Explore the vast range of titles available.

Sleep disturbances are associated with poor health outcomes in adults. However, little is known about the sleep disturbances that occur in adult eczema. We studied the association between adult eczema and sleep disturbance and their impact on overall health and health care utilization. We used the 2012 National Health Interview Survey, a cross-sectional questionnaire of 34,613 adults. Eczema was associated with higher odds of fatigue (odds ratio (95% confidence interval): 2.97 (2.65–3.34)), regular daytime sleepiness (2.66 (2.34–3.01)), and regular insomnia (2.36 (2.11–2.64)), even after controlling for sleep duration, history of allergic disease, sociodemographics, and body mass index. There were significant interactions between eczema and fatigue, sleepiness, and insomnia as predictors of poorer overall health status, number of sick days, and doctor visits, such that eczema and each of the sleep symptoms were associated with higher odds of poorer outcomes than either eczema or sleep symptoms alone. Latent class analysis was used and identified five classes of fatigue, sleep disturbances, and allergic disorders. Two classes had high probabilities of eczema: one with high probabilities of asthma, hay fever, food allergy, and multiple sleep symptoms and the other with intermediate probability of insomnia alone. Future studies are warranted to better characterize sleep loss in eczema and develop strategies for treatment and prevention.

Excessive daytime sleepiness (EDS) is classically viewed as a consequence of insufficient sleep or a symptom of sleep disorders. Epidemiological and clinical evidence have shown that patients reporting EDS in tandem with sleep disorders (e.g., obstructive sleep apnoea) are at greater cardiovascular risk than non-sleepy patients. While this may simply be attributable to EDS being present in patients with a more severe condition, treatment of sleep disorders does not consistently alleviate EDS, indicating potential aetiological differences. Moreover, not all patients with sleep disorders report EDS, and daytime sleepiness may be present even in the absence of any identifiable sleep disorder; thus, EDS could represent an independent pathophysiology. The purpose of this review is twofold: first, to highlight evidence that EDS increases cardiovascular risk in the presence of sleep disorders such as obstructive sleep apnoea, narcolepsy and idiopathic hypersomnia and second, to propose the notion that EDS may also increase cardiovascular risk in the absence of known sleep disorders, as supported by some epidemiological and observational data. We further highlight preliminary evidence suggesting systemic inflammation, which could be attributable to dysfunction of the gut microbiome and adipose tissue, as well as deleterious epigenetic changes, may promote EDS while also increasing cardiovascular risk; however, these pathways may be reciprocal and/or circumstantial. Additionally, gaps within the literature are noted followed by directions for future research.

ObjectiveTo systematically investigate the association of environmental risk factors and prodromal features with incident Parkinson’s disease (PD) diagnosis and the interaction of genetic risk with these factors. To evaluate whether existing risk prediction algorithms are improved by the inclusion of genetic risk scores.MethodsWe identified individuals with an incident diagnosis of PD (n=1276) and controls (n=500 406) in UK Biobank. We determined the association of risk factors with incident PD using adjusted logistic regression models. We constructed polygenic risk scores (PRSs) using external weights and selected the best PRS from a subset of the cohort (30%). The PRS was used in a separate testing set (70%) to examine gene–environment interactions and compare predictive models for PD.ResultsStrong evidence of association (false discovery rate <0.05) was found between PD and a positive family history of PD, a positive family history of dementia, non-smoking, low alcohol consumption, depression, daytime somnolence, epilepsy and earlier menarche. Individuals with the highest 10% of PRSs had increased risk of PD (OR 3.37, 95% CI 2.41 to 4.70) compared with the lowest risk decile. A higher PRS was associated with earlier age at PD diagnosis and inclusion of the PRS in the PREDICT-PD algorithm led to a modest improvement in model performance. We found evidence of an interaction between the PRS and diabetes.InterpretationHere, we used UK Biobank data to reproduce several well-known associations with PD, to demonstrate the validity of a PRS and to demonstrate a novel gene–environment interaction, whereby the effect of diabetes on PD risk appears to depend on background genetic risk for PD.

Sleep disturbances are prevalent in severe mental disorders but their type and frequency across diagnostic categories has not been investigated in large scale studies. Participants with Schizophrenia spectrum disorders (SCZ, (N = 617)), Bipolar disorders (BD, (N = 440)), and Healthy Controls (HC, (N = 173)) were included in the study. Sleep disturbances (insomnia, hypersomnia and delayed sleep phase) were identified based on items from the Inventory of Depressive Symptoms – Clinician rated scale. Clinical symptoms were assessed with the Positive and Negative Syndrome scale and level of functioning with the Global assessment of Functioning scale. The rate of any sleep disturbance was 78% in SZ, 69% in BD and 39% in HC. Insomnia was the most frequently reported sleep disturbance across all groups. Both diagnostic groups reported significantly more of any sleep disturbances than HC (P < 0.001). Having a sleep disturbance was associated with more severe negative and depressive symptoms and with lower functioning across diagnostic groups (P < 0.001, η2 = 0.0071). Hypersomnia was the only sleep disturbance associated with previous treatment history. Sleep disturbances, including insomnia, hypersomnia and delayed sleep phase, are frequent in SCZ and BD, and associated with more severe clinical symptomatology across diagnostic groups. This suggests that sleep disturbance is a clinically relevant transdiagnostic phenomenon. •Insomnia, hypersomnia and delayed sleep phase are frequent in psychotic disorders.•Sleep disturbances are related to more severe symptomatology and lower functioning.•Sleep disturbances are a relevant transdiagnostic treatment target.•Differences in hypersomnia frequency is related to medication with sedative effects.

ObjectivesTo investigate the impact of sleep disturbances on Parkinson’s disease (PD) clinical motor subtypes and disease-related disability in a multicentre setting.MethodsWe report a cross-sectional relationship between sleep-related symptoms and clinical motor subtypes (tremor dominant (TD); intermediate; postural instability and gait disturbances (PIGDs)) identified in a multicentre study, including 436 patients with PD and 401 age-matched controls. PD-related sleep problems (PD-SP), excessive daytime sleepiness (EDS) and probable REM sleep behaviour disorder (pRBD) were evaluated using the PD sleep scale (PDSS)-2, Epworth Sleepiness Scale (ESS) and RBD screening questionnaire-Japanese version (RBDSQ-J), respectively.ResultsPD-SP (PDSS-2 ≥18; 35.1% vs 7.0%), EDS (ESS ≥10; 37.8% vs 15.5%) and pRBD (RBDSQ-J ≥5; 35.1% vs 7.7%) were more common in patients with PD than in controls. The prevalence of restless legs syndrome did not differ between patients with PD and controls (3.4% vs 2.7%). After adjusting for age, sex, disease duration and Movement Disorder Society-Unified PD Rating Scale (MDS-UPDRS) part III score, the PIGD group had higher PDSS-2 and ESS scores than the TD group. The RBDSQ-J scores did not differ among the TD, intermediate and PIGD groups. A stepwise regression model predicting the MDS-UPDRS part II score identified the Hoehn and Yahr stage, followed by the number of sleep-related symptoms (PD-SP, EDS and pRBD), disease duration, MDS-UPDRS part III score, PIGD subtype, depression and MDS-UPDRS part IV score as significant predictors.ConclusionOur study found a significant relationship between sleep disturbances and clinical motor subtypes. An increased number of sleep-related symptoms had an impact on disease-related disability.

Recent research has found evidence of an association between motor vehicle accidents (MVAs) or near miss accidents (NMAs), and excessive daytime sleepiness (EDS) or its main medical cause, Obstructive Sleep Apnea (OSA). However, EDS can also be due to non-medical factors, such as sleep debt (SD), which is common among professional truck drivers. On the opposite side, rest breaks and naps are known to protect against accidents. To investigate the association of OSA, SD, EDS, rest breaks and naps, with the occurrence of MVAs and NMAs in a large sample of truck drivers. 949 male truck drivers took part in a cross-sectional medical examination and were asked to complete a questionnaire about sleep and waking habits, risk factors for OSA and EDS. MVAs and NMAs were reported by 34.8% and 9.2% of participants, respectively. MVAs were significantly predicted by OSA (OR = 2.32 CI95% = 1.68-3.20), SD (OR = 1.45 CI95% = 1.29-1.63), EDS (OR = 1.73 CI95% = 1.15-2.61) and prevented by naps (OR = 0.59 CI95% = 0.44-0.79) or rest breaks (OR = 0.63 CI95% = 0.45-0.89). NMAs were significantly predicted by OSA (OR = 2.39 CI95% = 1.47-3.87) and SD (OR = 1.49 CI95% = 1.27-1.76) and prevented by naps (OR = 0.52 CI95% = 0.32-0.85) or rest breaks (OR = 0.49 CI95% = 0.29-0.82). When OSA, SD or EDS are present, the risk of MVAs or NMAs in truck drivers is severely increased. Taking a rest break or a nap appear to be protective against accidents.

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 ( = 64) reported sleeping 72 min longer based on clinical interviews ( < 0.001) and 23 min longer based on actigraphy ( = 0.011). Controls ( = 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 ( '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 ( '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.

Sleep disturbances, such as insomnia, obstructive sleep apnea, and daytime sleepiness, are common in people diagnosed with epilepsy. These disturbances can be attributed to nocturnal seizures, psychosocial factors, and/or the use of anti-epileptic drugs with sleep-modifying side effects. Epilepsy patients with poor sleep quality have intensified seizure frequency and disease progression compared to their well-rested counterparts. A better understanding of the complex relationship between sleep and epilepsy is needed, since approximately 20% of seizures and more than 90% of sudden unexpected deaths in epilepsy occur during sleep. Emerging studies suggest that neuroinflammation, (e.g., the CNS immune response characterized by the change in expression of inflammatory mediators and glial activation) may be a potential link between sleep deprivation and seizures. Here, we review the mechanisms by which sleep deprivation induces neuroinflammation and propose that neuroinflammation synergizes with seizure activity to worsen neurodegeneration in the epileptic brain. Additionally, we highlight the relevance of sleep interventions, often overlooked by physicians, to manage seizures, prevent epilepsy-related mortality, and improve quality of life.

Abstract Study Objectives Opioid-related adverse events (OAEs), including opioid use disorders, overdose, and death, are serious public health concerns. OAEs are often associated with disrupted sleep, but the long-term relationship between poor sleep and subsequent OAE risk remains unknown. This study investigates whether sleep behavior traits are associated with incident OAEs in a large population cohort. Methods 444 039 participants (mean age ± SD 57 ± 8 years) from the UK Biobank reported their sleep behavior traits (sleep duration, daytime sleepiness, insomnia-like complaints, napping, and chronotype) between 2006 and 2010. The frequency/severity of these traits determined a poor sleep behavior impacts score (0–9). Incident OAEs were obtained from hospitalization records during 12-year median follow-up. Cox proportional hazards models examined the association between sleep and OAEs. Results Short and long sleep duration, frequent daytime sleepiness, insomnia symptoms, and napping, but not chronotype, were associated with increased OAE risk in fully adjusted models. Compared to the minimal poor sleep behavior impacts group (scores of 0–1), the moderate (4–5) and significant (6–9) groups had hazard ratios of 1.47 (95% confidence interval [1.27, 1.71]), p < 0.001, and 2.19 ([1.82, 2.64], p < 0.001), respectively. The latter risk magnitude is greater than the risk associated with preexisting psychiatric illness or sedative-hypnotic medication use. In participants with moderate/significant poor sleep impacts (vs. minimal), subgroup analysis revealed that age <65 years was associated with a higher OAE risk than in those ≥65 years. Conclusions Certain sleep behavior traits and overall poor sleep impacts are associated with an increased risk for opioid-related adverse events. Graphical Abstract

Background There is a great association between the prevalence of obstructive sleep apnea (OSA) and asthma. Nonetheless, whether OSA impacts lung function, symptoms, and control in asthma and whether asthma increases the respiratory events in OSA are unknown. This meta-analysis aimed to examine the relationship between obstructive sleep apnea and asthma severity and vice versa. Methods We carried out a systematic search of PubMed, EMBASE, and Scopus from inception to September 2022. Primary outcomes were lung function, parameters of polysomnography, the risk of OSA in more severe or difficult-to-control asthmatic patients, and the risk of asthma in patients with more severe OSA. Heterogeneity was examined with the Q test and I 2 statistics. We also performed subgroup analysis, Meta-regression, and Egger’s test for bias analysis. Results 34 studies with 27,912 subjects were totally included. The results showed that the comorbidity of OSA aggravated lung function in asthmatic patients with a consequent decreased forced expiratory volume in one second %predicted (%FEV1) and the effect was particularly evident in children. %FEV1 tended to decrease in adult asthma patients complicated with OSA, but did not reach statistical significance. Interestingly, the risk of asthma seemed to be slightly lower in patients with more severe OSA (OR = 0.87, 95%CI 0.763–0.998). Asthma had no significant effect on polysomnography, but increased daytime sleepiness assessed by the Epworth Sleepiness Scale in OSA patients (WMD = 0.60, 95%CI 0.16–1.04). More severe asthma or difficult-to-control asthma was independently associated with OSA (odds ratio (OR) = 4.36, 95%CI 2.49–7.64). Conclusion OSA was associated with more severe or difficult-to-control asthma with decreased %FEV 1 in children. The effect of OSA on lung function in adult patients should be further confirmed. Asthma increased daytime sleepiness in OSA patients. More studies are warranted to investigate the effect of asthma on OSA severity and the impact of different OSA severity on the prevalence of asthma. It is strongly recommended that people with moderate-to-severe or difficult-to-control asthma screen for OSA and get the appropriate treatment.