Lifestyle and socio-economic inequalities in diabetes prevalence in South Africa: A decomposition analysis
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 literatu...
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| Vydáno v: | PloS one Ročník 14; číslo 1; s. e0211208 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
Public Library of Science
30.01.2019
Public Library of Science (PLoS) |
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| ISSN: | 1932-6203, 1932-6203 |
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| 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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| AbstractList | 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. 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. 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. 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.BACKGROUNDInequalities 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.METHODSThis 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.RESULTSSelf-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.CONCLUSIONDiabetes 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. 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. |
| Audience | Academic |
| Author | Pavlova, Milena Groot, Wim Booysen, Frederik Stokes, Andrew Mutyambizi, Chipo |
| AuthorAffiliation | 1 Population Health, Health Systems and Innovation, Human Sciences Research Council, Pretoria, South Africa 3 Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, United States of America 4 Department of Health Services Research; CAPHRI, Maastricht University Medical Centre, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands 2 University of the Witwatersrand, Johannesburg, South Africa Sciensano, BELGIUM |
| AuthorAffiliation_xml | – name: 1 Population Health, Health Systems and Innovation, Human Sciences Research Council, Pretoria, South Africa – name: 2 University of the Witwatersrand, Johannesburg, South Africa – name: 4 Department of Health Services Research; CAPHRI, Maastricht University Medical Centre, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands – name: 3 Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, United States of America – name: Sciensano, BELGIUM |
| Author_xml | – sequence: 1 givenname: Chipo orcidid: 0000-0003-4749-7280 surname: Mutyambizi fullname: Mutyambizi, Chipo – sequence: 2 givenname: Frederik surname: Booysen fullname: Booysen, Frederik – sequence: 3 givenname: Andrew surname: Stokes fullname: Stokes, Andrew – sequence: 4 givenname: Milena surname: Pavlova fullname: Pavlova, Milena – sequence: 5 givenname: Wim surname: Groot fullname: Groot, Wim |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30699173$$D View this record in MEDLINE/PubMed |
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| Copyright | COPYRIGHT 2019 Public Library of Science 2019 Mutyambizi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2019 Mutyambizi et al 2019 Mutyambizi et al |
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| Snippet | Inequalities in diabetes are widespread and are exacerbated by differences in lifestyle. Many studies that have estimated inequalities in diabetes make use of... Background Inequalities in diabetes are widespread and are exacerbated by differences in lifestyle. Many studies that have estimated inequalities in diabetes... BACKGROUND:Inequalities in diabetes are widespread and are exacerbated by differences in lifestyle. Many studies that have estimated inequalities in diabetes... Background Inequalities in diabetes are widespread and are exacerbated by differences in lifestyle. Many studies that have estimated inequalities in diabetes... |
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| SubjectTerms | Adolescent Adult Age Distribution Alcohol use Biology and Life Sciences Care and treatment Cross-Sectional Studies Decomposition Development policy Diabetes Diabetes mellitus Diabetes Mellitus - epidemiology Diabetes therapy Diabetics Diagnosis Economic analysis Economics Equality Exercise Female Health care Health care access Health care services accessibility Health Services Accessibility Health Status Disparities Health surveys Humans Life Style Male Medical care discrimination Medicine and Health Sciences Middle Aged Nutrition Obesity People and places Prevalence Rich people Risk factors Self Report Social aspects Socioeconomic Factors Socioeconomics South Africa - epidemiology Studies Systematic review Type 2 diabetes Young Adult |
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| Title | Lifestyle and socio-economic inequalities in diabetes prevalence in South Africa: A decomposition analysis |
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