Abstract

BackgroundHaving high-quality data available by 2020, disaggregated by income, is one of the Sustainable Development Goals (SGD). We explored how well coverage with skilled birth attendance (SBA) is predicted by asset-based wealth quintiles and by absolute income.MethodsWe used data from 293 national surveys conducted in 100 low and middle-income countries (LMICs) from 1991 to 2014. Data on household income were computed using national income levels and income inequality data available from the World Bank and the Standardized World Income Inequality Database. Multivariate regression was used to explore the predictive capacity of absolute income compared to the traditional measure of quintiles of wealth index.ResultsThe mean SBA coverage was 68.9% (SD: 24.2), compared to 64.7% (SD: 26.6) for institutional delivery coverage. Median daily family income in the same period was US$ 6.4 (IQR: 3.5–14.0). In cross-country analyses, log absolute income predicts 51.5% of the variability in SBA coverage compared to 22.0% predicted by the wealth index. For within-country analysis, use of absolute income improved the understanding of the gap in SBA coverage among the richest and poorest families. Information on income allowed identification of countries – such as Burkina Faso, Cambodia, Egypt, Nepal and Rwanda – which were well above what would be expected solely from changes in income.ConclusionAbsolute income is a better predictor of SBA and institutional delivery coverage than the relative measure of quintiles of wealth index and may help identify countries where increased coverage is likely due to interventions other than increased income.

Highlights

  • Having high-quality data available by 2020, disaggregated by income, is one of the Sustainable Development Goals (SGD)

  • We analyzed a total of 293 surveys (196 Demographic and Health Surveys (DHS), 86 Multiple Indicator Cluster Surveys (MICS) and 11 Reproductive Health Surveys (RHS)) conducted between 1991 and 2014 across 100 LMICS (See Additional file1: Table S1)

  • We showed that quintiles of absolute income are a better predictor of skilled birth attendance (SBA) coverage across countries compared to relative wealth quintiles

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Summary

Introduction

Having high-quality data available by 2020, disaggregated by income, is one of the Sustainable Development Goals (SGD). We explored how well coverage with skilled birth attendance (SBA) is predicted by asset-based wealth quintiles and by absolute income. The Sustainable Development Goals (SDGs 2030) were adopted by the United Nations in 2015. Target 17.18 requires the enhancement of country capacity to produce high-quality, timely and reliable data disaggregated by income and other stratifiers, by 2020 [1]. In spite of the SDG recommendation, few low and middle-income countries (LMICs) collect systematic data on household income [2]. Income may fluctuate more over time than other socioeconomic indicators such as the wealth index that is based on assets, dwelling materials and access to electricity and sanitation [3]. The association between income and health indicators is strong in most societies [4], it is not always possible to establish whether low income led to poor health, or whether poor health reduced income, for example due to unemployment or absenteeism [5, 6]

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