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• W2904006770 abstract "Epidemiologic analyses of the health effects of meteorological exposures typically rely on observations from the nearest weather station to assess exposure for geographically diverse populations. Gridded climate datasets (GCD) provide spatially resolved weather data that may offer improved exposure estimates, but have not been systematically validated for use in epidemiologic evaluations. As a validation, we linearly regressed daily weather estimates from two GCDs, PRISM and Daymet, to observations from a sample of weather stations across the conterminous United States and compared spatially resolved, population-weighted county average temperatures and heat indices from PRISM to single-pixel PRISM values at the weather stations to identify differences. We found that both Daymet and PRISM accurately estimate ambient temperature and mean heat index at sampled weather stations, but PRISM outperforms Daymet for assessments of humidity and maximum daily heat index. Moreover, spatially-resolved exposure estimates differ from point-based assessments, but with substantial inter-county heterogeneity. We conclude that GCDs offer a potentially useful approach to exposure assessment of meteorological variables that may, in some locations, reduce exposure measurement error, as well as permit assessment of populations distributed far from weather stations." @default.
• W2904006770 created "2018-12-22" @default.
• W2904006770 creator A5035731100 @default.
• W2904006770 creator A5075376639 @default.
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• W2904006770 date "2018-12-11" @default.
• W2904006770 modified "2023-10-16" @default.
• W2904006770 title "Suitability of gridded climate datasets for use in environmental epidemiology" @default.
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• W2904006770 doi "https://doi.org/10.1038/s41370-018-0105-2" @default.
• W2904006770 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6559872" @default.
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• W2904006770 hasPublicationYear "2018" @default.
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