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首页> 外文期刊>Environmental Science & Technology >Demographic and Behavioral Modifiers of Arsenic Exposure Pathways: A Bayesian Hierarchical Analysis of NHEXAS Data
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Demographic and Behavioral Modifiers of Arsenic Exposure Pathways: A Bayesian Hierarchical Analysis of NHEXAS Data

机译:砷暴露途径的人口统计学和行为修饰因子:NHEXAS数据的贝叶斯层次分析

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摘要

We introduce a Bayesian hierarchical statistical model that describes subpopulation-specif ic pathways of exposure to arsenic. Our model is fitted to data collected as part of the National Human Exposure Assessment Survey (NHEXAS) and builds on the structural-equation-based analysis of the same data by Clayton et al. (Journal of Exposure Analysis and Environmental Epidemiology, 2002,12,29-43). Using demographic information (e.g., gender or age) and surrogates for environmental exposure (e.g., tobacco usage or the average number of minutes spent in an enclosed workshop), we identify subgroup differences in exposure routes. Missing and censored data, as well as uncertainty due to measurement error, are handled systematically in the Bayesian framework. Our analysis indicates that household size, amount of time spent at home, use of tapwater for drinking and cooking, number of glasses of water drunk, use of central air conditioning, and use of gas equipment significantly modify the arsenic exposure pathways.
机译:我们介绍了贝叶斯分层统计模型,该模型描述了砷暴露的亚群特定途径。我们的模型适合作为国家人类暴露评估调查(NHEXAS)的一部分而收集的数据,并基于Clayton等人基于相同数据的结构方程式分析而建立。 (接触分析与环境流行病学杂志,2002,12,29-43)。使用人口统计信息(例如性别或年龄)和替代品进行环境暴露(例如烟草使用或在封闭式车间中平均花费的分钟数),我们确定暴露途径的亚组差异。在贝叶斯框架中系统地处理了丢失和检查的数据以及由于测量误差引起的不确定性。我们的分析表明,家庭规模,在家里花费的时间,使用自来水喝酒和做饭,喝杯水,使用中央空调以及使用燃气设备显着改变了砷的暴露途径。

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