Wealth-related inequalities in the coverage of reproductive, maternal, newborn and child health interventions in 36 countries in the African Region.

Fernando C Wehrmeister,Aluisio J D Barros,Leonardo Z Ferreira,Agbessi Amouzou,Abdoulaye Maïga,Tyler Porth,Ahmad Reza Hosseinpoor,Liliana Carvajal-Aguirre,Kathleen Strong,Cheikh Mbacké Fayé,Dessalegn Y Melesse,Tome Ca,Safia S Jiwani,Inácio Crochemore M Da Silva,Ties Boerma,Chelsea Taylor,Martin Mutua,Estelle Sidze

doi:10.2471/blt.19.249078

Abstract

ObjectiveTo investigate whether sub-Saharan African countries have succeeded in reducing wealth-related inequalities in the coverage of reproductive, maternal, newborn and child health interventions.MethodsWe analysed survey data from 36 countries, grouped into Central, East, Southern and West Africa subregions, in which at least two surveys had been conducted since 1995. We calculated the composite coverage index, a function of essential maternal and child health intervention parameters. We adopted the wealth index, divided into quintiles from poorest to wealthiest, to investigate wealth-related inequalities in coverage. We quantified trends with time by calculating average annual change in index using a least-squares weighted regression. We calculated population attributable risk to measure the contribution of wealth to the coverage index.FindingsWe noted large differences between the four regions, with a median composite coverage index ranging from 50.8% for West Africa to 75.3% for Southern Africa. Wealth-related inequalities were prevalent in all subregions, and were highest for West Africa and lowest for Southern Africa. Absolute income was not a predictor of coverage, as we observed a higher coverage in Southern (around 70%) compared with Central and West (around 40%) subregions for the same income. Wealth-related inequalities in coverage were reduced by the greatest amount in Southern Africa, and we found no evidence of inequality reduction in Central Africa.ConclusionOur data show that most countries in sub-Saharan Africa have succeeded in reducing wealth-related inequalities in the coverage of essential health services, even in the presence of conflict, economic hardship or political instability.

Highlights

Reaching all women and children with essential reproductive, maternal, newborn and child health interventions is a critical part of universal health coverage, and is represented by the Global Strategy for Women’s, Children’s and Adolescents’ Health 2016–2030.1 The millennium development goals focused on national improvements and not within-country inequalities, even though initiatives such as the Countdown to 2015 Collaboration began tracking inequalities in coverage.[2]
We investigated the extent to which sub-Saharan African countries have succeeded in reducing wealth-related inequalities in maternal, newborn and child health intervention coverage
We noted large differences between the four regions, with a composite coverage index ranging from 50.8% for West Africa to 75.3% for Southern Africa

Summary

Introduction

Reaching all women and children with essential reproductive, maternal, newborn and child health interventions is a critical part of universal health coverage, and is represented by the Global Strategy for Women’s, Children’s and Adolescents’ Health 2016–2030.1 The millennium development goals focused on national improvements and not within-country inequalities, even though initiatives such as the Countdown to 2015 Collaboration began tracking inequalities in coverage.[2] the sustainable development goals and the associated global and country-specific strategies continue to emphasize the importance of women’s, children’s and adolescents’ health with a focus on reducing all dimensions of inequality.[3]. Sub-Saharan Africa has the highest mortality rates for women during pregnancy and childbirth, for children and for adolescents, as well as the lowest coverage for many maternal, newborn and child health interventions.[4] Economic status, measured by wealth of the household, is often one of the most critical factors affecting coverage of such interventions, with large gaps between the poorest and wealthiest households. These findings illustrate the importance of the analysis of coverage trends by wealth to improve the targeting of health programmes

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Conclusion