To examine the annual incidence of acute whiplash injuries after road traffic crashes in a geographic catchment area in Northern Sweden during the period 2000-2009.
Descriptive epidemiology determined by prospectively collected data from a defined population.
The study was conducted at a public hospital in Sweden.
The population of the hospital's catchment area (136,600 inhabitants in 1999 and 144,500 in 2009).
At the emergency department, all injured persons (approximately 11,000 per year) were asked to answer a questionnaire about the injury incident. Data from the medical records also were analyzed. From 2000-2009, 15,506 persons were injured in vehicle crashes. Persons who were subject to an acute neck injury within whiplash-associated disorder grades 1-3 were included. The overall and annual incidences were calculated as incidence. Age, gender, type of injury event, and direction of impact were described. The incidences were compared with national statistics on insurance claims from 2003, 2007, and 2008 to detect changes in the proportions of claims.
The annual incidence of acute whiplash injuries. Secondary outcome measures were types of injury events, age and gender distribution, changes in the proportion of rear-end crashes during 2000-2009, and changes in the proportion of insurance claims during 2003-2008.
During 2000-2009, 3297 cases of acute whiplash injury were encountered. The overall incidence was 235/100,000/year. The average yearly increase in incidence was 1.0%. Women comprised 51.9% and men 48.1% of the injured. Car occupants (86.4%) and bicycle riders (6.1%) were most frequently injured. The proportion of rear-end crashes decreased from 55% to 45% from 2000-2009. The proportion of insurance claims significantly decreased between 2003 and 2008 (P
In Finland, the severity of road traffic injuries is determined using the International Classification of Diseases, 10th Revision, Finnish Modification (ICD-10-FM) injury codes from Finnish Hospital Discharge data and the automatic conversion tool (ICD-AIS map) developed by the Association for the Advancement of Automotive Medicine (AAAM). The aim of this study was to evaluate the ability of the ICD-AIS map to identify seriously injured patients due to traffic accidents in Finnish injury data by comparing the severity rating generated by an expert and by the ICD-AIS map.
Our data came from the North Kymi Hospital (level 2 trauma center at the time of the study). The data included 574 patients who were injured in traffic accidents during 2 years. The severity rating (Maximum Abbreviated Injury Scale [MAIS] 3+) of each patient was recorded retrospectively by an expert based on information from patient records. In addition, the rating was generated from ICD-10 injury codes by the ICD-AIS map conversion tool. These 2 ratings were compared by road user categories and the strength of agreement was described using Cohen's kappa.
The proportion of seriously injured patients was 10.1% as defined by the expert and 6.6% as generated by the ICD-AIS map; exact agreement was 65.5%. The highest concordance was for pedestrians (exact agreement 100%) and the weakest for moped drivers and motorcyclists (46.7%). Furthermore, the overall strength of agreement of the severity ratings (slightly or seriously injured) between the expert and the ICD-AIS map was good (??=?0.70). Most (65%) of the conversion problems were misclassifications caused by the simplicity of the Finnish ICD-10 injury codes compared to the injury codes used in the ICD-AIS map. In Finland, the injuries are recorded mainly with 4-digit codes and, infrequently, with 5-digit codes, whereas the ICD-AIS map defines up to 6-digit codes.
For this sample of simplified ICD-10-FM codes, the ICD-AIS map underestimated the number of seriously injured patients. The mapping result could be improved if at least open and closed fractures of extremities and visceral contusions and ruptures had separate codes. In addition, there were a few injury codes that should be considered for inclusion in the map.
OBJECTIVES: To determine if young adults with a history of typical absence epilepsy (AE) in childhood have a greater risk of accidental injury than controls with juvenile rheumatoid arthritis (JRA). To assess the nature and severity of these injuries. METHODS: All patients with AE or JRA diagnosed between 1977 and 1985, who were 18 years or older at the onset of the study, were identified from review of pediatric electroencephalographic records for the province of Nova Scotia (AE) or review of the medical records database at the only tertiary care pediatric center for the province (JRA). Fifty-nine (86%) of 69 patients with AE and 61 (80%) of 76 patients with JRA participated in an interview in 1994 or 1995, assessing nature, severity, and treatment of prior accidental injuries. Patients with AE were further questioned about injuries sustained during an absence seizure. RESULTS: Sixteen (27%) of 59 patients with AE reported accidental injury during an absence seizure, with risk of injury being 9% per person-year of AE. Most injuries (81%) occurred during anti-epileptic drug therapy. Although the majority of injuries did not require treatment, 2 (13%) of 16 patients required minor treatment and 2 (13%) of 16 were admitted to hospital. The risk of accidental injury resulting from an absence seizure in person-years at risk was highest in juvenile myoclonic epilepsy (45%), moderate in juvenile AE (14%), and lowest in childhood AE (3%). Patients with AE had a greater number of overall accidental injuries than those with JRA (P
It has been claimed that exposure to risk of road traffic accidents (usually conceptualized as mileage) is curvilinearly associated with crashes (i.e., the increase in number of crashes decreases with increased mileage). However, this effect has been criticized as mainly an artifact of self-reported data.
To test the proposition that self-reported accidents create part of the curvilinearity in data by under-reporting by high-accident drivers, self-reported and recorded collisions were plotted against hours of driving for bus drivers.
It was found that the recorded data differed from self-reported information at the high end of exposure, and had a more linear association with the exposure measure as compared to the self-reported data, thus supporting the hypothesis.
Part of the previously reported curvilinearity between accidents and exposure is apparently due to biased methods. Also, the interpretation of curvilinearity as an effect of exposure upon accidents was criticized as unfounded, as the causality may just as well go the other way.
The question of how exposure associates with crash involvement is far from resolved, and everyone who uses an exposure metric (mileage, time, induced) should be careful to investigate the exact properties of their variable before using it.
Recent research advocates the use of count models with random parameters as an alternative method for analyzing accident frequencies. In this paper a dataset composed of urban arterials in Vancouver, British Columbia, is considered where the 392 segments were clustered into 58 corridors. The main objective is to assess the corridor effects with alternate specifications. The proposed models were estimated in a Full Bayes context via Markov Chain Monte Carlo (MCMC) simulation and were compared in terms of their goodness of fit and inference. A variety of covariates were found to significantly influence accident frequencies. However, these covariates resulted in random parameters and thereby their effects on accident frequency were found to vary significantly across corridors. Further, a Poisson-lognormal (PLN) model with random parameters for each corridor provided the best fit. Apart from the improvement in goodness of fit, such an approach is useful in gaining new insights into how accident frequencies are influenced by the covariates, and in accounting for heterogeneity due to unobserved road geometrics, traffic characteristics, environmental factors and driver behavior. The inclusion of corridor effects in the mean function could also explain enough variation that some of the model covariates would be rendered non-significant and thereby affecting model inference.
Foreign drivers are considered to be a greater risk than domestic drivers in most countries in the world. Few empirical findings have been reported, though. This paper contributes some evidence of the risk of foreign drivers in south-eastern Finland during 1992-1995. Most of the foreign drivers are Russian. Based on accident statistics collected by the police and origin-destination studies carried out on the Finnish-Russian border stations, accident rates were calculated for both Finnish and foreign drivers. The results show that accident rates of foreign drivers are higher than rates of domestic drivers. The winter season is especially risky for foreign drivers. It is argued that the traffic culture of different countries largely explain the differences rather than some specific, technical risk parameters. Some probable risk parameters can be identified in this study, such as a lack of knowledge concerning traffic rules, insufficient winter-time driving skills and winter-time equipment, as well as the general attitude towards traffic safety which is reflected in the driving behavior.
This study was designed to investigate the relative accident risk of different road weather conditions and combinations of conditions. The study applied a recently developed method which is based on the notion of Palm probability, originating in the theory of random point processes, which in this case corresponds to picking a random vehicle from the traffic. The method consists of calculating the Palm distribution of different conditions and comparing it with the distribution of the same conditions as seen by the accidents. The condition affects the accident risk statistically, when these two distributions differ. The study included all police reported single- and multi-vehicle accidents (N?=?10,646) occurring on 43 main roads in Finland during the years 2014-2016. A major contribution of this paper is the demonstration of the method on national scale by using estimated hourly traffic volumes on road segments instead of measured ones, which would have been available for few roads only. Accident risks are commonly examined in relation to traffic volume. This paper includes the speed of the traffic and thus, the paper examines accident risk in relation to the time spent on the road segment in certain conditions. The hour-level weather and road condition data per segment were obtained from nearby road weather stations. The relative accident risks were increased for poor road weather conditions; however, they were highest for icy rain and slippery and very slippery road conditions. When comparing the relative accident risk based on road type, the results showed that the risk in poor weather and road conditions was higher on motorways compared to two-lane and multiple-lane roads even though the overall risk was lower on motorways. Furthermore, the corresponding relative accident risks were generally higher for single-vehicle accidents compared to multi-vehicle accidents.