Summer heat and mortality in New York City: how hot is too hot?
Background: To assess the public health risk of heat waves and to set criteria for alerts for excessive heat, various meteorologic metrics and models are used in different jurisdictions, generally without systematic comparisons of alternatives. We report such an analysis for New York City that compa...
| Publicado en: | Environmental Health Perspectives Vol. 118; no. 1; pp. 80 - 87 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
National Institute of Environmental Health Sciences
Jan2010
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105155881&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105155881 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00916765 3B5 jtl: Environmental Health Perspectives issn: 00916765 maglogo: N pubinfo: dt: Jan2010 vid: 118 iid: 1 pid: 56539 pub: National Institute of Environmental Health Sciences place: Research Triangle Park, North Carolina artinfo: ui: 105155881 2010605514 10.1289/ehp.0900906 NLM20056571 PMC2831972 105155881 ppf: 80 ppct: 7 formats: fmt: @attributes: type: P tig: atl: Summer heat and mortality in New York City: how hot is too hot? aug: au: Metzger KB Ito K Matte TD affil: Bureau of Environmental Surveillance and Policy, New York City Department of Health and Mental Hygiene, New York, New York 10007 sug: subj: Climate Heat Mortality Public Health Cause of Death Data Analysis Software Funding Source Goodness of Fit Chi Square Test Human New York Poisson Distribution ab: Background: To assess the public health risk of heat waves and to set criteria for alerts for excessive heat, various meteorologic metrics and models are used in different jurisdictions, generally without systematic comparisons of alternatives. We report such an analysis for New York City that compared maximum heat index with alternative metrics in models to predict daily variation in warm-season natural-cause mortality from 1997 through 2006. Materials and methods: We used Poisson time-series generalized linear models and generalized additive models to estimate weather-mortality relationships using various metrics, lag and averaging times, and functional forms and compared model fit. Results: A model that included cubic functions of maximum heat index on the same and each of the previous 3 days provided the best fit, better than models using maximum, minimum, or average temperature, or spatial synoptic classification (SSC) of weather type. We found that goodness of fit and maximum heat index-mortality functions were similar using parametric and nonparametric models. Same-day maximum heat index was linearly related to mortality risk across its range. The slopes at lags of 1, 2, and 3 days were flat across moderate values but increased sharply between maximum heat index of 95°F and 100°F (35-38°C). SSC or other meteorologic variables added to the maximum heat index model moderately improved goodness of fit, with slightly attenuated maximum heat index-mortality functions. Conclusions: In New York City, maximum heat index performed similarly to alternative and more complex metrics in estimating mortality risk during hot weather. The linear relationship supports issuing heat alerts in New York City when the heat index is forecast to exceed approximately 95-100°F. Periodic city-specific analyses using recent data are recommended to evaluate public health risks from extreme heat. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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