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Income inequality and weight status in US metropolitan areas

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  • Chang, Virginia W.
  • Christakis, Nicholas A.

Abstract

Prior empirical studies have demonstrated an association between income inequality and general health endpoints such as mortality and self-rated health, and findings have been taken as support for the hypothesis that inequality is detrimental to individual health. Unhealthy weight statuses may function as an intermediary link between inequality and more general heath endpoints. Using individual-level data from the 1996-98 Behavioral Risk Factor Surveillance System, we examine the relationship between individual weight status and income inequality in US metropolitan areas. Income inequality is calculated with data from the 1990 US Census 5% Public Use Microsample. In analyses stratified by race-sex groups, we do not find a positive association between income inequality and weight outcomes such as body mass index, the odds of being overweight, and the odds of being obese. Among white women, however, we do find a statistically significant inverse association between inequality and each of these weight outcomes, despite adjustments for individual-level covariates, metropolitan-level covariates, and census region. We also find that greater inequality is associated with higher odds for trying to lose weight among white women, even adjusting for current weight status. Although our findings are suggestive of a contextual effect of metropolitan area income inequality, we do not find an increased risk for unhealthy weight outcomes, adding to recent debates surrounding this topic.

Suggested Citation

  • Chang, Virginia W. & Christakis, Nicholas A., 2005. "Income inequality and weight status in US metropolitan areas," Social Science & Medicine, Elsevier, vol. 61(1), pages 83-96, July.
  • Handle: RePEc:eee:socmed:v:61:y:2005:i:1:p:83-96
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    References listed on IDEAS

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    Cited by:

    1. Hugh Gravelle & Matt Sutton, 2009. "Income, relative income, and self-reported health in Britain 1979-2000," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 125-145.
    2. Raffaele Lagravinese & Paolo Liberati & Giuliano Resce, 2017. "Exploring health outcomes by stochastic multi-objective acceptability analysis: an application to Italian regions," Working Papers. Collection B: Regional and sectoral economics 1703, Universidade de Vigo, GEN - Governance and Economics research Network.
    3. Chen, Zhuo & Meltzer, David, 2008. "Beefing up with the Chans: Evidence for the effects of relative income and income inequality on health from the China Health and Nutrition Survey," Social Science & Medicine, Elsevier, vol. 66(11), pages 2206-2217, June.
    4. Baum II, Charles L. & Ruhm, Christopher J., 2009. "Age, socioeconomic status and obesity growth," Journal of Health Economics, Elsevier, vol. 28(3), pages 635-648, May.
    5. Do, D. Phuong & Finch, Brian Karl & Basurto-Davila, Ricardo & Bird, Chloe & Escarce, Jose & Lurie, Nicole, 2008. "Does place explain racial health disparities? Quantifying the contribution of residential context to the Black/white health gap in the United States," Social Science & Medicine, Elsevier, vol. 67(8), pages 1258-1268, October.
    6. Darshan Zala, 2013. "Challenging The Spirit Level: Is There Really a Relationship between Inequality and Obesity?," Economic Affairs, Wiley Blackwell, vol. 33(2), pages 232-245, June.
    7. Charles L. Baum, 2017. "The Effects of College on Weight: Examining the “Freshman 15” Myth and Other Effects of College Over the Life Cycle," Demography, Springer;Population Association of America (PAA), vol. 54(1), pages 311-336, February.
    8. Matheson, Flora I. & Moineddin, Rahim & Glazier, Richard H., 2008. "The weight of place: A multilevel analysis of gender, neighborhood material deprivation, and body mass index among Canadian adults," Social Science & Medicine, Elsevier, vol. 66(3), pages 675-690, February.
    9. Kim, Daniel & Subramanian, S.V. & Gortmaker, Steven L. & Kawachi, Ichiro, 2006. "US state- and county-level social capital in relation to obesity and physical inactivity: A multilevel, multivariable analysis," Social Science & Medicine, Elsevier, vol. 63(4), pages 1045-1059, August.

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