Gayawan Ezra, Fasusi Oluwatoyin Deborah, Bandyopadhyay Dipankar
Department of Statistics, Federal University of Technology, Akure, Nigeria.
Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Spat Stat. 2020 Mar;35. doi: 10.1016/j.spasta.2020.100415. Epub 2020 Jan 30.
Child mortality has remained persistently high in most sub-Saharan African countries. Majority of the effort in analyzing the determinants, or covariables did not consider the duration of exposure to mortality risks. In addition, covariates are usually linked to the mean of the response variable, thereby neglecting the possible association with other higher moments. In this paper, we account for the duration of exposure via the child mortality index, defined as the ratio of observed to expected child death, for all women captured in the 2013 Nigeria Demographic and Health Survey. Based on this index, a structured additive distributional beta regression model was adopted to examine covariate effects on the probability of a woman experiencing no child mortality, the conditional expectation of mortality, and the mortality spread, controlling for latent spatial associations. Our inferential framework is Bayesian inference, powered by generic MCMC tools based on iterative weighted least squares. Results confirm the existence of significant variation in the likelihood of a woman experiencing no child mortality, and in the spread of mortality, across Nigerian states. Findings also show that although mortality is fairly spread among women aged ≥30 years, it is concentrated among the younger women.
在撒哈拉以南非洲的大多数国家,儿童死亡率一直居高不下。在分析决定因素或协变量时,大部分工作都没有考虑暴露于死亡风险的持续时间。此外,协变量通常与响应变量的均值相关联,从而忽略了与其他高阶矩的可能关联。在本文中,我们通过儿童死亡率指数来考虑暴露持续时间,该指数定义为观察到的儿童死亡与预期儿童死亡之比,适用于2013年尼日利亚人口与健康调查中涵盖的所有女性。基于该指数,我们采用了结构化加法分布贝塔回归模型,以检验协变量对女性未经历儿童死亡概率、死亡率的条件期望以及死亡率离散度的影响,并控制潜在的空间关联。我们的推断框架是贝叶斯推断,由基于迭代加权最小二乘法的通用MCMC工具提供支持。结果证实,在尼日利亚各州,女性未经历儿童死亡的可能性以及死亡率离散度存在显著差异。研究结果还表明,虽然死亡率在30岁及以上女性中分布较为均匀,但集中在年轻女性中。