Traffic injury prevention
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Traffic injury prevention · Jan 2015
Get a license, buckle up, and slow down: risky driving patterns among saudis.
Road traffic injuries are the largest cause of loss of disability-adjusted life years for men and women of all ages in the Kingdom of Saudi Arabia, but data on driving habits there are lacking. To inform policymakers on drivers' abilities and driving habits, we analyzed data from the Saudi Health Interview Survey 2013. ⋯ The high burden of road traffic injuries in the Kingdom is not surprising given our findings. Our study calls for aggressive monitoring and enforcement of traffic laws. Awareness and proper education for drivers and their families should be developed jointly by the Ministries of Health, Interior Affairs, and Education and provided through their channels.
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Traffic injury prevention · Jan 2015
Statistical analysis of bicyclists' injury severity at unsignalized intersections.
This study investigated factors correlated with the severity of injuries sustained by bicyclists in bicycle-motor vehicle crashes at unsignalized intersections to develop site-specific countermeasures and interventions to improve bicycle safety. ⋯ Based on these results, we suggest the development of educational programs focused on the following groups: child bicyclists, older bicyclists, and older drivers. Investigating and modifying street lighting could improve bicycle safety. Implementing road diets/traffic calming methods could create a safer traffic environment. Certain traffic control strategies (e.g., stop control) could be considered for uncontrolled intersections with high bicycle exposure, and helmet campaigns should be launched to increase helmet awareness and use. The study also suggests some interesting future research directions, including examining driver/bicyclist behaviors at uncontrolled intersections and studying the riding behaviors of child bicyclists in Kentucky.
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Traffic injury prevention · Jan 2015
Comparative StudyEffectiveness of motorcycle antilock braking systems (ABS) in reducing crashes, the first cross-national study.
This study set out to evaluate the effectiveness of motorcycle antilock braking systems (ABS) in reducing real-life crashes. Since the European Parliament has voted on legislation making ABS mandatory on all new motorcycles over 125 cc from 2016, the fitment rate in Europe is likely to increase in the coming years. Though previous research has focused on mostly large displacement motorcycles, this study used police reports from Spain (2006-2009), Italy (2009), and Sweden (2003-2012) in order to analyze a wide range of motorcycles, including scooters, and compare countries with different motorcycling habits. ⋯ At this stage, there is more than sufficient scientific-based evidence to support the implementation of ABS on all motorcycles, even light ones. Further research should aim at understanding the injury mitigating effects of motorcycle ABS, possibly in combination with combined braking systems.
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Traffic injury prevention · Jan 2015
Estimated injury risk for specific injuries and body regions in frontal motor vehicle crashes.
Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data. ⋯ These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.
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Traffic injury prevention · Jan 2015
On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants.
The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures. ⋯ The OSISP models achieve good discriminating capability for light truck occupants and a reasonable performance for heavy truck occupants. The prediction accuracy may be increased by acquiring more data. Belt use was the strongest predictor of severe injury for both light and heavy truck occupants. There is a need for behavior-based safety programs and/or other means to encourage truck occupants to always wear a seat belt.