Assessing the association between environmental impacts and health outcomes: a case study from Florida.
The Centers for Disease Control and Prevention (CDC) created the Environmental Public Health Tracking (EPHT) program to integrate hazard monitoring, exposure, and health effects surveillance into a cohesive tracking network. Part of Florida's effort to move toward implementation of EPHT is to develop models of the spatial and temporal association between myocardial infarctions (MIs) and ambient ozone levels in Florida. Existing data were obtained from Florida's Agency for Health Care Administration, Florida's Department of Environmental Protection, the U.S. Census Bureau, and CDC's Behavioral Risk Factor Surveillance System. These data were linked by both ignoring spatial support and using block kriging, a support-adjusted approach. The MI data were indirectly standardized by age, race/ethnicity, and sex. The state of Florida was used as the comparison standard to compute the MI standardized event ratio (SER) for each county and each month. After the data were linked, global models were used initially to relate MIs to ambient ozone levels, adjusting for covariates. The global models provide an estimated relative MI SER for the state. Realizing that the association in MIs and ozone might change across locations, local models were used to estimate the relative MI SER for each county, again adjusting for covariates. Results differed, depending on whether the spatial support was ignored or accounted for in the models. The opportunities and challenges associated with EPHT analyses are discussed and future directions highlighted.
Young
Linda J
LJ
Department of Statistics, University of Florida, Gainesville, FL 32611-0399, USA. LJYoung@ufl.edu
Gotway
Carol A
CA
Yang
Jie
J
Kearney
Greg
G
DuClos
Chris
C
D002487:Centers for Disease Control and Prevention, U.S.; D003625:Data Collection; D004781:Environmental Exposure / Q000009:adverse effects*; D005431:Florida / Q000453:epidemiology; D006801:Humans; D009203:Myocardial Infarction / Q000139:chemically induced / Q000453:epidemiology*; D010126:Ozone / Q000506:poisoning*; D052638:Particulate Matter / Q000506:poisoning*; D011159:Population Surveillance / Q000379:methods; D017751:Safety Management / Q000379:methods; D013029:Space-Time Clustering; D014481:United States
D052638:Particulate Matter; D010126:Ozone