Ocular Measures of Sleepiness Are Increased in Night Shift Workers Undergoing a Simulated Night Shift Near the Peak Time of the 6-Sulfatoxymelatonin Rhythm

Hilaire MA, Kirkley CL, Gregory KB, Clark T, Hanifin JP, Barger LK, Czeisler CA, Brainard GC, Lockley SW, Flynn-Evans EE. The effect of a dynamic lighting schedule on neurobehavioral performance during a 45-day simulated space mission

Study Objectives

We previously reported that during a 45-day simulated space mission, a dynamic lighting schedule (DLS) improved circadian phase alignment and performance assessed once on selected days. This study aimed to evaluate how DLS affected performance on a 5-minute psychomotor vigilance task (PVT) administered multiple times per day on selected days.

Methods

Sixteen crewmembers (37.4 ± 6.7 years; 5F) underwent six cycles of 2 × 8-hour/night followed by 5 × 5-hour/night sleep opportunities. During the DLS (n = 8), daytime white light exposure was blue-enriched (~6000 K; Level 1: 1079, Level 2: 76 melanopic equivalent daytime illuminance (melEDI) lux) and blue-depleted (~3000-4000 K; L1: 21, L2: 2 melEDI lux) 3 hours before bed. In the standard lighting schedule (SLS; n = 8), lighting remained constant (~4500K; L1: 284, L2 62 melEDI lux). Effects of lighting condition (DLS/SLS), sleep condition (5/8 hours), time into mission, and their interactions, and time awake on PVT performance were analyzed using generalized linear mixed models.

Results

The DLS was associated with fewer attentional lapses (reaction time [RT] > 500 milliseconds) compared to SLS. Lapses, mean RT, and 10% fastest/slowest RTs were worse following 5 compared to 8 hours of sleep but not between lighting conditions. There was an effect of time into mission on RTs, likely due to sleep loss. Overall performance differed by time of day, with longer RTs at the beginning and end of the day. There were more lapses and slower RTs in the afternoon in the SLS compared to the DLS condition.

Conclusions

Future missions should incorporate DLS to enhance circadian alignment and performance. This paper is part of the Sleep and Circadian Rhythms: Management of Fatigue in Occupational Settings Collection.

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.

PERCLOS-based technologies for detecting drowsiness: current evidence and future directions

Drowsiness associated with sleep loss and circadian misalignment is a risk factor for accidents and human error. The percentage of time that the eyes are more than 80% closed (PERCLOS) is one of the most validated indices used for the passive detection of drowsiness, which is increased with sleep deprivation, after partial sleep restriction, at nighttime, and by other drowsiness manipulations during vigilance tests, simulated driving, and on-road driving. However, some cases have been reported wherein PERCLOS was not affected by drowsiness manipulations, such as in moderate drowsiness conditions, in older adults, and during aviation-related tasks. Additionally, although PERCLOS is one of the most sensitive indices for detecting drowsiness-related performance impairments during the psychomotor vigilance test or behavioral maintenance of wakefulness test, no single index is currently available as an optimal marker for detecting drowsiness during driving or other real-world situations. Based on the current published evidence, this narrative review suggests that future studies should focus on: (1) standardization to minimize differences in the definition of PERCLOS between studies; (2) extensive validation using a single device that utilizes PERCLOS-based technology; (3) development and validation of technologies that integrate PERCLOS with other behavioral and/or physiological indices, because PERCLOS alone may not be sufficiently sensitive for detecting drowsiness caused by factors other than falling asleep, such as inattention or distraction; and (4) further validation studies and field trials targeting sleep disorders and trials in real-world environments. Through such studies, PERCLOS-based technology may contribute to preventing drowsiness-related accidents and human error.

The role of circadian phase in sleep and performance during Antarctic winter expeditions

The Antarctic environment presents an extreme variation in the natural light-dark cycle which can cause variability in the alignment of the circadian pacemaker with the timing of sleep, causing sleep disruption, and impaired mood and performance. This study assessed the incidence of circadian misalignment and the consequences for sleep, cognition, and psychological health in 51 over-wintering Antarctic expeditioners (45.6 ± 11.9 years) who completed daily sleep diaries, and monthly performance tests and psychological health questionnaires for 6 months. Circadian phase was assessed via monthly 48-h urine collections to assess the 6-sulphatoxymelatonin (aMT6s) rhythm. Although the average individual sleep duration was 7.2 ± 0.8 h, there was substantial sleep deficiency with 41.4% of sleep episodes <7 h and 19.1% <6 h. Circadian phase was highly variable and 34/50 expeditioners had sleep episodes that occurred at an abnormal circadian phase (acrophase outside of the sleep episode), accounting for 18.8% (295/1565) of sleep episodes. Expeditioners slept significantly less when misaligned (6.1 ± 1.3 h), compared with when aligned (7.3 ± 1.0 h; p < .0001). Performance and mood were worse when awake closer to the aMT6s peak and with increased time awake (all p < .0005). This research highlights the high incidence of circadian misalignment in Antarctic over-wintering expeditioners. Similar incidence has been observed in long-duration space flight, reinforcing the fidelity of Antarctica as a space analog. Circadian misalignment has considerable safety implications, and potentially longer term health risks for other circadian-controlled physiological systems. This increased risk highlights the need for preventative interventions, such as proactively planned lighting solutions, to ensure circadian alignment during long-duration Antarctic and space missions.

An evaluation and comparison of commercial driver sleepiness detection technology: a rapid review

Objective. Sleepiness-related motor vehicle crashes, caused by lack of sleep or driving during night-time hours, often result in serious injury or fatality. Sleepiness detection technology is rapidly emerging as a sleepiness risk mitigation strategy for drivers. Continuous monitoring technologies assess and alert to driver sleepiness in real-time, while fit for duty technologies provide a single assessment of sleepiness state. The aim of this rapid review was to evaluate and compare sleepiness detection technologies in relation to specifications, cost, target consumer group and validity.Approach. We evaluated a range of sleepiness detection technologies suitable for consumer groups ranging from regular drivers in private vehicles through to work-related drivers within large businesses.Main results. Continuous monitoring technologies typically ranged between $100 and $3000 AUD and had ongoing monthly costs for telematics functionality and manager alerts. Fit for duty technologies had either a one-off purchase cost or a monthly subscription cost. Of concern, the majority of commercial continuous monitoring technologies lacked scientific validation. While some technologies had promising findings in terms of their ability to detect and reduce driver sleepiness, further validation work is required. Field studies that evaluate the sensitivity and specificity of technology alerts under conditions that are regularly experienced by drivers are necessary. Additionally, there is a need for longitudinal naturalistic driving studies to determine whether sleepiness detection technologies actually reduce sleepiness-related crashes or near-crashes.Significance. There is an abundance of sleepiness detection technologies on the market, but a majority lacked validation. There is a need for these technologies and their validation to be regulated by a driver safety body. Otherwise, consumers will base their technology choices on cost and features, rather than the ability to save lives.

The wake maintenance zone shows task dependent changes in cognitive function following one night without sleep

Study Objectives

The interaction between homeostatic sleep pressure and circadian timing modulates the impact of sleep deprivation on cognition. We aimed to investigate how this interaction affects different cognitive functions.

Methods

Twenty-three healthy volunteers (18 males; mean age = 25.4 ± 5.7 years) underwent 40 hours of sleep deprivation under constant routine conditions. Performance on the Psychomotor Vigilance Test and a cognitive battery assessing vigilant attention, complex attention, recognition memory, and working memory was assessed in the morning (27 hours awake) and evening (37 hours awake) during sleep deprivation and compared to well-rested performance 24 hours earlier. Circadian phase assessments confirmed evening tests occurred in the wake maintenance zone (WMZ).

Results

Increased time awake significantly impacted performance on all measures except recognition memory. Post hoc analyses found performance on all measures was significantly impaired in the morning following 27 hours of sleep deprivation compared to well-rested performance 24 hours earlier. In contrast, complex attention and working memory were preserved in the WMZ after 37 hours awake compared to 24 hours earlier, while vigilant attention and PVT performance were significantly impaired. During sleep deprivation, composite scores of speed and accuracy were both impaired in the morning, while only speed was impaired during the WMZ.

Conclusions

We observed task- and time-dependent effects of sleep deprivation, such that vigilant attention was significantly impaired after both 27 hours and 37 hours awake (compared to when well-rested at the same circadian clock time). In contrast, complex attention and working memory were impaired at 27 hours awake, but preserved in the WMZ despite increased homeostatic sleep pressure (37 hours awake).

Application of a Limit-Cycle Oscillator Model for Prediction of Circadian Phase in Rotating Night Shift Workers

Practical alternatives to gold-standard measures of circadian timing in shift workers are needed. We assessed the feasibility of applying a limit-cycle oscillator model of the human circadian pacemaker to estimate circadian phase in 25 nursing and medical staff in a field setting during a transition from day/evening shifts (diurnal schedule) to 3-5 consecutive night shifts (night schedule). Ambulatory measurements of light and activity recorded with wrist actigraphs were used as inputs into the model. Model estimations were compared to urinary 6-sulphatoxymelatonin (aMT6s) acrophase measured on the diurnal schedule and last consecutive night shift. The model predicted aMT6s acrophase with an absolute mean error of 0.69 h on the diurnal schedule (SD = 0.94 h, 80% within ±1 hour), and 0.95 h on the night schedule (SD = 1.24 h, 68% within ±1 hour). The aMT6s phase shift from diurnal to night schedule was predicted to within ±1 hour in 56% of individuals. Our findings indicate the model can be generalized to a shift work setting, although prediction of inter-individual variability in circadian phase shift during night shifts was limited. This study provides the basis for further adaptation and validation of models for predicting circadian phase in rotating shift workers.

Generalizability of A Neural Network Model for Circadian Phase Prediction in Real-World Conditions

A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals on a fixed sleep schedule. This study aimed to test the generalizability of the model to other sleep schedules, including rotating shift work. Ambulatory wrist blue light irradiance and skin temperature data were collected in 16 healthy individuals on fixed and habitual sleep schedules, and 28 rotating shift workers. Artificial neural network models were trained to predict the circadian rhythm of (i) salivary melatonin on a fixed sleep schedule; (ii) urinary aMT6s on both fixed and habitual sleep schedules, including shift workers on a diurnal schedule; and (iii) urinary aMT6s in rotating shift workers on a night shift schedule. To determine predicted circadian phase, center of gravity of the fitted bimodal skewed baseline cosine curve was used for melatonin, and acrophase of the cosine curve for aMT6s. On a fixed sleep schedule, the model predicted melatonin phase to within ± 1 hour in 67% and ± 1.5 hours in 100% of participants, with mean absolute error of 41 ± 32 minutes. On diurnal schedules, including shift workers, the model predicted aMT6s acrophase to within ± 1 hour in 66% and ± 2 hours in 87% of participants, with mean absolute error of 63 ± 67 minutes. On night shift schedules, the model predicted aMT6s acrophase to within ± 1 hour in 42% and ± 2 hours in 53% of participants, with mean absolute error of 143 ± 155 minutes. Prediction accuracy was similar when using either 1 (wrist) or 11 skin temperature sensor inputs. These findings demonstrate that the model can predict circadian timing to within ± 2 hours for the vast majority of individuals on diurnal schedules, using blue light and a single temperature sensor. However, this approach did not generalize to night shift conditions.

Increased vulnerability to attentional failure during acute sleep deprivation in women depends on menstrual phase

Study Objectives

To investigate sex differences in the effect of sleep deprivation on performance, accounting for menstrual phase in women.

Methods

We examined alertness data from 124 healthy women and men (40 women, 84 men; aged 18-30 years) who maintained wakefulness for at least 30 hr in a laboratory setting using a constant routine protocol. Objective alertness was assessed every 2 hr using a 10 min psychomotor vigilance task. Subjective alertness was assessed every hour via the Karolinska Sleepiness Scale.

Results

Women in the follicular phase of the menstrual cycle demonstrated the poorest level of performance. This poor performance was most pronounced at times corresponding to the typical sleep episode, demonstrating a window of vulnerability at night during this menstrual phase. At 24 hr awake, over 60 per cent of their responses were lapses of >500 ms and over one-third of their responses were longer lapses of at least 3 s in duration. Women in the luteal phase, however, were relatively protected from alertness failure, performing similar or better than both follicular-phase women and men.

Conclusions

These results have important implications for education and intervention programs for shift workers, specifically during times of vulnerability to attentional failure that increase risk of injury.

The Impact of Shift Work on Sleep, Alertness and Performance in Healthcare Workers

Shift work is associated with impaired alertness and performance due to sleep loss and circadian misalignment. This study examined sleep between shift types (day, evening, night), and alertness and performance during day and night shifts in 52 intensive care workers. Sleep and wake duration between shifts were evaluated using wrist actigraphs and diaries. Subjective sleepiness (Karolinska Sleepiness Scale, KSS) and Psychomotor Vigilance Test (PVT) performance were examined during day shift, and on the first and subsequent night shifts (3^rd, 4^th or 5^th). Circadian phase was assessed using urinary 6-sulphatoxymelatonin rhythms. Sleep was most restricted between consecutive night shifts (5.74 ± 1.30 h), consecutive day shifts (5.83 ± 0.92 h) and between evening and day shifts (5.20 ± 0.90 h). KSS and PVT mean reaction times were higher at the end of the first and subsequent night shift compared to day shift, with KSS highest at the end of the first night. On nights, working during the circadian acrophase of the urinary melatonin rhythm led to poorer outcomes on the KSS and PVT. In rotating shift workers, early day shifts can be associated with similar sleep restriction to night shifts, particularly when scheduled immediately following an evening shift. Alertness and performance remain most impaired during night shifts given the lack of circadian adaptation to night work. Although healthcare workers perceive themselves to be less alert on the first night shift compared to subsequent night shifts, objective performance is equally impaired on subsequent nights.

Temporal dynamics of circadian phase shifting response to consecutive night shifts in healthcare workers: role of light-dark exposure

KEY POINTS

Shift work is highly prevalent and is associated with significant adverse health impacts. There is substantial inter-individual variability in the way the circadian clock responds to changing shift cycles. The mechanisms underlying this variability are not well understood. We tested the hypothesis that light-dark exposure is a significant contributor to this variability; when combined with diurnal preference, the relative timing of light exposure accounted for 71% of individual variability in circadian phase response to night shift work. These results will drive development of personalised approaches to manage circadian disruption among shift workers and other vulnerable populations to potentially reduce the increased risk of disease in these populations.

ABSTRACT

Night shift workers show highly variable rates of circadian adaptation. This study examined the relationship between light exposure patterns and the magnitude of circadian phase resetting in response to night shift work. In 21 participants (nursing and medical staff in an intensive care unit) circadian phase was measured using 6-sulphatoxymelatonin at baseline (day/evening shifts or days off) and after 3-4 consecutive night shifts. Daily light exposure was examined relative to individual circadian phase to quantify light intensity in the phase delay and phase advance portions of the light phase response curve (PRC). There was substantial inter-individual variability in the direction and magnitude of phase shift after three or four consecutive night shifts (mean phase delay -1:08 ± 1:31 h; range -3:43 h delay to +3:07 h phase advance). The relative difference in the distribution of light relative to the PRC combined with diurnal preference accounted for 71% of the variability in phase shift. Regression analysis incorporating these factors estimated phase shift to within ±60 min in 85% of participants. No participants met criteria for partial adaptation to night work after three or four consecutive night shifts. Our findings provide evidence that the phase resetting that does occur is based on individual light exposure patterns relative to an individual's baseline circadian phase. Thus, a 'one size fits all' approach to promoting adaptation to shift work using light therapy, implemented without knowledge of circadian phase, may not be efficacious for all individuals.

Randomised controlled trial of the efficacy of a blue-enriched light intervention to improve alertness and performance in night shift workers

OBJECTIVES

Night workers often experience high levels of sleepiness due to misalignment of the sleep-wake cycle from the circadian pacemaker, in addition to acute and chronic sleep loss. Exposure to light, in particular short wavelength light, can improve alertness and neurobehavioural performance. This randomised controlled trial examined the efficacy of blue-enriched polychromatic light to improve alertness and neurobehavioural performance in night workers.

DESIGN

Participants were 71 night shift workers (42 males; 32.8±10.5 years) who worked at least 6 hours between 22:00 and 08:00 hours. Sleep-wake logs and wrist actigraphy were collected for 1-3 weeks, followed by 48-hour urine collection to measure the circadian 6-sulphatoxymelatonin (aMT6s) rhythm. On the night following at least two consecutive night shifts, workers attended a simulated night shift in the laboratory which included subjective and objective assessments of sleepiness and performance. Workers were randomly assigned for exposure to one of two treatment conditions from 23:00 hours to 07:00 hours: blue-enriched white light (17 000 K, 89 lux; n=36) or standard white light (4000 K, 84 lux; n=35).

RESULTS

Subjective and objective sleepiness increased during the night shift in both light conditions (p<0.05, η_p²=0.06-0.31), but no significant effects of light condition were observed. The 17 000 K light, however, did improve subjective sleepiness relative to the 4000 K condition when light exposure coincided with the time of the aMT6s peak (p<0.05, d=0.41-0.60).

CONCLUSION

This study suggests that, while blue-enriched light has potential to improve subjective sleepiness in night shift workers, further research is needed in the selection of light properties to maximise the benefits.

TRIAL REGISTRATION NUMBER

The Australian New Zealand Clinical Trials Registry ACTRN12610000097044 (https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=320845&isReview=true).