Title of article :
Factors with the Highest Impact on Road Traffic Deaths in Iran; an Ecological Study
Author/Authors :
Razzaghi, Alireza Safety Promotion and Injury Prevention Research Center - Shahid Beheshti University of Medical Sciences, Tehran , Soori, Hamid Safety Promotion and Injury Prevention Research Center - Shahid Beheshti University of Medical Sciences, Tehran , Kavousi, Amir Department of Epidemiology - School of Public Health and Safety - Safety Promotion and Injury Prevention Research Center - Shahid Beheshti University of Medical Sciences, Tehran , Abadi, Alireza Department of Community Medicine - Shahid Beheshti University of Medical Sciences, Tehran , Khosravi, Ardeshir Department of Statistics and Informatics, Tehran
Abstract :
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.
Keywords :
Death , accidents , traffic , mortality , multiple trauma
Journal title :
Archives of Academic Emergency Medicine (AAEM)