CHILD NUTRITIONAL STATUS IN EGYPT: A COMPREHENSIVE ANALYSIS OF SOCIOECONOMIC DETERMINANTS USING A QUANTILE REGRESSION APPROACH.

Autor: Sharaf MF; Department of Economics,University of Alberta,Edmonton,Canada., Mansour EI; ‡Department of Economics,The New School for Social Research,New York,USA., Rashad AS; §Department of Economics,Frankfurt School of Finance & Management,Germany.
Jazyk: angličtina
Zdroj: Journal of biosocial science [J Biosoc Sci] 2019 Jan; Vol. 51 (1), pp. 1-17. Date of Electronic Publication: 2018 Jan 10.
DOI: 10.1017/S0021932017000633
Abstrakt: This study examined the underlying demographic and socioeconomic determinants of child nutritional status in Egypt using data from the most recent round of the Demographic and Health Survey. The height-for-age Z-score (HAZ) was used as a measure of child growth. A quantile regression approach was used to allow for a heterogeneous effect of each determinant along different percentiles of the conditional distribution of the HAZ. A nationally representative sample of 13,682 children aged 0-4 years was drawn from the 2014 Egypt DHS. The multivariate analyses included a set of HAZ determinants commonly used in the literature. The conditional and unconditional analyses revealed a socioeconomic gradient in child nutritional status, in which children of low income/education households have a worse HAZ than those from high income/education households. The results also showed significant disparities in child nutritional status by demographic and social characteristics. The quantile regression results showed that the association between the demographic and socioeconomic factors and HAZ differed along the conditional HAZ distribution. Intervention measures need to consider the heterogeneous effect of the determinants of child nutritional status along the different percentiles of the HAZ distribution. There is no one-size-fits-all policy to combat child malnutrition; a multifaceted approach and targeted policy interventions are required to address this problem effectively.
Databáze: MEDLINE