title: Pattern of traffic injuries in Shanghai: implications for control.
abstract: In China, traffic-related injuries are often treated as transportation issues, called 'accidents'. The objectives of the research are to analyse traffic injury patterns, estimate costs of traffic injuries and provide evidence to develop effective prevention strategies. There were over 1 500 deaths due to traffic-related injuries annually in Shanghai from 1987 to 2003, and it is rising year by year with the rate of growth in motorization. The rates of annual increase are 3.59% in fatalities (from 7.78 to 14.18 per 100000 population) and 10.46% in non-fatalities (from 53.93 to 264.98 per 100000 population) respectively during the period. The analysis of the geographic information system showed that the geographic distribution of traffic injuries in the countryside regions of Shanghai had the highest rates. Labour force groups represented the majority of fatalities (70.97%) and serious traffic injuries (90.51%). The mortality rates were 18.40 per 100000 population and 10.02 per 100000 population in 45-65 year age group and 15-44 year age group respectively; the morbidity rates of serious traffic injuries were 121.60 per 100000 population and 70.46 per 100000 population in the same groups respectively. And females generally showed a lower incidence than males. In general, fatalities and injuries were higher for drivers, bicyclists and pedestrians. Among road traffic injury-related fatalities, 66.8% were attributed to head injuries. Of those with fatal head injuries, bicyclists accounted for 29.8% of the total; pedestrians accounted for 28.3%; motorcyclists accounted for 25.5%. Total traffic injury cost was estimated at least US $645989580 in Shanghai in 2003. Good injury intervention programmes need to be done as soon as possible to effectively reduce traffic injury burden in Shanghai, China.
authors.affiliation: Shanghai Municipal Center for Disease Control and Prevention, 1380 Zhong Shan West Road, Shanghai, China. huanyi@scdc.sh.cn
authors.forename: Li
authors.initials: L
authors.lastname: Yan-Hong
authors.forename: Yousif
authors.initials: Y
authors.lastname: Rahim
authors.forename: Lu
authors.initials: L
authors.lastname: Wei
authors.forename: Song
authors.initials: S
authors.lastname: Gui-Xiang
authors.forename: Yu
authors.initials: Y
authors.lastname: Yan
authors.forename: Zhou
authors.initials: Z
authors.lastname: De Ding
authors.forename: Zhang
authors.initials: Z
authors.lastname: Sheng-Nian
authors.forename: Zhou
authors.initials: Z
authors.lastname: Shun-Fu
authors.forename: Chen
authors.initials: C
authors.lastname: Shao-Ming
authors.forename: Yang
authors.initials: Y
authors.lastname: Bing-Jie
mesh_terms: D000063:Accidents, Traffic / Q000191:economics / Q000401:mortality / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D001642:Bicycling / Q000293:injuries*; D002648:Child; D002675:Child, Preschool; D002681:China / Q000453:epidemiology; D003365:Costs and Cost Analysis; D005260:Female; D040362:Geographic Information Systems; D006801:Humans; D007223:Infant; D008297:Male; D008875:Middle Aged; D009049:Motorcycles / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D017678:Sex Distribution