Abstract
BACKGROUND: Road traffic accidents are still serious, especially in developing countries. This paper takes China as a typical example of a developing country with rich characteristics related to road traffic safety for analysis. METHODS: Temporal, spatial, road traffic accidents and economic information were gathered from the China Statistical Yearbook. Principal components analysis (PCA) was employed to establish a comprehensive indicator to represent road traffic safety based on different types of road traffic accidents information. Pearson correlation analysis and Eta coefficient test were performed to analyze whether time and space characteristics would affect the established indicator. Then the established indicator was introduced as dependent variable while year and regions as independent variables in the mixed linear model (MLM). At last, single-element regression model was built to study the impact of GDP per capita on road traffic safety. RESULTS: In PCA, the variance explained by the established indicator was 93.993%. The results of Pearson correlation analysis and Eta coefficient test suggested that time and region were both related to the established indicator. MLM showed that the year, the regions and the interaction between them influenced road traffic safety in China significantly. The single-variable regression analysis indicated that, with the increase in GDP per capita, road traffic safety initially decreased and then increased. CONCLUSION: Road traffic safety in China was grim and changed greatly between different regions and years. This might be attributed to the yearly economic development and disparities among regions. .