Drivers of associations between daytime-nighttime compound temperature extremes and mortality in China

白天 中国 环境科学 大气科学 气候学 人口学 气象学 地理 物理 地质学 社会学 考古
作者
Jun Yang,Maigeng Zhou,Cui Guo,Sui Zhu,Mohammad Javad Zare Sakhvidi,Weeberb J. Réquia,Qinghua Sun,Shilu Tong,Mengmeng Li,Qiyong Liu
出处
期刊:Communications medicine [Springer Nature]
卷期号:4 (1)
标识
DOI:10.1038/s43856-024-00557-0
摘要

Abstract Background Temperature extremes are anticipated to become more frequent and more intense under the context of climate change. While current evidence on health effects of compound extreme temperature event is scarce. Methods This nationwide cross-sectional study collected daily data on weather and mortality for 161 Chinese districts/counties during 2007-2013. A quasi-Poisson generalized linear model was first applied to assess effects of daytime-only, nighttime-only and compound daytime-nighttime heat wave (and cold spell) on cause-specific mortality. Then a random-effect meta-analysis was used to produce pooled estimates at national level. Stratification analyses were performed by relative humidity, individual and regional characteristics. Results Here we show that mortality risks of compound daytime-nighttime temperature extremes are much higher than those occurring only in the daytime or nighttime. Humid weather further exaggerates the mortality risk during heat waves, while dry air enhances the risk during cold weather. People who are elderly, illiterate, and those with ischemic heart disease and respiratory disease are particularly vulnerable to extreme temperature. At the community-level, population size, urbanization rate, proportion of elderly and PM2.5 are positively associated with increased risks associated with heat waves. Temperature, humidity and normalized difference vegetation index are positively associated with the effects of cold weather, with an opposite trend for latitude and diurnal temperature range. Conclusions This nationwide study highlights the importance of incorporating compound daytime-nighttime extreme temperature events and humid conditions into early warning systems and urban design/planning.
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