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- Publisher Website: 10.1016/j.envint.2017.09.011
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- PMID: 28934628
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Article: The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather
Title | The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather |
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Authors | |
Keywords | Heat vulnerability index Case-crossover analysis Spatial mapping Hot weather mortality Index performance Public health |
Issue Date | 2017 |
Citation | Environment International, 2017, v. 109, p. 42-52 How to Cite? |
Abstract | © 2017 The Authors Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998–2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68–0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat. |
Persistent Identifier | http://hdl.handle.net/10722/265718 |
ISSN | 2023 Impact Factor: 10.3 2023 SCImago Journal Rankings: 3.015 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Krstic, Nikolas | - |
dc.contributor.author | Yuchi, Weiran | - |
dc.contributor.author | Ho, Hung Chak | - |
dc.contributor.author | Walker, Blake B. | - |
dc.contributor.author | Knudby, Anders J. | - |
dc.contributor.author | Henderson, Sarah B. | - |
dc.date.accessioned | 2018-12-03T01:21:29Z | - |
dc.date.available | 2018-12-03T01:21:29Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Environment International, 2017, v. 109, p. 42-52 | - |
dc.identifier.issn | 0160-4120 | - |
dc.identifier.uri | http://hdl.handle.net/10722/265718 | - |
dc.description.abstract | © 2017 The Authors Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998–2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68–0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat. | - |
dc.language | eng | - |
dc.relation.ispartof | Environment International | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Heat vulnerability index | - |
dc.subject | Case-crossover analysis | - |
dc.subject | Spatial mapping | - |
dc.subject | Hot weather mortality | - |
dc.subject | Index performance | - |
dc.subject | Public health | - |
dc.title | The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather | - |
dc.type | Article | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1016/j.envint.2017.09.011 | - |
dc.identifier.pmid | 28934628 | - |
dc.identifier.scopus | eid_2-s2.0-85029475062 | - |
dc.identifier.volume | 109 | - |
dc.identifier.spage | 42 | - |
dc.identifier.epage | 52 | - |
dc.identifier.eissn | 1873-6750 | - |
dc.identifier.isi | WOS:000413744800005 | - |
dc.identifier.issnl | 0160-4120 | - |