Predictors Of Poor Sleep Quality Research Articles

Daytime Sleepiness and Sleep Quality among Undergraduate Medical Students in Sialkot, Pakistan

Background/ObjectiveDaytime sleepiness and poor sleep quality are common among medical students, and are expected to affect their academic performance. The common problems are duration of sleep, delayed onset of sleep, and daytime sleepiness. The objective of this study is to determine the prevalence of daytime sleepiness and sleep quality and associated risk factors among medical students in a medical college in Sialkot, Pakistan.MethodsIn this cross-sectional study, 154 medical students were selected through stratified random sampling techniques. Pittsburgh Sleep Quality Index (PSQI) was used to assess the sleep pattern and Epworth Sleepiness Scale (ESS) was used to measure daytime sleepiness. The association of sleep quality and daytime sleepiness and the risk factors were determined through regression analysis.ResultsThe results showed that students who suffered from poor sleep quality was 64%; abnormal sleep latency was 51%, narcoleptic 43.2%, and sleep disturbance 31%. In the multivariate analysis after adjustment of covariates, in terms of sleep habits, females and second academic year students were more than two times likely to have a sleep disorder [Odds Ratio (OR) = 2.33; 95% Confidence Interval (CI), 1.66–2.91 and OR = 2.33; 95% CI, 2.74–7.34, respectively]. Regarding narcolepsy, female participants (OR = 2.03; 95% CI, 1.24–16.7), stress during examination (OR = 1.90; 95% CI, 1.07–47.05), poor sleep after physical activity (OR = 1.76; 95% CI, 1.10–30.00), and second academic year students (OR = 2.07; 95% CI, 1.85–2.54) were two times more at risk of severe narcolepsy.ConclusionThe majority of students suffered from poor sleep quality and daytime sleepiness. Female sex and academic years were the major predictors of poor sleep quality and daytime sleepiness. There is a need for awareness and counseling among students to help reduce the burden of sleep disorder.

Poor sleep quality among young adults: The role of anxiety, depression, musculoskeletal pain, and low dietary calcium intake.

This study examined the relationships between sleep quality, anxiety, depression, musculoskeletal pain (MSP), and calcium intake. In this cross-sectional study (N = 1422), sleep was assessed using the Pittsburgh Sleep Quality Index, anxiety and depression were assessed using the Hospital Anxiety and Depression Scale, and calcium intake and MSP were assessed by self-reporting. Poor sleep quality was reported by 62.66% of the participants. The participants with poor sleep quality reported lower calcium intake, higher anxiety and depression levels, more severe MSP, and multisite pain. Anxiety, depression, low calcium intake, and multisite pain were significant predictors of poor sleep quality. Anxiety was predicted by poor sleep quality, depression, multisite pain, and sex (ie, female). Depression was predicted by anxiety, poor sleep quality, and low calcium intake. The findings underscore the role of low calcium intake in the development of sleep problems, anxiety, depression, and MSP. Individuals with these conditions should be advised to increase their calcium intake.

Association of poor sleep quality with risk factors after coronary artery bypass graft surgery—A prospective cohort study

Fragmented sleep is a daunting experience and a common health problem with high prevalence among patients 3months after coronary artery bypass grafting (CABG). However, the potential predictors on poor seep quality remains unexplored. The main purpose of this study was to determine the predictors of poor sleep quality among patients 3months after CABG. A prospective cohort study is a part of the randomized controlled trial between 2012 and 2013 in which 400 adult patients undergoing elective CABG were being randomly sampled as per the inclusion criteria followed up at 3months after CABG surgery in the cardiovascular outpatient clinic of a tertiary-care hospital. The study was conducted according to the Declaration of Helsinki and was approved by the institutional ethical committee. All participants gave written informed consent on having received detailed information on the study. Demographic and clinical data were obtained from medical records at the time of CABG. The data on sleep quality were collected by using the Pittsburgh Sleep Quality Index and state anxiety was evaluated utilizing state-trait anxiety inventory (STAI-YI fo3rm). Multivariable logistic regression examined the association between the postoperative poor sleep quality and clinical, preoperative state anxiety, and angina. The significant variables are chosen based on the P-value associated with the significant level of model that lies on α=0.05. Logit determination and the correlation between the variables are also discussed for further analysis. A total of 187 patients (mean age 55.6±12.05years) completed the questionnaire. Most patients (78%) reported poor sleep quality (4.23±1.24) (PQSI score of less than 5). There was a strong relationship between PQSI and state anxiety. The higher state anxiety among 68% of patients with the mean score (53.51±9.55) had 6.42 (95% CI 3.04-9.61) times the odds of being classified as high risk for sleep disturbance. There are 3 factors that most significant of the 8 factors tested were identified as having influence significantly on the poor sleep quality. These factors are diabetes (OR 1.186, 95% CI 1.016-1.097, P>.01), body mass index>30kg/m2 (OR 2.36, 95% CI 1.041-1.172, P>.05), sedentary lifestyle (OR 1.091, 95% CI 1.016-1.159, P>.01), and preoperative state anxiety (OR 1.186, 95% CI 1.074-1.115, P>.01). Even though the body mass index>30kg/m2, sedentary lifestyle, and diabetes were significantly associated with sleep quality, the only factor with more significantly related to poor sleep quality was preoperative state anxiety which is the strong predictor of poor sleep quality. Hence, early recognition of predictors and careful management of poor sleep quality is warranted.

Prevalence of poor sleep quality and its associated factors among hypertensive patients on follow up at Jimma University Medical Center

Several studies have reported an association between the abnormal duration of sleep and chronic conditions including hypertension. However, the existing body of evidence is not entirely significant; as insignificant associations between poor sleep and blood pressure (BP) have been found across differentstudies. The aim of this study was to determine prevalence and factors associated with poor sleep quality among hypertensive patients in Jimma University Medical Center. An institution based cross sectional study design was employed from June 01 to July 15, 2018 among 279 hypertensive patientson follow-up at Jimma University Medical Centre chronic clinic, Jimma, Ethiopia. Data collection was done by using face to face interview. Sleep quality was measured by using validated, standard Pittsburgh sleep quality index (PSQI). PSQI total score ≥5 was considered as a diagnostic of poor sleep quality. On multivariate logistic regression variables with of p value of <0.05 was considered as predictors of poor sleep quality. A total of 279 hypertensive patients were enrolled into the study. Out of which 279, 142 (50.9%) were males. The prevalence of poor sleep quality among hypertensive patient was 99 (35.5%). Physical inactivity (AOR = 0.288, 95% CI: (0.130-0.639), diastolic blood pressure Stage I (AOR = 3.923, 95% CI: 1.052-14.632) and diastolic blood pressure Stage II (AOR = 4.520; 95% CI: 1.079-18.931) were identified as independent predictors of poor sleep quality. In conclusion, about one-third of hypertensive patients were poor sleepers. High diastolic blood pressure and physical inactivity are independent predictors of poor sleep quality among hypertensive patients.

Impression of Twitter and Whatsapp on Sleep Quality Among Nursing Students In Indonesia

Introduction: The widely used social media by mobile-platform, which makes communication easier, faster, enhance effective flow of information. However, it may have the potential negative effect in quality of sleep in nursing students. The purpose of this study was to examined the impact of using social media and identified predictors of poor sleep quality among nursing students. Methods: A school-based survey design was conducted. Totally, 264 students at school of health sciences in West Java with usage social media platform were participated in this study. The extensive self-administered questionnaires were used to assess extent of using social media and the Pittsburgh Sleep Quality Index. Logistic regression analysis by a backward-stepwise technique was used to determine predictors of poor sleep quality. Results: One out of two nursing students (59.5 %) used both Instagram and WhatsApp, mostly at nights (59.8%), and more than 4-hour daily (19.3%). Majority nursing students (94.3%) have poor quality of sleep. Quality of sleep was differed significantly in bachelor students (p=0.03) in 8th semester (p = 0.006). Younger nursing students (β = 0.025, p = 0.021, 95% CI 0.001-0.566) who use social media less than 3-month (β = .019, p = 0.001, 95% CI 0.002-0.212), mostly during weekends and in 8th semester (β = 41.32, p = 0.018, 95% CI 1.902-897.73) were predictor of poorer sleep quality. Conclusion: Findings indicated a strong need for integrating sleep quality education and provide health-education to promote correct and effective use of social networks to minimize possible side effects in nursing students.

Sleep Quality and Nocturnal Symptoms in a Community-Based COPD Cohort

Small studies have suggested that patients with chronic obstructive pulmonary disease (COPD) have poor sleep quality. Our aim was to examine the prevalence of subjective sleep-related complaints and predictors of poor sleep quality in a large community-based COPD cohort. We analyzed cross-sectional data on sleep questionnaire responses from the Canadian Cohort of Obstructive Lung Disease (CanCOLD) study, a population-based, prospective longitudinal cohort study across Canada. The cohort comprises a COPD group and two matched non-COPD (never-smokers and ever-smokers) groups. Sleep-related symptoms were assessed using questionnaires including Pittsburgh Sleep Quality Index (PSQI). A total score of PSQI > 5 is indicative of poor sleep quality. Health-related quality of life measures and the presence of mood disturbance were assessed using Short Form-36™ Health Survey (SF-36) multi-item questionnaires and Hospital Anxiety and Depression Scale (HADS), respectively. Predictors of poor sleep quality were analyzed using multivariable logistic regression analysis. Of the 1123 subjects, 263 were healthy controls, 323 at-risk controls, and 537 had COPD (297 had mild, 240 with moderate to severe disease). The mean PSQI score was not significantly different between groups. COPD patients with poor sleep quality had lower diffusion capacity, higher HADS anxiety and depression scores and lower SF-36 mental and physical component summary scores than COPD patients classified as good sleepers. The presence of restless legs and obstructive sleep apnea symptoms, waist circumference, predicted diffusion capacity and HADS anxiety and depression scores were identified as independent predictors of poor sleep quality.

Prevalence and factors associated with poor sleep quality in inflammatory bowel disease outpatients.

sleep disorders are common in the general population and have obvious repercussions on quality of life. Poor sleep quality is associated to inflammatory activity and fatigue in inflammatory bowel disease (IBD) patients. This study aimed to analyze the prevalence of poor sleep quality and the factors associated with it, in IBD outpatients. an observational and prospective study was performed in which epidemiological, clinical and laboratory data were collected from clinical records and patients who consecutively attended an outpatient clinic. Pittsburgh Sleep Quality index (PSQI), Hospital Anxiety and Depression Scale (HADS) and International Physical Activity Questionnaire (IPAQ) were used to measure sleep quality, anxiety, depression and physical activity, respectively. Treatment optimizations, hospital admissions or surgery were prospectively verified three months after the baseline visit. one hundred and two patients were included and 54.9 % had poor sleep quality (PSQI score > 5). No association was found between poor sleep quality and IBD-related variables such as type of disease, ulcerative colitis (UC) extent, Crohn's disease (CD) location or behavior, time from diagnosis, treatment, prior admissions or surgery and laboratory values. Rotating night shift job (OR 6.116, 95 % CI: 1.312-28.514), HAD score for depression (OR 1.125, 95 % CI: 1.062-1.490) and frequency (days per week) of vigorous physical activity (OR 0.783, 95 % CI: 0.619-0.991) were independent predictors of poor sleep quality. A Pittsburgh questionnaire score higher than 5 was not significantly associated to treatment optimization in the total patient cohort (15.2 % vs 18.2 %, p = 0.451), in UC patients (18.2 % vs 10.7 %, p = 0.362) or CD patients (12.5 % vs 25.9 %, p = 0.198). poor sleep quality is present in more than half of IBD patients. Aspects not directly related to IBD are associated to poor sleep quality.

EncephalApp Stroop App predicts poor sleep quality in patients with minimal hepatic encephalopathy due to hepatitis B-induced liver cirrhosis.

Background/Aim:A novel computerised Stroop test- EncephalApp Stroop App (EncephalApp) has good diagnostic validity for minimal hepatic encephalopathy (MHE) in cirrhotic patients. The Stroop test is correlated with sleep disturbances which are common, and severely affects health-related quality of life in cirrhotic patients with MHE. We evaluated the relationship between sleep quality and EncephalApp results in patients with MHE due to hepatitis B-induced liver cirrhosis.Patients and Methods:We enrolled 180 adult patients with hepatitis B-induced cirrhosis. All patients were tested using the psychometric hepatic encephalopathy score (PHES) and EncephalApp. We analysed the diagnostic validity of EncephalApp for MHE using PHES as the gold standard for reference. The sleep quality of included patients was evaluated using the Pittsburgh Sleep Quality Index (PSQI). The predictive factors for poor sleep quality were analysed using backwards conditional stepwise logistic regression analysis.Results:Ninety-eight patients (54.4%) were diagnosed with MHE by PHES. Receiver operating characteristic (ROC) curve analysis showed that the threshold value of EncephalApp for MHE diagnosis was 225.60 s. EncephalApp showed 85.2% sensitivity and 77.3% specificity for diagnosing MHE; the area under the ROC curve was 0.864. PSQI scores of cirrhotic patients with MHE were significantly lower than those without MHE (P < 0.05). Child Turcotte Pugh grades (Odds ratio [OR] = 2.11 [1.55–2.85], P < 0.01) and the total Off-time plus On-time of EncephalApp (OR = 4.14 [1.95–6.29], P < 0.01) were independent predictors of poor sleep quality in MHE patients.Conclusions:The total Off-time plus On-time of EncephalApp predicts poor sleep quality in patients with MHE due to hepatitis B-induced cirrhosis.

The association of stress with sleep quality among medical students at King Abdulaziz University.

Objective:This study aims to determine the prevalence and the association of stress with sleep quality among medical students at King Abdulaziz University (KAU), Jeddah, Saudi Arabia.Methods:A cross-sectional study was done among 326 medical students of KAU using a stratified random sampling technique. An electronic self-administered questionnaire was used. Kessler Psychological Distress Scale (K10) and Pittsburgh Sleep Quality Index (PSQI) were used to assess the stress and sleep quality, respectively.Results:The overall students who experienced stress were 65%. The prevalence of poor sleep quality (total PSQI score ≥5) was 76.4%. There was a strong association between stress and poor sleep quality (value of Cramer's V = 0.371, P < 0.001), and it showed that the increase in stress level is a significant predictor of poor sleep quality.Conclusion:A high prevalence of stress and poor sleep quality was found among the students and the study confirms a strong association between them. We recommend establishing courses focusing on educating the students about proper sleep hygiene and how to deal with the stressful environment.

Prevalence, correlates, and impact of sleep disturbance in Chinese patients with primary Sjögren’s syndrome

Sleep disturbances are common in primary Sjögren's syndrome (pSS) patients and may lead to disease aggravation and decreased health-related quality of life (HRQoL). There are currently no known reported studies related to the prevalence, correlates, and impact of sleep disturbance in pSS patients from China. Therefore, this study aims to assess the sleep quality in Chinese pSS patients and evaluate its relationship with the disease activity, quality of life and mood disorders. A self-report survey was administered to 221 pSS patients and 198 healthy individuals using the Pittsburgh Sleep Quality Index (PSQI) for sleep quality. Disease activity and damage were evaluated with the European League Against Rheumatism Sjögren's syndrome disease activity index (ESSDAI). Independent samples t tests, Chi-square analysis, logistic regression were used to analyze these data. Our results found that the prevalence of poor sleep (PSQI≥6) was 57.5% and the mean global score of PSQI was 6.57 (SD 3.19) in patients, which were significantly higher than the controls (32.3% and 4.93 [SD 2.86], respectively). When trying to fall asleep, patients with pSS had some sleep disturbances, reduced sleep efficiency, increased number of awakenings than controls. There were significant correlations among dryness, ocular surface disease, HRQoL, pain, disease activity, anxiety/depression and sleep quality in pSS patients. Meanwhile, logistic regression models identified depression and Short Form-36 mental composite score as predictors of poor sleep quality. Sleep disturbances are commonly reported in pSS patients and sleep quality is lower in pSS patients than in healthy controls. The data suggested the need for holistic assessment and management of pSS patients.

Self-reported sleep quality and depression in post myocardial infarction patients attending cardiology outpatient clinics in Oman

ObjectiveThis study aimed to examine the sleep quality and prevalence of depression in post myocardial infarction patients attending cardiology outpatient clinics of selected hospitals in Oman. MethodsA descriptive cross-sectional design was used to collect data from patients (n = 180) who were at least 4 weeks post myocardial infarction diagnosis and receiving follow-up care in the outpatient clinic. The Arabic version of the Pittsburgh Sleep Quality Index and Patient Health Questionnaire-9 were used to assess sleep quality and depressive symptoms, respectively. ResultsThe sample mean age was 62.0 ± 11.3 years. Poor sleep quality affected 61.1% of the participants. The significant predictors of poor sleep quality were gender (P ≤ 0.05), body mass index (P ≤ 0.05), and self-reported regular exercise (P ≤ 0.01). The most impacted domains of sleep quality were sleep latency, sleep duration, and sleep disturbances. The prevalence of major depression was low (5%) and the rate of re-infarction was 27.2%. The prevalence of minimal to mild major depression with a potential of transitioning into major depression overtime was very high. Self-reported regular exercise (P ≤ 0.01) was the only significant predictor of depressive symptoms. ConclusionThe sleep quality of post myocardial infarction patients was poor and the prevalence of depression was low. There was no significant relationship between sleep quality or depression with re-infarction.

Postpartum Sleep and Breastfeeding Outcomes Among First-Time Mothers of Full-Term Newborns

To examine the impact of impaired sleep and its related health consequences (fatigue, hormone disruption, and mood changes) on two breastfeeding outcomes: milk volume and discontinued breastfeeding during the early postpartum period. A descriptive, correlational design was used. Participants were recruited via childbirth classes held at a large community hospital in the southeastern United States. The sample included 29 healthy women who were first-time mothers (ages 22–35 years) and exclusively breastfeeding healthy, full-term newborns. A home visit was conducted at 2-weeks postpartum. Data were collected using a sleep diary, General Sleep Disturbance Scale (GSDS), 7-item Lee Fatigue Scale (LFS-7), Edinburgh Postnatal Depression Scale (EPDS), Perceived Stress Scale (PSS-10), and State-Trait Anxiety Index (STAI). A test weight was performed during the visit, immediately before and after breastfeeding, and was repeated for two consecutive feedings. A follow-up phone interview was conducted to determine breastfeeding status at 1-month postpartum. All women were exclusively breastfeeding at 2-weeks postpartum, and most (90%) were breastfeeding exclusively at 1 month. At 2 weeks, participants in this study were sleep disturbed (69.2%), fatigued (82.8%), experiencing symptoms of anxiety (27.6%), and expressing more symptoms of depression (27.6%) compared with low-risk postpartum women in the United States. Stress was a significant predictor of poor sleep quality (β = .597, p = .001). Poor sleep quality was a significant predictor for lower breast milk production during the 2nd postpartum week (β = –.695, p = .02). Findings highlight a need to develop stress-reduction interventions that might lead to improved sleep during the postpartum period. Improved sleep may have a positive impact on breast milk production. Appropriate screening for depression symptoms and anxiety are also needed for early detection and assistance for postpartum women who develop mood disorders.

Alcohol Consumption as a Moderator of Anxiety and Sleep Quality.

ABSTRACTBackground:Although people who sleep poorly may attempt to relieve anxiety for better sleep quality, whether daily alcohol consumption is a factor that moderates anxiety and sleep disturbance is not known.Purpose:The aim of the study was to explore (a) the association between anxiety and sleep quality and (b) whether daily alcohol consumption acted as a moderator between anxiety and sleep quality in those who reported sleeping poorly.Methods:Eighty-four participants aged 20–80 years who reported poor sleep (Pittsburgh Sleep Quality Index > 5) in northern Taiwan were enrolled in this cross-sectional study. A structured questionnaire covering demographics (including daily alcohol consumption), level of anxiety, level of depression, and perceived sleep quality was used to collect data.Results:The participants were mostly women (72.6%). The mean age was 41.81 (SD = 12.62) years; 51.2%, 19.0%, 13.1%, and 14.3%, respectively, had minimal, mild, moderate, and severe anxiety. After adjusting for factors related to sleep quality using multiple regression analysis, receiving sleep therapy, consuming alcohol on a daily basis, and having anxiety were found to be predictors of poor sleep quality. Moreover, daily alcohol consumption was found to moderate the relationship between anxiety and sleep quality.Conclusions/Implications for Practice:People who sleep poorly should avoid misusing alcohol to self-treat poor sleep quality or anxiety and should instead utilize sleep hygiene education and mental healthcare. Daily alcohol consumption may be a moderator between anxiety status and sleep quality.

Depression, anxiety, and bodily pain independently predict poor sleep quality among adult women attending a primary health center of Puducherry, India.

Background:Sleep disorders and mental health problems are common diagnoses in primary care settings. The objective of this study was to estimate the magnitude of poor sleep, depression, and anxiety through opportunistic screening and to find out the independent predictors of poor sleep quality among female participants.Materials and Methods:A hospital-based study was conducted in the outpatient department (OPD) of an urban primary health center of Puducherry. Patients and accompanying healthy attendants ≥ 18 years of age who visited the OPD for any reason were included. Those with serious acute illness, previously diagnosed mental illness, pregnant women, and women in postpartum period (upto 6 weeks) were excluded. Systematic random sampling was used to select the participants. A semi-structured questionnaire was used to collect sociodemographic and clinical details along with the Pittsburgh Sleep Quality Index (PSQI) and the Hospital Anxiety and Depression Scale. Height and weight were also measured.Results:A total of 301 participants were recruited. Mean age of the participants was 49.4 (standard deviation 15.2) years. Magnitude of poor sleep (PSQI score > 5), abnormal anxiety, and abnormal depression were 118 (39.2%), 60 (19.9%), and 28 (9.3%) respectively. Multivariate logistic regression analysis showed that history of pain [odds ratio (OR) 3.2 (1.6–6.5), P = 0.001], abnormal anxiety [OR 2.5 (1.2–5.6), P = 0.021], and abnormal depression [OR 4.3 (1.4–13.2), P = 0.01] independently predicted poor sleep quality among females.Conclusion:OPD-based opportunistic screening for sleep and mental health problems should be routinely conducted by primary care and family physicians.

Perceived stress and worldview influence sleep quality in Bolivian and United States university students

ObjectiveThis study investigated predictors of poor sleep quality among American and Bolivian students. DesignA cross-sectional survey was designed and administered to undergraduate university students. Setting and participantsPsychology classes from 2 public universities (Texas, USA, and Bolivia) were convenience sampled (n = 80 American students; 60 Bolivian students). MeasurementsWe used a sleep quality index and the Perceived Stress Scale. We added questions concerning worldview, sleep hygiene, sleep deficiency, health behaviors, and demographics. ResultsFive variables predicted poor sleep quality: perceived stress, sleep hygiene, sleep deficiency, worldview, and site. Greater stress positively associated with poorer sleep in both cultures. Yet, Bolivian students reported significantly more stress than American students but experienced significantly better sleep quality. Worldview, a measure of optimism or pessimism about the world, negatively associated with sleep quality in both cultures. ConclusionThree variables that predict sleep quality (worldview, sleep hygiene, and sleep deficiency) did not differ significantly between countries. Only perceived stress differed by country but contrary to the predicted direction. Thus, this work reveals new avenues for future work to the investigation of sleep in different cultures. Lastly, we offer recommendations to ameliorate poor sleep in university students.

Psychological Distress Induces Poor Sleep Quality: A Cross-Sectional Study of Pharmacy Students in Bandung City, Indonesia

Introduction: Poor subjective sleep quality in undergraduate students has not been widely studied in Bandung city, Indonesia. Poor sleep quality has been related to a number of risk factors for poor health outcomes. Objective: To analyze the association between psychological distress and subjective sleep quality. Methods: A cross sectional survey was done in one of the universities of Bandung city, Indonesia. Data were collected from 290 undergraduate students selected through consecutive sampling. Pittsburg Sleep Quality Index (PSQI) and Kessler-10 questionnaire were administered. Results: The prevalence of psychological distress was well (43.1%), mild (28.6%), moderate (20.7%), and severe (7.6%). The overall sleep quality was poor and good in 84.5% and 15.5% of the students. There was a significant association between psychological distress and poor sleep quality (p=0.006). The multivariate analysis suggested that psychological distress was a predictor of poor sleep quality (OR 1.991; 95% CI, 1.311−3.026). Conclusion: There is a need for an awareness of the college resources to help manage the stress levels of students through effective coping strategy-related study habits.

Predialysis fluid overload linked with quality of sleep in patients undergoing hemodialysis

ObjectiveHemodialysis (HD) patients are exposed to dysregulated fluid balance which can lead to overhydration. Poor sleep quality and excessive daytime sleepiness are particularly common in these patients, however the relationship between fluid status and sleep quality and daytime sleepiness has not yet been studied. Therefore, the aim of this study is to evaluate the correlations between fluid status and sleep quality and daytime sleepiness in HD patients. MethodThis cross-sectional study included 115 HD patients and 30 healthy control subjects from the HD center of Shanghai Ninth People's Hospital. Fluid compartments [total body water (TBW)], extracellular water (ECW)] and overhydration index (OH) were analyzed by multifrequency bio-impedance (BCM). Overhydration was defined as OH/ECW≥7%. HD patients were divided into an overhydration group and non overhydration group according to OH/ECW. Sleep quality was assessed by the Chinese version of the Pittsburgh Sleep Quality Index (PSQI), and excessive daytime sleepiness was evaluated by the Epworth Sleepiness Scale (ESS). ResultsThe prevalence rate of fluid overload in HD patients was 65.2%. Poor sleep quality (PSQI≥5) and excessive daytime sleepiness (ESS≥11) were significantly higher in HD patients compared with the healthy controls [6 (3, 10) vs.2.11 ± 1.59, p = 0.000; 3 (0, 6) vs.1.68 ± 1.07, p = 0.045]. Furthermore, the PSQI scores were higher in HD patients with overhydration (7.8 ± 4.5 vs. 4.8 ± 3.2, p = 0.000). The component scores 1, 2, 3 and 5 of the PSQI showed significant differences between the overhydration and non overhydration groups. The ESS scores did not show differences between the two groups (3.9 ± 4.1 vs. 3.3 ± 3.5, p = 0.508). OH was correlated with Systolic BP and Diastolic BP, and additionally was an independent predictor of poor sleep quality. ConclusionFluid overload is significantly linked with poor quality of sleep in HD patients, however there is no association with excessive daytime sleepiness. Our study provides new insight into possible treatment strategies. Future studies should examine the effects of optimizing fluid status on quality of sleep.

Prospective evaluation of the impact of covert hepatic encephalopathy on quality of life and sleep in cirrhotic patients.

Minimal hepatic encephalopathy (HE) and HE grade 1 (HE1) according to the West Haven criteria have recently been grouped as one entity named-covert HE- (CHE). Data regarding the impact of CHE on health-related quality of life (HRQoL) and sleep quality are controversial. First, to determine whether CHE affects HRQoL and sleep quality of cirrhotic patients and second, whether minimal HE (MHE) and HE1 affect HRQoL and sleep quality to a comparable extent. A total of 145 consecutive cirrhotic patients were enrolled. HE1 was diagnosed clinically according to the West Haven criteria. Critical flicker frequency and the Psychometric Hepatic Encephalopathy Score were used to detect MHE. Chronic Liver Disease Questionnaire (CLDQ) was used to assess HRQoL and Pittsburgh Sleep Quality Index (PSQI) was applied to assess sleep quality. Covert HE was detected in 59 (40.7%) patients (MHE: n=40; HE1: n=19). Multivariate analysis identified CHE (P<0.001) and female gender (P=0.006) as independent predictors of reduced HRQoL (CLDQ total score). CHE (P=0.021), low haemoglobin (P=0.024) and female gender (P=0.003) were identified as independent predictors of poor sleep quality (PSQI total score). Results of CLDQ and PSQI were comparable in patients with HE1 and MHE (CLDQ: 4.6±0.9 vs 4.5±1.2, P=0.907; PSQI: 11.3±3.8 vs 9.9±5.0, P=0.3). Covert HE was associated with impaired HRQoL and sleep quality. MHE and HE1 affected both outcomes to a comparable extent supporting the use of CHE as a clinically useful term for patients with both entities of HE in clinical practice.

A cross-sectional survey of the nature and correlates of sleep disturbance in people with psoriasis.

Research suggests that sleep disturbance is common in psoriasis. While several sleep investigations have been conducted in psoriasis populations, many have methodological shortcomings, and no study has examined multiple dimensions of sleep-wake functioning. Moreover, research has yet to be performed comprehensively examining the range of physical and psychological factors that may affect sleep in people with psoriasis. To characterize sleep disturbance using validated measures and to identify physical and psychological predictors of sleep quality in people with psoriasis. An online survey was conducted (186 respondents; mean age 39·2 years) comprising validated measures assessing sleep [Pittsburgh Sleep; Quality Index (PSQI), Berlin Questionnaire, Pre-Sleep Arousal Scale]; chronotype (Morningness-Eveningness Questionnaire); mood (Hospital Anxiety and Depression Scale); itch (5-D Itch Scale); and psoriasis severity (Simplified Psoriasis Index). Group comparisons and regression analyses were used to examine predictors of poor sleep. The mean PSQI score was 9·2 ± 4·3, with 76·3% scoring above the threshold for poor sleep (≥ 6 on the PSQI) and 32·5% scoring 'positive' for probable obstructive sleep apnoea (OSA). Poor sleep and high likelihood of OSA were associated with more severe psoriasis (P < 0·05; η = 0·07; η2 = 0·005). Cognitive arousal (β = 0·26, P = 0·001), itch (β = 0·26, P < 0·001) and depression (β = 0·24, P = 0·001) were the most robust predictors of poor sleep quality, which, together with somatic arousal (β = 0·17, P = 0·022), accounted for 43% of variance in PSQI scores. Poor sleep is common in psoriasis and associated with psychological and physical factors. Rates of probable OSA are also high. Given the importance of restorative sleep for health, sleep complaints should receive greater clinical attention in the management of psoriasis.

Prevalence and Predictors of Poor Sleep Quality in Patients on Maintenance Hemodialysis

Majority of patients on maintenance hemodialysis complain of poor quality of sleep. Earlier studies show controversial findings with regard to the prevalence and predictors of poor quality of sleep in this group. Hence, the present study was planned. Adult subjects undergoing maintenance hemodialysis were included in this study. Their demographic data, history regarding chronic kidney disease, co-morbidities, and details related to hemodialysis were recorded. Sleep quality was assessed using Pittsburg Sleep Quality Index. A total of 201 patients were included in this study. Average age of the subjects was 54.7 ± 15.1 years and duration of kidney disease was 37.1 ± 19.8 years. 40.3% subjects were women and 50.7% of sample complained of poor quality sleep. Poor sleepers had less than 3/week dialysis (68.6% among poor sleepers vs. 21.2% among good sleepers; P < 0.001), nighttime dialysis shift (52.9 vs. 20.2% among good sleepers; P < 0.001), diabetes mellitus (56.9 vs. 39.4% among good sleepers; P = 0.01), and hypnotic use (P < 0.001). Similarly, subjects with poor sleep quality were older (57.3 ± 14.3 vs. 52.1 ± 15.4 years among good sleepers; P = 0.01). Binomial logistic regression showed that less than thrice a week dialysis and schedule of maintenance hemodialysis predicted the poor sleep quality. Less than 3/week dialysis increased the odds for poor sleep by 6.6 (P < 0.001) and afternoon and nighttime maintenance hemodialysis shift by 3.2 (P < 0.001) and 4.6 (P < 0.001), respectively. Poor sleep is a common complaint in patients on hemodialysis. We found that the evening or night shift of hemodialysis and twice weekly hemodialysis worsened the quality of sleep.