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Phenotyping in clinical nutrition

Reference values of body composition parameters for Vietnamese men and women

Abstract

Background

Body composition parameters are linked to cardio-metabolic risk. However, high-quality reference values of body composition are scarce, particularly in Asian population. The aim of study was to construct sex- and age-specific normative reference values of body composition for the Vietnamese population.

Methods

This study was designed as a cross-sectional investigation that involved 2700 women and 1459 men aged between 20 and 90 (average 48, SD 15) who were participants in the population-based Vietnam Osteoporosis Study. Whole-body composition parameters (e.g., fat mass and lean mass) and site-specific (head, arms, trunk, and legs) parameters were measured by dual-energy X-ray absorptiometry (Hologic Horizon). Reference curves for each parameter and anatomical site were constructed using the Generalized Additive Model for Location Scale and Shape modeling technique.

Results

Overall, 8% of women and 11% of men were classified as obese (body mass index ≥ 27.5 kg/m2). Most fat mass was deposited at the trunk (~50%), followed by the leg (~33%). Women had ~10% more body fat (relative to body weight) than men. However, whole-body lean mass was higher in men than women, with the average difference being ~13 kg. Moreover, men had more bone mineral content than women (2110 vs. 1600 g). We also provided a comparison of age-related changes in body composition parameters between Vietnamese and US Whites.

Conclusion

These data provide gender- and age-specific reference values of body composition parameters for Vietnamese population. These normative values provide health professionals and the public with a resource for interpretation of body composition data.

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Fig. 1: Age-related change in whole-body PBF (%) for women (left) and men (right).
Fig. 2: Age-related change in whole-body fat mass (kg) for women (left) and men (right).
Fig. 3: Age-related change in whole-body lean mass (kg) for women (left) and men (right).
Fig. 4: Age-related change in whole-body bone mineral content (g) for women (left) and men (right).

References

  1. Lee DH, Giovannucci EL. Body composition and mortality in the general population: a review of epidemiologic studies. Exp Biol Med. 2018;243:1275–85.

    Article  CAS  Google Scholar 

  2. Rolland Y, Gallini A, Cristini C, Schott AM, Blain H, Beauchet O, et al. Body-composition predictors of mortality in women aged ≥ 75 y: data from a large population-based cohort study with a 17-y follow-up. Am J Clin Nutr. 2014;100:1352–60.

    Article  CAS  Google Scholar 

  3. Bray GA, Heisel WE, Afshin A, Jensen MD, Dietz WH, Long M, et al. The science of obesity management: an Endocrine Society Scientific Statement. Endocr Rev. 2018;39:79–132.

    Article  Google Scholar 

  4. Gomez-Ambrosi J, Silva C, Galofre JC, Escalada J, Santos S, Millan D, et al. Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. Int J Obes. 2012;36:286–94.

    Article  CAS  Google Scholar 

  5. DeMarco VG, Aroor AR, Sowers JR. The pathophysiology of hypertension in patients with obesity. Nat Rev Endocrinol. 2014;10:364–76.

    Article  CAS  Google Scholar 

  6. Misra D, Fielding RA, Felson DT, Niu J, Brown C, Nevitt M, et al. Risk of knee osteoarthritis with obesity, sarcopenic obesity, and sarcopenia. Arthritis Rheumatol. 2019;71:232–7.

    Article  Google Scholar 

  7. Chen GC, Arthur R, Iyengar NM, Kamensky V, Xue X, Wassertheil-Smoller S, et al. Association between regional body fat and cardiovascular disease risk among postmenopausal women with normal body mass index. Eur Heart J. 2019;40:2849–55.

    Article  CAS  Google Scholar 

  8. Ho-Pham LT, Lai TQ, Nguyen MT, Nguyen TV. Relationship between body mass index and percent body fat in Vietnamese: implications for the diagnosis of obesity. PLoS ONE. 2015;10:e0127198.

    Article  Google Scholar 

  9. Pietrobelli A, Formica C, Wang Z, Heymsfield SB. Dual-energy X-ray absorptiometry body composition model: review of physical concepts. Am J Physiol. 1996;271:E941–51.

    CAS  PubMed  Google Scholar 

  10. Wang J, Thornton JC, Russell M, Burastero S, Heymsfield S, Pierson RN Jr. Asians have lower body mass index (BMI) but higher percent body fat than do whites: comparisons of anthropometric measurements. Am J Clin Nutr. 1994;60:23–8.

    Article  CAS  Google Scholar 

  11. Ho-Pham LT, Lai TQ, Nguyen ND, Barrett-Connor E, Nguyen TV. Similarity in percent body fat between white and Vietnamese women: implication for a universal definition of obesity. Obesity. 2010;18:1242–6.

    Article  Google Scholar 

  12. Pham DD, Lee SK, Shin C, Kim NH, Eisman JA, Center JR, et al. Koreans do not have higher percent body fat than Australians: implication for the diagnosis of obesity in Asians. Obesity. 2019;27:1892–7.

    Article  Google Scholar 

  13. Baim S, Leonard MB, Bianchi ML, Hans DB, Kalkwarf HJ, Langman CB, et al. Official positions of the International Society for Clinical Densitometry and executive summary of the 2007 ISCD Pediatric Position Development Conference. J Clin Densitom. 2008;11:6–21.

    Article  Google Scholar 

  14. Shepherd JA, Baim S, Bilezikian JP, Schousboe JT. Executive summary of the 2013 International Society for Clinical Densitometry Position Development Conference on Body Composition. J Clin Densitom. 2013;16:489–95.

    Article  Google Scholar 

  15. Kelly TL, Wilson KE, Heymsfield SB. Dual energy X-ray absorptiometry body composition reference values from NHANES. PLoS ONE. 2009;4:e7038.

    Article  Google Scholar 

  16. Imboden MT, Swartz AM, Finch HW, Harber MP, Kaminsky LA. Reference standards for lean mass measures using GE dual energy x-ray absorptiometry in Caucasian adults. PLoS ONE. 2017;12:e0176161.

    Article  Google Scholar 

  17. Ito H, Ohshima A, Ohto N, Ogasawara M, Tsuzuki M, Takao K, et al. Relation between body composition and age in healthy Japanese subjects. Eur J Clin Nutr. 2001;55:462–70.

    Article  CAS  Google Scholar 

  18. Ho-Pham LT, Nguyen TV. The Vietnam osteoporosis study: rationale and design. Osteoporos Sarcopenia. 2017;3:90–7.

    Article  Google Scholar 

  19. R Development Core Team. R: a language and environment for statistical computing. 2.7.0 ed. http://www.R-project.org. Vienna: R Foundation for Statistical Computing; 2008.

  20. Stasinopoulos DM, Rigby RA. Generalized additive models for location scale and shape (GAMLSS) in R. J R Stat Soc C. 2005;54:507–54.

    Article  Google Scholar 

  21. Cole TJ, Green PJ. Smoothing reference centile curves: the LMS method and penalized likelihood. Stat Med. 1992;11:1305–19.

    Article  CAS  Google Scholar 

  22. Stasinopoulos DM, Rigby RA, Heller RF, Voudouris V, De Bastiani F. Flexible regression and smoothing using GAMLSS in R. CRC Press, Boca Raton, Florida; 2017.

  23. Berman NG, Wong WK, Bhasin S, Ipp E. Applications of segmented regression models for biomedical studies. Am J Physiol. 1996;270:E723–32.

    CAS  PubMed  Google Scholar 

  24. Muggeo VMR. segmented: an R package to fit regression models with broken-line relationships. R News. 2008;8:20–5.

    Google Scholar 

  25. Wilson JP, Kanaya AM, Fan B, Shepherd JA. Ratio of trunk to leg volume as a new body shape metric for diabetes and mortality. PLoS ONE. 2013;8:e68716.

    Article  CAS  Google Scholar 

  26. Snijder MB, Dekker JM, Visser M, Bouter LM, Stehouwer CD, Yudkin JS, et al. Trunk fat and leg fat have independent and opposite associations with fasting and postload glucose levels: the Hoorn study. Diabetes Care. 2004;27:372–7.

    Article  Google Scholar 

  27. Aasen G, Fagertun H, Halse J. Body composition analysis by dual X-ray absorptiometry: in vivo and in vitro comparison of three different fan-beam instruments. Scand J Clin Lab Invest. 2006;66:659–66.

    Article  CAS  Google Scholar 

  28. Min KB, Min JY. Android and gynoid fat percentages and serum lipid levels in United States adults. Clin Endocrinol. 2015;82:377–87.

    Article  CAS  Google Scholar 

  29. Santanasto AJ, Goodpaster BH, Kritchevsky SB, Miljkovic I, Satterfield S, Schwartz AV, et al. Body composition remodeling and mortality: the health aging and body composition study. J Gerontol A Biol Sci Med Sci. 2017;72:513–9.

    PubMed  Google Scholar 

  30. Jackson AS, Stanforth PR, Gagnon J, Rankinen T, Leon AS, Rao DC, et al. The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study. Int J Obes Relat Metab Disord. 2002;26:789–96.

    Article  CAS  Google Scholar 

  31. Womersley J. A comparison of the skinfold method with extent of ‘overweight’ and various weight-height relationships in the assessment of obesity. Br J Nutr. 1977;38:271–84.

    Article  CAS  Google Scholar 

  32. O’Sullivan AJ. Does oestrogen allow women to store fat more efficiently? A biological advantage for fertility and gestation. Obes Rev. 2009;10:168–77.

    Article  Google Scholar 

  33. Brown LM, Clegg DJ. Central effects of estradiol in the regulation of food intake, body weight, and adiposity. J Steroid Biochem Mol Biol. 2010;122:65–73.

    Article  CAS  Google Scholar 

  34. Power ML, Schulkin J. Sex differences in fat storage, fat metabolism, and the health risks from obesity: possible evolutionary origins. Br J Nutr. 2008;99:931–40.

    Article  CAS  Google Scholar 

  35. Ho-Pham LT, Lai TQ, Nguyen ND, Barrett-Connor E, Nguyen TV. Similarity in percent body fat between white and Vietnamese women: implication for a universal definition of obesity. Obesity. 2010;18:1242–6.

    Article  Google Scholar 

  36. Consultation WHOE. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363:157–63.

    Article  Google Scholar 

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Acknowledgements

We sincerely thank MS Tran Thi Ngoc Trang and Fr Pham Ba Lam for coordinating the recruitment of participants. We also thank doctors and medical students of the Pham Ngoc Thach University of Medicine for the data collection and clinical measurements.

Funding

This research is funded by the Foundation for Science and Technology Development of Ton Duc Thang University (FOSTECT, http://fostect.tdt.edu.vn), Grant number FOSTECT.2014.BR.09, and a grant from the Department of Science and Technology of Ho Chi Minh City. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

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Contributions

Conceived and designed the experiments: TVN, LTHP, and HGN. Performed the experiments: TVN, LTHP, NVL, and KHND. Analyzed the data: HGN and TVN. Wrote the paper: HGN, LTHP, and TVN.

Corresponding author

Correspondence to Lan T. Ho-Pham.

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The authors declare that they have no conflict of interest.

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Nguyen, H.G., Le, N.V., Nguyen-Duong, K.H. et al. Reference values of body composition parameters for Vietnamese men and women. Eur J Clin Nutr 75, 1283–1290 (2021). https://doi.org/10.1038/s41430-020-00840-y

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