Poor Sleep Group Research Articles

Sleep Patterns Related to Emotion Dysregulation Among Adolescents and Young Adults.

Adolescents and young adults in the college setting often report poor sleep hygiene and quality. These sleep difficulties may be related to emotion dysregulation, which is highly relevant to broader adjustment. The current study aimed to empirically identify latent groups of healthy college students with distinct subjective sleep patterns and examine differences in emotion dysregulation between subgroups. College students (N = 476; Mage=19.38) completed the Adolescent Sleep-Wake Scale-Revised, Adolescent Sleep Hygiene Scale-Revised, and Difficulties in Emotion Dysregulation Scale. Most participants were White (78%), non-Hispanic/Latinx (85%), and female (77%). Latent profile analysis identified patterns of sleep with maximum likelihood estimation. Bolck-Croon-Hagenaars procedure evaluated differences in emotion dysregulation by class. A three-class model had optimal fit, Bayesian information criterion = 11,577.001, Bootstrapped Parametric Likelihood Ratio Test = -5,763.042, p < .001, entropy = .815. The three profiles identified were good sleep (overall high sleep quality and hygiene; n = 219), moderate sleep (low sleep quality with mix of low and high sleep hygiene; n = 221), and poor sleep (very low sleep quality and hygiene; n = 36). Those in the good sleep group (M = 68.06, SE = 1.5) reported significantly less emotion dysregulation than the moderate sleep group (M = 92.12, SE = 1.67; X2(2) = 98.34, p = .001) and the poor sleep group (M = 99.51, SE = 4.10; p < .001). The moderate and poor sleep groups did not significantly differ, X2(2) = 2.60, p = .11. Emotion dysregulation differed across three sleep profiles, with participants classified in the good sleep group reporting, on average, the lowest emotion dysregulation, compared to the moderate and poor sleep groups. These findings highlight contextual factors of sleep that may be clinically targeted to promote emotion regulation.

Very-Short-Term Sleep Deprivation Slows Early Recovery of Lymphocytes in Septic Patients.

Sleep plays an important role in immune function. However, the effects of very-short-term sleep deprivation on the early recovery of immune function after sepsis remain unclear. This study was conducted in the intensive care unit to investigate the effects of 2 consecutive days of sleep deprivation (SD) on lymphocyte recovery over the following few days in septic patients who were recovering from a critical illness. The patients' self-reports of sleep quality was assessed using the Richards–Campbell Sleep Questionnaire at 0 and 24 h after inclusion. The demographic, clinical, laboratory, treatment, and outcome data were collected and compared between the good sleep group and poor sleep group. We found that 2 consecutive days of SD decreased the absolute lymphocyte count (ALC) and ALC recovery at 3 days after SD. Furthermore, post-septic poor sleep decreased the plasma levels of atrial natriuretic peptide (ANP) immediately after 2 consecutive days of SD. The ANP levels at 24 h after inclusion were positively correlated with ALC recovery, the number of CD3+ T cells, or the number of CD3+ CD4+ cells in the peripheral blood on day 5 after inclusion. Our data suggested that very-short-term poor sleep quality could slow down lymphocyte recovery over the following few days in septic patients who were recovering from a critical illness. Our results underscore the significance of very-short-term SD on serious negative effects on the immune function. Therefore, it is suggested that continuous SD or several short-term SD with short intervals should be avoided in septic patients.

745 Association of Longitudinal Sleep Profiles with Cognitive Functioning in Bipolar Disorder

Abstract Introduction Emerging evidence suggests that some cognitive deficits in bipolar disorder may be attributed to sleep disturbance. However, current findings are limited by cross sectional analyses or longitudinal studies with sparse follow up on sleep quality. The current study examined longitudinal profiles of sleep as predictors of cognitive performance across a series of domains to better understand how sleep disturbance may impact in bipolar patients. Methods 241 bipolar disorder and 103 control participants had their sleep measured at baseline, 6- and 12-months using the Pittsburgh Sleep Quality Index (PSQI). Individuals with a “poor” categorical PSQI sleep rating (PSQI total score &amp;gt;5) at all time points were categorized as “Poor Sleepers” (n = 134). Those rated “good” at each time point were “Healthy Sleepers” (n = 107), and those with at least one discrepant sleep rating at any time point were labeled “Unstable Sleepers” (n = 103). Cognitive performance was assessed at 12-months, testing domains of memory, processing speed, and executive function. ANOVAs controlling for demographics, mood symptom severity, and diagnostic group examined effects of sleep profiles on cognitive function. Results Main effects for sleep group were found for the California Verbal Learning Test across all short and long delay recall conditions (F’s 4.45 – 5.8, p &amp;lt;.02 for all). The poor sleep group performed the worst, while no main effects for diagnosis were observed. Main effects of sleep group were found for time conditions of the Trail making task (F = 4.18, p = .016), but not for errors. Conclusion Sleep quality was more strongly related to verbal and visual memory than bipolar diagnosis, with weaker effects for executive function. Some cognitive domains in bipolar disorder may be more closely related to sleep disturbance than endogenous factors. Future studies should explore how improvements in sleep functioning relate to neurocognitive outcomes, and whether cognitive performance varies as a function of sleep instability independent of mood instability. Support (if any) Support: Heinz C. Prechter Bipolar Research Fund at the University of Michigan Depression Center, the Department of Veterans Affairs (IK2-CX001501; PI: Boland), the VISN 4 MIRECC, and National Institute of Mental Health (K23MH118580; PI: Goldschmied).

Impact of inflammatory markers on the relationship between sleep quality and diabetic kidney disease.

Both poor sleep and diabetic kidney disease are closely associated with inflammation. However, the correlation between poor sleep and diabetic kidney disease has not been wellclarified. Thus, the aim of this study was to determine the mediating role that inflammatory markers play in the pathogenic effectof poor sleep on the severity of diabetic kidney disease (DKD). A cross-sectional survey was conducted on 336 patients withtype 2 diabetes (T2D). DKD was diagnosed according to the guidelines of the National Kidney Foundation-Kidney Disease Outcome Quality Initiative (NKF-K/DOQI). The Pittsburg Sleep Quality Index (PSQI) score was applied to assess patients for the quality of their sleep. Patients with a PSQIscore of more than 5 were assigned to the poor sleep group, and the rest of the patients were assigned to the good sleep group. Circulating levels of six inflammatory biomarkers related to poor sleep and DKD were measured. The prevalence of DKD was higher in patients with poor sleepquality than in those with good sleepquality (42% vs. 25%, P = 0.002). After adjustment, poor sleepquality (PSQI score OR 1.075 [95%CI 1.018-1.135], P = 0.009) remained independently associated with DKD. PSQI score was found to be positively related to fibroblast growth factor (FGF23), interleukin 6 (IL-6), P-selectin, and intercellular adhesion molecule-1 (ICAM-1) (P < 0.01), rather than fibrinogen and C-reactive protein (CRP) in linear regression models. As revealed by multiple mediation analysis, FGF23 and IL-6 mediated 26% and 23% of the relationship between PSQI score and urinary microalbumin (UMA), respectively. Similarly, the FGF23 and ICAM-1, instead of IL-6 and P-selectin, mediated 32% and 24% of the association between PSQI and estimated glomerular filtration rate (eGFR), respectively. Poor sleepquality is independently associated with DKD. These results suggest that inflammatory markers contribute to a pathogenic connection between poor sleep and DKD.

Sleep and personality in college students: A preliminary study

IntroductionSleep represents an important process in the stable behavioural and emotional functioning of the individual and is an important health indicator. Personality is related with academic and occupational achievement, quality of interpersonal relationships, but also with sleep. Concerning personality, individuals with lower emotional stability have greater sensitivity to stress and maladaptive sleep-related behaviour.ObjectivesThe main goal of this study is to analyze the relation between sleep quality and personality in college students.MethodsThis study employed a correlational design. A sample of 220 Portuguese students (84.9% females), with mean age of 19.5 years (sd=3.4), from different health courses, filled in the Pittsburgh Sleep Quality Questionnaire and HEXACO-60, during a single individual session. A descriptive statistical analysis, a Pearson correlation analyses and the t Student test, for independent samples, were performed.ResultsThe results showed a predominance of poor sleep quality among students (96.3%). The more prevalent HEXACO dimensions are: Conscientiousness (X=32.6; sd=4.2) and Emotionality (X=31.2; sd=5.2). When exploring personality differences between sleep groups (GSG=Good Sleep Group; PSG=Poor Sleep Group) a significant difference was found in mean scores of the dimension Emotionality. It was observed that the PSG revealed higher levels of Emotionality than the GSG (PSG=31.5; sd=5.1; PSG=26.3; sd=4.0; p&lt;.05).ConclusionsCollege students self-report a poor sleep and the prevalent personality dimensions are Conscientiousness and Emotionality. Students with higher levels of Emotionality (fearfulness, anxiety, dependence and sentimentality) presented a poor sleep. To conclude, mediation studies are needed in order to better understanding the link between personality and sleep.

Psychosocial factors influencing the dynamics and sleep quality in medical students

To analyze the dynamics and sleep quality in medical students during 2005-2009 years and evaluate possible factors influencing this process. The study included 2788 medical 1st, 4th and 6th year students (1919 girls, 869 young men). All participants underwent comprehensive psychophysiological testing. Self-reported questionnaire containing 45 questions about sleep quality, sleep hygiene, chronotype, behaviour was administered. Five hundred and seventeen girls and 260 young men were studied twice. During 14 years, a negative sleep quality trend was observed in university students of all groups. The poor sleep group in 2019 consisted of 12.0-13.4% of girls and 8.2-18.4% of young men. About half of students have rated their own sleep as good (48.9-58.3% of girls and 52.2-55.4% of young men). From the first up to last semester of the study sleep quality is getting worse. The prospective analysis revealed the greater negative prognostic impact of self-reported poor sleep on academic performance in girls compared with young men. In the 4th year of the study, there were many poor-sleepers of both genders required more years of study for successful academic achievement. Students reported poor sleep were more activated and performed psychometrical tasks faster. Sleep quality, especially in girls, was significantly correlated with 19 psychosocial factors. The reliable marker of poor sleep may be feeling of lack of time both in girls (r= -0.32, p<0.01; r= -0.29, p<0.01; r= -0.22, p<0.05, respectively) and young men (r= -0.21, p<0.05; r= -0.34, p<0.01; r= -0.27, p<0.05, respectively) in their 1st, 4th and 6th study year, and the consequence was the slower transition to active functioning in the morning and lower health self-evaluation.

The relationship between thyroid function tests and sleep quality: cross-sectional study.

IntroductionThe relationship between sleep and hormones have long been recognized. Studies indicated that sleep quality is one of the major modulatory effects on the endocrine system. In this study, we aimed to assess the serum concentration of thyroid hormones in individuals who suffered from low quality sleep.Material and MethodsBased on the Pittsburgh Sleep Quality Index and ISMA Stress questionnaire, we divided 83 participants into two groups. Forty-one individuals with low quality sleep group and 42 with good quality sleep group, all from the male students of a medical school in Tehran, Iran, participated in this descriptive and cross-sectional study. Then, serum levels of thyroid hormones including free T3, free T4, and TSH were assessed and compared between two groups.ResultsThere were a significant increase in serum levels of FT4 (p=0.01) and TSH (p=0.02). There were also meaningful correlations between sleep score and stress score (p=0.008) as well as stress score and FT4 (p=0.03) in the case group.ConclusionsThe current study showed that thyroid function tests (T4 and TSH) significantly rose in the poor sleep condition. We also found correlations between sleep score, stress score, and FT4 in the poor sleep condition group that suggest low sleep quality can affect thyroid hormones.

Impact of sleep quality on post-stroke anxiety in stroke patients.

ObjectiveTo explore whether poor sleep is associated with post‐stroke anxiety (PSA) in Chinese patients with acute ischemic stroke (AIS) and to verify whether poor sleep is a predictor of PSA.MethodsA total of 327 patients with AIS were enrolled and followed up for 1 month. Sleep quality within 1 month before stroke was evaluated using the Pittsburgh Sleep Quality Index (PSQI) at admission. The patients were divided into the poor sleep group (PSQI > 7, n = 76) and good sleep group (PSQI ≤ 7, n = 251). One month after stroke, patients with obvious anxiety symptoms and a Hamilton Anxiety Scale score >7 were diagnosed with PSA.ResultsEighty‐seven patients (26.6%) were diagnosed with PSA. Compared to the good sleep quality group, the incidence of PSA in patients with poor sleep quality was higher (42.1% vs. 21.9%, p = .001). Poor sleep quality is more common in patients with PSA (35.6% vs. 18.8%, p = .001). A logistic regression analysis indicated that poor sleep quality was significantly associated with PSA (OR: 2.265, 95% CI: 1.262–4.067, p = .003). After adjusting for conventional and identified risk factors, poor sleep quality was found to be independently associated with PSA (OR: 2.676, 95% CI: 1.451–4.936, p = .001).ConclusionsPoor sleep quality before stroke was associated with PSA and may be an independent risk factor of PSA 1 month after AIS onset.

Prospective assessment and risk factors of sleep disturbances in total hip and knee arthroplasty based on an Enhanced Recovery After Surgery concept.

This study aimed to examine sleep quality and risk factors associated with sleep disturbance in patients undergoing total joint arthroplasty (TJA) managed with anenhanced recovery protocol from preoperatively until 12weeks postoperatively in order to provide suggestions for improving the prevention and treatment of sleep disturbance in these patients. The Chinese versions of the Pittsburgh Sleep Quality Index (CPSQI) and Epworth Sleepiness Scale (CESS) were used to evaluate sleep quality. Pain was measured by a visual analog scale (VAS). Neuropsychological status was also assessed, using the Center for Epidemiological Studies Depression Scale (CESD) and Zung Self-Rating Anxiety Scale (ZSAS). Of 107 patients (66% women), the prevalence of sleep disturbance was as high as 60% preoperatively. CPSQI score significantly increased postoperativelyfrom baseline to 2weeks before decreasing rapidly to a lower level than preoperative baseline. CESS scores of postoperative weeks1 and 2 increased significantly compared with baseline and decreased significantly after 4weeks, and a positive correlation was found between CESS and CPSQI score. VAS score significantly decreased from baseline over all time points in the postoperative period. A good sleeper group was more likely to suffer from severe sleep disturbance after surgery than a poor sleeper group with a bigger increase of CPSQI score. Multivariate logistic regression analysis indicated that pain and anxiety were risk factors associated with postoperative sleep disturbance. Sleep disturbance is highly prevalent among patients undergoing TJA. More attention and multimodal approaches with well-controlled pain, mental counseling, and possibly preemptive use of sleep medication may improve sleep quality in TJA patients to promote recovery.

The Association of Sleep Quality with Dietary Intake and Rate of General and Central Obesity among Young Female Students in Qazvin City, Iran

Background: Insufficient sleep duration and unhealthy diet are associated with weight gain. However, little is known about the association of sleep quality with dietary intake and obesity. The aim of the present study was to compare dietary intake and anthropometric indices between good and poor sleepers. Methods: In this cross-sectional study, a total of 260 femles youth aged 18-30 years were recruited among the students of Qazvin University of Medical Sciences. The evaluated variables consisted of sleep quality, dietary intake, and anthropometric indices. Statistical analysis was performed using SPSS version 21.0. Results: Participants in the poor quality sleep group had higher intakes of calorie (P &lt; 0.001) and carbohydrate (P &lt; 0.001), and lower protein intake (P &lt; 0.01) in comparison with good sleepers. Regarding food groups, poor sleepers had higher intake of bread-grains (P = 0.02) group, but lower intake of meat-alternatives (P &lt; 0.001), vegetables (P &lt; 0.001), and fruits (P &lt; 0.001) in comparison with the good sleepers. Participants in the poor quality sleep group had higher weight (P &lt; 0.001), body mass index (P &lt; 0.001), waist circumference (P &lt; 0.001), and fat mass (P &lt; 0.001) in comparison with good sleepers. Conclusion: Our findings emphasize the relationship of poor quality sleep with unhealthy dietary intake and obesity in young female women.

Burnout in university faculty: An interaction between subjective sleep quality and the OXTR rs2268498 polymorphism

BackgroundJob burnout is a stress-related syndrome influenced by both genetic and environmental factors. Poor sleep quality acting as a stressor may lead to job burnout. The oxytocin receptor gene (OXTR) related to stress reactivity may also exert an effect on job burnout. We aimed to explore the effect of sleep quality, a functional OXTR rs2268498 polymorphism, and their interaction on job burnout in the Chinese population, which has not been explored yet. MethodsA preliminary study was performed using a cross-sectional design. The Pittsburgh Sleep Quality Index (PSQI) and the Malash Burnout Inventory (MBI) were measured from 575 healthy subjects. The OXTR rs2468498 polymorphism was genotyped in 376 subjects. ResultsThere were significant main effects of sleep quality (p<0.05), but not of the OXTR rs2468498 genotype on burnout. Interestingly, the interaction between sleep quality and the rs2468498 genotype was significant (p<0.05). In the poor sleep group, the C allele (C/C and T/C) carriers showed higher Emotional Exhaustion level than T homozygotes, while in the good sleep group, the C allele carrier showed a lower Emotional Exhaustion level. LimitationsThis study covered subjects from only one university and the sample size for genotyping was relatively small. As we analyzed only the OXTR rs2268498 polymorphism, this study could not reveal the effects of the cerebrospinal oxytocin concentration and the haplotypes. ConclusionsOur findings suggest that the OXTR polymorphism modulates the influence of subjective sleep quality on burnout. We conclude that the C allele of the OXTR rs2468498 polymorphism plays a susceptible role in job burnout.

Long-term hydroxychloroquine therapy improves the quality of sleep in patients with primary Sjögren's syndrome: a real-world study.

Patients with primary Sjögren's syndrome (pSS) often suffer from sleep disturbance. Studies suggest it may be related to symptoms, including xerostomia and dry eyes. Clinical studies have confirmed that hydroxychloroquine (HCQ) has a definite effect on pSS, but there is no clear report about its effect on sleep disorders in pSS patients. A total of 383 pSS patients were enrolled and followed up. The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate the sleep quality of the patients, and the World Health Organization Quality of Life Brief Version (WHOQOL-BREF) scale was used to evaluate the quality of life (QoL) of patients. The European League assessed the patient's condition against Rheumatism Sjögren's syndrome patients reported index (ESSPRI). According to PSQI, patients were divided into two groups: good sleep group (GSG) and poor sleep group (PSG). The risk factors of sleep disorder are analyzed by univariate and multivariate analysis. The patients were further divided into HCQ-administered group and non-administered group, and the differences of baseline characteristics and outcome in follow-up between the two groups were compared. There were 208 patients with PSG (54.3%) and 175 patients with GSG (45.7%). Further, there is no statistical difference between the two groups in baseline data. Also, there were 112 cases (53.8%) and 118 cases (67.4%) taking HCQ in the two groups, respectively, P=0.007. Univariate and multivariate analysis showed that long-term use of HCQ, menopause, and income were related to sleep quality. The patients were divided into the HCQ-administered group (n=230) and non-administered group (n=153) according to whether they took HCQ. One hundred eighteen patients (51.3%) in the HCQ-administered group had a good sleep, and 58 patients in the non- administered group had a good sleep (37.9%), P<0.05. At followup, the PSQI of the two groups were 7.3±2.1 vs. 8.1±2.4, respectively, P<0.05 and the ESSPRI were 4.9±1.1 vs. 5.4±1.3, P<0.05. The QoL of the two groups of patients was statistically different in all four dimensions, P<0.05. Long-term use of HCQ can reduce the risk of sleep disturbance in patients with primary Sjögren's syndrome.

Poor-sleep is associated with slow recovery from lymphopenia and an increased need for ICU care in hospitalized patients with COVID-19: A retrospective cohort study

Sleep is known to play an important role in immune function. However, the effects of sleep quality during hospitalization for COVID-19 remain unclear. This retrospective, single-center cohort study was conducted to investigate the effects of sleep quality on recovery from lymphopenia and clinical outcomes in hospitalized patients with laboratory-confirmed COVID-19 admitted to the West District of Wuhan Union Hospital between January 25 and March 15, 2020. The Richards-Campbell sleep questionnaire (RCSQ) and Pittsburgh Sleep Quality Index (PSQI) were used to assess sleep quality. The epidemiological, demographic, clinical, laboratory, treatment, and outcome data were collected from electronic medical records and compared between the good-sleep group and poor-sleep group. In all, 135 patients (60 in good-sleep group and 75 in poor-sleep group) were included in this study. There were no significant between-group differences regarding demographic and baseline characteristics, as well as laboratory parameters upon admission and in-hospital treatment. Compared with patients in the good-sleep group, patients in the poor-sleep group had lower absolute lymphocyte count (ALC) (day 14: median, 1.10 vs 1.32, P = 0.0055; day 21: median, 1.18 vs 1.48, P = 0.0034) and its reduced recovery rate (day 14: median, 56.91 vs 69.40, P = 0.0255; day 21: median, 61.40 vs 111.47, P = 0.0003), as well as increased neutrophil-to-lymphocyte ratio (NLR; day 14: median, 3.17 vs 2.44, P = 0.0284; day 21: median, 2.73 vs 2.23, P = 0.0092) and its associated deterioration rate (day 14: median, −39.65 vs −61.09, P = 0.0155; day 21: median, −51.40% vs −75.43, P = 0.0003). Nine [12.0%] patients in the poor-sleep group required ICU care (P = 0.0151); meanwhile, none of the patients in good-sleep group required ICU care. Patients in the poor-sleep group had increased duration of hospital stay (33.0 [23.0–47.0] days vs 25.0 [20.5–36.5] days, P = 0.0116) compared to those in the good-sleep group. An increased incidence of hospital-acquired infection (seven [9.3%] vs one [1.7%]) was observed in the poor-sleep group compared to the good-sleep group; however, this difference was not significant (P = 0.1316). In conclusion, poor sleep quality during hospitalization in COVID-19 patients with lymphopenia is associated with a slow recovery from lymphopenia and an increased need for ICU care.

Association Between Sleep Quality and Symptoms Following a Sports-Related Concussion in the Pediatric Population

PURPOSE: To determine if there is an association between reported sleep quality and concussion symptoms in pediatric athletes. METHODS: A review of prospectively collected data from subjects diagnosed with a sports-related concussion between October 2015 and June 2017, and enrolled in the North Texas Concussion Network Prospective Registry (Con-Tex), was performed. Subjects were treated at one of four outpatient clinics, in North Texas, specializing in concussions. Records were reviewed for sleep quality, indicated by composite scores on the Pittsburgh Sleep Quality Index (PSQI). According to PSQI guidelines, good sleep quality (GOOD SLEEP group) is indicated by a composite score of <5 (possible total=21), and poor sleep quality (POOR SLEEP group) by a score of >5. Demographics, symptoms, and total symptom score, as assessed by the Sports Concussion Assessment Tool 3 (SCAT3) at initial visit and 3-month follow-up, were compared between groups. RESULTS: Of 356 eligible subjects, 180 (50.6%) were girls and 176 (49.4%) were boys, with a mean age of 14.38 years (7-18). 261 subjects had a PSQI composite score of <5 at their initial visit (GOOD SLEEP), while 95 had scores >5 (POOR SLEEP). At initial visit, the POOR SLEEP group had a higher mean PSQI composite score (8.7) and total symptom score on SCAT3 (39.2) compared to the GOOD SLEEP group (2.6 and 20.4, respectively, p<.0001). The POOR SLEEP group also had a higher mean PSQI composite score (5.7) and total symptom score (12.2) at 3 months compared to the GOOD SLEEP group (3.0 and 4.2, respectively, p<.0001), although both groups improved. Additionally, subjects in the POOR SLEEP group reported more fatigue, drowsiness, and trouble falling asleep on the SCAT3 at both the initial visit and 3-month follow-up when compared to the GOOD SLEEP group (p<.005). Gender was also significantly different between the two sleep groups with more girls included in the POOR SLEEP group than boys (61.1% vs 38.9%, respectively, p=.017). CONCLUSIONS: Poor sleep was strongly associated with increased symptom burden within pediatric athletes both at initial visit and 3-month follow-up post-concussion. Clinicians should include an evaluation of sleep quality in young athletes treated for a sports-related concussion.

The effect of sleep on motor skill learning in young badminton players aged 6–9 years

The objective of this study was to examine the effect of sleep on the acquisition of motor skills in young badminton players. Thirteen badminton players, aged 6–9 years (8.0 ± 0.3 years; mean ± SE), practiced the shuttle bouncing drill, and a skill none of the players had prior experience with. After practice sessions, shuttle bouncing performance was immediately tested and then retested 1 week later. We evaluated sleep parameters for 7 consecutive days using actigraphy. Using the median value of sleep efficiency, subjects were divided into two groups: good sleepers and poor sleepers. Good sleepers had shorter sleep latency (p < 0.05), longer wake after sleep onset (p < 0.001), longer total sleep time (p < 0.005), and higher sleep efficiency (p < 0.001) than the poor sleepers. Interestingly, improvement in shuttle bouncing performance was significantly greater in the good sleeper group than that in the poor sleeper group (p < 0.05). In addition, we found that changes in the shuttle bouncing performance positively correlated with sleep efficiency (β = 0.765, p < 0.01) and total sleep time (β = 0.588, p < 0.05) after adjusting for their badminton career. These data suggest that sleep may affect the acquisition of motor skills in young players.

Sleep Quality Among Elderly People Within the Outpatient Department of Songklanagarind Hospital, Thailand: A Cross-Sectional Study

Objective: To determine the prevalence of sleep quality in the elderly within our outpatient department.Material and Method: A cross-sectional study was conducted by; calculating the sample size for a survey with ‘proportion to size’ at the outpatient department of Songklanagarind Hospital from; October to November, 2015. A total of 408 participants aged between 65 and 99 were interviewed. Demographic and sleep-related data were collected. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) – Thai version. The results were analyzed in terms of descriptive statistics and conducted using R-Epicalc and R-Survey software.Results: Our subjects were predominantly married females. The proportion of those in the 65-74 age range was 63.0%.Most of the participants (70.8%) were poor sleepers, with mean and median PSQI scores of 7.7 and 7.0, respectively.Regarding poor sleepers, their problems were; short sleep duration (99.7%), poor sleep efficiency (61.6%) and daytime dysfunction (51.6%).Conclusion: Similarly to previous studies, our findings showed a high prevalence of poor sleep quality in the elderlypopulation. A sleep duration of less than 6 hours was the major problem in the poor sleeper group. Gaining a betterinsight into sleep quality correlating with comorbidities is recommended.

Longitudinal sleep phenotypes among offspring of bipolar parents and community controls

BackgroundSleep disturbances are a prominent feature of bipolar disorder (BP). However, it remains unclear how sleep phenotypes may evolve among at-risk youth, and their relevance to BP onset. MethodsPittsburgh Bipolar Offspring Study (BIOS) offspring (ages 10–18) and their parents completed assessments approximately every two years pertaining to current psychopathology and offspring sleep habits. A latent transition analysis (LTA) identified latent sleep groups within offspring based on their ratings of six sleep domains using the School Sleep Habits Survey. Demographic and clinical characteristics were compared between sleep groups. Logistic regression tested links between sleep group and BP onset at the subsequent assessment. ResultsThe LTA model identified latent groups of good, poor, and variable sleepers. We observed an overall trend of good sleep becoming variable, and then poor, as youth age. Offspring in the poor sleep group were more likely to have psychopathology. Adjusting for age and depression, poor sleepers had nearly twice the odds of developing BP relative to good (OR=1.99, CI=0.45–8.91) or variable (OR=2.03, CI=0.72–5.72) sleepers. LimitationsLimitations include the use of proximal sleep phenotypes to predict BP onset, and a self-report measure of sleep ConclusionsWe found three non-overlapping sleep phenotype groups in a large sample of offspring of bipolar probands and offspring of demographically-matched community control parents. Clinicians should consider that youth will likely experience variable and/or poor sleep as they age, and that at-risk youth with poor sleep may be at increased risk of developing MDD and BP at their next assessment.

Association of sleep quality in Behcet disease with disease activity, depression, and quality of life in Korean population.

Background/AimsSleep disturbance is prime concern in patients with Behcet disease. The purpose of this study was to find out the effects of sleep quality, in Korean patients suffering from Behcet disease. We further investigated the relationship between depression, quality of life and the clinical findings of Behcet disease.MethodsThe study was performed by the cross-sectional design. Sleep quality was assessed by the Korean version of Pittsburgh sleep quality index (PSQI). Disease activity of Behcet disease was evaluated by Behcet disease current activity form (BDCAF). Depression was assessed by the Korean version of Beck depression inventory second edition (BDI-2). Quality of life was assessed by the Korean version of the Leeds Behcet disease quality of life measure (BDQoL).ResultsAmong the 100 patients studied, 42% reported poor sleep quality (PSQI ≥ 9). These patients have a higher BDI-2, total BDCAF and pain visual analogue scale (VAS) score (p < 0.001, p = 0.022, and p = 0.005). Considering BDCAF, the frequency of genital ulcer was significantly higher (p = 0.01). Behcet was higher in females. The BDQoL was lower in poor sleeper group (p = 0.004 and p < 0.001). Among 7 PSQI components, daytime dysfunction was higher in patients with high disease activity (p = 0.03). Total PSQI score were strongly correlated with BDCAF, BDI-2, BDQoL, and pain VAS score (p = 0.02, p < 0.001, p < 0.001, and p < 0.001, respectively).ConclusionsLow sleep quality is directly associated with disease activity, depression, and quality of life in Korean patients with Behcet disease.

Positive Psychological Traits, Perceived Stress and Quality of Life Associated with Sleep Quality in Community-Dwelling People

Background: The objective of this study was to identify the sleep problems most often encountered by people according to the presence or absence of physical and mental disorder. The aim of the present study was to investigate the associations among positive psychological traits, perceived stress, quality of life and sleep quality in community participants. Methods: Three hundred and sixty-seven community participants aged 20 to 90 years old completed SHS, GQ-6, AHS, PSS, PSQI and WHOQOL-BREF. Participants with severe physical disorders, sleep disorder, and those taking psychotropic medication were excluded from the study. Results: Stepwise regression analysis was applied in the analysis. Happiness, hope, perceived stress and quality of life were associated with sleep quality. Gratitude showed no significance. Happiness, hope, perceived stress and quality of life explained 31% of the variance for sleep quality. A majority of participants (73.5%) had PSQI ≥ 5, which is suggestive of sleep problems. The poor sleep group had lower scores on positive psychological traits (except for gratitude), higher perceived stress and lower quality of life compared to the good sleep group. Conclusions: Our results suggested that preventive and intervention programs targeting community participants should focus on developing strategies to increase positive psychological traits and decrease perceived stress in order to improve sleep problems.

Association of sleep quality with hypertension in the elderly of Jino nationality: a multilevel model analysis

Objective: To evaluate the association of sleep quality with hypertension in the elderly population aged 60 years and older of Jino nationality. Methods: In August 2015, a cross-sectional population-based survey was conducted to investigate the prevalence of hypertension in 805 subjects sampled by multistage stratified and cluster sampling from the elderly population of Jino nationality, the sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI, a poor sleep group was defined as having a global PSQI score>7, a good sleep group was with a score of 7 or less), and the multilevel Logistic regression model was applied to analyze the association of sleep quality with hypertension. Results: A total of 793 eligible participants were available for analysis. Overall, 118 participants (14.9%) were in the poor sleep group, and 675 participants (85.1%) were in the good sleep group. The prevalence of hypertension, prevalence of isolated systolic hypertension, average systolic blood pressure (SBP) and diastolic blood pressure (DBP) of the poor sleep group were significantly high than those of the good sleep group[73.7%, 22.0%, (139.2±17.7) and (82.5±10.6) mmHg (1 mmHg=0.133 kPa) vs 33.0%, 9.0%, (131.2±15.0) and (78.5±8.9) mmHg, all P<0.05]. The results of covariate-adjusted multilevel Logistic regression model indicated that subjective sleep quality (OR=2.64, 95% CI: 1.08-6.44), sleep latency (OR=2.98, 95% CI: 1.52-5.86), sleep disturbance (OR=2.93, 95% CI: 1.06-8.10), daytime dysfunction (OR=3.86, 95% CI: 1.74-8.58) and poor sleep (OR=3.98, 95% CI: 2.05-7.73) had the positive correlation with hypertension. Conclusions: The elderly population of Jino nationality with poor sleep have high SBP and DBP. There are positive associations of PSQI and its components with hypertension in the elderly population of Jino nationality.