0019 Drowsy Driving in a Community Sample: Associations with Sleep Duration, Insomnia Severity, Daytime Sleepiness, and Fatigue. (25th May 2022)

• Record Type: Journal Article
• Authors: Hamze, Mohi; Kennedy, Kathryn; Hale, Lauren; Branas, Charles; Killgore, William; Wills, Chloe; Grandner, Michael
• Is Part Of: Sleep. Volume 45(2022)Supplement 1
• Page Start: A8
• Page End: A8
• Publication Date: 2022-05-25
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsac079.018
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: Drowsy driving is an important public health concern. Yet, real-world data on drowsy driving patterns remains relatively scarce. The present study aimed to investigate reports of drowsy driving in a general community sample and whether these are associated with daytime and nighttime sleep health risk factors. Methods: Data were obtained through the Sleep and Health Activity, Diet, Environment, and Socialization (SHADES) study, which recruited N=1, 007 working-age adults from the Philadelphia area. Drowsy driving was assessed with the item from the CDC BRFSS, "During the past 30 days, have you ever nodded off or fallen asleep, even just for a brief moment, while driving?" Responses were coded as "yes" or "no" (or "don't drive, " which was excluded). Sleep-related factors included sleep duration (NHANES item, assessed in hours), insomnia (Insomnia Severity Index [ISI]), sleepiness (Epworth Sleepiness Scale [ESS]), fatigue (Fatigue Severity Scale [FSS]), and sleep medication use (PSQI item). Covariates included age, sex, education, income, race/ethnicity, employment, body mass index, and stress (Perceived Stress Scale). Results: The sample consisted of N=738 adults, excluding those who did not drive in the past 30 days. After adjustment for covariates, each hour of sleep duration was associated with a 23% reduction in likelihood of drowsy driving (OR=0.77; 95%CI[0.66, 0.89]; p<0.0005). Likelihood of drowsy driving increased with each point on the ISI by 8% (OR=1.08; 95%CI[1.04, 1.13]; p<0.0005), with each point on the ESS by 19% (OR=1.19; 95%CI[1.13, 1.26]; p<0.0005), and with each point on the FSS by 4% (OR=1.04; 95%CI[1.02, 1.06]; p<0.0005). Sleep medication use was not associated with drowsy driving. In a post-hoc model that combined duration, insomnia, sleepiness, and fatigue, unique effects were seen for sleepiness (OR=1.17; 95%CI[1.10.1.23]; p<0.0005) and sleep duration (OR=0.82; 95%CI[0.70, 0.98]; p=0.026). Conclusion: Drowsy driving in a community sample is associated with less sleep duration and more insomnia, sleepiness, and fatigue. These effects may overlap, though daytime sleepiness emerged as the most robust risk factor. The combined model showed that sleep duration also contributed variance that was otherwise unexplained by the other factors. Drowsy driving prevention efforts should focus on sufficient sleep and daytime sleepiness as screening and prevention targets. Support (If Any):