Nabi Hermann, Guéguen Alice, Chiron Mireille, Lafont Sylviane, Zins Marie, Lagarde Emmanuel
Institut National de la Santé et de la Recherche Médicale, U687-IFR69, Saint-Maurice, F-94415 France.
BMJ. 2006 Jul 8;333(7558):75. doi: 10.1136/bmj.38863.638194.AE. Epub 2006 Jun 23.
To examine the association between self assessed driving while sleepy and the risk of serious road traffic accidents (RTAs).
Prospective cohort study.
France.
13 299 of the 19 894 living members of the GAZEL cohort, workers and recent retirees of a French national utility company followed up since 1989.
Frequency of driving while sleepy in the previous 12 months, reported in 2001; rate ratios for serious RTAs in 2001-3, estimated by using generalised linear Poisson regression models with time dependent covariates.
The risk of serious RTAs increased proportionally with the frequency of self reported driving while sleepy. After adjustment for sociodemographic characteristics, driving behaviour variables, work conditions, retirement, medical conditions and treatments, depressive symptoms, and sleep disorders, the adjusted rate ratios of serious RTAs for participants who reported driving while sleepy in the previous 12 months "a few times" or "once a month or more often" were 1.5 (95% confidence interval 1.2 to 2.0) and 2.9 (1.3 to 6.3) respectively compared with those who reported not driving while sleepy over the same period. These associations were not explained by any reported sleep disorders.
Self assessed driving while sleepy was a powerful predictor of serious RTAs, suggesting that drivers' awareness of their sleepiness while driving is not sufficient to prevent them from having RTAs. Messages on prevention should therefore focus on convincing sleepy drivers to stop driving and sleep before resuming their journey.
研究自我评估的困倦驾驶与严重道路交通事故(RTA)风险之间的关联。
前瞻性队列研究。
法国。
GAZEL队列的19894名在世成员中的13299名,这些人是一家法国国家公用事业公司的员工和近期退休人员,自1989年起接受随访。
2001年报告的过去12个月内困倦驾驶的频率;2001 - 2003年严重RTA的发病率比,通过使用具有时间依存性协变量的广义线性泊松回归模型进行估计。
严重RTA的风险与自我报告的困倦驾驶频率成比例增加。在对社会人口学特征、驾驶行为变量、工作条件、退休情况、医疗状况和治疗、抑郁症状以及睡眠障碍进行调整后,与同期报告无困倦驾驶的参与者相比,报告在过去12个月内“几次”或“每月一次或更频繁”困倦驾驶的参与者严重RTA的调整发病率比分别为1.5(95%置信区间1.2至2.0)和2.9(1.3至6.3)。这些关联不能用任何报告的睡眠障碍来解释。
自我评估的困倦驾驶是严重RTA的有力预测因素,这表明驾驶员对自己驾驶时的困倦意识不足以防止他们发生RTA。因此,预防信息应侧重于说服困倦的驾驶员在继续旅程之前停车睡觉。