Life onboard a submarine: Sleep, fatigue, and lifestyle behaviors of sailors on a circadian-aligned watchstanding schedule.

This study characterizes, for the first time, the lives of U.S. Navy submariners engaged in normal, sea-based operations while following a circadian-aligned 24-h watchstanding schedule. Fifty-eight submarine crewmembers provided objective (actigraphy) and subjective (questionnaires) sleep data, and information about mood and lifestyle behaviors during 30 days underway. Projected performance scores and estimated circadian phase times were also calculated from actigraphy-based sleep/wake data. Submariners' objective (6.62 ± 0.94 h; mean ± SD) and subjective (5.90 ± 1.38 h) daily sleep quantities while underway were largely comparable to the sleep reportedly received by Sailors across other Navy platforms and watchstanding schedules. Additionally, submariners' actigraphy-predicted circadian phases shifted progressively toward better alignment with watchstanding schedules across time. Nevertheless, subjective sleep quality was low, submariners engaged in unfavorable lifestyle behaviors (lack of regular meals and exercise), and participants reported decreased mood at the completion of their underway time. Recommendations for countermeasure development are provided.

Advancing a U.S. navy shipboard infrastructure for sleep monitoring with wearable technology.

Development of fatigue management solutions is critical to U.S. Navy populations. This study explored the operational feasibility and acceptability of commercial wearable devices (Oura Ring and ReadiBand) in a warship environment with 845 Sailors across five ship cohorts during at-sea operations ranging from 10 to 31 days. Participants were required to wear both devices and check-in daily with research staff. Both devices functioned as designed in the environment and reliably collected sleep-wake data. Over 10,000 person-days at-sea, overall prevalence of Oura and ReadiBand use was 69% and 71%, respectively. Individual use rates were 71 ± 38% of days underway for Oura and 59 ± 34% for ReadiBand. Analysis of individual factors showed increasing device use and less device interference with age, and more men than women found the devices comfortable. This study provides initial support that commercial wearables can contribute to infrastructures for operational fatigue management in naval environments.

Daytime Sleep-Tracking Performance of Four Commercial Wearable Devices During Unrestricted Home Sleep.

Purpose: Previous studies have found that many commercial wearable devices can accurately track sleep-wake patterns in laboratory or home settings. However, nearly all previous studies tested devices under conditions with fixed time in bed (TIB) and during nighttime sleep episodes only. Despite its relevance to shift workers and others with irregular sleep schedules, it is largely unknown how devices track daytime sleep. Therefore, we tested the sleep-tracking performance of four commercial wearable devices during unrestricted home daytime sleep. Participants and Methods: Participants were 16 healthy young adults (6 men, 10 women; 26.6 ± 4.6 years, mean ± SD) with habitual daytime sleep schedules. Participants slept at home for 1 week under unrestricted conditions (ie, self-selecting TIB) using a set of four commercial wearable devices and completed reference sleep logs. Wearables included the Fatigue Science ReadiBand, Fitbit Inspire HR, Oura Ring, and Polar Vantage V Titan. Daytime sleep episode TIB biases and frequencies of missed and false-positive daytime sleep episodes were examined. Results: TIB bias was low in general for all devices on most daytime sleep episodes, but some exhibited large biases (eg, >1 h). Total missed daytime sleep episodes were as follows: Fatigue Science: 3.6%; Fitbit: 4.8%; Oura: 6.0%; Polar: 37.3%. Missed episodes occurred most often when TIB was short (eg, naps <4 h). Conclusion: When daytime sleep episodes were recorded, the devices generally exhibited similar performance for tracking TIB (ie, most episodes had low bias). However, the devices failed to detect some daytime episodes, which occurred most often when TIB was short, but varied across devices (especially Polar, which missed over one-third of episodes). Findings suggest that accurate daytime sleep tracking is largely achievable with commercial wearable devices. However, performance differences for missed recordings suggest that some devices vary in reliability (especially for naps), but improvements could likely be made with changes to algorithm sensitivities.

Caffeine consumption and sleep in a submarine environment: An observational study.

Submariners face many environmental and operational challenges to maintaining good sleep, including suboptimal lighting, shift work, and frequent interruptions. Anecdotally, many Sailors consume caffeine to alleviate the effects of poor sleep on alertness, mood, and performance; however, caffeine itself may also degrade sleep quantity and/or quality. This study provides the first exploration of the potential relationship between caffeine use and sleep onboard submarines. Objective measures (wrist actigraphy, available from 45 participants), self-report sleep metrics, and self-reported caffeine consumption were collected from 58 US Navy Sailors before and during a routine submarine underway at sea lasting 30 days. Contrary to expectations, less caffeine was reportedly consumed at sea (232.8 ± 241.1 mg) than on land prior to the underway (M = 284.4 ± 251.7 mg; X2 (1) = 7.43, p = 0.006), positive rather than negative relationships were observed between caffeine consumption and sleep efficiency (F = 6.11, p = 0.02), and negative relationships were observed between caffeine consumption and wake after sleep onset (F = 9.36, p = 0.004) and sleep fragmentation (F = 24.73, p < 0.0001). However, in contrast, higher caffeine consumption was also negatively related to self-reported sleep duration while at sea (F = 4.73, p = 0.03). This observational study is the first to measure relationships between caffeine consumption and sleep quantity and/or quality in a submarine environment. We propose that the unique submarine environment and the unique caffeine consumption patterns of submariners should be considered in the development of potential countermeasures for sleepiness.

Sleep, Immune Function, and Vaccinations in Military Personnel: Challenges and Future Directions.

The U.S. military invests substantial resources to vaccinate all personnel, including recruits, against operationally important infectious disease threats. However, research suggests that vaccine immune response and, therefore, vaccine effectiveness may be inadvertently reduced because of chronic and/or acute sleep deficiency experienced by recipients around the time of vaccination. Because sleep deficiency is expected and even necessary in deployed and training contexts, research investigations of the impacts of sleep and related physiological systems such as circadian rhythms on vaccine effectiveness in military settings are needed. Specifically, research should be aimed at understanding the effects of sleep deficiency, as well as vaccine administration schedules, on response to vaccination and clinical protection. Furthermore, knowledge gaps among military medical leadership on sleep, vaccines, and immune health should be assessed. This area of research may benefit the health and readiness of service members while also decreasing health care utilization and associated costs from illness.

The bi-directional relationship between post-traumatic stress disorder and obstructive sleep apnea and/or insomnia in a large U.S. military cohort.

OBJECTIVES: Determine if a bi-directional relationship exists between the development of sleep disorders (obstructive sleep apnea [OSA] and/or insomnia) and existing post-traumatic stress disorder (PTSD), and vice versa; and examine military-related factors associated with these potential relationships. DESIGN: Longitudinal analyses of a prospective representative U.S. military cohort. PARTICIPANTS: Millennium Cohort Study responders in 2011-2013 (Time 1 [T1]) and 2014-2016 (Time 2 [T2]) without insomnia or OSA at T1 (N = 65,915) or without PTSD at T1 (N = 71,256). MEASUREMENTS: Provider-diagnosed OSA, self-reported items for insomnia, provider-diagnosed PTSD, and current PTSD symptoms were assessed at T1 and T2. Adjusted multivariable models identified military-related factors associated with new-onset PTSD in those with OSA and/or insomnia, and vice versa. RESULTS: Self-reported history of provider-diagnosed PTSD without current symptoms at T1 was associated with new-onset OSA only and comorbid OSA/insomnia at T2, while current PTSD symptoms and/or diagnosis was associated with new-onset insomnia only. OSA/insomnia at T1 was consistently associated with newly reported PTSD symptoms or diagnosis except that insomnia only was not associated with newly reported provider-diagnosed PTSD. Military-related risk factors significantly associated with the bi-directional relationship for new-onset PTSD or OSA/insomnia included prior deployment with higher combat exposure and recent separation from the military; being an officer was protective for both outcomes. CONCLUSIONS: In this large military cohort, findings suggest that PTSD and OSA and/or insomnia are bi-directionally predictive for their development, which was sometimes revealed by health care utilization. Relevant military-related risk factors should be considered in efforts to prevent or treat PTSD and/or sleep disorders.

Performance of Four Commercial Wearable Sleep-Tracking Devices Tested Under Unrestricted Conditions at Home in Healthy Young Adults.

Purpose: Commercial wearable sleep-tracking devices are growing in popularity and in recent studies have performed well against gold standard sleep measurement techniques. However, most studies were conducted in controlled laboratory conditions. We therefore aimed to test the performance of devices under naturalistic unrestricted home sleep conditions. Participants and Methods: Healthy young adults (n = 21; 12 women, 9 men; 29.0 ± 5.0 years, mean ± SD) slept at home under unrestricted conditions for 1 week using a set of commercial wearable sleep-tracking devices and completed daily sleep diaries. Devices included the Fatigue Science Readiband, Fitbit Inspire HR, Oura ring, and Polar Vantage V Titan. Participants also wore a research-grade actigraphy watch (Philips Respironics Actiwatch 2) for comparison. To assess performance, all devices were compared with a high performing mobile sleep electroencephalography headband device (Dreem 2). Analyses included epoch-by-epoch and sleep summary agreement comparisons. Results: Devices accurately tracked sleep-wake summary metrics (ie, time in bed, total sleep time, sleep efficiency, sleep latency, wake after sleep onset) on most nights but performed best on nights with higher sleep efficiency. Epoch-by-epoch sensitivity (for sleep) and specificity (for wake), respectively, were as follows: Actiwatch (0.95, 0.35), Fatigue Science (0.94, 0.40), Fitbit (0.93, 0.45), Oura (0.94, 0.41), and Polar (0.96, 0.35). Sleep stage-tracking performance was mixed, with high variability. Conclusion: As in previous studies, all devices were better at detecting sleep than wake, and most devices compared favorably to actigraphy in wake detection. Devices performed best on nights with more consolidated sleep patterns. Unrestricted sleep TIB differences were accurately tracked on most nights. High variability in sleep stage-tracking performance suggests that these devices, in their current form, are still best utilized for tracking sleep-wake outcomes and not sleep stages. Most commercial wearables exhibited promising performance for tracking sleep-wake in real-world conditions, further supporting their consideration as an alternative to actigraphy.

Prevalence and predictors of insomnia and sleep medication use in a large tri-service US military sample.

OBJECTIVE: The presence of insomnia in the general military population is not well known. This study aimed to determine the prevalence of probable clinical insomnia and identify factors leading to new-onset insomnia and/or sleep medication use in a large military population. DESIGN: Cross-sectional and longitudinal analyses of a prospective cohort study. PARTICIPANTS: A tri-service US military and veteran cohort (sample range 99,383-137,114). MEASUREMENTS: Participants were surveyed in 2013 (Time 1 [T1]) and 2016 (Time 2 [T2]) using the clinically validated Insomnia Severity Index. The prevalence of insomnia and sleep medication use was quantified at both times. Multivariable models identified military factors associated with new-onset insomnia and/or sleep medication use while adjusting for covariates. RESULTS: The prevalence of insomnia at T1 and T2 was 16.3% and 11.2%, respectively. New-onset insomnia at T2 was reported by 6.0% of participants screening negative at T1; risk factors included Army service, combat deployment experience, and separation from military service. The prevalence of sleep medication use at T1 and T2 was 23.1% and 25.1%, respectively. Sleep medication use at T2 was newly-reported by 17.1% of participants not reporting sleep medication use at T1; risk factors included number of deployments and having a healthcare occupation. CONCLUSIONS: The prevalence of probable clinical insomnia in this large general military population is within the range of previous reports in military and civilian populations. Certain military factors that predict new-onset insomnia and/or sleep medication use should be considered when designing and implementing sleep interventions in military populations.

Longitudinal associations of military-related factors on self-reported sleep among U.S. service members.

STUDY OBJECTIVES: Sleep loss is common in the military, which can negatively affect health and readiness; however, it is largely unknown how sleep varies over a military career. This study sought to examine the relationships between military-related factors and the new onset and reoccurrence of short sleep duration and insomnia symptoms. METHODS: Millennium Cohort Study data were used to track U.S. military service members over time to examine longitudinal changes in sleep. Outcomes were self-reported average sleep duration (categorized as ≤5 h, 6 h, or 7-9 h [recommended]) and/or insomnia symptoms (having trouble falling or staying asleep). Associations between military-related factors and the new onset and reoccurrence of these sleep characteristics were determined, after controlling for multiple health and behavioral factors. RESULTS: Military-related factors consistently associated with an increased risk for new onset and/or reoccurrence of short sleep duration and insomnia symptoms included active duty component, Army or Marine Corps service, combat deployment, and longer than average deployment lengths. Military officers and noncombat deployers had decreased risk for either sleep characteristic. Time-in-service and separation from the military were complex factors; they lowered risk for ≤5 h sleep but increased risk for insomnia symptoms. CONCLUSIONS: Various military-related factors contribute to risk of short sleep duration and/or insomnia symptoms over time, although some factors affect these sleep characteristics differently. Also, even when these sleep characteristics remit, some military personnel have an increased risk of reoccurrence. Efforts to improve sleep prioritization and implement interventions targeting at-risk military populations, behaviors, and other significant factors are warranted.

Performance of seven consumer sleep-tracking devices compared with polysomnography.

STUDY OBJECTIVES: Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG). METHODS: In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three nonwearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG. RESULTS: Most devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18-0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep. CONCLUSIONS: Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility.

Validation of Zulu Watch against Polysomnography and Actigraphy for On-Wrist Sleep-Wake Determination and Sleep-Depth Estimation.

Traditional measures of sleep or commercial wearables may not be ideal for use in operational environments. The Zulu watch is a commercial sleep-tracking device designed to collect longitudinal sleep data in real-world environments. Laboratory testing is the initial step towards validating a device for real-world sleep evaluation; therefore, the Zulu watch was tested against the gold-standard polysomnography (PSG) and actigraphy. Eight healthy, young adult participants wore a Zulu watch and Actiwatch simultaneously over a 3-day laboratory PSG sleep study. The accuracy, sensitivity, and specificity of epoch-by-epoch data were tested against PSG and actigraphy. Sleep summary statistics were compared using paired samples t-tests, intraclass correlation coefficients, and Bland-Altman plots. Compared with either PSG or actigraphy, both the accuracy and sensitivity for Zulu watch sleep-wake determination were >90%, while the specificity was low (~26% vs. PSG, ~33% vs. actigraphy). The accuracy for sleep scoring vs. PSG was ~87% for interrupted sleep, ~52% for light sleep, and ~49% for deep sleep. The Zulu watch showed mixed results but performed well in determining total sleep time, sleep efficiency, sleep onset, and final awakening in healthy adults compared with PSG or actigraphy. The next step will be to test the Zulu watch's ability to evaluate sleep in industrial operations.

Utilizing the National Basketball Association's COVID-19 restart "bubble" to uncover the impact of travel and circadian disruption on athletic performance.

On March 11th, 2020, the National Basketball Association (NBA) paused its season after ~ 64 games due to the Coronavirus 2019 (COVID-19) outbreak, only to resume ~ 5 months later with the top 22 teams isolated together (known as the "bubble") in Orlando, Florida to play eight games each as an end to the regular season. This restart, with no new travel by teams, provided a natural experiment whereby the impact of travel and home-court advantage could be systematically examined. We show here that in the pre-COVID-19 regular season, traveling across time zones reduces winning percentage, team shooting accuracy, and turnover percentage, whereas traveling in general reduces offensive rebounding and increases the number of points the opposing (home) team scores. Moreover, we demonstrate that competition in a scenario where no teams travel (restart bubble) reduces the typical effects of travel and home-court advantage on winning percentage, shooting accuracy, and rebounding. Thus, home-court advantage in professional basketball appears to be linked with the away team's impaired shooting accuracy (i.e., movement precision) and rebounding, which may be separately influenced by either circadian disruption or the general effect of travel, as these differences manifest differently when teams travel within or across multiple time zones.

Prediction of individual differences in circadian adaptation to night work among older adults: application of a mathematical model using individual sleep-wake and light exposure data.

Circadian misalignment remains a distinct challenge for night shift workers. Variability in individual sleep-wake/light-dark patterns might contribute to individual differences in circadian alignment in night shift workers. In this simulation study, we compared the predicted phase shift from a mathematical model of the effect of light on the human circadian pacemaker to the observed melatonin phase shift among individuals who completed one of four interventions during simulated night shift work. Two inputs to the model were used to simulate circadian phase: sleep-wake/light-dark patterns measured from a wrist monitor (Simulation 1) and sleep-wake/light-dark patterns measured from a wrist monitor enhanced by known light levels measured at the level of the eye during simulated night shifts (Simulation 2). The estimated phase shift from the model was within 2 hours of the observed phase shift in ~80% of night shift workers for both simulations; none of the model-predicted phase shifts was more than ~3 hours from the observed phase shift. Overall, the root-mean-square error between observed and predicted phase shifts was better for Simulation 1. The light input from the wrist monitor informed by actual light level measured at the eye performed better in the sub-group exposed to bright light during their night shifts. The findings from this simulation study suggest that using a mathematical model combined with sleep-wake and light exposure data from a wrist monitor can facilitate the design of shift work schedules to enhance circadian alignment, which is expected to improve sleep, alertness, and performance.

Scheduled afternoon-evening sleep leads to better night shift performance in older adults.

OBJECTIVES: This study investigated whether an intervention designed to reduce homeostatic sleep pressure would improve night shift performance and alertness in older adults. METHODS: Non-shift workers aged 57.9±4.6 (mean±SD) worked four day (07:00-15:00) and four night shifts (23:00-07:00). Two intervention groups were instructed to remain awake until ~13:00 after each night shift: the sleep timing group (ST; n=9) was instructed to spend 8 hours in bed attempting sleep, and the sleep ad-lib group (n=9) was given no further sleep instructions. A control group (n=9) from our previous study was not given any sleep instructions. Hourly Karolinska Sleepiness Scales and Psychomotor Vigilance Tasks assessed subjective sleepiness and performance. RESULTS: The ST group maintained their day shift sleep durations on night shifts, whereas the control group slept less. The ST group were able to maintain stable performance and alertness across the initial part of the night shift, while the control group's alertness and performance declined across the entire night. Wake duration before a night shift negatively impacted sustained attention and self-reported sleepiness but not reaction time, whereas sleep duration before a night shift affected reaction time and ability to sustain attention but not self-reported sleepiness. CONCLUSIONS: A behavioural change under the control of the individual worker, spending 8 hours in bed and waking close to the start of the night shift, allowed participants to acquire more sleep and improved performance on the night shift in older adults. Both sleep duration and timing are important factors for night shift performance and self-reported sleepiness.

Unrestricted evening use of light-emitting tablet computers delays self-selected bedtime and disrupts circadian timing and alertness.

Consumer electronic devices play an important role in modern society. Technological advancements continually improve their utility and portability, making possible the near-constant use of electronic devices during waking hours. For most people, this includes the evening hours close to bedtime. Evening exposure to light-emitting (LE) devices can adversely affect circadian timing, sleep, and alertness, even when participants maintain a fixed 8-hour sleep episode in darkness and the duration of evening LE-device exposure is limited. Here, we tested the effects of evening LE-device use when participants were allowed to self-select their bedtimes, with wake times fixed as on work/school days. Nine healthy adults (3 women, 25.7 ± 3.0 years) participated in a randomized and counterbalanced study comparing five consecutive evenings of unrestricted LE-tablet computer use versus evenings reading from printed materials. On evenings when using LE-tablets, participants' self-selected bedtimes were on average half an hour later (22:03 ± 00:48 vs. 21:32 ± 00:27 h; P = 0.030), and they showed suppressed melatonin levels (54.17 ± 18.00 vs. 9.75 ± 22.75%; P < 0.001), delayed timing of melatonin secretion onset (20:23 ± 01:06 vs. 19:35 ± 00:59 h; P < 0.001), and later sleep onset (22:25 ± 00:54 vs. 21:54 ± 00:25 h; P = 0.041). When using LE-tablets, participants rated themselves as less sleepy in the evenings (P = 0.030) and less alert in the first hour after awakening on the following mornings (P < 0.001). These findings demonstrate that evening use of LE-tablets can induce delays in self-selected bedtimes, suppress melatonin secretion, and impair next-morning alertness, which may impact the health, performance, and safety of users.

Circadian Entrainment to the Natural Light-Dark Cycle across Seasons and the Weekend.

Reduced exposure to daytime sunlight and increased exposure to electrical lighting at night leads to late circadian and sleep timing [1-3]. We have previously shown that exposure to a natural summer 14 hr 40 min:9 hr 20 min light-dark cycle entrains the human circadian clock to solar time, such that the internal biological night begins near sunset and ends near sunrise [1]. Here we show that the beginning of the biological night and sleep occur earlier after a week's exposure to a natural winter 9 hr 20 min:14 hr 40 min light-dark cycle as compared to the modern electrical lighting environment. Further, we find that the human circadian clock is sensitive to seasonal changes in the natural light-dark cycle, showing an expansion of the biological night in winter compared to summer, akin to that seen in non-humans [4-8]. We also show that circadian and sleep timing occur earlier after spending a weekend camping in a summer 14 hr 39 min:9 hr 21 min natural light-dark cycle compared to a typical weekend in the modern environment. Weekend exposure to natural light was sufficient to achieve ∼69% of the shift in circadian timing we previously reported after a week's exposure to natural light [1]. These findings provide evidence that the human circadian clock adapts to seasonal changes in the natural light-dark cycle and is timed later in the modern environment in both winter and summer. Further, we demonstrate that earlier circadian timing can be rapidly achieved through natural light exposure during a weekend spent camping.

Scheduled evening sleep and enhanced lighting improve adaptation to night shift work in older adults.

OBJECTIVES: We tested whether a sleep and circadian-based treatment shown to improve circadian adaptation to night shifts and attenuate negative effects on alertness, performance and sleep in young adults would also be effective in older adults. METHODS: We assessed subjective alertness, sustained attention (psychomotor vigilance task, PVT), sleep duration (actigraphy) and circadian timing (salivary dim-light melatonin onset, DLMO) in 18 older adults (57.2±3.8 years; mean±SD) in a simulated shift work protocol. 4 day shifts were followed by 3 night shifts in the laboratory. Participants slept at home and were randomised to either the treatment group (scheduled evening sleep and enhanced lighting during the latter half of night shifts) or control group (ad-lib sleep and typical lighting during night shifts). RESULTS: Compared with day shifts, alertness and sustained attention declined on the first night shift in both groups, and was worse in the latter half of the night shifts. Alertness and attention improved on nights 2 and 3 for the treatment group but remained lower for the control group. Sleep duration in the treatment group remained similar to baseline (6-7 hours) following night shifts, but was shorter (3-5 hours) following night shifts in the control group. Treatment group circadian timing advanced by 169.3±16.1 min (mean±SEM) but did not shift (-9.7±9.9 min) in the control group. CONCLUSIONS: The combined treatment of scheduled evening sleep and enhanced lighting increased sleep duration and partially aligned circadian phase with sleep and work timing, resulting in improved night shift alertness and performance.

Aging and Circadian Rhythms.

Aging is associated with numerous changes, including changes in sleep timing, duration, and quality. The circadian timing system interacts with a sleep-wake homeostatic system to regulate human sleep, including sleep timing and structure. This article reviews key features of the human circadian timing system, age-related changes in the circadian timing system, and how those changes may contribute to the observed alterations in sleep.

Effects of caffeine on the human circadian clock in vivo and in vitro.

Caffeine's wakefulness-promoting and sleep-disrupting effects are well established, yet whether caffeine affects human circadian timing is unknown. We show that evening caffeine consumption delays the human circadian melatonin rhythm in vivo and that chronic application of caffeine lengthens the circadian period of molecular oscillations in vitro, primarily with an adenosine receptor/cyclic adenosine monophosphate (AMP)-dependent mechanism. In a double-blind, placebo-controlled, ~49-day long, within-subject study, we found that consumption of a caffeine dose equivalent to that in a double espresso 3 hours before habitual bedtime induced a ~40-min phase delay of the circadian melatonin rhythm in humans. This magnitude of delay was nearly half of the magnitude of the phase-delaying response induced by exposure to 3 hours of evening bright light (~3000 lux, ~7 W/m(2)) that began at habitual bedtime. Furthermore, using human osteosarcoma U2OS cells expressing clock gene luciferase reporters, we found a dose-dependent lengthening of the circadian period by caffeine. By pharmacological dissection and small interfering RNA knockdown, we established that perturbation of adenosine receptor signaling, but not ryanodine receptor or phosphodiesterase activity, was sufficient to account for caffeine's effects on cellular timekeeping. We also used a cyclic AMP biosensor to show that caffeine increased cyclic AMP levels, indicating that caffeine influenced a core component of the cellular circadian clock. Together, our findings demonstrate that caffeine influences human circadian timing, showing one way that the world's most widely consumed psychoactive drug affects human physiology.

Age-related changes in slow wave activity rise time and NREM sleep EEG with and without zolpidem in healthy young and older adults.

OBJECTIVE: Whether there are age-related changes in slow wave activity (SWA) rise time, a marker of homeostatic sleep drive, is unknown. Additionally, although sleep medication use is highest among older adults, the quantitative electroencephalographic (EEG) profile of the most commonly prescribed sleep medication, zolpidem, in older adults is also unknown. We therefore quantified age-related and regional brain differences in sleep EEG with and without zolpidem. METHODS: Thirteen healthy young adults aged 21.9 ± 2.2 years and 12 healthy older adults aged 67.4 ± 4.2 years participated in a randomized, double-blind, within-subject study that compared placebo to 5 mg zolpidem. RESULTS: Older adults showed a smaller rise in SWA and zolpidem increased age-related differences in SWA rise time such that age differences were observed earlier after latency to persistent sleep. Age-related differences in EEG power differed by brain region. Older, but not young, adults showed zolpidem-dependent reductions in theta and alpha frequencies. Zolpidem decreased stage 1 in older adults and did not alter other age-related sleep architecture parameters. CONCLUSIONS: SWA findings provide additional support for reduced homeostatic sleep drive or reduced ability to respond to sleep drive with age. Consequences of reduced power in theta and alpha frequencies in older adults remain to be elucidated.