Road Traffic Death Rate and Human Development Index in 2007-2016 at the Global Level: Trend Analysis

Background: Numerous studies working on the association between the human development index (HDI) and road traffic death rate (RTDR) , merely focused on developed countries, have not thus far reflected on the relationship between the HDI components and RTDR. Therefore, this study aimed to analyze the trends of RTDR and their association with the HDI and its components from 2007 to 2016. Methods: : The RTDR data for 131 countries were imported into the unconditional latent growth model (LGM) to assess the trends of RTDR between 2007 and 2016. The impact of the HDI and its components (viz. education, income and life expectancy [LE viz]) on the trajectory of RTDR was also evaluated using the conditional LGM. Classification and regression trees (CARTs) were then applied to classify the countries based on the HDI and its components into downward or upward trends. The importance of the HDI components in the CART models was further extracted through random forests (RFs). Results: : The results of the unconditional LGM indicated an overall decreasing trend in RTDR. A total number of 106 and 25 countries also had a downward and upward trend of RTDR, respectively. Based on the conditional LGM, the outcomes revealed the negative effect of the HDI and its components on the model parameters. The accuracy of the CARTs was at least by 85%, indicating its high classification performance. According to the findings of RFs, LE was the most crucial variable in the CART models. Conclusion: Overall, RTDR is concluded to be multifactorial. As this study showed, the HDI and its LE component are the main determinants of RTDR at the global level. In addition, legislative factors and sociocultural context of countries are assumed as important issues that should be considered by policy-makers to control RTD.