Spatial Factors Related to Traffic Crashes on Pedestrians in All Districts of Tehran

Document Type: Original Article

Authors

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

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

3 Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran

4 Department of Human Geography/Urban Planning, University of Tehran, Tehran, Iran

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

6 Department of Epidemiology, School of Public Health, Tehran University of Medical Sciences

7 Crashes Office, Tehran’s Traffic Police, Tehran

Abstract

Background: A great proportion of deaths due to traffic crashes occur for pedestrians, both in developing and developed countries.
Objectives: The aim of the present study was to determine the spatial factors related to the frequency of traffic crashes on pedestrians in
districts of Tehran city. Methods: This was a cross‑sectional study. All traffic crashes on pedestrians during 2013–2015 were included in this
study. The data were extracted from different sources such as traffic police main office, Tehran municipal office, and Iran statistics center.
Poisson and negative binomial regression models were used to analyze the role of environment and district on frequency of traffic crashes.
Moreover, the likelihood‑ratio test has been used for comparison between models, while assessment of goodness‑of‑fit has been reported
using R2, Akaike information criteria, and Bayesian information criteria. Results: Of 12,090 crashes, 11,895 (98.4%) had led to injuries, while
195 (1.6%) had led to deaths. The frequency of crashes varied substantially in different districts of Tehran. The incidence of injuries did not
show any particular pattern, whereas the pattern of incidence of deaths was lower in central districts in comparison to higher incidence in
marginal districts (e.g., north, south, west, and east of Tehran). The results of the final model showed a statistically significant association among
various variables such as demographics, web of roads, rate of traveling, and land use with the outcome as number of crashes in geographic
units. Conclusions: Frequency distribution of traffic crashes leading to injury and/or death is completely different in various districts of Tehran.
Demographic as well as spatial characteristics also play an important role in determining this distribution. Regional planning, appropriate traffic
management, control measures on spatial risk factors, and educational programs could substantially improve the safety of pedestrians in Tehran.

Keywords


1. World Health Organization. Global Status Report on Road Safety 2018. Licence: CC BYNC‑SA 3.0 IGO. Geneva: World Health Organization; 2018.

2. European Union, Road Safety in the European Union. Trends, Statistics and Main Challenges. European Union, Road safety in the European Union; 2015. Available from: http://ec.europa.eu/roadsafety. [Last accessed on 2015 Feb 01].

3. Slaughter DR, Williams N, Wall SP, Glass NE, Simon R, Todd SR, et al. A community traffic safety analysis of pedestrian and bicyclist injuries based on the catchment area of a trauma center. J Trauma Acute Care Surg 2014;76:1103‑10.

4. Miranda‑Moreno LF, Morency P, El‑Geneidy AM. The link between built environment, pedestrian activity and pedestrian‑vehicle collision occurrence at signalized intersections. Accid Anal Prev 2011;43:1624‑34.

5. Mohan D, Tsimhoni O, Sivak M, Flannagan MJ. Road Safety in India: Challenges and Opportunities. The University of Michigan, Transportation Research Institute; 2009.

6. Moradi A, Soori H, Kavousi A, Eshghabadi F, Nematollahi S, Zeini S. Effective environmental factors on geographical distribution of traffic accidents on pedestrians, downtown Tehran city. Int J Crit Illn Inj Sci 2017;7:101‑6.

7. Accident Bureau. Bulletin of Statistics and Analysis of Accidents. Tehran: Traffic Police of Rahvar; 2015.

8. Iran’s Population and Housing Census‑2016. Iran Statistics Center; 2018.

9. Center for Studies and Planning in Tehran. Mobility, Transportation and Communication Networks of Tehran Comprehensive Plan. Ministry of Housing and Urban Development and Tehran Municipality; 2006.

10. Tehran Municipality. Tehran; 2015. Available from: http://www.tehran.ir. [Last accessed on 2015 Feb 01].

11. The Number of Trips Made. Teran: Railway Company of Tehran and Suburbs; 2011.

12. United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects: The 2012 Revision. New York, USA: United Nations, Department of Economic and Social Affairs, Population Division; 2013.

13. Ayati E, Abbasi E. Application of zero‑inflated regression models in modeling accidents on urban highways. Omran Modares J 2011;11:1‑15. 14. Hilbe JM. Negative Binomial Regression. London, England: Cambridge University Press; 2011.

15. Cottrill CD, Thakuriah PV. Evaluating pedestrian crashes in areas with high low‑income or minority populations. Accid Anal Prev 2010;42:1718‑28.

16. 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.

17. Siddiqui C, Abdel‑Aty M, Choi K. Macroscopic spatial analysis of pedestrian and bicycle crashes. Accid Anal Prev 2012;45:382‑91.

18. 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.

19. McArthur A, Savolainen P, Gates T. Spatial analysis of child pedestrian and bicycle crashes: Development of safety performance function for areas adjacent to schools. Transportation Research Record. J Transp Res Board 2014;2465:57-63.

20. Hashimoto T. Spatial Analysis of Pedestrian Accidents. USA: University of South Florida; 2005.

 21. 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.

22. Green J, Muir H, Maher M. Child pedestrian casualties and deprivation. Accid Anal Prev 2011;43:714‑23.

23. Yao S, Loo BP. Identification of hazardous road locations for pedestrians. Procedia Eng 2012;45:815‑23.

24. Wier M, Weintraub J, Humphreys EH, Seto E, Bhatia R. An area‑level model of vehicle‑pedestrian injury collisions with implications for land use and transportation planning. Accid Anal Prev 2009;41:137‑45.