Comparison of Temperature-Mortality Associations Across the Middle East Using Different Exposure Estimation Approaches.

Abstract

Listen

Translate article

Traditional temperature-health studies have predominantly relied on temperature measurements from stations or modelled spatial averages from gridded temperature datasets. It has been suggested that population-weighted spatial averages would perform better in remote regions with large temperature and population variability. This would be particularly true in regions other than North America and Europe where outcome data is often only available on a crude spatial scale, but no studies have examined this in such regions, where temperatures can be particularly hot. Using the Middle East as a climate hotspot, our objective was to illustrate the utility of population weighting temperature exposures in understudied regions with large health data aggregation areas. We used a daily 1km × 1km temperature dataset for 152 administrative regions in 12 Middle Eastern countries. From 2003 to 2020, for each administrative region, we computed daily minimum and maximum population-weighted and unweighted spatial average temperatures. To illustrate, we examined temperature-mortality associations in two countries: Kuwait and Jordan. We used distributed lag non-linear models to estimate the daily timeseries temperature-mortality associations in using three temperature exposure measurement approaches: station temperatures, unweighted spatial averages, and population-weighted temperatures. For each scenario, we fitted country-specific optimized parameters and compared them using three metrics: 1) exposure-response relationships, 2) minimum mortality temperatures and 3) attributable mortality estimates. The study region had geographically sporadic yet densely populated areas within each country. In both Kuwait and Jordan, population-weighted and unweighted spatial average temperatures resulted in fairly similar exposure-response curves, whereas both were notably different from station temperatures. Minimum mortality temperatures were 30.2, 28.6, and 28.3°C in Kuwait for station, unweighted spatial average, and population-weighted temperatures, respectively. In Jordan, the corresponding temperatures were 20.6, 20.9, and 20°C. Heat attributable mortality calculated using population-weighted temperatures increased by 15% compared to the traditionally used station temperatures in Kuwait and Jordan, respectively, and -0.4% and 5% compared to unweighted spatial average temperatures. Spatial averaging, whether weighted or unweighted, is a valuable tool for estimating heat-attributable mortality. This is especially true in regions like the Middle East, where granular temperature data are often unavailable and health studies are urgently needed. Population-weighted temperatures may better capture localized exposures in areas with significant population clustering, though their exact added effect on top of unweighted spatial averages remains a tentative conclusion.. https://doi.org/10.1289/EHP16010.