Abstract
PDS 66: Climate change, Exhibition Hall (PDS), Ground floor, August 28, 2019, 1:30 PM - 3:00 PM Background: Identifying characteristics of vulnerability to high temperatures will aid climate change adaptation efforts. Previous research is mixed on air conditioning (AC) effects on heat-associated health outcomes. Most prior studies lacked individual-level AC ownership and housing information. We assessed how housing types, central AC ownership, demographics, and comorbidities modify associations between extreme heat (EH, temperature > 99th percentile) and natural-cause mortality among individuals 65 and older in five Ohio counties. Methods: Ohio Department of Health mortality data were merged with housing data from Cuyahoga, Lucas, Franklin, Hamilton, and Summit County tax assessors by residential address. We defined four non-AC and one AC housing type. Lag day 0-1 average temperature was modeled from 1-km-resolution satellite-derived land surface temperature and airport air temperature. Quintiles of the modified Charleson Comorbidity Index were calculated from Centers for Medicare and Medicaid Services Chronic Conditions data on fee-for-service beneficiaries and merged with the mortality and weather data by birth and death dates and ZIP code. We used a case-crossover design, with controls within the same half-month as the case. We interacted EH with housing type (combinations of AC, basement, and stories) or central AC ownership, marital status, black race, and comorbidity index. Results: For EH vs. non-EH, mortality risk varied significantly between counties, and was increased 44% (95% CI: 17%, 77%) in Cuyahoga County among residents without AC only. Aside from AC status, associations did not vary significantly within housing types. In Cuyahoga County, in homes without AC, risks were strongest among non-married blacks with at least one comorbidity (97% increased risk, 95% CI: 91%, 200%), but risks did not increase monotonically with comorbidity number. Conclusions: Risk of heat-associated mortality was increased among certain individuals without central AC, depending on county and personal health and demographic characteristics. Interventions should focus on households with these characteristics.
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