The longitudinal associations between mental health indicators and digital media use and physical activity during adolescence: A latent class approach

IntroductionEvidence for the relationship between movement behaviors and mental health among adolescents is inconclusive. We aimed to identify profiles of digital media use (including related bedtime delay) and leisure-time physical activity (LTPA) in adolescence, and to examine whether preadolescent mental health predicted later behavior profiles.MethodsThis study included 1285 participants assessed at 11 years of age, and followed-up four years later. Participants completed the Self-Perception Profile for Children (SPPC), Center for Epidemiological Studies Depression Scale for Children (CES-DC) and Screen for Child Anxiety-Related Emotional Disorders (SCARED) at baseline, and reported digital media use (active and passive use, gaming, and related bedtime delays) and LTPA at follow-up. A latent class approach was employed to identify behavior profiles, membership of which was then predicted with mental health and covariates, including baseline digital media use and LTPA.ResultsWe identified four behavior profiles: 1) high digital media use/moderate LTPA (20% of adolescents; 78% boys), 2) moderate digital media use/high LTPA (31%; 28%), 3) high digital media use/high LTPA (26%; 15%), 4) high passive digital media use and gaming/low LTPA (23%; 89%). After adjusting for covariates, higher LTPA and better perception of athletic competence at baseline associated with higher odds of belonging to any other profile than to the unhealthiest profile (4) at follow-up. Symptoms of depression or anxiety did not associate with later behavior profiles.ConclusionsLTPA and related self-esteem seem to be stronger predictors of future digital media use and LTPA behavior during adolescence than mental health symptoms alone.     

Associations of accelerometer-based sleep duration and self-reported sleep difficulties with cognitive function in late mid-life: the Finnish Retirement and Aging Study

ObjectivesPrior evidence suggests that sleep duration and sleep difficulties may be associated with cognitive function in old age, but little is known about the sleep–cognition association in late mid-life. Our aim was to examine the associations of accelerometer-based sleep duration as well as subjective sleep difficulties with different domains of cognitive function among aging workers.MethodsThe study population consisted of 289 participants (mean age 62.4 years, SD 1.02; 83% women) from the Finnish Retirement and Aging Study (FIREA). Sleep difficulties were measured using Jenkins Sleep Problem Scale (difficulties falling asleep, difficulties maintaining sleep, waking up too early in the morning, and nonrestorative sleep). Sleep duration was measured with wrist-worn accelerometer and self-report, and participants were divided into short (<7 h/night), mid-range (7–9 h/night) and long (≥9 h/night) sleepers. Participants underwent extensive cognitive testing covering three domains: (1) memory, (2) executive function, and (3) attention and information processing.ResultsGreater difficulties in waking up too early in the morning were associated with poorer executive function measured with Spatial Working Memory (SWM) test (p = 0.005). Additionally, nonrestorative sleep was associated with poorer executive function measured with Trail Making Test, B–A, (p = 0.036) and borderline significantly with lower SWM (p = 0.056). Compared to mid-range sleepers, long sleepers tended to have poorer cognitive function (all memory function tests and SWM), but the associations were not statistically significant due to small number of long sleepers.ConclusionsSubjective sleep difficulties may be linked to poorer executive function in a relatively healthy population of older workers in their 60 s. Thus, promoting good sleep quality may translate into better cognitive health in late mid-life.     

The association among demographic factors,health behaviors and sleep quality in youth with Autism Spectrum Disorder

BackgroundA majority of youth with Autism Spectrum Disorder (ASD) have disrupted sleep patterns, but there has been limited research examining factors associated with sleep in this population. Objective: The objective of this study was to compare demographic and lifestyle behaviors with sleep quality in youth with ASD. Methods: A total of 49 children (12.44 years; 78% male) with ASD wore the Actigraph GT9X accelerometer over seven days and nights to assess moderate to vigorous physical activity (MVPA), sedentary behavior (SB), total sleep duration, and sleep efficiency. Parents reported their child’s weekly amount of screen time and demographic information. Participants were classified according to whether they met sleep criteria for duration and efficiency (8–9 h of sleep duration and ≥85% sleep efficiency). T-tests and ANOVA were used to compare demographic and lifestyle factors between the groups. Results: Participants who meet both sleep duration and efficiency criteria had greater minutes of MVPA per day (113.65 min/day) than participants who only met sleep efficiency criteria (40.27 min/day) and participants who did not meet either sleep criteria (67.5 min/day; p < 0.0001). Additionally, participants who met both sleep criteria had fewer minutes of SB compared to those who only met sleep efficiency criteria (384.79 vs 526.05 min/day; p = 0.02). Conclusions: Youth who had indicators of good sleep quality had greater amounts of MVPA and lower amounts of SB. Studies should further examine the relationship between sleep and health behaviors in youth with ASD to determine causal mechanisms, leading to more effective sleep interventions.     

Sleep quality in times of Covid-19 pandemic

BackgroundDue to the 2019 novel coronavirus (COVID-19) disease outbreak, social distancing measures were imposed to control the spread of the pandemic. However, isolation may affect negatively the psychological well-being and impair sleep quality. Our aim was to evaluate the sleep quality of respiratory patients during the COVID-19 pandemic lockdown.MethodsAll patients who underwent a telemedicine appointment from March 30 to April 30 of 2020 were asked to participate in the survey. Sleep difficulties were measured using Jenkins Sleep Scale.ResultsThe study population consisted of 365 patients (mean age 63.9 years, 55.6% male, 50.1% with sleep-disordered breathing [SDB]). During the lockdown, 78.9% of participants were confined at home without working. Most patients (69.6%) reported at least one sleep difficulty and frequent awakenings was the most prevalent problem. Reporting at least one sleep difficulty was associated with home confinement without working, female gender and diagnosed or suspected SDB, after adjustment for cohabitation status and use of anxiolytics. Home confinement without working was associated with difficulties falling asleep and waking up too early in the morning. Older age was a protective factor for difficulties falling asleep, waking up too early and non-restorative sleep. Notably, SDB patients with good compliance to positive airway pressure therapy were less likely to report sleep difficulties.ConclusionsHome confinement without working, female gender and SDB may predict a higher risk of reporting sleep difficulties. Medical support during major disasters should be strengthened and potentially delivered through telemedicine, as this comprehensive approach could reduce psychological distress and improve sleep quality.     

Obstructive sleep apnea,CPAP therapy and Parkinson's disease motor function: A longitudinal study

IntroductionWe aimed to assess, in patients with Parkinson's disease (PD), the association between obstructive sleep apnea (OSA), progression of motor dysfunction and the effect of OSA treatment.MethodsData were analysed from a prospective cohort study of idiopathic PD patients from a movement disorders clinic. Patients found to have OSA on polysomnography (apnea-hypopnea index [AHI] ≥15 events/h, OSA+) were offered treatment using continuous positive airway pressure (CPAP). CPAP+ was defined as an average ≥ 2 h/night use at each follow-up. Motor symptoms were assessed using the motor section of the Movement Disorder Society Unified Parkinson's Disease Rating Scale (mUPDRS) and the Timed-Up-And-Go (TUG). Follow-up times were 3, 6 and 12 months. Mixed models were constructed, adjusting for age, sex, body mass index, levodopa equivalent dose and comorbidities.ResultsWe studied 67 individuals (61.2% male) of mean age 64.7 years (SD = 10.1). Baseline mUPDRS was higher in OSA+ compared to OSA- (24.5 [13.6] vs. 16.2 [7.2], p < 0.001). Motor dysfunction increased at comparable rates in OSA- and OSA+CPAP-. However, in OSA+CPAP+, mUPDRS change was significantly lower compared to OSA- (β = −0.01 vs. 0.61, p = 0.03; p = 0.12 vs. OSA+CPAP- [β = 0.39]) and TUG change was lower compared to OSA+CPAP- (β = −0.01 vs. 0.13, p = 0.002; p = 0.05 vs. OSA- [β = 0.02]).ConclusionsIn this PD cohort, OSA was associated with higher baseline mUPDRS. In those with OSA, CPAP use was associated with stabilization of motor function (mUPDRS and TUG) over 12 months. These observations support further research to clarify the role of OSA in PD pathophysiology and motor dysfunction.     

阻塞性睡眠呼吸暂停低通气综合征患者CYP3A4基因多态性的检测

目的探讨阻塞性睡眠呼吸暂停低通气综合征(OSAHS)CYP3A4基因的多态性,了解其对芬太尼类药物的敏感性及不同基因型的人群分布特征,指导临床个体化用药。方法对50例OSAHS患者进行CYP3A4基因的多态性检测,采静脉血,通过DNA抽提-PCR扩增-焦磷酸测序方法检测CYP3A4基因。结果野生纯合型型34例(68%),突变杂合型15例(30%),突变纯合型型1例(2%)。结论OSAHS患者中约2%为AA型,该型对芬太尼类药物极其敏感,术后有易发生窒息的风险,应高度警惕芬太尼类药物呼吸抑制的潜在风险。     

Automated classification of depression from structural brain measures across two independent community‐based cohorts

Major depressive disorder (MDD) has been the subject of many neuroimaging case–control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically‐ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well‐phenotyped community‐based group of current MDD cases with clinical interview‐based diagnoses (from STratifying Resilience and Depression Longitudinally cohort, ‘STRADL’). We performed a set of exploratory predictive classification analyses with measures related to brain morphometry and white matter integrity. We applied three classifier types—SVM, penalised logistic regression or decision tree—either with or without optimisation, and with or without feature selection. We then determined whether similar accuracies could be replicated in a larger independent population‐based sample with self‐reported current depression (UK Biobank cohort). Additional analyses extended to lifetime MDD diagnoses—remitted MDD in STRADL, and lifetime‐experienced MDD in UK Biobank. The highest cross‐validation accuracy (75%) was achieved in the initial current MDD sample with a decision tree classifier and cortical surface area features. The most frequently selected decision tree split variables included surface areas of bilateral caudal anterior cingulate, left lingual gyrus, left superior frontal, right precentral and paracentral regions. High accuracy was not achieved in the larger samples with self‐reported current depression (53.73%), with remitted MDD (57.48%), or with lifetime‐experienced MDD (52.68–60.29%). Our results indicate that high predictive classification accuracies may not immediately translate to larger samples with broader criteria for depression, and may not be robust across different classification approaches.     

Evaluating the inhibitory potential of Withania somnifera on platelet aggregation and inflammation enzymes: An in vitro and in silico study

Context Withania somnifera (L.) Dunal is traditionally used for treating various ailments, but lacks scientific evaluation.

Objective This study evaluates Withania somnifera (WS) for its effect on platelet activity and inflammatory enzymes.

Materials and methods Aqueous and ethanolic (1:1) leaf extracts were subjected to in vitro indirect haemolytic activity using Naja naja venom, human platelet aggregation was quantified for lipid peroxidation using arachidonic acid (AA) as agonist and 5-lipoxygenase (5-LOX) levels were determined using standard spectrometric assays. Further, molecular docking was performed by the ligand fit method using molegro software package (Molegro ApS, Aarhus, Denmark).

Results The study found that aqueous and ethanol extracts have very negligible effect (15%) with an IC₅₀ value of 13.8?mg/mL on PLA₂ from Naja naja venom. Further, extracts of WS also had very little effect (18%) with an IC₅₀ value of 16.6?mg/mL on malondialdehyde (MDA) formation. However, a 65% inhibition of 5-LOX with an IC₅₀ value of 0.92?mg/mL was observed in 1:1 ethanol extracts. The same was evident from SAR model with the active ingredient withaferin A binding predominantly on Phe 77, Tyr 98, Arg 99, Asp 164, Leu 168, Ser 382, Arg 395, Tyr 396 and Tyr 614 with an atomic contact energy value of??128.96 compared to standard phenidone (?103.61). Thus, the current study validates the application of WS for inflammatory diseases.

Conclusion This study reveals the inhibitory potential of W. somnifera on inflammatory enzymes and platelet aggregation. Thus, WS can serve as a newer, safer and affordable medicine for inflammatory diseases.