Sleep Medicine

Major international sporting events frequently impose exogenous demands that challenge adult circadian rhythms, often leading to the misalignment of sleep-wake cycles and social schedules. This cross-sectional study investigated the impact of the FIFA 2022 World Cup on adult sleep patterns to assess the prevalence and determinants of tournament-associated circadian disruption. Through an online survey, we captured data on sleep duration, timing, and subjective quality from a diverse adult population using Pittsburgh Sleep Quality Index (PSQI) score. The results indicate that 81.3% had high problematic sleep according to PSQI scores, while only 9% perceived that their sleep pattern was impacted by watching matches during the tournament. While 83.7% of the participants had low or mild anxiety according to GAD-7 scores, we found that GAD-7 scores correlated significantly with PSQI scores. Married participants had significantly lower PSQI scores (RR 0.856, p = .005), while those who reported that their sleep hours had changed during the tournament had significantly higher PSQI scores (1.180, P-value <0.001). Males reported a significantly high impact of the tournament on their sleep (OR 2.622, P-value <0.001). In conclusion, our data demonstrate a discrepancy between self-perception of sleep quality and self-rated assessment by PSQI scores, as well as the substantial impact of major international sporting events on adult sleep hygiene. The results provide data-driven insights helpful in evaluating potential circadian risks and informing public health strategies for major sporting events such as the FIFA world cup.

Chronic partial and acute total sleep loss have a distinct impact on sleep architecture. Namely, acute sleep deprivation primarily leads to a strong rebound of slow wave sleep, while chronic sleep restriction results in an increased propensity of REM sleep. The aim of this work was to examine whether these different effects would translate into quantifiable changes in sleep state boundaries and dynamics using a model-based method. Besides conventional sleep stage scoring, we applied an EEG model (state space approach) for dynamic analysis of nocturnal EEG recordings in 14 healthy subjects under experimental chronic sleep restriction (last of 7 nights with 5 hours of time in bed) and after acute sleep deprivation (sleep following 40 hours of wakefulness), in comparison to baseline sleep. Subjects under chronic sleep restriction revealed increased similarities in the frequency composition of REM sleep and wakefulness and thus, a decreased differentiation of state boundaries between the two behavioral states. Contrarily, acute sleep deprivation affected the spectral composition of NREM sleep. Only acute sleep deprivation resulted in more stable slow wave sleep. Our explorative study confirmed that the distinct effects of increased REM sleep and slow wave sleep propensity following acute total and chronic partial sleep loss are reflected in differential changes of behavioral state boundaries and sleep dynamics. This suggests that these sleep structure characteristics are state dependent, which may allow using such measures in the future to track treatment effects in clinical populations characterized by sleep behavioral state dysregulation.

Excessive daytime sleepiness (EDS) is a common but inconsistently predicted symptom of obstructive sleep apnea (OSA). OSA is typically diagnosed with polysomnography (PSG), and the current standard for severity assessment is the apnea-hypopnea index (AHI). AHI has many limitations, including its inability to explain physiological mechanisms or reflect variability in patient symptoms, such as EDS. This retrospective study aims to find physiological and demographic parameters that better predict EDS in patients with OSA and to evaluate whether these parameters outperform AHI using PSG data from the Mount Sinai Integrative Sleep Center. Clinical variables used to predict EDS included arousal index (AI), average oxygen desaturation during sleep, average heart rate during sleep, and AHI, along with demographic variables including age, sex, and BMI. Hypothesis tests, logistic regression models, and decision tree classifier models were performed on the data to discriminate sleepy from nonsleepy patients as determined by an Epworth Sleepiness Scale (ESS) score [&ge;] 10. AI and oxygen desaturation were found to be the most predictive physiological variables, and sex and BMI were found to be the most predictive demographic variables. The final decision tree model with these four variables outperformed the AHI in predicting EDS. These findings suggest that daytime sleepiness in OSA can be better explained by measures of apnea burden, oxygenation impairment, and patient demographics than by AHI alone, although these remain only modestly predictive. Future studies should focus on investigating more comprehensive physiological markers, multi-night sleep data, and more objective assessments of sleepiness.

Study Objectives Co morbid insomnia and sleep apnea (COMISA) is challenging clinically and difficult to treat. Our goal was to assess how much COMISA is the mere addition of two phenotypes or display features indicative of genuine statistical interactions. Methods A total of 152,487 patients from 240 sleep centers across 30 US states were included. Insomnia was defined as difficulty initiating/maintaining sleep with daytime fatigue/sleepiness occurring "often"/"always". OSA was defined as having an Apnea Hypopnea Index (AHI) more than 15 events/h. Modified Poisson regression was conducted to evaluate multiplicative interactions between insomnia and OSA on common comorbidities and sleep symptoms. Additive interactions were also examined. Linear regression models were used to evaluate additive interactions for PSG parameters. The false discovery rate was controlled using the Benjamini Hochberg procedure. Results After adjustment for confounders, insomnia and OSA demonstrated positive interactions for depression, chronic muscular pain, headache, subjective excessive daytime sleepiness (EDS), naps, and pre-sleep anxious and muscular tension (adjusted p < 0.05). Furthermore, insomnia and OSA demonstrated positive interactions for parameters related to respiratory disturbance, including AHI, oxygen desaturation index (ODI), respiratory disturbance index (RDI), total arousal index (AI) and respiratory AI, and negative interactions for minimum oxygen saturation and percentage of rapid eye movement stage (REM%) (adjusted p < 0.05). Furthermore, the adverse effects of insomnia and OSA on AHI, ODI, RDI and REM% were substantially amplified in males. Conclusions Our findings demonstrate that insomnia and OSA do not merely coexist but genuinely interact synergistically to amplify selected adverse clinical outcomes.

Importance Sleep-disordered breathing (SDB) is common in childhood and is associated with attentional and behavioral impairments despite largely preserved sleep macrostructure and minimal abnormalities in conventional electroencephalographic measures. This discrepancy has contributed to the perception that sleep is relatively preserved in pediatric SDB and has limited understanding of the physiological mechanisms underlying morbidity. Objective To determine whether pediatric SDB is associated with disruption of the regional organization and homeostatic dynamics of slow-wave activity (SWA), a key physiological marker of sleep-dependent neural recovery and development. Design, Setting, and Participants Cross-sectional study of 62 children aged 4 to 12 years who underwent overnight polysomnography with high-density electroencephalography in a laboratory setting. Participants were recruited from clinical referrals and the community, spanning the full spectrum of SDB severity. Exposures SDB severity indexed by hypopnea index (HI), apnea-hypopnea index (AHI), and obstructive apnea index (OAI). Main Outcomes and Measures Regional electroencephalogram-derived SWA (0.5 to 4 Hz) topography and exponential decay parameters derived from frontal and posterior cortical regions. The frontal-to-posterior decay-rate ratio was evaluated as a summary measure of regional sleep homeostasis. Results In children with lower hypopnea index, SWA demonstrated the expected developmental pattern, with posterior predominance in younger children and a progressive shift toward a more balanced anterior-posterior distribution with age. Increasing HI was associated with attenuation or reversal of this spatial organization. Global SWA showed no meaningful association with SDB severity. In contrast, regional frontal and posterior decay parameters were strongly associated with HI (adjusted R2 = 0.53; p < 1e-6) but not OAI (adjusted R2 = 0.05; p = .95). The frontal-to-posterior decay-rate ratio showed the strongest association with HI {beta} = 4.15; 95% CI, 3.17-5.13; p < 1e-10; adjusted R2 = 0.55. Conclusions and Relevance Pediatric SDB was associated with regional disruption of slow-wave sleep homeostasis rather than global loss of deep sleep. These alterations affected both the spatial organization and temporal dynamics of SWA during a period of active cortical maturation and were not captured by conventional sleep metrics. Regional SWA dynamics may provide a developmentally sensitive marker of physiological disease burden in children with SDB.

Background: Sleep disruption is prevalent in people with neurodevelopmental disorders such as autism but is not clear whether it occurs as an endophenotype or secondary to other behaviours. The ABCD Study is a population-based longitudinal study that monitors the health, demography and lifestyle of over 11,000 children in the US. In this study we leverage these data to investigate whether traits consistent with autism (social responsiveness) are associated with sleep disruption independent of lifestyle and other behavioural measures. Methods: Autistic traits were assessed using the Social Responsiveness Scale at age 11, and sleep disruption and behavioural outcomes were assessed at ages 11 and 13 years using the Sleep Disturbance Scale, and the Child Behaviour Check List, respectively. Demographic, health and lifestyle-related variables were assessed by caregiver questionnaires. Regression models were applied to investigate associations between autistic traits and sleep outcomes. Results: There was a significant cross-sectional association between sleep disturbance and SRS at age 11 years old that was independent of sex, ethnicity, socioeconomic position, physical activity, sedentary behaviour and anxiety/depression ({beta} = 0.12, 95% CI (0.07, 0.17); p < 0.001), that persisted at age 13, and that was modulated by chronotype, with evening types showing a stronger association. Discussion: Social responsiveness assessed in early adolescence (age 11) were associated with sleep disruption independent of multiple confounding factors and were prospectively associated with sleep disruption at age 13 years. These findings contribute to the evidence that disruption of sleep and circadian timing may have a primary role in the neurobiological mechanisms that mediate autistic traits.

Background and Objectives: Area-based hypoxic burden, termed as hypoxic dip area (HDA) has been studied as a novel obstructive sleep apnea (OSA) metric that may better characterize intermittent hypoxemia in OSA and thereby better predict outcomes. However, to be of use in routine clinical care, a physiological normative value is necessary. Here we attempt to use several large cohorts to establish a percentile-based threshold that can classify individuals with normal vs. abnormal physiological profiles. Methods: Data from 10 cohorts (EPISONO, FINS, Dayfun, MrOS, MESA, SHHS, APPLES, WSC, CFS, and AIRS [Mount Sinai Clinical Cohort]; n=14,031 subjects) were included. HDA was defined as the area bounded by SpO2 nadirs ([&ge;]2% desaturation) flanking left/right peaks. The 97.5th percentile of HDA among asymptomatic subjects (n=136) from EPISONO, FINS, and DAYFUN (aged 20-52 years; 46 [33.8%] male) was used to define normal and elevated HDA levels. Physiological features, clinical comorbidities, and incident cardiovascular disease (CVD) events and mortality were compared between normal/elevated HDA groups. Sensitivity analyses were conducted using age-, sex-, and BMI-adjusted threshold derived from multivariable regression model. Results: The 97.5% percentile cutoff of HDA was 8.6%min/h, classifying 4,500 individuals as normal HDA and 9,531 as elevated HDA. Individuals with elevated HDA ([&ge;]8.6%min/h) demonstrated greater nocturnal hypoxemia (lower baseline SpO2, higher T90, T85, T80 and oxygen desaturation index), higher AHI (apnea-hypopnea index) and arousal index, and greater daytime sleepiness as well as a higher prevalence of lifetime CVD and hypertension across cohorts. Elevated HDA was related with a higher prevalence of incident CVD events and mortality in unadjusted analyses, although these associations were attenuated after adjustment for confounding factors. Results were similar using alternative thresholds derived from multivariable regression analyses. Conclusions: A physiologically derived cutoff of 8.6% min/h for HDA effectively distinguishes physiological profiles across respiratory, arousal, and oxygenation domains and generalizes across multiple cohorts. Those with elevated HDA had a higher prevalence of incident CVD outcomes, although observed relationships were attenuated after further adjustment. Our findings provide a physiologically interpretable threshold for HDA that can be readily used in clinical use.

This study investigated bidirectional associations between maternal sleep and depressive symptoms from preconception to postpartum, and whether infant sleep mediated or moderated these associations. We used data from the Generation R Next Study (N=2,294). Maternal sleep (specifically general sleep disturbance, latency, quality, duration, and midpoint) and depressive symptoms were prospectively assessed at five timepoints from preconception to 12-month postpartum. Sleep was self-assessed with the General Sleep Disturbance Scale and Munich Chronotype Questionnaire; depressive symptoms with the Adult Self Report depression/anxiety subscale and Edinburgh Postnatal Depression Scale. Infant sleep (specifically night awakenings, nocturnal sleep duration, and latency) was parent-reported at 1-month postpartum using the Brief Infant Sleep Questionnaire. Bidirectional associations were examined using Autoregressive Latent Trajectory Models with Structured Residuals. The role of infant sleep was examined using mediation and moderation analyses. We found that maternal sleep and depressive symptoms were both stable over time. For sleep quality and disturbance, bidirectional associations suggested slightly stronger effects from depression to sleep (sleep quality:{beta}depression[-&gt;]sleep quality=0.11, 95%CI:0.07 - 0.14; general sleep disturbance:{beta}depression[-&gt;]sleep disturbance=0.14, 95%CI:0.10 - 0.18) than from sleep to depression ({beta}sleep quality/disturbance[-&gt;]depression=0.07 for both, 95%CIs:0.03 - 0.11). For latency, effects were comparable in both directions ({beta}depression[-&gt;]sleep latency=0.06, 95%CI:0.03 - 0.09; {beta}sleep latency[-&gt;]depression=0.05, 95%CI:0.01 - 0.09). The association between depressive symptoms and sleep latency was both mediated (9.7%) and moderated (p<0.05) by infant sleep latency. In conclusion, general maternal sleep disturbance, sleep quality, and sleep latency showed bidirectional associations with depressive symptoms from preconception/early pregnancy onwards. Infant sleep latency may represent a potential modifiable factor within this cycle.

Sleep health reflects interacting demographic, clinical, micro- and macroarchitectural, and neurophysiological factors that may not be captured by single metrics or diagnostic categories. We applied hierarchical clustering to longitudinal Sleep Heart Health Study data from 1,468 adults with complete polysomnographic, demographic/clinical, and pre-sleep electroencephalographic data at two visits separated by 5.19 {+/-} 0.27 years. Forty nonredundant features selected from candidate demographic/clinical, sleep-stage, and pre-sleep spectral measures were clustered independently at each visit. Four reproducible sleep-health phenotypes emerged: a group with preserved deep sleep and favorable mental-health ratings; a large light-sleep group with low N3 and high N1; an older, physically unhealthy group with shorter total and rapid-eye-movement sleep; and a younger, physically healthy group with longer total and rapid-eye-movement sleep. The same population-level structure was evident at both visits, although only 37.7% of participants retained the same cluster assignment, with transitions most directed toward the light-sleep phenotype. An independent analysis of slow-wave morphology, excluded from cluster construction, differentiated all four phenotypes after false-discovery-rate correction. Groups with preserved or healthier sleep showed more numerous, higher-amplitude, steeper, and shorter slow waves, whereas the light-sleep and physically unhealthy groups showed weaker and more prolonged slow waves. Pre-sleep spectral features did not differ significantly across clusters after correction. These findings identify reproducible but individually dynamic sleep-health phenotypes and demonstrate that macro-architectural cluster structure is reflected in independent measures of NREM sleep microarchitecture.

Objectives. To test whether one week of self-administered morning bright light therapy (BLT) improves sleep, daytime sleepiness and alertness, mood, and objective cognition in healthy university students. Methods. Thirty-three healthy students completed a two-week randomized within-subject crossover trial comparing one week of morning BLT (30 min of 10,000 lx; melanopic equivalent daylight illuminance of approximately 8,989 lx) with one week of usual-light control in counterbalanced order, with no washout. Sleep was assessed with wrist-worn Fitbit sleep tracking and daily diaries; daytime sleepiness (Karolinska and Stanford Sleepiness Scales), positive and negative affect (PANAS), mood (POMS), and a cognitive battery (Stroop, Flanker, Corsi, verbal span) were also assessed, alongside post-trial semi-structured interviews. Outcomes were analyzed with linear mixed-effects models, with Holm correction across five primary outcomes. Results. BLT reduced daytime sleepiness in a time-of-day-specific manner (condition x time-of-day interaction; largest reduction at 12:00, dz = -0.58, with a smaller but still significant reduction at 15:00), reduced night-to-night variability in sleep duration (dz = -0.52), increased Fitbit sleep efficiency (dz = 0.81), and increased PANAS positive affect (dz = 0.41). Objective cognition was unchanged across all measures. Interviews indicated that participants experienced BLT primarily as a sleep and alertness intervention, with minor tolerability issues. Conclusions. Brief morning BLT improved alertness, sleep regularity and efficiency, and positive affect, but not objective cognition, in healthy students, supporting morning light as a low-burden strategy for daytime functioning while cautioning against overstating cognitive benefits.

Study Objectives To develop and initially validate the Circadian Disruption Index (CDI), a self-report measure of circadian disruption, and obtain preliminary evidence of its responsiveness to circadian health education. Methods In Study 1, 244 participants completed a 22-item CDI version and external measures. The sample was randomly divided for exploratory and confirmatory factor analyses. Internal consistency, external associations, and discrimination of poor sleep quality were examined. In Study 2, 72 postgraduate students completed the CDI before and 1 week after a 16-hour circadian health education program in an uncontrolled pre-post design. Results Analyses yielded a 15-item, three-factor structure comprising rhythm stability and light exposure, behavioral habits and diet, and sleep quality and subjective complaints. Total-score internal consistency was acceptable (Cronbach's = 0.871). Confirmatory factor analysis showed a comparative fit index of 0.902 and a root mean square error of approximation of 0.072, although the Tucker-Lewis index was 0.882. CDI scores correlated with sleep quality, chronotype, corrected midsleep on free days, depression, and anxiety, but not social jetlag. The area under the curve for poor sleep quality was 0.807 (95% confidence interval, 0.753-0.862), with an exploratory cutoff of [&le;] 23. In Study 2, CDI scores decreased from 22.26 to 19.88 (p = 0.002; Cohen's dz = 0.36). Conclusions The CDI demonstrated satisfactory internal consistency, a meaningful multidimensional structure, and responsiveness to short-term changes following circadian health education, supporting its potential utility for assessing circadian disruption and monitoring circadian-related behavioral changes.

Study Objectives: To evaluate a framework using wearable data to personalize the definition of short sleep, comparing its temporal and functional characteristics against a fixed threshold. Methods: 462 healthy adults wore sleep trackers and provided daily ecological momentary assessments for a year. Short sleep was defined using either a fixed threshold of <6 h/night (fSS) or personalized thresholds anchored to individual sleep-duration distributions (pSS). Temporal patterns of consecutive short-sleep nights were characterized. Linear mixed-effects models examined associations between accumulating short-sleep nights and short- and long-term markers. Sleep patterns across six other countries were also evaluated. Results: pSS and fSS produced similar average thresholds and overall prevalence of short-sleep nights. However, pSS showed larger effect estimates for short-term outcomes, including alertness, sleep satisfaction, stress, sleep heart rate, HRV, and sedentariness. Effects increased with successive short-sleep nights. Proportion of pSS showed stronger association with blood pressure and arterial stiffness. Isolated short nights were common, whereas longer runs were uncommon and typically followed by incomplete recovery sleep. Personalized thresholds distinguished stable short sleepers with few pSS nights from individuals experiencing recurrent sleep shortfall and highlighted vulnerability among those achieving recommended sleep duration but with high variability. Despite marked cross-country differences in sleep habits, the distribution of short-sleep runs, and termination patterns were remarkably similar. Conclusion: Anchoring short sleep to individual habitual sleep distribution captures relative sleep shortfall beyond absolute duration, better characterizing the functional impact of short sleep. Preventive strategies may benefit from limiting pSS accumulation together with addressing sporadic inadequate sleep.

Alexithymia is the inability to identify and describe emotions, associated with an increased risk of somatic and psychiatric disease. Alexithymia is also characterized by reduced subjective sleep quality. However, it is not well-known if this reduction in sleep quality reflects physiological changes in sleep, a specific alteration in perceived sleep quality not captured by objective metrics, or a non-specific spillover of the negative affective style which characterizes alexithymia. In BSETS, a large (N=228) EEG study of naturalistic sleep, we found that alexithymia symptoms are associated with worse habitual (AIS) and current (GSQS) subjective sleep quality ({beta}AIS=0.207, pAIS=0.002, {beta}GSQS=0.203, pGSQS=0.002). However, we observed no significant association between alexithymia and EEG-based sleep efficiency ({beta}=- 0.017, p=0.791). The association with subjective sleep quality was almost completely attenuated when controlling for either depressive symptoms (PHQ-9, {beta}AIS=0.001, pAIS=0.982, {beta}GSQS=0.044, pGSQS=0.486) or trait neuroticism (ZKPQ, BFI-44, {beta}AIS=0.057, pAIS=0.442, {beta}GSQS=0.048, pGSQS=0.514). A possible exception is the Difficulty Identifying Feelings alexithymia dimension, reflecting complaints about the labeling of interoceptive experiences, which was associated with lower subjective sleep quality even after covariate control. This pattern of findings suggests that alexithymia is characterized only by alterations of subjective sleep quality, and even these reflect a non-specific increase in negative affect which influences self-reports of sleep quality, rather than a specific reduction in perceived sleep quality itself.

Abstract Importance: Socially vulnerable patients have a high burden of obstructive sleep apnea, but the stage of the referral pathway at which access barriers arise is uncertain. Objective: To determine whether area-level social deprivation was associated with appointment scheduling, wait time, cancellations, or no-shows among adults referred for specialist obstructive sleep apnea care. Design: This was a cross-sectional study evaluating patients referred from December 1, 2016 through November 30, 2019. Data were analyzed from January 30, 2026 to May 16, 2026. Setting: Foothills Medical Centre Sleep Centre in Calgary, Canada. Participants: Adults referred to a tertiary academic sleep centre in Calgary, Alberta, Canada. Eligible patients had valid provincial health insurance and either a scheduled clinic appointment or home sleep apnea test data available. Exposures: Quintiles of the four Canadian Index of Multiple Deprivation domains: residential instability, economic dependency, ethnocultural composition, and situational vulnerability. Main Outcomes and Measures: The primary outcome was receipt of a scheduled specialist appointment. Secondary outcomes were time from referral to the first attended appointment and number of appointment cancellations or no-shows. Results: Among 3111 patients (mean [SD] age, 53.7 [14.3] years; 40.7% female), 1766 (56.7%) were scheduled and 1647 (52.9%) attended an appointment. Each quintile increase in situational vulnerability was associated with lower odds of scheduling (adjusted odds ratio [95% confidence interval] 0.86 [0.81-0.92]), whereas each quintile increase in ethnocultural composition was associated with higher odds (adjusted odds ratio [95% confidence interval] 1.32 [1.22-1.43]). Residential instability and economic dependency were not associated with scheduling. No deprivation domain was associated with time to the first attended appointment, cancellations, or no-shows. Conclusions and Relevance: In this cohort, area-level deprivation was associated with whether patients were scheduled for an appointment but not with wait time or missed visits after scheduling. These findings suggest that equity interventions should focus on completion of referral and scheduling processes.

Evidence suggests that insomnia disorder is associated with pathophysiological alterations that may contribute to long-term physical, mental and inflammatory-related health risks. Cognitive behavioral therapy for insomnia (CBTi) is the first-line treatment for insomnia disorder, yet its effects on physiological outcomes remain unclear. This randomized-controlled trial examined the effects of CBTi on cardiovascular and immunological biomarkers. Sixty-two participants with insomnia disorder were randomized to group-CBTi (N = 33, 75.8% female, Mage = 48.8 + 17.1 years) or Waitlist (WL) control (N = 29, 75.9% female, Mage = 52.2 + 15.6 years). Cardiovascular parameters included systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), and nocturnal heart rate variability (HRV). Inflammatory markers from blood samples included C-reactive protein (CRP), tumor necrosis factor-alpha (TNF- ), interleukin-6 (IL-6) and brain-derived neurotrophic factor (BDNF). All outcomes were assessed at baseline (T1), post-treatment assessment (T2, following completion of CBTi or WL period), and 6-months for the WL group (T3, after CBTi for the WL participants). No significant Group-by-time effects were observed for SBP, DBP, HR, HRV and any inflammatory markers (ps > .05) from T1 to T2. When pooling treatment effects following CBTi exposure across both groups (T1 to T2 in CBTi group and T1 to T3 in WL group), no significant biomarker changes were observed. Overall, results indicate that CBTi did not produce detectable changes in cardiovascular or inflammatory markers among healthy individuals with insomnia disorder. These findings suggest physiological responses to CBTi are complex and may reflect dynamic and context-dependent processes (https://www.isrctn.com/ISRCTN13983243).

Background and Objective: Diabetes mellitus (DM) causes autonomic neuropathy, which may alter nocturnal respiratory rate (NRR). To test the association between DM and NRR, we analyzed elective polysomnograms of four large observational cohorts. Research Design and Methods: We performed cross-sectional analysis of over 25,000 individuals with polysomnograms (PSGs) from the Sleep Heart Health Study (SHHS), Hispanic Community Health Study/Study of Latinos (HCHS/SOL), Osteoporotic Fractures in Men Study (MrOS), and Wisconsin Sleep Cohort (WSC). Patient-level NRRs were derived from inductance plethysmography waveforms. DM status was determined by self-report, physician diagnosis, medication use, or laboratory values, depending on the cohort. We related DM and NRR (continuous and dichotomized) using logistic regression models and adjusted for potential confounders. Cohort-specific results were combined using random-effects meta-analysis. Results: Meta-analysis of unadjusted models showed a pooled odds ratio (OR) of 1.10 (95% CI:1.04-1.17) for each breath-per-minute (brpm) increase in NRR. This association remained significant after multivariable adjustment (OR:1.06, 95% CI:1.02-1.11). Dichotomized analyses similarly showed higher odds of DM across dichotomization thresholds ranging from 15 to 21 brpm. At a threshold of 18 brpm, the unadjusted pooled OR was 1.77 (95% CI:1.23-2.55, P=0.0022), and the adjusted OR was 1.49 (95% CI:1.10-2.02, P=0.0098). Conclusions: Clinically stable outpatients with elevated NRR have an increased prevalence of DM. Additional studies are needed to investigate whether the mechanism is autonomic neuropathy and whether monitoring NRR can detect early complications of DM.

Study Objectives. Sleep characteristics are often estimated using self-reports, which may differ from objective measurements, a phenomenon known as sleep discrepancy. However, the factors associated with the degree of sleep discrepancy remain poorly understood. Methods. In the current study, a large healthy participant sample of the Budapest Sleep, Experiences and Traits Study (total N=267, 1899 nights) completed a 7-day protocol including mobile EEG recordings and sleep diaries, and also provided questionnaire-based reports of habitual sleep. We compared analogous sleep metrics from these three modalities, and used cross-validated LASSO regression to investigate demographic, psychological and lifestyle-related factors associated with increased sleep discrepancy across all three modalities, at both between- and within-participant levels. Results. Daily diaries estimated EEG-based sleep timing accurately (mean r=0.83), but were less accurate for sleep onset latency and quality. In contrast, questionnaire reports of habitual sleep provided inaccurate measures of even sleep timing (mean r=0.49) and considerably misestimated sleep timing and duration. Insomnia and depressive symptoms, napping, co-sleeping and personality traits were associated with increased sleep discrepancy. Conclusion. In healthy adults, questionnaires about habitual sleep provide only moderately accurate and biased estimates of actual sleep. Daily diaries provide considerably more accurate estimates, but sleep onset latency and physiological sleep quality is estimated by all self-reports less accurately than sleep timing. Sleep discrepancy is also present in healthy participants, it is particularly and its degree is affected by non-pathological characteristics. Long-term monitoring by daily diaries or wearables should be preferred to self-report questionnaires to measure sleep.

Background: Bidirectional next-day associations between sleep disturbances and affective symptoms have been shown in previous research, yet the consecutive day effects between these factors remains poorly understood. Methods: We analysed longitudinal ecological momentary assessment (EMA) data obtained from a subsample of young persons in the Brazilian High-Risk Cohort (BHRC) study collected in 2020-2021. Participants reported sleep quality each morning and rated affective symptoms relating to mood, anxiety, and energy four times daily for 28 days. We selected 88 individuals (17.83{+/-}1.74 years, 56 [63.6%] female gender) with at least one instance where individuals were observed three-days in a row. Within-person bidirectional next-day effects between sleep quality and affective symptoms were estimated using mixed-effects regression analysis adjusting. We then applied g-estimation approaches to estimate the effect that lagged sleep quality and consecutive improvements in sleep quality had on affective symptoms. Results: Sleep quality and affective symptoms had bidirectional next-day effects, with sleep quality tending to have greater influence on affective symptoms than the reverse. Improved lagged sleep quality had positive effects on affective symptoms incrementally above the prior night's sleep quality. Also, improvement of sleep quality across consecutive days had incremental and approximately equal effects on affective symptoms. Conclusions: Sleep quality and affective symptoms exhibit a feedback loop, whereby poor sleep quality influences affective symptoms over consecutive days. Breaking these feedback loops, by improving sleep quality across several consecutive nights should improve affective symptoms. This supports interventions that target sustained improvement in sleep and possibly circadian regulation to improve affective symptoms.

Background: Shiftwork disrupts natural sleep-wake cycles, alters light exposure patterns, and contributes to circadian misalignment. Detrimental health consequences associated with shift work include elevated risk for metabolic disorders, cardiovascular disease, cancer and all-cause mortality. Healthcare workers have one of the highest rates of shift work exposure, yet there are relatively few non-pharmacological interventions (with good evidence) developed to improve sleep outcomes in this population. Objective: A pre-post pilot interventional study assessed the acceptability and perceived effectiveness of commercial noise-masking earbuds on improving subjective sleep characteristics among National Health Service (NHS) healthcare staff working fast rotating shifts. Methods: Noise-masking sleep earbuds (Kokoon NightBuds) were worn for a pilot six-week intervention by twenty-seven NHS nurses (aged 26-43 years, 88.9% female) working fast rotating shifts from the EClocker Study. Sensors inside the earbuds were paired with a smartphone app to monitor sleep. An audio library in the smartphone app delivered personalised relaxation exercises and sleep techniques drawn from cognitive behavioural therapy for insomnia (CBT-I). A pre-post two-week monitoring period with daily smartphone-based Experience Sampling Methods (ESM) captured perceived daily sleep patterns. Acceptability and perceived effectiveness of the earbuds in promoting better sleep outcomes was assessed. Results: Use of the noise-masking sleep earbuds over a six-week period was associated with positive sleep improvement trends and elicited promising acceptability. Almost two thirds of NHS fast rotating shift nurses (63%) subjectively reported reductions in general sleep disturbance symptoms (PSQI Global), one in four experienced perceived sleep quality improvements (SQ; 25.9%), one in five reported sleeping longer (TST; 22.2%), and a third perceived falling asleep faster (SOL; 33.3%), had better sleep efficiency (SE; 33.3%) and improved daytime dysfunction (33.3%) (PSQI subcomponent scores). Sleep diaries (CSD) collected daily using smartphone-based ESM also demonstrated small improvements post-sleep earbud use; nurses reported sleeping an average 18 minutes longer (TST) and fell asleep more easily, on average 11 minutes faster (SOL). Sleep earbuds were generally well tolerated; 56% of nurses reported the earbuds as (somewhat to very) helpful, 52% reported (somewhat to strongly) falling asleep more easily (SOL), 44% felt (somewhat to strongly) their sleep quality was improved (SQ) and 30% agreed (somewhat to strongly) they slept longer (TST) and had less disturbed sleep. Conclusions: To our knowledge, this is the first study in Europe to pilot noise-masking earbuds as a potential non-pharmacological aid to improve sleep-wake behaviours or mitigate fatigue for healthcare staff. Preliminary results showed promising acceptability and (small) perceived sleep improvement trends following a targeted six-week earbud intervention in NHS fast rotating shift nurses.

Background: Adolescent sleep health is a growing public health concern, yet no culturally responsive sleep health program has been developed for Aboriginal and Torres Strait Islander (First Nations) young people. This study reports the outcomes and acceptability of Australia's first co-designed sleep health program for First Nations adolescents. Methods: The Let's Yarn About Sleep adolescent program was co-designed with First Nations community members from 23 Traditional groups, involving 174 Elders, adolescents, parents, carers, and service providers. The program drew on an Aboriginal pedagogical framework and the COM-B behaviour change model, integrating Western and First Nations sleep science, and was delivered by Aboriginal Youth Workers trained as Sleep Coaches. Outcomes included self-reported improvements in sleep knowledge, sleep timing and continuity, sleep quality, overall sleep health, and psychological distress. Post-program changes in outcomes were assessed using linear mixed-effects regression analyses. Program ratings and yarning-based feedback assessed acceptability. Findings: 70 First Nations young people participated in the program (median age 13.0 years, range 12 - 8; 67.1% female). Sleep knowledge improved substantially, with the mean composite score increasing from -0.65 (SD 1.23) at baseline to 0.82 (SD 1.27) at follow-up, a large effect (Cohen's d = 1.18; p < 0.001). A significant improvement was observed in the overall sleep health score, representing a medium effect (Cohen's d = 0.63; {beta} = 0.68, 95% CI: 0.31 - 1.04; p < 0.001). Psychological distress showed a directional reduction that did not reach statistical significance (Cohen's d = 0.32; {beta} =0.49, 95% CI:-1.08 - 0.09; p = 0.097), though a modest beneficial effect cannot be excluded. High acceptability was reflected in program ratings and qualitative feedback, with participants reporting greater sleep awareness, improved sleep behaviours, and strong community engagement with the program. Interpretation: A culturally grounded, co-designed sleep health program can improve sleep knowledge and overall sleep health and achieve high acceptability among First Nations adolescents. Community leadership, local delivery, and the embedding of First Nations worldviews are likely central to achieving impact, highlighting a promising pathway to address sleep health inequities Funding: Medical Research Future Fund (APP1201569). No competing interests