Torbjörn Åkerstedt

Purpose: Sleep disturbances are common in individuals with psychiatric diseases and may emerge years before diagnosis. It remains unclear whether they reflect modifiable risk factors or early manifestations of psychiatric illness. We aimed to investigate how different sleep dimensions relate to the risk of subsequent psychiatric illness, and how sleep symptoms evolve before and after diagnosis. Methods: We analyzed data from 24,038 participants in the Swedish Longitudinal Occupational Survey of Health (2010–2018), linked to national health registers. Associations between baseline sleep characteristics and incident psychiatric diagnoses were estimated using Cox proportional hazards models. Symptom trajectories were modelled using non-linear mixed-effects models on a backward timescale centered at diagnosis. Results: A total of 716 participants (2.9%) were diagnosed with a psychiatric disorder during follow-up. There was a U-shaped association between sleep duration and incident psychiatric illness. All sleep-related symptoms were associated with increased risk, with the strongest association observed for mental fatigue (HR 2.09, 95% CI 1.77–2.48). Insufficient sleep and sleep-disordered breathing were more common among those who later developed psychiatric illness, with differences remaining relatively stable over time. In contrast, other sleep complaints, such as insomnia symptoms and fatigue, progressively worsened prior to diagnosis and improved thereafter, although levels remained elevated compared to unaffected individuals. Long sleep duration and delayed wake-up times were exceptions, showing continued worsening post-diagnosis. Conclusion: Gradually intensifying sleep disturbances may reflect emerging psychiatric vulnerability consistent with a prodromal phase. Where repeated monitoring is feasible, these symptoms could serve as early warning signs to guide preventive efforts.

It is not clear whether gender differences in self-reported sleep reflect polysomnographical differences. We here investigated gender differences in polysomnography (PSG) variables and their association with rated sleep quality for recorded sleep. The participants were 238 women and 238 men who were recorded for a night with PSG (home recordings), and provided sleep quality ratings for the recorded night. Analyses of variance showed that women reported significantly lower sleep quality than men, but it showed significantly better PSG sleep (fewer awakenings per hour, lower N1%, longer total sleep time, higher sleep efficiency, and more N3%, among others). However, men underestimated their objective number of awakenings and had a shorter objective time awake per objective awakening (6.4 ± .6 vs 8.2 ± .6 minutes for women, p < .05). Men with short awakenings (<7.8 min per awakening) had a high self-reported sleep quality, in contrast to men with long awakenings or women regardless of the duration of awakenings. When men with short awakenings were excluded, self-reported sleep quality no longer differed between genders. Gender differences in PSG variables increased with age. In addition, better self-reported sleep quality was associated with “better” PSG values for both genders. In conclusion, women reported poorer sleep quality than men but showed better objective sleep. It is suggested that men’s better self-reported sleep is associated with an inability to perceive/remember short awakenings. The findings open a new view of gender differences in sleep, and indicate a need for experimental studies on gender differences in the perception of awakenings, their duration, and rated sleep quality. Statement of Significance The lack of correspondence between gender differences in objective and self-reported sleep seems paradoxical. The present study suggests that the lack of correspondence may be, at least partly, due to men’s inability to perceive short awakenings. This may lead to a new understanding of gender differences in sleep and their importance. Ascertaining the reasons for the male difficulty in perceiving short awakenings should be an important next step.

Study Objectives: Insomnia disorder, affecting 10% of the population, poses a significant public health concern and is a risk-factor for many health issues. Cognitive behavioral therapy is first-choice treatment, but the key component—sleep restriction therapy—presents with side effects and adherence challenges. Sleep compression therapy, suggested as a potentially gentler alternative, has never been directly compared to sleep restriction therapy. Methods: Single-blind trial at the Internet Psychiatry Clinic in Stockholm, Sweden. Patients with insomnia disorder were randomized 1:1 to evaluate non-inferiority of sleep compression therapy to sleep restriction therapy in improving insomnia and to compare important clinical aspects. Primary outcome: self-reported Insomnia Severity Index (ISI), assessed pretreatment, weeks 1–5, and week 10. Non-inferiority analysis based on intent-to-treat analyses with multiple imputation and mixed effects models. Results: Adults with insomnia (n = 234; mean age 44.3 [SD = 13.7] years, 173 [73.4%] female) received treatment as a 10-week highly structured, therapist-guided online program, to strengthen experimental integrity and treatment fidelity. Both treatments improved insomnia severity with large effects. Sleep compression therapy failed to show non-inferiority with a conservative limit of 1.6 ISI-points (95% CI: −0.01, 1.70), gave statistically significantly smaller improvements (p = .006), and was associated with slower improvements despite better adherence and somewhat less side effects. Conclusions: This direct comparison and well-controlled trial provides empirically based support for clinicians to prioritize sleep restriction therapy over sleep compression therapy, while the latter can be a valid alternative when sleep restriction therapy cannot be used. Clinical Trial: CompRest—a Comparison Between Sleep Compression and Sleep Restriction for Treating Insomnia. URL: https://clinicaltrials.gov/study/NCT02743338?term=NCT02743338&rank=1 Registration: NCT02743338.

Increased waste clearance in the brain is thought to occur most readily during late-stage sleep (stage N3). Sleep deprivation disrupts time spent in deeper sleep stages, fragmenting the clearance process. Here, we have utilized the publicly available Stockholm Sleepy Brain Study to investigate whether various sleep-related measures are associated with changes in perivascular space (PVS) volume fraction following a late-night short-sleep experiment. Our sample consisted of 60 participants divided into old (65-75 years) and young (20-30 years) age groups. We found that partial sleep deprivation was not significantly associated with major PVS changes. In the centrum semiovale, we observed an interaction between percentage of total sleep time spent in N3 and sleep deprivation status on PVS volume fraction. In the basal ganglia, we saw an interaction between N2 (both percentage of total sleep time and absolute time in minutes) and sleep deprivation status. However, the significance of these findings did not survive multiple comparisons corrections. This work highlights the need for future longitudinal studies of PVS and sleep, allowing for quantification of within-subject morphological changes occurring in PVS due to patterns of poor sleep. Our findings here provide insight on the impacts that a single night of late-night short-sleep has on the perivascular waste clearance system. Statement of Significance: Sleep issues have been known to be associated with a variety of health risks. Recent research has shown the importance of sleep for brain clearance, with increases in brain clearance occurring during sleep. PVS seen on MRI are known to represent both influx and efflux pathways for the exchange of cerebrospinal fluid (CSF) and interstitial fluid (ISF) in the brain parenchyma, a key process underlying the waste clearance system. ¹ Numerous recent studies have found links between sleep disruption and PVS volume changes. However, no study to date has been able to examine within-subject changes in PVS resulting from experimental manipulation of sleep. Our study represents the first within-subject study looking at the effects of partial sleep deprivation on PVS volume fraction using an automated PVS segmentation technique.