Association of CLOCK rs1801260 Polymorphism with Sleep Quality in Residents of the Far North.

Sleep quality in patients studied with laboratory-based polysomnography may differ from sleep quality in patients studied at home but remains clinically relevant and important to describe. We assessed objective sleep quality and explored factors associated with poor sleep in patients undergoing laboratory-based polysomnography. We reviewed diagnostic polysomnography studies from a 10-year period at a single sleep center. Total sleep time (TST) and sleep efficiency (SE) were assessed as markers of sleep quality. Poor sleep was defined as TST ≤ 4 hours or SE ≤ 50%. Multivariable analysis was performed to determine associations between objective sleep quality as an outcome and multiple candidate predictors including age, sex, race, body mass index, comorbidities, severity of obstructive sleep apnea, and central nervous system medications. Among 4957 patients (age 53 ± 15 years), average TST and median SE were 5.8 hours and 79%, respectively. There were 556 (11%) and 406 (8%) patients who had poor sleep based on TST and SE, respectively. In multivariable analysis, those who were older (per 10 years: 1.48 [1.34, 1.63]), male (1.38 [1.14,1.68]), and had severe obstructive sleep apnea (1.76 [1.28, 2.43]) were more likely to have short sleep. Antidepressant use was associated with lower odds of short sleep (0.77 [0.59,1.00]). Older age (per 10 years: 1.48 [1.34, 1.62]), male sex (1.34 [1.07,1.68]), and severe obstructive sleep apnea (2.16 [1.47, 3.21]) were associated with higher odds of poor SE. We describe TST and SE from a single sleep center cohort. Multiple demographic characteristics were associated with poor objective sleep in patients during laboratory-based polysomnography. Harrison EI, Roth RH, Lobo JM, et al. Sleep time and efficiency in patients undergoing laboratory-based polysomnography. J Clin Sleep Med. 2021;17(8):1591-1598.

Poor sleep quality, often resulting from poor sleep hygiene, is common among medical students. Educational interventions aimed at improving sleep knowledge are beneficial for sleep quality in healthy populations. However, sleep education is often given minimal attention in medical school curriculums. The aim of the study was to explore whether a short educational intervention could improve sleep knowledge, and consequently sleep quality, among medical students. We recruited preclinical- and clinical-stage medical students during the 2017-2018 academic year. Students completed a demographic survey, the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), and the Assessment of Sleep Knowledge in Medical Education (ASKME) questionnaire. Students then attended a lecture on the physiology and importance of sleep. To assess the efficacy of the intervention, questionnaires were repeated 4 months thereafter. A total of 87 students (31 preclinical) with a mean age of 25.86 years (standard deviation [SD], 3.33), 51 of whom were women, participated in the study. At baseline, students had poor sleep quality with a PSQI mean score of 5.9 (SD, 2.37), without significant sleepiness, and a mean ESS score of 8.86 (SD, 4.32). The mean ASKME scores were consistent with poor sleep knowledge at 11.87 (SD, 4.32). After the intervention, the mean ASKME results improved to 14.15 (SD, 4.5; P < .001), whereas sleep quality did not. The effect was similar in preclinical and clinical medical students. Sleep knowledge was inadequate among medical students, who also experienced poor sleep quality. A short educational intervention improved sleep knowledge but was insufficient at improving sleep quality. Further studies are needed to determine which interventions may provide benefit in both sleep knowledge and sleep quality.

Sleep quality is crucial for the health of individuals with disabilities. Care farming, also known as social farming, offers health, social, and educational care services to individuals with diverse needs, including those with disabilities and disorders. This study quantitatively examined the relationship between care farming activities and sleep quality among individuals with and without (control) disorders using secondary data provided by a national institution. The dataset was not collected by the research team but included sleep measurements recorded through a validated non-wearable device. Within the group with psychological disorders, this study compared three subgroups (mental, neurodevelopmental, and intellectual disorders) to understand the specific relationship of care farming with sleep quality. Sleep latency, sleep efficiency, and wake after sleep onset (WASO) were analyzed. Compared to those in the control group, individuals with psychological disorders exhibited significantly greater variance in sleep latency and WASO scores. Notably, the group with psychological disorders experienced decreased WASO following farm work compared to non-working days, whereas the control group showed no significant changes. Significant differences in sleep efficiency between the groups were observed on non-working days, suggesting that the gap in sleep performance narrowed after workdays. Sleep quality varied across psychological disorder subgroups: neurodevelopmental disorders were strongly associated with differences in sleep latency and efficiency, whereas individuals with mental and intellectual disorders showed a 6.5-min reduction in WASO on working days. Using quantitative data, the findings indicate a a relatively positive association between farming practices and sleep quality in individuals with psychological disorders who participated in these activities. These findings highlight the importance of considering both psychological disorder types and distinguishing between working and non-working days when evaluating sleep quality.

In patients treated with noninvasive ventilation, sleep-related breathing changes can modify patient-ventilator interactions, which could reduce its effectiveness. The aim of this prospective observational study was to determine the impact of sleep/wake state on leaks, upper airway obstructive events, and asynchronies in patients treated by long-term noninvasive ventilation. Stable patients adapted to noninvasive ventilation were considered for nocturnal polysomnography. Unintentional leaks, upper airway obstructive events, and asynchronies were compared between sleep and awake periods. Twenty-eight patients were enrolled. Underlying diagnoses were neuromuscular disease (n = 11), chest wall disease (n = 8), and obesity-hypoventilation (n = 9). Leaks were more frequent in sleep than in awake periods, with a median of 10% (interquartile range [IQR], 0%-75%) vs 1% (IQR, 0%-9%) of time (P < .001), respectively. During sleep, asynchronies with and without associated leak affected 27% of breaths (IQR, 16%-39%) compared with non-leak-related asynchronies that were recorded in 8% (IQR, 3%-25%) of breaths (P < .001). Asynchronies affecting more than 10% of total breaths were more frequent in sleep (25 patients, 89%) than in awake time (8 patients, 29%; P = .25). Eleven patients (39%) presented with 5 or more upper airway obstructive events without reduction in ventilatory drive per hour of sleep. In patients adapted to home noninvasive ventilation, leaks, asynchronies, and upper airway obstructive events are frequent during the night and are concentrated in sleep periods. Asynchronies are often associated with leaks. These findings may have clinical implications considering that in patients with low sleep efficiency respiratory events could be underestimated if sleep is not evaluated. Martí S, Ferré A, Sampol G, etal. Sleep increases leaks and asynchronies during home noninvasive ventilation: a polysomnographic study. J Clin Sleep Med. 2022;18(1):225-233.

Breakfast Consumption Augments Appetite, Eating Behavior, and Exploratory Markers of Sleep Quality Compared with Skipping Breakfast in Healthy Young Adults

Sleep quality has a significant impact on the physical and mental health of the young population. To evaluate sleep efficiency, sleep disturbances, and use of sleep medication among university students in Jordan and toexamine differences in these problems in relation to selected demographic and health-risk behaviors. The study used a cross-sectional design and a multi-stage sampling technique. Three public universities were randomly selected from three major governorates in Jordan. The Arabic version of the Pittsburgh Sleep Quality Index was used to measure sleep efficiency, sleep disturbances, and the use of sleep medication. Descriptive statistics and Kruskal-Wallis tests were used to analyze the data. Of 1308 students whoparticipated in the study, 27% reported sleep efficiency less than 85%, 45% of the students reported nocturnal awakening, 30% reported getting up to use the bathroom, and 9% reported using medication to help sleep. Differences in sleep efficiency, sleep disturbances, and use of sleep medication were found in relation to students' gender, income, marital status, smoking status, and academic achievement. Poor sleep efficiency, sleep disturbances, and the use of sleep medications are significant problems affecting sleep quality among university students. Students' gender, marital status, income, smoking status, and academic achievement are important factors associated with sleep quality. Sleep screening among university students is required to identify and provide treatment for sleep problems.Furthermore, educating university students about the effects of smoking on health in general and on sleep in particular should be mandated.

Disturbed sleep is a common problem and can have profound effects on older adults. Social relationships are known to be associated with quantity and quality of sleep. To extend prior research, we examined the associations of daily social interactions and sleep, using objective sleep measures and an ecological momentary assessments (EMA) approach. Participants in the Einstein Aging Study (n=285, Mage=77, range=70-90, 68% women, 46% White, 40% Black) reported their recent social interactions and physical contact four times a day for 16 days via EMA on mobile phones. Objective sleep measures (sleep timing, night sleep time, wake after sleep onset (WASO), sleep maintenance efficiency) were calculated from concurrent wrist actigraphy. Multilevel models controlled for demographics, living arrangement, Instrumental Activities of Daily Living, sleep-disordered breathing, and hypoxemia. Results showed that, on days when older adults had more day-time social interactions than their average, they had earlier sleep timing, shorter night sleep time, and less WASO, but no differences in sleep efficiency. On days when older adults had more physical contact than their average, they had earlier sleep timing and shorter night sleep time but no differences in WASO or sleep efficiency. These micro-longitudinal analyses among older adults suggest that daily social interactions are related to subsequent earlier sleep timing and shorter sleep at night, and can be beneficial for sleep quality. Physical contact seemed to be only associated with the timing and quantity of sleep but not sleep quality. Potential benefits of using an EMA approach in sleep research will be discussed.

To evaluate the relations between sleep characteristics and cardiovascular risk factors and napping behavior, and to assess whether daytime napping leads to subsequent better or worse sleep. The sample consisted of 224 (African American, Caucasian, and Asian) middle-aged men and women. Sleep measures included nine nights of actigraphy and sleep diaries, sleep questionnaires, and one night of polysomnography to measure sleep disordered breathing. More frequent napping was associated with shorter nighttime sleep duration averaged across the nine nights of actigraphy (especially among African Americans), more daytime sleepiness, more pain and fatigue by diary, and increased body mass index and waist circumference. Shorter nighttime sleep duration was associated with taking a nap during the next day and taking a nap was associated with less efficient sleep the next night. Napping in middle-aged men and women is associated with overall less nighttime sleep in African Americans and lower sleep efficiency as measured by actigraphy, and increased BMI and central adiposity. These findings point to the importance of measuring of napping in understanding associations of sleep with cardiovascular risk.

Background: Poor sleep quality as assessed by overnight polysomnography (i.e., low sleep efficiency and/or low % rapid-eye movement (REM) sleep) is frequently reported in COPD. More symptomatic patients tend to present with worst sleep quality ( Scharf et al. Int J Chron Obstruct Pulmon Dis. 2010;6:1–12 ). Considering the close association between symptom burden and lung hyperinflation in COPD ( O9Donnell DE et al. Expert Rev Respir Med. 2016;10:823-34 ), we hypothesized that hyperinflation would be negatively related to sleep quality in these patients. Methods: We retrospectively assessed 182 patients (FEV 1 =69±20% predicted, GOLD stages I to IV) who performed spirometry, body plethysmography and overnight polysomnography. Results: Sleep efficiency (68±16%) and % REM (14±8%) were reduced compared to historical controls. In a multiple regression analysis, inspiratory capacity/total lung capacity (IC/TLC) ratio, apnea-hypopnea index (AHI) and sleep SpO 2 nadir - but not FEV 1 or body mass index - remained as independent predictors of poor sleep efficiency ( p 2 p 1 (% predicted) than their counterparts with better sleep quality (0.40±0.09 vs 0.44±0.09; p Conclusion: Lung hyperinflation is associated with poor sleep quality regardless the severity of airflow obstruction in patients with COPD. Decreasing overnight lung volumes might prove therapeutically useful to improve sleep quality in these patients.

Loss of muscle mass, particularly in old age, can restrict mobility and physical function. Sleep is thought to play a key role in the maintenance of muscle mass; sleep disturbances have a prevalence of 6-30% in Germany. In this study, based on data from the Berlin Aging Study II (BASE-II), we analyze the relationship between sleep efficiency and quality on the one hand, and muscle mass and muscle function on the other. We analyzed cross-sectional data from 1196 subjects (52.5% women; 68 ± 4 years). Sleep behavior was assessed with questions from the Pittsburgh Sleep Quality Index; appendicular lean mass (ALM) with dual x-ray absorp - tiometry; and muscle function with a measure of grip strength and with questionnaires about physical activity and impairment of physical activities. Low muscle mass was determined from the ALM corrected by the body-mass index (BMI), i.e., from the ratio ALM/BMI. 19.1% of the women and 13.4% of the men reported poor sleep quality. Men whose ALM/BMI ratio was below the cutoff value for low muscle mass more frequently reported very poor sleep efficiency (9.1% , versus 4.8% in women; p<0.002). The adjusted odds ratio for low muscle mass was 2.8 for men with poor sleep quality (95% confidence interval: [1.1; 6.7]) and 4.3 for men with poor sleep efficiency [1.2; 15.1]. In women, there was no statistically significant association between sleep quality and efficiency on the one hand and ALM/BMI values below cutoff on the other, but poor sleep quality was found to be associated with reduced grip strength (16.25 kg ± 2.33 kg versus 15.67 kg ± 2.38 kg; p = 0.009) and low appendicular lean mass (ALM: 16.25 kg ± 2.33 kg versus 15.67 kg ± 2.38 kg; p = 0.016). These findings support the hypothesis of a link between sleep and muscle mass. The dependence of muscle mass on sleep behavior needs to be investigated in longitudinal studies.

This study aims to compare subjective and objective sleep quality in patients with obstructive sleep apnea (OSA), given the high prevalence of this sleep disorder that can affect sleep quality. This research enrolled 195 individuals diagnosed with OSA, with an Apnea Hypopnea Index (AHI) of 5 or higher based on polysomnography. Participants completed the Pittsburgh Sleep Quality Index (PSQI) questionnaire for subjective sleep quality. Objective sleep quality derived from sleep efficiency reported in overnight polysomnography. An analysis of sleep efficiency showed that 12.8% of people had poor-quality sleep. The PSQI was also used to measure subjective sleep quality, and 64.1% of respondents reported having poor sleep quality. No significant correlation was observed between sleep efficiency and PSQI scores. Obesity has a negative correlation (ρ = -0.168, p = 0.019) with sleep efficiency, highlighting the effect of BMI on sleep fragmentation. Male sex was linked to a lower risk of poor objective sleep quality, according to logistic regression analysis (adjusted OR = 0.314, 95% CI = 0.113-0.872). Frequent use of sleeping pills was linked to a lower probability of experiencing subjectively poor sleep quality (adjusted OR = 0.077, 95% CI = 0.024-0.243). This study highlights that a significant portion of OSA patients have poor sleep quality, subjectively. Although sleep efficiency is an important objective metrics, its lack of correlation with subjective sleep quality in this population highlights the complexity of assessing sleep health and the need for comprehensive evaluation tools in these patients.

Cognitive behavioral therapy for insomnia (CBT-I) has been shown to improve both sleep and depressive symptoms, but predictors of depression outcome following CBT-I have not been well examined. This study investigated how chronotype (i.e., morningness-eveningness trait) and changes in sleep efficiency (SE) were related to changes in depressive symptoms among recipients of CBT-I. Included were 419 adult insomnia outpatients from a sleep disorders clinic (43.20% males, age mean ± standard deviation = 48.14 ± 14.02). All participants completed the Composite Scale of Morningness and attended at least 4 sessions of a 6-session group CBT-I. SE was extracted from sleep diary; depressive symptoms were assessed using the Beck Depression Inventory (BDI) prior to (Baseline), and at the end (End) of intervention. Multilevel structural equation modeling revealed that from Baseline to End, SE increased and BDI decreased significantly. Controlling for age, sex, BDI, and SE at Baseline, stronger evening chronotype and less improvement in SE significantly and uniquely predicted less reduction in BDI from Baseline to End. Chronotype did not predict improvement in SE. In an insomnia outpatient sample, SE and depressive symptoms improved significantly after a CBT-I group intervention. All chronotypes benefited from sleep improvement, but those with greater eveningness and/or less sleep improvement experienced less reduction in depressive symptom severity. This suggests that evening preference and insomnia symptoms may have distinct relationships with mood, raising the possibility that the effect of CBT-I on depressive symptoms could be enhanced by assessing and addressing circadian factors.

BackgroundMultiple Sclerosis (MS) is a chronic inflammatory autoimmune, neurodegenerative disease that affects regular mobility and leads predominantly to physical disability. Poor sleep quality, commonly reported in MS patients, impacts their physical activity (PA). Accelerometers monitor 24-h activity patterns, offering insights into disease progression in daily life. ObjectiveTo test if the sleep quality variables of MS patients, as assessed with wrist-worn accelerometers, differ from those of controls and are associated with PA and disease severity variables. MethodsSeven-day raw accelerometer data collected from 40 MS patients and 24 controls was processed using an open-source GGIR package, from which variables of sleep quality (sleep efficiency, wake after sleep onset (WASO), sleep regularity index (SRI), intradaily variability (IV)) and PA (of different intensities: inactivity, light (LPA), moderate (MPA), vigorous (VPA)) were analyzed. The variables were compared between the two study groups and in MS patients, correlation tested associations among the variables of sleep quality, PA, and disease severity (assessed with the Expanded Disability Status Scale, EDSS). ResultsSleep efficiency was the only variable that differed significantly between MS patients and controls (lower in MS, p = 0.01). Both SRI (positively) and IV (negatively) correlated with the time spent in LPA and MPA. WASO correlated negatively with inactivity. ConclusionThis is one of the few studies with a wrist-worn accelerometer that shows a difference in sleep efficiency between MS patients and controls and, in MS, an association of sleep quality variables with PA variables.

Introduction Black adults in the US have shorter sleep duration, lower sleep efficiency, and worse sleep quality compared to Non-Hispanic White adults. Racial segregation may be a contributing factor to sleep disparities as individuals living in disadvantaged communities may have greater exposure to bright lights, noise, and poor air quality and may have more difficulties accessing resources. This study examines the cross-sectional associations between racial segregation and sleep health (sleep duration, efficiency, and quality) among middle-aged Black adults. Methods The sample included 366 Black adults who participated in the Coronary Artery Risk Development in Young Adults (CARDIA) Sleep Health Ancillary Study. The Sleep Health Ancillary study was conducted during the Y35 CARDIA examination (2020-2024). Racial segregation was measured using the Getis-Ord Gi* statistic, a measure of standard deviation (SD) between the neighborhood’s racial composition and the surrounding area’s racial composition. Sleep measures included sleep duration and efficiency (derived from actigraphy data using Actiware Software [version 6.2.0.39]) and subjective sleep quality (measured by the Pittsburgh Sleep Quality Scale [PSQI]). Linear regression models were fitted to examine associations between racial segregation and sleep health parameters. Results Participants were 68.8% female and a mean age of 60.7 years (SD=3.9). Mean G-scores were 2.4 (SD=2.8), suggesting greater racial segregation among Black adults. Mean sleep efficiency, duration, and quality values were 80.0% (SD=8.3), 384.6 min (SD=64.4), and 7.1 (SD=4.3), respectively. In univariate analysis, racial segregation was associated with significantly lower sleep efficiency (B=-0.45, 95% CI=-0.76 to -0.14), but there were no associations with sleep duration or subjective sleep quality. The association between racial segregation and sleep efficiency remained significant after adjusting for age, gender, education, and marital status (B=-0.37, 95% CI=-0.72 to -0.03) but was attenuated (B=-0.32, 95% CI=-0.68 to 0.04) after adjusting for cardiovascular risk factors (body mass index, diabetes, hypertension) and depressive symptoms. Conclusion There is an association between racial segregation and sleep efficiency among middle-aged Black adults in the CARDIA cohort. This association was not independent of cardiovascular risk factors or depressive symptoms. Future studies should evaluate the specific features of racially segregated neighborhoods that are strongly related to worsening sleep health. Support (if any)

BackgroundPain is a cardinal symptom of chronic rheumatic conditions and can involve nociceptive and non-nociceptive (neuropathic) components that may be linked to central sensitization. Poor sleep quality has been connected...