The Role of Interaction‑Based Effects on Fatal Accidents Using Logic Regression

Document Type : Original Article

Authors

1 Student Research Committee, Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

2 Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

3 Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences

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

5 Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

10.4103/atr.atr_105_18

Abstract

Background and Objectives: Road traffic accidents(RTAs) were estimated to be the eighth major cause of death worldwide in 2016. Investigation of various factors alone can distort the results. Thus, it is important to consider interactions among the various factors associated with RTAs. Logic regression was used to investigate the important combinations among traffic accident variables. Methods: In this analytical study, the existing 1‑year data from the police accident database in 2014 were examined. The Legal Medicine Organization database was also used to correct death after 30 days. Logic regression, a generalized regression model, was used to explore the interactions among different factors of the accident. Results: Cross‑validation results showed the best model in the form of three trees and eight leaves. Being a professional driver and exposure to a heavy vehicle on sandy or earthy road double the chance of death. Operating an unsafe car on a road with curve increases the odds of a fatal crash by 1.65 times. Driver error on a nonresidential road without any shoulders adds 90% to the odds of having a deadly crash. Conclusions: The significance of the interactions between the road and driver factors shows that roads with poor design can cause a driver to make mistakes and increase fatal accidents. Therefore, politicians must consider constructing structures alongside nonresidential roads and proper shoulders, install signs at curves, and repair pavement in order to reduce the fatality of accidents. It is also recommended that manufacturers of commercial vehicles install proper safeguards in all heavy vehicles to reduce fatal accidents.

Keywords

References

1. World Health Organization. Global Status Report on Road Safety 2018. Geneva: World Health Organization; 2018.
2. World Health Organization. Disability‑Adjusted Life Years (DALYs); 2018. Available from: http://www.who.int/gho/mortality_burden_ disease/daly_rates/text/en/. [Last cited on 2019 Dec 02].
3. Nantulya VM, Reich MR. The neglected epidemic: Road traffic injuries in developing countries. BMJ 2002;324:1139‑41.
4. Ameratunga S, Hijar M, Norton R. Road‑traffic injuries: Confronting disparities to address a global‑health problem. Lancet 2006;367:1533‑40.
5. World Health Organisation. WHO Report 2015: Data Tables” (PDF) (Official Report). Geneva: World Health Organisation; 2015.
6. Peden MM, McGee K, Krug E. Injury: A Leading Cause of the Global Burden of Disease, 2000. Geneva: World Health Organization; 2002.
7. Moghaddam FR, Afandizadeh S, Ziyadi M. Prediction of accident severity using artificial neural networks. Int J Civil Eng 2011;9:41.
8. Niezgoda M, Kamiński T, Kruszewski M. Measuring driver behaviour‑indicators for traffic safety. J KONES 2012;19:503‑11.
9. World Health Organization. The Injury Chart Book: A Graphical Overview of the Global Burden of Injuries. Geneva: World Health Organization; 2002.
10. World Health Organization. Global Status Report on Road Safety 2015. Geneva: World Health Organization; 2015.
11. Naghavi M, Shahraz S, Bhalla K, Jafari N, Pourmalek F, Bartels D, et al. Adverse health outcomes of road traffic injuries in Iran after rapid motorization. Arch Iran Med 2009;12:284‑94.
12. Peden M, Scurfield R, Sleet D, Mohan D, Hyder AA, Jarawan E, et al. World Report on Road Traffic Injury Prevention. World Health Organization: Geneva; 2004.
13. Schepers P, Hagenzieker M, Methorst R, van Wee B, Wegman F. A conceptual framework for road safety and mobility applied to cycling safety. Accid Anal Prev 2014;62:331‑40.
14. Ruczinski I, Kooperberg C, LeBlanc M. Logic regression. J Comput Graphical Statistics 2003;12:475‑511.
15. Lucek PR, Ott J. Neural network analysis of complex traits. Genet Epidemiol 1997;14:1101‑6.
16. Kim YS. Effects of Driver, Vehicle, and Environment Characteristics on Collision Warning System Design: Institutionen för Teknik och Naturvetenskap; 2001.
17. Royal D. National Survey of Speeding and Unsafe Driving Attitudes and Behaviors: 2002. Findings. Vol. 2. United States: National Highway Traffic Safety Administration; 2004.
18. Vägverket PF. Swedish Road Administration. Borlänge, Sweden: Roads and Traffic, Publication. 2006. p. 23E‑52.
19. Ratanavaraha V, Suangka S. Impacts of accident severity factors and loss values of crashes on expressways in Thailand. IATSS Res 2014;37:130‑6.
20. Islam M, Tanaboriboon Y, editors. Crash Investigation and Reconstruction the New Experience in Developing Countries: Thailand Case Study. Proceedings of the Road Safety on Four Continents Conference; 2005.
21. Khalili M, Pakgohar A. Logistic regression approach in road defects impact on accident severity. J Emerg Technol Web Intell 2013;5:132‑5.
22. Bandyopadhyaya R, Mitra S. Modelling severity level in multi‑vehicle collision on Indian highways. Procedia Soc Behav Sci 2013;104:1011‑9.
23. Plankermann K. Human Factors as Causes for Road Traffic Accidents in the Sultanate of Oman under Consideration of Road Construction Designs. PhD, Universität Regensburg: Philosophy; 2014.
24. Senders JW, Kristofferson A, Levison W, Dietrich C, Ward J. The attentional demand of automobile driving. Bolt, Beranek and Newman Incorporated. Highway Res Record 1967;195:15-33.
25. Williamson A. Fatigue and coping with driver distraction. In: Faulks IJ, Regan M, Stevenson M, Brown J, Porter A, Irwin JD, (Eds.). Distracted driving. Sydney, NSW: Australasian College of Road Safety. 2007. p. 611-22.
26. Al‑Ghamdi AS. Using logistic regression to estimate the influence of accident factors on accident severity. Accid Anal Prev 2002;34:729‑41.
27. Zegeer C, Twomey J, Heckman M, Hayward J. Safety Effectiveness of Highway Design Features. Washington, DC: FHWA; 1992.
28. Kanchan T, Kulkarni V, Bakkannavar SM, Kumar N, Unnikrishnan B. Analysis of fatal road traffic accidents in a coastal township of South India. J Forensic Legal Med 2012;19:448‑51.
29. Mohamed MG, Saunier N, Miranda‑Moreno LF, Ukkusuri SV. A clustering regression approach: A comprehensive injury severity analysis of pedestrian‑vehicle crashes in New York, US and Montreal, Canada. Safety Sci 2013;54:27‑37.
30. Chu HC. An investigation of the risk factors causing severe injuries in crashes involving gravel trucks. Traffic Inj Prev 2012;13:355‑63.
31. Islam MB, Kanitpong K. Identification of factors in road accidents through in‑depth accident analysis. IATSS Res 2008;32:58‑67.
Archives of Trauma Research
Volume 7, Issue 4 - Serial Number 27
October 2018
Pages 140-145

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History

  • Receive Date: 01 June 2018
  • Accept Date: 01 October 2018

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