Predictors Of Poor Sleep Quality Research Articles

Sleep quality and associated factors among adult patients with epilepsy attending follow-up care at referral hospitals in Amhara region, Ethiopia.

Globally, epilepsy is the commonest neurological disorder in adults. It has significant health and economic consequences to the affected individuals and the family. There is ample evidence that epileptic patients are at increased risk of poor sleep quality than the general population. However, there is limited evidence on sleep quality among epileptic patients and associated factors in Ethiopia. Therefore, this study investigated the prevalence of poor sleep quality and associated factors among adult patients with epilepsy. Institutional based cross-sectional study was conducted among adult epileptic patients attending follow-up care at referral hospitals in the Amhara region. A total of 575 epileptic patients were recruited using a stratified systematic random sampling technique. An interviewer-administered semi-structured questionnaire and record review were used for data collection. To assess sleep quality the pretested Pittsburgh Sleep Quality Index (PSQI) tool was used. A binary logistic regression model was used to assess factors associated with poor sleep quality. Variables with a p-value less than 0.2 in the bivariable binary logistic regression analysis were considered for the multivariable binary logistic regression analysis. In the multivariable binary logistic regression analysis, the Adjusted Odds Ratio (AOR) with the 95% Confidence Interval (CI) were reported to declare the statistical significance and strength of association. Model fitness was assessed using the Hosmer-Lemeshow test and was adequate (p>0.05). Multicollinearity of the independent variables was assessed using the Variance Inflation Factor (VIF) and the mean VIF was less than 10. A total of 565 participants were enrolled in the study with a response rate of 98.3%. The prevalence of poor sleep quality among adult epileptic patients was 68.8% [95% CI: 64.8%, 72.5%]. In the multivariable binary logistic regression, being unable to read and write [AOR = 3.16, 95%CI: 1.53, 6.51], taking polytherapy treatment [AOR = 2.10, 95% CI: 1.37, 3.21], poor medication adherence [AOR = 2.53, 95%CI: 1.02, 6.23] and having poor support [AOR = 2.72, 95%CI: 1.53, 4.82] and moderate social support [AOR = 1.89, 95%CI: 1.05, 3.41] were significantly associated with higher odds of poor sleep quality. Poor sleep quality is a major public health concern in Ethiopia. The patient's level of education, number of medication use, medication adherence, and social support were found significant predictors of poor sleep quality. These findings highlight improving medication adherence and social support are effective strategies to improve the sleep quality of epileptic patients. Besides, it is better to give special emphasis to those epileptic patients with a low level of education and taking polytherapy to enhance sleep quality.

Internet addiction and sleep quality among medical students during the COVID-19 pandemic: A multinational cross-sectional survey.

The emergence of the COVID-19 pandemic has affected the lives of many people, including medical students. The present study explored internet addiction and changes in sleep patterns among medical students during the pandemic and assessed the relationship between them. A cross-sectional study was carried out in seven countries, the Dominican Republic, Egypt, Guyana, India, Mexico, Pakistan, and Sudan, using a convenience sampling technique, an online survey comprising demographic details, information regarding COVID-19, the Pittsburgh Sleep Quality Index (PSQI), and the Internet Addiction Test (IAT). In total, 2749 participants completed the questionnaire. Of the total, 67.6% scored above 30 in the IAT, suggesting the presence of an Internet addiction, and 73.5% scored equal and above 5 in the PSQI, suggesting poor sleep quality. Internet addiction was found to be significant predictors of poor sleep quality, causing 13.2% of the variance in poor sleep quality. Participants who reported COVID-19 related symptoms had disturbed sleep and higher internet addiction levels when compared with those who did not. Participants who reported a diagnosis of COVID-19 reported poor sleep quality. Those living with a COVID-19 diagnosed patient reported higher internet addiction and worse sleep quality compared with those who did not have any COVID-19 patients in their surroundings. The results of this study suggest that internet addiction and poor sleep quality are two issues that require addressing amongst medical students. Medical training institutions should do their best to minimize their negative impact, particularly during the current COVID-19 pandemic.

Association of Poor Sleep With Depressive and Anxiety Symptoms by HIV Disease Status: Women's Interagency HIV Study.

Background:Sleep disturbances are prevalent in women living with HIV (WLWH) and can affect mental health and overall quality of life. We examined the prevalence and predictors of poor sleep quality in a US cohort of WLWH and HIV-uninfected controls and the relationship between sleep quality and mental health symptom burden stratified by HIV disease status (viremic WLWH, aviremic WLWH, and HIV-uninfected women).Methods:Sleep quality was assessed using the Pittsburgh Sleep Quality Index in 1583 (400 viremic WLWH, 723 aviremic WLWH, and 460 HIV-uninfected women) Women's Interagency HIV Study participants. Depressive and anxiety symptoms were concurrently assessed using the Center for Epidemiological Studies-Depression (CES-D) scale and General Anxiety Disorder (GAD-7) scale. Associations between poor sleep quality (global Pittsburgh Sleep Quality Index >5) and both high depressive (CES-D ≥16) and anxiety (GAD-7 ≥10) symptoms were each assessed by HIV disease status using multivariable logistic regression models.Results:Prevalence of poor sleep quality in the overall sample was 52%, differed by HIV disease status (P = 0.045), and was significantly associated with high depressive and anxiety symptoms in (1) viremic WLWH, (2) aviremic WLWH, and (3) HIV-uninfected women [CES-D: (1) adjusted odds ratio (aOR) = 7.50, 95% confidence interval (CI): 4.10 to 13.7; (2) aOR = 4.54, 95% CI: 3.07 to 6.73; and (3) aOR = 6.03, 95% CI: 3.50 to 10.4; GAD-7: (1) aOR = 5.20; 95% CI: 2.60 to 10.4, (2) aOR = 6.03; 95% CI: 3.67 to 9.91, and (3) aOR = 6.24; 95% CI: 3.11 to 12.6].Conclusions:Poor sleep quality is highly prevalent, as is mental health symptom burden, among WLWH and HIV-uninfected controls. Future longitudinal studies are necessary to clarify the directionality of the relationship.

Longitudinal epidemiological study of subjective sleep quality in Japanese adolescents to investigate predictors of poor sleep quality.

The online version contains supplementary material available at 10.1007/s41105-021-00343-8.

Prevalence of sleep disruption and determinants of sleepiness in a cohort of Italian hospital physicians: The PRESOMO study.

Nightshift work can cause daytime somnolence and decreased alertness, and can increase risk of medical errors, occupational injuries and car accidents. We used a structured questionnaire, including the Epworth Sleepiness Scale (ESS), to assess the prevalence and the determinants of sleep disruption in 268 Italian University hospital physicians from Cagliari (N = 57), Milan (N = 180) and Pisa (N = 31), who participated in the multicentre study on the prevalence of sleep disturbance among hospital physicians (PRESOMO); 198 of them (74%) were engaged in nightshift work. We explored the association between history of nightshift work and poor sleep quality and daytime somnolence with multivariate logistic regression, adjusting by personal and lifestyle covariates. Age, female gender, taking medication interfering with sleep and an elevated ESS score were significant predictors of poor sleep quality and daytime somnolence. Nightshift work was associated with a higher prevalence of unrestful sleep (84% versus 70%; odds ratio [OR] = 2.4, 95% confidence interval [CI] 1.18–5.05) and daytime dozing (57% versus 35%; OR = 1.9, 95% CI 1.03–3.64), with an upward trend by years of engagement in nightshift work for both conditions (p = .043 and 0.017, respectively), and by number of nightshifts/year for unrestful sleep (p = .024). Such an association was not detected with the ESS scale. Our results suggest that nightshift work significantly affects sleep quality and daytime somnolence in hospital physicians, who might underestimate their daytime dozing problem, when asked to subjectively scale it.

Gambling Problems Are Associated with Alcohol Misuse and Insomnia: Results from a Representative National Telephone Survey.

Gambling has significant costs to the community, with a health burden similar in scale to major depression. To reduce its impact, it is necessary to understand factors that may exacerbate harm from gambling. The gambling environment of late-night licensed venues and 24/7 online gambling has the potential to negatively impact sleep and increase alcohol consumption. This study explored gambling, alcohol, and sleep problems to understand whether there is a relationship between these three factors. Telephone interviews were conducted with a representative sample of Australian adults (n = 3760) combined across three waves of the National Social Survey. Participants completed screening measures for at-risk gambling, at-risk alcohol consumption, insomnia (2015 wave only), and sleep quality. There were small but significant positive correlations between problem gambling and alcohol misuse, problem gambling and insomnia, and problem gambling and poor sleep quality. A regression model showed that gambling problems and alcohol misuse were significant independent predictors of insomnia. A separate regression showed gambling problems (and not alcohol misuse) were a significant predictor of poor sleep quality, but only in one survey wave. Findings suggest that gambling, alcohol, and sleep problems are related within persons. Further research should examine the mechanisms through which this relationship exists.

Body image dissatisfaction and lower self-esteem as major predictors of poor sleep quality in gynecological cancer patients after surgery: cross-sectional study

BackgroundSleep quality is among the indicators associated with the quality of life of patients with cancer. A multitude of factors may affect patient sleep quality and are considered as associated predictive factors. The aim of this study was to examine the predictors of poor sleep quality in Moroccan women with gynecological cancer after radical surgery.MethodsA cross-sectional study was carried out at the Oncology Department of the Ibn Rochd University Hospital, Casablanca (Morocco), on women who had undergone radical surgery for gynecological cancer (n = 100; mean age: 50.94 years). To assess sleep quality, symptoms of depression and anxiety, self-esteem and body image, the following translated and validated Arabic versions of the tools were used: Pittsburgh Sleep Quality Index (PSQI), Hospital Anxiety and Depression Scale, Rosenberg’s Self-Esteem Scale and Body Image Scale. To determine predictors of sleep quality, multiple linear and hierarchical regressions were used.Results78% of participants were considered poor sleepers, most of them exhibited very poor subjective quality (53%), longer sleep onset latency (55%), short period of sleep (42%) and low rate of usual sleep efficiency (47%). 79% of these patients did not use sleep medication and 28% were in poor shape during the day. Waking up in the middle of the night or early in the morning and getting up to use the bathroom were the main reasons for poor sleep quality. Higher PSQI scores were positively correlated with higher scores of anxiety, depression, body image dissatisfaction and with lower self-esteem (p < 0.001). The medical coverage system, body image dissatisfaction and low self-esteem predicted poor sleep quality. After controlling for the socio-demographic variables (age and medical coverage system), higher body image dissatisfaction and lower self-esteem significantly predicted lower sleep quality.ConclusionBody image dissatisfaction and lower self-esteem were positively linked to sleep disturbance in women with gynecological cancer after undergone radical surgery. These two predictors require systematic evaluation and adequate management to prevent sleep disorders and mental distress as well as improving the quality of life of these patients.

Associations Between Chrononutrition With Sleep Quality and Melatonin Rhythm of Pregnant Women

Abstract Objectives Chrononutrition is referred to as a zeitgeber for its ability to synchronize the circadian rhythm. In addition to the role as circadian marker, sleep and melatonin are important factors for optimal maternal and infant outcomes. Understanding the chrononutrition factors associated with sleep quality and melatonin rhythm during pregnancy has practical importance for preventive care. Hence, this study aimed to examine the association between chrononutrition with sleep quality and melatonin rhythm during pregnancy. Methods A total of 114 primigravidas were recruited at randomly selected government maternal and child clinics in Kuala Lumpur, Malaysia. Gestational age and pre-pregnancy body mass index (BMI) were extracted from clinic records. Components of chrononutrition including meal timing, meal frequency, eating window, breakfast skipping, and night eating were assessed using 3-day food record. Sleep quality in the third trimester was determined using Pittsburgh Sleep Quality Index (PSQI). Subsample (n = 48) provided salivary samples at 4 time-points (9:00, 15:00, 21:00 and 3:00 h) over 24 hours for melatonin assay. Results The mean gestational age of participants was 33.0 (2.1) weeks; 13% were underweight and 22% were overweight/obese before pregnancy. Average daily meal frequency was 4.1 (0.9). The majority (68%) practiced a shorter eating window (≤12 hours); 25% skipped breakfast and 19% ate within 2 hours pre-bedtime. The prevalence of poor sleep among the participants was 56%. Mean salivary melatonin level was 19.6 (16.3) pmol/L. In the adjusted linear regression model, lower meal frequency and fat intake during dinner were significant predictors of poor sleep quality (β = −0.266, P = 0.035 and β = −0.232, P = 0.026, respectively). Eating nearer to bedtime was significantly associated with greater deviation of melatonin acrophase from mid-sleep clock time (β = −0.339, P = 0.043). Conclusions Findings suggested that unfavorable characteristics of chrononutrition may contribute to poor sleep and misalignment of melatonin phase. Components of chrononutrition may be incorporated into meal intervention to improve maternal sleep quality and circadian health. Funding Sources Research relating to this abstract was funded by the Ministry of Education Malaysia Fundamental Research Grant.

Poor sleep quality and its associated factors among pregnant women in Northern Ethiopia, 2020: A cross sectional study.

Sleep is a physiologic necessity for all humankind. Pregnant women, in particular, need adequate sleep to develop their fetuses as well as save energy required for delivery. A change in sleep quality and quantity is the most common phenomena during pregnancy due to mechanical and hormonal factors. However, there is a scarcity of data about poor sleep quality and its associated factors among pregnant mothers in Ethiopia. Therefore, this study aims to determine the prevalence of poor sleep quality and its associated factors among pregnant mothers at Wadila primary hospital, Ethiopia. Institution based cross-sectional study design was employed on 411 pregnant mothers. Data were collected using a pre-tested interviewer administered questionnaire. SPSS Version 23 for Windows software was used for data analyses. Bivariate analysis was conducted to detect the association between dependent and independent variables, and to choose candidate variables (p < 0.25) for multivariate logistic regression. Statistical significance was set at p-value <0.05. A total of 411 participants were included in the study making a response rate of 97.4%. Overall, 68.4% of participants found to have poor sleep quality (PSQI>5). Age of the mother [age 20-30 years; AOR = 4.3 CI (1.8, 9.9), p = 0.001, and age >30 years; AOR = 4.7 CI (1.6, 13.9) p = 0.005], gestational age [second trimester, AOR = 2.46, CI (1.2, 4.9), p = 0.01 and third trimester, AOR = 7.5, CI (3.2, 17.8), p = 0.000] and parity [multiparous women; AOR = 2.1(1.24, 3.6) p = 0.006] were predictor variables for poor sleep quality among pregnant mothers. More than two-third of pregnant mothers had poor sleep quality. Advanced maternal age, increased gestational age and multiparty are found to be predictors of poor sleep quality in pregnant women.

Sleep Disturbance in Inflammatory Bowel Disease Is Associated with Disease Activity and Adverse Outcome

Background: There is growing evidence about the relationship between sleep quality (SQ) and disease activity in inflammatory bowel disease (IBD). This study aimed to identify the prevalence of sleep disturbance in IBD and its predictive factors and to assess its association with worse outcome. Methods: IBD patients were prospectively enrolled. Clinical activity, inflammatory activity (high C-reactive protein or fecal calprotectin), and SQ (assessed using the Pittsburgh Sleep Quality Index) were evaluated, and logistic regression was used to identify predictors of poor SQ at baseline. The development of disability or disease progression at 6 months (surgery, hospitalization, development of stenosis, penetrating or perianal disease, steroid dependency, or start/change immunosuppression) was compared between patients with and without poor SQ. Results: Two hundred and five patients were enrolled, with 44.9% (n = 92) reporting poor SQ. On multivariate analysis, current smoking (OR 2.80), extraintestinal manifestations (OR 2.68), clinical activity (OR 3.31), and inflammatory activity (OR 4.62) were predictive factors of poor SQ. Cox proportional hazards model showed that poor SQ was predictive of worse prognosis at 6 months (HR 2.470). Conclusion: There is a high prevalence of poor SQ in IBD patients, highlighting the importance of its inclusion in patient-reported outcomes. Sleep disturbance seems to have prognostic value in IBD.

Prevalence of Poor Sleep Quality Among Physicians During the COVID-19 Pandemic.

Background: Sleep quality is influenced adversely or favorably by various intrinsic and extrinsic factors and sleep deprivation is a common problem facing doctors.Objectives: To assess sleep quality among physicians during coronavirus disease 2019 (COVID-19) pandemic and correlate it with possible predictors.Methods: This cross-sectional four-months study included a total of 344 physicians from different medical centers in the period between July 2020 and October 2020, during the COVID-19 pandemic. Physicians were aged between 24 and 60 years from different specialties. Data were collected using the Pittsburgh Sleep Quality Index (PSQI) questionnaire and Hospital Anxiety Depression Scale (HADS).Results: Among our participant physicians there was poor sleep quality in 71.2%, while good sleep quality was present in 28.8%. There were significant correlations between poor sleep quality and the following parameters in the univariate logistic regression analysis: anxiety features (P value <0.001), depressive features (P value <0.001), and past history of COVID-19 (P value 0.003). However, multivariate logistic regression analysis showed that only the presence of anxiety features (P value <0.001) and depressive features (P value <0.001) could be used as significant independent predictor of poor sleep quality among physicians during COVID-19.Conclusion: Presence of anxiety and or depressive features among physicians are the most significant independent predictors of poor sleep quality during the COVID-19 pandemic.

Sleep quality in stable chronic obstructive pulmonary disease patients in Zagazig University Hospitals, Egypt

BackgroundChronic obstructive pulmonary disease (COPD) causes changes in sleep quality with accompanied nocturnal drops in oxygen saturation leading to cardiac dysrhythmias, pulmonary hypertension, and more arousal. However, this sleep disturbance is an aspect of COPD that is still under evaluation. Therefore, this work is designed to detect sleep quality with type and frequency of sleep-related breathing disorders in stable COPD patients.ResultsThis is a cross-sectional study that included 60 stable COPD patients. Full night polysomnographies were performed to all patients with assessment of their sleep quality and presence of sleep-disordered breathing. The studied patients were classified into two groups: group I (COPD with good sleep quality) and group II (COPD with poor sleep quality). The results revealed that the more severe the COPD degree, the worse the sleep quality parameters represented by sleep latency, sleep efficiency, and arousal index with a significant statistical difference (P < 0.05). Furthermore, a highly significant statistical difference was noticed regarding time spent in REM sleep among poor sleep quality patients with different grades of severity (P = 0.003). Additionally, obstructive sleep apnea hypopnea syndrome was the most frequent sleep-disordered breathing (65%), followed by nocturnal oxygen desaturation (17%) among poor quality sleeper.ConclusionAbnormal sleep quality is more common in moderate and severe COPD patients. Obstructive sleep apnea is the most frequent sleep-related breathing disorders among COPD patients. Increased BMI%, higher Berlin scores, and lower values of PaO2 and FOSQ-10 scores are strong predictors of poor sleep quality among COPD patients.

Sleep quality among cardiac patients on follow up at Jimma Medical Center, southwestern Ethiopia.

IntroductionChronic heart failure is associated with changes in sleep pattern and affects quality of sleep among patients with heart failure. Poor sleep has a negative impact on the patients’ quality of life, furthermore it compromises cognition and one’s self-care practice. Though, factors affecting sleep among heart failure patients have been investigated in developed world, there are limited studies in regards to it in developing countries like Ethiopia.ObjectiveThe aim of the study is to assess the level of sleep quality and associated factors among heart failure patients who are on follow up at Jimma Medical Center (JMC).Material and MethodsHospital based cross sectional study was employed among the total sample of 111 chronic heart failure patients admitted to medical ward and having follow up at cardiac center of JMC. The data was collected from April 1 - April 30, 2019 through face-to-face interview by using structured questionnaire. Pittsburg Sleep Quality Index (PSQI) was applied to assess sleep quality. PSQI score <5 refers to good sleep quality. Data was checked, cleaned for possible errors, entered into Epidata version 4.3.1 and finally exported to SPSS version 20 for further analysis. Appropriate statistical analyses (cross tabulation and logistic regression) were applied. A p value less than 0.05 was used to declare statistical significance.ResultsThe mean age was 49±14 that ranges from 20-89 years by which majority of them 34 (30.6%) belongs to interval age of 35-44 years. The mean of PSQI score was 4.9±2.79 that ranges from 1-17 scores. Majority of the cardiac patients [69(62.2%)] were considered as having good sleep status (PSQI score <5) while the remaining 42 (37.8%) were considered as poor sleepers with PSQI score >5. Two variables (age of patients more than 65 years and presence of comorbidity) were identified as associated factors with poor sleep quality having P-value less than 0.05 and specific AOR with 95%CI of 4.087 (2.013-8.612) and 3.042 (1.074-8.619), respectively.ConclusionPoor sleep quality is common in heart failure patients. Age >65 years and comorbidities are predictors of poor sleep quality in these patients.

Kronik Böbrek Hastalığı Olan Hastalarda Kötü Uyku Kalitesiyle İlgili Faktörlerin Böbrek Yetmezliğinin İlerlemesine Etkisi

Aim: In recent years, limited studies have been attempted to characterize the quality of sleep in patients with predialysis CKD, and the evidence has shown that insufficient sleep time or poor-quality sleep lead to the progression of CKD. In this study, we aimed to determine the factors related to poor sleep quality in chronic kidney patients and evaluate the effects of these factors on renal progression. Materials and Methods: Patients with pre-dialysis CKD (E3-E5) over 18 years of age who did not have cardiovascular disease, obstructive sleep apnea, and active infection, started to be followed between June 2015 and November 2015, were included in the study. The sleep quality of these patients was measured using the Pittsburgh sleep quality index (PSQI). At the end of the 4-year follow-up, the primary outcomes of the patients were accepted as ESRD, ESRD + mortality, and progression (25 ml/min reduction in GFR). Results: Of the 179 patients followed in the study, 107 (59.8%) had good sleep quality, 72 (40.2%) had poor sleep quality. In the Binary Logistic Regression analysis performed to detect independent markers of poor sleep quality; old age and female gender were found to be independent predictors of poor sleep quality. It was found that poor sleep quality did not affect renal progression conditions such as ESRD, ESRD + Mortality, and GFR≥ 25 ml/min decrease. Conclusion: As a result, we determined that age and female gender are independent determinants of poor sleep quality and poor sleep quality increases mortality.

The Mental Health of Female Physicians and Nurses in Oman during the COVID-19 Pandemic.

ObjectivesWe sought to assess the impact of the COVID-19 pandemic on female doctors and nurses’ mental health in Oman.MethodsWe conducted a cross-sectional, web-based survey of 402 female doctors and nurses recruited from several health facilities in Oman. We used the Generalized Anxiety Disorder (GAD-7) scale, the Perceived Stress Scale (PSS-10), the WHO-5 Well-Being Index (WHO-5), and the Sleep Quality Scale to determine the prevalence rates of anxiety, stress, well-being, and sleep quality.ResultsA total of 231 (57.5%) Omanis and 171 (42.5%) non-Omanis participated in this study. Of the total 402 participants, 28.4% were physicians and 71.6% were nurses. One in four (27.9%) participants reported caring for COVID-19 patients. One in four (27.9%) had moderate to severe anxiety. A higher proportion of Omanis (32.0%) had moderate to severe anxiety than non-Omanis (22.2%). Six in 10 (60.7%) scored at or above the mean on the PSS-10. Doctors and nurses who cared for COVID-19 patients reported higher levels of stress than those who did not. Almost half (45.3%) of the participants scored 50% or less on the well-being scale. A higher proportion of Omanis and those who cared for COVID-19 cases scored ≤ 50. Four in 10 (39.3%) had poor sleep quality; this was particularly prevalent among Omanis. A multiple regression analysis revealed that anxiety, stress, and well-being were significant predictors of poor sleep quality.ConclusionsThe COVID-19 pandemic is having a significant effect on the mental health of health care workers in Oman. In this study, nurses, Omanis, and frontline health care workers were the most impacted by the global health crisis. Urgent psychological, social, and administrative interventions and support should be implemented to mitigate mental health risks in these groups.

The association between micronutrient status and sleep quality in patients with depression: a case-control study.

Few previous studies estimated the association between micronutrient status and sleep quality; no previous work was done in patients with depression compared with healthy controls. Using a case-control design, 96 patients with depression were age- and sex-matched with 96 healthy controls. Dietary assessment utilized a standardized questionnaire, and analysis focused comprehensively on 18 micronutrient items. Sleep quality was measured using the Pittsburg Sleep Quality Index (PSQI). Descriptive statistics were used to summarize findings. Logistic regression analysis was used to identify predictors of poor sleep quality. Patients with depression had a significantly lower sleep quality than controls with PSQI scores of 7.3 ± 2.7 and 5.1 ± 2.5, respectively. The prevalence of poor sleep quality in patients with depression was almost double the prevalence of poor sleep quality in the general population. The micronutrient status of vitamin B12 and Mg successfully predicted sleep quality in healthy controls. However, in patients with depression, micronutrient status failed to predict sleep quality. The current research showed that sleep quality was positively associated with Mg intake, and negatively associated with vitamin B12 in healthy adults. For patients with depressionin this study sample, sleep quality was not associated with micronutrient intake status. Further research is needed to determine if intake of micronutrients can improve sleep and/or depressive symptoms in patients with depression.

Factors Affecting Sleep Quality Among the University Students in Bangladesh: A Cross-Sectional Structured Interview Study

The main objective of the present study was to investigate the association of risk factors on sleep quality of Bangladeshi university students. A total of 332 students participated in a cross-sectional structured interview study. Utilizing the Pittsburgh Sleep Quality Index, the overall prevalence of poor sleep quality among the students was 66.6%, and the prevalence was higher among the female students (81.4%). Females had a 4.1 times higher risk of having poor sleep quality (AOR = 4.12, 95% CI 2.15–7.86, p < .001). Students who usually slept less than 7 h at night had 8.4 times higher risk of being a poor sleeper (AOR = 8.41, 95% CI 4.42–16.01, p < .001) compared to those who slept 7 h or more at night. Duration of bedtime social media use was highly associated with poor sleep quality. Those who used social media 1 h or more before bedtime were 4.3 times more likely to have poor sleep quality compared to those who did not use social media at all before bedtime (AOR = 4.33, 95% CI 1.38–13.51, p = .012). Prevalence of poor sleep quality was found very high among the Bangladeshi university students. Being female, having less sleep a night, and spending more than an hour using social media before sleep were independent predictors of poor sleep quality.

The relationship between depressive symptoms, somatic complaints, and concussion history with poor sleep in collegiate athletes

ObjectiveOngoing exploration of factors related to poor sleep in collegiate athletes is important as understanding of the risks and consequences of poor sleep in this specific population increases. DesignRetrospective cohort study. SettingUniversity in the Pacific Northwest. ParticipantsOne-hundred thirty-seven male and female collegiate athletes across 5 collision, contact, and limited contact team sports. MeasurementsDepressive symptoms (Patient Health Questionnaire 9; PHQ-9), anxiety symptoms (General Anxiety Disorder 7; GAD-7), and somatic complaints (Patient Health Questionnaire 15; PHQ-15). Sleep quality (Pittsburgh Sleep Quality Index; PSQI) used both a cutoff score ≥6 and a cutoff score of ≥8, indicating "poor sleep quality" to reduce threats to divergent validity. ResultsPoor sleep quality as defined by PSQI ≥ 6 was present in 53% of athletes, and as defined by PSQI ≥ 8 was identified in 33.5% of the cohort. There were no differences in the incidence of poor sleepers between sport, race/ethnicity, or sex. Multiple regression analysis revealed that depressive symptoms, somatic complaints, Caucasian race, male sex, and number of concussions were significant predictors of poor sleep (P < .05). The model accounted for 43% of the variance in PSQI and primarily by depressive symptoms explaining 9% of reported sleep quality variability. Anxiety symptoms, sport category, and history of migraines were not significant predictors of poor sleep quality. ConclusionsA high incidence of poor sleep among collegiate athletes was observed regardless of sport, and may be related to depressive symptoms, somatic complaints, Caucasian race, male sex, and historical number of concussions.

Predictors of sleep quality among university students: the use of advanced machine learning techniques.

To assess the prevalence of sleep disturbances among university students and investigate potential correlated factors and their relative importance in quantifying sleep quality using advanced machine learning techniques. A total of 1600 university students participated in this cross-sectional study. Sociodemographic information was collected, and the Pittsburgh Sleep Quality Index (PSQI) was administered to assess sleep quality among university students. Study variables were evaluated using logistic regression and advanced machine learning techniques. Study variables that were significant in the logistic regression and had high mean decrease in model accuracy in the machine learning technique were considered important predictors of sleep quality. The mean (SD) age of the sample was 26.65 (6.38) and 57% of them were females. The prevalence of poor sleep quality in our sample was 70%. The most accurate and balanced predictive model was the random forest model with a 74% accuracy and a 95% specificity. Age and number of cups of tea per day were identified as protective factors for a better sleep quality, while electronics usage hours, headache, other systematic diseases, and neck pain were found risk factors for poor sleep quality. Six predictors of poor sleep quality were identified in university students in which 2 of them were protective and 3 were risk factors. The results of this study can be used to promote health and well-being in university students, improve their academic performance, and assist in developing appropriate interventions.

The examination of sleep quality for frontline healthcare workers during the outbreak of COVID-19.

PurposeFew studies have addressed the sleep disturbances of healthcare workers during crisis events of public health. This study aimed to examine the sleep quality of frontline healthcare workers (FLHCW) in Bahrain during the COVID-19 pandemic, and compare it with the sleep quality of non-frontline healthcare workers (NFLHCW).MethodsHealthcare workers (n = 280) from multiple facilities belonging to the Ministry of Health, Bahrain, were invited to participate in this cross-sectional study. An online questionnaire, including socio-demographics, the Pittsburgh Sleep Quality Index (PSQI), and the Perceived Stress Scale (PSS), was used to evaluate sleep disturbances and stress levels of healthcare workers. Poor sleep quality was defined as PSQI ≥ 5 and moderate-severe stress as PSS ≥ 14. Descriptive statistics were used to compare the scores of FLHCW and NFLHCW. Univariate and multivariate binary logistic regressions were used to identify predictors of poor sleep quality, moderate-severe stress, and the combined problem of poor sleep quality and moderate-severe stress.ResultsA total of 257 participants (129 FLHCW and 128 NFLHCW) provided usable responses. The overall PSQI and PSS scores were 7.0 ± 3.3 and 20.2 ± 7.1, respectively. The FLHCW scored higher in the PSQI and PSS compared with the NFLHCW; however, the differences in the PSQI and PSS scores were not statistically significant. For the FLHCW, 75% were poor sleepers, 85% had moderate-severe stress, and 61% had both poor sleep quality and moderate-severe stress. For the NFLHCW, 76% were poor sleepers, 84% had moderate-severe stress, and 62% had both poor sleep quality and moderate-severe stress. Female sex and professional background were the predictors of poor sleep quality and stress.ConclusionsPoor sleep quality and stress are common during the COVID-19 crisis. Approximately, 60% of both FLHCW and NFLHCW have poor sleep quality combined with moderate-severe stress.