| [Objectives]The datas of road traffic injury in Nanning were collected by the records of Guangxi Public Security Bureau Traffic Police Bureau from 2000-2009. And the GIS software ArcGIS 10 was used to built GIS database of road traffic injury in Nanning. Then described and analysed the epidemiology trend, the causes and the spatial distribution of road traffic injury in Nanning, and the non-conditional Logistic regression was used to explore its influencing factors, and the GIS-based spatial regression was used to forecast the road traffic injury. So, they could be used to provide a scientific thereunder for preventing, controlling, monitoring, establishing intervention measures and decision-making.[Methods]The epidemiology trend and the causes of road traffic injury in Nanning were described and analysed by applying epidemiological methods, and the non-conditional Logistic regression was applied to explore its influencing factors, and the GIS-based spatial regression was used to forecast the road traffic injury, and the spatial autocorrelation analysis, the high/low clustering analysis and the hot sport analysis were used to explore the spatial distribution of traffic injury.[Results](1)The epidemiology trend of road traffic injury in Nanning①Time trend:From 2000 to 2009, the number of occurrence, deaths, wounds and the direct economic losses caused by road traffic accident in Nanning had an upward trend until 2005, and then declined after 2005. The accident rates, vehicle injury rates, vehicle mortality, population injury rates, and the comprehensive accident rates were steadily declined since 2005. The months of January, June, July and October had more traffic accidents to be occurred, while the fewer ones were the months of February, March and April. The most number of occurrence caused by traffic accidents was occurred at 22:00 to 23:00, while the least ones was occurred at 03:00 to 04:00; the most number of deaths caused by traffic accident was occurred at 19:00 to 20:00, while the least ones was occurred at 03:00 to 04:00; the most number of wounds caused by traffic accident was occurred at 20:00 to 21:00, while the least ones was occurred at 18:00 to 19:00; the most number of the direct economic losses caused by traffic accident was occurred at 20:00 to 21:00, while the least ones was occurred at 03:00 to 04:00.②The city zone distribution:The number of occurrence caused by traffic accident was mainly concentrated in the Qingxiu, Xingning, Jiangnan and the Xixiangtang district, which accounted for 91.9% of the total number of accidents. And the number of casualties in these four districts caused by traffic accident which accounted for 90.2% of the total number of casualties.③Population distribution:The number of casualties caused by traffic accident was mostly male, and the male and female ratio was 2.7:1. The largest number of casualties was the young adults aged 20 to 40, which accounted for 51.2% of the total number of casualties. And the number of casualties was mainly concentrated in three occupations, which included the personnel of production about farming, forestry, herd, fishery and the water conservancy, the personnel of production and related workers about the operators of transportational equipment, and the joblessness, the number of casualties about these three occupations groups accounted for 59.2% of the total number of casualties.④The disease burden of road traffic injury:The most serious losses of YPLL, WYPLL and VYPLL was the young adults aged 20 to 40, respectively, which accounted for 58.3%,62.3% and 90.6% of the total number of losses.⑤The type of road traffic accident:The general accident, mild accident and the serious accident were the main type of traffic accident. The most number of deaths was caused by serious accident, which accounted for 94.6% of the total number of deaths, while the most number of wounds was caused by general accident,which accounted for 58.2% of the total number of wounds.⑥The forms of road traffic accident:The main forms of traffic accident were the side collision and the frontal collision. Among which, the most serious casualties was caused by the frontal collision, and accounted for 39.8% of the total number of casualties.⑦The road traffic accident casualties'traffic modes:The traffic accident casualties'main traffic modes were driving motorcycle, walking and by car, and which accounted for 31.9%,20.7% and 15.5% of the total number of casualties. (2)The cause of formation caused by road traffic injury in Nanning①The causes of road traffic accident:The most traffic accidents was caused by motor vehicle drivers, and the injury of casualties were the most serious, and the number of occurrence and casualties caused by traffic accidents accounted for 79.4% and 80.7% of the total number of traffic accident and casualties, respectively.②The human factors:90.0% of the road traffic accidents were caused by male motor vehicle drivers. The young adults aged 20 to 40 and the motor vehicle drivers whose driving years less than 5 were most prone to causing road traffic accident, and which accounted for 67.1% and 44.0% of the total number of traffic accidents, respectively.③The vehicle factors:The number of motor vehicle increased year by year in Nanning from 2000 to 2009, and the number of motor vehicle increased from 193273 to 595677. However, the results from the partial correlation analysis showed that the number of casualties caused by traffic accident was not correlated with the number of motor vehicle(p= 0.071> 0.05).④The road factors:The traffic accidents were mainly occurred on the plain landform, dry road surface, concrete road surface, bitumen road surface, straight road and arterial road, which accounted for 73.2%,89.7%,52.5%,46.1%, 86.6% and 62.5% of the total number of traffic accidents, respectively.⑤The environmental factors:Traffic accident was most prone to occurring in sunny day, daytime or when traffic signal was sign-marking, and the injury of casualties was the most serious, which accounted for 75.4%,51.3% and 58.9% of the total number of traffic accidents, and which accounted for 73.9%,52.4% and 60.6% of the total number of casualties, respectively. (3)The influencing factors of road traffic injury in NanningThe single factor Logistic regression analysis showed that the possible influencing factors of traffic injury were as follows:illegal turn (B=-0.930, OR=0.395), illegal back a car (B=-1.358, OR=0.257), illegal U-turn (B=-0.797, OR=0.451), illegal changing lane (B=-0.891, OR=0.410), illegal accounting the lane for driving (B=0.861, OR=2.366), not enough lengthways space (B=-0.970, OR=0.379), driving without a license (B=3.340, OR=28.229); motor vehicle drivers'driving experience are less than 5 years (B=0.466, OR=1.593) and the driving experience are less than 10 years (B=0.538, OR=1.712); hilly landform (B=0.904, OR=2.470); the secondary road (B=0.319, OR=1.376), the third road (B=0.492, OR=1.635), the fourth road (B=1.154, OR=3.172); no traffic signal (B=2.244, OR=9.429), commanding by policeman (B=-0.931, OR=0.394); the daytime (B=-0.389, OR=0.678).The multiple factor Logistic regression analysis showed that the possible influencing factors of traffic injury were as follows:drunken driving (B=-0.611, OR=0.543), illegal turn (B=-0.913, OR=0.401), illegal back a car (B=-1.768, OR=0.171), illegal parking (B=-1.312, OR=0.269), illegal U-turn (B=-1.006, OR=0.366), illegal sliding (B=-0.800, OR=0.449), illegal changing lane (B=-1.128, OR=0.324), do not follow the provisions to give way (B=-0.498, OR=0.608), not enough lengthways space (B=-1.020, OR=0.360), illegal traffic signals (B=-0.514, OR=0.598), driving without a license (B=2.513, OR=12.336); hilly landform (B=0.710, OR=2.034); no traffic signal (B=2.083, OR=8.027); the daytime (B=-0.385, OR=0.680).(4)The prediction of road traffic injury in NanningThe multiple factor spatial regression model showed that the number of occurrence and casualties caused by road traffic injury in Nanning had a low cluster distribution trend, however, the model prediction was on the low side.(5)The spatial distribution of road traffic injuries in NanningThe spatial distribution of road traffic accident in Nanning showed that the road traffic accidents mainly occurred in the border region Civic Center. And the global spatial autocorrelation analysis showed that the number of casualties caused by traffic accident had a clustering distribution trend; and the high/low clustering analysis showed that the number of casualties had a low clustering distribution trend; and the local spatial autocorrelation analysis showed that the number of casualties had a high-low distribution trend in which the six city zones'common junction area, while the number of casualties had a high-high distribution trend in which away from the six city zones'common junction area; and the hot spot analysis showed that the number of casualties had a low clustering trend in which the six city zones'common junction area, while the number of casualties had a high clustering in which away from the six city zones'common junction area.[Conclusions]In recent years, there was a slowly downward trend in the road traffic accident and injury of Nanning. The time distribution, the population distribution, the city zone distribution and the spatial distribution there which had some obvious features; the male and the young adults aged 20 to 40 made up of the largest number of casualties caused by the traffic accident; the most serious losses of YPLL, WYPLL and VYPLL was the young adults aged 20 to 40; and the most traffic accidents were caused by motor vehicle drivers, and more male motor vehicle drivers than female, and the young adults aged 20 to 40 and the motor vehicle drivers whose driving years less than 5 were most prone to causing traffic accident; the good road conditions and traffic environment were more prone to causing traffic accident and injury; the main risk factors of traffic injury were the motor vehicle drivers driving without a license and no traffic signal, while the main protective factor was the traffic be commanded by policeman. |
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