182232 Intra-urban spatial patterns of societal risk and vulnerability to heat waves

Monday, October 27, 2008

Christopher K. Uejio, MA , Nelson Institute for Environmental Studies, Center for Sustainability and the Global Environment, University of Wisconsin-Madison, Madison, WI
Olga Wilhelmi, PhD , Institute for the Study of Society and Environment, National Center for Atmospheric Research, Boulder, CO
Jay Golden, PhD , National Center of Excellence on SMART Innovations for Urban Climate + Energy, the School of Sustainability, & the CEE Dept., Arizona State University, Tempe, AZ
Dave Mills , Stratus Consulting Inc., Boulder, CO
Jason P. Samenow , Climate Change Division, US EPA, Washington, DC
A spatial analysis of societal vulnerability and risk to excessive heat were conducted for two urban areas in the United States: Phoenix, AZ and Philadelphia, PA. To identify populations at risk for adverse health outcomes during extreme heat events we analyzed two cities in terms of their climatological, environmental and societal characteristics. Geographic Information Systems (GIS) and spatial statistics were used to identify spatial patterns of biophysical and social factors contributing to the heat-related morbidity and mortality. Analysis presented in this work, expands upon previous univariate ecologic studies and takes a multivariate approach to investigate the relative importance of neighborhood level heat exposure, socio-economic vulnerability and neighborhood stability to heat morbidity or mortality. We also compare the sensitivity and specificity of two multivariate statistical methods; a traditional Generalized Linear Model and a machine learning Classification and Regression Tree algorithm. Philadelphia neighborhoods with heat mortality cases are characterized by low housing values and a higher fraction of black residents. Such characteristics interestingly also describe neighborhoods with a disproportionate burden of lead poisoning cases. Phoenix neighborhoods with high heat distress calls tend to have a higher fraction of socially isolated, black, hispanic, disabled, and linguistically isolated residents. Enhanced urban heat island effect temperatures measured from remotely sensed satellite imagery also explains heat distress call variability across the city. A similar societal risk and vulnerability analysis may be particularly beneficial for municipalities without a heat wave preparedness plan or a comprehensive heat watch/warning system.

Learning Objectives:
1. Recognize that heat wave mortality accounts for more fatalities in the United States than any other weather hazard. 2. Articulate the potential benefits and limitations of a neighborhood level ecologic study for identifying negative health outcome risk groups. 3. Compare and contrast multivariate statistical and Geographic Information Systems techniques for quantifying and mapping health risk.

Keywords: Environmental Justice, Geographic Information Systems

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: of my education and research experience. I have a strong educational background in frequentist statistics, geographic and spatial methods, and publication record in the broader environmental health field.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.