0607 Prevalence and Correlates of Sleep Disorders Among Users of a Consumer Sleep Technology. (25th May 2022)

• Record Type: Journal Article
• Authors: Gahan, Luke; Gottlieb, Elie; Aman, Aman; Watson, Nathaniel; Raymann, Roy
• Is Part Of: Sleep. Volume 45(2022)Supplement 1
• Page Start: A266
• Page End: A267
• 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/zsac079.604
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: Sleep disorders constitute a major public health burden yet remain widely undiagnosed and untreated. The prevalence of diagnosed sleep disorders and associations with objectively measured sleep-wake dysfunction vary widely across populations. Here, we examined the self-reported prevalence and objective sleep architectural correlates of four sleep disorders in a large sample of individuals using a consumer sleep technology. Methods: Data from 33, 429 users (mean age: 44.6, 55.1% female) across 1, 842, 282 nights were included in the analysis from the PSG-validated SleepScore Mobile Application, which uses a non-contact, sonar-based method to objectively capture sleep-related metrics, and questionnaires to capture self-reported data. Subjective sleep disorder information was ascertained by asking users, "Which of the following sleep disorders has a healthcare professional diagnosed you with?" Linear regression was used for analysis, while age and gender were used as confounding variables, with the cohort reporting "None of the above" were used reference group for research purposes. Results: The prevalence of reported disorders were "None of the above" (n=23, 732, 71.0%), sleep apnea/SDB (n=5, 309, 15.9%), insomnia (n=3, 968, 11.9%), RLS/PLM (n=2, 295, 6.87%), or narcolepsy (n=266, 0.8%). Narcolepsy was associated with the greatest reduction in TST (ß=-23.6 mins, SE=3.475, p<0.001) while insomnia was associated with smallest (ß=-5.7mins, SE=0.979, p<0.001). Narcolepsy was associated with the greatest increase in WASO (ß=7.0 mins, SE=1.815, p<0.001) while insomnia was associated with smallest (ß=2.2 mins, SE=0.511, p<0.001). RLS/PLM was associated with the greatest increase in SOL (ß=3.9mins, SE=0.302, p<0.001) while sleep apnea/SDB was associated with the smallest (ß=2.171 mins, SE=0.22, p<0.001). Narcolepsy was associated with the greatest decrease in SE (ß=-3.05%, SE=0.5, p<0.001) while insomnia was associated with smallest (ß=-1.42%, SE=0.1, p<0.001). Conclusion: Self-reported sleep disorders were associated with objectively poor sleep in a big data consumer sleep technology analysis. These findings suggest consumer sleep technologies may have value in screening for sleep disorders in the general population and may motivate these individuals to seek care in clinical sleep medicine settings. Support (If Any):