Are the poorest poor being left behind? Estimating global inequalities in reproductive, maternal, newborn and child health

Abstract

Introduction: Wealth-related inequalities in reproductive, maternal, neonatal and child health have been widely studied by dividing the population into quintiles. We present a comprehensive analysis of wealth inequalities for the composite coverage index (CCI) using national health surveys carried out since 2010, using wealth deciles and absolute income estimates as stratification variables, and show how these new approaches expand on traditional equity analyses.

Methods: 83 low-income and middle-income countries were studied. The CCI is a combined measure of coverage with eight key reproductive, maternal, newborn and child health interventions. It was disaggregated by wealth deciles for visual inspection of inequalities, and the slope index of inequality (SII) was estimated. The correlation between coverage in the extreme deciles and SII was assessed. Finally, we used multilevel models to examine how the CCI varies according to the estimated absolute income for each wealth quintile in the surveys.

Results: The analyses of coverage by wealth deciles and by absolute income show that inequality is mostly driven by coverage among the poor, which is much more variable than coverage among the rich across countries. Regardless of national coverage, in 61 of the countries, the wealthiest decile achieved 70% or higher CCI coverage. Well-performing countries were particularly effective in achieving high coverage among the poor. In contrast, underperforming countries failed to reach the poorest, despite reaching the better-off.

Conclusion: There are huge inequalities between the richest and the poorest women and children in most countries. These inequalities are strongly driven by low coverage among the poorest given the wealthiest groups achieve high coverage irrespective of where they live, overcoming any barriers that are an impediment to others. Countries that 'punched above their weight' in coverage, given their level of absolute wealth, were those that best managed to reach their poorest women and children.

Keywords: child health; maternal health.

Figure 1

Equiplot showing the coverage with the composite coverage index by wealth deciles for the 83 study countries ordered by decreasing inequality. The depth marks indicate the range of inequality in percentage points measured by the slope index of inequality. DHS and MICS, 2010–2017. DHS, Demographic Health Surveys; MICS, Multiple Indicator Cluster Surveys.

Figure 2

Slope index of inequality versus CCI coverage for the poorest 10% and the richest 10% households in each of the 83 study countries with the respective regression lines plotted. DHS and MICS, 2010–2017. CCI, composite coverage index; DHS, Demographic Health Surveys; MICS, Multiple Indicator Cluster Surveys.

Figure 3

Composite coverage index (CCI) versus annual household income (2011 international dollars at purchasing power parity (PPP)) fitted through multilevel linear model. Figure 3A (left) presents the predicted line on a linear scale with its 95% CI. Figure 3B (right) presents the predicted line plus all wealth quintiles in each country on a log scale. DHS and MICs, 2010–2017. DHS, Demographic Health Surveys; I$, international dollars; MICS, Multiple Indicator Cluster Surveys.

Figure 4

Countries with an income less than $1300 in the poorest quintile are highlighted in green when they present a higher-than-expected composite coverage index (CCI) and in Burgundy when they present a CCI coverage lower than expected. The black line represents the expected CCI coverage for a given level of income, and all quintiles are presented as shaded dots in the background. DHS and MICs, 2010–2017. DHS, Demographic Health Surveys; I$, international dollars; MICS, Multiple Indicator Cluster Surveys; PPP, purchasing power parity.

Figure 5

Countries in green are those with a composite coverage index (CCI) more than 20 percentage points higher than expected for the poorest quintile and those in Burgundy had a CCI coverage less than 20 percentage points than expected. The black line represents the expected CCI coverage for a given level of income, and all quintiles are presented as shaded dots in the background. DHS and MICs, 2010–2017. DHS, Demographic Health Surveys; I$, international dollars; MICS, Multiple Indicator Cluster Surveys; PPP, purchasing power parity.