• Christopher Drake, Timothy Roehrs, Naomi Breslau, Eric Johnson, Catherine Jefferson, Holly Scofield, and Thomas Roth.
• Sleep Disorders and Research Center, Henry Ford Hospital, 2799 West Grand Blvd, CFP3, Detroit, MI 48202, USA. cdrake1@hfhs.org
• Sleep. 2010 Jun 1; 33 (6): 745-52.

Study ObjectivesThe purpose of this study was to determine the risk of DMV documented crashes as a function of physiological sleepiness in a population-based sample.Design24-hour laboratory assessment (nocturnal polysomnogram and daytime MSLT) and 10-year crash rate based on DMV obtained accident records.Participants618 individuals (mean age = 41.6 +/- 12.8; 48.5% male) were recruited from the general population of southeastern Michigan using random-digit dialing techniques.ResultsSubjects 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).InterventionsN/A.ConclusionsThese 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.

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