Skip to main content

Data from: Lifestyle and socio-economic inequalities in diabetes prevalence in South Africa: a decomposition analysis


Mutyambizi, Chipo et al. (2019), Data from: Lifestyle and socio-economic inequalities in diabetes prevalence in South Africa: a decomposition analysis, Dryad, Dataset,


Background: Inequalities in diabetes are widespread and are exacerbated by differences in lifestyle. Many studies that have estimated inequalities in diabetes make use of self-reported diabetes which is often biased by differences in access to health care and diabetes awareness. This study adds to this literature by making use of a more objective standardised measure of diabetes in South Africa. The study estimates socio-economic inequalities in undiagnosed diabetes, diagnosed diabetes (self-reported), as well as total diabetes (undiagnosed diabetics + diagnosed diabetics). The study also examines the contribution of lifestyle factors to diabetes inequalities in South Africa. Methods: This cross sectional study uses data from the 2012 South African National Health and Nutrition Examination Survey (SANHANES-1) and applies the Erreygers Concentration Indices to assess socio-economic inequalities in diabetes. Contributions of lifestyle factors to inequalities in diabetes are assessed using a decomposition method. Results: Self-reported diabetes and total diabetes (undiagnosed diabetics + diagnosed diabetics) were significantly concentrated amongst the rich (CI = 0.0746; p < 0.05 and CI = 0.0859; p < 0.05). The concentration index for undiagnosed diabetes was insignificant but pro-poor. The decomposition showed that lifestyle factors contributed 22% and 35% to socioeconomic inequalities in self-reported and total diabetes, respectively. Conclusion: Diabetes in South Africa is more concentrated amongst higher socio-economic groups when measured using self-reported diabetes or clinical data. Our findings also show that the extent of inequality is worse in the total diabetes outcome (undiagnosed diabetics + diagnosed diabetics) when compared to the self-reported diabetes outcome. Although in comparison to other determinants, the contribution of lifestyle factors was modest, these contributions are important in the development of policies that address socio-economic inequalities in the prevalence of diabetes.

Usage notes


South Africa