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      Socioeconomic Inequalities in Adult Obesity Prevalence in South Africa: A Decomposition Analysis

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          Abstract

          In recent years, there has been a dramatic increase in obesity in low and middle income countries. However, there is limited research in these countries showing the prevalence and determinants of obesity. In this study, we examine the socioeconomic inequalities in obesity among South African adults. We use nationally representative data from the South Africa National Income Dynamic Survey of 2008 to: (1) construct an asset index using multiple correspondence analyses (MCA) as a proxy for socioeconomic status; (2) estimate concentration indices (CI) to measure socioeconomic inequalities in obesity; and (3) perform a decomposition analysis to determine the factors that contribute to socioeconomic related inequalities. Consistent with other studies, we find that women are more obese than men. The findings show that obesity inequalities exist in South Africa. Rich men are more likely to be obese than their poorer counterparts with a concentration index of 0.27. Women on the other hand have similar obesity patterns, regardless of socioeconomic status with CI of 0.07. The results of the decomposition analysis suggest that asset index contributes positively and highly to socio-economic inequality in obesity among females; physical exercise contributes negatively to the socio-economic inequality. In the case of males, educational attainment and asset index contributed more to socio-economic inequalities in obesity. Our findings suggest that focusing on economically well-off men and all women across socioeconomic status is one way to address the obesity problem in South Africa.

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          Estimating wealth effects without expenditure data--or tears: an application to educational enrollments in states of India.

          Using data from India, we estimate the relationship between household wealth and children's school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children's enrollment across Indian states. On average a "rich" child is 31 percentage points more likely to be enrolled than a "poor" child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                21 March 2014
                March 2014
                : 11
                : 3
                : 3387-3406
                Affiliations
                [1 ]Health Economics Unit, School of Public Health and Family Medicine, University of Cape Town, Cape Town 7925, South Africa; E-Mail: Olufunke.Alaba@ 123456uct.ac.za
                [2 ]PRICELESS SA, MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, University of the Witwatersrand, Johannesburg 2050, South Africa
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: lumbwechola@ 123456hotmail.com ; Tel.: +27-713-364-261; Fax: +27-117-172-084.
                Article
                ijerph-11-03387
                10.3390/ijerph110303387
                3987040
                24662998
                a4dbe7bc-e5e6-4674-8355-1688df42cc2d
                © 2014 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                : 23 December 2013
                : 10 March 2014
                : 11 March 2014
                Categories
                Article

                Public health
                obesity,south africa,inequality
                Public health
                obesity, south africa, inequality

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