Abstract
(1) Background: To demonstrate the potential effects of missing exposure data and model choice on public health conclusions concerning the impact of heat waves on heat-related morbidity. (2) Methods: Using four different methods to impute missing exposure data, four statistical models (case-crossover, time-series, zero-inflated, and truncated models) are compared. The methods are used to relate heat waves, based on heat index, and heat-related morbidities for Florida from 2005–2012. (3) Results: Truncated models using maximum daily heat index, imputed using spatio-temporal methods, provided the best model fit of regional and statewide heat-related morbidity, outperforming the commonly used case-crossover and time-series analysis methods. (4) Conclusions: The extent of missing exposure data, the method used to impute missing exposure data and the statistical model chosen can influence statistical inference. Further, using a statewide truncated negative binomial model, statistically significant associations between heat-related morbidity and regional heat index effects were identified.
Highlights
Climate change, with respect to extreme heat, is a primary public health concern, especially in Florida
Public health researchers have either focused on times of known extreme heat events, eliminating the need for a data-driven extreme heat definition; studied one locale or city-specific heat waves, which typically results in exposure data having similar quality or patterns of missingness across heat waves; or have used only 10–20 years of weather data to define extreme heat, a shorter duration than that used in climate science [1,2,3,4,5,6]
Case-crossover, time-series, zero-inflated, and truncated models were built for each combination of region and missing data approach
Summary
With respect to extreme heat, is a primary public health concern, especially in Florida. Complications of studying extreme heat can compound when long-term exposure data are missing or incomplete. These missing data can change analytical and public health conclusions from these studies. Public health researchers have either focused on times of known extreme heat events, eliminating the need for a data-driven extreme heat definition; studied one locale or city-specific heat waves, which typically results in exposure data having similar quality or patterns of missingness across heat waves; or have used only 10–20 years of weather data to define extreme heat, a shorter duration than that used in climate science [1,2,3,4,5,6]. For Florida, 40 years of maximum daily heat index data from
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