Shaohua Wang1, Yanyan Chen2, Jianling Huang3, Zhuo Liu4, Jia Li4, Jianming Ma5. 1. Beijing University of Technology, Beijing Key Laboratory of Traffic Engineering, Beijing 100124, China; Tianjin University of Technology and Education, Tianjin Collaborative Innovation Center of Traffic Safety and Control, Tianjin 300222, China. 2. Beijing University of Technology, Beijing Key Laboratory of Traffic Engineering, Beijing 100124, China. Electronic address: cdyan@bjut.edu.cn. 3. Beijing University of Technology, Beijing Key Laboratory of Traffic Engineering, Beijing 100124, China; Beijing Transportation Information Center, Beijing 100161, China. 4. Beijing University of Technology, Beijing Key Laboratory of Traffic Engineering, Beijing 100124, China. 5. Texas Department of Transportation. 9500 N. Lake Creek Pkwy, Austin, TX 78717, USA.
Abstract
INTRODUCTION: Numerous studies have demonstrated the close relationship between alcohol availability and alcohol-related crashes. However, there is still a lack of spatial empirical analysis regarding this relationship, particularly in large cities of developing countries. Differences in alcohol outlets and drinking patterns in these cities may lead to quite different patterns of crash outcomes. METHOD: 3356 alcohol-related crashes were collected from the blood-alcohol test report of a forensic institution in Tianjin, China. Density of alcohol outlets such as retail locations, entertainment venues, restaurants, hotels, and companies were extracted based on 2114 Traffic Analysis Zones (TAZ) together with the residential and demographic characteristics. After applying the exploratory spatial data analysis, this research developed and compared the traditional Ordinary Least Square model (OLS), Spatial Lag Model (SLM), Spatial Error Model (SEM) and Spatial Durbin Model (SDM) to explore spatial effects of all the variables. RESULTS: The results of incremental spatial autocorrelation show that the most significant distance threshold of alcohol-related roadway traffic crashes is 3 km. The SDM is found to be the optimal spatial model to characterize the relationship between alcohol outlets and crashes. The number of alcohol-involved traffic crashes is positively related to population density and retail density, but negatively related to the company density, hotel density, and residential density within the same TAZ. Meanwhile, dense population and hotels have reverse spillover effects in adjacent zones. CONCLUSIONS: The significant spatial direct effect and spillover effect of alcohol outlet densities on drunk driving crashes should not be neglected. These findings could help improve transportation planning, traffic law enforcement and traffic management for large cities in developing countries.
INTRODUCTION: Numerous studies have demonstrated the close relationship between alcohol availability and alcohol-related crashes. However, there is still a lack of spatial empirical analysis regarding this relationship, particularly in large cities of developing countries. Differences in alcohol outlets and drinking patterns in these cities may lead to quite different patterns of crash outcomes. METHOD: 3356 alcohol-related crashes were collected from the blood-alcohol test report of a forensic institution in Tianjin, China. Density of alcohol outlets such as retail locations, entertainment venues, restaurants, hotels, and companies were extracted based on 2114 Traffic Analysis Zones (TAZ) together with the residential and demographic characteristics. After applying the exploratory spatial data analysis, this research developed and compared the traditional Ordinary Least Square model (OLS), Spatial Lag Model (SLM), Spatial Error Model (SEM) and Spatial Durbin Model (SDM) to explore spatial effects of all the variables. RESULTS: The results of incremental spatial autocorrelation show that the most significant distance threshold of alcohol-related roadway traffic crashes is 3 km. The SDM is found to be the optimal spatial model to characterize the relationship between alcohol outlets and crashes. The number of alcohol-involved traffic crashes is positively related to population density and retail density, but negatively related to the company density, hotel density, and residential density within the same TAZ. Meanwhile, dense population and hotels have reverse spillover effects in adjacent zones. CONCLUSIONS: The significant spatial direct effect and spillover effect of alcohol outlet densities on drunk driving crashes should not be neglected. These findings could help improve transportation planning, traffic law enforcement and traffic management for large cities in developing countries.
Authors: Guofa Li; Yuan Liao; Qiangqiang Guo; Caixiong Shen; Weijian Lai Journal: Int J Environ Res Public Health Date: 2021-01-28 Impact factor: 3.390