92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Tuesday, 24 January 2012: 11:15 AM
Community-Level Indicators of Vulnerability to Heat Stress in North Carolina
Room 333 (New Orleans Convention Center )
Margaret Mae Kovach, Southeast Regional Climate Center, Chapel Hill, NC; and C. M. Fuhrmann, C. E. Konrad, and C. Harrison

Exposure to extreme heat can overwhelm a person's ability to thermoregulate, increasing the likelihood of succumbing to heat stroke or exacerbating pre-existing medical conditions. The health impacts of heat can largely be managed through preparedness plans that target the most vulnerable populations and communities. While many studies of heat-related morbidity and mortality have focused on characterizing individuals most at risk, far fewer studies have examined the socio-economic conditions and demographic characteristics that make these individuals particularly vulnerable. In this study, Geographic Information Systems (GIS) techniques are employed to relate emergency department (ED) admissions for heat stress to various community level demographic characteristics across the state of North Carolina. Due to its humid subtropical climate, topographic variability, diverse demographics, and statewide morbidity surveillance network, North Caroline provides an excellent setting to study local indicators of vulnerability to heat stress. Data on ED admissions are acquired from the North Carolina Disease Tracking and Epidemiologic Collection Tool (NC DETECT) and are utilized to provide detailed information of all heat-related admissions from 2006 to 2008 across the state. A wide range of demographic information, including housing, education level, racial status, income, employment, and age information is obtained from census data and interpolated to the zip code level to match the scale of ED data. Additionally, satellite land cover data is obtained from Earth Satellite Corporation (EarthSat) and extrapolated to the zip code level to provide a dominant land cover type. These land cover types play a strong role in mediating temperature and humidity at a local scale across the study region. Geographical regression analyses are employed to tie heat related ED admissions to the demographic and land cover attributes at the zip code level.

Supplementary URL: