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.

Epidemiology and Population Health

The association between BMI and health-related quality of life in the US population: sex, age and ethnicity matters

International Journal of Obesity volume 42, pages 318–326 (2018)Cite this article

Subjects

Abstract

Background:

Obesity is a major public health problem. Detailed knowledge about the relationship between body mass index (BMI) and health-related quality of life (HRQL) is important for deriving effective and cost-effective prevention and weight management strategies. This study aims to describe the sex-, age- and ethnicity-specific association between BMI and HRQL in the US adult population.

Methods:

Analyses are based on pooled cross-sectional data from 41 459 participants of the Medical Expenditure Panel Survey (MEPS) Household Component (HC) for the years 2000–2003. BMI was calculated using self-reported height and weight, and HRQL was assessed with the EuroQol five-dimensional questionnaire. Generalized additive models were fitted with a smooth function for BMI and a smooth-factor interaction for BMI with sex adjusted for age, ethnicity, poverty, smoking and physical activity. Models were further stratified by age and ethnicity.

Results:

The association between BMI and HRQL is inverse U-shaped with a HRQL high point at a BMI of 22 kg m−2 in women and a HRQL high plateau at BMI values of 22–30 kg m−2 in men. Men aged 50 years and older with a BMI of 29 kg m−2 reported on average five-point higher visual analog scale (VAS) scores than peers with a BMI of 20 kg m−2. The inverse U-shaped association is more pronounced in older people, and the BMI–HRQL relationship differs between ethnicities. In Hispanics, the BMI associated with the highest HRQL is higher than in white people and, in black women, the BMI–HRQL association has an almost linear negative slope.

Conclusions:

The results show that a more differentiated use of BMI cutoffs in scientific discussions and daily practice is indicated. The findings should be considered in the design of future weight loss and weight management programs.

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

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

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

Figure 1
Figure 2
Figure 3

References

  1. Bhaskaran K, Douglas I, Forbes H, dos-Santos-Silva I, Leon DA, Smeeth L . Body-mass index and risk of 22 specific cancers: a population-based cohort study of 5.24 million UK adults. Lancet 2014; 384: 755–765.

    Article  Google Scholar 

  2. Bays HE, Chapman RH, Grandy S . The relationship of body mass index to diabetes mellitus, hypertension and dyslipidaemia: comparison of data from two national surveys. Int J Clin Pract 2007; 61: 737–747.

    Article  CAS  Google Scholar 

  3. Taylor HA Jr, Coady SA, Levy D, Walker ER, Vasan RS, Liu J et al. Relationships of BMI to cardiovascular risk factors differ by ethnicity. Obesity 2010; 18: 1638–1645.

    Article  Google Scholar 

  4. Aune D, Sen A, Prasad M, Norat T, Janszky I, Tonstad S et al. BMI and all cause mortality: systematic review and non-linear dose–response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants. BMJ 2016; 353: i2156.

    Article  Google Scholar 

  5. Cawley J, Meyerhoefer C . The medical care costs of obesity: an instrumental variables approach. J Health Econ 2012; 31: 219–230.

    Article  Google Scholar 

  6. Berrington de Gonzalez A, Hartge P, Cerhan JR, Flint AJ, Hannan L, MacInnis RJ et al. Body-mass index and mortality among 1.46 million white adults. N Engl J Med 2010; 363: 2211–2219.

    Article  CAS  Google Scholar 

  7. Calle EE, Thun MJ, Petrelli JM, Rodriguez C, Heath CWJ Body-mass . index and mortality in a prospective cohort of U.S. adults. N Engl J Med 1999; 341: 1097–1105.

    Article  CAS  Google Scholar 

  8. Colin Bell A, Adair LS, Popkin BM . Ethnic differences in the association between body mass index and hypertension. Am J Epidemiol 2002; 155: 346–353.

    Article  CAS  Google Scholar 

  9. Wood-Dauphinee S . Assessing quality of life in clinical research: from where have we come and where are we going? J Clin Epidemiol 1999; 52: 355–363.

    Article  CAS  Google Scholar 

  10. Jia H, Lubetkin E . The impact of obesity on health-related quality-of-life in the general adult US population. J Public Health 2005; 27: 156–164.

    Article  Google Scholar 

  11. Hunger M, Thorand B, Schunk M, Doring A, Menn P, Peters A et al. Multimorbidity and health-related quality of life in the older population: results from the German KORA-age study. Health Qual Life Outcomes 2011; 9: 53.

    Article  Google Scholar 

  12. Xu Y, Zhou Z, Li Y, Yang J, Guo X, Gao J et al. Exploring the nonlinear relationship between body mass index and health-related quality of life among adults: a cross-sectional study in Shaanxi Province, China. Health Qual Life Outcomes 2015; 13: 1–9.

    Article  Google Scholar 

  13. Kearns B, Ara R, Young T, Relton C . Association between body mass index and health-related quality of life, and the impact of self-reported long-term conditions – cross-sectional study from the south Yorkshire cohort dataset. BMC Public Health 2013; 13: 1–11.

    Article  Google Scholar 

  14. Agency for Healthcare Research and Quality. The Medical Expenditure Panel Survey (MEPS) Household Component. Retrieved from https://meps.ahrq.gov/mepsweb/survey_comp/household.jsp (last accessed on) 2017.

  15. Centers for Disease Control and Prevention. National Health Interview Survey. Retrieved from https://www.cdc.gov/nchs/nhis/ (last accessed on) 2017.

  16. Rand S, Caiels J Using proxies to assess quality of life: a review of the issues and challenges. May 2015. Discussion Paper 2899. Retrieved from http://www.pssru.ac.uk/archive/pdf/4980.pdf (last accessed on) 2017.

  17. Shaw JW, Johnson JA, Coons SJ . US valuation of the EQ-5D health states: development and testing of the D1 valuation model. Med Care 2005; 43: 203–220.

    Article  Google Scholar 

  18. Agency for Healthcare Research and Quality. MEPS-HC Summary Data Tables Technical Notes. Retrieved from https://meps.ahrq.gov/survey_comp/hc_technical_notes.shtml (last accessed on) 2017.

  19. McAdams MA, Van Dam RM, Hu FB . Comparison of self-reported and measured BMI as correlates of disease markers in US adults. Obesity 2007; 15: 188–196.

    Article  Google Scholar 

  20. Sach T, Barton G, Doherty M, Muir K, Jenkinson C, Avery A . The relationship between body mass index and health-related quality of life: comparing the EQ-5D, EuroQol VAS and SF-6D. Int J Obesity 2006; 31: 189–196.

    Article  Google Scholar 

  21. Keating CL, Peeters A, Swinburn BA, Magliano DJ, Moodie ML . Utility-based quality of life associated with overweight and obesity: the Australian diabetes, obesity, and lifestyle study. Obesity 2013; 21: 652–655.

    Article  Google Scholar 

  22. Bentley TG, Palta M, Paulsen AJ, Cherepanov D, Dunham NC, Feeny D et al. Race and gender associations between obesity and nine health-related quality-of-life measures. Qual Life Res 2011; 20: 665–674.

    Article  Google Scholar 

  23. Ul-Haq Z, Mackay DF, Fenwick E, Pell JP . Meta-analysis of the association between body mass index and health-related quality of life among adults, assessed by the SF-36. Obesity 2013; 21: E322–E327.

    Article  Google Scholar 

  24. Soltoft F, Hammer M, Kragh N . The association of body mass index and health-related quality of life in the general population: data from the 2003 health survey of England. Qual Life Res 2009; 18: 1293–1299.

    Article  CAS  Google Scholar 

  25. Stevens J . Ethnic-specific revisions of body mass index cutoffs to define overweight and obesity in Asians are not warranted. Int J Obes Relat Metab Disord 2003; 27: 1297–1299.

    Article  CAS  Google Scholar 

  26. Laxy M, Hunger M, Stark R, Meisinger C, Kirchberger I, Heier M et al. The burden of diabetes mellitus in patients with coronary heart disease: a methodological approach to assess quality-adjusted life-years based on individual-level longitudinal survey data. Value Health 2015; 18: 969–976.

    Article  Google Scholar 

  27. Pasco JA, Nicholson GC, Brennan SL, Kotowicz MA . Prevalence of obesity and the relationship between the body mass index and body fat: cross-sectional, population-based data. PLoS One 2012; 7: e29580.

    Article  CAS  Google Scholar 

  28. Misra R, Lager J . Ethnic and gender differences in psychosocial factors, glycemic control, and quality of life among adult type 2 diabetic patients. J Diabetes Compl 2009; 23: 54–64.

    Article  Google Scholar 

  29. Palaniappan LP, Carnethon MR, Fortmann SP . Heterogeneity in the relationship between ethnicity, BMI, and fasting insulin. Diabetes Care 2002; 25: 1351–1357.

    Article  Google Scholar 

  30. Puhl RM, Heuer CA . Obesity stigma: important considerations for public health. Am J Public Health 2010; 100: 1019–1028.

    Article  Google Scholar 

  31. Walters SJ, Brazier JE . Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Qual of Life Res 2005; 14: 1523–1532.

    Article  Google Scholar 

Download references

Acknowledgements

We thank Dr Michaela Schunk for her very helpful comments on drafts of the manuscript.

Author contributions

ML was responsible for the design of the study, carried out some parts of the statistical analyses and drafted the manuscript. CK carried out the main part of the statistical analyses and commented on drafts of the manuscript. CT and RH commented on drafts of the manuscript. All authors read and approved the final version of the manuscript.

Author information

Authors and Affiliations

  1. Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health, München, Neuherberg, Germany

    M Laxy, C Teuner, R Holle & C Kurz

  2. German Center for Diabetes Research (DZD), München, Neuherberg, Germany

    M Laxy & R Holle

Authors
  1. M Laxy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C Teuner
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R Holle
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. C Kurz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M Laxy.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies this paper on International Journal of Obesity website

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Laxy, M., Teuner, C., Holle, R. et al. The association between BMI and health-related quality of life in the US population: sex, age and ethnicity matters. Int J Obes 42, 318–326 (2018). https://doi.org/10.1038/ijo.2017.252

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ijo.2017.252

This article is cited by

Search

Advanced search

Quick links