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

Biol Psychol. 2022 Apr:170:108290. doi: 10.1016/j.biopsycho.2022.108290. Epub 2022 Feb 19.


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.

Keywords: Adult; Human; Machine learning; Polysomnography; Sleep; Sleep quality.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Aged
  • Child, Preschool
  • Humans
  • Middle Aged
  • Polysomnography
  • Self Report
  • Sleep
  • Sleep Quality*
  • Wakefulness*