Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada; Centre for Hip Health and Mobility, Vancouver, Canada.
School of Planning, Public Policy and Management, College of Design, University of Oregon, Eugene, USA.
Accid Anal Prev. 2020 Jun;141:105540. doi: 10.1016/j.aap.2020.105540. Epub 2020 Apr 15.
Increased cycling uptake can improve population health, but barriers include real and perceived risks. Crash risk factors are important to understand in order to improve safety and increase cycling uptake. Many studies of cycling crash risk are based on combining diverse sources of crash and exposure data, such as police databases (crashes) and travel surveys (exposure), based on shared geography and time. When conflating crash and exposure data from different sources, the risk factors that can be quantified are only those variables common to both datasets, which tend to be limited to geography (e.g. countries, provinces, municipalities) and a few general road user characteristics (e.g. gender and age strata). The Physical Activity through Sustainable Transport Approaches (PASTA) project was a prospective cohort study that collected both crash and exposure data from seven European cities (Antwerp, Barcelona, London, Örebro, Rome, Vienna and Zürich). The goal of this research was to use data from the PASTA project to quantify exposure-adjusted crash rates and model adjusted crash risk factors, including detailed sociodemographic characteristics, attitudes about transportation, neighbourhood built environment features and location by city. We used negative binomial regression to model the influence of risk factors independent of exposure. Of the 4,180 cyclists, 10.2 % reported 535 crashes. We found that overall crash rates were 6.7 times higher in London, the city with the highest crash rate, relative to Örebro, the city with the lowest rate. Differences in overall crash rates between cities are driven largely by crashes that did not require medical treatment and that involved motor-vehicles. In a parsimonious crash risk model, we found higher crash risks for less frequent cyclists, men, those who perceive cycling to not be well regarded in their neighbourhood, and those who live in areas of very high building density. Longitudinal collection of crash and exposure data can provide important insights into individual differences in crash risk. Substantial differences in crash risks between cities, neighbourhoods and population groups suggest there is great potential for improvement in cycling safety.
增加自行车出行量可以改善人口健康，但存在一些实际和感知到的风险障碍。为了提高安全性和增加自行车出行量，了解碰撞风险因素非常重要。许多自行车碰撞风险研究都是基于结合不同来源的碰撞和暴露数据，例如警察数据库（碰撞）和出行调查（暴露），这些数据基于共享的地理位置和时间。当合并来自不同来源的碰撞和暴露数据时，能够量化的风险因素仅限于两个数据集共有的变量，这些变量往往仅限于地理位置（例如国家、省份、直辖市）和一些一般的道路使用者特征（例如性别和年龄层次）。“通过可持续交通方式进行体育活动”（PASTA）项目是一项前瞻性队列研究，从七个欧洲城市（安特卫普、巴塞罗那、伦敦、厄勒布鲁、罗马、维也纳和苏黎世）收集了碰撞和暴露数据。该研究的目的是使用 PASTA 项目的数据来量化暴露调整后的碰撞率和模型调整后的碰撞风险因素，包括详细的社会人口特征、对交通的态度、社区建筑环境特征以及按城市划分的位置。我们使用负二项回归来独立于暴露因素来模拟风险因素的影响。在 4180 名自行车手，有 10.2%报告了 535 起事故。我们发现，相对于碰撞率最低的厄勒布鲁，伦敦的总体碰撞率高出 6.7 倍，伦敦是碰撞率最高的城市。城市之间整体碰撞率的差异主要是由无需医疗治疗且涉及机动车的碰撞造成的。在一个简约的碰撞风险模型中，我们发现自行车出行频率较低、男性、认为自己社区中自行车出行不受欢迎以及居住在建筑密度非常高的地区的人，发生碰撞的风险更高。连续收集碰撞和暴露数据可以为个体差异的碰撞风险提供重要的见解。城市、社区和人群之间的碰撞风险存在很大差异，这表明自行车安全有很大的改进空间。
