Environmental health exposures to airborne chemicals often originate from chemical mixtures. Environmental health professionals may be interested in assessing exposure to one or more of the chemicals in these mixtures, but often exposure measurement data are not available, either because measurements were not collected/assessed for all exposure scenarios of interest or because some of the measurements were below the analytical methods' limits of detection (i.e. censored). In some cases, based on chemical laws, two or more components may have linear relationships with one another, whether in a single or in multiple mixtures. Although bivariate analyses can be used if the correlation is high, often correlations are low. To serve this need, this paper develops a multivariate framework for assessing exposure using relationships of the chemicals present in these mixtures. This framework accounts for censored measurements in all chemicals, allowing us to develop unbiased exposure estimates. We assessed our model's performance against simpler models at a variety of censoring levels and assessed our model's 95% coverage. We applied our model to assess vapor exposure from measurements of three chemicals in crude oil taken on the Ocean Intervention III during the Deepwater Horizon oil spill response and clean-up.

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使用多个化学预测因子预测暴露的多元左删失贝叶斯模型

空气中化学物质的环境健康暴露通常来自化学混合物。环境卫生专业人员可能对评估对这些混合物中的一种或多种化学品的暴露感兴趣，但通常无法获得暴露测量数据，因为没有针对所有感兴趣的暴露场景收集/评估测量值，或者因为某些测量值是低于分析方法的检测限（即删失）。在某些情况下，根据化学定律，两种或多种成分可能彼此具有线性关系，无论是在单一混合物中还是在多种混合物中。虽然如果相关性很高，可以使用双变量分析，但相关性通常很低。为了满足这一需求，本文使用这些混合物中存在的化学物质的关系开发了一个用于评估暴露的多变量框架。该框架考虑了所有化学品中的审查测量，使我们能够制定无偏见的暴露估计。我们在各种审查级别上针对更简单的模型评估了我们的模型的性能，并评估了我们模型的 95% 覆盖率。我们应用我们的模型来评估在深水地平线溢油响应和清理期间对海洋干预 III 中原油中三种化学物质的测量结果的蒸气暴露。s 95% 的覆盖率。我们应用我们的模型来评估在深水地平线溢油响应和清理期间对海洋干预 III 中原油中三种化学物质的测量结果的蒸气暴露。s 95% 的覆盖率。我们应用我们的模型来评估在深水地平线溢油响应和清理期间对海洋干预 III 中原油中三种化学物质的测量结果的蒸气暴露。