Time Sleepiness Research Articles

Excessive Daytime Sleepiness among Chronic Kidney Disease Patients

Background:Excessive daytime sleepiness is defined as the incapacity to keep alert or awake during the major waking activities of the day, causing unintentional pauses of drowsiness or sleep. Chronic kidney diseasepatients commonly suffer from excessive daytime sleepiness which in turn affectstheir quality of life. Objectives: This prospective cross-sectional study was conductedto evaluate the prevalence of excessive daytime sleepiness among chronic kidney disease patients. Patients and methods: The study was carried out on one hundred patients with known chronic kidney disease who attended Aswan University hospital during the period between May 2017 and March 2020; 42.0% males and 58.0% females with a mean age of 53.9 ± 16.97 years. We evaluated day time sleepiness among those patients using Epworth Sleepiness Scale (ESS); the standardized score for the assessment of daytime sleepiness. Results: We found that 56% of the patients had excessive daytime sleepiness (ESS > 10) with themedian ESS of the participants was 10.0.There was no statistically significant correlation between the ESS and each of serum urea, serum creatinine, and eGFR. Conclusion:Excessive daytime sleepiness is common among CKD patients with a prevalence of 56% that may affect their quality of life.

Elusive hypersomnolence in seasonal affective disorder: actigraphic and self-reported sleep in and out of depressive episodes.

Hypersomnolence has been considered a prominent feature of seasonal affective disorder (SAD) despite mixed research findings. In the largest multi-season study conducted to date, we aimed to clarify the nature and extent of hypersomnolence in SAD using multiple measurements during winter depressive episodes and summer remission. Sleep measurements assessed in individuals with SAD and nonseasonal, never-depressed controls included actigraphy, daily sleep diaries, retrospective self-report questionnaires, and self-reported hypersomnia assessed via clinical interviews. To characterize hypersomnolence in SAD we (1) compared sleep between diagnostic groups and seasons, (2) examined correlates of self-reported hypersomnia in SAD, and (3) assessed agreement between commonly used measurement modalities. In winter compared to summer, individuals with SAD (n = 64) reported sleeping 72 min longer based on clinical interviews (p < 0.001) and 23 min longer based on actigraphy (p = 0.011). Controls (n = 80) did not differ across seasons. There were no seasonal or group differences on total sleep time when assessed by sleep diaries or retrospective self-reports (p's > 0.05). Endorsement of winter hypersomnia in SAD participants was predicted by greater fatigue, total sleep time, time in bed, naps, and later sleep midpoints (p's < 0.05). Despite a winter increase in total sleep time and year-round elevated daytime sleepiness, the average total sleep time (7 h) suggest hypersomnolence is a poor characterization of SAD. Importantly, self-reported hypersomnia captures multiple sleep disruptions, not solely lengthened sleep duration. We recommend using a multimodal assessment of hypersomnolence in mood disorders prior to sleep intervention.

Effect of sleep quality on educational performance of paramedic students of Prince Sultan Military College of Health Sciences (PSMCHS) in the Eastern Province of Kingdom of Saudi Arabia (KSA)

Increasing students’ academic stress especially during exams may result in sleep disorders, fatigue, poor academic performance and low functional efficiency. The aim of this research is to investigate the effect of sleep quality on educational performance of paramedic students. This research depends on a cross-sectional observational study. The samples of the study were 150 individual who will be chosen randomly from Saudi PSMCHS-Dhahran paramedic students. Data related to demographic aspects, work-related information was gathered from the samples of the study. Finally, the data of the study was analyzed through SPSS program. Four sleep scales were adopted for the study like Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Fatigue Severity Scale (FSS) and Kessler Psychological Distress Scale (KPDS). The level of education like diploma and bachelor had a significant relation between the ESS and FSS. Bridging level of education has relation with KPDS. Marital status and BMI were significant with ISI and KPDS respectively. Physiological distress and excessive day time sleepiness were significant with ISI, FSS and KPDS.It can be stated that sleep quality of paramedic students is affected with high ratio by the educational performance. This is because the high stress of work regarding paramedic students leads them to have less amount of sleep quality and then this affects their educational performance.

The Different Facets of Heart Rate Variability in Obstructive Sleep Apnea.

Obstructive sleep apnea (OSA), a heterogeneous and multifactorial sleep related breathing disorder with high prevalence, is a recognized risk factor for cardiovascular morbidity and mortality. Autonomic dysfunction leads to adverse cardiovascular outcomes in diverse pathways. Heart rate is a complex physiological process involving neurovisceral networks and relative regulatory mechanisms such as thermoregulation, renin-angiotensin-aldosterone mechanisms, and metabolic mechanisms. Heart rate variability (HRV) is considered as a reliable and non-invasive measure of autonomic modulation response and adaptation to endogenous and exogenous stimuli. HRV measures may add a new dimension to help understand the interplay between cardiac and nervous system involvement in OSA. The aim of this review is to introduce the various applications of HRV in different aspects of OSA to examine the impaired neuro-cardiac modulation. More specifically, the topics covered include: HRV time windows, sleep staging, arousal, sleepiness, hypoxia, mental illness, and mortality and morbidity. All of these aspects show pathways in the clinical implementation of HRV to screen, diagnose, classify, and predict patients as a reasonable and more convenient alternative to current measures.

Sleep Quality and Day Time Sleepiness in Patients with Type-2 Diabetes

The present study was undertaken to observe the sleep quality and day time sleepiness in patients with type-2 diabetes. The study included thirty type 2 diabetic patients and thirty age and gender matched healthyparticipants. Pittsburgh Sleep Quality index (PSQI) was used to assess the sleep quality of the participants.Epworth sleepiness scale was used to assess the day time sleepiness. There was significantly lower sleepquality in the diabetic patients when compared with the healthy individuals (P&lt;0.001). There was significantlyhigher day time sleepiness in the diabetic patients when compared with the healthy individuals (P&lt;0.001).The study results suggest that there was a significant deterioration of sleep quality in diabetic individualswhich is reflected in day time sleepiness scores as diabetic individuals have higher day time sleepiness.We recommend further detailed studies to understand the association and also to develop better treatmentstrategies for the benefit of population in general.

Day Time Sleepiness and Quality of Life Predicts Perceived Stress among Youth

The aim of the current study was to examine the predictive strength of Perceived Stress among Youth. The variables used in the current study were Day Time Sleepiness, Quality of Life and Perceived Stress. The sample consists of 150 Youth (81Male &amp; 69 Female) with in age range of 18-24 years. The Epworth Sleepiness Scale (ESS) (Johns, 1991), World Health Organization Quality of Life (WHO-BRIEF), and Perceived Stress Scale (PSS) (Cohen, Kamarck, &amp; Mermelstein, 1983) were used. The data were analysed by using descriptive statistics i.e. Mean and SD, Pearson’s Product Moment correlation and step wise multiple regression analysis. The results indicated that Day Time Sleepiness (r = .56, p&lt;.001) and Quality of Life (r = .52, p&lt;.001) have significant positive relation with Perceived Stress among Youth. The step wise regression analysis found Day Time Sleepiness (R2 = .31, p&lt;.001) and Psychological Health related Quality of Life (R2 = .39, p&lt;.001) are the predictors of Perceived Stress. Both the variable accounts 39% of total variance in Perceived Stress among Youth.

845 Progressive external ophthalmoplegia in sleep apnea presenting as floppy eyelid syndrome

Abstract Introduction Floppy eye lid syndrome (FES) is known to be associated with Obstructive sleep apnea (OSA) and chronic progressive external ophthalmoplegia (CPEO) is a rare genetic disorder with mitochondrial myopathy that may present with isolated eye lid ptosis in the initial stages. In a patient with loud snoring and obesity, treating obstructive sleep apnea may improve Floppy eyelid syndrome. Report of case(s) 52-year-old African – American male with past medical history of Hypertension, obesity, glaucoma, CPEO status bilateral blepharoplasty with failed surgical treatment. Patient was referred to Sleep medicine team to rule out Obstructive Sleep Apnea aa a cause of possible underlying FES and residual ptosis. On exam, patient was noted to have bilateral brow and eyelid ptosis and mild ataxic gait. MRI brain with and without contrast was unremarkable. Deltoid muscle biopsy was suggestive of possible congenital myopathy and mild denervation atrophy. Polysomnogram showed severe OSA with AHI of 74.1 per hour and patient was initiated on Auto CPAP at a pressure setting of 7–20 cm H2O. CPAP treatment improved snoring, OSA and subjective symptoms of excessive day time sleepiness but did not improve the residual ptosis. Conclusion Treatment of severe OSA in a patient previously diagnosed with CPEO and failed surgical treatment with bilateral blepharoplasty, did not alter the course of residual ptosis/ floppy eyelids even though his other sleep apnea symptoms have improved. Support (if any) 1. McNab AA. Floppy eyelid syndrome and obstructive sleep apnea. Ophthalmic Plast Reconstr Surg. 1997 Jun;13(2):98–114. doi: 10.1097/00002341-199706000-00005. PMID: 9185193.

749 Is daytime sleepiness a risk factor for depression and the prevalence of depression in patients with EDS referred for PSG

Abstract Introduction Excessive daytime sleepiness affects 18.9–27% of the general population. [1] Patients with excessive daytime sleepiness have a higher prevalence of major depressive episodes. [2] Depression is also associated with poor medical compliance which may further affect management of excessive day time sleepiness. [3] We therefore are interested in the prevalence of depression in patients undergoing in-lab testing for excessive sleepiness and the association of positive depression screening. Methods Retrospective review of diagnostic polysomnograms (PSG) in a tertiary care facility was conducted on patients over 18 years of age. The elements collected include: gender, age, BMI, Depression scale defined by PHQ-9, EDS defined by Epworth’s Sleepiness scale, AHI = Apnea Hypopnea Index, PLMS = Periodic Limb Movements in Sleep. Results There were a total of 32 subjects. Median age was 49 with 43% male and average BMI of 35. The mean PHQ-9 score was 5.8. The mean Epworth score was 8.5. The correlation of the two values was r= 0.078. 12 patients are classified as having EDS. 7 patients (58.3%) in the EDS group were positive for depression screen. 18 patients (90%) without EDS were positive for depression screen. There is no statistical difference 2 groups (58.3% vs 90%, p=1). The mean PHQ-9 score in EDS group is 5.5. The mean PHQ-9 score in non EDS group is 5.95. There is no statistical difference between 2 groups PHQ-9(5.5 vs 5.95, p=0.779). Conclusion Our study cohort did not find a correlation between subjective sleepiness and depression in individuals presenting for in lab polysomnography. This may be related to the sample size or be an indication that many other factors contribute to the sleepiness in this cohort. Support (if any) 1. Hein M. et al (2019) Prevalence and risk factors of excessive daytime sleepiness in major depression: A study with 703 individuals referred for polysomnography. J Affect Disord. 2. Chellappa SL. et al (2006) Excessive daytime sleepiness in patients with depressive disorder. Braz J Psychiatry. 3. Grenard JL et al (2011) Depression and medication adherence in the treatment of chronic diseases in the United States: a meta-analysis. J Gen Intern Med

English

BACKGROUND Obstructive sleep apnoea (OSA) is a chronic disorder in which repetitive episodes of cessation of breathing occurs during sleep due to collapse of upper airway leading to recurrent awakening, sleep fragmentation, and perturbation in ventilatory function. The disorder is much more common than realised and the manifestations in children are different from those in adults. OSAS may present in different ways like cognitive dysfunction, excessive day time somnolence, decreased attention span, drooling of saliva, mood disorders like depression or irritability as well as adverse cardiovascular sequelae like hypertension, heart failure. Polysomnography or overnight sleep studies remain the gold standard for the diagnosis of paediatric obstructive sleep apnoea (POSA) disorder. Therapeutic approaches for POSA include surgical and nonsurgical means. The choice of therapy depends on various factors like aetiology, severity of the POSA and patient’s choice. Although continuous positive airway pressure (CPAP) remains the first line therapy in adults, the introduction of oral appliances provided an attractive alternative and made the role of dentists more prominent in management of this disorder. OSA is often under-diagnosed due to lack of awareness. So, it is essential for dentists to be aware of the various aspects of this disorder as well as its management. KEY WORDS OSA, Paediatric Dentist, Oral Appliances, Non-Invasive Management

Sleep disorders and risk of traffic crashes: A naturalistic driving study analysis

Sleep disorders and various acute and chronic medical conditions affect the quality and quantity of an individual’s sleep causing excessive day time sleepiness. This study examined the relationship between clinical sleep disorders (i.e., shift work sleep disorder (SWSD), sleep apnea and insomnia) and crashes using naturalistic driving study data. Using data from 1892 events that occurred in six different US states, random effect binary logistic regression models were developed to estimate crash risk associated with SWSD, sleep apnea and insomnia. The study found that sleep disorders elevate crash risk in drivers. Drivers with SWSD exhibited the highest crash risk (OR = 2.96). Older drivers with SWSD were found to be more vulnerable and prone to crashes than other drivers. The analysis showed that drivers with sleep apnea and insomnia were 29% and 33% more likely, respectively, to be involved in a crash or a near-crash. For drivers with insomnia, factors such as age and sleep quality can elevate the associated crash risk. Decrease in sleep quality increases the likelihood of crash or near crash. The study also found that individuals with a sleep disorder are 29% more likely to be inattentive while driving as compared to drivers without a sleep disorder. The OR values found in this study were lower than those reported in studies using self-reported data and driver simulator experiments. In addition to medical diagnosis and treatment, transportation agencies could also consider alleviation strategies such as providing sufficient rest areas on highways and using technology such as in-vehicle and personal technologies that monitor drowsy in-vehicle behavior to increase driver attention. The use of transportation modes such as taxi, transportation network companies (e.g. Uber), or public transit, can be an alternative for shift workers returning home after completing their shift.

Assessment of sleep quality and its predictors among newly diagnosed psychiatric patients.

Poor sleep is a vital symptom observed in many psychiatric conditions and is the most neglected and underdiagnosed. The current study aims at assessment of sleep quality among psychiatric patients using the Pittsburgh Sleep Quality Index (PSQI) scale and to identify the predictors of sleep quality. A hospital-based cross-sectional observational study conducted in the Psychiatry department with a sample size of 256 patients for six months. PSQI scale was used to assess sleep quality and multiple logistic regression was used (to identify) the predictors for poor sleep quality. The mean age of the study population was 37.95±14.11 years, with 148 (58%) male study participants. 192 (75%) of the study population had poor sleep quality with respect to PSQI scale with a mean score of 9.05±4.65 that was well above the expected range (0-5) suggestive of compromised quality of sleep (p=0.001). Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness and at least one completely sleepless night in the past one week of admission were identified as good predictors for poor sleep quality. Our study addresses the importance of assessing sleep quality regardless of the psychiatric conditions. We recommend screening patients if they have Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness or at least one completely sleepless night in the past one week of admission predictors for comorbid sleep disorders.

Sleep disorders among health care workers practicing in emergency department in south tunisia

IntroductionSleep disorders are the most common health problem among the health care staff, mainly those who perform night shifts.ObjectivesTo assess the prevalence of sleep disorders among health care workers in emergency department and to determine its associated factors.MethodsIt was a cross-sectional study, including health care workers assigned to emergency ward and intensive care unit of Hedi Chaker and Habib Bourguiba hospitals in Sfax and regional hospital of Kebili, during the first six months of 2017. We used an anonymous and confidential self-administered questionnaire. We used hospital anxiety and depression scale (HAD) to assess anxiety and depression. Sleep quality was assessed by the Pittsburgh Sleep Quality Index and day time sleepiness by the Epworth Sleepiness Scale.Results240 nurses were included. Mean age was 37 years-old, 59.2% were female and 64.2% were married and 79.2% assured night shifts. The prevalence of sleep disorders was 70.4%. Sleep difficulties were significantly correlated with anxiety (p=0.001) and depression (p=0.02). In multivariate study, sleep disorders were related to the absence of leisure activity (OR=0.42 [0.19-0.94]; p=0.035) and anxiety (OR=3 [1.4-6.1]; p=0.002). 40.8% of nurses experienced drowsiness. Sleepiness was significantly correlated with the absence of leisure activities (p=0.04) and with psychiatric family history (p=0.02). In the multivariate study, sleep disorders were correlated with female gender (OR=0.43 [0.19-0.9]; p=0.042) and with no leisure activity (OR=2.6 [1.2-5.6]; p=0.01).ConclusionsSleep disorders were common among emergency nurses, in order of that; working conditions should be improved to provide less stressful conditions for nurses.Conflict of interestNo significant relationships.

Hypothalamic lesions in neuromyelitis optica spectrum disorders: exploring a scoring system based on magnetic resonance imaging.

We propose a scoring system for early diagnosis of sleep abnormalities in neuromyelitis optica spectrum disorders (NMOSD) with hypothalamic lesions based on magnetic resonance imaging (MRI). We evaluated MRI features of 45 patients with hypothalamic lesions identified from two cohorts. Univariate logistic regression analysis identified factors associated with sleepiness, which were subsequently used to develop a scoring system. Interrater reliability was determined using intraclass correlation coefficient (ICC). Correlations between scores and clinical features were analyzed. In total, 48.9% of 45 patients with hypothalamic lesions exhibited sleepiness. The number of involved slices, maximum width/length of hypothalamic lesions, and boundaries extending beyond the hypothalamus were associated with sleepiness (all p < 0.05). The sensitivity and specificity of the scoring system were 68.2% and 87.0%, respectively. The ICC values for the maximum width and length measurement of hypothalamic lesions were 0.82 and 0.81, respectively. Daily sleep time and Epworth sleepiness scale scores were positively correlated with MRI-based scores (p < 0.05, 95% confidence interval (CI) 0.69-0.93 and p < 0.05, 95% CI 0.55-0.88, respectively). A scoring system based on MRI features was developed to provide diagnosis of sleepiness in NMOSD with hypothalamic lesions earlier than other measures.

Myopia, Melatonin and Conjunctival Ultraviolet Autofluorescence: A Comparative Cross-sectional Study in Indian Myopes

ABSTRACT Purpose: To explore the role of outdoor light exposure by estimating ocular sun exposure measured by Conjunctival Ultraviolet Autofluorescence (CUVAF) imaging and serum melatonin levels in myopes and non-myopes. Materials & Methods: Age and sex matched emmetropes and myopes (60 each) aged 10–25 years participated. Those with a history of ocular surgery or any ocular or systemic co-morbidity were excluded. Socio-demographic parameters, sun exposure questionnaires, indoor and outdoor activity profile, morning serum melatonin levels, sleep pattern, degree of myopia, ocular biometry and area of CUVAF on ultraviolet photography were noted and analyzed. Results: Mean age of myopes (18 ± 4.5 years) and emmetropes (18.5 ± 4 years) was similar (P = .523). Serum melatonin levels were significantly higher (P = .001) among myopes (89.45 pg/ml) as compared to emmetropes (52.83 pg/ml). Lifetime sun exposure was significantly lower in myopes than emmetropes (P = .0003). Area of CUVAF was inversely related to degree of myopia (P < .0001). Day time sleepiness was greater in myopes (51.7%) than emmetropes (15%) (P < .0001). There was a positive correlation between serum melatonin levels and axial length among myopes (correlation coefficient = 0.27; P = .03). Age and gender had no association with serum melatonin levels. Conclusion: This study demonstrates an inverse relationship between serum melatonin levels and degree of CUVAF in myopes. A novel link between serum melatonin, axial length and outdoor sun exposure is highlighted in the current study.

Modifiable Comorbidities Associated with Cognitive Decline in Parkinson's Disease.

Cognitive impairment (CI) is one of the most feared and debilitating complications of PD. No therapy has been shown to slow or prevent CI in PD. To determine associations between modifiable comorbidities, including cardiovascular disease risk factors, mood disorders, and sleep characteristics, and rate of cognitive decline in Parkinson's disease (PD). Data from the Parkinson's Progression Markers Initiative (PPMI) cohort was queried for baseline cardiovascular disease risk factors, mood disorders, and sleep characteristics. Linear mixed- effects models (LME) were used to examine the association between baseline factors and change in cognition, evaluated by the Montreal Cognitive Assessment (MoCA) over time. Baseline comorbidities found to affect MoCA decline were assessed for an association with focal cognitive domains using LME. Higher Body Mass Index (BMI) (β = -0.009, P = 0.039), State Trait Anxiety Inventory (STAI) (β = -0.005, P < 0.001), Geriatric Depression Scale (GDS) (β = -0.034, P < 0.001), Epworth Sleepiness Scale (ESS) (β = -0.017, P = 0.003), and REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) (β = -0.037, P < 0.001) were associated with faster rates of MoCA decline. Using established cut-offs for clinically significant symptoms, being overweight, or the presence of depression, excessive day time sleepiness (EDS), and possible REM sleep behavior disorder (pRBD), were all associated with faster rate of cognitive decline. Several modifiable baseline comorbidities are associated with faster rate of CI over time in patients with PD. These associations identify potential opportunities for early intervention that could influence CI in PD.

Utility of a Novel Clinical Triad (Chandrans TRIAD) for Early Diagnosis of Autoimmune Encephalitis (AIE) in Patients with Progressive Cognitive Decline

Autoimmune Encephalitis (AIE) often presents with cognitive and behavioural symptoms often mimickingprogressive degenerative dementias. Early identification of these potentially reversible conditions can improve patientoutcomes, reduce caregiver burden and promote cost effectiveness. The clinical trial of symptoms namely panicattacks, catatonia and day time sleepiness is often associated with anti N-methyl D-aspartate (NMDA) receptormediated encephalitis and the former two symptoms along with seizures is suggestive of anti-Voltage Gated PotassiumChannel (VGKC) receptor mediated encephalitis. This triad serves as a pragmatic tool to easily identify AIE and alsohelps to distinguish between the two conditions.

Sleep Disorders Among Undergraduate Health Students in Bristol, United Kingdom

Daytime Sleepiness and poor sleep quality are common among medical students. The objective of study is to determine the prevalence of daytime sleepiness and sleep quality and associated risk factors among medical students in medical college, in Bristol, United Kingdom. It was a cross-sectional study and 153 medical students were selected through stratified random sampling techniques. Pittsburgh Sleep Quality Index was used to assess the sleep pattern and Epworth Sleepiness Scale was used to measure daytime sleepiness. Association of sleep quality and daytime sleepiness and its risk factors were determined through regression analysis. Students suffering from severe disorder of sleep quality was 21.6% and severe daytime sleepiness 3.9%. In multivariate analysis after adjustment of covariates, in daytime sleepiness, male gender (OR.1.33, CI 1.06-3.04) [p-value 0.040] and those students who smoke cigarettes [OR 4.65, (CI 1.48-5.14) [p-value 0.018] were more likely associated with severe daytime sleepiness disorder. In Sleep quality disorder, those students who had low academic score [OR 3.13(CI 1.28-4.87) [p-value 0.035] and those students who smoke cigarettes [OR 3.04 (CI 2.34-4.29) [p-value 0.010] were more than likely associated with severe sleep quality disorder. Majority of students suffered from poor sleep quality and day time sleepiness. Male gender, smoking, academic score and academic years was the major predictor for poor sleep quality and day time sleepiness. There is need for awareness and counselling among student for reduced the sleep disorder burden.

Evaluation of day time sleepiness using Epworth sleepiness score among medical students

Introduction: Physiologic and cognitive function in humans vary considerably with the circadian rhythm, which also regulates the sleep cycle. Sleep is an active, repetitive and reversible behavior serving several different physiological functions. Medical students are a unique group of young adults whose academic commitments and lifestyle can have an impact on their sleep habits. Objectives: To evaluate day time sleepiness using Epworth sleepiness score among medical students. Materials and Methods: The study population consisted of 130 first year MBBS students selected randomly based on their consent. Data was collected with the help of Epworth sleepiness scale. Results and Conclusion: The present study demonstrated the presence of excessive day time sleepiness among 45% of the students. Since a strong relationship is evident between good sleep quality and high academic performance, measures to improve the sleep quality among medical students need to be focused. Keywords: Sleep deprivation, Day time sleepiness, Epworth sleepiness score, Medical students.

Gender-Specific Association of Body Fat Composition with Risk of Obstructive Sleep Apnea among People Living With HIV/AIDS: A Cross-Sectional Study

Background: Obesity and regional fat distribution are among the strongest risk factors for obstructive sleep apnea (OSA) in the general population. People living with HIV (PLHIV) may be at increased risk of OSA because of their distinct body fat composition. This study examined the association of body fat composition with the risk of OSA in PLHIV. Methods: We conducted a cross-sectional prospective study at a tertiary HIV care unit, recruiting 400 PLHIV [female: 317, 79.2%; median age of 44 years; median year of HIV duration of 5 years]. Participants were surveyed using standardized instruments to assess the risk of OSA, sleep duration and, sleepiness. Body fat composition was evaluated with anthropometric measurements and bioelectric impedance Results: Sixty-three of the participants (15.8%; 95% confidence interval [CI], 12.4%–19.8%) had risk of OSA, while 24 (6.0%) of them had risk of OSA and excessive day time sleepiness and 30 (7.5%) had risk of OSA with concomitant short sleep duration. BMI and markers of central obesity were significantly associated with risk of OSA in females but not in males. Waist circumference, Waist to hip ratio, Visceral fat level performed similarly in predicting the risk of OSA in females with Area Under the Curve (AUC) of 0.668, 95% CI (0.613, 0.719); 0.704, 95% CI (0.651, 0.754); 0.663, 95% CI (0.608, 0.715) respectively, with VFL having the best accuracy. Conclusions: The risk of OSA among PLHIV was associated with measures of visceral adiposity in females and not in males.

Association between physical activity, screen time activities, diet patterns and daytime sleepiness in a sample of Brazilian adolescents

ObjectiveTo examine the association between physical activity, screen time, eating habits and daytime sleepiness among Brazilian adolescents. MethodsAdolescents from three high schools (n = 876, 49.8% female, 16.4 ± 1.2 years) participated in this cross-sectional survey. Variables related to lifestyle behaviors (ie, physical activity, screen time, eating habits, sleep duration) were collected through an online questionnaire. Daytime sleepiness was assessed using the Pediatric Daytime Sleepiness Scale (PDSS). Excessive daytime sleepiness was defined as a PDSS score ≥20. ResultsThe average PDSS score was 18.9 (SD ± 4.8) points and 46.8% of adolescents were classified as having excessive daytime sleepiness. Physical activity was inversely associated with PDSS score (β = −0.29, 95% CI -0.47; −0.11). Consuming processed foods frequently (β = 1.16, 95% CI 0.85; 1.47) and using social media (β = 0.22, 95% CI 0.14; 0.30) were positively associated with PDSS score. Similar findings were observed for the odds of excessive daytime sleepiness. Physical activity was inversely associated (OR = 0.91, 95% CI 0.84; 0.99), while frequent consumption of processed foods (OR = 1.55, 95% CI 1.33; 1.82) and using social media (OR = 1.13, 95% CI 1.02; 1.24) were positively associated with excessive daytime sleepiness. ConclusionsLower physical activity level, a higher consumption processed foods, and higher social media use were associated with daytime sleepiness in this sample of Brazilian adolescents.