Sleep Disorders and Research Center, Henry Ford Hospital, 2799 West Grand Blvd, CFP3, Detroit, MI 48202, USA.
Sleep. 2010 Jun;33(6):745-52. doi: 10.1093/sleep/33.6.745.
The purpose of this study was to determine the risk of DMV documented crashes as a function of physiological sleepiness in a population-based sample.
24-hour laboratory assessment (nocturnal polysomnogram and daytime MSLT) and 10-year crash rate based on DMV obtained accident records.
618 individuals (mean age = 41.6 +/- 12.8; 48.5% male) were recruited from the general population of southeastern Michigan using random-digit dialing techniques.
Subjects were divided into 3 groups based on their average MSLT latency (in minutes) as follows: excessively sleepy, 0.0 to < or = 5.0 (n = 69); moderately sleepy, 5.0 to < or = 10.0 (n = 204); and alert, > 10 (n = 345). Main outcome measures were DMV data on accidents from 1995-2005. Rates for all accidents in the 3 MSLT groups were: excessively sleepy = 59.4%, moderately sleepy = 52.5%, alert = 47.3%. Excessively sleepy subjects were at significantly greater risk of an accident over the 10-year period compared to alert subjects. A similar relation was observed when we limited the database to those accident victims with severe injury (excessively sleepy = 4.3%, moderately sleepy = 0.5%, alert = 0.6%; P = 0.028). When the victim was the only occupant of the car, subjects in the lowest MSLT group (highest sleepiness) had the greatest crash rate compared with alert individuals (excessively sleepy = 52.2%, moderately sleepy = 42.2%, alert = 37.4%; P = 0.022).
N/A.
These data demonstrate that the MSLT, a physiological measure of sleepiness, is predictive of an increased risk of DMV documented automotive crashes in the general population.
本研究旨在确定在基于人群的样本中,DMV 记录的撞车事故风险与生理困倦的关系。
24 小时实验室评估(夜间多导睡眠图和白天 MSLT)和基于 DMV 获取的事故记录的 10 年撞车率。
采用随机数字拨号技术,从密歇根州东南部的一般人群中招募了 618 名参与者(平均年龄=41.6±12.8;48.5%为男性)。
根据平均 MSLT 潜伏期(分钟),将受试者分为 3 组:极度困倦,0.0 至 <或= 5.0(n=69);中度困倦,5.0 至 <或= 10.0(n=204);和警觉,> 10(n=345)。主要观察指标为 1995-2005 年 DMV 事故数据。3 个 MSLT 组的所有事故发生率为:极度困倦=59.4%,中度困倦=52.5%,警觉=47.3%。在 10 年期间,极度困倦的受试者发生事故的风险明显高于警觉的受试者。当我们将数据库限制为那些受重伤的事故受害者时,观察到了类似的关系(极度困倦=4.3%,中度困倦=0.5%,警觉=0.6%;P=0.028)。当受害者是车内唯一的乘客时,MSLT 最低组(最困倦)的受试者与警觉的个体相比,撞车率最高(极度困倦=52.2%,中度困倦=42.2%,警觉=37.4%;P=0.022)。
无。
这些数据表明,MSLT 作为一种生理困倦测量方法,可以预测一般人群中 DMV 记录的汽车撞车事故风险增加。