Uranium exposure in drinking water and cardiovascular disease in the Strong Heart Study

项目总结 铀(U)是一种自然存在的元素，可能与心血管健康结局有关。横穿 美国，铀通过风和水的侵蚀释放到环境中，以及 人为开采、碾磨等多种形式的铀加工。重要的是，U在美国印第安人中无处不在 (AI)心血管疾病(CVD)负担高得不成比例的社区，以及U 通过饮用水接触仍然是一个令人担忧的问题。而公共场所中铀的最高污染物水平(MCL) 水系统(30微克/L)于2008年生效，在此之前美国没有对MCL进行监管，AI 依赖私人水井供水的社区不受监管。强心研究(SHS)，a 北达科他州、南达科他州、亚利桑那州和俄克拉何马州人工智能社区心血管疾病的前瞻性研究， 代表了了解铀暴露对健康结果的程度和影响的重要人群。这 需要对水和内部剂量铀暴露进行全面评估，包括在 尿液。然而，尿U数据仅在基于亲属关系的SHS扩展中可用，这些扩展包括 强心家庭研究(SHFS)，需要估计整个SHS社区的这种暴露 以确定铀暴露水平升高的人群，并确定其长期健康后果。这样做的目的是 研究将1)估计SHS和SHFS参与者的水U暴露，依赖于现有的全国 地下水测量，2)估计SHS参与者的尿铀浓度 在SHFS中饮用水U和尿U浓度之间的关系，以及3)调查是否估计 SHS和SHFS中的铀暴露(水和尿液)与心血管疾病结局有关，总体上和根据 参与者地域等特点。水铀暴露估算(目标1)将依赖于社区水 来自美国环境保护局的铀浓度的系统估计 水文地球化学和水系沉积物勘测数据库，包括355,547个采样点 在1975至1980年间收集的整个连续的美国；USGS国家水信息系统，它 提供全美190多万个地点的水资源数据；强心水研究是一项试点 家庭用水U措施研究(n=441)；以及美国地质调查局勘测研究。这些数据集将是 用于将水U度量值分配给家庭位置。对于目标2，估计水量之间的关系 SHFS中的铀暴露和尿铀浓度将被用来预测SHS参与者的尿U值 使用机器学习方法。对于目标3，我们将调查估计水量和 SHS和SHFS患者尿铀浓度与临床和亚临床心血管结局的关系 参与者。这项工作将评估整个SHS中的U暴露，识别风险增加的人群 与铀相关的心血管疾病结果，并为干预措施提供信息，以减少人工智能社区和其他社区的水铀暴露 美国各地同样受到铀暴露影响的社区。

PROJECT SUMMARY Uranium (U) is a naturally occurring element potentially associated with cardiovascular health outcomes. Across the United States (US), U is released into the environment through wind and water erosion, as well as anthropogenic mining, milling and other forms of U processing. Importantly, U is ubiquitous in American Indian (AI) communities, where the cardiovascular disease (CVD) burden remains disproportionally high, and U exposure via drinking water remains a concern. While the maximum contaminant level (MCL) for U in public water systems (30 µg/L) took effect in 2008, no MCL was regulated in the US prior to this time, and AI communities relying on private wells for drinking water are not regulated. The Strong Heart Study (SHS), a prospective study of CVD among AI communities in North Dakota, South Dakota, Arizona and Oklahoma, represents an important population to understand the extent and impact of U exposure on health outcomes. This requires a comprehensive assessment of both water and internal dose U exposure, including U measured in urine. However, urinary U data is only available in a kinship-based extension of the SHS, those comprising the Strong Heart Family Study (SHFS), and there is need to estimate this exposure across the entire SHS community to identify those with elevated U exposure and determine the long-term health outcomes. The objectives of this study are to 1) estimate water U exposure in SHS and SHFS participants relying on existing nationwide groundwater measurements, 2) estimate urinary U concentrations in SHS participants leveraging the associations between drinking water U and urinary U concentrations in the SHFS, and 3) investigate if estimated U exposure (water and urinary) in the SHS and SHFS is linked to CVD outcomes, both overall, and according to participant region and other characteristics. Water U exposure estimations (Aim 1) will rely on community water system estimations of U concentrations derived from the US EPA, the National Uranium Resource Evaluation Hydrogeochemical and Stream Sediment Reconnaissance database, which includes 335,547 sampling locations across the contiguous US collected from 1975 to 1980; the USGS National Water Information System, which provides water-resources data on over 1.9 million sites across the US; the Strong Heart Water Study, a pilot study of household water U measures (n = 441); and the USGS Reconnaissance study. These datasets will be used to assign water U measures to household locations. For Aim 2, the relationship between estimated water U exposure and urinary U concentrations in SHFS will be used to predict urinary U values in SHS participants with machine learning approaches. For Aim 3, we will investigate the association between estimated water and urinary U concentrations with both clinical and subclinical cardiovascular outcomes in SHS and SHFS participants. This work will estimate U exposure across the entire SHS, identify populations at increased risk of U-related CVD outcomes, and inform interventions to reduce water U exposure in AI communities and other communities equally affected by U exposure across the US.