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.     

Validity of the Pupillographic Sleepiness Test for the diagnosis of daytime sleepiness in children and adolescents and its relationship to sleepiness-associated outcomes

ObjectivesTo report validation data for the Pupillographic Sleepiness Test (PST) in children and adolescents, evaluate its applicability for diagnosing excessive daytime sleepiness and its relationship to sleepiness-associated outcomes.MethodsA cross-sectional diagnostic test accuracy study was performed. Patients underwent three PST at 9 a.m. (T1), 11 a.m. (T2) and 1 p.m. (T3) plus the Multiple Sleep Latency Test (MSLT) on a single day. Additionally, two neurocognitive tests were performed and three questionnaires about quality of life, sleep-related self-efficacy and behavioural aspects completed. Gender-stratified z-values of the natural logarithm of the Pupillary Unrest Index (z-lnPUI) were correlated to Sleep Latency (SL) and Mean Sleep Latency (MSL) and to variables of neurocognitive tests and questionnaires using Spearman's rank correlation. Cut-off values were determined by receiver operating characteristic (ROC) analysis.Results47 patients were recruited (median 10.6 years, range 6–18). Correlation between z-lnPUI and SL was r_T1 = −0.373 (p = 0.011); r_T2 = −0.320 (p = 0.028) and r_T3 = −0.336 (p = 0.022). Correlation between z-lnPUI and MSL was r_T1 = −0.338 (p = 0.020); r_T2 = −0.202 (p = 0.173); r_T3 = −0.117 (p = 0.433). ROC analysis showed an area under the curve of 90.7% and PUI cut-off values of 12.6 mm/min (boys) and 11.6 mm/min (girls). There were moderate correlations between z-lnPUI_T1 and reaction time and omission errors in neurocognitive tests (r = 0.394, p = 0.007 and 0.391, p = 0.008).ConclusionsWe found satisfactory correlations between PST and MSLT results. The z-lnPUI_T1 was related to MSL and objective measures of attention ability. Given this accuracy, the PST may be used as a screening tool for evaluating daytime sleepiness in children and adolescents. Corresponding gender-related reference values are now available.     

Daytime course of sleepiness in de novo Parkinson's disease patients

Normal subjects show an increase of sleepiness in the morning, early afternoon and before sleep. In the advanced stages of Parkinson's disease (PD) the mean level of sleepiness is quite high, while with respect to healthy subjects it seems to be unchanged in the early stages. The aim of this study was to evaluate the time–course of the sleepiness level during the wakefulness period in untreated patients with early‐stage Parkinson's disease. Eighteen Parkinson's disease patients who had never been treated before with dopaminergic drugs (male = 9, female = 9, age: 68.39 ± 1.89, mean ± standard error) and 18 healthy subjects (male = 9, female = 9, age: 67.22 ± 1.98) were recruited for this study. All subjects underwent continuous actigraphic recording for three consecutive days, during which they also completed the Karolinska Sleepiness Scale (KSS) once an hour throughout wakefulness. Our results showed a higher level of sleepiness in the patients than the controls in the hours following awakening and in the early afternoon, specifically at 08:00 and 14:00 hours (08:00 hours, PD patients, KSS: 3 ± 0.3 versus healthy subjects, KSS: 2 ± 0.2, P < 0.05; 14:00 hours, PD patients, KSS: 4.4 ± 0.5 versus healthy subjects, KSS: 3 ± 0.3, P < 0.05). We suggest that some daytime hours are sensitive windows showing the first increase of sleepiness which will spread later to the whole daytime.     

Cystic fibrosis patients have poor sleep quality despite normal sleep latency and efficiency

STUDY OBJECTIVES: Cystic fibrosis (CF) patients may be predisposed to poor sleep quality due to upper and lower airway abnormalities and impaired gas exchange. Previous sleep investigations of CF patients using single-night polysomnography have reported conflicting results. We hypothesized that sampling sleep for a prolonged period in a patient's normal environment may give a more representative assessment of sleep quality than a single-night polysomnogram, and that impaired sleep quality would correlate with pulmonary disease severity and self-assessed sleep quality. DESIGN: Using wrist actigraphy, we measured sleep quality in clinically stable CF patients and age-matched control subjects. In addition, each CF patient and control subject completed the following three questionnaires: the Epworth sleepiness scale; the Pittsburgh sleep quality index (PSQI); and the Medical Outcomes Study 36-item short form. RESULTS: Twenty CF patients and control subjects were enrolled in the study, and were well-matched for age, sex, and body mass index. The mean (+/- SD) FEV(1) for CF patients was 61.0 +/- 20.1% predicted. CF patients and control subjects had similar sleep duration, sleep latency, and sleep efficiency. However, CF patients had higher PSQI scores (6.45 vs 4.55, respectively; p = .04), a higher fragmentation index (FI) [31.72 vs 18.02, respectively; p < 0.001], and less immobile time (88.87 vs 91.89, respectively; p = 0.02). There was a significant correlation of FI with FEV(1) and PSQI scores. CONCLUSIONS: Stable CF patients have disrupted sleep, and sleep disruption may in part be related to the severity of pulmonary disease. In addition, the PSQI may be useful in detecting CF patients with poor sleep quality.     

Intermittent fasting during Ramadan: does it affect sleep?

Islamic intermittent fasting is distinct from regular voluntary or experimental fasting. We hypothesised that if a regimen of a fixed sleep–wake schedule and a fixed caloric intake is followed during intermittent fasting, the effects of fasting on sleep architecture and daytime sleepiness will be minimal. Therefore, we designed this study to objectively assess the effects of Islamic intermittent fasting on sleep architecture and daytime sleepiness. Eight healthy volunteers reported to the Sleep Disorders Centre on five occasions for polysomnography and multiple sleep latency tests: (1) during adaptation; (2) 3 weeks before Ramadan, after having performed Islamic fasting for 1 week (baseline fasting); (3) 1 week before Ramadan (non‐fasting baseline); (4) 2 weeks into Ramadan (Ramadan); and (5) 2 weeks after Ramadan (non‐fasting; Recovery). Daytime sleepiness was assessed using the Epworth Sleepiness Scale and the multiple sleep latency test. The participants had a mean age of 26.6 ± 4.9 years, a body mass index of 23.7 ± 3.5 kg m^?2 and an Epworth Sleepiness Scale score of 7.3 ± 2.7. There was no change in weight or the Epworth Sleepiness Scale in the four study periods. The rapid eye movement sleep percentage was significantly lower during fasting. There was no difference in sleep latency, non‐rapid eye movement sleep percentage, arousal index and sleep efficiency. The multiple sleep latency test analysis revealed no difference in the sleep latency between the ‘non‐fasting baseline’, ‘baseline fasting’, ‘Ramadan’ and ‘Recovery’ time points. Under conditions of a fixed sleep–wake schedule and a fixed caloric intake, Islamic intermittent fasting results in decreased rapid eye movement sleep with no impact on other sleep stages, the arousal index or daytime sleepiness.     

Dissociations among daytime sleepiness,nighttime sleep,and cognitive status in Parkinson's disease

BackgroundDaytime and nighttime sleep disturbances and cognitive impairment occur frequently in Parkinson's disease (PD), but little is known about the interdependence of these non-motor complications. Thus, we examined the relationships among excessive daytime sleepiness, nighttime sleep quality and cognitive impairment in PD, including severity and specific cognitive deficits.MethodsNinety-three PD patients underwent clinical and neuropsychological evaluations including the Epworth Sleepiness Scale (ESS) and Pittsburgh Sleep Quality Index (PSQI). Patients were classified as having normal cognition (PD-NC), mild cognitive impairment (PD-MCI), or dementia (PDD) using recently proposed Movement Disorder Society PD-MCI and PDD criteria. Relationships between the sleep and cognitive measures and PD cognitive groups were examined.ResultsThe PD cohort included PD-NC (n = 28), PD-MCI (n = 40), and PDD (n = 25) patients. ESS scores, as a measure of daytime sleepiness, were significantly worse (p = 0.005) in cognitively impaired PD patients, particularly PDD patients. ESS scores correlated significantly with Mini-Mental State Examination scores and also with cognitive domain scores for attention/working memory, executive function, memory, and visuospatial function. In contrast, PSQI scores, as a measure of nighttime sleep quality, neither differed among cognitive groups nor correlated with any cognitive measures.ConclusionsDaytime sleepiness in PD, but not nighttime sleep problems, is associated with cognitive impairment in PD, especially in the setting of dementia, and attention/working memory, executive function, memory, and visuospatial deficits. The presence of nighttime sleep problems is pervasive across the PD cognitive spectrum, from normal cognition to dementia, and is not independently associated with cognitive impairment or deficits in cognitive domains.     

Correlations between night eating,sleep quality,and excessive daytime sleepiness in a severely obese UK population

Objective

The relationships between night eating, poor sleep quality, and obesity-related comorbidity in a severely obese UK clinic population is unknown. We used validated tools to identify prevalence and to explore this relationship.

Methods

Consecutive consenting clinic attendees completed the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Score (ESS), and Night Eating Questionnaire (NEQ) to identify sleep quality, excessive daytime sleepiness (EDS) (a surrogate marker for suspected obstructive sleep apnea [OSA]), and night eating, respectively. Proportions of individuals above and below tool cutoff points were compared. Pearson product moment correlation coefficients examined relationships between total scores.

Results

Reported prevalence from 144 participants (mean body mass index [BMI] 46.9 [9.5] kg/m²; age 44.6 [12.1] years; 68% women) had poor sleep quality (73.0%), suspected OSA (30.8%), and night-eating behavior (2.8%). The strongest correlation between PSQI and NEQ scores (r = 0.54; P < .001) was undiminished after controlling for EDS. Although significantly correlated, PSQI and ESS scores (r = 0.31; P < .001) reduced after controlling for night eating (r = 0.21; P = .02). Correlation between NEQ and ESS scores (r = 0.26; P = .002) was smaller and nonsignificant after controlling for sleep quality (r = 0.12; P = .18).

Conclusions

Poor sleep quality is common in severe obesity, though night eating is rare. The association between poor sleep quality and night eating is not influenced by the presence of EDS.