This grant proposes to identify medical and other individual characteristics of persons aged over 64 years that put them at increased risk of dying due to weather, to identify interactions with air pollution that contribute to that risk, and to identify profiles of patterns of pollutants and weather parameters that are particularly associated with elevated risk. Further, we will identify characteristics of community, such as socio-economic status, percent of impermeable surface, of green space, of water, climate zone, variability of weather, air conditioning prevalence, behavioral risk, baseline disease rates, etc which modify the risk of dying, and finally, interactions between the community level and individual characteristics. Importantly, these community level characteristics will be defined on the zip code level, not the city level, allowing us to capture the impact of true local land use. In addition, examining a less explored weather parameter, we will examine the association of rainfall with hospital admissions for gastrointestinal illness in the elderly. Finally, we will conduct a pilot risk assessment using projections, again on a fine scale, of the distribution of weather and pollution in 2030 compared to today, as well as community level projects of changes in risk modifiers. The results of this analysis will aid NIH by identifying disease states that convey risk, and more broadly aid the task of identifying interventions that can improve public health by reducing risk, and where, geographically, those interventions will be most efficacious. The methods used will be case-crossover and case-only analyses to identify risk and risk modifiers, and k-clustering to group weather and air pollution parameters.
This project will identify medical conditions, demographic characteristics, neighborhood land use patterns, climate patterns, socioeconomic patterns and co-exposures to air pollutants that modify the effects of weather and weather extremes on the risk of dying in a national cohort of Medicare recipients in 135 US cities. In addition, it will identify the effects of rainfall on gastrointestinal illness in the elderly living in cities with surface water supplies.
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|Nguyen, J L; Schwartz, J; Dockery, D W (2014) The relationship between indoor and outdoor temperature, apparent temperature, relative humidity, and absolute humidity. Indoor Air 24:103-12|
|Zhang, Kai; Li, Yun; Schwartz, Joel D et al. (2014) What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods. Environ Res 132:350-9|
|Zanobetti, Antonella; O'Neill, Marie S; Gronlund, Carina J et al. (2013) Susceptibility to mortality in weather extremes: effect modification by personal and small-area characteristics. Epidemiology 24:809-19|
|Zanobetti, Antonella; O'Neill, Marie S; Gronlund, Carina J et al. (2012) Summer temperature variability and long-term survival among elderly people with chronic disease. Proc Natl Acad Sci U S A 109:6608-13|