| [Objectives]To analyze epidemiological characteristics of Road Traffic Injuries (RTI) in Guilin city from2000to2009, establish a geographic information database of RTI in Guilin, and explore the application value and signification of geographic information system (GIS) spatial analysis technology in the study of RTI, so as to provide a scientific basis for making policies of preventing and controlling RTI.[Methods]We collected RTI data of Guilin city from2000to2009through Guangxi Zhuang Autonomous Region Public Security Department Traffic Administrative Bureau, compared the RTI lethality rates with a x2test using SPSS13.0, analysed the distribution of RTI and casualties in month and24hours with circular distribution analysis, and selected the influencing factors of RTI with non-conditional Logistic regression analysis using SPSS13.0, wherein, all significant levels were0.05. And then, we extracted the longitude and latitudeof of occurrence points of RTI in Guilin city using MapInfo8.5, and established a geographic information database of RTI in Guilin using GIS. At the same time, we performed point density analysis, spatial regression analysis, spatial autocorrelation analysis and inverse distance weighted interpolation analysis for spatial distribution characteristics of RTI, and then drew thematic maps of RTI in Guilin city.[Results](1) The traffic safety level of Guilin city:The number of occurrences of RIT in Guinlin city was3603in total from2000to2009, which caused506people died and2911people injured, and led to a direct ecomomic loss of10.11million yuan. The incidence and million car mortality of RTI in Guilin city declined in general from2000to2009. However, population injury rate and mortality rate per100000persons of RTI fluctuated irregularly.(2) The regional distribution of RTI in Guilin city:The number of occurrences of RIT in Xiangshan district was the highest, but the number of deaths and fatality rate of RTI in Yanshan district were the highest. Differences of RTI fatality rate among each urban district were significant (P=0.000).(3) The time distribution of RTI in Guilin city:①The top three in the number of occurrences of RIT were2001,2003and2006respectively; the number of deaths was the highest in2006, followed by2001and2004; the number of injuries was the highest in2006,2005and2007; and the economic loss was the maximum in2003, which accounted for18.60%of the total. Differences of RTI fatality rate among each year were statistical significance (P=0.000), and the RTI fatality rate in2008was the highest.②RTI mainly concentrated from July to September and December to January of the next year, but casualties mainly concentrated from August to October.③The peak period of occurrence of RTI was from20:00to24:00and14:00to16:00each day; the number of deaths of RTI suddenly rose from18:00, and reached the peak from20:00to22:00; and the injuries also mainly concentrated in the period from20:00to24:00, and reached the peak from20:00to22:00.(4) The population distribution of RTI in Guilin city:①The population distribution of RTI in Guilin city:①The male-female ratios of the deaths and injuries of RTI were2.54:1and2.34:1respectively; the number of deaths of RTI was the highest among old people at age greater than or equal to65years, followed by young people at age from31to35years; the injuries mainly concentrated in young people at age from21to45years; and old people at age greater than or equal to56years and children at age less than or equal to10years had the highest RTI fatality rate.②The injury proportion of passengers was the highest, followed by motorcycle drivers and pedestrians; however, the death proportion of pedestrians was highest, followed by motorcycle drivers, non-motor vehicle drivers and passengers; and the RTI fatality rate of pedestrians was highest, followed by non-motor vehicle drivers.(5) The main reasons of RTI:Among the main reasons of RTI in Guilin city, human factor accounted for97.06%, wherein the reasons of motor vehicle drivers accounted for more than80%. The main reasons of RTI were giving way against the regulations, violating the traffic signals, insufficient longitudinal spacing and driving on the wrong lanes against the rules. (6) The epidemic of RTI under different conditions:①The number of occurances and deaths of RTI caused by the drivers with driving ages more than1year and less than or equal to5years was the highest.②the number of occurances of RTI was the highest and the injury proportion and death proportion were the largest in a traffic control mode only with signs and markings, followed by a no control mode.③RTI mainly occurred on ordinary city roads, followed by secondary roads, but the RTI fatality rate on secondary and first-class roads was the highest (P=0.000). The number of occurances and casualties of RTI on flat and straight roads are the highest, but the RTI fatality rate on curved steep slopes are generally the highest (P=0.000).④The number of occurances and casualties of RTI on ordinary roads was the highest, but the RTI fatality rate in tunnels was the most serious and was significantly higher than other crossroad section types (P=0.000). The number of occurances and casualties of RTI in hilly topographies was the highest.⑤RTI occurred mostly on dry pavements, and the caused number of casualties stood first on the list. The number of occurances and casualties of RTI on cement pavements was also the highest, but the RTI fatality rate on sand and depeter roads was obviously higher than other pavement structures.⑥RTI occurred mostly on sunny days, and the caused injury proportion and death proportion were also the largest. RTI mainly occurred during the day and the caused number of casualties was also the highest, which was followed by a condition of no street lamp lighting at night, but the RTI fatality rate was highest in a condition of street lamp lighting at night (P=0.001).(7) Influencing factors of RTI:The non-conditional multiple factors Logistic regression analysis of the factors showed the following main influencing factors of RTI:driving age more than1year but less than or equal to5years, fatigue driving, speeding, insufficient longitudinal spacing, violating the traffic signals, first-class road, secondary road, general curved steep slope and four-branch crossroad.(8) The results of GIS spatial analysis for RTI in Guilin city as follow:①The occurance of RTI mainly concentrated in city centers. However, RTI showed a sporadic state far away from the city centers. The injuries caused by RTI also concentrated in the city centers. The farther distance was from the city centers, the less people got injured. The deaths caused by RTI concentrated in suburbs.②The results of whole domain spatial autocorrelation analysis showed that Moran’s I score was0.067401, Z score was1.992636, and P score was0.046301and less than0.05, which demonstrated that the casualties of RTI in Guilin city had spatial aggregation.③Local area spatial autocorrelation analysis found that the number of casualties of RTI in the city centers showed high-value clusters and with low-value elements (HL) around. However, the number of casualties of RTI showed high-value clusters (HH) in districts far away from the city centers. [Conclusion](1) RTI and casualties caused by RTI had population aggregation, time aggregation and space aggregation.(2) RTI in Guilin city was mainly caused by human factors, especially the factors of motor vehicle drivers.(3) Since the RTI was preventable, targeted intervening measures were taken on the selected various risk factors, which would decrease the incidence and casualty rate of RTI effectively.(4) The results of GIS spatial analysis were consistent with the results of general epidemiological research. However, the former could demonstrate the roads and areas in which RTI had the spatial aggregation intuitively and accurately in the form of maps, which can provide more scientific basis for making polocies of preventing and controlling RTI, and has an extremely important use value. |
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