Association between the hemoglobin-to-red cell distribution width ratio and poor sleep quality in US adults.

Children with overweight or obesity are more likely to experience sleep disorders, although the role of weight in pediatric insomnia treatment has not been examined. The current study examined the relationships of high body mass with pretreatment insomnia severity and global sleep problems and the potential moderating impact of weight on changes in insomnia severity following insomnia treatment. Participants included 1,133 youth ages 2-18 years clinically referred for insomnia treatment. The Pediatric Insomnia Severity Index was collected at the initial assessment and throughout treatment as part of routine clinical care. Treatment status was coded as no treatment, early termination, and completed treatment. Secondary measures of global sleep problems at the initial assessment included the Adolescent Sleep Wake Scale, Adolescent Sleep Hygiene Scale, and Children's Sleep Habits Questionnaire. Medical chart review of visits within ± 3 months of baseline was used to obtain age-adjusted and sex-adjusted body mass index Z-score. Among adolescents, regression analyses found that higher body mass index Z-score modestly predicted baseline insomnia severity (P = .021) and worse sleep hygiene (P < .001). For children, higher body mass index Z-score was modestly associated with baseline total sleep problems (P = .006) but not insomnia severity (P = .792). Across ages, body mass index Z-score predicted neither treatment status nor insomnia improvement (P > .05). Findings were similar in categorical analyses comparing patients with overweight/obesity to healthy weight. Although there is evidence that children of higher body mass present for insomnia treatment with greater sleep concerns, body mass does not predict treatment completion or insomnia improvement. Data suggest insomnia treatment is effective irrespective of weight status. Duraccio KM, Simmons DM, Beebe DW, Byars KC. Relationship of overweight and obesity to insomnia severity, sleep quality, and insomnia improvement in a clinically referred pediatric sample. J Clin Sleep Med. 2022;18(4):1083-1091.

BackgroundSeveral studies have indicated a potential association between obesity, depression, and sleep disorders. However, the role of depression in mediating the relationship between obesity and sleep disorders remains unclear. The Body Roundness Index (BRI), a more precise anthropometric measure of obesity than the traditional body mass index (BMI), is particularly effective in assessing body and visceral fat levels. This study examines the relationship between BRI and sleep disorders, with a focus on whether depression influences this association.MethodsThis study included data from 32,504 participants in the National Health and Nutrition Examination Survey (NHANES) 2005–2018 cycle. The association between BRI and sleep disorders was examined through subgroup analysis, restricted cubic spline (RCS) modeling, threshold effect analysis, and multivariable logistic regression. Furthermore, the predictive capabilities of various anthropometric indices—including BRI, weight-adjusted waist index (WWI), BMI, and weight—on sleep disorder incidence were assessed using Receiver Operating Characteristic (ROC) curve analysis. Finally, a Mediation analysis was also performed to explore the potential role of depression in this relationship.ResultsThis study included 32,504 participants, of whom 4,568 reported sleep disorders. After adjusting for all covariates using multivariable logistic regression, each one-unit increase in BRI was associated with a 13% higher prevalence of sleep disorders (OR = 1.13, 95% CI: 1.09, 1.16) and an 8% higher prevalence of depression (OR = 1.08, 95% CI: 1.05, 1.11). Similar results were obtained when BRI was divided into tertiles, with a significant trend (P for trend < 0.05). RCS and threshold effect analyses revealed a nonlinear relationship between BRI and sleep disorder prevalence, with a breakpoint of 3.508. The ROC curve analysis revealed that BRI had a superior predictive capability compared to traditional obesity indices, with an area under the curve (AUC) of 0.637 (95% CI, 0.628–0.645, all P < 0.001). Mediation analysis further indicated that 14% of the association between BRI and sleep disorders was mediated by depression (P < 0.001).ConclusionElevated BRI levels were linked to a higher prevalence of sleep disorders, with depression acting as a partial mediator in this relationship. These findings emphasize the potential connection between obesity, depression, and sleep disorders, highlighting the importance of managing visceral fat to mitigate the risk of sleep disorders.Clinical trial numberNot applicable.

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.

The purpose of this study was to determine sleep quality and presence of sleep disorders in participants with spinal cord injury (SCI). A web-based survey, available online from February 2011 to July 2013, using validated sleep questionnaires, advertised via the internet and locally through SCI consumer organizations in the United States, Australia, New Zealand, and Canada, was designed to evaluate sleep in adults with self-reported SCI. Demographic characteristics and medical history were obtained from participant self-report. In our study population, 70% of the 304 participants were male with a mean age of 45 ± 13 years. The mean duration of injury was 16 ± 12 years. Cervical injuries were reported by 49% and thoracic injuries noted in 40% of participants. Increased sleep apnea risk was noted in 31% of participants, with 66% reporting snoring. Insomnia symptoms were reported by 54% of the respondents. Almost 40% of participants ranked their sleep quality as "fairly bad" to "very bad" in the previous month, 29% reported "often" or "almost always" waking up because of pain, and 22% had difficulty falling asleep because of leg cramps. In the past year, 27% of the respondents reported daily uncomfortable leg sensations and 28% found these leg symptoms to be "moderately to extremely distressing." This study increases the awareness that insomnia, sleep apnea, and poor sleep quality are common in individuals with chronic SCI; often coexisting. There is a need for increased screening for sleep problems by healthcare providers taking care of individuals living with SCI.

Background: Sleep disorders are being more prevalent among general population. Its poor sleep quality causes depression, accidents, mortality, and morbidity among general population. Aim: To know the prevalence of sleep disorder among general population. Methods: Data was collected from general population of Karachi in 6 days. Questionnaire for Sleep-Quality Developed by Colin Espie, Professor of Sleep Medicine, University of Oxford was used to assess the sleep problems and sleep quality of respondents. Results: Moreover, 6.2% reported had severe sleeping problems and need clinical attention. 5.9% had some sleeping problems. 38.2% of respondents have good sleep while 49.75 had great sleep quality. Majority of respondents belong to age 20 to 30 age groups, students, undergraduate, female, exercised once in a week and were vegetarian. Age 20 to 30 age groups, students, undergraduate, female, exercised once in a week and being vegetarian was associated with sleep problem (P&lt;0.05). 20 to 30 age group, Health sector and inter education level, diabetes, obesity, difficult breathing, snoring while sleeping and smoking was associated with sleep problems(P&lt;0.05). Wherever, &gt;30 age group, undergraduate education level, students, exercising once in a week and eating vegetarian food were associated with good sleep quality(P&lt;0.05). Poor sleep quality causes depression, accidents, mortality, and morbidity among general population. Conclusion: This study will provide the important information to the higher authorities related to the most vulnerable groups related to sleep problems and factors associated with good sleep quality. Keywords: Sleep disorders, sleep quality, vulnerable groups, comorbidities

Sleep and allergic disease: A summary of the literature and future directions for research

Individuals with opioid use disorder (OUD) may experience worsening sleep quality over time, and a subset of individuals may have sleep disturbances that precede opioid use and do not resolve following abstinence. The purpose of the present study was to (1) collect retrospective reports of sleep across the lifespan and (2) identify characteristics associated with persistent sleep disturbance and changes in sleep quality in persons with OUD. Adults with OUD (n = 154) completed a cross-sectional study assessing current and past sleep disturbance, opioid use history, and chronic pain. Repeated-measures analysis of variance was used to examine changes in retrospectively reported sleep quality, and whether changes varied by screening positive for insomnia and/or chronic pain. Multivariate linear regression analyses were used to identify additional correlates of persistent sleep disturbance. Participants reported that their sleep quality declined over their lifespan. Changes in reported sleep over time varied based on whether the individual screened positive for co-occurring insomnia and/or chronic pain. In regression analyses, female sex (β = 0.16, P = .042), a greater number of treatment episodes (β = 0.20, P = .024), and positive screens for chronic pain (β = 0.19, P = .018) and insomnia (β=0.22, P = .013) were associated with self-reported persistent sleep disturbance. Only a portion of participants who screened positive for sleep disorders had received a formal diagnosis. OUD treatment providers should routinely screen for co-occurring sleep disturbance and chronic pain. Interventions that treat co-occurring OUD, sleep disturbance, and chronic pain are needed. Ellis JD, Mayo JL, Gamaldo CE, Finan PH, Huhn AS. Worsening sleep quality across the lifespan and persistent sleep disturbances in persons with opioid use disorder. J Clin Sleep Med. 2022;18(2):587-595.

To determine the incremental increases in health care utilization and expenditures associated with sleep disorders. Adults with a diagnosis of a sleep disorder (International Classification of Diseases, 10th Revision, code G47.x) within the medical conditions file of the 2018 Medical Expenditure Panel Survey medical conditions file were identified. This dataset was then linked to the consolidated expenditures file and comparisons in health care utilization and expenditures were made between those with and without sleep disorders. Multivariate analyses, adjusted for demographics and comorbidities, were conducted for these comparisons. Overall, 5.6% ± 0.2% of the study population had been diagnosed with a sleep disorder, representing approximately 13.6 ± 0.6 million adults in the United States. Those with sleep disorders were more likely to be non-Hispanic, White, and female, with a higher proportion with public insurance and higher Charlson Comorbidity Scores. Adults with sleep disorders were found to have increased utilization of office visits (16.3 ± 0.8 vs 8.7 ± 0.3, P < .001), emergency room visits (0.52 ± 0.03 vs 0.37 ± 0.02, P < .001), and prescriptions (39.7 ± 1.2 vs 21.9 ± 0.4, P < .001) vs those without sleep disorders. The additional incremental health care expenses for those with sleep disorders were increased in all examined measures: total health care expense ($6,975 ± $800, P < .001), total office-based expenditures ($1,694 ± $277, P < .001), total prescription expenditures ($2,574 ± $364, P < .001), and total self-expenditures for prescriptions ($195 ± $32, P < .001). Sleep disorders are associated with significantly higher rates of health care utilization and expenditures. By using the conservative prevalence estimate found in this study, the overall incremental health care costs of sleep disorders in the United States represents approximately $94.9 billion. Huyett P, Bhattacharyya N. Incremental health care utilization and expenditures for sleep disorders in the United States. J Clin Sleep Med. 2021;17(10):1981-1986.

Sleep quality and mental health in the context of COVID-19 pandemic and lockdown in Morocco

Association of sleep disorder with bulbar weakness and short-term outcomes in myasthenia gravis.

Sleep disorders in a sample of Egyptian high risk pregnant females

To determine the prevalence of sleep disorders in the United States and the association between sleep disorders and all-cause mortality. A cross-sectional analysis of the 2009 to 2010 National Health and Nutrition Examination Survey (NHANES) and 2015 National Death Index (NDI) was performed. The 2009 to 2010 NHANES national household survey for adults ≥ 18 years was examined for the prevalence of sleep disorders as well as standard demographics and the presence of comorbidities (coronary artery disease [CAD], stroke, and emphysema). This dataset was linked to the 2015 NDI to associate the presence of sleep disorders with 5-year all-cause mortality. The study sample had a mean age of 46.1 years old, was 48.3% male, and had an average body mass index (BMI) of 28.7 (28.4-28.9). 7.1% (6.5%-7.7%) of adults reported being diagnosed with a sleep disorder, which represents an estimated 15.9 million (13.2-18.6) patients. The estimated mortality rate for those having a sleep disorder was 9.3% (7.2%-11.9%) compared to 5.2% (4.5%-5.9%) without a sleep disorder (odds ratio 1.89, P = <.001). After adjusting for age, sex, BMI, CAD, stroke, and emphysema, having a sleep disorder remained a significant predictor of increased mortality (hazard ratio, 1.5 [1.02-2.18], P = .042). This study reports a high prevalence of self-reported but physician-diagnosed sleep disorders; however, this likely represents an underestimate. Given the association with all-cause mortality, there is a need for increased recognition of undiagnosed sleep disorders within the United States. 2b Laryngoscope, 131:686-689, 2021.

Sleep Disturbance and Disorders within Adult Inpatient Rehabilitation Settings: A Systematic Review to Identify Both the Prevalence of Disorders and the Efficacy of Existing Interventions

Adolescents and Emerging Adults' Sleep Patterns: New Developments

Background and Aims End stage kidney disease is a chronic condition known to have myriad effects in the different organ systems which directly impact quality of life. One aspect that is commonly affected but, unfortunately, may not be adequately addressed in this population is sleep problems. Various studies have shown that sleep disorders are highly prevalent in the dialysis population. As sleep is one of the inherent reparative mechanisms of the body, screening and identifying sleep problems may greatly translate to an improved quality of life and even over-all health. The aims of this study were to describe the sleep quality of hemodialysis patients in our local setting and ascertain the prevalence of sleep disorders, beginning with assessment of their sleep quality then dwelling more specifically with insomnia and obstructive sleep apnea syndrome (OSAS). These two sleep disorders are one of the most prevalent in the dialysis population with OSAS specifically related with adverse cardiovascular effects. Ultimately, this study envisioned to educate nurses, primary care physicians, and nephrologists about the importance of screening for sleep disorders in order to make proper referrals or initiate interventions that will improve sleep and well-being of dialysis patients. Method This study was a descriptive cross-sectional study conducted at a tertiary government hospital in Davao City, Philippines from July to September 2024. There were 189 adult hemodialysis patients included in the study. Excluded from the study were those below 19 years of age, patients on peritoneal dialysis, patients diagnosed with insomnia or any neurologic disorder that may hinder from understanding the questionnaires used. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) Questionnaire. Screening forms used to identify risk for insomnia and OSAS were PSQI and STOP-BANG Questionnaire, respectively. Results A total of 189 hemodialysis patients were evaluated for their sleep quality and screened for insomnia and obstructive sleep apnea. Majority of the patients were between the age of 41-60 years, males, and married. The top 3 causes of end stage renal disease were chronic glomerulonephritis, hypertensive kidney disease, and diabetic kidney disease. Common co-morbid illnesses were hypertension, diabetes, and cardiovascular disease. Majority were on 3x a week dialysis schedule, in the morning, with a 4-hour dialysis session. Hemodialysis access was mostly via arteriovenous fistula and dialyzers utilized were mostly hi-flux with dialyzer re-use at most for 5 dialysis sessions or below. Mean age was 49.1 years and mean dialysis vintage of 70.2 months. Majority of the patients were anemic with a mean hemoglobin of 106.6 g/L, mean phosphorus level of 5.2 mmol/L, URR reflected adequate hemodialysis with a mean of 69.1%, and mean BMI was 23.2 kg.m2 (overweight based on Asia-Pacific Body Mass Index Classification). The study showed a high prevalence of poor sleep quality and insomnia risk (68.3%) in all age groups of hemodialysis patients using the PSQI Questionnaire. The prevalence rate for OSAS was recorded at 45.0% using the STOP-BANG Questionnaire. None of the demographic and clinical parameters considered were associated with poor sleep quality and risk for insomnia. In contrast, older age, male sex, diabetic kidney disease, presence of co-morbid illness, higher BMI, and larger neck circumference were found to be significantly associated (p-value &amp;lt;.005) with OSAS. Moreover, there was no significant association noted between poor sleep quality and OSAS. Conclusion Poor sleep quality, insomnia, and obstructive sleep apnea are common problems in hemodialysis patients. The use of screening questionnaires like PSQI for sleep quality and insomnia and STOP-BANG for OSAS can be very helpful in hemodialysis patients for further evaluation and management.