Lifestyle and socio-economic inequalities in diabetes prevalence in South Africa: a decomposition analysis
SOURCE: PLoS One
OUTPUT TYPE: Journal Article
PUBLICATION YEAR: 2019
TITLE AUTHOR(S): C.Mutyambizi, F.Booysen, A.Stokes, M.Pavlova, W.Groot
KEYWORDS: DIABETES, LIFESTYLE, SOCIO-ECONOMIC INEQUALITIES
Print: HSRC Library: shelf number 10717
HANDLE: 20.500.11910/13431
URI: http://hdl.handle.net/20.500.11910/13431
OUTPUT TYPE: Journal Article
PUBLICATION YEAR: 2019
TITLE AUTHOR(S): C.Mutyambizi, F.Booysen, A.Stokes, M.Pavlova, W.Groot
KEYWORDS: DIABETES, LIFESTYLE, SOCIO-ECONOMIC INEQUALITIES
Print: HSRC Library: shelf number 10717
HANDLE: 20.500.11910/13431
URI: http://hdl.handle.net/20.500.11910/13431
If you would like to obtain a copy of this Research Output, please contact Hanlie Baudin at researchoutputs@hsrc.ac.za.
Abstract
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. 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. 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. 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.-
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