Quality of Life, Self-Reported Cognitive Difficulties, and Performance-Based Cognitive Problems in Multiple Sclerosis: What's Sleep Got to Do With It?

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.

Introduction: Sleep quantity has been associated with higher risk of cardiovascular disease (CVD), however little is known about the impact of sleep quality on subclinical CVD. Hypothesis: Poor sleep quality is associated with subclinical CVD. Methods: We assessed the relationship between sleep quality and common carotid artery intima media thickness (IMT) through a cross-sectional analysis of a sub sample of 442 disease-free women from the Mexican Teacher’s Cohort. Sleep quality was evaluated through the Pittsburgh Sleep Quality Index (PSQI) in an online questionnaire applied to participants in 2014-2016. We defined poor sleep quality as a PSQI score above 5. Right and left carotid IMT was measured at clinical visits in 2012, 2013 and 2016 through carotid ultrasound performed by trained neurologists; results were log-transformed. Subclinical CVD was defined as the mean of right and left IMT ≥0.8mm or the presence of an atherosclerotic plaque. Multivariable linear and logistic regression models were used to evaluate the association of sleep quality with IMT or subclinical CVD, respectively. Results: In women of 49±5 years, the prevalence of poor sleep quality was 41% (185 of 442) and of subclinical CVD was 12.2% (54 of 442). The multivariable-adjusted percent difference of IMT was 2.4% (95% CI 0.03, 4.9), greater amongst those with poor sleep versus adequate sleep quality. The odds of developing subclinical CVD in women with poor sleep quality were 2.2 (95% CI 1.2, 4.1) times greater than those with adequate sleep quality (figure). Additionally, further adjustments for stress and depressive symptoms attenuated the results and were no longer statistically significant. Conclusion: Poor sleep quality is associated with IMT and subclinical CVD in a population of middle-aged women and this association is potentially mediated by stress and depression. Further analysis is needed regarding this association.

Objectives: To assess factors associated with poor sleep quality and excessive daytime sleepiness (EDS) in late pregnancy.Methods: A cross sectional study was carried out on 109 pregnant women in their third trimester admitted to Teaching Hospital Peradeniya using validated Sinhala translations of both Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS). Consecutive sampling was used from February to April 2021.Results: Application of PSQI demonstrated that 59.6% had a poor overall sleep quality (PSQI score&gt;5). Subcomponent analysis showed poor sleep duration (&lt; 06 hours per day) in 27.5%, sleep latency of over 30 minutes in 29.4%, poor sleep efficiency among 33.9% and day-time dysfunction in 30.3%. Poor overall sleep quality was associated with presence of foetal movements (OR=11.8, 95% CI=1.5-93.5) and backache (OR=3.8, 95% CI=1.2-12.3). Poor sleep duration was associated with the presence of one or more pregnancy related complications (OR=3.4, 95% CI=1.4-8.5) and advanced maternal age over 35 years (OR=3.7, 95% CI=1.4-9.7). Increased sleep latency over 30 minutes was seen in mothers over 34 weeks of gestation (OR=9.1, 95% CI=2.9-28.6) and over 10kg of weight gain (OR=5.3, 95% CI=1.2-24.4). Application of ESS demonstrated 26.6% had EDS, which was associated with maternal employment (OR=2.8, 95% CI=1.1-7.1) and higher educational status (OR=4.7, 95% CI=1.5-15.1). EDS did not result in poor sleep quality, however, mothers experiencing insomnia had a higher PSQI score (Mean ± SD 7.2±3.7 vs 6.2±3.4 hours, p=0.044).Conclusion: Majority of pregnant women in third trimester had poor overall sleep quality. EDS was seen among one fourth. Modifiable risk factors were associated with poor sleep quality and EDS.

IntroductionUnderstanding health behaviors, such as sleep and dietary patterns, is important for health promotion and disease prevention. College period is a complicated, difficult time to maintain healthy behaviors. In this regard, little is known about the impact of sleep and diet quality on well-being among college young adults. Hence, we aimed to study the impact of sleep and diet quality on well-being in college students.Materials and MethodsThree hundred-twelve Mexican college students (82% females; 20.6 ± 3.4years) were included in a cross-sectional study. Participants completed the following validated questionnaires: Well-being Index to assess well-being (high scores indicate high well-being), Pittsburg Sleep Quality Index for sleep quality (scores &gt; 5 indicate poor sleep quality), and a validate version of the Health Eating Index for Mexican population to assess diet quality (scores &gt; 80 indicate good diet quality). BMI and physical activity were also assessed. Scores were treated as continuous variables, and statistical analysis were performed using SPSS v24 and adjusted for confounding variables.ResultsSixty-seven percent of our population showed a poor sleep quality and eighty-four percent needs to make changes in their diet in order to improve its quality. On the other hand, fifty-one percent of the studied population had a low well-being perception. Poor sleep quality (p &lt; 0.001) and low diet quality (p &lt; 0.001) associated with a lower well-being perception. In addition, poor sleep quality is associated with low diet quality (p &lt; 0.05). Regarding food consumption, higher sweets (p &lt; 0.001) and soft-drink (p &lt; 0.001) intake was inversely associated with well-being scores. Likewise, high consumption of sweets (p &lt; 0.05) and soft-drink (p &lt; 0.05), and low fruit (p &lt; 0.05) and cereal (p &lt; 0.05) consumption are linked to poor sleep quality.DiscussionOur results show that half of the studied population had a low well-being, and also that poor sleep and diet quality are frequent among college students. Interestingly, the fact that poor sleep and diet quality were associated to a lower perception of well-being highlights the importance of promoting sleep hygiene and diet quality among college students as an important strategy to improve well-being and health, even in young adults. In addition, we found that higher sweets and soft-drink consumption were associated to both low well-being perception and poor sleep quality. Hence, it is important to promote healthy habits regarding eating and sleeping well, in order to improve well-being perception among college students.

This study aimed to determine the prevalence and associated factors of depressive symptoms, poor sleep, and life quality among patients with systemic sclerosis (SSc). This was a cross-sectional study including 120 SSc patients. Demographic and clinical data were obtained. The Short Form Health Survey 36 (SF-36), Pittsburgh Sleep Quality Index (PSQI), and short form of the Beck Depression Questionnaire were used to evaluate life quality, sleep quality, and self-reported depressive symptoms, respectively. The obtained data were analyzed to identify the demographic and clinical risk associations for depressive symptoms, poor sleep, and life quality. Of 120 participants, 108 patients (90%) were female. The mean age was 42.23 years, and the mean disease duration was 13.58 years. Most of the patients were married, unemployed, or housekeepers. Most of them had moderate economic conditions and tertiary education. The total scores of the SF-36 and PSQI questionnaires were 93.25±3.7 and 9.02±4.51, respectively, which showed good life quality but poor sleep quality. The prevalence of depressive symptoms was 44.16% (n=53), and most of them had mild to moderate depressive symptoms. The factors that correlated with life quality were occupational status and cough. The factors that negatively correlated with sleep quality were the presence of digital ulcers, cough, and dysphasia. The presence of cough, dyspnea, and gastroesophageal reflux disease was associated with depressive symptoms. Our study showed a high prevalence of poor sleep quality and depressive symptoms among SSc patients. We found that gastrointestinal symptoms, respiratory symptoms, and digital ulcers affected patients' life quality, sleep quality, and mental status. Our results also demonstrated that depression was correlated with poor sleep quality, and they were both risk factors for diminished life quality. Identification of these factors would help to make pharmacological and non-pharmacological interventions to improve the quality of life and sleep in SSc patients.

BackgroundThe prevalence of inadequate sleep in the general population is rising. While the detrimental health consequences of sleep disorders such as sleep‐disordered breathing are well established, little is known on the contributory role of perceived sleep quality on cardiometabolic risk profile. Importantly, poor sleep quality may be reported even in absence of objective findings of suboptimal sleep. We hypothesized that subjective poor sleep quality would be associated with markers of cardiometabolic risk in individuals without sleep disorders.MethodsWe compiled data from 667 research subjects (446 males, age 36.4±13.8 years) studied in the Cardiovascular/Sleep Laboratory at Mayo Clinic from 2000 to 2017. Subjects with history of sleep disorders and/or overt cardiovascular diseases, as determined from medical record or self‐report, were excluded from this study. Health status was further confirmed by physical exam. Supine systolic and diastolic blood pressure (SBP/DBP), height, weight, and waist and hip circumferences were collected. Body mass index (BMI, kg/m2) was derived from height and weight. Presence of hypertension (SBP and/or DBP ≥140/80 mmHg) and obesity (BMI ≥30 kg/m2) was recorded. Subjective sleep quality was self‐reported as either good or poor. Analysis of variance and Chi‐square tests were performed to examine differences in outcome measures according to sleep quality. Logistic regression models were run to examine the predictive value of poor sleep quality for hypertension and obesity risk.ResultsPoor subjective sleep quality was reported by 231 individuals out of 667 (34.6%). Subjects with perceived poor sleep were older (poor sleep vs good sleep: 42.3±12.9 years vs 33.2±13.3 years, p&lt;0.0001), with greater BMI (31.4±7 kg/m2 vs 26.5±6.3 kg/m2, p&lt;0.0001), waist (104.6±17.8 kg/m2 vs 89.7±14.8 kg/m2, p&lt;0.0001) and hip (111.8±14.8 kg/m2 vs 102.3±11.5 kg/m2, p&lt;0.0001) circumference than good sleepers. Compared to the latter group, SBP and DBP values were also higher in self‐evaluated poor sleepers (poor sleep vs good sleep, SBP: 128.8±15.5 mmHg vs 122.9±14.4 mmHg, p&lt;0.0001; DBP: 74.5±10.6 mmHg vs 71.8±11.4 mmHg, p=0.012). Obesity was more prevalent in those with subjective poor sleep quality than in good sleepers (53.3% vs 19.7%, p&lt;0.0001). Similarly, 72.5% of patients with hypertension reported poor sleep quality while only 27.5% of them were good sleepers (p&lt;0.0001). In comparison to good sleep quality, perceived poor sleep was associated with 3.6 times greater risk of obesity (95% CI 2.5, 5.2, p&lt;0.0001) and 3.5 times greater risk of hypertension (95% CI 1.7, 6.9, p=0.0004) after correcting for conventional covariates. Significance was retained after further adjustment for reported snoring and witnessed apneas.ConclusionsPoor perceived sleep quality is independently associated with elevated risk of high blood pressure and excess body weight in individuals without sleep disorders. These findings favor the concept that promoting adequate sleep quality, even subjectively, may benefit cardiometabolic health.Support or Funding InformationAmerican Heart Association grant 16SDG27250156; National Institutes of Health grants RO1 HL 065176 and HL 134808.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Female athletes with menstrual abnormalities have poor sleep quality. However, whether female athletes with poor sleep quality based on subjective assessment have distinctive changes in objective measures of sleep in association with menses remains unclear. This study aimed to compare changes in objective sleep measurements during and following menses between collegiate female athletes with and without poor subjective sleep quality. Female collegiate athletes (age range/mean ± standard deviation: 18-22/ 22.2±1.1) with regular menstrual cycles were recruited. The participants underwent home electroencephalogram monitoring during the first and second nights after the onset of menses and one night between the seventh and 10th nights after menses onset (mid-follicular phase). The Pittsburgh Sleep Quality Index (PSQI) was used to assess the subjective sleep quality. Interactions between the presence of poor subjective sleep quality (ie, PSQI ≥6) and changes in objective measures of sleep in association with menses were analyzed. Data of 45 athletes, including 13 with poor subjective sleep quality, showed that changes in arousal index in athletes with poor subjective sleep quality were distinctive from those in athletes without poor subjective sleep quality (p = 0.036 for interaction). In athletes with poor subjective sleep quality, the arousal index was significantly increased in menses (p for analysis of variance, 0.015), especially on the first night after the onset of menses compared with during the mid-follicular phase (p = 0.016). Collegiate female athletes with regular menstrual cycles are likely to have poor subjective sleep quality in association with more frequent arousal during the first night after the onset of menses than during the mid-follicular phase.

Sleep is a vital biological, reparative, and restorative phenomenon, and poor sleep has a serious detrimental effect on health. Poor sleep quality is a serious problem as it adversely affects a person's ability to function physically and socially, as well as their potential for profession and quality of life. The degree of hypertension directly affects sleep quality, and poor sleep can exacerbate hypertensive symptoms. This study assesses hypertension patients' sleep quality in a rural health training centre in Chennai. 1. To study the prevalence of poor sleep quality among hypertensive patients. 2. To determine the association between selected socio-demographic factors and sleep quality among these patients. Hypertensives attending the outpatient department of a rural health and training centre were selected in a systematic manner and administered a semi-structured interview schedule and the Pittsburgh Sleep Quality Index (PSQI) questionnaire followed by a basic clinical examination. Using the PSQI, they were categorised as having either poor or good sleep quality and the association between selected socio-demographic factors and sleep quality was assessed. Out of the 179 study participants, there were almost equal numbers of male and female participants. The mean age of participants was 57.80 years (standard deviation (SD) = 9.8 yrs.). Among the study participants, 44.13% had completed secondary level of school as an education qualification and 6.70% were illiterate. By the modified BG Prasad classification 2022, most of the study participants (34.08%) came under the class II socioeconomic classification. A large proportion (78.8%) of study participants had poor sleep quality. The difference in sleep quality was observed with respect to gender, socio-economic class, alcohol consumption and body mass index (BMI). This observational study shows that individuals with hypertension suffer significantly from poor sleep. A poor quality of sleep was reported by 78.77% of the patients in this study. Statistically significant factors that influenced sleep quality were gender, alcohol consumption and BMI.

Despite the evidence of a relationship between loneliness, problematic social networking sites use (PSNSU), and sleep quality, associations between specific PSNSU symptoms and loneliness in individuals with poor vs. good sleep quality and possible gender differences have yet to be understood. We examined the relationships between loneliness and PSNSU symptoms (i.e., preference for online social interaction – POSI, mood regulation, deficient self-regulation, and negative outcomes), and possible moderating effects of gender for individuals with poor vs. good sleep quality. Seven hundred and sixty-three young adults completed an online survey including self-report measures of sleep quality, loneliness, and PSNSU symptoms. Individuals with poor sleep quality reported higher levels of loneliness and greater scores on all PSNSU domains than those with good sleep quality. Slope analyses revealed that in men vs. women with poor sleep quality, greater deficient self-regulation of social networking sites use was associated with lower levels of loneliness. Conversely, in men vs. women with good sleep quality, greater POSI was associated with higher levels of loneliness. Our findings showed that individuals with poor sleep quality are characterized by higher levels of loneliness and more severe PSNSU symptoms that may be the result of sleep disturbance-related metabolic, neural, and hormonal processes. Moreover, our results highlight gender differences for individuals with poor vs. good sleep quality which may help clarify the nature of the association between loneliness and PSNSU.

Objectives:Adhering to management guidelines, including routine follow-up and education, is crucial for the effective management of chronic diseases such as diabetes. Uncontrolled diabetes is linked to poor sleep quality. We used nationally representative data from community-dwelling Koreans to investigate potential associations between non-adherence to diabetes management and poor sleep quality.Methods:Of the 228 340 participants in the 2018 Korea Community Health Survey, we analyzed data from 68 246 participants aged 65 years and older. Based on their diabetes status and adherence to diabetes-related tests (glycated hemoglobin, fundus examination, and urine microalbuminuria) and management education, study participants were divided into 3 groups: no diabetes, adherence, and non-adherence. Outcome variables included poor overall sleep quality and sleep disturbances, as measured by the Pittsburgh Sleep Quality Index.Results:The study included 934 participants in the adherence group (2.0%) and 13 420 in the non-adherence group (20.2%). Participants displaying non-adherence were significantly more likely to report poor overall sleep quality (adjusted odds ratio [aOR], 1.09; 95% confidence interval [CI], 1.04 to 1.13) and to experience sleep fragmentation, nocturia, pain during sleep, and difficulty falling asleep compared to participants without diabetes. Even in the earlier stage of diabetes, non-adherent participants were more likely to report poor sleep quality (aOR, 1.06; 95% CI, 1.00 to 1.18).Conclusions:Patients with diabetes who do not follow management guidelines are more likely to experience poor sleep quality than those without diabetes. Emphasizing diabetes management and increasing awareness of management strategies may improve sleep quality among patients with this disease.

Introduction Diagnoses of cancer and depression are independent predictors of poor sleep, but less is known about subjective sleep quality among patients with both of these potential risk factors or about recommendations made by physicians for improving sleep among this population. This study examines correlates of poor subjective sleep quality and sleep recommendations received by patients with cancer enrolled in the Collaborative Oncology Project to Enhance Depression Care (COPE-D), a collaborative care intervention to treat depression among patients with cancer. Methods Participants were 74 adult cancer survivors. Demographic and clinical characteristics, subjective sleep quality, and provider sleep recommendations were obtained by patient self-report prior to intervention. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI), general health status was measured using the PROMIS Global-10, and depressive symptoms were measured using the PHQ-9. Results 81% of patients reported significantly poor sleep quality (PSQI global scores &amp;gt;8) and 75.3% reported poor sleep efficiency (&amp;lt;85%). The strongest correlates of poor sleep quality were worse global mental (r=-.431, p&amp;lt;.01) and physical health (r=-.40, p=&amp;lt;.01). 63% reported pain interference with sleep at least once per week. Cancer type and stage, current cancer treatment, and depressive symptoms were not significantly associated with poor sleep quality (p’s&amp;gt;.05). 12% of those reporting sleep disturbances since their cancer diagnosis had not discussed these problems with a medical provider. Among those who talked to their provider, 41.8% reported receiving sleep hygiene recommendations, 40.5% anti-depressants, 14.9% sedative-hypnotic medication (e.g. zolpidem, benzodiazepines), 10.8% cognitive behavioral therapy, 9.6% antihistamines, 6.8% melatonin, and 4.1% were recommended meditation or hypnosis. Conclusion Cancer patients seeking treatment for depression report very high rates of poor subjective sleep quality, which was most strongly associated with global mental and physical health. Improved screening and patient-provider communication about sleep may be especially beneficial for this at-risk population. Support Merck Foundation Alliance to Advance Patient-Centered Cancer Care

A multidimensional approach to sleep health in multiple sclerosis

Interim results of a quality improvement study evaluating subjective and objective sleep quality in hospitalized adults with acute leukemia

ABSTRACTObjective/Background: Poor sleep quality is common in pregnancy and associated with increased psychological distress, which has adverse consequences for families. Emerging theory suggests that mindfulness-based interventions may help reduce cognitive and emotional reactivity to stressful events. The current study examines the effects of a mindfulness-based intervention on the relationship between poor sleep quality and increased depression symptom severity and perceived stress during pregnancy. Additionally, we explored the prevalence of poor sleep quality in this unique sample and the impact of intervention on sleep quality. Participants: Participants were 215 ethnically diverse, overweight and obese, predominantly low-income pregnant women drawn from a study examining the impact of an 8-week mindfulness-based program (Mindful Moms Training; MMT) to reduce excessive gestational weight gain, stress, and depression compared to treatment as usual (TAU). Methods: Participants reported global sleep quality, depressive symptoms, and perceived stress at baseline and postintervention. Results: Most participants (63%) were categorized as poor sleepers at baseline. MMT participants did not experience significantly greater improvement in sleep quality compared to TAU participants. Baseline poor global sleep quality predicted increased depression symptom severity for all participants. Baseline poor global sleep quality predicted increased perceived stress for the TAU group only; this association was not evident in the MMT group. Conclusions: Poor sleep quality is prevalent in overweight and obese predominantly low-income pregnant women. Poor sleep quality was associated with worsening psychological distress, but mindfulness training significantly attenuated the influence of poor sleep on perceived stress.

To identify a screening tool for poor self-reported sleep quality at 12 weeks according to non-invasive measurements and patients’ characteristics in the first week after mild traumatic brain injury (mTBI), data from 473 mTBI participants were collected and follow-ups were performed at 12 weeks. Patients with previous poor self-reported sleep quality prior to the injury were excluded. Patients were then divided into two groups at 12 weeks according to the Pittsburgh Sleep Quality Index based on whether or not they experienced poor sleep quality. The analysis was performed on personal profiles and heart rate variability (HRV) for 1 week. After analyzing the non-invasive measurements and characteristics of mTBI patients who did not complain of poor sleep quality, several factors were found to be relevant to the delayed onset of poor sleep quality, including age, gender, and HRV measurements. The HRV–age–gender (HAG) index was proposed and found to have 100% sensitivity (cut-off, 7; specificity, 0.537) to predicting whether the patient will experience poor sleep quality after mTBI at the 12-week follow-up. The HAG index helps us to identify patients with mTBI who have no sleep quality complaints but are prone to developing poor self-reported sleep quality. Additional interventions to improve sleep quality would be important for these particular patients in the future.