Background: Virtually all heat-related morbidity/mortality (HRMM) is preventable, yet extreme heat events (EHE) remain the leading cause of weather-related deaths in the United States. There is strong scientific evidence that global warming will lead to EHE that occur with increased frequency, intensity, and altered meteorological profiles (e.g., more humid with higher nighttime temperatures). The 2003 EHE in Europe that led to >40,000 deaths, and the 2006 EHE in California that led to >600 deaths and >16,000 excess emergency department visits, highlight the urgent need to enhance heat warning systems and vulnerable population protection, under current and future climatic conditions. Improved strategies to prevent heat-related morbidity and mortality (HRMM) can be developed from analytic frameworks or models that more fully account for joint probabilities of risk factors (e.g., heat, air pollution, and co- morbidity), rather than only examine risk in the context of single (or limited number) exposure-response relations (e.g., heat indices and excess mortality estimates). Furthermore, the frameworks/models need to incorporate information at/across different geographic scales, including a much finer spatial resolution than has previously been accomplished. Goal/Specific Aims: Goal: Develop the analytic framework to: (1) advance knowledge of the relations between HRMM and ambient heat, in particular EHE with different meteorologically-defined profiles, and the underlying determinants of risk;and (2) to translate that information into public health policy guidelines that reflect current climatological conditions, and conditions that are projected to exist under different climate models and scenarios.
Aim 1 a. Identify empirically-defined climate subregions that correlate with geospatial patterns of morbidity and mortality, and determine if spatial patterns of mortality differ from those of morbidity.
Aim 1 b. Determine the meteorological parameters (individual or combinations), and thresholds for those parameters, that are most correlated with risk of emergency department visits, hospitalizations or deaths.
Aim 1 c. Identify determinants of vulnerability that modify the relations or risks observed under Specific Aim 1a and 1b, including consideration of: (1) population- related factors (e.g., sex, age, race/ethnicity, socioeconomic factors), and (2) environmental factors (e.g., land-use, urbanization, air quality).
Aim 2 : Based on information and models derived under Aim 1, model projected HRMM for selected General Circulation Models (GCM) and scenarios in the IPCC database. Methods: The overall analytic strategy is to conduct a series of quantitative evaluations at different geographical/spatial scales using measured and modeled meteorological data, and readily available secondary morbidity/mortality data (emergency department visits, hospitalizations, and vital statistics death certificate data) and risk factor data (e.g., health status/co-morbidities, demographics, social/behavioral factors, and land surface and built environment characteristics). To integrate this information we will develop a Multi-Determinant Model and Integrated Assessment framework. Analyses of projected HRMM risks will incorporate information derived from analyses of relevant parameters from a carefully selected subset of GCM and scenarios available in the IPCC4 database. We will evaluate a range of model projections on their coarse global grid as well as dynamically downscaled over key time periods to 10km resolution over California by the ECPC-RSM regional model. Geographical Information Systems (GIS) technology and advanced geostatistical, as well as traditional statistical and epidemiological analytic methods will be used to treat data and develop risk estimates. The study capitalizes on the infrastructure of the California Environmental Health Tracking Program (EHTP) sponsored by the Centers for Disease Control and Prevention, and Scripps Institution of Oceanography, Climate, Atmospheric Science and Physical Oceanography programs. Expected Results: An analytic framework will be established to assess past and future climatological influences on HRMM in California. Information derived from this framework will be translated to enhance heat warning systems and develop strategies to reduce community, population and individual vulnerability - with relevance to millions of California residents, and potentially many other U.S. populations. The models can be used to assess efficacy of heat warning systems and interventions and other adaptation strategies, and of climate change mitigation strategies.

Public Health Relevance

(provided by applicant): All heat-related morbidity/mortality is preventable, yet heat waves remain the leading cause of weather-related deaths in the United States and climate change is predicted to increase the frequency and intensity of heat waves. For this project a team of public health and climate scientists will develop models and information required to enhance heat warning systems and vulnerable population protection under current and future climatic conditions in California, with relevance to all parts of the U.S.

National Institute of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
NIH Challenge Grants and Partnerships Program (RC1)
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Special Emphasis Panel (ZRG1-PSE-C (58))
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Dilworth, Caroline H
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University of California Davis
Internal Medicine/Medicine
Schools of Medicine
United States
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