Socioeconomic factors contributing to under-five mortality in sub-Saharan Africa: a decomposition analysis

Abstract

Background: In sub-Saharan Africa, socioeconomic factors such as place of residence, mother's educational level, or household wealth, are strongly associated with risk factors of under-five mortality (U5M) such as health behavior or exposure to diseases and injuries. The aim of the study was to assess the relative contribution of four known socioeconomic factors to the variability in U5M in sub-Saharan countries.

Methods: The study was based on birth histories from the Demographic and Health Surveys conducted in 32 sub-Saharan countries in 2010-2016. The relative contribution of sex of the child, place of residence, mother's educational level, and household wealth to the variability in U5M was assessed using a regression-based decomposition of a Gini-type index.

Results: The Gini index - measuring the variability in U5M related to the four socioeconomic factors - varied from 0.006 (95%CI: 0.001-0.010) in Liberia 2013 to 0.034 (95%CI: 0.029-0.039) in Côte d'Ivoire 2011/12. The main contributors to the Gini index (with a relative contribution higher than 25%) were different across countries: mother's educational level in 13 countries, sex of the child in 12 countries, household wealth in 11 countries, and place of residence in 8 countries (in some countries, more than one main contributor was identified).

Conclusions: Factors related to socioeconomic status exert varied effects on the variability in U5M in sub-Saharan African countries. The findings provide evidence in support of prioritizing intersectoral interventions aiming at improving child survival in all subgroups of a population.

Keywords: Gini decomposition; Poisson regression; Socioeconomic inequalities; Sub-Saharan Africa; Under-five mortality.

Fig. 1

Under-five mortality rates (U5MR, left) versus variability in U5MR measured by a Gini index (right) in the 32 countries, Demographic and Health Surveys 2010–2016 (0–5 years prior to each survey)

Fig. 2

Classification of the 32 countries according to the main contributors to the variability in U5MR. A factor was defined as a main contributor if its contribution to the variability in U5MR exceeded 25% according to the regression-based decomposition of the Gini index (Table 2). The Venn diagram was developed using the R function “venn.diagram”

Fig. 3

Classification of the 32 countries according to the main contributors to the variability in U5M. A factor was defined as a main contributor if its contribution to the variability in U5M exceeded 25% according to the regression-based decomposition of the Gini index (Tables)