Introduction: The largest proportion of road traffic deaths (RTDs) happen in Low and Middle Income Countries (LMICs). The efforts for decreasing RTDs can be successful if there is precise information about its related risk factors. This study aimed to determine economic, population, road, and vehicle factors with the highest impacts on RTDs in Iran.
Methods: This is an ecological study, which has been done using covariates including: the population density, economic growth, urbanization, distance traveled (km) in 100 thousand people, the length of urban roads, the length of rural roads and the Vehicle per 1000 population for each province of Iran in 2015. The covariates considered had been gathered from different sources and to determine which one of the covariates has an effect on RTDs, the Negative Binomial (NB) regression model was used.
Results: The mean number of RTDs per 100000 population was 474 ± 70.59 in 2015. The highest and lowest rates of death belonged to Fars and Qom provinces, respectively. The results of the univariate model showed the population density as the only covariate of RTDs (p=0.001). Also, among other covariates, GDP was the only variable with a p-value equal to 0.2. In the multivariate NB model, it was seen that the population density (p=0.001), and GDP (p=0.02) significantly correlated with RTDs. For a unit (Million Rial) increase in the GDP of the province, the number of deaths decreased by as much as 0.0014. In addition, for a unit increase in population density, the number of deaths went up by as much as 30.
Conclusion: Population density and GDP had positive and negative effects on the number of fatal road traffic injuries, respectively. By considering these factors in presentational and controlling programs on road traffic injuries, it is possible to decrease the RTDs.
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