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 $\ge 30$ years, it is concentrated among the younger women.

在大多数撒哈拉以南非洲国家，儿童死亡率一直很高。分析决定因素或协变量的大部分工作都没有考虑死亡风险的持续时间。此外，协变量通常与响应变量的平均值相关联，从而忽略了与其他较高矩的可能关联。在本文中，我们通过儿童死亡率指数来说明暴露的持续时间，该指数定义为2013年尼日利亚人口与健康调查中捕获的所有妇女的观察到的儿童死亡与预期儿童死亡的比率。根据此指数，采用结构化的累加分布β回归模型来检验协变量对妇女无子女死亡率，有条件的死亡率预期和死亡率分布的影响，控制潜在的空间关联。我们的推理框架是贝叶斯推理，由基于迭代加权最小二乘的通用MCMC工具提供支持。结果证实，在尼日利亚各州，没有儿童死亡的妇女的可能性以及死亡率的分布存在显着差异。研究结果还表明，尽管死亡率在年龄较大的女性中相当分散$\ge 30$ 年，它集中于年轻妇女。