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  • Title: Poverty and inequality - but of what - as social determinants of health in Africa?
    Author: Worku EB, Woldesenbet SA.
    Journal: Afr Health Sci; 2015 Dec; 15(4):1330-8. PubMed ID: 26958038.
    Abstract:
    BACKGROUND: Many African economies have achieved substantial economic growth over the past recent years, yet several of the Millennium Development Goals (MDGs) including those concerned with health, remain considerably behind target. This paper examines whether progress towards these goals is being hampered by existing levels of poverty and income inequality. It also considers whether the inequality hypothesis of Wilkinson and Pickett1 applies to population health outcomes in African states. METHODS: Correlation analysis and scatter plots were used to assess graphically the link between variations in health outcomes, level of poverty and income inequality in different countries. Health status outcomes were measured by using four indicators: infant and under-five (child) mortality rates; maternal mortality ratios; and life expectancy at birth. In each of the 52 African nations, the proportion of the population living below the poverty line is used as an indicator of the level of poverty and Gini coefficient as a measure of income inequality. The study used a comprehensive review of secondary and relevant literature that are pertinent in the subject area. The data datasets obtained online from UNICEF2 and UNDP3 (2009) used to test the research questions. World Health Organization the three broad dimensions to consider when moving towards better population health outcome through Universal Health Coverage and the Social Determinants of Health framework reviewed to establish the poverty and income inequality link in African countries population health outcomes. RESULTS: The study shows that poverty is strongly associated with all health outcome differences in Africa (IMR, cc = 0.63; U5MR, cc = 0.64; MMR, cc = 0.49; life expectancy at birth, cc = -0.67); income inequality with only one of the four indicators (IMR, cc = 0.14; U5MR, cc = 0.07; MMR, cc = 0.22; life expectancy at birth, cc = -0.49), whereas income inequality is associated with one of the four indicators. CONCLUSION: The study shows that tackling poverty should be the immediate concern in Africaas a means of promoting better health for all. There is a question mark over whether the findings of Wilkinson and Pickett1 on the relationship between income inequality and health apply to Africa. The reasons for this question mark are discussed. More research is needed to investigate whether the inequality results found in this study are replicated in other studies of African health.
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