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Abstract
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OBJECTIVE To analyze the epidemiological characteristics of electric bicycle road injuries based on the data of emergency cases in Shanghai hospitals, and provide evidence for road traffic injury prevention.
METHODS From March to July 2019, a questionnaire survey was conducted among 213 e-bike cyclists who had seen road traffic injuries in the emergency department of three general hospitals in Shanghai. A combination of quantitative and qualitative analysis is used to analyze the three distribution characteristics of accidents and the main causes of accidents.
RESULTS The accident occurred mainly from 07:00-09:00, accounting for 25.40%; the injured were mainly factory operators, office workers, and online delivery personnel, accounting for 29.58%, 15.02% and 11.27% respectively; 45.07 respectively % And 27.70% of accidents occurred on non-motorized vehicle lanes and intersections; narrow and crowded roads are the most common adverse road environment; not wearing a helmet and using mobile phones are common dangerous behaviors, accounting for 74.18% and 43.31% respectively; qualitative analysis results show "Using a mobile phone", "turning" and "suddenly changing driving mode" are the most frequently mentioned keywords.
CONCLUSION Electric bicycle-related road traffic injuries have their distinctive characteristics in terms of population distribution and accident causes. All departments and organizations should cooperate to improve the construction and maintenance of road environmental infrastructure, standardize the distribution industry standards; further improve and implement laws and regulations for electric bicycles , To reduce the occurrence of dangerous behaviors such as running red lights, drunk cycling or not wearing helmets; road traffic safety education for high-risk groups of injuries, cultivating good travel habits for road users, and promoting e-bike riders to standardize riding are all helpful Reduce the incidence of road traffic injuries.
Keywords : road traffic injuries , electric bicycles , epidemic characteristics , qualitative analysis , emergency data
Language: zh |