Gender Differences in Nighttime Sleep Patterns and Variability Across the Adult Lifespan: A Global-Scale Wearables Study

  • Sigga Svala Jonasdottir
  • , Kelton Minor
  • , Sune Lehmann*
  • *Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Previous research on sleep patterns across the lifespan have largely been limited to self-report measures and constrained to certain geographic regions. Using a global sleep dataset of in-situ observations from wearable activity trackers, we examine how sleep duration, timing, misalignment, and variability develop with age and vary by gender and BMI for non-shift workers. We analyze 11.14 million nights from 69,650 adult non-shift workers aged 19-67 from 47 countries. We use mixed effects models to examine age-related trends in naturalistic sleep patterns and assess gender and BMI differences in these trends while controlling for user and country-level variation. Our results confirm that sleep duration decreases, the prevalence of nighttime awakenings increases, while sleep onset and offset advance to become earlier with age. Although men tend to sleep less than women across the lifespan, nighttime awakenings are more prevalent for women, with the greatest disparity found from early to middle adulthood, a life stage associated with child-rearing. Sleep onset and duration variability are nearly fixed across the lifespan with higher values on weekends than weekdays. Sleep offset variability declines relatively rapidly through early adulthood until age 35-39, then plateaus on weekdays, but continues to decrease on weekends. The weekend-weekday contrast in sleep patterns changes as people age with small to negligible differences between genders. A massive dataset generated by pervasive consumer wearable devices confirms age-related changes in sleep and affirms that there are both persistent and life-stage dependent differences in sleep patterns between genders.
Original languageEnglish
Article numberzsaa169
JournalSleep
Volume44
Issue number2
Number of pages16
ISSN0161-8105
DOIs
Publication statusPublished - 2021

Keywords

  • Sleep
  • Big data
  • Aging
  • Gender
  • Sleep variability
  • Sleep misalignmen
  • Sleep timing and duration

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