Sleepiness, near-misses and driving accidents among a representative population of French drivers.
Langue
EN
Article de revue
Ce document a été publié dans
Journal of Sleep Research. 2010-12-01, vol. 19, n° 4, p. 578-84
Résumé en anglais
Study objectives were to determine the prevalence of sleepy driving accidents and to explore the factors associated with near-miss driving accidents and actual driving accidents in France. An epidemiological survey based ...Lire la suite >
Study objectives were to determine the prevalence of sleepy driving accidents and to explore the factors associated with near-miss driving accidents and actual driving accidents in France. An epidemiological survey based on telephone interviews was conducted on a representative sample of French drivers. The questionnaire included sociodemographics, driving and sleep disorder items, and the Epworth sleepiness scale. Of 4774 drivers (response rate: 86%), 28% experienced at least one episode of severe sleepiness at the wheel (i.e. requiring to stop driving) in the previous year; 11% of drivers reported at least one near-miss accident in the previous year (46% sleep-related); 5.8% of drivers reported at least one accident, 5.2% of these being sleep related (an estimate of 90,000 sleep-related accidents per year in France). Sleepy driving accidents occurred more often in the city (53.8%), during short trips (84.6%) and during the day (84.6%). Using logistic regression, the best predictive factor for near-misses was the occurrence of at least one episode of severe sleepiness at the wheel in the past year [odds ratio (OR) 6.50, 95% confidence interval (CI), 5.20-8.12, P < 0.001]. The best predictive factors for accidents were being young (18-30 years; OR 2.13, 95% CI, 1.51-3.00, P < 0.001) and experiencing at least one episode of severe sleepiness at the wheel (OR 2.03, 95% CI, 1.57-2.64, P < 0.001). Sleepiness at the wheel is a risk factor as important as age for traffic accidents. Near-misses are highly correlated to sleepiness at the wheel and should be considered as strong warning signals for future accidents.< Réduire
Mots clés en anglais
Accidents
Traffic
Adolescent
Adult
Age Factors
Aged
Arousal
Automobile Driving
Confidence Intervals
Fatigue
Female
France
Humans
Logistic Models
Male
Middle Aged
Odds Ratio
Regression Analysis
Sex Factors
Young Adult
Unités de recherche