The Impact of Drought on Arsenic Exposure and Cardiometabolic Outcomes in a Rural Aging Population

项目概要/摘要 干旱是一种重要的自然灾害，但对美国老年人的健康影响 各国尚未得到广泛研究。这项研究旨在提供心脏代谢健康的证据， 干旱带来的风险。干旱可能导致地下水过度抽取，这反过来可能导致 砷从含水层粘土释放到饮用水源。干旱对砷暴露的影响 以及由此产生的人群健康结果具有潜在的重要性，本研究旨在解决 这种知识差距。我们建议使用圣路易斯山谷的数据进行回顾性队列研究 糖尿病研究，以及对San Francisco水和环境条件的水文地质测量 Luis Valley，以澄清干旱、水中砷、砷暴露（通过尿液测量）之间的关系 生物标志物）和心脏代谢健康结果，包括新发糖尿病（DM）、新发心血管疾病 疾病（CVD）和全因死亡率。这项工作是社区参与，包括K12外展 成分目的1量化干旱与个体砷暴露以及由此与事件的关系 心血管疾病、糖尿病和死亡率。目标2生成地下水砷的函数模型， 水文预测器使用机器学习方法，并利用它来探索之间的关系 干旱，模拟水砷和目标1的结果。目标3估计了 采用巢式病例对照设计研究累积砷暴露与CVD、DM和死亡率的关系 以及Aim 2模型对砷暴露时间的预测。目标4是一项模拟研究， 未来CVD和DM结果在不同的情景下的干旱条件下，有和没有反事实 减少饮用水砷的干预措施。

Project Summary / Abstract Droughts are an important natural disaster but the health implications for elderly populations in the United States have not been extensively studied. This study seeks to provide evidence on the cardiometabolic health risks posed by drought. Droughts can contribute to groundwater over-pumping, and this may in turn lead to arsenic release from aquifer clays into drinking water sources. The impacts of drought on arsenic exposure and resultant health outcomes in human populations are potentially important and this study seeks to address that knowledge gap. We propose to conduct a retrospective cohort study using data from the San Luis Valley Diabetes Study, as well as hydrogeological measurements of water and environmental conditions in the San Luis Valley, to clarify relationships between drought, arsenic in water, arsenic exposure (as measured by urine biomarker), and cardiometabolic health outcomes including incident diabetes (DM), incident cardiovascular disease (CVD), and all-cause mortality. This work is community-engaged and includes a K12 outreach component. Aim 1 quantifies the relationship of drought to individual arsenic exposures and thence to incident CVD, incident DM, and mortality. Aim 2 generates a model for groundwater arsenic as a function of hydrological predictors using machine learning approaches, and uses this to explore relationships between drought, modeled water arsenic and the outcomes of Aim 1. Aim 3 estimates the association between cumulative arsenic exposure and incident CVD, incident DM, and mortality, using a nested case-control design and predictions over time of arsenic exposure from the Aim 2 model. Aim 4 is a simulation study projecting future CVD and DM outcomes under different scenarios of drought conditions, with and without counterfactual interventions to reduce drinking water arsenic.