Regional inequalities in child malnutrition in Egypt, Jordan, and Yemen: a Blinder-Oaxaca decomposition analysis

Abstract

There is substantial evidence that on average, urban children have better health outcomes than rural children. This paper investigates the underlying factors that account for the regional disparities in child malnutrition in three Arab countries, namely; Egypt, Jordan, and Yemen. We use data on a nationally representative sample from the most recent rounds of the Demographic and Health Survey. A Blinder-Oaxaca decomposition analysis is conducted to decompose the rural-urban differences in child nutrition outcomes into two components; one that is explained by regional differences in the level of the determinants (covariate effects), and another component that is explained by differences in the effect of the determinants on the child nutritional status (coefficient effects). Results show that the under-five stunting rates are 20 % in Egypt, 46.5 % in Yemen, and 7.7 % in Jordan. The rural- urban gap in child malnutrition was minor in the case of Egypt (2.3 %) and Jordan (1.5 %), while the regional gap was significant in the case of Yemen (17.7 %). Results of the Blinder-Oaxaca decomposition show that the covariate effect is dominant in the case of Yemen while the coefficients effect dominates in the case of Jordan. Income inequality between urban and rural households explains most of the malnutrition gap. Results were robust to the different decomposition weighting schemes. By identifying the underlying factors behind the rural- urban health disparities, the findings of this paper help in designing effective intervention measures aimed at reducing regional inequalities and improving population health outcomes.

Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16

“…In the last step of our analysis, we applied a regression‐decomposition to assess the ability of the various determinants described above to predict spatial patterns in stunting and differences between very high‐burden and low‐burden districts. This approach has been used widely in literature to study mean outcome differences between groups (Jann, ), including differences in child malnutrition between geographical areas (Sharaf & Rashad, ; Spears et al, ; Srinivasan et al, ) and between populations measured at different points of time (Headey, Hoddinott, Ali, Tesfaye, & Dereje, ). This analysis effectively combines the analysis of differences in means of the explanatory variables ( X ) and regression estimates of the coefficients associated with these variables (β X ).…”

“…Some previous studies have shown that child undernutrition clusters in specific regions in developing countries (Fenn, Morris, & Frost, 2004;Gebreyesus, Mariam, Woldehanna, & Lindtjorn, 2016) and different types of spatial analysis studies have been conducted to identify geographical inequalities in child stunting (Fenn et al, 2004, Gebreyesus et al, 2016, Adekanmbi, Uthman, & Mudasiru, 2013, Alemu, Ahmed, Yalew, & Birhanu, 2016. However, much less has been done on explaining the factors that contribute to spatial variability in stunting (Di Cesare et al, 2015;Haile, Azage, Mola, & Rainey, 2016;Sharaf & Rashad, 2016;Srinivasan, Zanello, & Shankar, 2013), particularly in India. Although India is a highly populated country with a high burden of stunting, limited evidence exists on spatial analysis to examine the patterns of stunting across the country.…”

Trends and drivers of change in the prevalence of anaemia among 1 million women and children in India, 2006 to 2016

“…In contrast, if a determinant has either a small regression coefficient or small change over time, the decomposition analysis will not identify the determinant as an important driver of anaemia reduction. Regression-decomposition has been used widely to study mean outcome differences between groups, 33 including differences in child malnutrition between geographical areas 34–36 and between populations measured at different points of time. 37 Because changes in Hb and anaemia were minimal for non-pregnant women, the decomposition analyses were conducted only for children and pregnant women.…”

Prevalence of Short Stature and Malnutrition among Egyptian Primary School Children and their Coexistence with Anemia

“…41,42 SES and rural-urban inequalities in underweight were observed in our study and also have been highlighted by many studies. [43][44][45] Inequality of income between rural and urban households explains most of the malnutrition gap. 44 Understanding of the nature and the underlying factors behind urban-rural health inequalities may help in designing effective measures for improving population health.…”

“…[43][44][45] Inequality of income between rural and urban households explains most of the malnutrition gap. 44 Understanding of the nature and the underlying factors behind urban-rural health inequalities may help in designing effective measures for improving population health. Present study reported that about 21.8% of the children were overweight and obese, it is much close to the global prevalence which has risen dramatically from just 4% in 1975 to over 18% in 2016.…”