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Nayak SG, Shrestha S, Kinney PL, Ross Z, Sheridan SC, Pantea CI, Hsu WH, Muscatiello N, Hwang SA. Development of a heat vulnerability index for New York State. Public Health 2017; 161:127-137. [PMID: 29195682 DOI: 10.1016/j.puhe.2017.09.006] [Citation(s) in RCA: 75] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Revised: 08/11/2017] [Accepted: 09/20/2017] [Indexed: 11/25/2022]
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.
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Affiliation(s)
- S G Nayak
- New York State Department of Health, Center for Environmental Health, Empire State Plaza, Albany, NY 12237, USA.
| | - S Shrestha
- 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
| | - P L Kinney
- Boston University School of Public Health, Department of Environmental Health, 715 Albany St, Talbot 4W, Boston MA 02118-02526, USA
| | - Z Ross
- ZevRoss Spatial Analysis, Ithaca, NY, USA
| | - S C Sheridan
- Kent State University, Department of Geography, McGilvrey Hall 443, Kent, OH 44242, USA
| | - C I Pantea
- New York State Department of Health, Center for Environmental Health, Empire State Plaza, Albany, NY 12237, USA
| | - W H Hsu
- New York State Department of Health, Center for Environmental Health, Empire State Plaza, Albany, NY 12237, USA
| | - N Muscatiello
- 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
| | - S A Hwang
- 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
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Abstract
Data from the telephone interview portion of the New York State Farm Family Health and Hazard Surveillance Project were used to study the prevalence and predictors of joint pain in a cohort of farmers and farm residents. The participants were owner/operators, workers, and residents from a representative sample of farms from 12 New York counties. A total of 1706 participants completed a telephone interview on musculoskeletal conditions. Joint trouble was defined as self-reported aches, pain, or discomfort in the past year in each of five different joint areas. The 12-month prevalence of joint trouble was: lower back 41%, neck/shoulders 35%, knees 29%, hands/wrists 28%, and hips 15%. Using logistic regression modeling, significant risk factors for joint trouble were identified (p < 0.05). Older age and being female increased the risk of aches, pain, or discomfort in most joints. Being the owner/operator increased the risk of neck/shoulder and lower back trouble, and being a worker increased the risk of neck/shoulder trouble. Doing tractor work was associated with trouble in all five joint areas, and milking was associated with knee trouble. These findings indicate that personal risk factors and the intensity and nature of the farm work contribute to joint trouble. Ergonomic improvements to tractors and milking facilities should be a high priority.
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Affiliation(s)
- M I Gomez
- Center for Environmental Health, Bureau of Environmental and Occupational Epidemiology, New York State Department of Health, 547 River Street, Room 200, Troy, NY 12180-2216, USA.
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Abstract
BACKGROUND This study was conducted to assess the health status and safety practices among year-round adult farm workers and residents and included a telephone interview survey of 1,727 persons from 552 farms. METHODS Logistic regression was used to analyze four safety questions. RESULTS Among 541 farm owner/operators significant predictors of making substitutions in the use of chemicals and major changes to equipment include younger age, more persons assisting on the farm, and higher gross sales. Having training is associated with having more than a high school education. Among all participants the perception that personal protective equipment are useful is associated with being younger, male, an owner/operator or worker, and having at least a high school education. CONCLUSIONS These findings suggest that older and less educated farmers should be targeted for health and safety programs.
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Affiliation(s)
- S A Hwang
- Bureau of Environmental and Occupational Epidemiology, New York State Department of Health, Troy, New York 12180-2216, USA.
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