A Protocol to Determine Circadian Phase by At-Home Salivary Dim Light Melatonin Onset Assessment.

Internal circadian phase assessment is increasingly acknowledged as a critical clinical tool for the diagnosis, monitoring, and treatment of circadian rhythm sleep-wake disorders and for investigating circadian timing in other medical disorders. The widespread use of in-laboratory circadian phase assessments in routine practice has been limited, most likely because circadian phase assessment is not required by formal diagnostic nosologies, and is not generally covered by insurance. At-home assessment of salivary dim light melatonin onset (DLMO, a validated circadian phase marker) is an increasingly accepted approach to assess circadian phase. This approach may help meet the increased demand for assessments and has the advantages of lower cost and greater patient convenience. We reviewed the literature describing at-home salivary DLMO assessment methods and identified factors deemed to be important to successful implementation. Here, we provide specific protocol recommendations for conducting at-home salivary DLMO assessments to facilitate a standardized approach for clinical and research purposes. Key factors include control of lighting, sampling rate, and timing, and measures of patient compliance. We include findings from implementation of an optimization algorithm to determine the most efficient number and timing of samples in patients with Delayed Sleep-Wake Phase Disorder. We also provide recommendations for assay methods and interpretation. Providing definitive criteria for each factor, along with detailed instructions for protocol implementation, will enable more widespread adoption of at-home circadian phase assessments as a standardized clinical diagnostic, monitoring, and treatment tool.

Obstructive Sleep Apnea is a Risk Factor for Incident COVID-19 Infection.

Cross-sectional studies suggest that obstructive sleep apnea (OSA) is a potential risk factor for incident COVID-19 infection, but longitudinal studies are lacking. In this study, two surveys from a large general population cohort, the COVID-19 Outbreak Public Evaluation (COPE) Initiative, undertaken 147 ± 58 days apart were analyzed to determine whether the pre-existing OSA was a risk factor for the incidence of COVID-19. Of the 24,803 respondents completing the initial survey, 14,950 were negative for COVID-19; data from the follow-up survey were available for 2,325 respondents. Those with incident COVID-19 infection had a slightly higher prevalence of OSA (14.3 vs. 11.5%, p=0.068). Stratification by treatment status revealed that those untreated for their OSA were at greater risk for developing COVID-19 infection (OSA Untreated, 14.2 vs. 7.4%, p≤0.05). In a logistic regression model adjusted for comorbidities, demographic and socioeconomic factors and the interaction between vaccination status and OSA, incident COVID-19 infection was 2.15 times more likely in those with untreated OSA (aOR: 2.15, 95% CI: 1.18-3.92, p≤0.05). Stratification by treatment status revealed only untreated OSA participants were at greater risk for COVID-19 (aOR: 3.21, 95% CI: 1.25-8.23, p≤0.05). The evidence from this study confirms untreated OSA as a risk factor for acquiring COVID-19 infection and highlights the importance of actively treating and managing OSA as a preventative mechanism against COVID-19 disease.

Rapid Online Data Collection and Reporting to Local Health Departments during the Pandemic: The COVID-19 Outbreak Public Evaluation (COPE) Initiative SARS-CoV-2 Case Surveys.

OBJECTIVES: To develop and implement a pilot online data collection tool to help local health departments with their COVID-19 pandemic response efforts and inform health department actions. DESIGN: The COVID-19 Outbreak Public Evaluation (COPE) was an online survey and was distributed by participating sites to individuals who recently tested positive for SARS-CoV-2. Surveys recorded participant demographics and assessed recent infection risk behaviors (eg, mask use, air travel), vaccination status, sleep and exercise habits, social behaviors and beliefs, and physical and mental health. SETTING: Seven health departments participated in the initiative, which took place during May 1 to September 30, 2022. Identical items were administered to demographically representative samples of adults nationally in the United States within a similar timeframe. PARTICIPANTS: A total of 38 555 participants completed surveys. Responses from participants with recent SARS-CoV-2 infections were compared with respondents from the national surveys who did not have evidence or awareness of prior SARS-CoV-2 infections. MAIN OUTCOME MEASURE: To implement of a process that allows health departments to receive data from local cases and compare this information to national controls during the COVID-19 pandemic. RESULTS: Fifty-four biweekly reports were provided to public health departments between May and September 2022. Information and comparisons within the reports were updated in response to evolving public health priorities for the pandemic response. The initiative helped to guide public health response efforts during the COVID-19 pandemic. Moreover, the receptiveness by local health departments and participants provides evidence to support this data collection and reporting model as a component of the public health response to future emergencies. CONCLUSION: This project demonstrates the feasibility of a centralized, rapid, and adaptive data collection system for local health departments and provides evidence to advocate for data collection methods to help guide local health departments to respond in a timely and effective manner to future public health emergencies.

Higher central circadian temperature amplitude is associated with greater metabolite rhythmicity in humans.

Robust circadian rhythms are essential for optimal health. The central circadian clock controls temperature rhythms, which are known to organize the timing of peripheral circadian rhythms in rodents. In humans, however, it is unknown whether temperature rhythms relate to the organization of circadian rhythms throughout the body. We assessed core body temperature amplitude and the rhythmicity of 929 blood plasma metabolites across a 40-h constant routine protocol, controlling for behavioral and environmental factors that mask endogenous temperature rhythms, in 23 healthy individuals (mean [± SD] age = 25.4 ± 5.7 years, 5 women). Valid core body temperature data were available in 17/23 (mean [± SD] age = 25.6 ± 6.3 years, 1 woman). Individuals with higher core body temperature amplitude had a greater number of metabolites exhibiting circadian rhythms (R2 = 0.37, p = .009). Higher core body temperature amplitude was also associated with less variability in the free-fitted periods of metabolite rhythms within an individual (R2 = 0.47, p = .002). These findings indicate that a more robust central circadian clock is associated with greater organization of circadian metabolite rhythms in humans. Metabolite rhythms may therefore provide a window into the strength of the central circadian clock.

Sleep and long COVID: Preexisting sleep issues and the risk of PASC in a large general population using 3 different model definitions.

Study Objectives: Insomnia, poor sleep quality and extremes of sleep duration are associated with COVID-19 infection. This study assessed whether these factors are related to Post-Acute Sequelae of SARS-CoV-2 infection (PASC). Methods: Cross-sectional survey of a general population of 24,803 U.S. adults to determine the association of insomnia, poor sleep quality and sleep duration with PASC. Results: Prevalence rates of PASC among previously COVID-19 infected participants for three definitions of PASC were COPE (21.9%), NICE (38.9%) and RECOVER PASC Score (15.3%). PASC was associated with insomnia in all 3 models in fully adjusted models with adjusted odds ratios (aORs) and 95% confidence intervals (CI) ranging from 1.30 (95% CI: 1.11-1.52, p≤0.05, PASC Score) to 1.52 (95% CI: 1.34-1.71, p≤0.001, (NICE). Poor sleep quality was related to PASC in all models with aORs ranging from 1.77 (95% CI: 1.60-1.97, p≤0.001, NICE) to 2.00 (95% CI: 1.77-2.26, p≤0.001, COPE). Sleep <6 hours was associated with PASC with aORs between 1.59 (95% CI: 1.40-1.80, p≤0.001, PASC Score) to 1.70 (95% CI: 1.53-1.89, p≤0.001, COPE). Sleep ≥ 9 hours was not associated with PASC in any model. Although vaccination with COVID-19 booster decreased the likelihood of developing PASC, it did not attenuate associations between insomnia, poor sleep quality and short sleep duration with PASC in any of the models. Conclusions: Insomnia, poor sleep quality and short sleep duration are potential risk factors for PASC. Interventions to improve sleep may decrease the development of PASC.

Device-Measured Weekend Catch-Up Sleep, Mortality, and Cardiovascular Disease Incidence in Adults.

STUDY OBJECTIVE: Attempting to recover a sleep debt by extending sleep over the weekend is a common compensatory behavior in the population and is recommended by sleep-focused organizations. However, the purported benefits of catch-up sleep are based on a limited number of cross-sectional studies that relied on self-reported sleep. The objective of this study was to examine the association between accelerometer-derived weekend catch-up sleep and mortality and incident cardiovascular disease (CVD) in adults. METHODS: A prospective cohort study of UK adults who wore wrist-attached accelerometers was conducted. Weekend catch-up sleep was defined as a longer average sleep duration on weekends compared to weekdays. Participants were categorized into four groups: no weekend catch-up sleep (reference); >0 to <1 hour; ≥1 to <2 hours; and ≥2 hours difference. Associations between weekend catch-up sleep and mortality and incident CVD were assessed using Cox proportional hazards regression, adjusted for potential confounders. RESULTS: A total of 73,513 participants (sample for mortality) and 70,518 participants (sample for CVD incidence) were included, with an average (SD) follow-up period of 8.0 (0.9) years. In multivariable-adjusted models, weekend catch-up sleep was not associated with mortality (≥2 hours group: hazard ratio [HR], 1.17 [95% CI, 0.97-1.41]) or incident CVD (HR, 1.05 [95% CI, 0.94-1.18]). Dose-response analyses treating catch-up sleep as a continuous measure or analyses restricted to adults sleeping less than 6 hours on weekdays at baseline were in agreement with these findings. CONCLUSION: Weekend catch-up sleep was not associated with mortality or CVD incidence. These findings do not align with previous evidence and recommendations by sleep authorities suggesting that extending sleep over the weekend may offer protective health benefits.

SleepSync: Early Testing of a Personalised Sleep-Wake Management Smartphone Application for Improving Sleep and Cognitive Fitness in Defence Shift Workers.

Shift work, long work hours, and operational tasks contribute to sleep and circadian disruption in defence personnel, with profound impacts on cognition. To address this, a digital technology, the SleepSync app, was designed for use in defence. A pre-post design study was undertaken to examine whether four weeks app use improved sleep and cognitive fitness (high performance neurocognition) in a cohort of shift workers from the Royal Australian Air Force. In total, 13 of approximately 20 shift-working personnel from one base volunteered for the study. Sleep outcomes were assessed using the Insomnia Severity Index (ISI), the Patient-Reported Outcomes Measurement Information System (PROMIS), Sleep Disturbance and Sleep-Related Impairment Scales, the Glasgow Sleep Effort Scale, the Sleep Hygiene Index, and mental health was assessed using the Depression, Anxiety, and Stress Scale-21. Sustained attention was measured using the 3-min Psychomotor Vigilance Task (PVT) and controlled response using the NBack. Results showed significant improvements in insomnia (ISI scores 10.31 at baseline and 7.50 after app use), sleep-related impairments (SRI T-scores 53.03 at baseline to 46.75 post-app use), and healthy sleep practices (SHI scores 21.61 at baseline to 18.83 post-app use; all p < 0.001). Trends for improvement were recorded for depression. NBack incorrect responses reduced significantly (9.36 at baseline; reduced by -3.87 at last week of app use, p < 0.001), but no other objective measures improved. These findings suggest that SleepSync may improve sleep and positively enhance cognitive fitness but warrants further investigation in large samples. Randomised control trials with other cohorts of defence personnel are needed to confirm the utility of this intervention in defence settings.

Assessment and management of sleep disorders in shift workers: Challenges and considerations for general practice.

BACKGROUND: Shift work is characterised by displaced sleep opportunities and associated sleep disturbance. Shift workers often report sleepiness and other wake time symptoms associated with poor sleep. However, clinical sleep disorders are also prevalent in shift workers. Although prevalence rates are similar or higher in shift workers compared with the general population, help seeking in shift workers with sleep disorders is low. OBJECTIVE: This article aims to provide general practitioners with a contemporary overview of the prevalence rates for sleep disorders in shift workers, to clarify the existing evidence relating to mental and physical health consequences of sleep disorders in shift workers and to highlight the need to consider undiagnosed sleep disorders before attributing sleep-related symptoms solely to work schedules. DISCUSSION: Symptoms of sleep loss associated with shift work overlap with symptoms experienced by individuals living with sleep disorders. Although >40% of middle-aged Australians live with a sleep disorder that requires investigation and management, symptoms in shift workers are often attributed to the work schedule and, as a result, might not be investigated for appropriate diagnosis and treatment. We argue that screening for sleep disorders in shift workers with sleep complaints should be a priority.

Association of Chronotype and Shiftwork With COVID-19 Infection.

OBJECTIVE: This study assesses whether chronotype is related to COVID-19 infection and whether there is an interaction with shift work. Methods: This study used a cross-sectional survey of 19,821 U.S. adults. Results: COVID-19 infection occurred in 40% of participants, 32.6% morning and 17.2% evening chronotypes. After adjusting for demographic and socioeconomic factors, shift/remote work, sleep duration, and comorbidities, morning chronotype was associated with a higher (adjusted odds ratio [aOR]: 1.15, 95% CI: 1.10-1.21) and evening chronotype with a lower (aOR: 0.82, 95% CI: 0.78-0.87) prevalence of COVID-19 infection in comparison to an intermediate chronotype. Working exclusively night shifts was not associated with higher prevalence of COVID-19. Morning chronotype and working some evening shifts was associated with the highest prevalence of previous COVID-19 infection (aOR: 1.87, 95% CI: 1.28-2.74). Conclusion: Morning chronotype and working a mixture of shifts increase risk of COVID-19 infection.

Disruptions to sleep and circadian rhythms are associated with poorer athlete mental health in female, but not male, elite Australian Rules footballers.

Elite athletes are vulnerable to sleep and circadian disruption and associated mental health symptoms. This study aimed to investigate sex differences in sleep, circadian rhythms, and mental health, as well as the moderating role of sex in the prediction of mental health, among male professional and female semi-professional elite athletes. Participants were 87 elite Australian Rules football (ARF) athletes (43% female; mean [standard deviation] age 24.0 [4.1] years). Participants completed baseline questionnaires, 2 weeks of sleep/wake monitoring via actigraphy, and a circadian phase assessment (dim-light melatonin onset [DLMO]). Cross-sectional data were collected in training-only Australian Football League (AFL) Men's and Women's pre-season periods, with 53 providing data in two pre-seasons. Female athletes, relative to males, reported poorer mental health (a higher athlete psychological strain score), had a later mid-sleep time (by 28 min), reported a greater preference towards eveningness, and displayed a later circadian phase (by 33 min). For female athletes, lower sleep efficiency and lower sleep regularity were associated with poorer mental health. For female athletes, there were U-shaped relationships between both morningness-eveningness and phase angle (interval between sleep onset and DLMO time) and mental health. No significant relationships were found for male athletes. In summary, elite female ARF athletes reported poorer mental health, relative to males, especially when experiencing sleep or circadian disruption. Lifestyle factors associated with sex differences in ARF professionalism (scheduling, finances, supports) may contribute to these findings. Programmes to improve sleep, circadian alignment, and mental health among female semi-professional elite athletes should be strongly considered.

Accurate detection of acute sleep deprivation using a metabolomic biomarker-A machine learning approach.

Sleep deprivation enhances risk for serious injury and fatality on the roads and in workplaces. To facilitate future management of these risks through advanced detection, we developed and validated a metabolomic biomarker of sleep deprivation in healthy, young participants, across three experiments. Bi-hourly plasma samples from 2 × 40-hour extended wake protocols (for train/test models) and 1 × 40-hour protocol with an 8-hour overnight sleep interval were analyzed by untargeted liquid chromatography-mass spectrometry. Using a knowledge-based machine learning approach, five consistently important variables were used to build predictive models. Sleep deprivation (24 to 38 hours awake) was predicted accurately in classification models [versus well-rested (0 to 16 hours)] (accuracy = 94.7%/AUC 99.2%, 79.3%/AUC 89.1%) and to a lesser extent in regression (R2 = 86.1 and 47.8%) models for within- and between-participant models, respectively. Metabolites were identified for replicability/future deployment. This approach for detecting acute sleep deprivation offers potential to reduce accidents through "fitness for duty" or "post-accident analysis" assessments.

Association of Obstructive Sleep Apnea with Post-Acute Sequelae of SARS-CoV-2 Infection.

BACKGROUND: Obstructive sleep apnea is associated with COVID-19 infection. Less clear is whether obstructive sleep apnea is a risk factor for the development of post-acute sequelae of SARS-CoV-2 infection (PASC). STUDY DESIGN: Cross-sectional survey of a general population of 24,803 US adults to determine the association of obstructive sleep apnea with PASC. RESULTS: COVID-19 infection occurred in 10,324 (41.6%) participants. Prevalence of persistent (>3 months post infection) putative PASC-related physical and mental health symptoms ranged from 6.5% (peripheral edema) to 19.6% (nervous/anxious). In logistic regression models, obstructive sleep apnea was associated with all putative PASC-related symptoms with the highest adjusted odds ratios being fever (2.053) and nervous/anxious (1.939). In 4 logistic regression models of overall PASC derived from elastic net regression, obstructive sleep apnea was associated with PASC (range of adjusted odds ratios: 1.934-2.071); this association was mitigated in those with treated obstructive sleep apnea. In the best fitting overall model requiring ≥3 symptoms, PASC prevalence was 21.9%. CONCLUSION: In a general population sample, obstructive sleep apnea is associated with the development of PASC-related symptoms and a global definition of PASC. Treated obstructive sleep apnea mitigates the latter risk. The presence of 3 or more PASC symptoms may be useful in identifying cases and for future research.

Subjective awareness of sleepiness while driving in younger and older adults.

Understanding whether drivers can accurately assess sleepiness is essential for educational campaigns advising drivers to stop driving when feeling sleepy. However, few studies have examined this in real-world driving environments, particularly among older drivers who comprise a large proportion of all road users. To examine the accuracy of subjective sleepiness ratings in predicting subsequent driving impairment and physiological drowsiness, 16 younger (21-33 years) and 17 older (50-65 years) adults drove an instrumented vehicle for 2 h on closed loop under two conditions: well-rested and 29 h sleep deprivation. Sleepiness ratings (Karolinska Sleepiness Scale, Likelihood of Falling Asleep scale, Sleepiness Symptoms Questionnaire) were obtained every 15min, alongside lane deviations, near crash events, and ocular indices of drowsiness. All subjective sleepiness measures increased with sleep deprivation for both age groups (p < 0.013). While most subjective sleepiness ratings significantly predicted driving impairment and drowsiness in younger adults (OR: 1.7-15.6, p < 0.02), this was only apparent for KSS, likelihood of falling asleep, and "difficulty staying in the lane for the older adults" (OR: 2.76-2.86, p = 0.02). This may be due to an altered perception of sleepiness in older adults, or due to lowered objective signs of impairment in the older group. Our data suggest that (i) younger and older drivers are aware of sleepiness; (ii) the best subjective scale may differ across age groups; and (iii) future research should expand on the best subjective measures to inform of crash risk in older adults to inform tailored educational road safety campaigns on signs of sleepiness.

Sleep and mental health among unpaid caregivers of children, adults, and both: United States, 2022.

OBJECTIVES: We sought to characterize sleep and mental health, and their relationship, among unpaid caregivers. METHODS: During March through August 2022, four waves of cross-sectional surveys were administered to US adults using demographic quota sampling and weighting to improve representativeness of the US adult population. RESULTS: Among 19,767 respondents, 6260 (31.7%) identified as serving one or more unpaid caregiving roles. Compared to people without caregiving roles, caregivers more commonly reported sleep duration outside the healthy range (7-9 hours), insomnia symptoms, diagnosed sleep disorders, and more commonly screened positive for anxiety, depression, and burnout symptoms. Multivariable analyses adjusted for demographics characteristics revealed unpaid caregivers had several-fold elevated odds of adverse mental health symptoms; associations were attenuated but remained significant after adjusting for impaired and nonoptimal sleep. CONCLUSIONS: Both sleep and mental health challenges are disproportionately experienced by and commonly co-occur among unpaid caregivers, especially those who care for both children and adults. These populations, which serve critical societal roles, may benefit from enhanced support services to address sleep and mental health.

A pilot study of light exposure as a countermeasure for menstrual phase-dependent neurobehavioral performance impairment in women.

OBJECTIVE: To examine effects of menstrual phase and nighttime light exposure on subjective sleepiness and auditory Psychomotor Vigilance Task performance. METHODS: Twenty-nine premenopausal women (12 =Follicular; 17 =Luteal) completed a 6.5-hour nighttime monochromatic light exposure with varying wavelengths (420-620 nm) and irradiances (1.03-14.12 µW/cm2). Subjective sleepiness, reaction time, and attentional lapses were compared between menstrual phases in women with minimal (<33%) or substantial (≥33%) light-induced melatonin suppression. RESULTS: When melatonin was not suppressed, women in the follicular phase had significantly worse reaction time (mean difference=145.1 ms, 95% CI 51.8-238.3, p < .001, Cohen's D=1.9) and lapses (mean difference=12.9 lapses, 95% CI 4.37-21.41, p < .001, Cohen's D=1.7) compared to women in the luteal phase. When melatonin was suppressed, women in the follicular phase had significantly better reaction time (mean difference=152.1 ms, 95% CI 43.88-260.3, p < .001, Cohen's D=1.7) and lapses (mean difference=12.3 lapses, 95% CI 1.14-25.6, p < .01, Cohen's D=1.6) compared to when melatonin was not suppressed, such that their performance was not different (p > .9) from women in the luteal phase. Subjective sleepiness did not differ by menstrual phase (mean difference=0.6, p > .08) or melatonin suppression (mean difference=0.2, p > .4). CONCLUSIONS: Nighttime light exposure sufficient to suppress melatonin can also mitigate neurobehavioral performance deficits associated with the follicular phase. Despite the relatively small sample size, these data suggest that nighttime light may be a valuable strategy to help reduce errors and accidents in female shift workers.

Circadian adaptation to night shift work is associated with higher REM sleep duration.

OBJECTIVE: To investigate the influence of the degree of circadian adaptation to night work on sleep architecture following night shift. METHODS: Thirty four night workers (11 females; 33.8 ± 10.1years) completed a simulated night shift following 2-7 typical night shifts. Participants completed a laboratory-based simulated night shift (21:00-07:00 hours), followed by a recovery sleep opportunity (∼09:00-17:00 hours), recorded using polysomnography. Urinary 6-sulphatoxymelatonin (aMT6s) rhythm acrophase was used as a marker of circadian phase. Sleep duration and architecture were compared between individuals with aMT6s acrophase before (unadapted group, n = 22) or after (partially adapted group, n = 12) bedtime. RESULTS: Bedtime occurred on average 2.16 hours before aMT6s acrophase in the partially adapted group and 3.91 hours after acrophase in the unadapted group. The partially adapted group had more sleep during the week before the simulated night than the unadapted group (6.47 ± 1.02 vs. 5.26 ± 1.48 hours, p = .02). After the simulated night shift, both groups had similar total sleep time (partially adapted: 6.68 ± 0.80 hours, unadapted: 6.63 ± 0.88 hours, p > .05). The partially adapted group had longer total rapid eye movement sleep duration than the unadapted group (106.79 ± 32.05 minutes vs. 77.90 ± 28.86 minutes, p = .01). After 5-hours, rapid eye movement sleep accumulation was higher in the partially adapted compared to the unadapted group (p = .02). Sleep latency and other stages were not affected by circadian adaptation. DISCUSSION: Partial circadian adaptation to night shift was associated with longer rapid eye movement sleep duration during daytime sleep, highlighting the influence of entrainment between the sleep-wake cycle and the circadian pacemaker in night workers. The findings have important implications for sleep and subsequent alertness associated with shift work.

The organization of sleep-wake patterns around daily schedules in college students.

Time is a zero-sum game, and consequently, sleep is often sacrificed for waking activities. For college students, daily activities, comprised of scheduled classes, work, study, social and other extracurricular events, are major contributors to insufficient and poor-quality sleep. We investigated the impact of daily schedules on sleep-wake timing in 223 undergraduate students (age: 18-27 years, 37% females) from a United States (U.S.) university, monitored for approximately 30 days. Sleep-wake timing and daily recorded activities (attendance at academic, studying, exercise-based and/or extracurricular activities) were captured by a twice-daily internet-based diary. Wrist-worn actigraphy was conducted to confirm sleep-wake timing. Linear mixed models were used to quantify associations between daily schedule and sleep-wake timing at between-person and within-person levels. Later schedule start time predicted later sleep onset (between and within: p<.001), longer sleep duration on the previous night (within: p<.001), and later wake time (between and within: p<.001). Later schedule end time predicted later sleep onset (between: p<.05, within: p<.001) and shorter sleep duration that night (within: p<.001). For every 1 hour that recorded activities extended beyond 10pm, sleep onset was delayed by 15 minutes at the within-person level and 45 minutes at the between-person level, and sleep duration was shortened by 5 and 23 minutes, respectively. Increased daily documented total activity time predicted earlier wake (between and within: p<.001), later sleep onset that night (within: p<.05), and shorter sleep duration (within: p<.001). These results indicate that daily schedules are an important factor in shaping sleep timing and duration in college students.

The importance of sleep regularity: a consensus statement of the National Sleep Foundation sleep timing and variability panel.

OBJECTIVE: To develop and present consensus findings of the National Sleep Foundation sleep timing and variability panel regarding the impact of sleep timing variability on health and performance. METHODS: The National Sleep Foundation assembled a panel of sleep and circadian experts to evaluate the scientific evidence and conduct a formal consensus and voting procedure. A systematic literature review was conducted using the NIH National Library of Medicine PubMed database, and panelists voted on the appropriateness of 3 questions using a modified Delphi RAND/UCLA Appropriateness Method with 2 rounds of voting. RESULTS: The literature search and panel review identified 63 full text publications to inform consensus voting. Panelists achieved consensus on each question: (1) is daily regularity in sleep timing important for (a) health or (b) performance? and (2) when sleep is of insufficient duration during the week (or work days), is catch-up sleep on weekends (or non-work days) important for health? Based on the evidence currently available, panelists agreed to an affirmative response to all 3 questions. CONCLUSIONS: Consistency of sleep onset and offset timing is important for health, safety, and performance. Nonetheless, when insufficient sleep is obtained during the week/work days, weekend/non-work day catch-up sleep may be beneficial.