1. Courtney Smith Prepared for the California Department of Public Health Notes All projections are in GCS North American 1983. Data sources include U.S. Census 2000, the California Energy Commission, the U.S.G.S Seamless Server, and the California Public Health Department. December 2010 Conclusion Protecting the people are most vulnerable and least able to prepare for the threat of heat waves will require a targeted strengthening of public heath services and infrastructure. Strategies that incorporate geographical and social vulnerability can help in the allocation of resources and the placement of infrastructure, such as central cooling facilities. The State should particularly focus on the LA region as its dense population and high risk means it offers the greatest opportunity for avoided heat-related morbidity. In addition to large at-risk populations, much of the LA region is a flat basin that can suffer higher temperatures with bordering mountains trapping heat. Objective To ensure the State’s public health infrastructure has the capacity to withstand the challenges to health posed by climate change and heat, it is essential to know which communities or populations are most vulnerable and then identify strategies and resources to diminish their risk. Mapping community determinants of heat vulnerability can inform local resource allocation and regional/ statewide emergency response planning efforts. Introduction Climate change is the greatest environmental health threats of the 21 st century. Many of its impacts, including increased heatwaves, are already being felt. Because not all populations are at equal health risk from heat, knowing where vulnerable populations are located can inform critical adaptation efforts. While understanding vulnerability to heat at the individual level is important, many additional factors, such as ethnicity, poverty, diabetes rates, and air conditioning prevalence are all risk factors highly associated with death from heat-related events. These community determinants of heat vulnerability were mapped to better understand the geographical location of at-risk populations in California. Methods Variable Selection Community-level variables associated with heat vulnerability were identified. Statewide data for a subsection of these were selected based on availability (summarized in Table 1). The data was aligned so increasing values correlated with higher vulnerability. Data Scaling For data not available on the census tract level, the value for larger regions were assigned to census tracts located in that region. For instance, ac prevalence was only available by Climate Zone(CZ). CZ to zip code conversions were found, allowing a conversion from zip codes to census tract by spatially joining 2009 Tiger/LINE Shapefiles for both these geographic levels. Assigning Vulnerability Scores Each variable was divided into categories based on distribution. For each variable, each census tract was assigned a score based on the categories’ influence on vulnerability (Table 2). In the absence of detailed understanding of the impacts of each variable on vulnerability, it was assumed each had equal impact and summed assigned scores (using the Union tool), creating a relative heat-vulnerability index for California. Results The map shows, that based on these four community- level variables, the Central Valley, North Central California and Los Angeles are particularly vulnerable to heat. From the contribution of each score to the final vulnerability index, it appears high levels of poverty and diabetes is driving much of the vulnerability in High diabetes and poverty levels accounts for vulnerability seen in the more rural areas. Community Determinants of Vulnerability to Heat in Los Angeles County Limitations Scaling county and larger regional data down to the census tract level for too many variables can hide many disparities between census tracts located in the same county/region. In addition, many other important community-level variables, such as amount of impervious service and green space are also strong determines of community vulnerability; however, are not included here. Heat and Elevation There is also an association between heat and land elevation due to adiabatic effects, with lower level elevations experiencing great heat. While temperature is the product of a complex system, visualizing elevation differences in the LA basin may provide insight into differential heat exposure. To do this, a DEM for the region was retrieved from the USGS Seamless Data, contours and a subsequent TIN created, then mapped using ArcScene. Elevation Model of Los Angeles Basin Air conditioning rates, poverty and demographic characteristics are all driving vulnerability in the LA area. Geographic Coordinate System: GCS_North_American_1983 Datum: D_North_American_1983 Mapping Community Determinants of Heat Vulnerability for the State of California Table 1: Heat Vulnerability Data VariableData SourceOriginal Scale Percent below 1999 national poverty line U.S. Census 2000, Summary File 3, www.factfinder.govwww.factfinder.gov Census tract (2000) Percent people of colorU.S. Census 2000, Summary File 1, www.factfinder.gov Census tract (2000) Percent of households with no central air conditioning California Energy Commission, http://www.energy.ca.gov/applia nces/rass/ http://www.energy.ca.gov/applia nces/rass/ California Energy Commission Climate Zones Percent of population with diabetes California Department of Public Health, Diabetes in California Counties, 2009 County Table 2: Vulnerability Scores VariableCategoryVulnerability Score Percent below 1999 national poverty line0-10%0 10.1-20%1 20.1-42%2 Percent people of color0-30%0 31-60%1 61-100%2 Percent of households with no central air conditioning13-15%0 15.1-21%1 21.1-27%2 27.1-55%3 55.1-79%4 Percent of population with diabetes3.5-6.3%0 6.31-7.8%1 7.81-9.7%2 Geographic Coordinate System: GCS_North_American_1983 Datum: D_North_American_1983