540 Age Trends in Sleep Across the Lifespan: Findings from the Pittsburgh Lifespan Sleep Databank

Introduction Sleep continuously changes over the human lifespan and it does so across multiple dimensions, including duration, timing, efficiency, and variability. Although studies focused on specific developmental periods have shown age-related changes in sleep, methodological differences make it difficult to synthesize information across studies to fully understand precisely when these sleep changes occur. Our goal was to use individual-level actigraphy and self-report sleep data from a single site to characterize age trends and sex differences in actigraphy and self-report sleep dimensions across the healthy human lifespan. To accomplish this goal, we developed the Pittsburgh Lifespan Sleep Databank (PLSD), a large aggregate databank of participants from sleep research studies conducted at the University of Pittsburgh. Methods In the present analysis, we included N=1,070 PLSD participants from 21 studies without a major psychiatric, sleep, or medical condition. We used Generalized Additive Models to examine flexible, potentially non-linear relationships between age and sleep dimensions (actigraphy and self-report duration, efficiency, and timing; actigraphy variability) from ages 10 to 87. We also examined whether these sleep characteristics differed by sex across the lifespan. Results The most dramatic age-related trends were observed in sleep timing. Actigraphy and self-report sleep onset time shifted later between ages 10–18 and then shifted earlier again during the 20s. Actigraphy and self-report wake-up time also shifted earlier during the mid-20s through late 30s. Self-report duration became shorter from approximately ages 10–20. Self-report sleep efficiency and actigraphy variability both decreased over the entire lifespan. Relative to males, females tended to have earlier self-report sleep onset, higher actigraphy sleep efficiency, and longer actigraphy duration. Conclusion By focusing on lifespan sleep rather than specific age segments of the samples, we can provide a unified assessment of age-related changes and sex differences from childhood through older adulthood. An understanding of age trends and sex differences in sleep in healthy individuals – and explicating the timing and nature of these difference – can be used to identify periods of sleep-related risk or resilience and guide intervention efforts. Support (if any) University of Pittsburgh Clinical and Translational Science Institute (UL1TR001857).