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Published on: October 22, 2014
Income inequality and cardiovascular disease risk factors in a highly unequal country: a fixed-effects analysis from
Kafui Adjaye-Gbewonyo1, Ichiro Kawachi1, S V Subramanian1
1Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, 677 Huntington Avenue, Kresge 7th Floor, Boston, MA, 02115, USA.
Background:
Chronic stress associated with high income inequality has been hypothesized to increase CVD risk and other adverse health outcomes. However, most evidence comes from high-income countries, and there is limited evidence on the link between income inequality and biomarkers of chronic stress and risk for CVD. This study examines how changes in income inequality over recent years relate to changes in CVD risk factors in South Africa, home to some of the highest levels of income inequality globally.
Methods:
We linked longitudinal data from 9356 individuals interviewed in the 2008 and 2012 National Income Dynamics Study to district-level Gini coefficients estimated from census and survey data. We investigated whether subnational district income inequality was associated with several modifiable risk factors for cardiovascular disease (CVD) in South Africa, including body mass index (BMI), waist circumference, blood pressure, physical inactivity, smoking, and high alcohol consumption. We ran individual fixed-effects models to examine the association between changes in income inequality and changes in CVD risk factors over time. Linear models were used for continuous metabolic outcomes while conditional Poisson models were used to estimate risk ratios for dichotomous behavioral outcomes.
Results:
Both income inequality and prevalence of most CVD risk factors increased over the period of study. In longitudinal fixed-effects models, changes in district Gini coefficients were not significantly associated with changes in CVD risk factors.
Conclusions:
Our findings do not support the hypothesis that subnational district income inequality is associated with CVD risk factors within the high-inequality setting of South Africa.
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