0607 Prevalence and Correlates of Sleep Disorders Among Users of a Consumer Sleep Technology

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