Mustapha, J; Haghparast Bidgoli, H; Grijalva-Eternod, C; (2014) Economic and Gender Inequalities are Important Determinants of Anaemia and Acute Malnutrition in Children aged <5 years in Low- and Middle-Income Countries. In: Proceedings of the 10th World Health Economics Congress. International Health Economics Association: Dublin, Ireland.

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Abstract

Background: Poverty is a known determinant of malnutrition, especially in less-affluent countries. However the large variance in malnutrition, prevalence noted across these countries cannot be fully explained by differences in national wealth alone. Therefore, additional socioeconomic factors e.g. inequalities, are likely to also contribute towards this variance. This study aimed to explore the possible associations between economic and gender inequalities with malnutrition in children aged <5years, specifically anaemia and global acute malnutrition (GAM), using data from Low and Middle-Income Countries. / Methods: Anaemia and GAM prevalence data was obtained for 48 countries from the DHS STATcompiler and for 7 countries for which this data was unavailable, it was obtained from the World Bank, WHO and UNICEF data. The World Bank’s Gini Index and UNDP’s Gender Inequality Index (GII) were used to measure economic inequality and gender inequality respectively. The World Bank’s GDP/Capita adjusted for purchasing power parity was used as the measure of countries’ wealth.Maternal biological factors (average women’s height, total fertility rate and maternal age at first birth) and demographic factors (women’s literacy rate and percentage of people living in urban settings) were mostly obtained from the DHS STATcompiler, with some few from the World Bank databases. Concentration curves and indices were used to measure and display the magnitude of inequalities in the distribution of anaemia and GAM across countries, when ranked by Human Development Index (HDI) and GII. Associations between GII and income inequality and anaemia and GAM were explored, separately, using linear regression. The associations were later adjusted for countries’ wealth and maternal biological and demographic factors. A final multivariable model was constructed, each for anaemia and GAM, including all significant factors observed in the initial analysis. / Results: When ranked by GII, the prevalence distribution of both anaemia and GAM were highly unequal across countries, being higher and lower in countries with high and low GII scores respectively. A similar pattern was observed when ranking by HDI, with malnutrition prevalence concentrating more in countries with lower HDI scores. After adjusting for country’s wealth level and maternal biological and demographic factors, GII showed a significant, independent and positive association with anaemia prevalence, explaining 50% of the variance between countries. The Gini index showed a significant, independent and negative association with GAM, explaining about 30% of the variance. Conclusions: Gender inequality and/or low women’s status in society may explain, independently, the high anaemia prevalence in many low- and middle-income countries. In contrast, poverty appears to be more important than income inequality for explaining GAM prevalence. Future analysis using a larger sample of countries, or using multilevel modelling for analysis, may provide further insights into the associations between wealth and inequalities and the global burden of malnutrition.

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