The objective of this study was to describe a population of children admitted to a tertiary care pediatric hospital with severe trauma to identify key areas for injury prevention research, and programming.
Retrospective chart review conducted on all children 0-17 years admitted to the Children's Hospital of Eastern Ontario (CHEO) between April 1, 1996, and March 31, 2000, following acute trauma. Each record was reviewed and assigned an ISS using the AIS 1990 revision. All cases with an ISS > 11 were included in the study.
There were 2610 trauma cases admitted to CHEO over the study period. Of these, 237 (9.1%) had severe trauma (ISS > 11). Sixty-two percent were male. Twenty-nine percent were between the ages of 10 and 14 years, 27% between 5 and 9 years, 16% between 15 and 17 years, 15% between 1 and 4 years, and 13% less than 1 year old. The most common mechanisms of injury were due to motor vehicle traffic (39%), falls (24%), child abuse (8%), and sports (5%). Of those resulting from motor vehicle traffic, 53 (57%) were occupants, 22 (24%) were pedestrians, and 18 (19%) were cyclists. When combining traffic and nontraffic mechanisms, 26 (11% of all severe trauma cases) occurred as a result of cycling incidents. The most severe injury in 65% of patients was to the head and neck body region.
Research efforts and activities to prevent severe pediatric trauma in our region should focus on road safety, protection from head injuries, avoidance of falls, and prevention of child abuse.
Acceptability and concurrent validity of measures to predict older driver involvement in motor vehicle crashes: an Emergency Department pilot case-control study.
CanDRIVE(1): a Canadian Institutes of Health Research (CIHR) Institute of Aging funded New Emerging Team, Elisabeth-Bruyère Research Institute, 43 Bruyère Street, Ottawa, ON, Canada K1N 5C8. fmolnar@ottawahospital.on.ca
Older drivers have one of the highest motor vehicle crash (MVC) rates per kilometer driven, largely due to the functional effects of the accumulation, and progression of age-associated medical conditions that eventually impact on fitness-to-drive. Consequently, physicians in many jurisdictions are legally mandated to report to licensing authorities patients who are judged to be medically at risk for MVCs. Unfortunately, physicians lack evidence-based tools to assess the fitness-to-drive of their older patients. This paper reports on a pilot study that examines the acceptability and association with MVC of components of a comprehensive clinical assessment battery.
To evaluate the acceptability to participants of components of a comprehensive assessment battery, and to explore potential predictors of MVC that can be employed in front-line clinical settings.
Case-control study of 10 older drivers presenting to a tertiary care hospital emergency department after involvement in an MVC and 20 age-matched controls.
The measures tested were generally found to be acceptable to participants. Positive associations (p
This paper describes some of the main findings from two separate studies on accident prediction models for urban junctions and urban road links described in [Uheldsmodel for bygader-Del1: Modeller for 3-og 4-benede kryds. Notat 22, The Danish Road Directorate, 1995; Uheldsmodel for bygader- Del2: Modeller for straekninger. Notat 59, The Danish Road Directorate, 1998] (Greibe and Hemdorff, 1995, 1988). The main objective for the studies was to establish simple, practicable accident models that can predict the expected number of accidents at urban junctions and road links as accurately as possible. The models can be used to identify factors affecting road safety and in relation to 'black spot' identification and network safety analysis undertaken by local road authorities. The accident prediction models are based on data from 1036 junctions and 142 km road links in urban areas. Generalised linear modelling techniques were used to relate accident frequencies to explanatory variables. The estimated accident prediction models for road links were capable of describing more than 60% of the systematic variation ('percentage-explained' value) while the models for junctions had lower values. This indicates that modelling accidents for road links is less complicated than for junctions, probably due to a more uniform accident pattern and a simpler traffic flow exposure or due to lack of adequate explanatory variables for junctions. Explanatory variables describing road design and road geometry proved to be significant for road link models but less important in junction models. The most powerful variable for all models was motor vehicle traffic flow.
The objective of this paper was to identify the most dangerous segments of the Icelandic road system in terms of the number of accidents pr km and the rate of accidents pr million km travelled. First to identify the segments where the number of accidents is highest and where the risk of the individual traveller is the greatest. Second to evaluate if the association between the number and the rate of accidents is positive or negative. Third to identify the road segments that are the most dangerous in the sense of many accidents and great risk to individual travellers.
Main roads outside urban centers were divided into 45 segments that were on average 78 km in length. Infrequently travelled roads and roads within urban centers were omitted. Information on the length of roads, traffic density and number of accidents was used to calculate the number of accidents per km and the rate of accidents per million km travelled. The correlation between the number and rate of accidents was calculated and the most dangerous road segments were identified by the average rank order on both dimensions.
Most accidents pr km occurred on the main roads to and from the capital region, but also east towards Hvolsvöllur, north towards Akureyri and in the Mideast region of the country. The rate of accidents pr million km travelled was highest in the northeast region, in northern Snæfellsnes and in the Westfjords. The most dangerous roads on both dimensions were in Mideast, northern Westfjords, in the north between Blönduós and Akureyri and in northern Snæfellsnes.
Most accidents pr km occurred on roads with a low accident rate pr million km travelled. It is therefore possible to reduce accidents the most by increasing road safety where it is already the greatest but that would however increase inequalities in road safety. Policy development in transportation is therefore in part a question of priorities in healthcare. Individual equality in safety and health are not always fully compatible with economic concerns and the interests of the majority.
Road traffic injury is the leading cause of death among adolescents in high-income countries. Researchers attribute this threat to driver risk taking, which driver education (DE) attempts to reduce. Many North American authorities grant DE graduates earlier access to unsupervised driving despite no evidence of this being a safety benefit. This theoretical article examines risk taking and DE in relation to an apparent mobility bias (MB) in policymaking.
The MB is defined, the history and sources of driver risk taking are examined, and the failure of DE to reduce collision risk is analyzed in relation to a potential MB in licensing policies.
The author argues that DE's failure to reduce adolescent collision risk is associated with a MB that has produced insufficient research into DE programs and that influences public policymakers to grant earlier licensure to DE graduates. Recommendations are made regarding future research on DE and risk taking, coordinated improvements to DE and driver licensing, and a plan to reduce collision risk by encouraging parental supervision after adolescent licensure.
Research on adolescent driver risk taking would have direct applications in DE curricula development, driver's license evaluation criteria, graduated licensing (GDL) policies, as well as other aspects of human factor research into the crash-risk problem.
