Sleep-wake Patterns Research Articles

Actigraphy: Metrics reveal it is not a valid tool for determining sleep in neonates.

Study of emerging sleep-wake patterns in neonates is important for promptly identifying and treating abnormal sleep behaviours to ensure healthy infant development and neurobehavioral outcomes. Current methods to assess sleep are costly, labour intensive, and particularly difficult to implement in fragile, hospitalised infants requiring intensive medical care. The aim of the present study was to assess the validity of actigraphy as a tool for detecting sleep in preterm infants, using polysomnography (PSG) as the "gold standard". A total of 10 neonates (mean [SD] 35.8[1.2]weeks post-menstrual age; five female) hospitalised since birth for prematurity each participated in one 8-10hr session during which PSG and actigraphy were recorded simultaneously. Inter-feed minute-by-minute PSG Sleep-Wake scores were compared to concurrent actigraph epochs categorised as either "Sleep" or "Wake" using three separate movement-per-minute thresholds (≤20, ≤40, ≤80). Tool validity was assessed using five metrics. A key finding was that for each of the movement thresholds there was high agreement rate, sensitivity, and predictive value of sleep (85.2%-97.2%), whereas specificity and predictive value of wake remained low (12%-46%). Receiver operating characteristic curve analysis also revealed low discriminatory power of actigraphy for estimating sleep (area under the curve=0.636; Youden's Index J=0.2173). Lack of sufficient minutes of autonomous wake periods among infants was identified as a key limitation in actigraphy. Findings from the present study suggest actigraphy cannot be validated for Sleep/Wake discrimination in preterm infants and that proper validation requires sufficient data from periods of both Sleep and Wake.

Excessive daytime sleepiness in idiopathic blepharospasm

ObjectiveTo explore the frequency of excessive daytime sleepiness (EDS), and its impact on quality of life and its associated clinical factors in idiopathic blepharospasm. MethodsThis cross-sectional study was carried out in 425 idiopathic blepharospasm patients and a group of 424 age-matched and sex-matched healthy subjects. EDS was assessed with the Epworth Sleepiness Scale (ESS) in all subjects. Other clinical characteristics of patients with idiopathic blepharospasm including motor symptoms, sleep quality, depression, anxiety, cognition, and quality of life were also assessed. ResultsEDS was significantly more frequent in patients with idiopathic blepharospasm than in controls (22.1% vs 12.3%; p < 0.05). Blepharospasm patients with EDS scored significantly higher in Jankovic Rating scale, Hamilton Rating Scale for Depression (HDRS), Hamilton Rating Scale for Anxiety (HARS), and significantly lower in Montreal Cognitive Assessment (MoCA) and 36-Item Short Form Health Survey (SF-36) than those without EDS (p < 0.05). The binary logistic regression model indicated that male, younger age of onset of blepharospasm, higher motor scores, higher HDRS scores, and lower MoCA scores were associated with the presence of EDS in patients with blepharospasm (p < 0.05). ConclusionsRecognition and management of EDS in idiopathic blepharospasm patients is necessary as the occurrence of EDS was associated with higher motor burden, more serious mood and cognitive disturbances, and poorer quality of life. Our results suggest that blepharospasm may exhibit abnormal sleep-wake patterns and further support the clinical heterogeneity of the disease.

Change in sleep-wake cycle, use of digital media and emotional wellbeing amidst COVID-19 lockdown amongst dental students in India

Background: Maharashtra is one of the major hotspots affected with COVID-19 infection in India. By imposing lockdown to implement preventive and control strategies, entire world is trying to contain the spread of this potentially fatal pandemic. Lockdown has compelled people to stay at home, refrain from their day-to-day activity and lead to drastic lifestyle changes. Aim: The aim of the study was to assess the impact of COVID-19 pandemic lockdown on sleep-wake pattern and emotional status among Bachelor of Dental Surgery undergraduate students. Materials and Methods: This observational online survey was carried out among the undergraduate students of our dental college. The question on individual sleep cycle, wake up pattern, eating habits, working hours, screen time on T.V., mobile, and laptop were addressed before and during the lockdown. The results were tabulated and analyzed using the SPSS software version 17.0. If P &lt; 0.001, the results were reported to be statistically significant. Results: Statistical difference was observed in the usage of digital media, change in their sleep wake pattern, and eating habits among dental students during the lockdown period after applying paired test with P &lt; 0.001. Furthermore, these unpredictable changes in their working hour, sleeping pattern, eating habits, and concern about spending time build stressful situation among students. Conclusion: It can be concluded that the dental students have increased level of stress and disturbance in sleep-wake cycle and emotional well-being during this COVID-19 lockdown.

Gender differences in BaYaka forager sleep-wake patterns in forest and village contexts

Sleep studies in small-scale subsistence societies have broadened our understanding of cross-cultural sleep patterns, revealing the flexibility of human sleep. We examined sleep biology among BaYaka foragers from the Republic of Congo who move between environmentally similar but socio-ecologically distinct locations to access seasonal resources. We analyzed the sleep–wake patterns of 51 individuals as they resided in a village location (n = 39) and a forest camp (n = 23) (362 nights total). Overall, BaYaka exhibited high sleep fragmentation (50.5) and short total sleep time (5.94 h), suggestive of segmented sleep patterns. Sleep duration did not differ between locations, although poorer sleep quality was exhibited in the village. Linear mixed effect models demonstrated that women’s sleep differed significantly from men’s in the forest, with longer total sleep time (β ± SE = − 0.22 ± 0.09, confidence interval (CI) = [− 0.4, − 0.03]), and higher sleep quality (efficiency; β ± SE = − 0.24 ± 0.09, CI = [− 0.42, − 0.05]). These findings may be due to gender-specific social and economic activities. Circadian rhythms were consistent between locations, with women exhibiting stronger circadian stability. We highlight the importance of considering intra-cultural variation in sleep–wake patterns when taking sleep research into the field.

Sleep Diagnostics for Home Monitoring of Sleep Apnea Patients.

Objectives: Sleep time information is essential for monitoring of obstructive sleep apnea (OSA), as the severity assessment depends on the number of breathing disturbances per hour of sleep. However, clinical procedures for sleep monitoring rely on numerous uncomfortable sensors, which could affect sleeping patterns. Therefore, an automated method to identify sleep intervals from unobtrusive data is required. However, most unobtrusive sensors suffer from data loss and sensitivity to movement artifacts. Thus, current sleep detection methods are inadequate, as these require long intervals of good quality. Moreover, sleep monitoring of OSA patients is often less reliable due to heart rate disturbances, movement and sleep fragmentation. The primary aim was to develop a sleep-wake classifier for sleep time estimation of suspected OSA patients, based on single short-term segments of their cardiac and respiratory signals. The secondary aim was to define metrics to detect OSA patients directly from their predicted sleep-wake pattern and prioritize them for clinical diagnosis.Methods: This study used a dataset of 183 suspected OSA patients, of which 36 test subjects. First, a convolutional neural network was designed for sleep-wake classification based on healthier patients (AHI < 10). It employed single 30 s epochs of electrocardiograms and respiratory inductance plethysmograms. Sleep information and Total Sleep Time (TST) was derived for all patients using the short-term segments. Next, OSA patients were detected based on the average confidence of sleep predictions and the percentage of sleep-wake transitions in the predicted sleep architecture.Results: Sleep-wake classification on healthy, mild and moderate patients resulted in moderate κ scores of 0.51, 0.49, and 0.48, respectively. However, TST estimates decreased in accuracy with increasing AHI. Nevertheless, severe patients were detected with a sensitivity of 78% and specificity of 89%, and prioritized for clinical diagnosis. As such, their inaccurate TST estimate becomes irrelevant. Excluding detected OSA patients resulted in an overall estimated TST with a mean bias error of 21.9 (± 55.7) min and Pearson correlation of 0.74 to the reference.Conclusion: The presented framework offered a realistic tool for unobtrusive sleep monitoring of suspected OSA patients. Moreover, it enabled fast prioritization of severe patients for clinical diagnosis.

Sleep in Young People With Features of Borderline Personality Disorder: A Scoping Review.

Sleep disturbance is commonly reported in young people with features of borderline personality disorder (BPD). Examining sleep quality and sleep-wake patterns in young people with features of BPD is essential to inform the development of sleep-improvement interventions. A scoping review was conducted according to the Joanna Briggs Institute methodology. The objectives were to map the literature regarding sleep in young people with features of BPD, highlight areas for further investigation, and provide methodological recommendations for future research. Seven data sets were included in the review. Young people with features of BPD had poorer objective and subjective sleep quality, disturbed sleep architecture (particularly rapid-eye-movement sleep), an increased vulnerability to delayed sleep phase syndrome, and more nightmares and dream anxiety, compared with healthy individuals. Future research should use both objective and subjective sleep measures, include clinical comparison groups, and focus specifically on young people with BPD.

Neurobiology Youth Follow-up Study: protocol to establish a longitudinal and prospective research database using multimodal assessments for current and past mental health treatment-seeking young people within an early intervention service

IntroductionApproximately 75% of major mental illness occurs before the age of 25 years. Despite this, our capacity to provide effective, early and personalised interventions is limited by insufficient evidence for...

성인남녀의 두피·모발상태와 생활습관, 식습관, 탈모 인식도에 따른 관리행동에 관한 연구

This study attempted to investigate subjects’ general characteristics, self-diagnosis of scalp and hair conditions, perception of hair loss, dietary habit and lifestyle against 272 adult men and women living in Seoul, Incheon and Gyeonggi-go from October 20 to December 20, 2020 and compare their scalp & hair loss care behavior, and the results found the followings: In terms of a percentage of using natural shampoo and hair loss-care shampoo, a group with a high perception of hair loss was higher than a group with a low perception of hair loss (p<.05). In terms of the experience of scalp & hair loss care, the group with a high perception of hair loss was greater than the group with a low perception of hair loss (p<.01). When asked about their greatest effort to prevent hair loss, the group with a high perception of hair loss answered ‘careful selection of scalp & hair care products’ and ‘taking nutrients’ while the group with a low perception of hair loss said ‘stress management’ and ‘regular sleep-wake pattern’ (p<.05). Concerning effective scalp & hair loss care, ‘professional care’, ‘preventive care’ and ‘treatment’ were high with statistical significance in the group with a low perception of hair loss while ‘unnecessary (16.0%)’ was mostly responded in the group with a low perception of hair loss (p<.001).

Mental health and sleep habits/problems in children aged 3\u20134 years: a population study

BackgroundSleep is essential for mental health at all ages, but few studies have investigated the importance of sleep for mental health in early childhood. Therefore, this study examined the association between mental health and sleep habits/problems in children aged 3–4 years.MethodsChildren aged 3 to 4 years who were living in the community (n = 415; 211/204 boys/girls) were recruited for this study. Their mental health was assessed using the Strengths and Difficulties Questionnaire (SDQ), and their sleep habits/problems were evaluated using the Child and Adolescent Sleep Checklist.ResultsBased on the total difficulties score of the SDQ, the children were divided into two groups: a poor mental health group (n = 76) and a control group (n = 339). In terms of sleep habits, which included total sleep time, bedtime, wake time, and nap conditions, there were no differences between the two groups. Regarding sleep-related problems, however, anxiety before going to sleep (p = 0.026), circadian rhythm abnormalities (p = 0.014), and sleepiness during classes outside of naptimes (p = 0.031) were significantly higher in the poor mental health group than in the control group. Multiple regression analysis showed that poor mental health status was significantly associated with sleepiness and snoring (p = 0.017 and p = 0.018, respectively).ConclusionsThe mental health status of 3–4-year-old children was associated with sleep-related problems, namely sleepiness and snoring. Healthcare providers should pay attention to children’s irregular sleep-wake patterns; moreover, interventions for appropriate sleep hygiene will reduce the psychological burden on both children and their families.

Associations of circadian factors with insomnia symptoms and emotional and behavioral problems among school-age children.

To examine the associations of circadian characteristics (ie, chronotype and social jetlag) with insomnia symptoms and emotional and behavioral problems among school-age children. A total of 620 primary school children (medianage = 10.06, standard deviation = 1.16, 58.7% boys) were recruited and assessed by a set of parent-report questionnaires, including Children's Sleep Habit Questionnaire for measuring sleep-wake patterns and insomnia symptoms (bedtime resistance, sleep onset delay, and night waking), Children's Chronotype Questionnaire for assessing the child's chronotype preference, and Strength and Difficulties Questionnaire for assessing emotional and behavioral problems. Linear regression models were applied to examine the associations of chronotype and social jetlag with insomnia symptoms and mental health outcomes, in which age, sex, family income, and average sleep duration were entered as covariates. Evening chronotype was significantly associated with bedtime resistance and sleep onset delay, while social jetlag was not related to insomnia symptoms. Evening chronotype was also significantly associated with externalizing symptoms after controlling for potential confounders. Evening chronotype, but not social jetlag, was the risk factor for insomnia symptoms, and evening chronotype was further associated with increased behavioral problems in school-age children. Our findings underscored the roles of circadian factors in relation to sleep and mental health problems in this young population. Sun W, Kwok NTT, Chan NY, etal. Associations of circadian factors with insomnia symptoms and emotional and behavioral problems among school-age children. J Clin Sleep Med. 2021;17(10):2107-2114.

A six-factor structure of individual variation in the tendencies to become sleepy and to sleep at different times of the day

A multidimensional approach has been previously applied for modeling and assessment of individual differences in the ability to sleep or to stay awake at certain clock hours. More recently the 19 time-point Visuo-verbal Judgment Task (VJT) has been proposed to predict changes in sleepiness level from the morning hours to the next day afternoon. The dimensionality of the VJT has not been explored so far. We applied a structural model of individual variation in sleep-wake behavior and habits for explaining the pattern of relationship between the VJT's dimensions yielded by rotation of principal components with eigenvalue>1. The responses to 19 items of the VJT, 72 items of 6-scale Sleep Wake Pattern Assessment Questionnaire (SWPAQ) and 60 items of 6-scale Sleep-Wake Adaptability Test (SWAT) were collected from 1037 survey participants. Factor analyses yielded 4 factorial dimensions of morning (08:00–11:00), daytime (12:00–20:00), nighttime (21:00–04:00), and after 24 h sleepiness (06:00–12:00 next day). The model was found to be capable to explain the correlations among 4 constructs of the VJT as well as the correlations among previously developed scales of the SWPAQ and SWAT. The results confirmed the predictive power of the model and its applicability for multidimensional assessments in chronobiological and chronopsychological studies.

Subjective sleep quality, quantitative sleep features, and their associations dependent on demographic characteristics, habitual sleep\u2013wake patterns, and distinction of weekdays/weekends

Generally applicable qualifications of sleep and principles for achieving better sleep are difficult to design, because sleep quality can depend on individual demographic characteristics and lifestyles. In this study, the static and dynamic features of sleep–wake patterns were analyzed in association with quantitative sleep-related parameters and self-rated sleep quality to serve as a practical selection of sleep–wake patterns fitted to individual conditions. Data obtained over a 2-week period by actigraphy from university students and information technology workers were measured to obtain a daily subjective rating of sleep quality using the Oguri–Shirakawa–Azumi (OSA) sleep inventory. Qualitative sleep quality in terms of OSA score and quantitative sleep-related and chronobiological features were analyzed with regard to their dependency on the demographic characteristics, habitual sleep–wake patterns (HSWP), and distinction of weekdays/weekends. Multi-factor ANOVA was used to further investigate their dependencies regarding multiple ways of interactions between the demographic characteristics, HSWP, and distinction of weekdays/weekends. Subjective sleep quality and quantitative sleep-related parameters depended on the demographic characteristics, and so did their associations. The classification of day-to-day variations in HSWP showed four clusters that were effective factors for understanding their dependencies. Multi-factor analysis revealed demographic characteristics, HSWP, distinction of weekdays/weekends, and their multi-way interactions up to 3rd order as significant effectors of qualitative and quantitative quality of sleep. This study clarified how quantitative sleep-related parameters, subjective sleep quality, and their associations depended on demographic characteristics. Furthermore, their dependency was understood as a combination of multi-way interactions between the demographic characteristics, HSWP, and the distinction of weekdays/weekends. Our findings could provide a basis for the design of individually matched sleep–wake patterns.

Влияние режима сна и бодрствования на адаптационные возможности организма полярников в условиях антарктической зимовки

This article studies the influence of the sleep pattern (duration of uninterrupted sleep and rhythm of sleep periods) on the condition of the body’s adaptive resources during a year-round stay at a research station in Antarctica. We compared two cases that coincide in most parameters of daily life (living conditions, influence of environmental factors, level of social contacts, anthropometric data, and health status), but differ in terms of day regimen due to work activities. To assess the body’s adaptive capabilities, the index of regulatory and adaptive status (IRAS) was used, calculated by parameters obtained by the method of cardio-respiratory synchronism. The first subject (a radio operator) showed IRAS dynamics coinciding with deterioration and improvement of environmental conditions (daylight hours, weather conditions) affecting the Antarctic station staff, which was a predicted result. The second subject (a meteorologist) demonstrated a fundamentally different dynamics of the body’s adaptive capabilities: during deterioration of environmental conditions, the body’s adaptive resources increased due to lower work intensity and, as a result, a significant improvement in the sleep pattern. IRAS dynamics showed that the amount and quality of sleep has a more significant impact on human health than adverse weather conditions (storms). This opens up a wide range of opportunities to compensate for unavoidable adverse environmental conditions and help to preserve, as much as possible, the capacity for work in members of polar expeditions during wintering, as sudden decompensation can cause disruption to ongoing programmes at the research station. For citation: Dey V.A., Polishchuk S.V., Pokrovskiy V.M. Influence of Sleep–Wake Patterns on the Body’s Adaptive Capabilities During Antarctic Wintering. Journal of Medical and Biological Research, 2021, vol. 9, no. 2, pp. 138–144. DOI: 10.37482/2687-1491-Z051

Characterization of pharmaco-EEG fingerprint and sleep-wake profiles of Lavandula angustifolia Mill. essential oil inhalation and diazepam administration in rats

Ethnopharmacological relevanceLavandula angustifolia Mill. Essential oil (Lavender EO) has a long history of medicinal use and is particularly claimed to possess anxiolytic and sedative properties. Lavender EO aromatherapy has been used to reduce distress and improve insomnia naturally. Increasing evidence appeared to show similarities between the effects of lavender EO and the anxiolytic drugs, benzodiazepines. However, its effects on sleep-wake and electrical brain patterns in comparison to that of the standard anxiolytic, diazepam, remained to be explored. Aim of the studyThe aim of this work was to investigate electroencephalography (EEG) profiles and sleep-pattern elicited by lavender EO inhalation compared to that of diazepam, a standard anxiolytic drug in in vivo rat model. Materials and methodsAdult male Wistar rats were anesthetized for electrode implantation on the frontal and parietal skulls. EEG signals were recorded for 180 min following intraperitoneal injection of diazepam (10 mg/kg) or during continuous inhalation of lavender EO (200 μL) or distilled water (control). Fast Fourier transform was used for the analyses of EEG power spectra and sleep-wake parameters. ResultsDuring a 30–60 min period, diazepam and lavender EO significantly increased frontal powers of 0.78–45.31 and 7.03–18.36 Hz, respectively. Both treatments also increased parietal powers with lower magnitudes of significant change. Significant increases in some frequency ranges remained until a 60–90 min period. Sleep-wake analyses also revealed that diazepam significantly reduced time spent in wake, increased time spent in non-rapid eye movement (NREM), increased episode duration of NREM, decreased numbers of wake episode and decreased rapid eye movement (REM) sleep latency. On the other hand, lavender EO only significantly decreased wake episodes and latency to REM sleep. Lavender EO inhalation reduced numbers of wake episode but maintain normal time spent in wake, NREM and REM sleeps. ConclusionsThese findings might suggest beneficial and distinct anxiolytic-like effects of lavender EO for sleep enhancing purposes.

Validation of the Munich Actimetry Sleep Detection Algorithm for estimating sleep-wake patterns from activity recordings.

Periods of sleep and wakefulness can be estimated from wrist-locomotor activity recordings via algorithms that identify periods of relative activity and inactivity. Here, we evaluated the performance of our Munich Actimetry Sleep Detection Algorithm. The Munich Actimetry Sleep Detection Algorithm uses a moving 24-h threshold and correlation procedure estimating relatively consolidated periods of sleep and wake. The Munich Actimetry Sleep Detection Algorithm was validated against sleep logs and polysomnography. Sleep-log validation was performed on two field samples collected over 54 and 34days (median) in 34 adolescents and 28 young adults. Polysomnographic validation was performed on a clinical sample of 23 individuals undergoing one night of polysomnography. Epoch-by-epoch analyses were conducted and comparisons of sleep measures carried out via Bland-Altman plots and correlations. Compared with sleep logs, the Munich Actimetry Sleep Detection Algorithm classified sleep with a median sensitivity of 80% (interquartile range [IQR]=75%-86%) and specificity of 91% (87%-92%). Mean onset and offset times were highly correlated (r=.86-.91). Compared with polysomnography, the Munich Actimetry Sleep Detection Algorithm reached a median sensitivity of 92% (85%-100%) but low specificity of 33% (10%-98%), owing to the low frequency of wake episodes in the night-time polysomnographic recordings. The Munich Actimetry Sleep Detection Algorithm overestimated sleep onset (~21min) and underestimated wake after sleep onset (~26min), while not performing systematically differently from polysomnography in other sleep parameters. These results demonstrate the validity of the Munich Actimetry Sleep Detection Algorithm in faithfully estimating sleep-wake patterns in field studies. With its good performance across daytime and night-time, it enables analyses of sleep-wake patterns in long recordings performed to assess circadian and sleep regularity and is therefore an excellent objective alternative to sleep logs in field settings.

Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes.

The purpose of this study was to describe objective sleep-wake characteristics and glycemia over 7-14 days in young adults with type 1 diabetes. In addition, person-level associations among objective sleep-wake characteristics (total sleep time, sleep variability, and sleep fragmentation index), daytime sleepiness, and glycemia (glycemic control and glucose variability) were examined. In this cross-sectional study, objective sleep-wake characteristics were measured via actigraphy and glucose variability via continuous glucose monitoring over 6-14 days. At baseline, participants completed the Psychomotor Vigilance Test, the Trail Making Test, and questionnaires on daytime sleepiness, sleep quality, and sleep disturbance including sleep diaries. Forty-six participants (mean age, 22.3 ± 3.2 years) wore a wrist actigraph and underwent continuous glucose monitoring concurrently for 6-14 days. Greater sleep variability was directly associated with greater glucose variability (mean of daily differences; r = .33, P = .036). Higher daytime sleepiness was directly associated with greater glucose variability (mean of daily differences; r = .50, P = .001). The association between sleep variability and glucose variability (mean of daily differences) was no longer significant when accounting for daytime sleepiness and controlling for type 1 diabetes duration (P > .05). A higher sleep fragmentation index was associated with greater glucose variability (B = 1.27, P = .010, pr2 = 0.40) after controlling for type 1 diabetes duration and accounting for higher daytime sleepiness. Sleep-wake variability, sleep fragmentation, daytime sleepiness, and the associations with glycemia are new dimensions to consider in young adults with type 1 diabetes. Sleep habits in this population may explain higher glucose variability, and optimizing sleep may improve overall diabetes management. Griggs S, Hickman RL Jr, Strohl KP, Redeker NS, Crawford SL, Grey M. Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes. J Clin Sleep Med. 2021;17(9):1865-1874.

549 Associations of Bedtime, Wake-time and Employment Status by Gender and Race

Abstract Introduction Poor sleep quality has been reported in the unemployed compared with employed. How sleep varies by employment status has been rarely examined at a population level. Therefore, we investigated sleep-wake patterns among employed, unemployed but actively seeking a job, and not-in-the-labor-force participants by gender and race/ethnicity. Methods Methods We used data from the American Time Use Survey (ATUS), a nationally representative sample of US residents aged ≥15years, which records weekday/weekend activities in a 24-hour period (4:00am-4:00am). This sample was restricted to participants aged 25–60 years (n=130,062). This analysis utilized functional nonparametric regression based on dimension reduction and neighborhood matching. We modeled the relationship between participant-specific sleep-wake trajectories, coded by minute, and employment status. Implementing the counterfactual approach, we estimated the effects of each employment scenario on participant-level expected sleep trajectory. This approach allowed the examination of hypothetical sleep-wake trajectories for each participant if their employment status differed from the observed. We then marginalized these findings to gender and race/ethnic subpopulations, controlling for confounders and secular trends. Results Mean age was 42□0.01 years, nearly half (51%) of participants were women and 68% were Whites. The proportions of employed, unemployed, and not-in-the-labor-force were 79%, 16.5% and 4.5%, respectively. On average, unemployed and not-in-the-labor-force participants had a later bedtime and wake-time compared with employed. With the exception of Whites, each individual race/ethnicity group showed pronounced differences in sleep-wake patterns by employment status. Of note, the likelihood of still being asleep up to 9:00am was greater when unemployed in comparison to had they been employed. Compared with employed, differences in sleep-wake patterns were pronounced among Blacks and Hispanics had they been unemployed, but attenuated if they were out-of-the-labor-force. Gender alone was not a strong moderator of the relationship between sleep-wake patterns and employment status. Unemployed participants had bedtime after 11pm, regardless of gender or race/ethnicity. Conclusion Using the counterfactual approach, we predicted sleep-wake patterns among individuals had they been employed, unemployed, or out-of-the-labor-force by gender and race/ethnicity. Though cross-sectional, our data suggest that the sleep schedules of racial/ethnic minorities in comparison to Whites may be more affected by employment status. Support (if any):

685 Sleep Latency, Pre and Peri-COVID-19 Experiences and PTSD Symptoms: Results from the NYU COVID-19 Mental Health Study

IntroductionAn effective response to the COVID-19 pandemic has been the decision to subject individuals residing in New York City to quarantine rules in order to reduce the spread of the virus. As might have been expected, restriction of usual daily activities would affect individuals’ sleep-wake patterns. It is also known that exposure to traumatic experiences can also engender sleep disturbances, most notably in their ability to initiate sleep. This study investigated the associations between sleep onset latency (SOL), pre and peri-COVID-19 exposure and symptoms of posttraumatic stress disorder (PTSD) among New Yorkers.Methods541 individuals (female = 373(69%); mean age=40.9) were recruited during the summer and fall of 2020 in New York City to participate in the NYU-COVID-19 Mental Health Study. Participants provided sociodemographic data and were also asked to respond to the COVID-19 quarantine experiences, comprised of seven binary questions, the PTSD Checklist-PCL-5, and the Pittsburg Sleep Quality Index. Descriptive and linear regression analysis were performed to explore associations of scores on the COVID-19 quarantine experience with PTSD and sleep data. All analyses were performed using SPSS 25.0ResultsRegression analyses revealed that SOL emerged as the strongest independent predictor of PTSD symptoms [B(t) = −.630(12.7); p < .001]; factors adjusted in the model included pre and peri-covid-19 factors such as age, sex, job type, and quarantine experience. Analyses assessing potential interaction effect revealed that quarantine experience did not affect the relationship between SOL and PTSD [B(t) = .086(.831); p = >.005]. The other sleep factors in the model did not yield significance. sleep duration had a weak correlation with quarantine, it was not found to be a predictor of PTSD.ConclusionWe observed that SOL was the most important determinant of PTSD symptoms among individuals exposed to COVID-19. This is consistent with other findings suggesting that a sizable proportion of individuals exposed to pandemics are likely to experience sleep disturbances. It is plausible that quarantine might lead to increased daytime naps, which may impact SOL. Further research is needed to better understand the association of SOL and PTSD as a result of Covid-19.Support (if any)K07AG052685, R01MD007716, R01HL142066, T32HL129953, K01HL135452, R01HL152453

Brain Tumours Involving the Areas of the Circadian System Result in Disturbances in Melatonin Secretion, Fatigue and Poor Quality of Life

Background: Sleep disturbances, circadian abnormalities and poor health are often reported in children with brain tumours. The objective of this study was to examine circadian function, sleep pattern, fatigue and mental health in these children. We hypothesized that children with tumours involving the areas of the circadian system have altered melatonin secretion. Design: Cross-sectional study. Methods: 309 children diagnosed with a tumour in the brain or cervical medulla and aged ≤18 years were identified, 174 met the inclusion criteria, and 68 consented to participate. They were divided according to their tumour location into 1) location involving the areas of the circadian system, i.e. diencephalon, pineal gland, brain stem and cervical medulla and 2) other areas. Sleep-wake patterns were assessed by two weeks of sleep diary recordings and actigraphy in 66 and 61 children, respectively. Diurnal saliva-melatonin levels were measured in 51 children. Sleep quality, fatigue and mental health were assessed in 65 children by Children’s Sleep Habits Questionnaire, Strengths and Difficulties Questionnaire and Pediatric Quality of Life Inventory, Multidimensional Fatigue Scale and Generic Core Scale. Results: All children had normal sleep-wake patterns without significant between-group differences. The children with tumours involving the areas of the circadian system had lower melatonin peak levels (p=0.03) and a tendency of lower levels at 00 h and 04 h (all p=0.06). Three patterns of diurnal melatonin profiles were observed: Normal, low peak and phase-shifted peak. In comparison of the two patient groups, more children with tumours involving the areas of the circadian system had melatonin profiles with low peak values (29% vs 13%) and one had phase-shifted peak (3% vs 0%), although not significant. These children were more affected by mental problems (p<0.01), more cognitive fatigued (p=0.03) and had poorer quality of life (p=0.01) than children with tumours located elsewhere. Conclusion: Children with tumours affecting the areas of the circadian system including the diencephalon, pineal gland, brain stem and cervical medulla have altered melatonin secretion, are fatigued, have poor mental health and poor quality of life. Circadian disturbances may adversely affect health and have negative psychological impact.

Determination of the sleep-wake pattern and feasibility of NREM/REM discrimination using the non-invasive piezoelectric system in rats.

The piezoelectric cage-floor sensors have been used to successfully dissect sleep patterns in mice based on signal features related to respiration and body movements. We studied performance of the piezoelectric system to quantify the sleep-wake pattern in the rat over 7days of recording compared with a visual electroencephalogram/electromyogram scoring, and under two light/dark (LD12:12 and LD16:8) photoperiods leading to change in the 24-hr sleep characteristics (N=7 per group). The total sleep time (%/24hr) over the 7days recording and hourly sleep time over the last 24-hr recording were not statistically different between methods under the two photoperiods. Both methods detected higher total sleep time with the LD16:8 photoperiod compared with LD12:12 (p<.05), and correlated significantly (p<.001) at light and dark periods during each photoperiod. The accuracies for discrimination of sleep-wake patterns between methods were 81.9% and 84.9% for LD12:12 and LD16:8, respectively. In addition, spectral analysis of the respiratory signal given by piezo during all 10-s periods of the corresponding non-rapid eye movement and rapid eye movement sleep periods recorded by electroencephalogram/electromyogram resulted in selection of 36 features that could be inserted in an automated non-rapid eye movement sleep and rapid eye movement sleep classification, with 90% accuracy with the electroencephalogram/electromyogram visual scoring. The piezo system proved to be a reliable non-invasive alternative to electroencephalogram recording to study total sleep time in rat, with feasibility to discriminate between non-rapid eye movement and rapid eye movement sleep stages. This will be interesting in pharmacological or bio-behavioural studies evaluating sleep patterns or the restorative functions of sleep in the body and the brain.