Risk factors for extremely serious road accidents: Results from national Road Accident Statistical Annual Report of China

• Published in: PloS one Vol. 13; no. 8; p. e0201587
• Main Authors: Liu, Guodong, Chen, Siyu, Zeng, Ziqian, Cui, Huijie, Fang, Yanfei, Gu, Dongqing, Yin, Zhiyong, Wang, Zhengguo
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.08.2018; Public Library of Science (PLoS)
• Subjects: Accident Prevention; Accidents; Accidents - classification; Accidents - statistics & numerical data; Alcoholic beverages; Annual reports; China - epidemiology; Comparative analysis; Dependent variables; Driver fatigue; Driving; Driving ability; Drunkenness; Earth Sciences; Engineering and Technology; Epidemiology; Extreme values; Fatalities; Fatigue; Fatigue - epidemiology; Forensic engineering; Hospitals; Humans; Income distribution; Independent variables; Injuries; Laboratories; Medicine; Medicine and Health Sciences; Motor Vehicles - statistics & numerical data; Outdoor air quality; Patient outcomes; People and Places; Physical Sciences; Planning; Prevention; Public health; Regression Analysis; Retrospective Studies; Risk analysis; Risk Factors; Risk sharing; Roads; Roads & highways; Security; Social Sciences; Statistical analysis; Statistics; Surgery; Terrain; Toll roads; Traffic accidents; Traffic accidents & safety; Traffic management; Traffic police; Traffic safety; Transportation planning; Trauma; China; United Kingdom > UK; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0201587

In the past decades, extremely serious road accidents with a death toll over ten in each have become a severe public health problem in China. This study investigates risk factors contributing to extremely serious road accidents, which will be crucial for accident prevention. Collecting data from The Road Accident Statistical Annual Report openly issued by China's Traffic Management Bureau of the Public Security Ministry for the time period 2004-2015, we used the monthly case number of extreme serious road accidents as the dependent variable. We then selected ten risk factors as primary independent variables: professional driver, driving under influence (alcohol or drug), fatigue, vehicle type, overload, brake problem, weather, road classification, terrain, and region. The method of negative binominal regression was implemented to investigate the association between these risk factors and extremely serious road accidents. A total of 346 extremely serious road accidents were included in our analysis. On a national scale, we found that professional driver [incidence rate ratio (IRR): 1.10, 95% CI: 1.02-1.19], fatigue (IRR: 1.15, 95% CI: 1.03-1.29), large vehicle type (IRR: 1.11, 95% CI: 1.03-1.21), overload (IRR: 1.09, 95% CI: 1.03-1.16), and terrain (IRR: 1.09, 95% CI: 1.01-1.18) were significantly associated with extremely serious road accidents. Besides, separate analyses on western and non-western region indicated that both regions had shared risk factors as well as distinct factors. Our study identifies professional driver, fatigue, large vehicle type, overload, and terrain as significant risk factors of extremely serious road accidents in China, and targeted and preventative measures could be taken based on our findings.