S G Nayak1, S Shrestha2, P L Kinney3, Z Ross4, S C Sheridan5, C I Pantea6, W H Hsu6, N Muscatiello2, S A Hwang2. 1. New York State Department of Health, Center for Environmental Health, Empire State Plaza, Albany, NY 12237, USA. Electronic address: seema.nayak@health.ny.gov. 2. New York State Department of Health, Center for Environmental Health, Empire State Plaza, Albany, NY 12237, USA; University at Albany, SUNY, School of Public Health, Department of Epidemiology and Biostatistics, 1 University Place, Rensselaer, NY 12144, USA. 3. Boston University School of Public Health, Department of Environmental Health, 715 Albany St, Talbot 4W, Boston MA 02118-02526, USA. 4. ZevRoss Spatial Analysis, Ithaca, NY, USA. 5. Kent State University, Department of Geography, McGilvrey Hall 443, Kent, OH 44242, USA. 6. New York State Department of Health, Center for Environmental Health, Empire State Plaza, Albany, NY 12237, USA.
Abstract
OBJECTIVES: The frequency and intensity of extreme heat events are increasing in New York State (NYS) and have been linked with increased heat-related morbidity and mortality. But these effects are not uniform across the state and can vary across large regions due to regional sociodemographic and environmental factors which impact an individual's response or adaptive capacity to heat and in turn contribute to vulnerability among certain populations. We developed a heat vulnerability index (HVI) to identify heat-vulnerable populations and regions in NYS. STUDY DESIGN: Census tract level environmental and sociodemographic heat-vulnerability variables were used to develop the HVI to identify heat-vulnerable populations and areas. METHODS: Variables were identified from a comprehensive literature review and climate-health research in NYS. We obtained data from 2010 US Census Bureau and 2011 National Land Cover Database. We used principal component analysis to reduce correlated variables to fewer uncorrelated components, and then calculated the cumulative HVI for each census tract by summing up the scores across the components. The HVI was then mapped across NYS (excluding New York City) to display spatial vulnerability. The prevalence rates of heat stress were compared across HVI score categories. RESULTS: Thirteen variables were reduced to four meaningful components representing 1) social/language vulnerability; 2) socioeconomic vulnerability; 3) environmental/urban vulnerability; and 4) elderly/ social isolation. Vulnerability to heat varied spatially in NYS with the HVI showing that metropolitan areas were most vulnerable, with language barriers and socioeconomic disadvantage contributing to the most vulnerability. Reliability of the HVI was supported by preliminary results where higher rates of heat stress were collocated in the regions with the highest HVI. CONCLUSIONS: The NYS HVI showed spatial variability in heat vulnerability across the state. Mapping the HVI allows quick identification of regions in NYS that could benefit from targeted interventions. The HVI will be used as a planning tool to help allocate appropriate adaptation measures like cooling centers and issue heat alerts to mitigate effects of heat in vulnerable areas.
OBJECTIVES: The frequency and intensity of extreme heat events are increasing in New York State (NYS) and have been linked with increased heat-related morbidity and mortality. But these effects are not uniform across the state and can vary across large regions due to regional sociodemographic and environmental factors which impact an individual's response or adaptive capacity to heat and in turn contribute to vulnerability among certain populations. We developed a heat vulnerability index (HVI) to identify heat-vulnerable populations and regions in NYS. STUDY DESIGN: Census tract level environmental and sociodemographic heat-vulnerability variables were used to develop the HVI to identify heat-vulnerable populations and areas. METHODS: Variables were identified from a comprehensive literature review and climate-health research in NYS. We obtained data from 2010 US Census Bureau and 2011 National Land Cover Database. We used principal component analysis to reduce correlated variables to fewer uncorrelated components, and then calculated the cumulative HVI for each census tract by summing up the scores across the components. The HVI was then mapped across NYS (excluding New York City) to display spatial vulnerability. The prevalence rates of heat stress were compared across HVI score categories. RESULTS: Thirteen variables were reduced to four meaningful components representing 1) social/language vulnerability; 2) socioeconomic vulnerability; 3) environmental/urban vulnerability; and 4) elderly/ social isolation. Vulnerability to heat varied spatially in NYS with the HVI showing that metropolitan areas were most vulnerable, with language barriers and socioeconomic disadvantage contributing to the most vulnerability. Reliability of the HVI was supported by preliminary results where higher rates of heat stress were collocated in the regions with the highest HVI. CONCLUSIONS: The NYS HVI showed spatial variability in heat vulnerability across the state. Mapping the HVI allows quick identification of regions in NYS that could benefit from targeted interventions. The HVI will be used as a planning tool to help allocate appropriate adaptation measures like cooling centers and issue heat alerts to mitigate effects of heat in vulnerable areas.
Authors: Patricia D Koman; Frank Romo; Peter Swinton; Graciela B Mentz; Ricardo F de Majo; Natalie R Sampson; Michael J Battaglia; Kimberly Hill-Knott; Guy O Williams; Marie S O'Neill; Amy J Schulz Journal: Health Place Date: 2019-10-22 Impact factor: 4.078