Summary The ineffectiveness of sleep hygiene as a treatment in clinical sleep medicine has raised some interesting questions. If it is known that, individually, each specific component of sleep hygiene is related to sleep, why wouldn't addressing multiple individual components (i.e., sleep hygiene education) result in improved sleep? Is there still a use for sleep hygiene? Global public health concern over poor sleep has increased the demand for effective sleep promotion strategies that are easily accessible to the general population. However, the extent to which sleep hygiene principles and strategies apply outside of clinical settings is not well known. The present review sought to evaluate the empirical evidence for several common sleep hygiene recommendations, including regular exercise, stress management, noise reduction, sleep timing regularity, and avoidance of caffeine, nicotine, alcohol, and daytime napping, with a particular emphasis on their public health utility. Thus, our review is not intended to be exhaustive regarding the clinical application of these techniques, but rather to focus on broader applications. Overall, though epidemiologic and experimental research generally supported an association between individual sleep hygiene recommendations and nocturnal sleep, the direct effects of individual recommendations on sleep remains largely untested in the general population. Suggestions for further clarification of sleep hygiene recommendations and considerations for the use of sleep hygiene in nonclinical populations are discussed.

In the wake of the COVID-19 pandemic, social restrictions to contain the spread of the virus have disrupted behaviors across the 24-h day including physical activity, sedentary behavior, and sleep among children (5–12 years old) and adolescents (13–17 years old). Preliminary evidence reports significant decreases in physical activity, increases in sedentary behavior, and disrupted sleep schedules/sleep quality in children and adolescents. This commentary discusses the impact of COVID-19-related restrictions on behaviors across the 24-h day in children and adolescents. Furthermore, we suggest recommendations through the lens of a socio-ecological model to provide strategies for lasting behavior change to insure the health and well-being of children and adolescents during the COVID-19 pandemic.

Clinicaltrials.gov identification number NCT00956423.

Background Several studies have shown a favorable effect of supervised exercise training on obstructive sleep apnea (OSA). This meta-analysis was conducted to analyze the data from these studies on the severity of OSA (primary outcome) in adults. Secondary outcomes of interest included body mass index (BMI), sleep efficiency, daytime sleepiness and cardiorespiratory fitness. Methods Two independent reviewers searched PubMed and Embase (from inception to March 6, 2013) to identify studies on the effects of supervised exercise training in adults with OSA. Pre- and postexercise training data on our primary and secondary outcomes were extracted. Results A total of 5 studies with 6 cohorts that enrolled a total of 129 study participants met the inclusion criteria. The pooled estimate of mean pre- to postintervention (exercise) reduction in AHI was −6.27 events/h (95 % confidence interval [CI] −8.54 to −3.99; p < 0.001). The pooled estimates of mean changes in BMI, sleep efficiency, Epworth sleepiness scale and VO2 peak were −1.37 (95 % CI −2.81 to 0.07; p = 0.06), 5.75 % (95 % CI 2.47–9.03; p = 0.001), −3.3 (95 % CI −5.57 to −1.02; p = 0.004), and 3.93 mL/kg/min (95 % CI 2.44–5.42; p < 0.001), respectively. Conclusions This meta-analysis shows a statistically significant effect of exercise in reducing the severity of sleep apnea in patients with OSA with minimal changes in body weight. Additionally, the significant effects of exercise on cardiorespiratory fitness, daytime sleepiness, and sleep efficiency indicate the potential value of exercise in the management of OSA.

Background Emerging cross-sectional reports find that the COVID-19 pandemic and related social restrictions negatively affect lifestyle behaviours and mental health in general populations. Aims To study the longitudinal impact of COVID-19 on work practices, lifestyle and well-being among desk workers during shelter-at-home restrictions. Methods We added follow-up after completion of a clinical trial among desk workers to longitudinally measure sedentary behaviour, physical activity, sleep, diet, mood, quality of life and work-related health using validated questionnaires and surveys. We compared outcomes assessed before and during COVID-19 shelter-at-home restrictions. We assessed whether changes in outcomes differed by remote working status (always, changed to or never remote) using analysis of covariance (ANCOVA). Results Participants (N = 112; 69% female; mean (SD) age = 45.4 (12.3) years; follow-up = 13.5 (6.8) months) had substantial changes to work practices, including 72% changing to remote work. Deleterious changes from before to during shelter-at-home included: 1.3 (3.5)-h increase in non-workday sedentary behaviour; 0.7 (2.8)-point worsening of sleep quality; 8.5 (21.2)-point increase in mood disturbance; reductions in five of eight quality of life subscales; 0.5 (1.1)-point decrease in work-related health (P &lt; 0.05). Other outcomes, including diet, physical activity and workday sedentary behaviour, remained stable (P ≥ 0.05). Workers who were remote before and during the pandemic had greater increases in non-workday sedentary behaviour and stress, with greater declines in physical functioning. Wake time was delayed overall by 41 (61) min, and more so in workers who changed to remote. Conclusions Employers should consider supporting healthy lifestyle and well-being among desk workers during pandemic-related social restrictions, regardless of remote working status.

Although exercise is widely believed to improve sleep, experimental evidence has found acute and chronic exercise to exert only modest effects on subsequent sleep. However, these studies are limited in that they have primarily used good sleepers (floor/ceiling effects). In contrast to experimental studies, epidemiologic studies have consistently reported significant positive associations between self-reported exercise habits and better self-reported sleep. This association has been confirmed across a wide range of demographics. Nonetheless, epidemiologic studies on this topic have also had limitations. They have often assessed exercise and sleep using instruments of dubious validity. Moreover, the studies have generally not included clinical diagnoses of sleep disorders. Thus, the clinical relevance of these findings is unclear. In addition, possible alternative explanations for the association of exercise and improved sleep have often not been controlled (e.g. bright light, other healthy behaviors). This review will focus on these epidemiologic studies. We will review and critique representative survey and epidemiologic studies of exercise and sleep and discuss directions for future research in this area.

Exercise has long been associated with better sleep, and evidence is accumulating on the efficacy of exercise as a nonpharmacologic treatment option for disturbed sleep. Recent research, however, has noted that poor sleep may contribute to low physical activity levels, emphasizing a robust bidirectional relationship between exercise and sleep. This article will briefly review the evidence supporting the use of exercise as a nonpharmacologic treatment for sleep disturbance, outline future research that is needed to establish the viability of exercise as a behavioral sleep treatment, describe recent research that has emphasized the potential influence of poor sleep on daytime activity levels, and discuss whether improving sleep may facilitate adoption and/or better adherence to a physically active lifestyle. With poor sleep and physical inactivity each recognized as key public health priorities, additional research into the bidirectional relationship between exercise and sleep has significant implications for facilitating greater exercise adherence and improving sleep in society.

BackgroundThe independent and combined influence of smoking, alcohol consumption, physical activity, diet, sitting time, and sleep duration and quality on health status is not routinely examined. This study investigates the relationships between these lifestyle behaviors, independently and in combination, and health-related quality of life (HRQOL).MethodsAdult members of the 10,000 Steps project (n = 159,699) were invited to participate in an online survey in November-December 2011. Participant socio-demographics, lifestyle behaviors, and HRQOL (poor self-rated health; frequent unhealthy days) were assessed by self-report. The combined influence of poor lifestyle behaviors were examined, independently and also as part of two lifestyle behavior indices, one excluding sleep quality (Index 1) and one including sleep quality (Index 2). Adjusted Cox proportional hazard models were used to examine relationships between lifestyle behaviors and HRQOL.ResultsA total of 10,478 participants provided complete data for the current study. For Index 1, the Prevalence Ratio (p value) of poor self-rated health was 1.54 (p = 0.001), 2.07 (p≤0.001), 3.00 (p≤0.001), 3.61 (p≤0.001) and 3.89 (p≤0.001) for people reporting two, three, four, five and six poor lifestyle behaviors, compared to people with 0–1 poor lifestyle behaviors. For Index 2, the Prevalence Ratio (p value) of poor self-rated health was 2.26 (p = 0.007), 3.29 (p≤0.001), 4.68 (p≤0.001), 6.48 (p≤0.001), 7.91 (p≤0.001) and 8.55 (p≤0.001) for people reporting two, three, four, five, six and seven poor lifestyle behaviors, compared to people with 0–1 poor lifestyle behaviors. Associations between the combined lifestyle behavior index and frequent unhealthy days were statistically significant and similar to those observed for poor self-rated health.ConclusionsEngaging in a greater number of poor lifestyle behaviors was associated with a higher prevalence of poor HRQOL. This association was exacerbated when sleep quality was included in the index.