0338 Composite Phase Deviation (CPD) As A Predictor Of Mood In College Students. (27th April 2018)

• Record Type: Journal Article
• Authors: Fischer, D; McHill, A; Sano, A; Picard, R W; Barger, L K; Czeisler, C A; Klerman, E B; Phillips, A J
• Is Part Of: Sleep. Volume 41(2018)Supplement 1
• Page Start: A129
• Page End: A129
• Publication Date: 2018-04-27
• 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/zsy061.337
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: We recently developed the Composite Phase Deviation (CPD), a metric that quantifies mistiming of sleep along two dimensions: (i) relative to an individual's habitual sleep timing, and (ii) relative to their sleep timing on the previous day. Given recent findings that sleep regularity can be predictive of mood, we examined whether CPD is also associated with mood in college students. Methods: Daily mood and actigraphy data were collected for ~30 days from 223 college students between 2013 and 2016. Participants rated their mood daily upon awakening on five visual scales (later scored 0–100): sleepy-alert, sad-happy, sluggish-energetic, sick-healthy, stressed-calm. Four different sleep parameters were computed after combining actigraphy and sleep-diaries: sleep duration, midsleep time, chronotype, and CPD. Chronotype was calculated as average midsleep time on weekends, corrected for sleep loss on weekdays. CPD quantifies the difference in midsleep timing between consecutive days and relative to chronotype, with higher values representing greater timing differences. Linear mixed models with random intercept for each participant were computed to predict daily mood as well as average mood over ~30 days. Results: A later daily midsleep time was associated with feeling more alert (unstandardized regression coefficient b=0.36), happier (b=0.31), and calmer (b=0.71) upon awakening, while a later chronotype was associated with feeling less alert (b=-2.31) and less energetic (b=-1.96) (all p<0.05). Sleep duration was the strongest predictor for daily mood upon awakening (longer sleep, better mood), but sleep duration was not associated with how students felt on average across the month of study. In contrast, CPD did not predict daily changes in mood but was the strongest predictor for average mood: students with higher CPD rated their mood as generally lower. Conclusion: Different dimensions of sleep were associated with differential effects on mood. While sleep duration was predictive of daily mood fluctuations, CPD was associated with an individual's average mood level. CPD may be more predictive of daily mood in a work context that imposes highly irregular sleep patterns, such as shift work. Support (If Any): R00HL119618, K24HL105664, R01HL114088, R01GM105018, R01HL128538, P01AG009975.