Predicting Hospitalization for Heat-Related Illness at the Census-Tract Level: Accuracy of a Generic Heat Vulnerability Index in Phoenix, Arizona (USA).
Background: Vulnerability mapping based on vulnerability indices is a pragmatic approach for highlighting the areas in a city where people are at the greatest risk of harm from heat, but the manner in which vulnerability is conceptualized influences the results. Objectives: We tested a generic natio...
| Publicado en: | Environmental Health Perspectives Vol. 123; no. 6; pp. 606 - 613 |
|---|---|
| Autores principales: | , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
National Institute of Environmental Health Sciences
Jun2015
|
| 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=103119688&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103119688 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00916765 3B5 jtl: Environmental Health Perspectives issn: 00916765 maglogo: N pubinfo: dt: Jun2015 vid: 123 iid: 6 pid: 56539 pub: National Institute of Environmental Health Sciences place: Research Triangle Park, North Carolina artinfo: ui: 103119688 103119688 103119688 10.1289/ehp.1307868 103119688 ppf: 606 ppct: 7 formats: fmt: @attributes: type: P tig: atl: Predicting Hospitalization for Heat-Related Illness at the Census-Tract Level: Accuracy of a Generic Heat Vulnerability Index in Phoenix, Arizona (USA). aug: au: Chuang, Wen-Ching Gober, Patricia affil: School of Sustainability sug: subj: Heat Adverse Effects Hospitalization Heat Stress Disorders Complications Disease Susceptibility Human Arizona Factor Analysis Descriptive Statistics Data Analysis Software Multiple Logistic Regression Spearman's Rank Correlation Coefficient Chi Square Test Aged Confidence Intervals Odds Ratio Funding Source Aged: 65+ years ab: Background: Vulnerability mapping based on vulnerability indices is a pragmatic approach for highlighting the areas in a city where people are at the greatest risk of harm from heat, but the manner in which vulnerability is conceptualized influences the results. Objectives: We tested a generic national heat-vulnerability index, based on a 10-variable indicator framework, using data on heat-related hospitalizations in Phoenix, Arizona. We also identified potential local risk factors not included in the generic indicators. Methods: To evaluate the accuracy of the generic index in a city-specific context, we used factor scores, derived from a factor analysis using census tract-level characteristics, as independent variables, and heat hospitalizations (with census tracts categorized as zero-, moderate-, or highincidence) as dependent variables in a multinomial logistic regression model. We also compared the geographical differences between a vulnerability map derived from the generic index and one derived from actual heat-related hospitalizations at the census-tract scale. Results: We found that the national-indicator framework correctly classified just over half (54%) of census tracts in Phoenix. Compared with all census tracts, high-vulnerability tracts that were misclassified by the index as zero-vulnerability tracts had higher average income and higher proportions of residents with a duration of residency < 5 years. Conclusion: The generic indicators of vulnerability are useful, but they are sensitive to scale, measurement, and context. Decision makers need to consider the characteristics of their cities to determine how closely vulnerability maps based on generic indicators reflect actual risk of harm. Citation: Chuang WC, Gober P. 2015. Predicting hospitalization for heat-related illness at the census-tract level: accuracy of a generic heat vulnerability index in Phoenix, Arizona (USA). Environ Health Perspect 123:606-612; pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|