Mapping Body Composition and Metabolic Risk Patterns Among Late Adolescents and Young Adults Using BIA

Authors

  • Akhitha Kangoju Department of Clinical Nutrition and Dietetics, Padmashree Institute of Management and Sciences, Bangalore Author
  • Stanzin Wangmo Department of Clinical Nutrition and Dietetics, Padmashree Institute of Management and Sciences, Bangalore Author
  • Saniya Siddiqua Department of Clinical Nutrition and Dietetics, Padmashree Institute of Management and Sciences, Bangalore Author
  • Akshatha K Department of Clinical Nutrition and Dietetics, Padmashree Institute of Management and Sciences, Bangalore, India Author https://orcid.org/0009-0006-9670-9816

DOI:

https://doi.org/10.63750/mfhctx25

Keywords:

Body composition, Bioelectrical impedance analysis, Metabolic risk, Late adolescents, Lifestyle

Abstract

Background: Lifestyle behaviours during late adolescence and young adulthood significantly influence body composition and future metabolic health. This study evaluates lifestyle, body composition and metabolic risk indicators in late adolescents and examines the influence of age and gender.

Methods: A total of 138 participants aged 18 to 25 years were enrolled in this cross-sectional study. Lifestyle data along with a structured questionnaire and body composition, were assessed. Statistical analyses included the chi-square test, considered statistically significant (p < 0.05).

Results: Among participants, 74.6% were females and 63.0% were aged 18- 21 years. Non-vegetarian dietary habits were predominant (62.3%) and lack of time was the major barrier to physical activity (50.0%). Most participants consumed 6-8 glasses of water daily (42.0%), while 88.4% reported sleeping less than 6 hours per night. Body composition assessment revealed high body fat mass in 61.6% of participants, with 64.5% having normal BMI and 18.1% having elevated BMI. Significant gender differences were observed in total body water (χ²=52.01, p<0.05), waist-to-hip ratio (χ²=7.51, p<0.05), body score (t=2.13, p<0.05) and body composition-related health conditions (χ²=5.58, p<0.05). Females showed higher body fat mass, obesity grade, and waist-to-hip ratio, whereas males had higher total body water, basal metabolic rate, and body scores. Age was significantly associated with BMI distribution (χ² = 7.94, p < 0.05).

Conclusion: Body composition varied significantly by age and gender among young adults. This highlights the importance of early screening and lifestyle interventions. BIA may be useful for identifying individuals at risk of future metabolic disorders.

Downloads

Download data is not yet available.

References

Adam, T. C., & Epel, E. S. (2007). Stress, eating and the reward system. Physiology & Behavior, 91(4), 449–458. https://doi.org/10.1016/j.physbeh.2007.04.011

Ashwell, M., Gunn, P., & Gibson, S. (2012). Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: Systematic review and meta-analysis. Obesity Reviews, 13(3), 275–286. https://doi.org/10.1111/j.1467-789X.2011.00952.x

Brach, J. S., Simonsick, E. M., Kritchevsky, S., Yaffe, K., Newman, A. B., & Health, Aging and Body Composition Study Research Group. (2004). The association between physical function and lifestyle activity and exercise in the Health, Aging and Body Composition Study. Journal of the American Geriatrics Society, 52(4), 502–509. https://doi.org/10.1111/j.1532-5415.2004.52154.x

Buysse, D. J. (2014). Sleep health: Can we define it? Does it matter? Sleep, 37(1), 9–17. https://doi.org/10.5665/sleep.3298

Chaput, J.-P., McHill, A. W., Cox, R. C., Broussard, J. L., Dutil, C., da Costa, B. G. G., Sampasa-Kanyinga, H., & Wright, K. P., Jr. (2023). The role of insufficient sleep and circadian misalignment in obesity. Nature Reviews Endocrinology, 19(2), 82–97. https://doi.org/10.1038/s41574-022-00747-7

Cunningham, J. J. (1980). A reanalysis of the factors influencing basal metabolic rate in normal adults. The American Journal of Clinical Nutrition, 33(11), 2372–2374. https://doi.org/10.1093/ajcn/33.11.2372

Gallagher, D., Heymsfield, S. B., Heo, M., Jebb, S. A., Murgatroyd, P. R., & Sakamoto, Y. (2000). Healthy percentage body fat ranges: An approach for developing guidelines based on body mass index. The American Journal of Clinical Nutrition, 72(3), 694–701. https://doi.org/10.1093/ajcn/72.3.694

Gupta, S., Sunder, N., & Pingali, P. L. (2020). Market access, production diversity, and diet diversity: Evidence from India. Food and Nutrition Bulletin, 41(2), 167–185. https://doi.org/10.1177/0379572120920061

Hall, K. D., Ayuketah, A., Brychta, R., Cai, H., Cassimatis, T., Chen, K. Y., Chung, S. T., Costa, E., Courville, A., Darcey, V., Fletcher, L. A., Forde, C. G., Gharib, A. M., Guo, J., Howard, R., Joseph, P. V., McGehee, S., Ouwerkerk, R., Raisinger, K., ... Zhou, M. (2019). Ultra-processed diets cause excess calorie intake and weight gain: An inpatient randomized controlled trial of ad libitum food intake. Cell Metabolism, 30(1), 67–77. https://doi.org/10.1016/j.cmet.2019.05.008

Hruby, A., & Hu, F. B. (2015). The epidemiology of obesity: A big picture. PharmacoEconomics, 33(7), 673–689. https://doi.org/10.1007/s40273-014-0243-x

Jackson, A. S., Stanforth, P. R., Gagnon, J., Rankinen, T., Leon, A. S., Rao, D. C., Skinner, J. S., Bouchard, C., & Wilmore, J. H. (2002). The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study. International Journal of Obesity, 26(6), 789–796. https://doi.org/10.1038/sj.ijo.0802006

Janssen, I., Katzmarzyk, P. T., & Ross, R. (2004). Waist circumference and not body mass index explains obesity-related health risk. The American Journal of Clinical Nutrition, 79(3), 379–384. https://doi.org/10.1093/ajcn/79.3.379

Johnstone, A. M., Murison, S. D., Duncan, J. S., Rance, K. A., & Speakman, J. R. (2005). Factors influencing variation in basal metabolic rate include fat-free mass, fat mass, age, and circulating thyroxine but not sex, circulating leptin, or triiodothyronine. The American Journal of Clinical Nutrition, 82(5), 941–948. https://doi.org/10.1093/ajcn/82.5.941

Keating, X. D., Guan, J., Piñero, J. C., & Bridges, D. M. (2005). A meta-analysis of college students' physical activity behaviors. Journal of American College Health, 54(2), 116–126. https://doi.org/10.3200/JACH.54.2.116-126

Kivimäki, M., Bartolomucci, A., & Kawachi, I. (2023). The multiple roles of life stress in metabolic disorders. Nature Reviews Endocrinology, 19(1), 10–27. https://doi.org/10.1038/s41574-022-00746-8

Kyle, U. G., Bosaeus, I., De Lorenzo, A. D., Deurenberg, P., Elia, M., Gómez, J. M., Heitmann, B. L., Kent-Smith, L., Melchior, J. C., Pirlich, M., Scharfetter, H., Schols, A. M. W. J., & Pichard, C. (2004a). Bioelectrical impedance analysis—Part I: Review of principles and methods. Clinical Nutrition, 23(5), 1226–1243. https://doi.org/10.1016/j.clnu.2004.06.004

Kyle, U. G., Bosaeus, I., De Lorenzo, A. D., Deurenberg, P., Elia, M., Gómez, J. M., Heitmann, B. L., Kent-Smith, L., Melchior, J. C., Pirlich, M., Scharfetter, H., Schols, A. M. W. J., & Pichard, C. (2004b). Bioelectrical impedance analysis—Part II: Utilization in clinical practice. Clinical Nutrition, 23(6), 1430–1453. https://doi.org/10.1016/j.clnu.2004.09.012

Lund, H. G., Reider, B. D., Whiting, A. B., & Prichard, J. R. (2010). Sleep patterns and predictors of disturbed sleep in a large population of college students. Journal of Adolescent Health, 46(2), 124–132. https://doi.org/10.1016/j.jadohealth.2009.06.016

Ng, M., Fleming, T., Robinson, M., Thomson, B., Graetz, N., Margono, C., Mullany, E. C., Biryukov, S., Abbafati, C., Abera, S. F., Abraham, J. P., Abu-Rmeileh, N. M. E., Achoki, T., AlBuhairan, F. S., Alemu, Z. A., Alfonso, R., Ali, M. K., Ali, R., Guzman, N. A., ... Gakidou, E. (2014). Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: A systematic analysis for the Global Burden of Disease Study 2013. The Lancet, 384(9945), 766–781. https://doi.org/10.1016/S0140-6736(14)60460-8

Patel, S. R., & Hu, F. B. (2008). Short sleep duration and weight gain: A systematic review. Obesity, 16(3), 643–653. https://doi.org/10.1038/oby.2007.118

Popkin, B. M. (2017). Relationship between shifts in food system dynamics and acceleration of the global nutrition transition. Nutrition Reviews, 75(2), 73–82. https://doi.org/10.1093/nutrit/nuw064

Saleh, D., Camart, N., & Romo, L. (2017). Predictors of stress in college students. Frontiers in Psychology, 8, Article 19. https://doi.org/10.3389/fpsyg.2017.00019

Stefan, N., Häring, H.-U., Hu, F. B., & Schulze, M. B. (2013). Metabolically healthy obesity: Epidemiology, mechanisms, and clinical implications. The Lancet Diabetes & Endocrinology, 1(2), 152–162. https://doi.org/10.1016/S2213-8587(13)70062-7

Torres, S. J., & Nowson, C. A. (2007). Relationship between stress, eating behavior, and obesity. Nutrition, 23(11–12), 887–894. https://doi.org/10.1016/j.nut.2007.08.008

Vadeboncoeur, C., Townsend, N., & Foster, C. (2015). A meta-analysis of weight gain in first year university students: Is freshman 15 a myth? BMC Obesity, 2, Article 22. https://doi.org/10.1186/s40608-015-0051-7

Wells, J. C. K. (2007). Sexual dimorphism of body composition. Best Practice & Research Clinical Endocrinology & Metabolism, 21(3), 415–430. https://doi.org/10.1016/j.beem.2007.04.007

Willett, W., Rockström, J., Loken, B., Springmann, M., Lang, T., Vermeulen, S., Garnett, T., Tilman, D., DeClerck, F., Wood, A., Jonell, M., Clark, M., Gordon, L. J., Fanzo, J., Hawkes, C., Zurayk, R., Rivera, J. A., De Vries, W., Majele Sibanda, L., ... Murray, C. J. L. (2019). Food in the Anthropocene: The EAT–Lancet Commission on healthy diets from sustainable food systems. The Lancet, 393(10170), 447–492. https://doi.org/10.1016/S0140-6736(18)31788-4

Downloads

Published

2026-09-30

Issue

Section

Research Articles

How to Cite

Kangoju, A., Wangmo, S., Siddiqua, S., & K, A. (2026). Mapping Body Composition and Metabolic Risk Patterns Among Late Adolescents and Young Adults Using BIA. Global Journal of Sport and Exercise Science, 2(3), 110-131. https://doi.org/10.63750/mfhctx25

Share

Similar Articles

1-10 of 27

You may also start an advanced similarity search for this article.