论文标题
使用贝叶斯等级惩罚的键回归模型估算全球国家的死产时间
Estimating the timing of stillbirths in countries worldwide using a Bayesian hierarchical penalized splines regression model
论文作者
论文摘要
减轻死产的全球负担对于改善儿童和孕产妇健康很重要。感兴趣的是理解死产时机中的模式 - 即，无论是出现在人体内还是天前时期），因为发生内部发生的死亡是可以在很大程度上预防的。但是，关于死产时机的数据可用性在世界范围内变化很大，低收入和中等收入国家通常几乎没有可靠的观察结果。在本文中，我们开发了一个贝叶斯惩罚的花键回归框架，以估计全球所有国家的死产的比例。该模型说明了与新生儿死亡率的已知关系，跨地理区域的信息汇总信息，并根据数据属性结合了不同的错误，并允许数据驱动的时间趋势。提出了加权程序来说明非代表性的亚国家数据。结果表明，随着时间的流逝，产前比例通常在减少，但是在某些地区，尤其是撒哈拉以南非洲，进展速度较慢。
Reducing the global burden of stillbirths is important to improving child and maternal health. Of interest is understanding patterns in the timing of stillbirths -- that is, whether they occur in the intra- or antepartum period -- because stillbirths that occur intrapartum are largely preventable. However, data availability on the timing of stillbirths is highly variable across the world, with low- and middle-income countries generally having few reliable observations. In this paper we develop a Bayesian penalized splines regression framework to estimate the proportion of stillbirths that are intrapartum for all countries worldwide. The model accounts for known relationships with neonatal mortality, pools information across geographic regions, incorporates different errors based on data attributes, and allows for data-driven temporal trends. A weighting procedure is proposed to account for unrepresentative subnational data. Results suggest that the intrapartum proportion is generally decreasing over time, but progress is slower in some regions, particularly Sub-Saharan Africa.
