Interventions to minimize jet lag after westward and eastward flight

Air travel across several time zones, i.e., transmeridian flight, causes negative effects—some of which occur during flight and some of which occur in the days after flight. Anecdotally, these effects are often referred to collectively as jet lag, but they are actually two separate phenomena—travel fatigue and jet lag—each with their own causes and consequences (Waterhouse et al., 2004). Travel fatigue refers to a collection of symptoms that occur during or immediately after long flights. These symptoms include fatigue, disorientation, and headache (Waterhouse et al., 2004)—primarily caused by the sleep loss, dehydration, hypoxia, and discomfort associated with being in an aircraft with confined space, recline-restricted seats, low air pressure, low humidity, etc., for 8–14 h (Brown et al., 2001; Roach et al., 2018). In contrast, jet lag refers to a collection of symptoms that occur in the days after flight across three or more time zones. These symptoms include headache, irritability, daytime sleepiness, difficulty sleeping at night, poor mental and physical performance, and poor gastrointestinal function (Waterhouse et al., 2004)—primarily caused by the mismatch between the circadian system, or internal body clock, which is synchronized to time cues in the departure time zone, and the desired timing of sleep and wake, which are typically synchronized to time cues in the destination time zone. In August 2020, the Olympic Games will be held in Tokyo, Japan. Athletes will travel from all over the world to compete in the Games, and many will have to travel across several time zones. For example, athletes traveling to Japan from North America and Western Europe will face time zone changes of 8–11 h west and 6–8 h east, respectively. Some athletes will travel to Japan, or nearby countries, weeks before their events, while others will arrive in Japan in the days prior to competition. In either case, athletes will want to adjust to the new time zone as quickly as possible so that they can prepare well and/or compete at the highest level. The purpose of this manuscript is to discuss the causes and consequences of jet lag and to provide examples of how to use judiciously timed light exposure/avoidance and/or exogenous melatonin ingestion to adapt the circadian system to a new time zone after transmeridian flight. These guides could be applied by athletes competing in the Tokyo 2020 Olympic Games, but they could also be applied by athletes traveling to other countries for training or competition, or by non-athletes traveling for business or pleasure

Sleep duration is reduced in elite athletes following night-time competition.

This study examined the impact of competition on the sleep/wake behaviour of elite athletes. The sleep/wake behaviour of Australian Rules Football players was assessed with wrist activity monitors on the night immediately before, and the night immediately after, a day game and an evening game. The time of day that a game occurred had a marked influence on sleep/wake behaviour later that night. After the evening game, sleep onset was later, time in bed was shorter and total sleep obtained was less than after the day game. It is yet to be determined whether a reduction in sleep after evening games impairs recovery

The evidence that cyclic alternating pattern subtypes affect cognitive functioning is very weak

In their recent paper, Ferri et al. [1] examined the relationships between cognitive functioning and three subtypes of the cyclic alternating pattern (CAP) in non-REM sleep. They concluded that ‘‘CAP A1 subtypes are associated with higher [i.e., better] cognitive functioning, whereas CAP A3 subtypes are associated with lower [i.e., poorer] cognitive functioning” (p. 378). For the reasons summarised below, we contend that In their recent paper, Ferri et al. [1] examined the relationships between cognitive functioning and three subtypes of the cyclic alternating pattern (CAP) in non-REM sleep. They concluded that ‘‘CAP A1 subtypes are associated with higher [i.e., better] cognitive functioning, whereas CAP A3 subtypes are associated with lower [i.e., poorer] cognitive functioning” (p. 378). For the reasons summarised below, we contend that this conclusion is not warranted based on the data presented

The duration of light exposure in the morning and early-afternoon affects adaptation to night work

Introduction : The aim of the study was to examine how the tim-ing of daytime sleep in the dark, and thus the timing of daytime light exposure, affects circadian adaptation to a week of simulated night shifts. It was hypothesised that night work would delay the circadian system – and the size of the delay would increase as the duration of exposure to morning and early- afternoon light (MAL) decreased. Methods : So far, 43 adults (21F, 22M) have been randomly assigned to one of four conditions in a laboratory- based simulated shiftwork protocol. Each condition included 7 consecutive 8- h night shifts (23:00–07:00 hr). The only difference between conditions was in the timing of the 7- h sleep opportunities in breaks between shifts – morning (08:30–15:30 hr, shortest MAL), split#1 (08:30–13:30 hr & 19:30–21:30 hr, short MAL), split#2 (08:30–10:30 hr & 16:30–21:30 hr, long MAL), and afternoon/evening (14:30–21:30 hr, longest MAL). Circadian phase was assessed using salivary dim light mela-tonin onset (DLMO) on the nights immediately before and after the week of night work. Light intensity was 75 lux during night shifts, < 0.03 lux during sleep, < 10 lux during DLMO assessments, and 350 lux at other times. Results : The DLMO data were analysed using a mixed- design ANOVA with one within- subjects factor (time: pre/post) and one between- subjects factor (condition). There was a significant interaction (F = 10.6; df = 3,39; p < .0001) – the type and size of the phase shift dif-fered between the conditions, i.e., morning (delay = 5.06 ± 2.11 hr), split#1 (delay = 2.58 ± 2.46 hr), split#2 (delay = 1.30 ± 2.62 hr), and afternoon/evening (advance = 0.71 ± 2.84 hr). Discussion : These data indicate that the timing of daytime sleep, and thus the amount of exposure to morning and early- afternoon light (MAL), substantially affects the degree of circadian adaptation to a week of night work. In situations where a shiftworker wishes to maximise adaptation to night work, the most sleep should be taken in the morning. To minimise adaptation, sleep should occur in the later afternoon and evening

Feedback has a positive effect on cognitive function during total sleep deprivation if there is sufficient time for it to be effectively processed

This study examined whether the provision of feedback and the interval between successive stimuli interact to affect performance on a serial simple reaction time test during sleep deprivation. Sixteen participants (9 female, 7 male, aged 18–27 yr) completed four versions of the 5-min psychomotor vigilance task for a handheld personal digital assistant (PalmPVT) every 2 h during 28 h of sustained wakefulness. The four versions differed in terms of whether or not they provided feedback immediately after each response, and whether the inter-stimulus intervals (ISIs) were long (2–10 s) or short (1–5 s). Cognitive function was assessed using reciprocal response time and percentage of responses that were lapses (i.e., had a response time ≥ 500 ms). Data were analysed using repeated measures ANOVA with three within-subjects factors: test session, feedback, and ISI. For both measures, the only significant interaction was between feedback and ISI. Cognitive function was enhanced by feedback when the ISIs were long because it provided motivation. Cognitive function was not affected by feedback when the ISIs were short because there was insufficient time to both attend to the feedback and prepare for the subsequent stimulus

How well do pilots sleep during long-haul flights?

It is imperative that shiftworkers in safety-critical workplaces obtain sufficient sleep to operate effectively. This presents a challenge to long-haul airline pilots who are required to supplement normal bed sleep with sleep on-board an aircraft during flight. In the current study, the sleep/wake behaviour of 301 airline pilots operating long-haul flight patterns was monitored for at least 2 weeks using self-report sleep diaries and wrist activity monitors. The data indicate that sleep opportunities in on-board rest facilities during long-haul flights result in a similar amount of sleep, but only 70% as much recovery, as duration-matched bed sleeps. Statement of Relevance: This study indicates that in-flight sleep provides airline pilots with 70% as much restoration as duration-matched bed sleep. To increase the restoration provided by in-flight sleep, airlines could take measures to improve the quality, or increase the amount, of sleep obtained by pilots during flights

Mild to moderate sleep restriction does not affect the cortisol awakening response in healthy adult males

The cortisol awakening response (CAR) is a distinct rise in cortisol that occurs upon awakening that is thought to contribute to arousal, energy boosting, and anticipation. There is some evidence to suggest that inadequate sleep may alter the CAR, but the relationship between sleep duration and CAR has not been systematically examined. Healthy males (n = 111; age: 23.0 ± 3.6 yrs) spent 10 consecutive days/nights in a sleep laboratory. After a baseline night (9 h time in bed), participants spent either 5 h (n = 19), 6 h (n = 23), 7 h (n = 16), 8 h (n = 27), or 9 h (n = 26) in bed for seven nights, followed by a 9 h recovery sleep. The saliva samples for cortisol assay were collected at 08:00 h, 08:30 h and 08:45 h at baseline, on experimental days 2 and 5 and on the recovery day. The primary dependent variables were the cortisol concentration at awakening (08:00 h) and the cortisol area under the curve (AUC). There was no effect of time in bed on either the cortisol concentration at awakening or cortisol AUC. In all the time in bed conditions, the cortisol AUC tended to be higher at baseline and lower on experimental day 5. Five consecutive nights of mild to moderate sleep restriction does not appear to affect the CAR in healthy male adults

How should a bio-mathematical model be used within a fatigue risk management system to determine whether or not a working time arrangement is safe?

Bio-mathematical models that predict fatigue and/or sleepiness have proved a useful adjunct in the management of what has been typically referred to as fatigue-related risk. Codifying what constitutes appropriate use of these models will be increasingly important over the next decade. Current guidelines for determining a safe working time arrangement based on model outputs generally use a single upper threshold and are, arguably, over-simplistic. These guidelines fail to incorporate explicitly essential aspects of the risk assessment process – namely, the inherent uncertainty and variability in human sleep–wake behavior; the non-linear relationship between fatigue, task performance and safety outcomes; the consequence of a fatigue-related error and its influence on overall risk; and the impact of risk mitigation or controls in reducing the likelihood or consequence of a fatigue-related error. As industry and regulatory bodies increasingly move toward performance-based approaches to safety management, any fatigue risk management system that includes a bio-mathematical model should specify what exactly is measured by the model, and how the model can be used in the context of a safety management system approach. This will require significant dialog between the various parties with an interest in bio-mathematical models, i.e. developers, vendors, end-users, and regulators. © 2015 Elsevier Lt

How well do truck drivers sleep in cabin sleeper berths?

The aim of this study was to evaluate the sleep obtained by livestock transport truck drivers while resting in truck sleeper berths during long-haul commercial operations. Operations were carried out in the very remote regions of Australia. The sample comprised of 32 drivers who wore wrist activity monitors and reported bed-times for a two-week period. Drivers had a mean ( standard deviation) age of 35.41 (9.78) years and had worked as truck drivers for 13.83 (9.11) years. On average, they obtained 6.07 (1.18) hours of sleep/24-h period. The majority of sleep occurred at night, but drivers occasionally supplemented their main sleep with a daytime nap. Consistent with operational demands, drivers were most likely to sleep in cabin sleeper berths (n = 394, 77%). Only a small proportion of sleeps were sampled at home (n = 63, 12%) or at truck depots (n = 56, 11%). Mixed-model ANOVA revealed that while earlier bed-times at home yielded more sleep, there were only marginal differences in sleep quality across location. No intrinsic safety concerns associated with the use of sleeper berths were identified across consecutive days of long-haul transport operations

Can a watch tell body clock time? Phase relationships between dim light melatonin onset and sleep markers determined from actigraphy, sleep diaries and the Munich Chronotype Questionnaire

Measurement of circadian phase (body clock timing) is often required for diagnosis and treatment of circadian rhythm disorders. However measurement of Dim Light Melatonin Onset (DLMO), the gold standard measure of circadian phase, is expensive and often impractical. As preferred timing of sleep reflects body clock timing, measurement of sleep markers provides a simple way to derive circadian phase. DLMO has been estimated from markers determined subjectively by questionnaires or sleep diaries; however actigraphy now provides the potential for objective and more accurate measurement of sleep markers. The aim of this study is to compare the phase differences between DLMO and sleep markers determined objectively by actigraphy, and subjectively by sleep diaries and the Munich ChronoType Questionnaire (MCTQ)