by the authors. This work is licensed under the Creative Commons Attribution 4.0 International License.