Estimating perinatal critical windows of susceptibility to environmental mixtures via structured Bayesian regression tree pairs.
Estimating perinatal critical windows of susceptibility to environmental mixtures via structured Bayesian regression tree pairs.
复制标题
通过结构化贝叶斯回归树对估计围产期对环境混合物敏感性的关键窗口。
DOI：
10.1111/biom.13568
复制
发表时间：
2023
期刊：
影响因子：
1.9
通讯作者：
Wilson,Ander
中科院分区：
文献类型：
--
作者：
Mork,Daniel;Wilson,Ander
母亲在怀孕期间接触环境化学品可能会改变分娩和儿童的健康结果。研究旨在确定暴露可能改变未来健康结果的关键窗口和时间段，并估计风险-反应关系。现有的统计方法侧重于估计在高时间分辨率下观察到的母体暴露于单一环境化学品（例如，怀孕期间每周一次）和儿童的健康结果。扩展到在高时间分辨率下观察到的多种化学品会带来维度问题，并且缺乏统计方法。我们提出了一个回归树为基础的模型，在高时间分辨率观察到的曝光的混合物。所提出的方法使用一个附加的合奏树对，定义结构化的主效应和时间分辨的预测之间的相互作用，并进行变量选择，选择出的模型预测与结果不相关。在模拟中，我们表明，基于树的方法比现有的方法进行更好的单次曝光，并可以准确地估计混合物的安全性-响应关系的临界窗口。我们应用我们的方法来估计在科罗拉多丹佛市出生队列中，整个妊娠期每周测量的五种暴露与出生体重之间的关系。我们确定了细颗粒物，二氧化硫和温度与出生体重呈负相关的关键窗口以及细颗粒物和温度之间的相互作用。软件在R软件包dlmtree中提供。
Maternal exposure to environmental chemicals during pregnancy can alter birth and children's health outcomes. Research seeks to identify critical windows, time periods when exposures can change future health outcomes, and estimate the exposure–response relationship. Existing statistical approaches focus on estimation of the association between maternal exposure to a single environmental chemical observed at high temporal resolution (e.g., weekly throughout pregnancy) and children's health outcomes. Extending to multiple chemicals observed at high temporal resolution poses a dimensionality problem and statistical methods are lacking. We propose a regression tree–based model for mixtures of exposures observed at high temporal resolution. The proposed approach uses an additive ensemble of tree pairs that defines structured main effects and interactions between time-resolved predictors and performs variable selection to select out of the model predictors not correlated with the outcome. In simulation, we show that the tree-based approach performs better than existing methods for a single exposure and can accurately estimate critical windows in the exposure–response relation for mixtures. We apply our method to estimate the relationship between five exposures measured weekly throughout pregnancy and birth weight in a Denver, Colorado, birth cohort. We identified critical windows during which fine particulate matter, sulfur dioxide, and temperature are negatively associated with birth weight and an interaction between fine particulate matter and temperature. Software is made available in the R package dlmtree.