Project 3: Cumulative Risk and Geospatial Health Disparities Related to Chemical and Non-Chemical Stressor Exposures

项目总结 环境健康差异是基于对多种化学品和非化学品的不同暴露。 脆弱人群中的压力源，许多与个人社会人口因素有关，其他与 他们居住的住房和社区。确定环境健康的性质和程度 在人口水平上的差异，并确定有意义的干预战略，我们需要关于 多应激源暴露模式和分析技术，以表征风险并评估 整个地理区域。数据限制包括可用的个人缺乏空间分辨率 社会人口和住房数据，或在空间解析的数据中缺乏多变量属性。此外, 尽管许多研究人员直接或间接地讨论了环境健康差距，但很少有人这样做 应用适当的分析技术，定量地确定是否存在差异(以及对谁存在差异)。 在项目3中，我们建议建立累积风险模型，并描述以下情况的性质和程度 环境健康差距与包括婴儿在内的整个生命周期的健康结果有关 人体测量(例如出生体重)、儿童生长轨迹和成人心血管死亡率。 在目标1中，我们将评估马萨诸塞州(MA)的暴露差异，使用第一个广泛的 与环境健康差距有关的地理数据库，整合了众多公共数据库和 应用网络抓取等新工具来获取新的数据流。在目标2中，我们将开发新的曝光 从我们的地理空间差异数据库中构建与住房、社区、物质困难和 社会人口压力源，使用项目1和2中的信息进行评估。暴露结构 将用于描述环境健康差异模式，还将与项目1共享，以 纳入流行病学分析。为了描述健康结果的差异，在目标3中，我们将使用 构建具有个体水平应激源暴露和属性的模拟人群的新技术 切尔西和多切斯特，马萨诸塞州，应用的方法可以外推到任何美国社区。我们会 结合化学和非化学应激源暴露模型进行累积风险评估 利用项目1中开发的模拟合成人口和多应激源流行病学模型。 最后，我们将开发和应用环境健康差距的量化衡量标准，并确定 假设性干预改变这些措施的程度。总而言之，项目3引入了一个独特的 将尖端地理空间数据与分析方法相结合，模拟个人级别的方法 在高地理分辨率下的社会人口学和暴露，以及解释和 解读环境健康差距。这些技术将提供关于环境的新见解 MA中的健康差异，方法可以外推到任何地理区域。

PROJECT SUMMARY Environmental health disparities are based on differential exposures to multiple chemical and non-chemical stressors among vulnerable populations, many related to individual sociodemographic factors, others related to the housing and neighborhoods in which they live. To determine the nature and degree of environmental health disparities at a population level, and to identify meaningful intervention strategies, we need information about multi-stressor exposure patterns and analytical techniques to characterize risk and evaluate disparities across entire geographical regions. Data limitations include lack of spatial resolution in available individual sociodemographic and housing data, or lack of multivariable attributes in spatially resolved data. In addition, although many investigators have discussed environmental health disparities directly or indirectly, few have applied appropriate analytical techniques to determine quantitatively whether disparities exist (and for whom). In Project 3 we propose to build cumulative risk models and characterize the nature and extent of environmental health disparities related to health outcomes across the life span, including infant anthropometric measures (e.g. birth weight), childhood growth trajectories, and adult cardiovascular mortality. In Aim 1 we will evaluate exposure disparities across Massachusetts (MA) using the first extensive geographical database relevant to environmental health disparities, integrating numerous public databases and applying novel tools like web scraping to obtain new data streams. In Aim 2 we will develop novel exposure constructs from our geospatial disparities database related to housing, neighborhood, material hardship, and sociodemographic stressors, evaluating them using information from Projects 1 and 2. Exposure constructs will be used to describe environmental health disparity patterns and will also be shared with Project 1 to incorporate into epidemiological analyses. To characterize disparities in health outcomes, in Aim 3 we will use novel techniques to construct simulated populations with individual-level stressor exposures and attributes in Chelsea and Dorchester, MA, applying methods that can be extrapolated to any US community. We will conduct a cumulative risk assessment by combining chemical and non-chemical stressor exposure models with the simulated synthetic population and the multi-stressor epidemiological models developed in Project 1. Finally we will develop and apply quantitative measures of environmental health disparities and determine the extent to which hypothetical interventions change these measures. In summary, Project 3 introduces a unique combination of cutting-edge geospatial data and analytical methods, approaches to simulate individual-level sociodemographics and exposures at high geographic resolution, and quantitative methods to explain and interpret environmental health disparities. These techniques will provide novel insight about environmental health disparities in MA, with methods that can be extrapolated to any geographical region.