Longitudinal Trajectories of Spectral Power During Sleep in Middle-Aged and Older Adults
Overview:
Textbook depictions of aging suggest a linear, almost deterministic, worsening of sleep architecture and sleep physiology in older adulthood. However, such conceptualizations of aging arise from group-averaged cross-sectional polysomnography data.
What was the approach to solving the problem?
We used a large-sample, longitudinal dataset to investigate individual trajectories in spectral power. We additionally tested the correspondence between time-dependent changes in NREM and REM spectral bands.
What NSRR data were used?
We used data from 2,202 middle-aged and older adults from the Sleep Heart Health Study. These participants completed two polysomnography sessions, approximately 5.23 years apart.
What were the results?
Cross-sectional analyses replicated that older adulthood is associated with shallower and more fragmented sleep. Likewise, group-averaged longitudinal data highlighted NREM delta power and NREM sigma power as showing the most decline (see Figure A below); the same spectral power bands during REM sleep, though, showed an increase across five years. Importantly, individual-level longitudinal analyses displayed severe heterogeneity across participants. There were so many participants who showed stable sleep over time, or even improving sleep physiology markers over time, that the average-level trends would be difficult to infer simply by visually inspecting the plots (see Figure B below for individual level trajectories of NREM delta power).
What were the conclusions and implications of this work?
One-size-fits-all “textbook” conceptualizations of sleep and aging may not fit any specific individual’s sleep trajectory. This heterogeneity was even observed for the strong group-level changes in NREM delta power and sigma (spindle) power, which are hypothesized to be markers of cognitive aging. Patterns of concordance and discordance across NREM and REM sleep across time might be explained by neural compensation and neural dedifferentiation processes, which are theorized to occur in the brain during aging. Understanding how neural compensation and/or dedifferentiation processes influence sleep-cognition interactions across adulthood would advance theoretical understanding of sleep and aging and may inform future targeted interventions.
Resources/multimedia
Link to Aging Brain publication
Link to Current Sleep Medicine Reports publication
Twitter: @BaylorSleep
Guest bloggers: Dr. Chenlu Gao & Dr. Michael K. Scullin, Baylor University
Paper Summary
Age-related changes in sleep appear to contribute to cognitive aging and dementia. However, most of the current understanding of sleep across the lifespan is based on cross-sectional evidence. Using data from the Sleep Heart Health Study, we investigated longitudinal changes in sleep micro-architecture, focusing on whether such age-related changes are experienced uniformly across individuals. Participants were 2,202 adults (ageBaseline = 62.40 ± 10.38, 55.36 % female, 87.92 % White) who completed home polysomnography assessment at two study visits, which were 5.23 years apart (range: 4–7 years). We analyzed NREM and REM spectral power density for each 0.5 Hz frequency bin, including slow oscillation (0.5–1 Hz), delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), sigma (12–15 Hz), and beta-1 (15–20 Hz) bands. Longitudinal comparisons showed a 5- year decline in NREM delta (p <.001) and NREM sigma power density (p <.001) as well as a 5-year increase in theta power density during NREM (p =.001) and power density for all frequency bands during REM sleep (ps < 0.05). In contrast to the notion that sleep declines linearly with advancing age, longitudinal trajectories varied considerably across individuals. Within individuals, the 5-year changes in NREM and REM power density were strongly correlated (slow oscillation: r = 0.46; delta: r = 0.67; theta r = 0.78; alpha r = 0.66; sigma: r = 0.71; beta-1: r = 0.73; ps < 0.001). The convergence in the longitudinal trajectories of NREM and REM activity may reflect age-related neural de-differentiation and/or compensation processes. Future research should investigate the neurocognitive implications of longitudinal changes in sleep micro-architecture and test whether interventions for improving key sleep micro-architecture features (such as NREM delta and sigma activity) also benefit cognition over time.