基于固有匹配对数据的交通事故致亡风险因素分析

机动车乘员在道路交通事故中死亡风险的大小受到很多因素的影响.为分析交通事故中致亡因素的非线性效应,在美国交通事故死亡分析报告(FARS)的数据基础上,对机动车乘员的事故结果进行匹配筛选,得到了固有匹配对数据.进而以相对死亡风险为衡量指标,通过非参数logistic回归的方法揭露了性别、年龄、安全带的使用情况以及座椅位置4个因素对致亡伤害的深层次影响机理,有望为交通安全政策的制定和交通安全措施的实施提供重要依据.除此之外,非参数logistic模型能够揭露年龄作为连续变量的重要非线性影响.研究结果表明,固有匹配对的数据结构能够排除外界因素对模型的干扰,且性别、年龄、安全带的使用情况以及座椅位置4个因素会对交通事故中机动车乘员死亡风险的大小造成显著影响.女性的死亡风险相对男性高出15.9%(对数值);使用安全带可以降低74.8%的死亡风险(对数值);死亡风险随机动车乘员年龄增长呈上升趋势;小汽车的后座左侧和后座中间位置是最安全的位置.

A Risk Analysis of Fatal Factors in Traffic Accidents Based on Inherent Matching Pairs

The risk ratio of occupants′ death in traffic accidents is affected by many factors.In order to understand the nonlinear effects, the data of fatal crashes that obtained from the Fatality Analysis Reporting System (FARS) are adopted.After matching and filtering the data, according to death of occupants, a dataset of inherent matching pairs is obtained.The relative risk of death is set as an indicator in this paper.A model based on nonparametric logistic regression is developed to estimate the influential mechanisms of gender, age, belt usage, and seating position on fatalities.The results are expected to provide an important basis for the development of policy and the implementation of measures for traffic safety.Besides, the model is able to reveal significant influence of nonlinear effects when age is regarded as a continuous variable.The results show that the four factors of gender, age, belt usage, and seating position can significantly affect the risk of occupants′ death in traffic accidents, and the structures of inherently matched pairs are able to exclude the interference of external factors in this model.Compared with male occupants, the risk of death of female is 15.9% higher (the logarithmic value);the usage of seat belt can reduce the risk of death by 74.8% (the logarithmic value);the risk of death increases with age;and the middle and left of rear seats are the safest seating positions in a car.