Objective underpinnings of self-reported sleep quality in middle-aged and older adults: The importance of N2 and wakefulness

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Publication Title

Biological Psychology






Study objectives: The measurable aspects of brain function (polysomnography, PSG) that are correlated with sleep satisfaction are poorly understood. Using recent developments in automated sleep scoring, which remove the within- and between-rater error associated with human scoring, we examine whether PSG measures are associated with sleep satisfaction. Design and setting: A single night of PSG data was compared to contemporaneously collected measures of sleep satisfaction with Random Forest regressions. Whole and partial night PSG data were scored using a novel machine learning algorithm. Participants: Community-dwelling adults (N = 3165) who participated in the Sleep Heart Health Study. Interventions: None. Measurements and results: Models explained 30% of sleep depth and 27% of sleep restfulness, with a similar top four predictors: minutes of N2 sleep, sleep efficiency, age, and minutes of wake after sleep onset (WASO). With increasing self-reported sleep quality, there was a progressive increase in N2 and decrease in WASO of similar magnitude, without systematic changes in N1, N3 or REM sleep. In comparing those with the best and worst self-reported sleep satisfaction, there was a range of approximately 30 min more N2, 30 min less WASO, an improvement of sleep efficiency of 7–8%, and an age span of 3–5 years. Examination of sleep most proximal to morning awakening revealed no greater explanatory power than the whole-night data set. Conclusions: Higher N2 and concomitant lower wake is associated with improved sleep satisfaction. Interventions that specifically target these may be suitable for improving the self-reported sleep experience.

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Funding Sponsor

National Heart, Lung, and Blood Institute


Adult, Human, Machine learning, Polysomnography, Sleep, Sleep quality