Vehicle configurations associated with anatomical-specific severe injuries resulting from traffic collisions
Autoři:
Fumihito Ito aff001; Yusuke Tsutsumi aff004; Kazuaki Shinohara aff006; Shunichi Fukuhara aff002; Noriaki Kurita aff001
Působiště autorů:
Department of Clinical Epidemiology, Fukushima Medical University, Fukushima City, Fukushima, Japan
aff001; Center for Innovative Research for Communities and Clinical Excellence (CIRC2LE), Fukushima Medical University, Fukushima City, Fukushima, Japan
aff002; Department of Sport Medicine, Fukushima Medical University, Fukushima City, Fukushima, Japan
aff003; Department of Emergency Medicine, National Hospital Organization Mito Medical Center, Mito, Ibaraki, Japan
aff004; Department of Healthcare Epidemiology, School of Public Health in the Graduate School of Medicine, Kyoto University, Kyoto, Japan
aff005; Department of Emergency and Critical Care Medicine, Ohta Nishinouchi Hospital, Koriyama, Fukushima, Japan
aff006; Department of Innovative Research & Education for Clinicians and Trainees (DiRECT), Fukushima Medical University Hospital, Fukushima City, Fukushima, Japan
aff007
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223388
Souhrn
Vehicles can be classified by configuration as either bonnet-type or cab-over type according to engine location. Compared to bonnet-type, the front compartment of cab-over type vehicles is considerably shorter; thus, it may be less likely to absorb the energy generated in a collision, and in turn be unable to prevent deformation of the occupant space and protect occupants from injury. This study was a cohort study involving 943 occupants of mini-vehicles who were injured in frontal collision accidents between 2001 and 2015 and transferred to Ohta Nishinouchi Hospital. The vehicle configuration was divided into bonnet-type and cab-over type (i.e., truck-type and wagon-type). The tested outcomes were anatomical-specific severe injury of the pelvis and extremities, the head and neck, the abdomen, and the chest. To estimate adjusted odds ratios (AOR) for associations between vehicle configuration and anatomical-specific severe injury, we fitted generalized estimating equations for each outcome. Compared with bonnet-type vehicles, a greater risk of serious pelvis and extremities injury was found for both truck (AOR: 2.21; 95% Confidence Interval [95% CI]: 1.22–4.00) and wagon-type vehicles (AOR: 3.43; 95%CI 1.60–7.39). For serious head and neck injury, truck-type vehicles were associated with greater risk (AOR: 2.04; 95% CI: 1.10–3.79) than bonnet-type vehicles, whereas wagon-type vehicles were not. Compared with the occupants of bonnet-type vehicles, cab-over type vehicle occupants were more likely to have serious pelvis and extremities injury during frontal collisions. Additionally, truck-type vehicle occupants were more likely to have serious head and neck injury than bonnet-type vehicle occupants. These findings are expected to promote safer behaviors for vehicle occupants and the automobile industry.
Klíčová slova:
Critical care and emergency medicine – Engines – Head – Head injury – Neck – Pelvis – Roads
Zdroje
1. World Health Organization. The Global Status Report on Road Safety 2015. 2015. Available from: http://www.who.int/violence_injury_prevention/road_safety_status/2015/en/
2. Jeon HJ, Kim SC, Shin J, Jung JY, Lee KH, Lee HY, et al. Risk of serious injury of occupants involved in frontal crashes of cab-over-type trucks. Traffic Inj Prev. 2017;18(8): 839–844. doi: 10.1080/15389588.2017.1315413 28384074
3. Kazuaki S. The difference of passengers severity between the type of the vehicle. Japanese Journal of Acute Medicine. 2010;34: 557–560 (in Japanese).
4. Ministry of Land, Infrastructure and Transport. Road Transport Vehicle Act. 2017. Available from: http://elaws.e-gov.go.jp/search/elawsSearch/elaws_search/lsg0500/detail?lawId=326M50000800074#1869 (in Japanese).
5. Japan Light Motor Vehicle and Motorcycle Association. Trends in vehicle ownership by vehicle type. 2018. Available from: http://www.zenkeijikyo.or.jp/statistics/4own (in Japanese).
6. The Japanese Association for The Surgery of Trauma. Japan Automobile Research Institute. The Abbreviated Injury Scale 1990 Revision Update 1998. Herusu Shuppan; 2003 (in Japanese).
7. Braver ER, Ferguson SA, Greene MA, Lund AK. Reductions in deaths in frontal crashes among right front passengers in vehicles equipped with passenger air bags. Jama. 1997;278(17): 1437–1439. 9356003
8. Siegel JH, Loo G, Dischinger PC, Burgess AR, Wang SC, Schneider LW, et al. Factors influencing the patterns of injuries and outcomes in car versus car crashes compared to sport utility, van, or pick-up truck versus car crashes: Crash Injury Research Engineering Network Study. J Trauma. 2001;51(5): 975–990. doi: 10.1097/00005373-200111000-00024 11706349
9. Japan Light Motor Vehicle and Motorcycle Association. Trends in new car sales volume by year and vehicle type in mini vehicles. 2018. Available from: http://www.zenkeijikyo.or.jp/statistics/4new-nendosui (in Japanese).
10. Hellinga LA, McCartt AT, Haire ER. Choice of teenagers' vehicles and views on vehicle safety: survey of parents of novice teenage drivers. J Safety Res. 2007;38(6): 707–713. doi: 10.1016/j.jsr.2007.10.003 18054603
11. Eichelberger AH, Teoh ER, McCartt AT. Vehicle choices for teenage drivers: A national survey of U.S. parents. J Safety Res. 2015;55: 1–5. doi: 10.1016/j.jsr.2015.07.006 26683541
12. Chen F, Chen S. Injury severities of truck drivers in single- and multi-vehicle accidents on rural highways. Accid Anal Prev. 2011;43(5):1677–88. doi: 10.1016/j.aap.2011.03.026 21658494
13. Chen F, Chen S, Ma X. Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data. J Safety Res. 2018;65:153–9. doi: 10.1016/j.jsr.2018.02.010 29776524
14. Ma C, Hao W, Xiang W, Yan W. The impact of aggressive driving behavior on driver-injury severity at highway-rail grade crossings accidents. Journal of Advanced Transportation. 2018;2018:1–10.
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