School of Management, Chongqing University of Technology, Chongqing, 400054, China.
School of Management, Chongqing University of Technology, Chongqing, 400054, China.
Chin J Traumatol. 2024 Dec;27(6):380-388. doi: 10.1016/j.cjtee.2024.07.001. Epub 2024 Jul 3.
Road traffic injuries (RTIs) have been one of the most serious public health problems in China. The purpose of this study was to investigate the extent to which traffic investment affects traffic fatalities in China as well as regional differences.
The cohort study analyzed the correlation between traffic investment and traffic fatalities, incorporating additional factors such as economic conditions, road infrastructure, population density, and lighting. The selected variables included the number of traffic fatalities, traffic investment, urban per capita road area, urban road length, road mileage, urban road lighting, population size, and per capita gross domestic product. Relevant data between 2004 and 2020 were collected for an analysis using a fixed effect regression model. A p < 0.05 is considered statistically significant. To reduce the heterogeneity caused by regional differences, the provinces were divided into 6 groups according to administrative districts, and the clustering standard error analysis was carried out.
Overall, there has been a significant improvement in road safety in China from 2004 to 2020, but some regions show an increase in traffic fatalities. The model reveals that traffic investment is significantly and positively correlated with the number of traffic fatalities. Holding all other factors constant, each 10,000 yuan increase in transport investment was associated with an average increase of 0.22 road traffic fatalities. In the analysis of regional differences, there was a significant positive correlation between traffic investment and traffic fatalities in the Northwest region and an increase of 10,000 yuan leads to an increase of 0.47. There was a significant negative correlation between road mileage, urban road lighting system, and population and traffic fatalities. For example, holding other factors constant, a 10,000 km reduction in road length would increase the number of traffic deaths by 45.56. The model results of urban per capita road area, urban road length, per capita gross domestic product, and the explained variables showed that p > 0.100, which was not statistically significant.
Therefore, traffic investments are essential for governments to develop measures to enhance road safety and reduce the risk of road fatalities. Adjusting traffic road investment and other covariates is conducive to improving traffic safety and reducing the risk of road fatalities. The road safety situation in different regions of China varies greatly. Local governments should consider the actual conditions to provide better road safety configuration policies.
道路交通伤害（RTIs）一直是中国最严重的公共卫生问题之一。本研究旨在探讨交通投资对中国交通死亡人数的影响程度以及地区差异。
本队列研究分析了交通投资与交通死亡人数之间的相关性，纳入了经济条件、道路基础设施、人口密度和照明等额外因素。所选变量包括交通死亡人数、交通投资、城市人均道路面积、城市道路长度、道路里程、城市道路照明、人口规模和人均国内生产总值。使用固定效应回归模型对 2004 年至 2020 年之间的相关数据进行分析。p<0.05 被认为具有统计学意义。为了减少因地区差异造成的异质性，根据行政区域将各省分为 6 组，并进行聚类标准误分析。
总体而言，中国的道路安全状况从 2004 年至 2020 年有了显著改善，但一些地区的交通死亡人数有所增加。模型显示，交通投资与交通死亡人数呈显著正相关。在其他所有因素保持不变的情况下，交通投资每增加 10000 元，交通死亡人数平均增加 0.22 人。在地区差异分析中，西北地区交通投资与交通死亡人数呈显著正相关，增加 10000 元会导致交通死亡人数增加 0.47 人。道路里程、城市道路照明系统和人口与交通死亡人数呈显著负相关。例如，在其他因素保持不变的情况下，道路长度减少 10000 公里会使交通死亡人数增加 45.56 人。城市人均道路面积、城市道路长度、人均国内生产总值和解释变量的模型结果表明，p>0.100，无统计学意义。
因此，交通投资对于政府制定提高道路安全和降低道路死亡风险的措施至关重要。调整交通道路投资和其他协变量有利于提高交通安全，降低道路死亡风险。中国不同地区的道路安全状况差异很大。地方政府应考虑实际情况，提供更好的道路安全配置政策。
