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:

Obesity and inequities in health in the developing world

Abstract

OBJECTIVE: To update the social distribution of women's obesity in the developing world and, in particular, to identify the specific level of economic development at which, if any, women's obesity in the developing world starts to fuel inequities in health.

DESIGN: Multilevel logistic regression analyses applied to anthropometric and socioeconomic data collected by nationally representative cross-sectional surveys conducted from 1992 to 2000 in 37 developing countries within a wide range of world regions and stages of economic development (gross national product (GNP) from US$190 to 4440 per capita).

SUBJECTS: In total, 148 579 nonpregnant women aged 20–49 y.

MEASUREMENTS: Body mass index to assess obesity status; quartiles of years of education to assess woman's socioeconomic status (SES), and GNP per capita to assess country's stage of economic development.

RESULTS: Belonging to the lower SES group confers strong protection against obesity in low-income economies, but it is a systematic risk factor for the disease in upper-middle income developing economies. A multilevel logistic model—including an interaction term between the country's GNP and each woman's SES—indicates that obesity starts to fuel health inequities in the developing world when the GNP reaches a value of about US$2500 per capita.

CONCLUSIONS: For most upper-middle income economies and part of the lower-middle income economies, obesity among adult women is already a relevant booster of health inequities and, in the absence of concerted national public actions to prevent obesity, economic growth will greatly expand the list of developing countries where this situation occurs.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1
Figure 2

Similar content being viewed by others

References

  1. World Health Organization. Obesity: preventing and managing the global epidemic. WHO: Geneva; 2000. WHO Technical Report Series No. 894.

  2. Sobal J, Stunkard AJ . Socioeconomic status and obesity: a review of the literature. Psychol Bull 1989; 105: 260–275.

    Article  CAS  Google Scholar 

  3. Berrios CX, Jadue HL, Zenteno AJ, Ross AMI, Rodrigues HP . Prevalencias de factores de riesgo de enfermedades crónicas. Estudio en la población general de la Región Metropolitana. Rev Med Chile 1990; 118: 597–604.

    CAS  PubMed  Google Scholar 

  4. Sichieri R, Coitinho DC, Leão MM, Recine E, Everhart JE . High temporal, geographical and income variation in body mass index among adults in Brazil. Am J Public Health 1994; 84: 793–798.

    Article  CAS  Google Scholar 

  5. Monteiro CA, Mondini L, Souza ALM, Popkin BM . The nutrition transition in Brazil. Eur J Clin Nutr 1995; 4: 105–113.

    Google Scholar 

  6. Grol MEC, Eimers JM, Alberts JF et al. Alarmingly high prevalence of obesity in Curaçao: data from an interview survey stratified for socioeconomic status. Int J Obes Relat Metab Disord 1997; 21: 1002–1009.

    Article  CAS  Google Scholar 

  7. Monteiro CA, Conde WL . A tendência secular da obesidade segundo estratos sociais: Nordeste e Sudeste do Brasil, 1975–1989–1997. Arq Bras Endocrinol Metab 1999; 43: 186–194.

    Article  Google Scholar 

  8. Monteiro CA, Benicio MHD'A, Conde WL, Popkin BM . Shifting obesity trends in Brazil. Eur J Clin Nutr 2000; 54: 342–346.

    Article  CAS  Google Scholar 

  9. Martorell R, Khan LK, Hughes ML, Grummer-Strawn LM . Obesity in women from developing countries. Eur J Clin Nutr 2000; 54: 247–252.

    Article  CAS  Google Scholar 

  10. Popkin BM, Ge K, Zhai F, Guo X, Ma H, Zohoori N . The nutrition transition in China: a cross-sectional analysis. Eur J Clin Nutr 1993; 47: 333–346.

    CAS  Google Scholar 

  11. Rivera JA, Barquera S, Campirano F, Campos I, Safdie M, Tovar V . Epidemiological and nutritional transition in Mexico: rapid increase of non-communicable chronic diseases and obesity. Public Health Nutr 2002; 5: 113–122.

    Article  Google Scholar 

  12. Thang NM, Popkin BM . Patterns of food consumption in Vietnam: effects on socioeconomic groups during an era of economic growth. Eur J Clin Nutr, (in press).

  13. Boerma JT, Sommerfelt AE . Demographic and Health Surveys (DHS): contributions and limitations. World Health Statistics Qtly 1993; 46: 222–226.

    CAS  Google Scholar 

  14. Lohman TG, Roche AF, Martorell R . Anthropometric standardization reference manual. Human Kinetics Books: Champain, IL; 1988.

    Google Scholar 

  15. Ahmad OB, Boschi-Pinto C, Lopez AD, Murray CJL, Lozano R, Inoue M . Age standardization of rates: a new WHO standard. World Health Organization: Geneva; 1999. (GPE Discussion Paper Series, No. 31).

    Google Scholar 

  16. Szklo M, Javier Nieto F . Epidemiology: beyond the basics. Aspen Publihers Inc.: Gaithersburg, MD; 2000.

    Google Scholar 

  17. Greenland S . Principles of multilevel modelling. Int J Epidemiol 2000; 29: 158–167.

    Article  CAS  Google Scholar 

  18. Van Erkel AR, Pattynama PMT . Receiver operating characteristic (ROC) analysis: basic principles and applications in radiology. Eur J Radiol 1998; 27: 88–94.

    Article  CAS  Google Scholar 

  19. Stata Corporation. Stata Statistical Software: Release 5.0. Stata Corportation: College Station, TX; 1997.

  20. Yang M, Rasbash J, Goldstein H, Barbosa M . MLwiN Macros for advanced multilevel modelling. Institute of Education: London; 1999.

    Google Scholar 

  21. Monteiro CA, Conde WL, Popkin BM . Is obesity replacing to undernutrition? Evidence from different social classes in Brazil. Public Health Nutr 2002; 5: 105–112.

    Article  Google Scholar 

  22. Stunkard AJ . Factors in obesity: current views. In: Peña M, Bacallao J (eds) Obesity and poverty: a new public health challenge. Pan American Health Organization: Washington, DC; 2000. pp 23–28.

    Google Scholar 

  23. Liberatos P, Link BG, Kesley JL . The measurement of social class in epidemiology. Epidemiol Rev 1988; 10: 87–121.

    Article  CAS  Google Scholar 

  24. World Health Organization. Diet, nutrition and the prevention of chronic diseases. WHO: Geneva; 2003. WHO Technical Report Series, No. 916.

Download references

Acknowledgements

We thank several colleagues who shared data with us, including Dr Juan Rivera (Mexico), Dr Debbie Bradshaw (South Africa) and the data coordinator of DHS. We also thank Aluísio JD Barros, Professor of Biostatistics at the University of Pelotas, Brazil, for his advice on the use of multilevel models. We thank the NIH (R01-HD30880 and R01-HD38700) and the Fogarty International Center, NIH for financial support for the analysis. We also wish to thank Ms Regina Rodrigues and Ms Frances L Dancy for administrative assistance, Mr Tom Swasey for graphics support, and Mr Bill Shapbell for editing assistant.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C A Monteiro.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Monteiro, C., Conde, W., Lu, B. et al. Obesity and inequities in health in the developing world. Int J Obes 28, 1181–1186 (2004). https://doi.org/10.1038/sj.ijo.0802716

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.ijo.0802716

Keywords

This article is cited by

Search

Quick links