Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Paper
  • Published:

The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study

Abstract

Objective: To study the effects of sex, age and race on the relation between body mass index (BMI) and measured percent body fat (%fat).

Design: Cross-sectional validation study of sedentary individuals.

Subjects: The Heritage Family Study cohort of 665 black and white men and women who ranged in age from 17 to 65 y.

Measurements: Body density determined from hydrostatic weighing. Percentage body fat determined with gender and race-specific, two-compartment models. BMI determined from height and weight, and sex and race in dummy coded form.

Results: Polynomial regression showed that the relationship between %fat and BMI was quadratic for both men and women. A natural log transformation of BMI adjusted for the non-linearity. Test for homogeneity of log transformed BMI and gender showed that the male–female slopes were within random variance, but the intercepts differed. For the same BMI, the %fat of females was 10.4% higher than that of males. General linear models analysis of the women's data showed that age, race and race-by-BMI interaction were independently related to %fat. The same analysis applied to the men's data showed that %fat was not just a function of BMI, but also age and age-by-BMI interaction. Multiple regression analyses provided models that defined the bias.

Conclusions: These data and results published in the literature show that BMI and %fat relationship are not independent of age and gender. These data showed a race effect for women, but not men. The failure to adjust for these sources of bias resulted in substantial differences in the proportion of subjects defined as obese by measured %fat.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1

Similar content being viewed by others

References

  1. Kuczmarski RJ, Flegal KM . Criteria for definition of overweight in transition: background and recommendations for the United States Am J Clin Nutr 2000 72: 1075–1081.

    Article  Google Scholar 

  2. McDowell A, Engel A, Massey J, Maurer K . Plan and operation of the second National Health and Nutrition Examination Survey, 1976–80 Series 1, 15, DHHS publication (PHS) 81-1317 US Government Printing Office: Washington, DC 1981.

    Google Scholar 

  3. World Health Organization. Obesity: preventing and managing the global epidemic Report of a WHO consultation on obesity World Health Organization: Geneva 1998.

  4. National Institutes of Health and National Heart Lung and Blood, Institute. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the Evidence Report Obes Res 1998 6 (Suppl 2): 515–209.

  5. Gallagher D, Visser M, Sepulveda D, Pierson RN, Harris T, Heymsfield SB . How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups Am J Epidemiol 1996 143: 228–239.

    Article  CAS  PubMed  Google Scholar 

  6. Deurenberg-Yap M, Schmidt G, van Staveren WA, Deurenberg P . The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore Int J Obes Relat Metab Disord 2000 24: 1011–1017.

    Article  CAS  PubMed  Google Scholar 

  7. Deurenberg P, Weststrate JA, Seidell JC . Body mass index as a measure of body fatness: age- and sex-specific prediction formulas Br J Nutr 1991 65: 105–114.

    Article  CAS  PubMed  Google Scholar 

  8. Deurenberg P, Yap M, van Staveren WA . Body mass index and percent body fat. A meta analysis among different ethnic groups Int J Obes Relat Metab Disord 1998 22: 1164–1171.

    Article  CAS  PubMed  Google Scholar 

  9. Womersley J, Durnin JVGA . 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: 271–284.

    Article  CAS  PubMed  Google Scholar 

  10. Deurenberg-Yap M, Schmidt G, van Staveren WA, Hautvast JG, Deurenberg P . Body fat measurement among Singaporean Chinese, Malays and Indians: a comparative study using a four-compartment model and different two-compartment models Br J Nutr 2001 85: 491–498.

    Article  CAS  PubMed  Google Scholar 

  11. Bouchard C, Leon AS, Rao DC, Skinner JS, Wilmore JH, Gagnon J . The Heritage Family Study: aims, design, and measurement protocol Med Sci Sports Exercise 1995 27: 721–729.

    Article  CAS  Google Scholar 

  12. Behnke AR, Wilmore JH . Evaluation and regulation of body build and composition Prentice-Hall: Englewood Cliffs, NJ 1974.

    Google Scholar 

  13. Wilmore JH, Despres J, Stanforth PR, Mandel S, Rice T, Gagnon J, Leon AS, Rao DC, Skinner JS, Bouchard C . Alterations in body weight and composition consequent to 20 wk of endurance training: the Heritage Family Study Am J Clin Nutr 1999 70: 346–352.

    Article  CAS  PubMed  Google Scholar 

  14. Siri WE . Body composition from fluid space and density In: Brozek J and Hanschel A (eds) Techniques for measuring body composition National Academy of Science: Washington, DC 1961.

    Google Scholar 

  15. Lohman TG . Applicability of body composition techniques and constants for children and youths Exercise Sports Sci Rev 1986 14: 325–357.

    Article  CAS  Google Scholar 

  16. Schutte JE, Townsend EJ, Hugg J, Shoup RF, Malina RM, Blomqvist CG . Density of lean body mass is greater in blacks than in whites J Appl Physiol 1984 56: 1647–1649.

    Article  CAS  PubMed  Google Scholar 

  17. Ortiz O, Russell M, Daley TL . Differences in skeletal muscle and bone mineral mass between black and white females and their relevance to estimates of body composition Am J Clin Nutr 1992 55: 8–13.

    Article  CAS  PubMed  Google Scholar 

  18. Gagnon J, Province MA, Bouchard C . The Heritage Family Study: quality assurance and quality control Ann Epidemiol 1996 6: 520–529.

    Article  CAS  PubMed  Google Scholar 

  19. Pedhauzur EJ . Multiple regression in behavioral research: explanation and prediction 3rd edn Harcourt Brace: New York 1997.

    Google Scholar 

  20. SAS. Statview 5.0 edn SAS Institute: Cary, NC 1998.

  21. Jackson AS, Pollock ML . Generalized equations for predicting body density of men Br J Nutr 1978 40: 497–504.

    Article  CAS  PubMed  Google Scholar 

  22. Jackson AS, Pollock ML, Ward A . Generalized equations for predicting body density of women Med Sci Sports Exercise 1980 12: 175–182.

    CAS  Google Scholar 

  23. Jackson AS . Research design and analysis of data procedures for predicting body density Med Sci Sports Exercise 1984 16: 616–620.

    CAS  Google Scholar 

  24. Jackson AS, Beard EF, Wier LT, Ross RM, Stuteville JE, Blair SN . Changes in aerobic power of men ages 25–70 y Med Sci Sports Exercise 1995 27: 113–120.

    CAS  Google Scholar 

  25. Pollock ML, Foster C, Knapp D, Rod JL, Schmidt DH . Effect of age and training on aerobic capacity and body composition of master athletes J Appl Physiol 1987 62: 725–731.

    Article  CAS  PubMed  Google Scholar 

  26. Fleg JL, Lakatta EG . Role of muscle loss in the age-associated reduction in VO2max J Appl Physiol 1988 65: 1147–1151.

    Article  CAS  PubMed  Google Scholar 

  27. Wagner DR, Heyward VH . Measures of body composition in blacks and whites: a comparative review Am J Clin Nutr 2000 71: 1392–1402.

    Article  CAS  PubMed  Google Scholar 

  28. Visser M, Gallagher D, Deurenberg P, Wang J, Pierson RN, Heymsfield SR . Density of fat-free body mass: relationship with race, age, and level of body fatness Am J Physiol 1997 272 (Endocrinol Metab 35): E781–E787.

    CAS  PubMed  Google Scholar 

  29. Hosmer DW, Lemeshow S . Applied logistic regression John Wiley: New York 1989.

    Google Scholar 

  30. Wellens RI, Roche AF, Khamis HJ, Jackson AS, Pollock ML, Siervogel RM . Relationships between body mass index and body composition Obes Res 1996 4: 35–44.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The Heritage Family Study is supported by the National Heart, Lung and Blood Institute through the following grants: HL45670 (C Bouchard, PI); HL47323 (AS Leon, PI); HL47317 (DC Rao, PI); HL47327 (JS Skinner, PI); and HL47321 (JH Wilmore, PI). Claude Bouchard is partially supported by the George A Bray Chair in Nutrition. Credit is also given to the University of Minnesota Clinical Research Center, NIH Grant MO1-RR000400. Further, Art Leon is partially supported by the Henry L Taylor Professorship in Exercise Science and Health Enhancement. Thanks are expressed to all of the co-principal investigators, investigators, co-investigators, local project coordinators, research assistants, laboratory technicians, and secretaries who have contributed to this study (see Bouchard et al10). Finally, the Heritage consortium is very thankful to those hard-working families whose participation has made these data possible.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to AS Jackson.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jackson, A., Stanforth, P., Gagnon, J. 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 26, 789–796 (2002). https://doi.org/10.1038/sj.ijo.0802006

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.ijo.0802006

Keywords

This article is cited by

Search

Quick links