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Decomposing race and gender differences in underweight and obesity in South Africa

Author

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  • Averett, Susan L.
  • Stacey, Nicholas
  • Wang, Yang

Abstract

Using data from the National Income Dynamics Study, we document differentials in both underweight and obesity across race and gender in post-Apartheid South Africa. Using a nonlinear decomposition method, we decompose these differences across gender within race and then across race within gender. Less than one third of the differences in obesity and underweight across gender are explained by differences in covariates. In contrast, at least 70% of the obesity differences across race are explained by differences in covariates. Behavioral variables such as smoking and exercise explain the largest part of the bodyweight differentials across gender. For bodyweight differentials across race within gender, however, socioeconomic status and background variables have the largest explanatory power for obesity differentials, while background variables play the key role in explaining the underweight differentials. These results indicate that eradicating obesity and underweight differentials will require targeting policies to specific groups.

Suggested Citation

  • Averett, Susan L. & Stacey, Nicholas & Wang, Yang, 2014. "Decomposing race and gender differences in underweight and obesity in South Africa," Economics & Human Biology, Elsevier, vol. 15(C), pages 23-40.
  • Handle: RePEc:eee:ehbiol:v:15:y:2014:i:c:p:23-40
    DOI: 10.1016/j.ehb.2014.05.003
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    Cited by:

    1. Joanna Ryan & Murray Leibbrandt, 2015. "Multidimensional Food Insecurity Measurement," SALDRU Working Papers 160, Southern Africa Labour and Development Research Unit, University of Cape Town.
    2. Nie, Peng & Ding, Lanlin & Sousa-Poza, Alfonso, 2019. "Decomposing adult obesity trends in China (1991–2011)," Economics & Human Biology, Elsevier, vol. 34(C), pages 5-15.
    3. Amin, Vikesh & Lhila, Aparna, 2016. "Decomposing racial differences in adolescent smoking in the U.S," Economics & Human Biology, Elsevier, vol. 22(C), pages 161-176.
    4. Aiyar, Anaka & Dhingra, Sunaina & Pingali, Prabhu, 2021. "Transitioning to an obese India: Demographic and structural determinants of the rapid rise in overweight incidence," Economics & Human Biology, Elsevier, vol. 43(C).
    5. Hamman, Mary K., 2021. "Disparities in COVID-19 mortality by county racial composition and the role of spring social distancing measures," Economics & Human Biology, Elsevier, vol. 41(C).
    6. Sengupta, Angan & Angeli, Federica & Syamala, Thelakkat S. & Dagnelie, Pieter C. & Schayck, C.P. van, 2015. "Overweight and obesity prevalence among Indian women by place of residence and socio-economic status: Contrasting patterns from ‘underweight states’ and ‘overweight states’ of India," Social Science & Medicine, Elsevier, vol. 138(C), pages 161-169.
    7. He, Qinying & Li, Xun & Wang, Rui, 2018. "Childhood obesity in China: Does grandparents’ coresidence matter?," Economics & Human Biology, Elsevier, vol. 29(C), pages 56-63.

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    More about this item

    Keywords

    Obesity; Underweight; South Africa; Fairlie decomposition;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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