Authors: Jihoon Jung*, Florida State University, Christopher K. Uejio, Floridat State Univeristy, Chris Duclos, Florida Department of Health, Melissa Jordan, Florida Department of Health, Keshia Reid, Florida Department of Health, Kristina Kintziger, University of Tennessee, Tabassum Insaf, New York State Department of Health
Topics: Medical and Health Geography, Climatology and Meteorology, Applied Geography
Keywords: Heat, vulnerability, health, case-crossover
Session Type: Paper
Start / End Time: 9:55 AM / 11:35 AM
Room: Madison A, Marriott, Mezzanine Level
Presentation File: No File Uploaded
This study investigated the vulnerability to heat exposure at the county level in Florida, U.S. The research area included all 67 counties in the state. The analysis period was from May to September 2008 to 2013. We used four kinds of data: 1) weather (temperature and humidity), 2) air pollution (ozone and PM 2.5), 3) health outcomes (emergency department (ED) and hospitalization admission for cardiovascular disease, dehydration, renal illness, respiratory disease, and heat-related illness), and, 4) socio-economic and demographic data. This study used the case-crossover analysis to examine the effects of air temperature on daily counts of health outcomes while controlling for air pollution exposure. We used a time-stratified design with a 28 day comparison window. Referent periods were extracted from ±7 and ±14 days to remove seasonality. The study has three main objectives. First, the study analyzes the risk of heat exposure for each disease category. Second, the study investigates whether the impact of heat exposure was modified by race, age, and sex. Lastly, we spatially examine the relationship between the extreme heat and health odds ratios and county level socioeconomic/demographic variables with spatial error/lag models. The results suggest heat-related illness shows the highest odds ratio (ED: 1.15, hospitalization: 1.15) and followed by dehydration (1.03, 1.02); renal illness (1.03, 1.01); cardiovascular disease (1.01, 1.01); and respiratory disease (1.01, 1.01). In addition, some groups such as Hispanics and female face relatively greater heat risks. We also found significant relationship between socioeconomic/demographic factors and heat health odds ratios.