Time Series Analysis of Association between Extreme Temperatures and Mortality of Injury in 11 Cities of China

Objectives To explore the association between extreme temperatures and mortality of injury in China.

Methods Injury mortality, meteorological and air pollutant data during 2014-2017 were collected in 11 cities/counties of the country. A quasi-Poisson regression with distributed lag non-linear model (DLNM) was performed to quantify the associations between extreme temperatures and mortality of injury, including the lag effects and cumulative relative risk (CRR), after considering the influences of air pollutants, relative humidity, long-term trends, and days of week. Meta-analysis was applied to further explore the pooled associations between extremely hot and cold temperatures and the mortality of injury, respectively.

Results This study explored the effects of extreme temperatures on mortality of injury in 11 cities in China. The impact of extreme high temperature on injury was greatest on the current day, and the lag effect was different varied by cities, ranging from (0~3) days in Wuxi, Feixi and Mengzi to (0~7) days in Harbin, Hailar and Yancheng. The lag effect of extreme low temperature on injury could last longer, up to two weeks, and the lag effect was different varied by cities, from (2~8) days in Mengzi to (21~30) days in Ningbo. Meta-analysis results showed that the CRR and 95% CI of the effects of extreme high temperature and extreme low temperature on injury were 1.42 (1.28, 1.58) and 1.12 (1.00, 1.25).

Conclusions Both extremely high and low temperatures could increase the mortality of injury, and the effects of extreme hot are higher than that of extreme cold.