Objective: To assess whether sleep timing and napping behavior are associated with increased obesity, independent of nocturnal sleep length.
Design, Setting, and Participants: This large, multinational, population-based cross-sectional study used data of participants from 60 study centers in 26 countries with varying income levels as part of the Prospective Urban Rural Epidemiology study. Participants were aged 35 to 70 years and were mainly recruited during 2005 and 2009. Data analysis occurred from October 2020 through March 2021.
Exposures: Sleep timing (ie, bedtime and wake-up time), nocturnal sleep duration, daytime napping.
Main Outcomes and Measures: The primary outcomes were prevalence of obesity, specified as general obesity, defined as body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 30 or greater, and abdominal obesity, defined as waist circumference greater than 102 cm for men or greater than 88 cm for women. Multilevel logistic regression models with random effects for study centers were performed to calculate adjusted odds ratios (AORs) and 95% CIs.
Results: Overall, 136 652 participants (81 652 [59.8%] women; mean [SD] age, 51.0 [9.8] years) were included in analysis. A total of 27 195 participants (19.9%) had general obesity, and 37 024 participants (27.1%) had abdominal obesity. The mean (SD) nocturnal sleep duration was 7.8 (1.4) hours, and the median (interquartile range) midsleep time was 2:15 am (1:30 am-3:00 am). A total of 19 660 participants (14.4%) had late bedtime behavior (ie, midnight or later). Compared with bedtime between 8 pm and 10 pm, late bedtime was associated with general obesity (AOR, 1.20; 95% CI, 1.12-1.29) and abdominal obesity (AOR, 1.20; 95% CI, 1.12-1.28), particularly among participants who went to bed between 2 am and 6 am (general obesity: AOR, 1.35; 95% CI, 1.18-1.54; abdominal obesity: AOR, 1.38; 95% CI, 1.21-1.58). Short nocturnal sleep of less than 6 hours was associated with general obesity (eg, <5 hours: AOR, 1.27; 95% CI, 1.13-1.43), but longer napping was associated with higher abdominal obesity prevalence (eg, ≥1 hours: AOR, 1.39; 95% CI, 1.31-1.47). Neither going to bed during the day (ie, before 8pm) nor wake-up time was associated with obesity.
Conclusions and Relevance: This cross-sectional study found that late nocturnal bedtime and short nocturnal sleep were associated with increased risk of obesity prevalence, while longer daytime napping did not reduce the risk but was associated with higher risk of abdominal obesity. Strategic weight control programs should also encourage earlier bedtime and avoid short nocturnal sleep to mitigate obesity epidemic.
METHODS: We surveyed 16 512 adults from July 2020 to August 2021 in 30 territories. Participants self-reported their medical histories and the perceived impact of COVID-19 on 18 lifestyle factors and 13 health outcomes. For each disease subgroup, we generated lifestyle, health outcome, and bridge networks. Variables with the highest centrality indices in each were identified central or bridge. We validated these networks using nonparametric and case-dropping subset bootstrapping and confirmed central and bridge variables' significantly higher indices through a centrality difference test.
FINDINGS: Among the 48 networks, 44 were validated (all correlation-stability coefficients >0.25). Six central lifestyle factors were identified: less consumption of snacks (for the chronic disease: anxiety), less sugary drinks (cancer, gastric ulcer, hypertension, insomnia, and pre-diabetes), less smoking tobacco (chronic obstructive pulmonary disease), frequency of exercise (depression and fatty liver disease), duration of exercise (irritable bowel syndrome), and overall amount of exercise (autoimmune disease, diabetes, eczema, heart attack, and high cholesterol). Two central health outcomes emerged: less emotional distress (chronic obstructive pulmonary disease, eczema, fatty liver disease, gastric ulcer, heart attack, high cholesterol, hypertension, insomnia, and pre-diabetes) and quality of life (anxiety, autoimmune disease, cancer, depression, diabetes, and irritable bowel syndrome). Four bridge lifestyles were identified: consumption of fruits and vegetables (diabetes, high cholesterol, hypertension, and insomnia), less duration of sitting (eczema, fatty liver disease, and heart attack), frequency of exercise (autoimmune disease, depression, and heart attack), and overall amount of exercise (anxiety, gastric ulcer, and insomnia). The centrality difference test showed the central and bridge variables had significantly higher centrality indices than others in their networks (P
Methods: This double-blind, randomized, placebo-controlled trial involved fifty subjects with sleep complaints. Subjects with a Pittsburgh Sleep Quality Index (PSQI) score between 6 and 15 were randomized to receive either IQP-AO-101 or placebo for 6 weeks, following a run-in period of one week. Sleep parameters were assessed at baseline and after 1, 4, and 6 weeks using the modified Athens Insomnia Scale (mAIS). Subjects were also instructed to wear an activity tracker and keep a sleep diary during the study. Other questionnaires administered were the Frankfurt Attention Inventory (FAIR-2) and the Profile of Mood States (POMS-65). Blood samples for safety laboratory parameters were taken before and at the end of the study.
Results: After 6 weeks, subjects who consumed IQP-AO-101 reported significant improvements in mAIS scores compared with placebo, including mAIS total score (11.76 ± 6.85 vs 4.00 ± 4.80; p < 0.001); night parameters composite score (5.20 ± 3.80 vs 2.04 ± 3.16; p = 0.001); and day parameters composite score (6.56 ± 4.10 vs 1.96 ± 2.65; p < 0.001). All individual parameters (Items 1 to 8) were also significantly improved from baseline after 6 weeks of IQP-AO-101 intake. Analysis of variance with baseline values as covariates showed statistically significant improvements across all individual parameters for IQP-AO-101 when compared to placebo. The measurements using the activity tracker, sleep diary, FAIR-2, and POMS did not reveal any significant differences between groups. No adverse effects related to the intake of IQP-AO-101 were reported. Tolerability was rated as very good by all the subjects and by the investigator for all cases.
Conclusions: In this study, IQP-AO-101 was well tolerated and efficacious for promoting sleep and enhancing daytime performance in subjects with moderate sleep disturbances.
Clinical Trial Registration: This trial is registered with ClinicalTrials.gov, no. NCT03114696.
OBJECTIVES: This systematic review aimed to identify, evaluate and summarise the published literature on the therapeutic roles of natural remedies in the treatment of HA to provide evidence for clinical practice.
METHODS: A systematic literature search was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Web of Science, PubMed and Science Direct Scopus were thoroughly searched for relevant published articles from June 2007 to July 2020.
RESULTS: Ten pre-clinical and two clinical studies were eligible for inclusion in this systematic review. We identified the therapeutic roles of medicinal plants Brassica napus, Gardenia jasminoides, Gastrodia elata, Ginkgo biloba, Glycyrrhiza inflata, Paeonia lactiflora, Pueraria lobata and Rehmannia glutinosa; herbal formulations Shaoyao Gancao Tang and Zhengan Xifeng Tang; and medicinal mushroom Hericium erinaceus in the treatment of HA. In this review, we evaluated the mode of actions contributing to their therapeutic effects, including activation of the ubiquitin-proteasome system, activation of antioxidant pathways, maintenance of intracellular calcium homeostasis and regulation of chaperones. We also briefly highlighted the integral cellular signalling pathways responsible for orchestrating the mode of actions.
CONCLUSION: We reviewed the therapeutic roles of natural remedies in improving or halting the progression of HA, which warrant further study for applications into clinical practice.
Objectives: The aim of this study was to analyze the TTI and outcomes of ART among MMT clients in primary health-care centers in Kuantan, Pahang.
Materials and Methods: This was a retrospective evaluation of MMT clients from 2006 to 2019. The TTI was calculated from the day of MMT enrolment to ART initiation. The trends of CD4 counts and viral loads were descriptively evaluated. Cox proportional hazard model was used to analyze the survival and treatment retention rate.
Results: A total of 67 MMT clients from six primary health-care centers were HIV-positive, of which 37 clients were started on ART. The mean TTI of ART was 27 months. The clients who were given ART had a mean CD4 count of 119 cells/mm3 at baseline and increased to 219 cells/mm3 after 6 months of ART. Only two patients (5.4%) in the ART subgroup had an unsuppressed viral load. The initiation of ART had reduced the risk of death by 72.8% (hazard ratio = 0.27, P = 0.024), and they are 13.1 times more likely to remain in treatment (P < 0.01).
Conclusion: The TTI of ART was delayed in this population. MMT clients who were given ART have better CD4 and viral load outcomes, helped reduced death risk and showed higher retention rates in MMT program.