The association between meteorological factors and road traffic injuries: a case analysis from Shantou city, China

被引:0
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作者
Jinghong Gao
Xiaojun Chen
Alistair Woodward
Xiaobo Liu
Haixia Wu
Yaogui Lu
Liping Li
Qiyong Liu
机构
[1] State Key Laboratory of Infectious Disease Prevention and Control,
[2] Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases,undefined
[3] National Institute for Communicable Disease Control and Prevention,undefined
[4] Chinese Center for Disease Control and Prevention,undefined
[5] Injury Prevention Research Center,undefined
[6] Shantou University Medical College,undefined
[7] First Affiliated Hospital of Shantou University Medical College,undefined
[8] School of Population Health,undefined
[9] University of Auckland,undefined
来源
Scientific Reports | / 6卷
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摘要
Few studies examined the associations of meteorological factors with road traffic injuries (RTIs). The purpose of the present study was to quantify the contributions of meteorological factors to RTI cases treated at a tertiary level hospital in Shantou city, China. A time-series diagram was employed to illustrate the time trends and seasonal variation of RTIs, and correlation analysis and multiple linear regression analysis were conducted to investigate the relationships between meteorological parameters and RTIs. RTIs followed a seasonal pattern as more cases occurred during summer and winter months. RTIs are positively correlated with temperature and sunshine duration, while negatively associated with wind speed. Temperature, sunshine hour and wind speed were included in the final linear model with regression coefficients of 0.65 (t = 2.36, P = 0.019), 2.23 (t = 2.72, P = 0.007) and −27.66 (t = −5.67, P < 0.001), respectively, accounting for 19.93% of the total variation of RTI cases. The findings can help us better understand the associations between meteorological factors and RTIs, and with potential contributions to the development and implementation of regional level evidence-based weather-responsive traffic management system in the future.
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