Explaining changes in child health inequality in the run up to the 2015 Millennium Development Goals (MDGs): The case of Zambia.
BACKGROUND
Child health interventions were drastically scaled up in the period leading up to 2015 as countries aimed at meeting the 2015 target of the Millennium Development Goals (MDGs). MDGs were defined in terms of achieving improvements in average health. Significant improvements in average child health are documented, but evidence also points to rising inequality. It is important to investigate factors that drive the increasing disparities in order to inform the post-2015 development agenda of reducing inequality, as captured in the Sustainable Development Goals (SDGs). We investigated changes in socioeconomic inequality in stunting and fever in Zambia in 2007 and 2014. Unlike the huge literature that seeks to quantify the contribution of different determinants on the observed inequality at any given time, we quantify determinants of changes in inequality.


METHODS
Data from the 2007 and 2014 waves of the Zambia Demographic and Health Survey (DHS) were utilized. Our sample consisted of children aged 0-5 years (n = 5,616 in 2007 and n = 12,714 in 2014). We employed multilevel models to assess the determinants of stunting and fever, which are two important child health indicators. The concentration index (CI) was used to measure the magnitude of inequality. Changes in inequality of stunting and fever were investigated using Oaxaca-type decomposition of the CI. In this approach, the change in the CI for stunting/fever is decomposed into changes in CI for each determinant and changes in the effect-measured as an elasticity-of each determinant on stunting/fever.


RESULTS
While average rates of stunting reduced in 2014 socioeconomic inequality in stunting increased significantly. Inequality in fever incidence also increased significantly, but average rates of fever did not reduce. The increase in the inequality (CI) of determinants accounted for the largest part (42.5%) of the increase in inequality of stunting, while the increase in the effect of determinants explained 35% of the increase. The determinants with the greatest total contribution (change in CI plus change in effect) to the increase in inequality of stunting were mother's height and weight, wealth, birth order, facility delivery, duration of breastfeeding, and maternal education. For fever, almost all (86%) the increase in inequality was accounted for by the increase in the effect of determinants of fever, while the distribution of determinants mattered less. The determinants with the greatest total contribution to the increase in inequality of fever were wealth, maternal education, birth order and breastfeeding duration. In the multilevel model, we found that the likelihood of a child being stunted or experiencing fever depends on the community in which they live.


CONCLUSIONS
To curb the increase in inequality of stunting and fever, policy may focus on improving levels of, and reducing inequality in, access to facility deliveries, maternal nutrition (which may be related to maternal weight and height), complementary feeding (for breastfed children), wealth, maternal education, and child care (related to birth order effects). Improving overall levels of these determinants contribute to the persistence of inequality if these determinants are unequally concentrated on the well off to begin with.
Centre for International Health, University of Bergen, Bergen, Norway.|Unit of Health Economics, School of Public Health, University of Zambia, Lusaka, Zambia.
Peter
P
Hangoma
Department of Economics, University of Bergen, Bergen, Norway.
Arild
A
Aakvik
Centre for International Health, University of Bergen, Bergen, Norway.|Centre for Intervention Science in Maternal and Child Health, University of Bergen, Bergen, Norway.
Bjarne
B
Robberstad
D000328:Adult; D000465:Algorithms; D000067576:Child Health / Q000592:standards / Q000706:statistics & numerical data*; D002675:Child, Preschool; D005260:Female; D005334:Fever / Q000453:epidemiology; D006130:Growth Disorders / Q000453:epidemiology; D054624:Health Status Disparities; D006306:Health Surveys; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009035:Mothers; D062486:Public Health Surveillance; D012307:Risk Factors; D012959:Socioeconomic Factors; D015024:Zambia / Q000453:epidemiology