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Social inequality in infant mortality in Angola: Evidence from a population based study

INTRODUCTION: Within country inequality in infant mortality poses a big challenge for countries moving towards the internationally agreed upon targets on child mortality by 2030. There is a lack of high-quality evidence on infant mortality measured through different dimensions of social inequality i...

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Autor principal: Shibre, Gebretsadik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580929/
https://www.ncbi.nlm.nih.gov/pubmed/33091077
http://dx.doi.org/10.1371/journal.pone.0241049
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author Shibre, Gebretsadik
author_facet Shibre, Gebretsadik
author_sort Shibre, Gebretsadik
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description INTRODUCTION: Within country inequality in infant mortality poses a big challenge for countries moving towards the internationally agreed upon targets on child mortality by 2030. There is a lack of high-quality evidence on infant mortality measured through different dimensions of social inequality in Angola. Thus, this paper was carried out to address the knowledge gap by conducting in-depth examination of infant mortality rate (IMR) inequality among population subgroups to provide more nuanced evidence to help end IMR disparity in the country. METHODS: The World Health Organization’s (WHO) Health Equity Assessment Toolkit (HEAT) was used to analyze IMR inequality. HEAT is a software application that facilitates examination of disparities in reproductive, maternal, neonatal and child health indicators using the WHO Health Equity Monitor (HEM) database. Inequality of IMR was analyzed through disaggregation by five equity stratifiers: education, wealth, gender, subnational region and residence. These were analyzed through three inequality measures: Population Attributable Risk, Ratio and Slope Index of Inequality. A 95% confidence Interval (CI) was built around point estimates to determine statistical significance. RESULTS: A notable disadvantage was found for children born to poor (Population Attributable Risk (PAR): -27.0; -28.4, -26.0) and uneducated (PAR: -17.0; -17.9, -16.0), women who live in rural areas (PAR: -7.3;-7.8, -6.7) and those residing in certain regions of the country (PAR: -43.0; 45.3, -4). Male infants had a higher risk of death than female infants (PAR: -6.8;-7.5, -6.2). The subnational regional variation of IMR had been the most evident when compared with the disparities in the other equity stratifers. CONCLUSIONS: Policymakers and planners need to address the disproportionately higher clustering of IMR among infants born to disadvantaged subpopulations through interventions that benefit such subgroups.
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spelling pubmed-75809292020-10-27 Social inequality in infant mortality in Angola: Evidence from a population based study Shibre, Gebretsadik PLoS One Research Article INTRODUCTION: Within country inequality in infant mortality poses a big challenge for countries moving towards the internationally agreed upon targets on child mortality by 2030. There is a lack of high-quality evidence on infant mortality measured through different dimensions of social inequality in Angola. Thus, this paper was carried out to address the knowledge gap by conducting in-depth examination of infant mortality rate (IMR) inequality among population subgroups to provide more nuanced evidence to help end IMR disparity in the country. METHODS: The World Health Organization’s (WHO) Health Equity Assessment Toolkit (HEAT) was used to analyze IMR inequality. HEAT is a software application that facilitates examination of disparities in reproductive, maternal, neonatal and child health indicators using the WHO Health Equity Monitor (HEM) database. Inequality of IMR was analyzed through disaggregation by five equity stratifiers: education, wealth, gender, subnational region and residence. These were analyzed through three inequality measures: Population Attributable Risk, Ratio and Slope Index of Inequality. A 95% confidence Interval (CI) was built around point estimates to determine statistical significance. RESULTS: A notable disadvantage was found for children born to poor (Population Attributable Risk (PAR): -27.0; -28.4, -26.0) and uneducated (PAR: -17.0; -17.9, -16.0), women who live in rural areas (PAR: -7.3;-7.8, -6.7) and those residing in certain regions of the country (PAR: -43.0; 45.3, -4). Male infants had a higher risk of death than female infants (PAR: -6.8;-7.5, -6.2). The subnational regional variation of IMR had been the most evident when compared with the disparities in the other equity stratifers. CONCLUSIONS: Policymakers and planners need to address the disproportionately higher clustering of IMR among infants born to disadvantaged subpopulations through interventions that benefit such subgroups. Public Library of Science 2020-10-22 /pmc/articles/PMC7580929/ /pubmed/33091077 http://dx.doi.org/10.1371/journal.pone.0241049 Text en © 2020 Gebretsadik Shibre http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Shibre, Gebretsadik
Social inequality in infant mortality in Angola: Evidence from a population based study
title Social inequality in infant mortality in Angola: Evidence from a population based study
title_full Social inequality in infant mortality in Angola: Evidence from a population based study
title_fullStr Social inequality in infant mortality in Angola: Evidence from a population based study
title_full_unstemmed Social inequality in infant mortality in Angola: Evidence from a population based study
title_short Social inequality in infant mortality in Angola: Evidence from a population based study
title_sort social inequality in infant mortality in angola: evidence from a population based study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580929/
https://www.ncbi.nlm.nih.gov/pubmed/33091077
http://dx.doi.org/10.1371/journal.pone.0241049
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