Modelling Under-Five Mortality through Multilevel Structured Additive Regression with Varying Coefficients for Asia and Sub-Saharan Africa
通过比较亚洲和撒哈拉以南非洲35个国家的DHS数据，使用贝叶斯多层次离散时间生存模型，发现基线风险、家庭规模、出生年份和母亲BMI等变量对儿童死亡率有显著非线性影响，且区域间决定因素差异明显。
Despite improvements in global child health during the last three decades, under-five mortality rates remain significantly high in sub-Saharan Africa and Asia. Both regions did not achieve the MDG target of reducing under-five mortality rates by two thirds by 2015. The underlying causes of under-five 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-five mortality rates, we aim to identify differences between the determinants of under-five mortality in these regions. We analyse a large sample of DHS data sets consisting of 35 sub-Saharan African countries and 13 Asian countries from 1992 to 2016. Using a discrete-time survival model that takes advantage of a recently developed multilevel framework in a Bayesian setting, allowing for important non-linear effects and cluster specific heterogeneity. We find strong non-linear effects for the baseline hazard, the household size, the year of birth, and the mother’s BMI. We find considerable differences in determinants between Asian and sub-Saharan African countries. This highlights the necessity to expand our current knowledge of the underlying mechanisms, and helps to formulate policy advices.