Evaluating Extreme Heat Event Definitions: Region-specific Investigation of Extreme Heat and Heat-related Mortality

Background: Extreme heat events (EHEs) are defined as sustained periods of abnormally and uncomfortably hot, and often humid, weather. EHE health effects include heat cramps, heat exhaustion, heat syncope, and heat stroke. According to Centers for Disease Control and Prevention, a total of 3,442 heat-related deaths were reported between 1999 and 2003. Several studies suggest that there is an added “heat wave” effect on mortality owing to sustained periods of extreme heat. Numerous EHE definitions are available from the public health and meteorology literature. EHE definitions can be classified into the following core criteria: 1. Daily heat metric: Daily maximum temperature, daily apparent temperature (heat index) , and diurnal temperature difference are used as metrics in studies exploring EHE definitions. 2. Duration: Number of consecutive days of extreme heat needed to constitute an EHE. The minimum duration in existing definitions varies from two to four days. 3. Threshold Type: Absolute—based on an observed absolute daily heat metric that does not change, or relative—based on an exceedance above a set percentile, which varies depending on the underlying daily heat metric distribution for a given location. 4. Intensity: Indicates the extremity of deviation that is required to constitute an EHE. Most definitions refer to the 95th, 97th, 98th, or 99th percentiles, or deviations above absolute thresholds, such as, 90 0F, 95 0F, 100 0F or 105 0F. A majority of studies apply a single EHE definition (based on one or more meteorological variables) to all climate regions, neglecting the potential influence of climate adaptation by resident populations. Studies that have extensively evaluated EHEs are limited to few geographic areas. Extending definitions from such studies to areas not previously studied may result in misidentification of EHEs. No national study conducted in the United States (U.S.) to date has accounted for daily heat-related mortality in defining EHEs. On the whole, there is lack of consensus in the environmental health literature on definitions and procedures to accurately identify periods of extreme heat associated with adverse health impacts. Methods and Objectives: For this analysis, several EHE definitions that have been used in the literature will be evaluated for their sensitivity and specificity in the context of daily heat-related mortality. The sensitivity statistic will help compare definitions of EHE that identify days that are part of an EHE resulting in excess mortality, and those identified days have at least one heat-related death; the specificity statistic will help compare definitions of EHE that identify days that are not part of an EHE resulting in excess mortality, and those identified days have no heat-related deaths. Station-based meteorology data from National Climatic Data Center for years 1999-2009 will be used and any county in the conterminous U.S. (lower 48 states) with an automated surface observing system unit will be included in this evaluation. For each heat event definition, a separate logistic regression (LR) model and Poisson rate regression (PRR) model will be estimated, keeping all daily-level meteorological variables the same across models. While the outcome in the LR model is a binary indicator of any reported heat-related death, the outcome in the PRR model is the count of heat-related deaths. The LR approach yields results that are easy to interpret; however, PRR can account not only for multiple daily deaths but also for population size (as opposed to assigning each spatial unit the same weight). The results of the modeling process will be used to assess the consistency of the relation between EHEs identified using each candidate definition and the occurrence of heat-related deaths. Expected Results: We hypothesize that people in different climatic regions have varying susceptibility to extreme heat, necessitating a region-specific investigation of extreme heat and associated heat-related mortality. Additionally, we anticipate that the most appropriate definition of EHEs may vary with climate region. Conclusions: We expect that this analysis will provide insights into the spatial and temporal distribution of EHEs nationally, and will improve understanding of the regional variation in frequency, intensity and duration of heat episodes. The results may be useful in tailoring heat alerts in different locations to reduce the potential adverse health impacts from extreme heat.