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Objective : A change toward Eveningness in circadian sleep-wake behavior is generally seen from childhood to adolescence, but less is known about circadian changes during adulthood. Circadian changes during mid-adulthood are of high interest, since Eveningness associates with a range of health-related problems, including psychological symptoms and mental disorders. In this study, we examined the circadian stability across 10 years, from 42 to 52 years of age, and how it is associated with sleep and mental health in a Finnish general population cohort follow-up-based ( n = 976). Method : Circadian type was assessed at both ages with a widely used item for self-estimated Morningness/Eveningness from the original Horne-Östberg Morningness-Eveningness Questionnaire. Generalized estimating equations were used for analyzing how a change in Morningness/Eveningness was associated with sleep and mental health longitudinally. Results : Our findings indicate that the circadian type is a highly stable trait during mid-adulthood with mainly moderate changes occurring in 42.2% of adults and no circadian change among 57.8% of adults. Most changes occurred within the same circadian type (23.9%), second to changes between moderate circadian types (13.3%). Changes between the Definite Evening-types and Morning-types were very rare (0.5%). Stable Evening-types reported more insufficient sleep, discrepancy between sleep duration on workdays and free days, and depression as compared to stable Morning-types. Moderate changes toward Morningness, comprising mostly those within Morning-types, were associated with reduced distress and psychological symptoms. Conclusions : In conclusion, our findings show high stability of mid-adulthood circadian type. However, changes toward Morningness seem to be associated with improved mental health. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

This study compared weekday and weekend actigraphy-measured and parent-reported sleep in relation to weight status among preschool-aged children. Participants were 3-6 years old preschoolers from the cross-sectional DAGIS-study with sleep data for ≥2 weekday and ≥2 weekend nights. Parents-reported sleep onset and wake-up times were gathered alongside 24 h hip-worn actigraphy. An unsupervised Hidden-Markov Model algorithm provided actigraphy-measured night time sleep without the guidance of reported sleep times. Waist-to-height ratio and age-and-sex-specific body mass index characterised weight status. Comparison of methods were assessed with consistency in quintile divisions and Spearman correlations. Associations between sleep and weight status were assessed with adjusted regression models. Participants included 638 children (49% girls) with a mean ± SD age of 4.76 ± 0.89. On weekdays, 98%-99% of actigraphy-measured and parent-reported sleep estimates were classified in the same or adjacent quintile and were strongly correlated (r s  = 0.79-0.85, p < 0.001). On weekends, 84%-98% of actigraphy-measured and parent-reported sleep estimates were respectively classified and correlations were moderate to strong (r s  = 0.62-0.86, p < 0.001). Compared with actigraphy-measured sleep, parent-reported sleep had consistently earlier onset, later wake-up, and greater duration. Earlier actigraphy-measured weekday sleep onset and midpoint were associated with a higher body mass index (respective β-estimates: -0.63, p < 0.01 and -0.75, p < 0.01) and waist-to-height ratio (-0.004, p = 0.03 and -0.01, p = 0.02). Though the sleep estimation methods were consistent and correlated, actigraphy measures should be favoured as they are more objective and sensitive to identifying associations between sleep timing and weight status compared with parent reports., (© 2023 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Objective: Associations of eveningness with health hazards benefit from analyzing to what extent the polygenic score for morningness correlates with the assessments of the behavioral trait of morningness-eveningness and chronotype., Methods: With a population-based sample of 17,243 Finnish adults, aged 25-74 years, this study examines the associations of four feasible assessment methods of chronotype, a) biological the genetic liability based on the polygenic score for morningness (PGS morn ), b) the widely-used single item for self-assessed morningness/eveningness (MEQ i19 ) of the original Morningness-Eveningness Questionnaire (MEQ), c) the behavioral trait of morningness-eveningness as assessed with the score on the shortened version (sMEQ) of the original MEQ, and d) the phase of entrainment as assessed with the habitual midpoint of sleep based on the self-reported sleep-wake schedule during weekend (Sleep mid-wknd ) as well as the sleep debt corrected midpoint of sleep (Sleep mid-corr )., Results: All self-report measures correlated with each other, but very weakly with the PGS morn , which explained 1-2% of the variation in diurnal preference or habitual sleep-wake schedule. The influence of age was greater on Sleep mid-wknd and Sleep mid-corr than on the sMEQ or MEQ i19 , indicating that the diurnal preference might be a more stable indicator for morningness-eveningness than the sleep-wake schedule. Analyses of the discrepancies between sMEQ and MEQ i19 indicated that eveningness can be over-estimated when relying on only the single-item self-assessment., Conclusions: The current polygenic score for morningness explains only a small proportion of the variation in diurnal preference or habitual sleep-wake schedule. The molecular genetic basis for morningness-eveningness needs further elucidation., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Sleep spindles are thalamocortical oscillations that contribute to sleep maintenance and sleep-related brain plasticity. The current study is an explorative study of the circadian dynamics of sleep spindles in relation to a polygenic score (PGS) for circadian preference towards morningness. The participants represent the 17-year follow-up of a birth cohort having both genome-wide data and an ambulatory sleep electroencephalography measurement available ( N = 154, Mean age = 16.9, SD = 0.1 years, 57% girls). Based on a recent genome-wide association study, we calculated a PGS for circadian preference towards morningness across the whole genome, including 354 single-nucleotide polymorphisms. Stage 2 slow (9-12.5 Hz, N = 186 739) and fast (12.5-16 Hz, N = 135 504) sleep spindles were detected using an automated algorithm with individual time tags and amplitudes for each spindle. There was a significant interaction of PGS for morningness and timing of sleep spindles across the night. These growth curve models showed a curvilinear trajectory of spindle amplitudes: those with a higher PGS for morningness showed higher slow spindle amplitudes in frontal derivations, and a faster dissipation of spindle amplitude in central derivations. Overall, the findings provide new evidence on how individual sleep spindle trajectories are influenced by genetic factors associated with circadian type. The finding may lead to new hypotheses on the associations previously observed between circadian types, psychiatric problems and spindle activity., (© 2020 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.)

Schizophrenia has been associated with disturbed sleep, even before the onset of the disorder, and also in non-schizophrenic first-order relatives. This may point to an underlying genetic influence. Here we examine whether weighted polygenic risk scores (PRS) for schizophrenia are associated with sleep spindle activity in healthy adolescents. Our sample comes from a community-based cohort of 157 non-schizophrenic adolescents (57% girls) having both genetic data and an overnight sleep EEG measurement available. Based on a recent genome-wide association study, we calculated PRS for schizophrenia across the whole genome. We also calculated PRS for the CACNA1l gene region, which has been associated with both schizophrenia and sleep spindle formation. We performed an overnight sleep EEG at the homes of the participants. Stage two sleep spindles were detected using an automated algorithm. Sleep spindle amplitude, duration, intensity and density were measured separately for central and frontal derivations and for fast (13-16 Hz) and slow (10-13 Hz) spindles. PRS for schizophrenia was associated with higher fast spindle amplitude (p = 0.04), density (p = 0.006) and intensity (p = 0.04) at the central derivation, and PRS in the CACNA1l region associated with higher slow spindle amplitude (p = 0.01), duration (p = 0.03) and intensity (p = 0.002) at the central derivation. A positive association between genetic variants for schizophrenia and sleep spindle activity among healthy adolescents supports a view that sleep spindles and schizophrenia share similar genetic pathways. This study suggests that altered sleep spindle activity might serve as an endophenotype of schizophrenia., (© 2018 European Sleep Research Society.)

Objective: Diagnosed autism spectrum disorders have been associated with a high prevalence of sleep problems, other psychiatric disorders and social deficits in adolescence. However, little is known about the possible connection between subclinical autistic traits and sleep. This study explored whether adolescents with elevated levels of subclinical autistic traits are at heightened risk for sleep problems., Methods: This study used data from the community cohort born in 1998. The sample consisted of 157 (57% girls) 17-year-old adolescents. Autistic traits were assessed using the Autism Spectrum Quotient (AQ). The Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI), and the Adult ADHD Self-Report Scale were utilized to control for comorbid psychiatric symptoms. Sleep was measured with actigraphy and sleep quality was self-rated using the Pittsburgh Sleep Quality Index (PSQI). Associations between autistic traits and sleep were examined using logistic regression analysis., Results: Elevated levels of autistic traits were significantly associated with shorter weekday sleep duration. Moreover, autistic traits remained an independent predictor of short sleep duration when comorbid psychiatric symptoms were controlled for (OR 1.14; 95% CI: 1.03-1.26)., Conclusions: The results suggest that subclinical autistic traits should be considered as a possible underlying mechanism affecting adolescent sleep., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

ADHD and its subclinical symptoms have been associated with both disturbed sleep and weakened overnight memory consolidation. As sleep spindle activity during NREM sleep plays a key role in both sleep maintenance and memory consolidation, we examined the association between subclinical ADHD symptoms and sleep spindle activity. Furthermore, we hypothesized that sleep spindle activity mediates the effect of ADHD symptoms on overnight learning outcome in a procedural memory task. We studied these questions in a community-based cohort of 170 adolescents (58% girls, mean age = 16.9, SD = 0.1 years), who filled in the Adult ADHD Self-Report Scale (ASRS-v1.1), and underwent an overnight sleep EEG coupled with a mirror tracing task before and after sleep. Elevated ADHD symptoms were associated with weaker fast sleep spindle activity, and poorer overnight learning in the procedural memory test. However, sleep spindles, contrary to the hypothesis, did not mediate the association between ADHD symptoms and overnight learning. Our results showed that a higher level of ADHD symptoms in adolescence is associated with similar alterations in sleep spindle activity as observed in many neuropsychiatric conditions and might contribute to altered synaptic connectivity and sleep fragmentation observed in ADHD., (Copyright © 2018. Published by Elsevier Inc.)

Objective: Recent genome-wide association studies (GWASs) have revealed new genetic variants behind self-reported individual circadian preference, a distinct biological trait that is fairly stable during adulthood. In this study we analyze whether these genetic variants associate with objectively measured sleep timing from childhood to adolescence, over a nine-year period, with self-reported circadian preference during late adolescence., Methods: The participants (N = 100, 61% girls) came from a community cohort from Finland born in 1998. Sleep midpoint was measured with actigraphy at 8, 12 and 17 years. Circadian preference was self-reported at the age of 17 years. Single nucleotide polymorphisms (SNPs) were extracted at 12 years of age from the Illumina OmniExpress Exome 1.2 bead array data. Weighted polygenic risk scores (PRSs) were calculated based on top SNPs from a recent GWAS for morningness-eveningness in an adult population., Results: The PRS for circadian preference towards morningness was associated with earlier sleep midpoint from childhood to adolescence. When the time points were analyzed separately, the association between genetic tendency towards morning preference and earlier sleep midpoint was strongest among the 17-year-olds. Furthermore, the shift towards later sleep rhythm from early to late adolescence was milder for those with a higher PRS for morning preference. PRS for morning preference was also associated with self-reported circadian preference towards morningness in late adolescence., Conclusion: Our results suggest that genetic variants found for circadian preference in adults are already associated with objective sleep timing during childhood and adolescence, and predict individual developmental sleep trajectories from childhood onwards., (Copyright © 2018. Published by Elsevier B.V.)

Objectives: To assess differences relating to circadian preference in objectively measured sleep patterns from childhood to adolescence over a 9-year period. We hypothesized there is developmental continuity in sleep timing and duration according to circadian preference., Study Design: Young participants (N = 111, 65% girls) from a community-based birth cohort underwent sleep actigraphy at mean ages 8.1 (SD = 0.3), 12.3 (SD = 0.5), and 16.9 (SD = 0.1) years. A short version of Morningness-Eveningness Questionnaire was administered in late adolescence. At each follow-up, sleep midpoint, duration, wake after sleep onset, sleep efficiency, and weekend catch-up sleep were compared between those reporting morning, intermediate, and evening preferences in late adolescence., Results: Mixed model analyses indicated that sleep timing was significantly earlier among morning types compared with evening types at all ages (P values < .04). The mean differences in sleep midpoint between morning and evening types increased from a mean of 19 minutes (age 8), 36 minutes (age 12), to 89 minutes (age 17). The largest change occurred from age 12 to 17 years. Sleep duration, wake after sleep onset, sleep efficiency, and catch-up sleep did not differ according to circadian preference., Conclusions: This study found significant continuity in sleep timing from childhood to adolescence over 9 years, indicating that late circadian preference reported in late adolescence begins to manifest in middle childhood. Further studies are needed to establish whether sleep timing has its origins at an even earlier age., (Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.)

Circadian preference toward eveningness has been associated with increased risk for mental health problems both in early adolescence and in adulthood. However, in late adolescence, when circadian rhythm naturally shifts to later, its significance for mental health is not clear. Accordingly, we studied how circadian rhythm estimated both by self-reported chronotype and by actigraph-defined midpoint of sleep was associated with self-reported psychiatric problems based on Youth Self Report (YSR). The study builds on a community cohort born in 1998, Helsinki, Finland. At age 17 years (mean age = 16.9, SD = 0.1 years), 183 adolescents (65.6% of the invited) participated in the study. We used the shortened version of the Horne-Östberg morningness-eveningness Questionnaire to define the chronotype, and actigraphs to define the naturally occur circadian rhythm over a 4 to 17 days' period (mean nights N = 8.3, SD = 1.8). The Achenbach software was used to obtain T-score values for YSR psychiatric problem scales. The analyses were adjusted for important covariates including gender, socioeconomic status, body mass index, pubertal maturation, mother's licorice consumption during pregnancy, and actigraph-defined sleep duration and quality. Eveningness was associated with higher scores in rule-breaking behavior and conduct problems (as assessed either by midpoint of sleep or by self-reported chronotype, p-values <0.05), attention deficit/hyperactivity problems (by self-reported chronotype, p-values <0.05), with affective problems (by midpoint of sleep and by self-reported chronotype, p-values <0.05) and somatic complaints (by self-reported chronotype, p-values <0.05), as compared to circadian tendency toward morningness. Our results suggest that the association between eveningness and externalizing problem behavior, present in children and younger adolescents, is also present in late adolescence when circadian rhythms shift toward evening.

Chronotype is an emerging predictor of health and longevity, and understanding its influence on chronic diseases is important for constructing conceptual models of long-term pathways to health. We assessed the associations of chronotype with health status in the general Finnish adult population. Our population-based data were derived from the National FINRISK 2012 study and consisted of 4414 participants, aged 25-74 years, living in Finland. As part of their health examination, participants were asked about their circadian preference to the daily activities (morningness-eveningness) and a diagnosis or treatment for a set of common noncommunicable medical conditions and chronic diseases during the past 12 months. We found that there were 1935 (43.8%) morning types (MTs) and 595 (13.5%) evening types (ETs) and that 1884 (42.7%) were intermediates. As compared with the MTs, the ETs had significantly greater odds for depression (OR = 2.44, 95% CI = 1.52-3.90, p < 0.001) and other mental disorders (OR = 5.18, 95% CI = 2.32-11.52, p < 0.001). The odds were also increased for gallstones, and chronic obstructive pulmonary disease, but these did not remain significant after controlling for multiple testing. Responses to the single-item subjective estimation on the chronotype yielded the association of the definitely evening type of persons with the diagnosis or treatment of cardiac insufficiency (OR = 1.99, 95% CI = 1.02-3.88, p = 0.044) that was corroborated as the greater the eveningness score was, the more common the diagnosis or treatment of cardiac insufficiency was (β = 0.92, 95% CI = 0.85-0.98, p = 0.013). This exploratory study adds further support to the role of evening chronotype in chronic disease risk, albeit underlying mechanisms remain to be elucidated.

Study Objectives: Our study explored if bedtimes influenced school performance and motivation, as well as the odds ratio (OR) for health-related concerns in adolescents., Methods: The School Health Promotion Study was based on an anonymous self-report questionnaire conducted in 90% of the municipalities in Finland. The study was conducted during 2008 and 2010 in Southern Finland, Eastern Finland, and Lapland, and during 2009 and 2011 in Western Finland, Northern Finland, and Åland. Several indicators were used to measure school performance and motivation. Accidents and health-related complaints, such as depressive symptoms, sleep quality, neck or shoulder pains, lower back pains, stomachaches, anxiety or nervousness, irritation or tantrums, headaches, and tiredness or dizziness were analyzed in relation to the usual bedtime. Our study had a relatively large sample size (N=384,076), consisting of students in the eighth and the ninth grades of secondary schools and the first and the second grades of upper secondary and vocational schools (ages 14-20 years) in Finland., Results: All of the various indicators used to assess school performance and motivation suggest that the later the bedtime of adolescents, the lower their school performance and their motivation. Similarly later bedtimes increase the OR for depressive symptoms and other negative health consequences in adolescents as well as a tendency towards accidents. All of these problems were emphasized in students with bedtimes of 11:30 PM and later., Conclusions: Late bedtimes, especially those after 11:30 PM, indicate poor sleep which deteriorates school performance and motivation and increases the OR for depressive symptoms and other health-related issues in adolescents., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Certain preferences for the timing of daily activities (chronotype) may predispose an individual to sleep problems and mood disorders. In this study, we have examined the link between chronotypes and depression. Participants (N = 6071) were recruited from a random sample of the general population aged 25 to 74 yrs living in defined geographical areas, as part of the National FINRISK Study in 2007 in Finland. Chronotype assessment was based on six items from the original Horne-Östberg Morningness-Eveningness Questionnaire. Depression was assessed with four self-reported items, including two probes for a diagnosis of a major depressive episode, diagnosed or treated depression, and use of antidepressants. We also analyzed correlations between chronotype and several health indicators, such as systolic and diastolic blood pressures, resting heart rate, weight, and waist circumference. The odds ratios for a range of indicators of depression were higher for evening types (2.7- to 4.1-fold) and intermediate types (1.5- to 1.9-fold) than for morning types. Our results suggest that individuals having a preference for evening hours to carry out their daily activities are prone to depression.

In this study, the authors analyzed whether chronotypes, sleep duration, and sleep sufficiency are associated with cardiovascular diseases and type 2 diabetes by using the National FINRISK Study 2007 data (N = 6258), being a representative sample of the population aged 25 to 74 living in five areas of Finland. Health status assessments and laboratory measurements from the participants (N = 4589) of the DILGOM substudy were used for the detailed analysis of chronotype. Evening types had a 2.5-fold odds ratio for type 2 diabetes (p < .01) as compared with morning types, the association being independent of sleep duration and sleep sufficiency. Evening types had a 1.3-fold odds ratio for arterial hypertension (p < .05 after controlling for sleep duration or sleep sufficiency), a faster resting heart rate and a lower systolic blood pressure (both p < .01), and lower levels of serum total cholesterol and low-density lipoprotein cholesterol (both p < .0001) than morning types. There were significant 1.2- to 1.4-fold odds ratios for arterial hypertension among those with long or short sleep durations or reduced sleep sufficiency. To conclude, the behavioral trait towards eveningness is suggested to predispose individuals to type 2 diabetes in particular, whereas compromised sleep is robustly associated with arterial hypertension.

Evolution is a continuous process that changes population genetics towards greater adaptation. Sleep is an example of a conservative trait that appears everywhere and is regulated similarly in the animal kingdom. Because of this similarity in sleep regulation different animal models and genetic modification can be used in basic research and in studies of sleep related diseases. Recent research has enlightened the function of the clock genes and the synaptic plasticity during sleep, so that we can better understand the need for sleep and the effects of sleep loss. This knowledge is needed in order to prevent and treat sleep related diseases.

Brigitte Holzinger,1,2 Franziska Nierwetberg,1 Frances Chung,3 Courtney J Bolstad,4 Bjørn Bjorvatn,5 Ngan Yin Chan,6 Yves Dauvilliers,7 Colin A Espie,8 Fang Han,9 Yuichi Inoue,10 Damien Leger,11 Tainá Macêdo,12 Kentaro Matsui,13,14 Ilona Merikanto,15,16 Charles M Morin,17 Sérgio A Mota-Rolim,18 Markku Partinen,19 Giuseppe Plazzi,20,21 Thomas Penzel,22 Mariusz Sieminski,23 Yun Kwok Wing,6 Serena Scarpelli,24 Michael R Nadorff,4,25 Luigi De Gennaro24,26 1Institute for Consciousness and Dream Research, Vienna, Austria; 2Medical University Vienna, Postgraduate Master ULG Sleep Coaching, Vienna, Austria; 3Department of Anesthesiology and Pain Medicine, University Health Network, University of Toronto, Toronto, ON, Canada; 4Mississippi State University, Mississippi State, MS, USA; 5Department of Global Public Health and Primary Care, University of Bergen and Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway; 6Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, Special Administrative Region, People’s Republic of China; 7Sleep-Wake Disorders Unit, Department of Neurology, Gui-de-Chauliac Hospital, CHU Montpellier, INM, Univ Montpellier, INSERM, Montpellier, France; 8Sir Jules Thorn Sleep & Circadian Neuroscience Institute (SCNi), University of Oxford, Oxford, UK; 9Department of Pulmonary and Critical Care Medicine, Peking University People’s Hospital, Beijing, People’s Republic of China; 10Tokyo Medical University, Tokyo, Japan; 11Université de Paris, APHP, Hôtel-Dieu, Centre du Sommeil et de la Vigilance, Paris, France; 12Department of Psychology, Federal University of Rio Grande do Norte, Natal, Brazil; 13Department of Laboratory Medicine, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Japan; 14Department of Psychiatry, Tokyo Women’s Medical University, Tokyo, Japan; 15SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 16Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; 17École de Psychologie, Centre d’étude des troubles du sommeil, Centre de recherche CERVO/Brain Research Center, Université Laval, Québec, QC, Canada; 18Brain Institute, Physiology and Behavior Department, and Onofre Lopes University Hospital - Federal University of Rio Grande do Norte, Natal, Brazil; 19Helsinki Sleep Clinic, Terveystalo Healthcare, and Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland; 20IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; 21Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; 22Sleep Medicine Center, Charité Universitätsmedizin Berlin, Berlin, Germany; 23Department of Emergency Medicine, Medical University of Gdansk, Gdansk, Poland; 24Department of Psychology, Sapienza University of Rome, Rome, Italy; 25Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; 26IRCCS Fondazione Santa Lucia, Rome, ItalyCorrespondence: Brigitte Holzinger, Tel +43 699 101 99 042, Email brigitte.holzinger@meduniwien.ac.atPurpose: The COVID-19 pandemic affects mental health and sleep, resulting in frequent nightmares. Therefore, identifying factors associated with nightmare frequency is important, as it can indicate mental health issues. The study aimed to investigate increases in nightmare frequency comparing the pre-pandemic and pandemic period, and identify its risk factors. Further, the mediating role of post-traumatic stress disorder symptoms between the pandemic and nightmares is explored.Patients and Methods: For this cross-sectional survey data were obtained via self-rating online survey (ICOSS: details in Partinen et al, 2021), which was open to anyone older than 18 years. The final volunteer sample consisted of 15,292 participants, divided according to their nightmare frequency (high: ≥ 1– 2 nights/week; low: < 1– 2 nights/week). A total of 9100 participants were excluded if answers on variables of interest were missing or receiving rewards for participation. Chi-square tests identified changes of nightmare frequency. Predictors of high nightmare frequency were assessed using logistic regression and presented as Odds Ratios. Post-hoc mediation models were used to investigate the role of post-traumatic stress symptoms (PTSS).Results: The mean age was 41.63 (SD=16.55) with 64.05% females. High nightmare frequency increased significantly from 13.24% to 22.35% during the pandemic. Factors associated with it included self-reported PTSS (OR=2.11), other mental disorders and various sleep disorders or problems. Financial burden due to the pandemic, confinement, having had COVID-19, and work situation during the pandemic were associated with nightmare frequency, those relations were partly mediated through PTSS.Conclusion: Our results display the pandemic influence on nightmare frequency, which in turn connects to multiple mental health and sleep factors. These relations were partly mediated through PTSS. The COVID-19 pandemic appears to have caused traumatization of a substantial proportion of society. Health care workers should consider nightmares in their screening routines, as it might indicate PTSS and/or other mental and sleep disorders.Keywords: COVID-19, nightmares, mental health, sleep, post-traumatic stress disorder, collective trauma

Ilona Merikanto,1– 3 Anu-Katriina Pesonen,4 Tiina Paunio,2,5 Timo Partonen2 1SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 2Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; 3Orton Orthopaedics Hospital, Helsinki, Finland; 4Department of Psychology and Logopedics and SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 5Department of Psychiatry and SleepWell Research Program, University of Helsinki and Helsinki University Hospital, Helsinki, FinlandCorrespondence: Ilona Merikanto, SleepWell Research Program, Faculty of Medicine, University of Helsinki, PL21, Helsinki, 00014, Finland, Email ilona.merikanto@helsinki.fiBackground: Circadian phenotype has a crucial role in determining wellbeing and health prospective. Evening-types have higher risk for sleep and mental health problems, which is also reflected in work wellbeing. However, there are no population-based studies examining the association of working ability and circadian typology at different working-age-groups. Also, the role of predisposing factors, ie, sleep-related differences between circadian types, has not been studied in relation to working ability among circadian types in a population-based sample.Methods: In this population-based sample of 13,114 working-age Finnish adults from 18 to 64 years of age, we examined the associations between circadian type, exhaustion and working ability and the roles of sleep-wake rhythm misalignment and insufficient sleep on these associations in 10-years-wide age-groups. Circadian type was assessed with the widely-used single item for self-assessed morningness/eveningness from the Horne-Östberg Morningness-Eveningness Questionnaire (MEQ).Results: Evening-types, especially definite evening-types, were more exhausted and had poorer working ability than morning-types. Higher exhaustion among evening-types was apparent in all working ages with a peak at ages 45 to 54 years. Poorer working ability in definite evening-types as compared to definite morning-types was found only at ages 35 to 54 years. Evening-types, especially definite-evening-types, had also more social jet lag and they reported more insufficient sleep than definite morning-types. More frequent insufficient sleep associated with poorer working ability and partly mediated the association between circadian type and working ability.Conclusion: Circadian phenotypes were found to differ in risk for exhaustion and in working ability, and this association was partly mediated by insufficient sleep. Our findings emphasize the importance to improve sleep especially among evening-types to ensure better work wellbeing.Keywords: burnout, chronotype, circadian rhythms, epidemiology, sleep, work wellbeing

Serena Scarpelli,1 Michael R Nadorff,2,3 Bjørn Bjorvatn,4 Frances Chung,5 Yves Dauvilliers,6 Colin A Espie,7 Yuichi Inoue,8 Kentaro Matsui,9,10 Ilona Merikanto,11,12 Charles M Morin,13 Thomas Penzel,14 Mariusz Sieminski,15 Han Fang,16 Tainá Macêdo,17 Sérgio A Mota-Rolim,18 Damien Leger,19 Giuseppe Plazzi,20,21 Ngan Yin Chan,22 Markku Partinen,23 Courtney J Bolstad,2 Brigitte Holzinger,24,25 Luigi De Gennaro1,26 1Department of Psychology, Sapienza University of Rome, Rome, Italy; 2Mississippi State University, Mississippi State, MS, USA; 3Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; 4Department of Public Health and Primary Care, University of Bergen and Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway; 5Department of Anesthesiology and Pain Medicine, University Health Network, University of Toronto, Toronto, Canada; 6Sleep-Wake Disorders Unit, Department of Neurology, Gui-de-Chauliac Hospital, CHU Montpellier, INM, Univ Montpellier, INSERM, Montpellier, France; 7Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; 8Tokyo Medical University, Tokyo, Japan; 9Department of Laboratory Medicine, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Japan; 10Department of Psychiatry, Tokyo Women’s Medical University, Tokyo, Japan; 11SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 12Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland; 13École de Psychologie, Centre d’étude des troubles du sommeil, Centre de recherche CERVO/Brain Research Center, Université Laval, Québec, Canada; 14Sleep Medicine Center, Charité Universitätsmedizin Berlin, Berlin, Germany; 15Department of Emergency Medicine, Medical University of Gdansk, Gdansk, Poland; 16Department of Pulmonary and Critical Care Medicine, Peking University People’s Hospital, Beijing, People’s Republic of China; 17Department of Psychology, Federal University of Rio Grande do Norte, Natal, Brazil; 18Brain Institute, Physiology and Behavior Department, and Onofre Lopes University Hospital - Federal University of Rio Grande do Norte, Natal, Brazil; 19Université de Paris, APHP, Hôtel-Dieu, Centre du Sommeil et de la Vigilance, Paris, France; 20IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; 21Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; 22Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, Special Administrative Regions, People’s Republic of China; 23Helsinki Sleep Clinic, Terveystalo Healthcare, and Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland; 24Institute for Consciousness and Dream Research, Vienna, Austria; 25Medical University Vienna, Postgraduate Master Program Medical Sleep Coaching, ZK-Schlafcoaching, Vienna, Austria; 26IRCCS Fondazione Santa Lucia, Rome, ItalyCorrespondence: Luigi De Gennaro, Tel +39-06-49917647, Fax +39-06-49917711, Email luigi.degennaro@uniroma1.itIntroduction: A growing number of studies have demonstrated that the coronavirus disease-19 (COVID-19) pandemic has severely affected sleep and dream activity in healthy people. To date, no investigation has examined dream activity specifically in COVID-19 patients.Methods: As part of the International COVID-19 Sleep Study (ICOSS), we compared 544 COVID-19 participants with 544 matched-controls. A within-subjects comparison between pre-pandemic and pandemic periods computed separately for controls and COVID-19 participants were performed on dream recall and nightmare frequency (DRF; NF). Also, non-parametric comparisons between controls and COVID-19 participants were carried out. Further, we compared psychological measures between the groups collected during pandemic. Ordinal logistic regression to detect the best predictors of NF was performed.Results: We found that people reported greater dream activity during the pandemic. Comparisons between controls and COVID-19 participants revealed a) no difference between groups concerning DRF in the pre-pandemic period and during the pandemic; b) no difference between groups concerning nightmare frequency in the pre-pandemic period; and c) COVID-19 participants reported significantly higher NF than controls during pandemic (p = 0.003). Additionally, we showed that a) anxiety, depression, post-traumatic stress-disorder (PTSD) symptom scores were higher in COVID-19 participants than controls; and b) quality of life and health as well as wellbeing (WHO-5) scores were significantly higher in controls than COVID-19 participants. Finally, ordinal logistic regression indicates that DRF (p < 0.001), PTSD (p < 0.001), anxiety (p = 0.018), insomnia (p = 0.039), COVID-19 severity (p = 0.014), sleep duration (p = 0.003) and age (p = 0.001) predicted NF.Discussion: Our work shows strong associations between increased nightmares in those reporting having had COVID-19. This suggests that the more that people were affected by COVID-19, the greater the impact upon dream activity and quality of life.Keywords: dreaming, pandemic, sleep, PTSD, anxiety, COVID-19 severity

Eirin Fränkl,1 Serena Scarpelli,2 Michael R Nadorff,3,4 Bjørn Bjorvatn,5 Courtney J Bolstad,3 Ngan Yin Chan,6 Frances Chung,7 Yves Dauvilliers,8 Colin A Espie,9 Yuichi Inoue,10,11 Damien Leger,12,13 Tainá Macêdo,14 Kentaro Matsui,15,16 Ilona Merikanto,17– 19 Charles M Morin,20 Sérgio Mota-Rolim,21 Markku Partinen,22,23 Thomas Penzel,24 Giuseppe Plazzi,25,26 Mariusz Sieminski,27 Yun Kwok Wing,6 Luigi De Gennaro,2,28 Brigitte Holzinger1,29 1Institute for Consciousness and Dream Research, Vienna, Austria; 2Department of Psychology, Sapienza University of Rome, Rome, Italy; 3Mississippi State University, Mississippi State, MS, USA; 4Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; 5Department of Global Public Health and Primary Care, University of Bergen, and Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway; 6Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China; 7Department of Anesthesiology and Pain Medicine, University Health Network, University of Toronto, Toronto, Canada; 8Sleep-Wake Disorders Center, Department of Neurology, Gui-de-Chauliac Hospital, Institute for Neurosciences of Montpellier INM, INSERM, University of Montpellier, Montpellier, France; 9Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; 10Department of Somnology, Tokyo Medical University, Tokyo, Japan; 11Japan Somnology Center, Neuropsychiatric Research Institute, Tokyo, Japan; 12Université de Paris, VIFASOM (EA 7331 Vigilance Fatigue, Sommeil et Santé Publique), Paris, France; 13APHP, Hotel-Dieu de Paris, Centre du Sommeil et de la Vigilance, Paris, France; 14Department of Psychology, Federal University of Rio Grande do Norte, Natal, Brazil; 15Department of Clinical Laboratory and Department of Sleep-Wake Disorders, National Center of Neurology and Psychiatry National Institute of Mental Health, Kodaira, Japan; 16Department of Psychiatry, Tokyo Women’s Medical University, Tokyo, Japan; 17Sleep Well Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 18Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland; 19Orton Orthopaedics Hospital, Helsinki, Finland; 20École de Psychologie, Centre d’étude des troubles du sommeil, Centre de recherche CERVO/Brain Research Center, Université Laval, Québec, Canada; 21Brain Institute, Physiology and Behavior Department, and Onofre Lopes University Hospital, Federal University of Rio Grande do Norte, Natal, Brazil; 22Helsinki Sleep Clinic, Terveystalo Healthcare, Helsinki, Finland; 23Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland; 24Sleep Medicine Center, Charité Universitätsmedizin Berlin, Berlin, Germany; 25IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; 26Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; 27Department of Emergency Medicine, Medical University of Gdansk, Gdansk, Poland; 28IRCCS Fondazione Santa Lucia, Rome, Italy; 29Medical University Vienna, ZK-Schlafcoaching, Vienna, AustriaCorrespondence: Brigitte HolzingerInstitute for Consciousness and Dream Research, Canongasse 13/1, Vienna, 1180, AustriaTel +43699-101 99 042Fax +4301-25330334600Email brigitte.holzinger@meduniwien.ac.atObjective: Many have reported odd dreams during the pandemic. Given that dreams are associated with mental health, understanding these changes could provide crucial information about wellbeing during the pandemic. This study explored associations between COVID-19 and dream recall frequency (DRF), and related social, health, and mental health factors.Methods: We conducted a cross-sectional web survey of 19,355 individuals in 14 countries from May to July 2020. We collected data on COVID-19, mental health, sleep and DRF during the pandemic. We performed McNemar Tests to compare low (< 3 nights per week) and high DRF (≥ 3 nights per week) before and during COVID-19 and to evaluate changes in sleep variables segmented by DRF. Chi-square tests were conducted to compare characteristics between low and high DRF. Logistic regression analyses were conducted to examine associations between various independent variables and DRF.Results: Reports of high DRF during the pandemic were higher than before the pandemic (P< 0.001). Female gender (aOR=1.25, 95% CI 1.10– 1.41), nightmares (aOR=4.22, 95% CI 3.45– 5.17), sleep talking (aOR= 2.36, 1.73– 3.23), sleep maintenance problems (aOR=1.34, 95% CI 1.15– 1.56), symptoms of REM sleep behavior disorder (RBD; aOR=1.24, 95% CI 1.09– 1.41) and repeated disturbing thoughts (posttraumatic stress disorder (PTSD) symptoms) were associated with high DRF. Age group 55– 64 years (aOR=0.69, 95% CI 0.58– 0.83) reported less high DRF than younger participants. Unadjusted OR showed associations between depression, anxiety, and DRF; however, in adjusted regression depression (aOR= 0.71, 0.59– 0.86) and anxiety (aOR=0.79, 95% CI 0.66– 0.94) were negatively associated with high DRF.Conclusion and Relevance: DRF was higher than pre-pandemic levels across four continents. DRF was associated with gender and parasomnias like nightmares and RBD symptoms, sleep maintenance problems, PTSD symptoms and negatively associated with depression and anxiety. The results implicate that COVID-19 is reflected in our dreams as an expression of the emotional intensity of the pandemic.Keywords: sleep, sleep disorder, mental health, parasomnia, collective threat