Modeling under-5 mortality through multilevel structured additive regression with varying coefficients for Asia and Sub-Saharan Africa

Despite improvements in global child health within the last three decades, under-5 mortality remains significantly high in Sub-Saharan and Asia. Both regions did not achieve the MDG target of reducing under-5 mortality by two thirds by 2015. The underlying causes of under-5 mortality differ significantly between countries and between regions, which highlights the need to expand our understanding of the determinants of child health in developing countries. By comparing the two geographic regions of the world with the highest under-5 mortality rates, we aim to gain new insights, and bring out potential differences between these regions and the causes of under-5 mortality. In addition, we aim to identify non-linear relationships between under-5 mortality and specific explanatory variables. We analyze a large data set consisting of 35 Sub-Saharan-African countries, and 13 Asian countries, using a multilevel discrete time survival model that takes advantage of a recently developed multilevel framework with structured additive predictor in a Bayesian setting. We analyze data from 131 individual surveys from 1992 to 2015, allowing for potential non-linear effects and cluster specific heterogeneity within models. We find strong non-linear effects for the baseline hazard, the household size, the age of the mother, the BMI of the mother, and the birth order of the child. Additionally, we find considerable differences in determinants between Asian and Sub-Saharan Asian countries.