Accident; analysis and prevention
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This study identifies and compares the significant factors affecting pedestrian crash injury severity at signalized and unsignalized intersections. The factors explored include geometric predictors (e.g., presence and type of crosswalk and presence of pedestrian refuge area), traffic predictors (e.g., annual average daily traffic (AADT), speed limit, and percentage of trucks), road user variables (e.g., pedestrian age and pedestrian maneuver before crash), environmental predictors (e.g., weather and lighting conditions), and vehicle-related predictors (e.g., vehicle type). The analysis was conducted using the mixed logit model, which allows the parameter estimates to randomly vary across the observations. ⋯ At unsignalized intersections, pedestrian walking along roadway, middle and very old pedestrians, at-fault pedestrians, vans, dark lighting condition, and higher speed limit were associated with higher pedestrian severity risk. On the other hand, standard crosswalks were associated with 1.36% reduction in pedestrian severe injuries. Several countermeasures to reduce pedestrian injury severity are recommended.
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This study examines the associations between lifetime traumatic brain injury (TBI), driver aggression, and motor vehicle collisions among a population sample of adults who reside in the province of Ontario, Canada. ⋯ This is the first population-based study to demonstrate a relationship between a history of TBI and higher rates of serious driver aggression and collision involvement. Given the large proportion of adult drivers with a history of TBI, these individuals may account for a disproportion burden of all traffic safety problems. Whether the increased road safety risk of adults with a history of TBI is reflective of neurocognitive deficits or is merely evidence of a cluster of unsafe activities produced by a higher risk lifestyles requires further research attention.
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In aging societies, increasing numbers of older drivers are involved in motor vehicle collisions (MVCs), and preserving their safety is a growing concern. In this study, we focused on whether older drivers were more likely to cause MVCs and injuries than drivers in other age groups. To do so we compared at-fault MVC incidence and resulting injury risks by drivers' ages, using data from Japan, a country with a rapidly aging population. ⋯ The at-fault MVC incidence showed a U-shaped curve across the drivers' ages, where teenage and the oldest drivers appeared to be the highest risk groups in terms of causing MVCs, and the incidence was higher for female drivers after age 25. The injury risk older drivers posed to other vehicle occupants because of their at-fault MVCs was lower than for drivers in other age groups, while their own injury risk appeared much higher. As the number of older drivers is increasing, efforts to reduce their at-fault MVCs appear justified.
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The main cause of death and serious disability in bicycle accidents is traumatic brain injury (TBI). The aim of this population-based study was to assess the incidence and costs of bicycle-related TBI across various age groups, and in comparison to all bicycle-related injuries, to identify main risk groups for the development of preventive strategies. Data from the National Injury Surveillance System and National Medical Registration were used for all patients with bicycle-related injuries and TBI who visited a Dutch emergency department (ED) between 1998 and 2012. ⋯ Older cyclists (aged 55+) were identified as main risk group for TBI, as they had highest ED attendance, injury rate, injury severity, admission to hospital or intensive care unit, and costs. Incidence of ED treatments due to cycling are high and often involve TBI, imposing a high burden on individuals and society. Older cyclists aged 55+ were identified as main risk group for TBI to be targeted in preventive strategies, due to their high risk for (serious) injuries and ever-increasing share of ED visits and hospital admissions.
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Many victims in traffic accidents do not receive optimal care due to the fact that the severity of their injuries is not realized early on. Triage protocols are based on physiological and anatomical criteria and subsequently on mechanisms of injury in order to reduce undertriage. In this study the value of accident characteristics for field triage is evaluated by developing an on scene injury severity prediction (OSISP) algorithm using only accident characteristics that are feasible to assess at the scene of accident. ⋯ Belt use is the strongest predictor followed by type of accident. Posted speed limit, age and accident location contribute substantially to increase model accuracy, whereas sex and airbag deployment contribute to a smaller extent and seat position is of limited value. These findings can be used to refine triage protocols used in Sweden and possibly other countries with similar traffic environments.