Bright-light exposure during daytime sleeping affects nocturnal melatonin secretion after simulated night work

The guidelines for night and shift workers recommend that after night work, they should sleep in a dark environment during the daytime. However, staying in a dark environment during the daytime reduces nocturnal melatonin secretion and delays its onset. Daytime bright-light exposure after night work is important for melatonin synthesis the subsequent night and for maintaining the circadian rhythms. However, it is not clear whether daytime sleeping after night work should be in a dim- or a bright-light environment for maintaining melatonin secretion. The aim of this study, therefore, was to evaluate the effect of bright-light exposure during daytime sleeping on nocturnal melatonin secretion after simulated night work. Twelve healthy male subjects, aged 24.8 ± 4.6 (mean ± SD), participated in 3-day sessions under two experimental conditions, bright light or dim light, in a random order. On the first day, the subjects entered the experimental room at 16:00 and saliva samples were collected every hour between 18:00 and 00:00 under dim-light conditions. Between 00:00 and 08:00, they participated in tasks that simulated night work. At 10:00 the next morning, they slept for 6 hours under either a bright-light condition (>3000 lx) or a dim-light condition (<50 lx). In the evening, saliva samples were collected as on the first day. The saliva samples were analyzed for melatonin concentration. Activity and sleep times were recorded by a wrist device worn throughout the experiment. In the statistical analysis, the time courses of melatonin concentration were compared between the two conditions by three-way repeated measurements ANOVA (light condition, day and time of day). The change in dim light melatonin onset (ΔDLMO) between the first and second days, and daytime and nocturnal sleep parameters after the simulated night work were compared between the light conditions using paired t-tests. The ANOVA results indicated a significant interaction (light condition and3 day) (p = .006). Post hoc tests indicated that in the dim-light condition, the melatonin concentration was significantly lower on the second day than on the first day (p = .046); however, in the bright-light condition, there was no significant difference in the melatonin concentration between the days (p = .560). There was a significant difference in ΔDLMO between the conditions (p = .015): DLMO after sleeping was advanced by 11.1 ± 17.4 min under bright-light conditions but delayed for 7.2 ± 13.6 min after sleeping under dim-light conditions. No significant differences were found in any sleep parameter. Our study demonstrated that daytime sleeping under bright-light conditions after night work could not reduce late evening melatonin secretion until midnight or delay the phase of melatonin secretion without decreasing the quality of the daytime sleeping. Thus, these results suggested that, to enhance melatonin secretion and to maintain their conventional sleep–wake cycle, after night work, shift workers should sleep during the daytime under bright-light conditions rather than dim-light conditions.     

Differences in workday sleep fragmentation,rest-activity cycle,sleep quality,and activity level among nurses working different shifts

ABSTRACT

Schedule changes associated with rotating shifts can interfere with the circadian rhythms of nurses and thereby affect their sleep duration, sleep quality, work efficiency, and work performance. The objectives of this study was to investigate differences in workday sleep fragmentation, rest-activity cycle, sleep quality, and activity level among nurses working different shifts. After filling out a basic information questionnaire and completing the Pittsburgh Sleep Quality Index (PSQI) questionnaire, participants were asked to wear an actigraph and keep sleep records for seven consecutive days. Data pertaining to wake after sleep onset (WASO), 24-hour autocorrelation coefficient (r24), and daytime activity mean was collected in order to investigate workday sleep fragmentation, rest-activity cycle, and daytime activity level. We obtained complete questionnaires and data from 191 nurses. Day- and evening-shift nurses had more regular workday rest-activity cycles than did night-shift nurses (F = 51.26, p < .001). After controlling for r24 coefficients, we determined that nurses who experienced greater workday sleep fragmentation had higher PSQI scores (β = .18, p = .008). After controlling for WASO times, we determined that nurses who had more regular rest-activity cycles on workdays had lower PSQI scores (β = – .16, p = .036). After controlling for shift type and WASO times, we determined that nurses with higher PSQI scores displayed lower activity levels (β = – .21, p = .015) and those with higher r24 coefficients displayed higher activity levels (β = .18, p = .040) on workdays. We then examined the causal path relationships. Among the shifts, only the day-shift nurses had a higher r24 (β = ?.59, p < .001) than did the night-shift nurses; WASO exerted a significant impact on PSQI scores (β = .20, p = .002); r24 had a significant and negative influence on PSQI scores (β = ?.38, p < .001), and PSQI scores significantly and negatively influenced workday activity levels (β = ?.20, p = .006). This study determined that day- and evening-shift nurses enjoyed more regular and consistent rest-activity cycles than did night-shift nurses; nurses with greater workday sleep fragmentation and/or more irregular rest-activity cycles experienced poorer sleep quality; and nurses suffering from poorer sleep quality displayed lower daytime activity levels on workdays.     

Preliminary findings for the validity of the Morningness–Eveningness-Stability Scale improved (MESSi): Correlations with activity levels and personality

Aim of the present study is an additional validation of the Morningness–Eveningness-Stability Scale improved (MESSi). We screened a total of 97 German students using the reduced Morningness–Eveningness Questionnaire (rMEQ) to identify a subsample (N = 42) of definite morning and evening types (31% males, mean age: 24.8 ± 5.8?years). The participants provided information about their sleep–wake rhythm (diary), personality traits (questionnaire) and experienced actigraphic monitoring. Correlations of the MESSi components “Morning affect subscale” (MA) (r = 0.91, p < 0.01) and “Eveningness subscale” (r = ?0.87, p < 0.01) with the rMEQ showed good convergent validity. MA was also significantly negatively correlated with the acrophase and the midpoint of sleep as measured by actigraphy.     

Athletes underestimate sleep quantity during daytime nap opportunities

ABSTRACT

This study examined the difference between athletes’ self-reported and objective sleep durations during two nap opportunities. Twelve well-trained male soccer players’ sleep durations were assessed using polysomnography and a self-report question during a 60- and 120-min nap opportunity. Participants underestimated sleep compared to objective sleep assessments for both the 60-min nap opportunity (p = 0.004) and 120-min nap opportunity (p = 0.001). Soccer players underestimated their sleep duration by approximately 10 min per hour of nap opportunity. It is yet to be determined if athletes are likely to underestimate sleep duration during their main nighttime sleep period.     

The impact of training schedules on the sleep and fatigue of elite athletes

In any sport, successful performance requires a planned approach to training and recovery. While sleep is recognized as an essential component of this approach, the amount and quality of sleep routinely obtained by elite athletes has not been systematically evaluated. Data were collected from 70 nationally ranked athletes from seven different sports. Athletes wore wrist activity monitors and completed self-report sleep/training diaries for 2 weeks during normal training. The athletes also recorded their fatigue level prior to each training session using a 7-point scale. On average, the athletes spent 08:18?±?01:12?h in bed, fell asleep at 23:06?±?01:12?h, woke at 6:48?±?01:30?h and obtained 06:30?±?01:24?h of sleep per night. There was a marked difference in the athletes’ sleep/wake behaviour on training days and rest days. Linear mixed model analyses revealed that on nights prior to training days, time spent in bed was significantly shorter (p?=?0.001), sleep onset and offset times were significantly earlier (p?<?0.001) and the amount of sleep obtained was significantly less (p?=?0.001), than on nights prior to rest days. Moreover, there was a significant effect of sleep duration on pre-training fatigue levels (p?≤?0.01). Specifically, shorter sleep durations were associated with higher levels of pre-training fatigue. Taken together, these findings suggest that the amount of sleep an elite athlete obtains is dictated by their training schedule. In particular, early morning starts reduce sleep duration and increase pre-training fatigue levels. When designing schedules, coaches should be aware of the implications of the timing of training sessions for sleep and fatigue. In cases where early morning starts are unavoidable, countermeasures for minimizing sleep loss – such as strategic napping during the day and correct sleep hygiene practices at night – should be considered.     

Late bedtimes prevent circadian phase advances to morning bright light in adolescents

ABSTRACT

We examined phase shifts to bright morning light when sleep was restricted by delaying bedtimes. Adolescents (n = 6) had 10-h sleep/dark opportunities for 6 days. For the next 2 days, half were put to bed 4.5 h later and then allowed to sleep for 5.5 h (evening room light + sleep restriction). The others continued the 10-h sleep opportunities (sleep satiation). Then, sleep schedules were gradually shifted earlier and participants received bright light (90 min, ~6000 lux) after waking for 3 days. As expected, sleep satiation participants advanced (~2 h). Evening room light + sleep restriction participants did not shift or delayed by 2–4 h.

Abbreviations: DLMO: dim light melatonin onset.     

Explaining Sleep Duration in Adolescents: The Impact of Socio‐Demographic and Lifestyle Factors and Working Status

Previous studies found students who both work and attend school undergo a partial sleep deprivation that accumulates across the week. The aim of the present study was to obtain information using a questionnaire on a number of variables (e.g., socio‐demographics, lifestyle, work timing, and sleep‐wake habits) considered to impact on sleep duration of working (n=51) and non‐working (n=41) high‐school students aged 14–21 yrs old attending evening classes (19:00–22:30 h) at a public school in the city of São Paulo, Brazil. Data were collected for working days and days off. Multiple linear regression analyses were performed to assess the factors associated with sleep duration on weekdays and weekends. Work, sex, age, smoking, consumption of alcohol and caffeine, and physical activity were considered control variables. Significant predictors of sleep duration were: work (p < 0.01), daily work duration (8–10 h/day; p < 0.01), sex (p=0.04), age 18–21 yrs (0.01), smoking (p=0.02) and drinking habits (p=0.03), irregular physical exercise (p < 0.01), ease of falling asleep (p=0.04), and the sleep‐wake cycle variables of napping (p < 0.01), nocturnal awakenings (p < 0.01), and mid‐sleep regularity (p < 0.01). The results confirm the hypotheses that young students who work and attend school showed a reduction in night‐time sleep duration. Sleep deprivation across the week, particularly in students working 8–10 h/day, is manifested through a sleep rebound (i.e., extended sleep duration) on Saturdays. However, the different roles played by socio‐demographic and lifestyle variables have proven to be factors that intervene with nocturnal sleep duration. The variables related to the sleep‐wake cycle—naps and night awakenings—proved to be associated with a slight reduction in night‐time sleep, while regularity in sleep and wake‐up schedules was shown to be associated with more extended sleep duration, with a distinct expression along the week and the weekend. Having to attend school and work, coupled with other socio‐demographic and lifestyle factors, creates an unfavorable scenario for satisfactory sleep duration.     

Intra-individual variability in the sleep of senior and junior rugby league athletes during the competitive season

This study examined the sleep intra-individual variability (IIV) of rugby league athletes across senior and junior levels during one week of the competitive season. Forty-five rugby league athletes across elite senior, sub-elite senior and elite junior levels each wore actigraphy monitors for seven days during the competitive season, and completed a subjective sleep diary each morning upon waking. Linear mixed models were used to assess differences in sleep measures between playing levels. Intra-individual standard deviations for each sleep measure were calculated for each athlete to determine their respective IIV, allowing differences in IIV between groups to be assessed. Elite junior athletes went to bed later (ES = 0.94 ± 0.50, p < 0.05) and woke later than elite senior athletes (ES = 0.94 ± 0.40, p < 0.05), while also displaying greater IIV when considering time in bed (ES = 1.14 ± 0.60, p < 0.05) and sleep duration (ES = 1.53 ± 0.64, p < 0.05) compared with elite senior athletes. Similarly, IIV was more pronounced in elite junior players for time in bed (ES = 0.88 ± 0.60, p < 0.05) and sleep duration (ES = 1.03 ± 0.64, p < 0.05) compared with sub-elite senior athletes. Despite this, elite junior athletes still obtained sufficient sleep duration, efficiency and quality. The outcomes of this investigation show a distinct difference in the habitual sleep-wake patterns of senior and junior rugby league athletes, and show how sleep IIV differs between playing levels in rugby league.     

The influence of the sleep-wake cycle on primary monosymptomatic nocturnal enuresis: a non-randomized comparative study

Backround: Enuresis implies severe stress in affected children, and impairs quality of life and sleep. Children with enuresis experience difficulties in their arousal from sleep, possibly associated with disturbances of the circadian rhythm. In this study, we aimed to evaluate the sleep–wake cycle and sleep disturbances in children with monosymptomatic enuresis nocturna (MEN). Method: The study comprised 70 children with MEN who were admitted to the pediatrics and urology outpatients department and 94 age-matched healthy controls. Parents completed “Strengths and Difficulties Questionnaire,” Children’s Sleep Habits Questionnaire (CSHQ), Children’s Chronotype Questionnaire scale. Results: Children with enuresis had significantly more sleep and psychological problem. Enuresis group reported higher bedtime resistance, parasomnias, breathing-related problems, and daytime sleepiness in CHSQ (p < 0.05). Although circadian preference did not differ statistically between the groups (p > 0.05), sleep duration on school days and awakening and mid-sleep points, both on scheduled and free days, were found to be significantly different in the enuretic group (p < 0.05). In logistic regression analysis, age, sleep period on scheduled days, sleep inertia on scheduled and free days were significant predictor for enuresis. Discussion: Children with enuresis were more likely to experience problematic sleep. This may reflect that enuretic children have impaired sleep–wake cycles, leading to dysregulation of daily functional changes of bladder capacity and related hormones such as ADH. These findings might imply a sleep–wake disturbance in enuresis.     

Sleep duration,nightshift work,and the timing of meals and urinary levels of 8-isoprostane and 6-sulfatoxymelatonin in Japanese women

It has been hypothesized that disruption of circadian rhythms affects human health. Shift work and sleep deprivation are thought to disrupt the normal light–dark cycle, although the disruption due to shiftwork may be dependent on sleep deprivation. Both conditions have been suggested to be associated with an increased risk of cardiometabolic disorders. Non-photic environmental factors, such as the timing of eating, are also thought to regulate circadian rhythm and thus, may have effects on health, but the evidence from human studies is scarce. Oxidative stress is a risk factor of cardiometabolic disorders. Some laboratory studies suggest an involvement of circadian clock genes in the regulation of the redox system. The present study aimed to examine the association of sleeping habits, nightshift work, and the timing of meals with urinary levels of 8-isoprostane, a marker of oxidative stress, and 6-sulfatoxymelatonin, the principal metabolite of melatonin. Study subjects were 542 women who had previously attended a breast cancer mass screening in a community in Japan. Information on bedtimes and wake-up times, history of nightshift work, and the timing of meals was obtained by a self-administered questionnaire. The 8-isoprostane and 6-sulfatoxymelatonin were measured using the first morning void of urine and expressed per mg of creatinine. The geometric mean of 8-isoprostane levels was 12.1% higher in women with ≤6 hours of sleep than that in those with >8 hours of sleep on weekdays, and longer sleep duration on weekdays was significantly associated with lower urinary levels of 8-isoprostane after controlling for covariates (p for trend = 0.04). Women who were currently working the nightshift had a 33.3% higher geometric mean of 8-isoprostane levels than those who were not working nightshift (p = 0.03). Urinary 6-sulfatoxymelatonin levels were unrelated to sleep habits or nightshift work. Women who ate breakfast at irregular times had a 19.8% higher geometric mean of 8-isoprostane levels than those who ate breakfast at a regular time or who did not eat (p = 0.02). Women who ate nighttime snacks at irregular times had a 16.2% higher geometric mean of 8-isoprostane levels than those who did not eat nighttime snacks or who ate nighttime snacks at a regular time (p = 0.003). Among women who ate dinner at a regular time, earlier times for dinner were associated with higher 8-isoprostane and 6-sulfatoxymelatonin levels (p values for trends were 0.01 and 0.02, respectively). However, the times of dinner and nighttime snack are overlapping, and the time of last meal of the day was not associated with 8-isoprostane and 6-sulfatoxymelatonin levels. The time of breakfast or lunch was not associated with these biomarkers among women who ate the meal at regular times. Disturbing the rhythmicity of daily life may be associated with oxidative stress.     

Influence of shift type on sleep quality of female nurses working monthly rotating shifts with cortisol awakening response as mediating variable

ABSTRACT

When shift nurses change shifts, it is likely to affect the cortisol patterns of their bodies and sleep quality. The objectives of this study was to verify the influence of monthly rotating day, evening and night shifts on the sleep quality of female nurses and determine whether the cortisol awakening response (CAR) mediates this relationship. A total of 132 female shift nurses were recruited, and ultimately 128 complete questionnaires and samples were obtained (subject loss rate = 3.0%) from 45 day-shift nurses, 44 evening-shift nurses and 39 night-shift nurses at a teaching hospital in Northern Taiwan. The Pittsburgh sleep quality index served as the research instrument that nurses used to collect saliva samples at home every day after waking and 30?min after waking so as to calculate the net increases in cortisol levels (CARi). Hierarchical multiple regression was employed to examine the influence of shift type on the sleep quality of the female nurses and the mediating effect of CARi. The results of this study indicate that shift type significantly influenced CARi (F = 19.66, p < 0.001) and that the regression coefficients of evening versus day shifts and night versus day shifts are both negative. Shift type also significantly influenced sleep quality (F = 15.13, p < 0.001), and the regression coefficients of evening versus day shifts and night versus day shifts are both positive. After controlling for the influence of shift type, CARi remained significantly correlated with sleep quality (ΔF = 5.17, p = 0.025). The results show that female evening-shift or night-shift nurses display significantly lower CARi and experience significantly poorer sleep quality than day-shift nurses. A greater CARi in the female shift nurses represents better sleep quality. Furthermore, the results prove that CARi is a mediating variable influencing the sleep quality of female shiftwork nurses.     

A validation study of Fitbit Charge 2™ compared with polysomnography in adults

We evaluated the performance of a consumer multi-sensory wristband (Fitbit Charge 2?), against polysomnography (PSG) in measuring sleep/wake state and sleep stage composition in healthy adults.

In-lab PSG and Fitbit Charge 2? data were obtained from a single overnight recording at the SRI Human Sleep Research Laboratory in 44 adults (19—61 years; 26 women; 25 Caucasian). Participants were screened to be free from mental and medical conditions. Presence of sleep disorders was evaluated with clinical PSG. PSG findings indicated periodic limb movement of sleep (PLMS, > 15/h) in nine participants, who were analyzed separately from the main group (n = 35). PSG and Fitbit Charge 2? sleep data were compared using paired t-tests, Bland–Altman plots, and epoch-by-epoch (EBE) analysis.

In the main group, Fitbit Charge 2? showed 0.96 sensitivity (accuracy to detect sleep), 0.61 specificity (accuracy to detect wake), 0.81 accuracy in detecting N1+N2 sleep (“light sleep”), 0.49 accuracy in detecting N3 sleep (“deep sleep”), and 0.74 accuracy in detecting rapid-eye-movement (REM) sleep. Fitbit Charge 2? significantly (p < 0.05) overestimated PSG TST by 9 min, N1+N2 sleep by 34 min, and underestimated PSG SOL by 4 min and N3 sleep by 24 min. PSG and Fitbit Charge 2? outcomes did not differ for WASO and time spent in REM sleep. No more than two participants fell outside the Bland–Altman agreement limits for all sleep measures. Fitbit Charge 2? correctly identified 82% of PSG-defined non-REM–REM sleep cycles across the night. Similar outcomes were found for the PLMS group.

Fitbit Charge 2? shows promise in detecting sleep-wake states and sleep stage composition relative to gold standard PSG, particularly in the estimation of REM sleep, but with limitations in N3 detection. Fitbit Charge 2? accuracy and reliability need to be further investigated in different settings (at-home, multiple nights) and in different populations in which sleep composition is known to vary (adolescents, elderly, patients with sleep disorders).     

Melatonin ingestion after exhaustive late-evening exercise improves sleep quality and quantity,and short-term performances in teenage athletes

ABSTRACT

The present study aimed to explore the effects of a single 10-mg dose of melatonin (MEL) administration after exhaustive late-evening exercise on sleep quality and quantity, and short-term physical and cognitive performances in healthy teenagers. Ten male adolescent athletes (mean ± SD, age = 15.4 ± 0.3 years, body-mass = 60.68 ± 5.7 kg, height = 167.9 ± 6.9 cm and BMI = 21.21 ± 2.5) performed two test sessions separated by at least one week. During each session, participants completed the Yo-Yo intermittent-recovery-test level-1 (YYIRT-1) at ~20:00 h. Then, sleep polysomnography was recorded from 22:15 min to 07:00 h, after a double blind randomized order administration of a single 10-mg tablet of MEL (MEL-10 mg) or Placebo (PLA). The following morning, Hooper wellness index was administered and the participants performed the Choice Reaction Time (CRT) test, the Zazzo test and some short-term physical exercises (YYIRT-1, vertical and horizontal Jumps (VJ; HJ), Hand grip strength (HG), and five-jump test (5-JT)). Evening total distance covered in the YYIRT-1 did not change during the two conditions (p > 0.05). Total sleep time (Δ = 24.55 mn; p < 0.001), sleep efficiency (Δ = 4.47%; p < 0.001), stage-3 sleep (N3 sleep) (Δ = 1.73%; p < 0.05) and rapid-eye-movement sleep (Δ = 2.15%; p < 0.001) were significantly higher with MEL in comparison with PLA. Moreover, sleep-onset-latency (Δ = –8.45mn; p < 0.001), total time of nocturnal awakenings after sleep-onset (NA) (Δ = –11 mn; p < 0.001), stage-1 sleep (N1 sleep) (Δ = –1.7%; p < 0.001) and stage-2 sleep (N2 sleep) (Δ = ?1.9%; p < 0.05) durations were lower with MEL. The Hooper index showed a better subjective sleep quality, a decrease of the subjective perception of fatigue and a reduced level of muscle soreness with MEL. Moreover, MEL improved speed and performance but not inaccuracy during the Zazzo test. CRT was faster with MEL. Morning YYIRT-1 (Δ = 82 m; p < 0.001) and 5-JT (Δ = 0.08 m; p < 0.05) performances were significantly higher with MEL in comparison with PLA. In contrast, HG, VJ and HJ performances did not change during the two conditions (p > 0.05). The administration of a single dose of MEL-10 mg after strenuous late-evening exercise improved sleep quality and quantity, selective attention, subjective assessment of the general wellness state, and some short-term physical performances the following morning in healthy teenagers.     

Disruptions in sleep–wake cycles in community-dwelling cancer patients receiving palliative care and their correlates

Significant disruptions in sleep–wake cycles have been found in advanced cancer patients in prior research. However, much remains to be known about specific sleep–wake cycle variables that are impaired in patients with a significantly altered performance status. More studies are also needed to explore the extent to which disrupted sleep–wake cycles are related to physical and psychological symptoms, time to death, maladaptive sleep behaviors, quality of life and 24-h light exposure. This study conducted in palliative cancer patients was aimed at characterizing patients’ sleep–wake cycles using various circadian parameters (i.e. amplitude, acrophase, mesor, up-mesor, down-mesor, rhythmicity coefficient). It also aimed to compare rest–activity rhythm variables of participants with a performance status of 2 vs. 3 on the Eastern Cooperative Oncology Group scale (ECOG) and to evaluate the relationships of sleep–wake cycle parameters with several possible correlates. The sample was composed of 55 community-dwelling cancer patients receiving palliative care with an ECOG of 2 or 3. Circadian parameters were assessed using an actigraphic device for seven consecutive 24-h periods. A light recording and a daily pain diary were completed for the same period. A battery of self-report scales was also administered. A dampened circadian rhythm, a low mean activity level, an early mean time of peak activity during the day, a late starting time of activity during the morning and an early time of decline of activity during the evening were observed. In addition, a less rhythmic sleep–wake cycle was associated with a shorter time to death (from the first home visit) and with a lower 24-h light exposure. Sleep–wake cycles are markedly disrupted in palliative cancer patients, especially, near the end of life. Effective non-pharmacological interventions are needed to improve patients’ circadian rhythms, including perhaps bright light therapy.     

Pulling the covers in electronic health records for an association study with self-reported sleep behaviors

ABSTRACT

The electronic health record (EHR) contains rich histories of clinical care, but has not traditionally been mined for information related to sleep habits. Here, we performed a retrospective EHR study based on a cohort of 3,652 individuals with self-reported sleep behaviors documented from visits to the sleep clinic. These individuals were obese (mean body mass index 33.6 kg/m²) and had a high prevalence of sleep apnea (60.5%), however we found sleep behaviors largely concordant with prior prospective cohort studies. In our cohort, average wake time was 1 hour later and average sleep duration was 40 minutes longer on weekends than on weekdays (p < 10^?12). Sleep duration varied considerably as a function of age and tended to be longer in females and in whites. Additionally, through phenome-wide association analyses, we found an association of long weekend sleep with depression, and an unexpectedly large number of associations of long weekday sleep with mental health and neurological disorders (q < 0.05). We then sought to replicate previously published genetic associations with morning/evening preference on a subset of our cohort with extant genotyping data (n = 555). While those findings did not replicate in our cohort, a polymorphism (rs3754214) in high linkage disequilibrium with a previously published polymorphism near TARS2 was associated with long sleep duration (p < 0.01). Collectively, our results highlight the potential of the EHR for uncovering the correlates of human sleep in real-world populations.     

Sleep Loss and Performance of Anaesthesia Trainees and Specialists

Fatigue risk associated with work schedules of hospital doctors is coming under increasing scrutiny, with much of the research and regulatory focus on trainees. However, provision of 24 h services involves both trainees and specialists, who have different but interdependent work patterns. This study examined work patterns, sleep (actigraphy, diaries) and performance (psychomotor vigilance task pre‐ and post‐duty) of 28 anaesthesia trainees and 20 specialists across a two‐week work cycle in two urban public hospitals. Trainees at one hospital worked back‐to‐back 12 h shifts, while the others usually worked 9 h day shifts but periodically worked a 14 h day (08:00–22:00 h) to maintain cover until arrival of the night shift (10 h). On 11% of day shifts and 23% of night shifts, trainees were working with ≥2 h of acute sleep loss. However, average sleep loss was not greater on night shifts, possibly because workload at night in one hospital often permitted some sleep. Post‐night shift performance was worse than post‐day shift performance for the median (t₍₁₃₁₎=3.57, p<0.001) and slowest 10% of reaction times (t₍₁₃₄₎=2.91, p<0.01). At the end of night shifts, poorer performance was associated with longer shift length, longer time since waking, greater acute sleep loss, and more total work in the past 24 h. Specialists at both hospitals had scheduled clinical duties during the day and were periodically scheduled on call to cover after‐hours services. On 8% of day shifts and 14% of day+call schedules, specialists were working with ≥2 h of acute sleep loss. They averaged 0.6 h less sleep when working day shifts (t_(23.5)=2.66, p=0.014) and 0.8 h less sleep when working day shifts+call schedules (t_(26.3)=2.65, p=0.013) than on days off. Post‐duty reaction times slowed linearly across consecutive duty days (median reaction time, t₍₁₃₁₎=?3.38, p<0.001; slowest 10%, t₍₁₆₀₎=?3.33, p<0.01; fastest 10%, t₍₁₃₈₎=?2.67, p<0.01). Poorer post‐duty performance was associated with greater acute sleep loss and longer time since waking, but better performance was associated with longer day shifts, consistent with circadian improvement in psychomotor performance across the waking day. This appears to be the first study to document sleep loss among specialist anaesthetists. Consistent with observations from experimental studies, the sleep loss of specialists across 12 consecutive working days was associated with a progressive decline in post‐duty PVT performance. However, this decline occurred with much less sleep restriction (< 1 h per day) than in laboratory studies, suggesting an exacerbating effect of extended wakefulness and/or cumulative fatigue associated with work demands. For both trainees and specialists, robust circadian variation in PVT performance was evident in this complex work setting, despite the potential confounds of variable shift durations and workloads. The relationship between PVT performance of an individual and the safe administration of anaesthesia in the operating theater is unknown. Nevertheless, the findings reinforce that any schedule changes to reduce work‐related fatigue need to consider circadian performance variation and the potential transfer of workload and fatigue risk between trainees and specialists.     

Effects of Filtering Visual Short Wavelengths During Nocturnal Shiftwork on Sleep and Performance

Circadian phase resetting is sensitive to visual short wavelengths (450–480?nm). Selectively filtering this range of wavelengths may reduce circadian misalignment and sleep impairment during irregular light-dark schedules associated with shiftwork. We examined the effects of filtering short wavelengths (<480?nm) during night shifts on sleep and performance in nine nurses (five females and four males; mean age?±?SD: 31.3?±?4.6 yrs). Participants were randomized to receive filtered light (intervention) or standard indoor light (baseline) on night shifts. Nighttime sleep after two night shifts and daytime sleep in between two night shifts was assessed by polysomnography (PSG). In addition, salivary melatonin levels and alertness were assessed every 2?h on the first night shift of each study period and on the middle night of a run of three night shifts in each study period. Sleep and performance under baseline and intervention conditions were compared with daytime performance on the seventh day shift, and nighttime sleep following the seventh daytime shift (comparator). On the baseline night PSG, total sleep time (TST) (p?<?0.01) and sleep efficiency (p?=?0.01) were significantly decreased and intervening wake times (wake after sleep onset [WASO]) (p?=?0.04) were significantly increased in relation to the comparator night sleep. In contrast, under intervention, TST was increased by a mean of 40?min compared with baseline, WASO was reduced and sleep efficiency was increased to levels similar to the comparator night. Daytime sleep was significantly impaired under both baseline and intervention conditions. Salivary melatonin levels were significantly higher on the first (p?<?0.05) and middle (p?<?0.01) night shifts under intervention compared with baseline. Subjective sleepiness increased throughout the night under both conditions (p?<?0.01). However, reaction time and throughput on vigilance tests were similar to daytime performance under intervention but impaired under baseline on the first night shift. By the middle night shift, the difference in performance was no longer significant between day shift and either of the two night shift conditions, suggesting some adaptation to the night shift had occurred under baseline conditions. These results suggest that both daytime and nighttime sleep are adversely affected in rotating-shift workers and that filtering short wavelengths may be an approach to reduce sleep disruption and improve performance in rotating-shift workers. (Author correspondence: casper@lunenfeld.ca)     

Athletes’ rest-activity circadian rhythm differs in accordance with the sport discipline

The correct expression of circadian rhythmicity is crucial for the body homeostasis. The rest-activity circadian rhythms (RARs) are involved in the control of the sleep-wake cycle and altered RARs could lead to a compromised health status. Many studies focused on examining sleep behavior and circadian rhythms in physically active subjects or athletes but, unexpectedly, no data on RARs are available. Therefore, we studied the existence of the RAR in athletes and the possible difference in RAR’s characteristics among sport disciplines. The study had a prospective observational design and RARs were recorded for five consecutive training days through actigraphy (Actiwatch 2 actigraph; Philips Respironics, OR, USA) in 43 athletes (mean age: 25.6 ± 3.2 years). Athletes competed in three different disciplines and had different training schedules and competition levels: professional triathletes (N = 10; 6 females and 4 males) had 2 morning (08:30–12:00) and 1 afternoon (15:00–17:00) training sessions, professional volleyball players (N = 19; 12 females and 7 males) used to train once in the morning (09:00–11:30) and once in the afternoon (15:00–18:00), and non-professional soccer players (N = 14; all males) trained always late in the evening (20:30–22:30). To determine the existence of RARs, the activity counts (A.C.) data were analyzed using the single and the population mean cosinor method; a one-way analysis of variance (ANOVA) followed by the Tukey–Kramer post-hoc test was used for the comparison of RAR characteristics among soccer, volleyball and triathlon athletes. Partial eta squared (?_p²) was used to determine the magnitude of the effect for significant outcomes (α = 0.05) in ANOVA. The presence of a significant RAR both for each of the 43 athletes (p < 0.001) and for the three categories of athletes (p < 0.001) was observed. RARs differed among sport disciplines: the Midline Estimating Statistic of Rhythm (MESOR) was significantly higher in triathletes (mean: 347 A.C. with 95% Confidence Interval [CI]: 314–379) compared to both volleyball (mean: 188 A.C. with 95% CI: 173–203; p < 0.001) and soccer players (mean: 289 A.C. with 95% CI: 267–312; p < 0.01) with ?_p² = 0.72. Amplitude (A) values showed the same significant trend of MESOR data (ANOVA: p < 0.001; ?_p² = 0.65) while the acrophase (Φ) occurred at 18:28 for soccer players, significantly later than triathlon (15:20 h; p < 0.001) and volleyball players (16:24 h; p < 0.001) (ANOVA: p < 0.001; ?p2 = 0.84). The higher training duration and intensity reached by triathlon athletes in the morning sessions caused a phase advance of their RAR’s acrophase Φ and higher MESOR and A amplitude compared to volleyball players and triathletes. Therefore, different sport disciplines require different training schedules, training loads and intensities that translate into different RARs. Strength coaches and medical staff of professional teams should strongly consider actigraphy as a practical and powerful tool to monitor RARs, sleep behavior, and the activity levels of their athletes; highlighting potential circadian disruptions through actigraphy could be helpful to prevent musculoskeletal injuries.     

The longer the better: Sleep–wake patterns during preparation of the World Rowing Junior Championships

Recovery is essential for high athletic performance, and therefore especially sleep has been identified as a crucial source for physical and psychological well-being. However, due to early-morning trainings, which are general practice in many sports, athletes are likely to experience sleep restrictions. Therefore, this study investigated the sleep–wake patterns of 55 junior national rowers (17.7 ± 0.6 years) via sleep logs and actigraphy during a four-week training camp. Recovery and stress ratings were obtained every morning with the Short Recovery and Stress Scale on a 7-point Likert-type scale ranging from 0 (does not apply at all) to 6 (fully applies). The first training session was scheduled for 6:30 h every day. With two to four training sessions per day, the training load was considerably increased from athletes’ home training. Objective sleep measures (n = 14) revealed less total sleep time (TST) in the first two weeks (409.6 ± 19.1 and 416.0 ± 16.3 min), while training volume and intensity were higher. In the second half of the camp, less training sessions were implemented, more afternoons were training free and TSTs were longer (436.3 ± 15.8 and 456.9 ± 25.7 min). A single occasion of 1.5-h delayed bedtime and usual early morning training (6:30 h) resulted in reduced ratings of Overall Recovery (OR) (M = 3.3 ± 1.3) and greater Negative Emotional State (NES) (M = 1.3 ± 1.2, p < .05), which returned to baseline on the next day. Following an extended night due to the only training-free day, sleep-offset times were shifted from ~5:30 to ~8:00 h, and each recovery and stress score improved (p < .01). Moreover, subjective ratings of the first six days were summarised as a baseline score to generate reference data as well as to explore the association between sleep and recovery. Intercorrelations of these sleep parameters emphasised the relationship between restful sleep and falling asleep quickly (r = .34, p < .05) as well as few awakenings (r = .35, p < .05). Overall, the findings highlight the impact of sleep on subjective recovery measures in the setting of a training camp. Providing the opportunity of extended sleep (and a day off) seems the most simple and effective strategy to enhance recovery and stress-related ratings.     

Effects of an adjunctive,chronotype-based light therapy in hospitalized patients with severe burnout symptoms - a pilot study

Light therapy is a well-established treatment option for seasonal affective disorders and is effective in reducing sleep problems and daytime fatigue. Symptoms of severe burnout include feelings of exhaustion and impaired sleep and mood. Thus, light therapy seems promising for burnout treatment. So far, light therapy effects in burnout were investigated in outpatient settings only, with inconclusive results. The present study targeted light therapy effects in an inpatient setting. Participants with severe burnout were recruited in two psychosomatic clinics and randomly assigned to a control group with multimodal psychiatric treatment or an add-on light treatment group. Participants in the latter group were additionally exposed to morning bright light (illuminance: 4246 lux, irradiance: 1802.81 µW.cm^?2) for 3 weeks, 30 minutes a day, timed to their chronotypes. Light effects on burnout symptoms, depression, well-being, daytime sleepiness, sleep quality, and attentional performance were measured twice (pre-/postintervention design). Adjunctive chronotype-based bright light therapy was well tolerated and improved burnout symptoms and well-being without additional effect on severity of depression. Furthermore, reduced daytime sleepiness, improved nighttime sleep quality, a sleep phase advance of 25 minutes, shortened sleep latency, less sleep disturbances and increased sleep duration were observed in the light treatment group. No group differences were found in attentional performance. Chronotype-based bright light therapy seems to be effective in improving burnout symptoms and sleep problems in patients with severe burnout symptoms. Further studies with larger sample sizes and objective measures of sleep are necessary to confirm these preliminary results before practical recommendations can be made.