Mingming Liang1, Dongdong Zhao2, Yile Wu1, Pengpeng Ye3, Yuan Wang3, Zhenhai Yao4, Peng Bi5, Leilei Duan6, Yehuan Sun7. 1. Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China. 2. The First Affiliated Hospital of Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China. 3. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China. 4. Anhui Meteorological Service Center, Anhui Meteorological Bureau, No. 16 Shihe Road, Hefei, 230000, Anhui, China. 5. School of Public Health, University of Adelaide, Adelaide, SA, 5005, Australia. 6. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China. Electronic address: duanleilei@ncncd.chinacdc.cn. 7. Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China; Center for Injury Control and Prevention, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China. Electronic address: yhsun_ahmu_edu@yeah.net.
Abstract
BACKGROUND: Although traffic accidents cause considerable economic losses and injuries to individuals, families, and communities, little is known about the impact of meteorological factors on the incidence of traffic accident injuries (TAIs). Therefore, a time-series study was conducted to explore the effect of meteorological variables on TAIs in Dalian, Northern China. METHODS: Poisson generalized linear models (PGLM) combined with distributed lag nonlinear models (DLNM) were used to estimate the association between daily TAIs and ambient temperature in Dalian, China, 2015-2017. The injury data collected by Dalian national injury surveillance hospitals, and meteorological data were extracted and accumulated from the National Meteorological Information Center. Modified the model with variables such as pressure, humidity, precipitation, PM2.5, SO2, O3, day of the week, seasonality, and time trend. In the subgroup analysis, the modification effects of gender and age were also examined. RESULTS: Both high temperatures (RR = 1.198, 95％CI：1.017-1.411) and low temperatures (RR = 1.017, 95％CI：1.001-1.035) increased the risk of TAIs. The cumulative lag effect would last until after the 7th day. While the 40-59 years subgroup seemed to be more vulnerable in high temperature environments, those who are more than 60 years showed higher TAIs in low temperatures for both single-day and cumulative TAI risks. CONCLUSIONS: Identifying the association between ambient temperature and traffic injuries could provide needed scientific evidence for relevant public health actions.
BACKGROUND: Although traffic accidents cause considerable economic losses and injuries to individuals, families, and communities, little is known about the impact of meteorological factors on the incidence of traffic accident injuries (TAIs). Therefore, a time-series study was conducted to explore the effect of meteorological variables on TAIs in Dalian, Northern China. METHODS: Poisson generalized linear models (PGLM) combined with distributed lag nonlinear models (DLNM) were used to estimate the association between daily TAIs and ambient temperature in Dalian, China, 2015-2017. The injury data collected by Dalian national injury surveillance hospitals, and meteorological data were extracted and accumulated from the National Meteorological Information Center. Modified the model with variables such as pressure, humidity, precipitation, PM2.5, SO2, O3, day of the week, seasonality, and time trend. In the subgroup analysis, the modification effects of gender and age were also examined. RESULTS: Both high temperatures (RR = 1.198, 95％CI：1.017-1.411) and low temperatures (RR = 1.017, 95％CI：1.001-1.035) increased the risk of TAIs. The cumulative lag effect would last until after the 7th day. While the 40-59 years subgroup seemed to be more vulnerable in high temperature environments, those who are more than 60 years showed higher TAIs in low temperatures for both single-day and cumulative TAI risks. CONCLUSIONS: Identifying the association between ambient temperature and traffic injuries could provide needed scientific evidence for relevant public health actions.
Authors: Ta-Chien Chan; Chih-Wei Pai; Chia-Chieh Wu; Jason C Hsu; Ray-Jade Chen; Wen-Ta Chiu; Carlos Lam Journal: Int J Environ Res Public Health Date: 2022-06-17 Impact factor: 4.614