Environmental Factors Influencing the Distribution of Pedestrian Traffic Accidents in Iran


1 Safety Promotion and Injury Prevention Research Center, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

2 Occupational Health and Safety Research Center, Hamadan University of Medical Sciences, Hamadan, Iran

3 Safety Promotion and Injury Prevention Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

4 Social Determinants of Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran


Background: This study aimed to determine the environmental factors affecting the frequency of accidents leading to injury and death related to pedestrians in 31 provinces of Iran. Methods: Data necessary for the study were extracted from databases of traffic police, statistics center, ministry of roads and urban development, and Iran meteorological organization. Hot spots analysis was used based on Getis‑Ord G statistics in geographically weighted regression models. Goodness of fit of models was evaluated using the Bayesian information criterion, Akaike’s information criterion and Deviance statistics. Results: In this study, 49,409 incidents were investigated. Of these, 48,382 (98%) cases were injuries and 1027 (2%) cases were fatal accidents. The incidence of fatal accidents does not follow a specific pattern; however, the incidence of accidents leading to injuries is higher in the central and the northeastern provinces of the country and lower in the southern and southeast provinces of the country. The final models showed that the relationship between different variables, including demographic characteristics, road network, and distance from the capital, traffic volume, and rainfall with dependent variables (number of accidents in geographic units), was statistically significant. Conclusion: In order to better design preventive plans for traffic accidents and promote the safety of passageways for pedestrians inside and outside the cities, these factors need to be considered more carefully, and practical solutions should be developed and implemented for their correction.


1. European Commission. Road Safety in the European Union, Trends, Statistics and Main Challenges. Luxembourg: Publications Office of the European Union; 2018.
2. Chong SL, Chiang LW, Allen JC Jr., Fleegler EW, Lee LK. Epidemiology of pedestrian‑motor vehicle fatalities and injuries, 2006‑2015. Am J Prev Med 2018;55:98‑105.
3. Martin JL, Wu D. Pedestrian fatality and impact speed squared: Cloglog modeling from French national data. Traffic Inj Prev 2018;19:94‑101.
4. Mohan D, Tsimhoni O, Sivak M, Flannagan MJ. Road Safety in India: Challenges and Opportunities. The University of Michigan, Transportation Research Institute; 2009. 
5. Accident Bureau. Bulletin of Statistics and Analysis of Accidents. Tehran: Traffic Police of Rahvar; 2015.
6. Richmond SA, Rothman L, Buliung R, Schwartz N, Larsen K, Howard A. Exploring the impact of a dedicated streetcar right‑of‑way on pedestrian motor vehicle collisions: A quasi experimental design. Accid Anal Prev 2014;71:222‑7.
7. Blazquez CA,Celis MS. A spatial and temporal analysis of child pedestrian crashes in Santiago,Chile. Accident Analysis &Prevention. 2013;50:304-11. 
8. Statter M, Schuble T, Harris‑Rosado M, Liu D, Quinlan K. Targeting pediatric pedestrian injury prevention efforts: Teasing the information through spatial analysis. J Trauma 2011;71:S511‑6.
9. Ukkusuri S, Miranda‑Moreno LF, Ramadurai G, Isa‑Tavarez J. The role of built environment on pedestrian crash frequency. Saf Sci 2012;50:1141‑51. 
10. Siddiqui C, Abdel‑Aty M, Choi K. Macroscopic spatial analysis of pedestrian and bicycle crashes. Accid Anal Prev 2012;45:382‑91. 
11. Wang C, Quddus MA, Ison SG. Predicting accident frequency at their severity levels and its application in site ranking using a two‑stage mixed multivariate model. Accid Anal Prev 2011;43:1979‑90.
12. CottrillCD, ThakuriahPV. Evaluating pedestrian crashes in areas with high low‑income or minority populations. Accid Anal Prev 2010;42:1718‑28. 
13. Lee C, Abdel‑Aty M. Comprehensive analysis of vehicle‑pedestrian crashes at intersections in Florida. Accid Anal Prev 2005;37:775‑86. 
14. Abdel‑Aty M, Keller J. Exploring the overall and specific crash severity levels at signalized intersections. Accid Anal Prev 2005;37:417‑25. 
15. Cloutier MS, Apparicio P, Thouez JP. GIS‑based spatial analysis of child pedestrian accidents near primary schools in Montréal, Canada. Appl GIS 2007;3:1‑18.
16. Fotheringham AS, Brunsdon C, Charlton M. Geographically weighted regression: The analysis of spatially varying relationships. Chichester, England; John Wiley and Sons; 2003. 
17. Ouni F, Belloumi M. Spatio‑temporal pattern of vulnerable road user’s collisions hot spots and related risk factors for injury severity in Tunisia. Transp Res Part F Traffic Psychol Behav 2018;56:477‑95. 
18. Sebert Kuhlmann AK, Brett J, Thomas D, Sain SR. Environmental characteristics associated with pedestrian‑motor vehicle collisions in Denver, Colorado. Am J Public Health 2009;99:1632‑7.
19. McArthur A, Savolainen PT, Gates TJ. Spatial analysis of child pedestrian and bicycle crashes: Development of safety performance function for areas adjacent to schools. Transp Res Rec 2014;2465:57‑63. 
20. Moradi A, Soori H, Kavousi A, Eshghabadi F, Jamshidi E. Spatial factors affecting the frequency of pedestrian traffic crashes: A systematic review. Arch Trauma Res 2016;5:e30796. 
21. Hashimoto T. Spatial Analysis of Pedestrian Accidents. USA: University of South Florida; 2005. 
22. Green J, Muir H, Maher M. Child pedestrian casualties and deprivation. Accid Anal Prev 2011;43:714‑23. 
23. Moradi A, Salamati P, Vahabzadeh E. The social determinants of risky driving on the intercity roads of Tehran Province, Iran: A case‑cohort study. Arch Trauma Res 2017;6:e36490:1‑8.