Socio-Economic Inequalities in Child Stunting Reduction in Sub-Saharan Africa

Abstract

Stunting in children less than five years of age is widespread in Sub-Saharan Africa. We aimed to: (i) evaluate how the prevalence of stunting has changed by socio-economic status and rural/urban residence, and (ii) assess inequalities in children's diet quality and access to maternal and child health care. We used data from nationally representative demographic and health- and multiple indicator cluster-surveys (DHS and MICS) to disaggregate the stunting prevalence by wealth quintile and rural/urban residence. The composite coverage index (CCI) reflecting weighed coverage of eight preventive and curative Reproductive, Maternal, Neonatal, and Child Health (RMNCH) interventions was used as a proxy for access to health care, and Minimum Dietary Diversity Score (MDDS) was used as a proxy for child diet quality. Stunting significantly decreased over the past decade, and reductions were faster for the most disadvantaged groups (rural and poorest wealth quintile), but in only 50% of the countries studied. Progress in reducing stunting has not been accompanied by improved equity as inequalities in MDDS (p < 0.01) and CCI (p < 0.001) persist by wealth quintile and rural-urban residence. Aligning food- and health-systems' interventions is needed to accelerate stunting reduction more equitably.

Keywords: continuum of care; inequities; stunting; sub-Saharan Africa.

Figure 1

Average stunting reductions in regions with Low- and Middle-Income Countries (LMIC). Authors’ graph using UNICEF-WHO-The World Bank: joint malnutrition estimates [2].

Figure 2

Change of stunting prevalence in rural relative to urban residence (rural-urban) over 1998–2008 to 2009–2018 periods. The graph presents excess changes relative to urban residence; negative values are desirable outcomes as it means faster changes in stunting are happening in the most disadvantaged group.

Figure 3

Change of stunting prevalence in the poorest relative to the wealthiest quintile (poorest-richest) over 1998–2008 to 2009–2018 periods. The graph presents excess changes relative to the wealthiest quintile; negative values are desirable outcomes as it means faster changes in stunting has happened in the most disadvantaged group.

Figure 4

Stunting prevalence by rural/urban residence. Data is from the most recent demographic and health surveys. Dots show stunting prevalence estimates for children younger than five years of age residing in rural (navy blue) and urban (orange) residence.

Figure 5

Stunting prevalence by wealth quintile. Dots represent estimated stunting prevalence for the poorest, second, middle, fourth, and the highest wealth quintile.

Figure 6

Coverage index of eight reproductive maternal neonatal and child interventions along the continuum of care (A) and proportion of children meeting minimum dietary diversity score (B) by rural/urban and poorest/richest quintile (n = 34). The boxplots present country level analyses of the latest round of DHS or MICS. Statistical tests are from independent t-test comparing prevalence in the poorest to the richest quintiles and rural to urban residents.