Background: Malnutrition is a prevalent public health concern in Ghana. While studies have identified factors that influence child malnutrition and related inequalities in Ghana, very little efforts have been made to decompose these inequalities across various household characteristics. This study examined the influence of socioeconomic factors on inequality in child malnutrition using a decomposition approach. Methods: The study employed cross section data from the 2011 Multiple Indicator Cluster Survey (MICS). Analysis was done at three levels: First, concentration curves were constructed to explore the nature of inequality in child malnutrition. Secondly, concentration indices were computed to quantify the magnitude of inequality. Thirdly, decomposition analysis was conducted to determine the role of mother’s education and health insurance coverage in inequality of child malnutrition. Results: The concentration curves showed that there exists a pro-poor inequality in child malnutrition measured by stunting and wasting. The concentration indices of these measures indicated that the magnitude of inequality was higher and significant at 1 % for weight-for-age (WAZ) (−0.1641), relative to height-for-age (HAZ) (−0.1613). The decomposition analyses show that whilst mother’s education contributed about 13 and 11 % to inequality in HAZ, it contributed about 18.9 and 11.8 % to inequality in WAZ for primary and secondary or above education attainments, respectively. Finally, health insurance contributed about 1.91 and 1.03 % to inequality in HAZ and WAZ, respectively. Conclusion: The results suggest that there is the need to encourage critical policies directed towards improving female literacy in the country. The existence of a functional health insurance system and increasing universal coverage are recommended to mitigate child malnutrition.
CITATION STYLE
Novignon, J., Aboagye, E., Agyemang, O. S., & Aryeetey, G. (2015). Socioeconomic-related inequalities in child malnutrition: evidence from the Ghana multiple indicator cluster survey. Health Economics Review, 5(1), 1–11. https://doi.org/10.1186/s13561-015-0072-4
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