ESTIMATING THE HEALTH EFFECTS OF ENVIRONMENTAL MIXTURES USING BAYESIAN SEMIPARAMETRIC REGRESSION AND SPARSITY INDUCING PRIORS
ESTIMATING THE HEALTH EFFECTS OF ENVIRONMENTAL MIXTURES USING BAYESIAN SEMIPARAMETRIC REGRESSION AND SPARSITY INDUCING PRIORS
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DOI：
10.1214/19-aoas1307
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发表时间：
2020-03-01
影响因子：
1.8
通讯作者：
Coull, Brent
中科院分区：
文献类型：
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作者：
Antonelli, Joseph;Mazumdar, Maitreyi;Coull, Brent
人类经常暴露于化学品和其他环境因素的混合物中，因此量化与环境混合物相关的健康影响是制定充分保护人类健康的环境政策的关键目标。对接触环境混合物的影响进行量化提出了若干统计挑战。通常情况下，暴露于多种污染物会相互作用，从而影响结果。此外，结果与某些暴露（如某些金属）之间的风险-响应关系可能表现出复杂的非线性形式，因为某些暴露在不同的暴露范围内可能是有益的，也可能是有害的。为了估计复杂混合物的健康影响，我们提出了一种灵活的贝叶斯方法，允许暴露相互作用，并与结果有非线性关系。我们使用多变量尖峰和板先验来诱导稀疏性，以确定哪些曝光与结果相关，哪些曝光相互作用。所提出的方法是可解释的，因为我们可以使用包含到模型中的后验概率来识别相互作用的污染物。我们利用我们的方法来研究接触金属对孟加拉国儿童神经发育的影响，并发现砷和锰之间存在非线性的相互作用关系。
Humans are routinely exposed to mixtures of chemical and other environmental factors, making the quantification of health effects associated with environmental mixtures a critical goal for establishing environmental policy sufficiently protective of human health. The quantification of the effects of exposure to an environmental mixture poses several statistical challenges. It is often the case that exposure to multiple pollutants interact with each other to affect an outcome. Further, the exposure-response relationship between an outcome and some exposures, such as some metals, can exhibit complex, nonlinear forms, since some exposures can be beneficial and detrimental at different ranges of exposure. To estimate the health effects of complex mixtures, we propose a flexible Bayesian approach that allows exposures to interact with each other and have nonlinear relationships with the outcome. We induce sparsity using multivariate spike and slab priors to determine which exposures are associated with the outcome and which exposures interact with each other. The proposed approach is interpretable, as we can use the posterior probabilities of inclusion into the model to identify pollutants that interact with each other. We utilize our approach to study the impact of exposure to metals on child neurodevelopment in Bangladesh and find a nonlinear, interactive relationship between arsenic and manganese.