The Association between Compound Hot Extremes and Mortality Risk in Shandong Province, China: A Time-Series Analysis

Abstract

Background: The occurrence of compound hot extreme (CHE) events in China is increasingly frequent. This study aimed to investigate the association between CHEs and all-cause mortality in Shandong Province and to estimate the attributable excess deaths. Methods: We collected daily data on weather, air pollution, and all-cause mortality at the subdistrict level in Shandong Province from 2013 to 2018. A CHE was defined as both daily maximum and minimum temperatures being higher than their historical 90th percentiles during 2013–2018 hot seasons. A case time-series analysis with a distributed lagged non-linear model was applied to analyze the subdistrict-specific association between different hot extremes and mortality risk, which were then pooled at the province level using meta-analysis. Results: Hot nights (RR = 1.44, 95%CI: 1.35–1.53) and CHEs (RR = 1.77, 95%CI: 1.64–1.90) were significantly associated with an increased mortality risk. CHEs had a greater effect for females (RR = 1.99, 95%CI: 1.81–2.19) and the elderly (>74 years) (RR = 2.14, 95%CI: 1.93–2.38) than their counterparts, respectively. Cardiovascular and respiratory deaths were more susceptible to CHEs than other deaths. Each year, 4888 (95%CI: 4133–5811) excess deaths in Shandong Province were attributable to CHEs, accounting for 2.60% (95%CI: 2.20–3.10%) of all-cause deaths and equating to 50 (95%CI: 42–58) deaths per 1,000,000 residents. The CHE-related mortality burden varied across subdistricts, with the highest occurring in the southeastern area and the lowest occurring in the northeastern and southwestern regions. Conclusion: CHEs and hot nights were substantially associated with excess deaths in Shandong Province, especially for females, the elderly, and residents living in the southeastern area. Our findings may facilitate the development of a heat alert warning system and preventive measures for vulnerable populations.