Differences In Sleep Patterns Research Articles

Differences In Sleep Patterns Between College Varsity Athletes And Non-athlete Controls Disappear In Midlife

Differences In Sleep Patterns Between College Varsity Athletes And Non-athlete Controls Disappear In Midlife

Sleep During the COVID-19 Pandemic: Longitudinal Observational Study Combining Multisensor Data With Questionnaires.

The COVID-19 pandemic prompted various containment strategies, such as work-from-home policies and reduced social contact, which significantly altered people's sleep routines. While previous studies have highlighted the negative impacts of these restrictions on sleep, they often lack a comprehensive perspective that considers other factors, such as seasonal variations and physical activity (PA), which can also influence sleep. This study aims to longitudinally examine the detailed changes in sleep patterns among working adults during the COVID-19 pandemic using a combination of repeated questionnaires and high-resolution passive measurements from wearable sensors. We investigate the association between sleep and 5 sets of variables: (1) demographics; (2) sleep-related habits; (3) PA behaviors; and external factors, including (4) pandemic-specific constraints and (5) seasonal variations during the study period. We recruited working adults in Finland for a 1-year study (June 2021-June 2022) conducted during the late stage of the COVID-19 pandemic. We collected multisensor data from fitness trackers worn by participants, as well as work and sleep-related measures through monthly questionnaires. Additionally, we used the Stringency Index for Finland at various points in time to estimate the degree of pandemic-related lockdown restrictions during the study period. We applied linear mixed models to examine changes in sleep patterns during this late stage of the pandemic and their association with the 5 sets of variables. The sleep patterns of 27,350 nights from 112 working adults were analyzed. Stricter pandemic measures were associated with an increase in total sleep time (TST) (β=.003, 95% CI 0.001-0.005; P<.001) and a delay in midsleep (MS) (β=.02, 95% CI 0.02-0.03; P<.001). Individuals who tend to snooze exhibited greater variability in both TST (β=.15, 95% CI 0.05-0.27; P=.006) and MS (β=.17, 95% CI 0.03-0.31; P=.01). Occupational differences in sleep pattern were observed, with service staff experiencing longer TST (β=.37, 95% CI 0.14-0.61; P=.004) and lower variability in TST (β=-.15, 95% CI -0.27 to -0.05; P<.001). Engaging in PA later in the day was associated with longer TST (β=.03, 95% CI 0.02-0.04; P<.001) and less variability in TST (β=-.01, 95% CI -0.02 to 0.00; P=.02). Higher intradaily variability in rest activity rhythm was associated with shorter TST (β=-.26, 95% CI -0.29 to -0.23; P<.001), earlier MS (β=-.29, 95% CI -0.33 to -0.26; P<.001), and reduced variability in TST (β=-.16, 95% CI -0.23 to -0.09; P<.001). Our study provided a comprehensive view of the factors affecting sleep patterns during the late stage of the pandemic. As we navigate the future of work after the pandemic, understanding how work arrangements, lifestyle choices, and sleep quality interact will be crucial for optimizing well-being and performance in the workforce.

Social Jetlag on Obesity-Related Outcomes in Spanish Adolescents: Cross-Sectional Evidence from the EHDLA Study.

This study aimed to investigate the association between social jetlag (SJL) and obesity-related outcomes among adolescents from Valle de Ricote (Region of Murcia, Spain). We explored the relationship between SJL and body mass index (BMI) z-score, waist circumference, and body fat percentage, as well as the odds of having excess weight, obesity, and abdominal obesity in a sample of Spanish adolescents. A cross-sectional study was conducted using data from the Eating Healthy and Daily Life Activities (EHDLA) project, which included 847 Spanish adolescents aged 12-17 years. SJL was assessed based on the differences in sleep patterns between weekdays and weekends. Obesity-related indicators such as BMI z-score, waist circumference, body fat percentage, excess weight, obesity, and abdominal obesity were measured. Generalized linear models with a Gaussian or binomial distribution were used to analyze the associations between SJL and obesity-related outcomes, adjusting for potential confounders. The analysis revealed significant associations between SJL and BMI z-score (unstandardized beta coefficient [B] = 0.15, 95% CI: 0.05 to 0.25, p = 0.003), waist circumference (B = 1.03, 95% CI: 0.39 to 1.67, p = 0.002), and body fat percentage (B = 0.83, 95% CI: 0.31 to 1.43, p = 0.008). Additionally, the odds ratios (ORs) for excess weight (OR = 1.35, 95% CI: 1.16 to 1.57; p < 0.001), obesity (OR = 1.59, 95% CI: 1.26 to 2.00; p < 0.001), and abdominal obesity (OR = 1.46, 95% CI: 1.23 to 1.72; p < 0.001) increased significantly with each 60 min increment in SJL. This study pointed out that the misalignment of sleeping times during weekdays and weekends (SJL) is significantly associated with higher BMI z-scores, waist circumference, body fat percentage, and higher odds of excess weight, obesity, and abdominal obesity among adolescents, being more significant in boys than in girls. These findings highlight the importance of addressing circadian misalignment in the prevention and management of obesity and its related metabolic disorders in this population.

Longitudinal associations between biopsychosocial stress indicators and sleep in older Puerto Rican adults

ObjectivesTo examine the association of biopsychosocial stress indicators (perceived stress, perceived discrimination, stressful life events, and allostatic load) with sleep outcomes (sleep duration and insomnia symptoms) and to examine sex and age interactions for associations between stress and sleep in older Puerto Rican adults. MethodsSecondary analyses were performed with 830 participants (72% female) from wave 2 (2006-2011) of the Boston Puerto Rican Health Study (BPRHS), a prospective population-based cohort study (45-75years at baseline) and Boston Puerto Rican Osteoporosis Study (BPROS) (2007-2012), an ancillary study of the BPRHS. Recruitment occurred in randomly selected census blocks using door-to-door and community-based activities. In-home data collection visits included a baseline assessment and follow-up interviews. Questionnaires assessed perceived stress, discrimination, stressful life events, and sleep. Allostatic load indicators were measured objectively. Regression models controlled for sociodemographic, behavioral, and health factors, with interaction analyses, followed by sex- and sex-by-age-stratified analyses. ResultsIn the prior 2years, participants with chronic stress had 50% greater odds of reporting nonoptimal sleep duration (<7 or >9 hours). Life events trajectories were significantly related to insomnia symptoms. Men ≥65years who experienced chronic stress had greater insomnia symptoms than women, or than men with low stress or acute stress. ConclusionsStressful life events may affect sleep duration and insomnia symptoms among older Puerto Rican adults, particularly men 65 years and older who experienced chronic stress. Given the differences in sleep patterns experienced by older adults and their relationships with health outcomes, identifying methods to support sleep health among those with chronic stress is important.

Sleep characteristics in underweight young females across their menstrual cycles: A sleep-monitoring survey study with preliminary results.

This study investigated the association between underweight and sleep in young females across their menstrual cycles. A lifestyle-monitoring survey was conducted among 38 female university students aged 18-24 years in Japan from January to December 2023. Sleep data from 28 participants were analysed. Participants were categorized into underweight (n = 10) and control (n = 18) groups based on a baseline body mass index cut-off of 18.5 kg m-2. Sleep parameters were assessed using a daily sleep questionnaire, sleep sensor mats, and urinary melatonin metabolites across their menstrual cycles. The results indicated no significant differences in sleep patterns between the underweight and control groups or menstrual cycle phases, as assessed using both the daily sleep questionnaire and the sleep sensor mats. However, underweight participants experienced more difficulty maintaining sleep during the follicular phase. Body mass index significantly correlated with sleep efficiency (rs = 0.52) and wake after sleep onset (rs = -0.56). While urinary melatonin metabolite levels did not differ significantly between the groups or menstrual cycle phases, decreased levels during the luteal phase were more prevalent in the underweight group (7 of 10 participants) than in the control group (3 of 13 participants). This study suggests an association between underweight and sleep quality, especially nocturnal awakening, in young females. These findings underscore the importance of considering sleep quality in the management of underweight young females to improve their overall health outcomes.

Sleep Patterns in Patients After Solid Organ Transplantation Including Gender and Age Differences. Survey Results From One Transplantation Centre in Poland

Sleep plays a crucial role in maintaining health. Transplant patients are exposed to numerous stressors and are at risk of sleep disturbances. The aim of this study was to assess the sleep patterns of transplant patients. An anonymous paper survey was carried out among patients from one transplant center in Poland. Respondents were asked about the quality and quantity of sleep and the overall impact of the transplantation on their night rest. Data were collected from June to November 2023. Data were obtained from 212 respondents (122 males and 90 females), aged 48.38 ± 13.68. The positive impact of transplantation on sleep hygiene was indicated by 57.4% of respondents, 28.9% observed no impact, and 13.6% rated the impact as negative. Our study showed that sleep is more satisfying in males than in females (62.8% of males and 46.7% of females). The analysis revealed that 38.9% of females need 30 minutes more than men to fall asleep. Additionally, females tend to get up half an hour later compared to men. About 71.9% of males declared good well-being the next day compared to 62.2% of females. Furthermore females declared more sleepiness the next day. The study also showed that older transplant recipients (over 50 years-of-age) report more frequent awakenings at night. The data collected showed differences in sleep patterns according to gender and age. Females and older patients should be screened for sleep disturbances during post-transplantation care.

Everyday Discrimination and Sleep Among Migrant and Non-migrant Filipinos: Longitudinal Analyses from the Health of Philippine Emigrants Study (HoPES).

This study aimed to (1) identify differences in sleep patterns between Filipino migrants and non-migrants across 2 years and (2) explore the impact of discrimination trajectories on sleep trajectories. The Health of Philippine Emigrants Study (HoPES) consisted of a migrant (n = 832) and non-migrant cohort (n = 805), with baseline data collected in the Philippines. Both cohorts were followed longitudinally, with the non-migrants followed in the Philippines and the migrant cohort followed to the United States. Sleep duration, quality, and difficulty were assessed with the National Institutes of Health Patient-Reported Outcomes Information System (PROMIS) inventory, and discrimination was measured with an adapted version of the Everyday Discrimination scale. Migrants reported a faster decline in sleep duration (-12min a year) but higher sleep quality than non-migrants over 2 years. Migrants who reported high initial levels of everyday discrimination also reported faster declines in sleep duration and a slower decline in sleep difficulty. Further, migrants who reported stable (versus declining) levels of discrimination over 2 years reported a faster decline in sleep quality. These results speak to the complexity of immigrant health patterns and long-term associations between discrimination and sleep processes.

Onsite versus home-office: differences in sleep patterns according to workplace.

This study aimed to evaluate the sleep patterns of students and employees working onsite versus those working from home during the COVID-19 pandemic using actigraphy. A total of 75students/employees (onsite: N = 40, home-office: N = 35; age range:19-56years; 32% male; 42.7% students, 49.3% employees) were studied between December2020 and January2022 using actigraphy, asleep diary, and an online questionnaire assessing sociodemographics and morningness-eveningness. Independent-sample t-tests, paired-sample tests, and amultivariate general linear model adjusting for age (fixed factors: sex and work environment) were applied. Overall, onsite workers had significantly earlier rise times (7:05 [SD: 1:11] versus 7:44 [1:08] hours) and midpoints of sleep (2:57 [0:58] versus 3:33 [0:58] hours) on weekdays compared to home-office workers. Sleep efficiency, sleep duration, variability of sleep timing, and social jetlag did not differ between the groups. Home-office workers showed adelay in sleep timing that did not affect any other sleep parameters such as sleep efficiency or nighttime sleep duration. The work environment had only marginal impact on sleep patterns and thus sleep health in this sample. Sleep timing variability did not differ between groups. The online version of this article (10.1007/s11818-023-00408-5) contains supplementary material1 and2, which is available to authorized users.

0249 Individual differences of sleep pattern and duration between two consecutive night shifts among night workers

Abstract Introduction Working at night leads to shortened and disturbed daytime sleep. Night workers usually adopt one of several sleep patterns between consecutive nights: sleeping right after night work (morning sleep), delaying sleep to the afternoon (afternoon sleep), or dividing sleep into two or more episodes (split sleep). However, few studies have examined sleep pattern and duration between consecutive nights in real-world workers. The objective of this study was to examine individual differences in sleep pattern and duration when working consecutive night shifts. Methods Night workers (n=241, 43.0±16.5y, 67.2% female) from various occupations who reported working consecutive nights completed an online survey. The survey included questions on socio-demographics and daytime sleep and nap schedules. Sleep pattern (morning vs. afternoon vs. split) and total sleep time (sleep+naps) were derived from survey responses. Cross-tabulations and ANOVA were conducted. Results On average, night workers reported a total daytime sleep of 5.37±2.69 hours (range 0-14.25 hours). 65.1% reported morning sleep, 10% afternoon sleep, and 24.9% split sleep. Split sleepers (6.78±2.13 hours) reported longer total sleep than morning (4.86±2.75 hours) or afternoon (5.11±2.37 hours) sleepers. Younger age (&amp;lt; 50y), single marital status, shorter night shift tenure (≤10 years), working ≤3 consecutive shifts, and having ill or disabled dependents were associated with greater prevalence of morning sleep; older age (≥50y), married or separated/widowed, &amp;gt;10 years night shift tenure, working ≥4 consecutive shifts, and having no dependents were associated with greater prevalence of afternoon or split sleep. Having childcare responsibility was associated with more split sleep than no children. Similarly, younger age (&amp;lt; 50y), singles, shorter night shift tenure, working three or fewer consecutive shifts, having ill or disabled dependents, and having a second job were associated with shorter total sleep. However, having childcare responsibility was associated with greater total sleep. Conclusion Sleep timing and duration between consecutive nights were influenced by age, marital status, dependents, night work tenure, and number of consecutive night shifts. Future studies are needed to explore what sleep pattern is most beneficial for sleep, performance, safety, and health outcomes of these workers. Support (if any) The study was supported by grant R01 AG044416 from the US National Institutes of Health.

Differences in sleep patterns between patients with anorexia nervosa and healthy controls: a cross-sectional study

BackgroundSleep difficulties are common in patients with anorexia nervosa (AN), but objective assessments have mostly been performed in hospital and laboratory settings. We aimed to identify differences in sleep patterns between patients with AN and healthy controls (HC) in their free-living environments, and potential associations between sleep patterns and clinical symptoms in patients with AN.MethodsThis cross-sectional study analyzed 20 patients with AN prior to them starting outpatient treatment and 23 HC. Sleep patterns were measured objectively using an accelerometer (Philips Actiwatch 2) for 7 consecutive days. Average sleep onset, sleep offset, total sleep time, sleep efficiency, wake after sleep onset (WASO) and mid-sleep awakenings lasting ≥ 5 min were compared between patients with AN and HC using nonparametric statistical analyses. Associations of sleep patterns with body mass index, eating-disorder symptoms, eating-disorder-associated impairment, and symptoms of depression were assessed in the patient group.ResultsCompared with HC, patients with AN had shorter WASO [median (interquartile range(IQR)): 33 vs. 42 min], but a longer average duration of mid-sleep awakenings lasting ≥ 5 min [median (IQR): 9 vs. 6 min, p = 0.006] and had more nights with no sleep (six nights in four patients with AN vs. zero nights in HC). There were no differences between patients with AN and HC regarding other sleep parameters and no significant correlations between sleep patterns and clinical parameters in patients with AN. However, HC presented a Intraindividual variability pattern that was closer to a normal distribution, whereas patients with AN tended to either have very regular or large variability in sleep onset time (AN; n = 7 < 25th percentile and n = 8 > 75th percentile vs. HC; n = 4 < 25 percentile and n = 3 > 75th percentile) during the week of sleep recordings.ConclusionPatients with AN seem to spend more time awake during the night and have more nights without sleep than do HC, even though their average weekly sleep duration did not differ from that in HC. The intraindividual variability in sleep pattern seems to be an important parameter that should be assessed when studying sleep in patients with AN.Trial registration ClinicalTroals.gov. Identifier: NCT02745067. Registered: April 20, 2016.

Gambaran Pengetahuan Siswa Tentang Gangguan Pola Tidur di MAN Model Palangka Raya

Sleep is a basic need for everyone so that the body can function normally after its daily activities. In adolescents there are changes in sleep patterns, including reduced sleep duration, delayed bedtime, and differences in sleep patterns on weekdays and weekends. Thus, the quality of adolescent sleep also tends to be reduced or disrupted. There are several serious consequences of sleep disturbances such as excessive daytime sleepiness, impaired attention and memory, depression, frequent falls, inappropriate use of hypnotics, and decreased quality of life. The purpose of this study was to determine the level of students' knowledge about sleep pattern disturbances at the Palangka Raya Model MAN in good, adequate and poor levels. This study uses a quantitative descriptive method. The population in this study were students at the Palangka Raya Model MAN in the 2020/2021 academic year. The sampling technique used was total sampling with a total sample of 90 respondents. The instrument used was a closed questionnaire. Based on the results of the study, it was obtained an overview of students' knowledge about sleep pattern disturbances in the good category of 78 people, the sufficient category of 12 people and no respondents in the less category. Based on the results of the study, it was shown that most of the students' knowledge of the Palangka Raya MAN Model regarding sleep disturbances was good, namely a number of 78 people. Suggestions for future researchers are to be able to develop this research so as to obtain varied research results.

Sleep Patterns during the COVID-19 Lockdown in Spain.

To mitigate the spread of the coronavirus disease (COVID-19) pandemic, governments around the world adopted exceptional lockdown measures. This led to the disruption of normal life routines, including sleep. The aim of this study was to analyze differences in sleep patterns and subjective variables of sleep quality before and during lockdown. A sample of 1673 Spanish adults (30% men; 82% of the total were between 21 and 50 years of age) was evaluated. The following sleep variables were evaluated: Sleep latency, sleep time, number and duration of awakenings, sleep satisfaction, daytime sleepiness, and the manifestation of symptoms related to sleep problems. Although 45% of people changed their sleep schedules (resulting in 42% sleeping longer during lockdown), sleep quality (37.6% worse), daytime sleepiness (28% worse), number of awakenings (36.9% more), and duration of awakenings (45% longer) were markedly worse. Statistical analyses indicated significant differences in all the evaluated sleep variables before and during lockdown in both men and women. Women reported less sleep satisfaction, and more symptoms related to sleep problems than men. A deterioration in the sleep patterns of the Spanish population, especially women, because of the lockdown declared due to the COVID-19 pandemic.

Nighttime sleep duration and variability in children with obstructive sleep apnea syndrome: Sociodemographic disparities and neurobehavioral outcomes

ObjectivesThis study examined differences in sleep patterns by race, ethnicity, and socioeconomic status (SES) among children with Obstructive Sleep Apnea Syndrome (OSAS), and linkages between sleep patterns and neurobehavioral functioning. MethodWe used baseline data from the Childhood Adenotonsillectomy Study (CHAT), a multicenter, single-blind, randomized controlled trial designed to evaluate the efficacy of early adenotonsillectomy versus watchful waiting with supportive care for children with OSAS. Participants included children with OSAS (ages 5.0–9.9 years). SES indicators were obtained via questionnaire and geocoding (ArcGIS version 10.1). Caregivers and teachers reported on child inattention/impulsivity and executive functioning. Nighttime sleep duration and variability were measured using five-night sleep diaries. ResultsBlack children experienced shorter nighttime sleep duration than White children, by about 25 min, as well as greater sleep duration variability, while sleep duration was more variable in children of “other” racial and ethnic backgrounds versus White children. Of the socioeconomic correlates, only lower family income was associated with sleep duration variability. A short and more variable nighttime sleep duration were each associated with caregiver-rated child inattention and impulsivity. Greater sleep duration variability was linked to greater teacher-rated, but not caregiver-rated, executive functioning impairments. ConclusionsCompared to White children with OSAS, Black children with OSAS experience a shorter and more variable nighttime sleep duration. Having a short and/or variable sleep duration may increase risk for neurobehavioral impairments in youth with OSAS, underscoring the potential benefits of sleep health promotion in the context of OSAS care.

Variations in Sleep Architecture among Different Subtypes of Schizophrenia: A Cross-sectional Study

Introduction: Schizophrenia is a severe mental disorder characterised by positive symptoms such as delusions and hallucinations, as well as negative symptoms including anhedonia, asociality, avolition, and affective blunting. It may also be associated with cognitive deficits. Sleep disturbances are commonly encountered in schizophrenia, and there may be variations in sleep patterns among its different subtypes. These differences in sleep patterns could have prognostic implications for the various subtypes of schizophrenia. Effective management of sleep disturbances could contribute to the recovery and wellbeing of individuals diagnosed with schizophrenia. Aim: To compare the differences in sleep architecture between the various subtypes of schizophrenia and to compare them with socio-demographically matched healthy volunteers. Materials and Methods: A cross-sectional study was conducted at the Institute of Psychiatry-Centre of Excellence, Kolkata, West Bengal, India over a duration of one year (May 2016 to June 2017). The study included 60 medication-naïve patients diagnosed with schizophrenia according to International Classification of Diseases (ICD)-10 criteria, and a control group of 30 demographically matched healthy volunteers. All study participants were aged between 18 and 60 years and free from any co-morbid illnesses. Patients with schizophrenia were further classified into four groups based on the ICD-10 subtypes: paranoid, hebephrenic, catatonic, and undifferentiated. Overnight polysomnography was performed to assess sleep parameters, including total record time, total sleep time, sleep onset latency, Rapid Eye Movement (REM), sleep latency, sleep efficiency, durations of Total Non Rapid Eye Movement (NREM) Sleep, Total REM sleep, and the different phases of NREM sleep. Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) version 20.0. Analysis of Variance (ANOVA), Chi-square, and t-test were used as applicable, with a p-value &lt;0.05 considered statistically significant. Results: The results showed a decrease in sleep efficiency, total sleep time, and shorter duration of mean N1, N2, and N3 sleep in schizophrenia patients compared to the control group. There was a significant difference in N3 sleep duration, reduced duration of total NREM and REM sleep, reduced REM latency, increased sleep onset latency, and the number of awakenings during sleep in schizophrenia patients. Statistically significant differences (p-values &lt;0.05) were also noted in some sleep parameters among the various subtypes of schizophrenia. The paranoid subtype had the shortest REM latency, while the catatonic subtype had the longest. The hebephrenic subtype had the lowest percentage of REM sleep and sleep efficiency, while the catatonic subtype had the highest. The duration of Slow Wave Sleep (SWS) was lowest in the undifferentiated subtype and highest in the catatonic subtype. Conclusion: This study reveals significant differences in sleep patterns between patients with schizophrenia and the control group, as well as among the various subtypes of schizophrenia. These distinctions provide insight into the relationship between schizophrenia subtypes, sleep irregularities, and clinical consequences. Further investigation is necessary to explore differences in sleep architecture among the various subtypes of schizophrenia and yield clinically meaningful results.

The Relationship of Sleep and Pain in Pediatric Sickle Cell Disease

Background: Pain interference and sleep problems (sleep disturbance and sleep-related impairment) are prevalent complications experienced by pediatric patients living with sickle cell disease (SCD). If sleep problems contribute to increased pain interference, sleep-directed behavioral interventions could be an additional non-opioid approach to minimizing pain in SCD patients. We hypothesized that sleep disturbance and sleep-related impairment are associated with an increase in pain interference. Second, we studied the prevalence of a later chronotype (preferred timing of sleep) and social jetlag (difference in sleep patterns during the week and weekend), which are measures of circadian sleep patterns, in pediatric patients with SCD. Methods: We performed a IRB approved cross-sectional survey of pediatric patients with SCD aged 8-17 years at a single clinic visit using PROMIS (Patient Reported Outcomes Measurement System) pain interference, sleep disturbance and sleep-related impairment item banks, which utilize T-scores to measure the severity of these parameters; greater scores in each domain signify greater severity. The µMCTQ (ultra-short Munich Chronotype Questionnaire) assessed mid-sleep time (a proxy for chronotype) and social jetlag. Analyses were performed to assess associations between PROMIS measures, sleep patterns and clinical variables using JMP Pro16 (Cary, NC). Results: One hundred and five patients (mean age: 13.1±2.6 years; 53 male, 52 female) completed the PROMIS sleep and pain measures. All participants approached completed the PROMIS evaluation for pain and sleep. The majority of patients (81.9%) were diagnosed with either HbSS or HbSβ0 -thalassemia and 61% were on hydroxyurea (alone or with an additional sickle cell modifying therapy). Pain interference was significantly associated with both sleep disturbance (r=0.49, p<0.0001) and sleep-related impairment (r=0.46, p<0.0001). In multivariate analysis for pain interference, both sleep disturbance (p=0.0007) and sleep-related impairment (p=0.006) remained in the model. Females participants reported higher T-scores for sleep-related impairment than males (females: 56.7± 10 vs males 50.2± 9.4, p=0.0009). Patients with one or more ED visits for pain in the last year reported greater sleep disturbance (55.0±8.5 vs 50.7± 10, p=0.046) and sleep-related impairment (57.1± 9.3 vs 52.1± 10.2, p=0.026) (Figure). The average mid-sleep time (clock time) was 4:14 ± 1:44 AM and the average social jetlag (hh:mm) was 2:32 ± 1:35. Conclusion: Pain interference is associated with both sleep disturbance and sleep-related impairment and our 100% acceptance rate for completing PROs highlights the clinical importance of performing formal sleep and pain assessments. A longitudinal examination of sleep and pain in pediatric SCD patients is needed to determine if sleep problems and pain have a bi-directional relationship. Furthermore, the high prevalence of later mid-sleep times and social jetlag in this sample suggests that longitudinal studies should incorporate measures of sleep timing and social jetlag impact on pain. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Automated sleep detection reveals differences in sleep patterns in an animal model of neocortical epilepsy.

Sleep in epilepsy is best studied in longitudinal preclinical animal models, where state changes can have significant effects on epileptic activities. Voluminous data makes it very difficult to mark sleep stages manually. This demands an automated way to detect sleep and wake states. We developed an approach to characterize sleep-wake states in continuous video-electroencephalography (EEG) recordings in animals. We compared brute force approach based on frequency band-power based thresholding with machine learning algorithms to detect sleep in 600 hours of EEG data from 4 epileptic and 2 control animals. We found that conventional delta and theta band-powers were prominent in sleep; however, this was not sufficient to detect sleep algorithmically. We therefore extracted a set of novel frequency bands to robustly differentiate individual sleep states by using brute-force algorithm and machine learning models, among which k-nearest neighbors (KNN) was the best predictor of sleep with 94% accuracy. We subsequently characterized sleep patterns in animals with chronically induced epileptic spiking in the neocortex from tetanus toxin injections using brute-force algorithm. We found that epileptic spiking animals (without seizures) sleep more frequently, with significantly longer sleep segments and overall daily sleep time, as compared to control animals. This automated algorithm could help expedite sleep studies and help us understand the relationship between sleep and patients with epilepsy.

0297 Exploring sex and strain differences in mouse models of sleep disruption

Abstract Introduction Sleep abnormalities are a common feature of neurodevelopmental disorders (NDDs), and can have severe consequences for the affected individual and their families. Although mouse models can be used to investigate the mechanistic basis for social deficits and other symptoms of NDDs, recapitulating sleep phenotypes in mice has proven to be difficult. In this study, we determined whether a sleep-disruption challenge could reveal or exacerbate sex and strain differences in sleep patterns, using two well-validated mouse models of autism-like behavior; the BALB/cByJ and C58/J inbred strains. Methods Mice were placed in a piezoelectric sleep system for 3 days to evaluate baseline sleep rhythms. Mice were then exposed to a series of novel environments, including open field boxes and activity wheel cages, for 3 hours during the morning period of the light cycle. Sleep rebound was determined by comparing percent time spent sleeping and average sleep bout length in the three 6-hr intervals before and after the sleep disruption. Subjects were males and females of the C57BL/6J, BALB/cByJ and C58/J strains. Results At baseline, the C57BL/6J and BALB/cByJ females showed significantly reduced percent sleep, in comparison to males. During rebound from sleep disruption, BALB/cByJ mice had higher percent time and longer sleep bouts than C57BL/6J, suggesting a greater vulnerability to the effects of sleep disruption. Additionally, female C58/J mice lacked the highly robust increase in percent sleep seen in C57BL/6J in the early night interval after sleep disruption. Conclusion Overall, the data provide evidence that this sleep disturbance procedure can induce a sleep rebound effect, which could be helpful in revealing strain and sex differences in NDD mouse models. Support (If Any)

The melatonin receptor gene polymorphism rs10830963 is not associated with significant differences in sleep patterns and biorhythms.

The melatonin receptor gene polymorphism rs10830963 is not associated with significant differences in sleep patterns and biorhythms.

Differences in Sleep Patterns and Mental Health Problems During Different Periods of COVID-19 Outbreak Among Community-Dwelling Older Men in Hong Kong.

Objectives: To determine the association of sleep with mental health among Hong Kong community-dwelling older men in the context of the COVID-19 pandemic. Methods: This additional analysis was derived from the community-dwelling men aged >60 recruited during three COVID-19 outbreaks (i.e., pre-outbreak, between the second and third wave, and during the third wave) in Hong Kong from July 2019 to September 2020. Sleep and mental health were measured by Pittsburgh Sleep Quality Index questionnaire and Hospital Anxiety and Depression Scale, respectively. Multivariate logistic regression models were performed for the associations between sleep and mental health after considering the outbreaks’ impact. Results: Subjects enrolled between the second and third wave tended to have better sleep but worse mental health. Positive associations between poor sleep and depression (AOR = 3.27, 95% CI: 1.60–7.03) and anxiety (AOR = 2.40, 95% CI: 1.07–5.76) were observed. The period “between second and third wave” was positively associated with depression (AOR = 2.65, 95% CI: 1.22–5.83), showing an additive interaction with poor sleep. Conclusion: The positive association between poor sleep and depression was aggravated by the period “between the second and third wave” among community-dwelling older males in Hong Kong.

Self-reported sleep disturbance patterns in urban Haitians: A latent class analysis

Sleep health is critical to overall health and quality of life. We investigated distinct patterns of sleep in Haitian men and women in post-earthquake Haiti, in an urban neighborhood impacted by non-partner sexual violence (NPSV). Latent Class Analysis enabled our development of a three-class model (3: Sleep Disturbance [SD] Often, 2: SD Sometimes, 1: No SD). We assessed relationships between class membership and SD correlates (e.g., experience of NPSV, feelings of depression, suicide intentions, physical health). More men (31.7%) than women (22.9%) experienced NPSV. Overall SD symptoms included 58% insomnia (nearly 2 times the 30% prevalence reported in the U.S.) and 40% restless sleep (>5 times the 7.7% prevalence reported outside of Haiti). Mean SD score for NPSV victims was significantly higher than that for non-victims. In multivariate models, women and men who reported higher level of suicide intentions, and poorer physical health had increased odds of membership in Class 3 (SD often). For women, odds of membership in Class 3 increased consonant with endorsement of NPSV. Reporting depression as mostly/constantly was associated with SD Class 3 for women, but not for men. Consideration of sex differences in sleep patterns and in NPSV experience is crucial and underscores healthy sleep among other critical intervention targets for recovery of NPSV traumatized residents in Haiti and in similar LMIC.