Nguyen Quynh C, Alirezaei Mitra, Yue Xiaohe, Mane Heran, Li Dapeng, Zhao Lingjun, Nguyen Thu T, Patel Rithik, Yu Weijun, Hu Ming, Quistberg D Alex, Tasdizen Tolga
Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, Maryland, USA
Department of Electrical and Computer Engineering, Scientific Computing and Imaging Institute, The University of Utah, Salt Lake City, Utah, USA.
Inj Prev. 2024 Jun 6. doi: 10.1136/ip-2023-045153.
The USA has higher rates of fatal motor vehicle collisions than most high-income countries. Previous studies examining the role of the built environment were generally limited to small geographic areas or single cities. This study aims to quantify associations between built environment characteristics and traffic collisions in the USA.
Built environment characteristics were derived from Google Street View images and summarised at the census tract level. Fatal traffic collisions were obtained from the 2019-2021 Fatality Analysis Reporting System. Fatal and non-fatal traffic collisions in Washington DC were obtained from the District Department of Transportation. Adjusted Poisson regression models examined whether built environment characteristics are related to motor vehicle collisions in the USA, controlling for census tract sociodemographic characteristics.
Census tracts in the highest tertile of sidewalks, single-lane roads, streetlights and street greenness had 70%, 50%, 30% and 26% fewer fatal vehicle collisions compared with those in the lowest tertile. Street greenness and single-lane roads were associated with 37% and 38% fewer pedestrian-involved and cyclist-involved fatal collisions. Analyses with fatal and non-fatal collisions in Washington DC found streetlights and stop signs were associated with fewer pedestrians and cyclists-involved vehicle collisions while road construction had an adverse association.
This study demonstrates the utility of using data algorithms that can automatically analyse street segments to create indicators of the built environment to enhance understanding of large-scale patterns and inform interventions to decrease road traffic injuries and fatalities.
美国致命机动车碰撞事故发生率高于大多数高收入国家。以往研究考察建成环境的作用时，通常局限于小地理区域或单个城市。本研究旨在量化美国建成环境特征与交通碰撞事故之间的关联。
建成环境特征源自谷歌街景图像，并在普查区层面进行汇总。致命交通碰撞事故数据来自2019 - 2021年死亡分析报告系统。华盛顿特区的致命和非致命交通碰撞事故数据来自特区交通运输部。调整后的泊松回归模型检验建成环境特征是否与美国机动车碰撞事故相关，并对普查区社会人口统计学特征进行控制。
人行道、单车道道路、路灯和街道绿化程度处于最高三分位数的普查区，与处于最低三分位数的普查区相比，致命车辆碰撞事故分别减少70%、50%、30%和26%。街道绿化和单车道道路与涉及行人及骑车人的致命碰撞事故分别减少37%和38%相关。对华盛顿特区致命和非致命碰撞事故的分析发现，路灯和停车标志与涉及行人和骑车人的车辆碰撞事故减少相关，而道路建设则有不利关联。
本研究证明了使用数据算法自动分析街道路段以创建建成环境指标的效用，有助于增强对大规模模式的理解，并为减少道路交通伤害和死亡的干预措施提供依据。
