Statistical Approaches for Investigating Periods of Susceptibility in Children's Environmental Health Research
Statistical Approaches for Investigating Periods of Susceptibility in Children's Environmental Health Research
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DOI：
10.1007/s40572-019-0224-5
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发表时间：
2019-03-01
影响因子：
7.9
通讯作者：
Braun, Joseph M.
中科院分区：
文献类型：
--
作者：
Buckley, Jessie P.;Hamra, Ghassan B.;Braun, Joseph M.
审查目的儿童环境健康研究人员越来越有兴趣确定个人最容易受到环境暴露不利影响的时间间隔。我们回顾了最近的进展，在方法评估易感periods.Recent FindingsWe确定了三个一般类的建模方法，旨在确定儿童的环境健康研究的易感时期：多个线人模型，分布滞后模型，贝叶斯方法。传统的回归模型的好处包括能够正式测试期间的影响差异，将高度时间分辨的曝光数据，或解决曝光期间或曝光mixture.SummarySeveral统计方法之间的相关性存在调查期间的敏感性。通过开展更多的基础生物学研究，进一步发展评估对复杂接触混合物的敏感性的统计方法，开展评价模型假设的验证研究，在不同人群中开展重复研究，以及考虑从受孕前到疾病发作的敏感期，将可推进对易感期的评估。
Purpose of ReviewChildren's environmental health researchers are increasingly interested in identifying time intervals during which individuals are most susceptible to adverse impacts of environmental exposures. We review recent advances in methods for assessing susceptible periods.Recent FindingsWe identified three general classes of modeling approaches aimed at identifying susceptible periods in children's environmental health research: multiple informant models, distributed lag models, and Bayesian approaches. Benefits over traditional regression modeling include the ability to formally test period effect differences, to incorporate highly time-resolved exposure data, or to address correlation among exposure periods or exposure mixtures.SummarySeveral statistical approaches exist for investigating periods of susceptibility. Assessment of susceptible periods would be advanced by additional basic biological research, further development of statistical methods to assess susceptibility to complex exposure mixtures, validation studies evaluating model assumptions, replication studies in different populations, and consideration of susceptible periods from before conception to disease onset.