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(http://www.niehs.nih.gov//portfolio/index.cfm?do=portfolio.grantdetail&&grant_number=R01ES032612&format=word)
| Principal Investigator: James, Katherine A | |
|---|---|
| Institute Receiving Award | University Of Colorado Denver |
| Location | Aurora, CO |
| Grant Number | R01ES032612 |
| Funding Organization | National Institute of Environmental Health Sciences |
| Award Funding Period | 05 Aug 2021 to 31 May 2026 |
| DESCRIPTION (provided by applicant): | 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. |
| Science Code(s)/Area of Science(s) |
Primary: 47 - Aging Secondary: 03 - Carcinogenesis/Cell Transformation |
| Publications | No publications associated with this grant |
| Program Officer | Ashlinn Quinn |