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The predictability of high-risk zones for heat-related mortality in seven US cities

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  • David Hondula
  • Robert Davis

Abstract

Heat-related mortality remains a public health challenge in the United States. The objective of this study was to determine the temporal consistency of high-risk zones for heat-related mortality using historical georeferenced mortality data from seven US cities. A generalized additive model was used to identify city-specific threshold temperatures associated with increased mortality, and then the mortality rate on threshold-exceeding days was calculated for each postal code comprising each study city. This process was iterated by withholding subsets of data from the model and assessing predictability via cross-validation. In all cities, the average mortality rate in postal codes targeted for intervention by the statistical model was higher than that in non-targeted areas. Targeted areas for interventions in the study data accounted for 50 % of excess heat-related deaths despite only accounting for 25 % of total mortality. Focusing intervention measures at certain geographical zones within urban areas could be an effective means of combating heat-related mortality because there is temporal consistency in places where the death rate is most sensitive to heat. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • David Hondula & Robert Davis, 2014. "The predictability of high-risk zones for heat-related mortality in seven US cities," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 771-788, November.
    • Handle: RePEc:spr:nathaz:v:74:y:2014:i:2:p:771-788
    DOI: 10.1007/s11069-014-1213-5
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    References listed on IDEAS

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    1. Scott Sheridan & Adam Kalkstein & Laurence Kalkstein, 2009. "Trends in heat-related mortality in the United States, 1975–2004," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 50(1), pages 145-160, July.
    2. Vaneckova, Pavla & Beggs, Paul J. & Jacobson, Carol R., 2010. "Spatial analysis of heat-related mortality among the elderly between 1993 and 2004 in Sydney, Australia," Social Science & Medicine, Elsevier, vol. 70(2), pages 293-304, January.
    3. Smith, Claire & Levermore, Geoff, 2008. "Designing urban spaces and buildings to improve sustainability and quality of life in a warmer world," Energy Policy, Elsevier, vol. 36(12), pages 4558-4562, December.
    4. Simon N. Wood, 2003. "Thin plate regression splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 95-114, February.
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    Cited by:

    1. Pierre Valois & Denis Talbot & Maxime Caron & Marie-Pier Carrier & Alexandre J. S. Morin & Jean-Sébastien Renaud & Johann Jacob & Pierre Gosselin, 2017. "Development and Validation of a Behavioural Index for Adaptation to High Summer Temperatures among Urban Dwellers," IJERPH, MDPI, vol. 14(7), pages 1-18, July.
    2. Tanja Wolf & Wen-Ching Chuang & Glenn McGregor, 2015. "On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?," IJERPH, MDPI, vol. 12(10), pages 1-29, October.
    3. Weiwen Wang & Wen Zhou & Edward Yan Yung Ng & Yong Xu, 2016. "Urban heat islands in Hong Kong: statistical modeling and trend detection," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 885-907, September.

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