Measuring the effect of vehicle safety on road traffic crash severity in Iran: using structural equation modeling
Objective: Vehicle safety plays a key role in reducing the number of road traffic deaths and serious injuries. This study aims to investigate the effect of vehicle safety on the severity of traffic crashes in Iran using structural equation modeling (SEM). Methods: This was a comparative cross-sectional study of all imported vehicles with Aras free trade zone license plate as well as all domestic vehicles (cars produced in Iran) commuting on Tabriz-Jolfa road. The study population included drivers who had accidents on Tabriz-Jolfa road over a period of one year from September 22, 2020 to September 21, 2021 and were injured or their vehicles had been damaged (n=652). Data was collected using set of questionnaires with 10 sections. The effect of independent variables, as exogenous latent variables (human, vehicle, and environmental factors), on a dependent variable, as an endogenous latent variable (crash severity) was measured using SEM. All data were analyzed using Mplus 8.0 software. Results: In the structure part of the model with foreign vehicles group, the effect sizes of three exogenous variables, i.e., human, environmental, and vehicle factors, on the dependent variables were found to be 0.412, 0.396 and 0.358, respectively. The effect sizes in the model with domestic vehicles were found to be 0.312, 0.702 and 0.820, respectively. Conclusion: Vehicle factors (variables related to car safety) had a high impact on crash severity in the national license plate and domestically manufactured vehicle group, indicating the necessity of improving vehicle safety.
2. Zampetti R, Messina G, Quercioli C, Vencia F, Genco L, Di Bartolomeo L, et al. Nonfatal road traffic injuries: can road safety campaigns prevent hazardous behavior? an Italian experience. Traffic Inj Prev. 2013;14(3):261-6.
3. Ozanne-Smith J, Schaumann JL, Oxley J. Injuries in adolescents: the public health response. International handbook on adolescent health and development. 2017:71-92.
4. World Health Organization. Global status report on road safety 2015. Geneva: World Health Organization; 2015.
5. Ameratunga S, Hijar M, Norton R. Road-traffic injuries: confronting disparities to address a global-health problem. Lancet. 2006;367(9521):1533-40.
6. Road safety statistics at regional level. Eurostat statistics explained. Available in: ec.eropa.eu/eurostat/statistics-explained/index.php?title=Archive:Road_safety_statistics_at_regional_level.
7. Wang K, Qin X. Use of structural equation modeling to measure severity of single-vehicle crashes. Transp Res Rec. 2014;2432:17-25.
8. Lee JY, Chung JH, Son B. Analysis of traffic accident size for Korean highway using structural equation models. Accid Anal Prev. 2008;40(6):1955-63.
9. Golob TF. Structural equation modeling for travel behavior research. Transp. Res. B: Methodol. 2003;37(1):1-25.
10. Hoyle RH. Handbook of structural equation modeling: The Guilford Press ;2012.
11. Kline RB. Principles and practice of structural equation modeling, 3rd ed.The Guilford Press; 2011.
12. De Pelsmacker P, Janssens W. The effect of norms, attitudes and habits on speeding behavior: scale development and model building and estimation. Accid Anal Prev. 2007;39(1):6-15.
13. Heidari M, Khorramdel K, Rakhshani T, Kazem S. Comparision of humanistic factor in incidence of driving accidents between Business community. Sci J Rescue & Relief. 2012;4:39-45.
14. Costa PT, McCrae RR (1992). Revised NEO personality inventory (NEO-PIR) and NEO five-factor inventory (NEO-FFI) professional manual. Odessa, FL: psychological assessment resources.
15. Alavi SS, Mohammadi M, Soori H, Mohammadi Kalhori S, Sepasi N, Khodakarami R, et al. Iranian version of Manchester driving behavior questionnaire (MDBQ): psychometric properties. Iran J psychiatry. 2016;11(1):37-42.
16. Daigre Blanco C, Ramos-Quiroga JA, Valero S, Bosch R, Roncero C, Gonxalvo B, et al. Adult ADHD self-report scale (ASRS-v1.1) symptom checklist in patients with substance use disorders. Actas Esp Psiquiatr. 2009;37(6):299-305.
17. Shahid A, Wilkinson K, Marcu S, Shapiro CM. Multidimensional fatigue inventory (MFI). STOP, THAT and One Hundred Other Sleep Scales: Springer Science & Business Media; 2012.
18. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry res. 1989;28(2):193-213.
19. Shiri P, Soori H, Hashemi-Nazari SS. Study of most important factors of voluntary engagement in distraction and susceptibility to involuntary distraction related to road traffic injuries. J Saf Promot Inj Prev. 2019;7(1). [Persian].
20. Abobakri O, Sadeghi-Bazargani H, Asghari-Jafarabadi M, Aghdam MB, Imani A, Tabrizi J, et al. Development and psychometric evaluation of a socioeconomic status questionnaire for urban households (SESIran): the preliminary version. Health Promot Perspec. 2016;5(4):250-60.
21. Muthén LK, Muthen BO (1998-2017). Mplus user's guide: statistical analysis with latent variables, Eighth Ed. Los Angeles, CA: Muthén & Muthén; 2017.
22. Hassan H, Abdel-Aty M. Analysis of drivers’ behavior under reduced visibility conditions using a structural equation modeling approach. Transp Res F: Traffic Psychol Behav. 2011;14:614-25.
23. Kupek E. Beyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders. BMC Med Res Methodol. 2006;6:13.
24. Shaaban K, Gaweesh S, Ahmed MM. Investigating in-vehicle distracting activities and crash risks for young drivers using structural equation modeling. PLoS One. 2020;15(7):e0235325.
25. Kim K, Pant P, Yamashita E. Measuring influence of accessibility on accident severity with structural equation modeling. Transportation research record. 2011;2236:1-10.
26. Sheykhfard A, Haghighi F, Nordfjærn T, Soltaninejad M. Structural equation modelling of potential risk factors for pedestrian accidents in rural and urban roads. Int J Inj Contr Saf Promot. 2021;28(1):46-57.
27. Al Reesi H, Al Maniri A, Plankermann K, Al Hinai M, Al Adawi S, Davey J, et al. Risky driving behavior among university students and staff in the Sultanate of Oman. Accid Anal Prev. 2013;58:1-9.
28. Akloweg Y, Hayshi Y, Kato H. The effect of used cars on African road traffic accidents: a case study of Addis Ababa, Ethiopia. Int J Urban Sci. 2011;15(1):61-9.
29. Mishra B, Sinha ND, Sukhla S, Sinha A. Epidemiological study of road traffic accident cases from Western Nepal. Indian J Community Med. 2010;35(1):115-21.
30. Cummings P, McKnight B, Rivara FP, Grossman DC. Association of driver air bags with driver fatality: a matched cohort study. BMJ. 2002;324(7346):1119-22.
31. Braver ER, Kyrychenko SY. Efficacy of side air bags in reducing driver deaths in driver-side collisions. Am J Epidemiol. 2004;159(6):556-64.
|Issue||Vol 7 No 2 (2023): Spring (April)|
|Air Bags Seat Belts Structural Equating Modeling Traffic Accidents|
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