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.     

Making errors at work due to sleepiness or sleep problems is not confined to non-standard work hours: results of the 2016 Sleep Health Foundation national survey

Almost one-third of Australians report having made errors at work that are related to sleep issues. While there is significant literature investigating the role of sleep in workplace health and safety in shiftworking and nightwork operations, long working hours, work-family conflict, and commute times getting longer also impact day workers’ sleep behaviors and opportunities. The aim of this study was to examine the relationship between sleep duration and disorders, sleep health and hygiene factors, work-related factors and errors at work in Australian workers. From a sample of 1011 Australian adults, age-adjusted binary logistic regression analyses were conducted in 512 workers who provided responses to the question “Thinking about the past three months, how many days did you make errors at work because you were too sleepy or you had a sleep problem?” A number of sleep behaviors and poor sleep hygiene factors were linked with work errors related to sleepiness or sleep problems, with age-adjusted odds of errors (confidence intervals) up to 11.6 times higher (5.4–25.1, p < 0.001) in those that snored, 7.7 (4.6–12.9) times higher in those reporting more than three sleep issues (p < 0.001), 7.0 times higher (3.4–14.8) in short (≤5 hours/night) sleepers (p < 0.021), 6.1 times higher (2.9–12.7) in those staying up later than planned most nights of the week (p< 0.001) and 2.4 times higher (1.6–3.7) in those drinking alcohol ≥3 nights/week before bed (p < 0.001). More than 40% of participants working non-standard hours reported making errors at work, and they were more likely to be young (compared to the main sample of workers) and more likely to engage in work activities in the hour before bed. Sleep factors (other than clinical sleep disorders) were associated with an increased likelihood of sleep-related work errors. Both day workers and those working non-standard hours engage in work, sleep and health behaviors that do not support good sleep health, which may be impacting safety and productivity in the workplace through increased sleepiness-related errors.     

Late chronotype and high social jetlag are associated with burnout in evening-shift workers: Assessment using the Chinese-version MCTQshift

Chronotypes are associated with shift work tolerance and sleep in shift workers, and sleep mediates the impact of shift work on mental health. However, the role of chronotype in the association between shift work and mental health has not been clarified. In this study, we aimed to examine the association between chronotype and burnout in shift workers, using the validated Munich ChronoType Questionnaire for shift workers (MCTQ^shift). A total of 288 shift workers with irregular shift frequencies were recruited and completed the Chinese-version MCTQ^shift and the Morningness–Eveningness Questionnaire (MEQ). Chronotypes were assessed by the calculation of corrected mid-sleep time (MSF_SC) from mid-sleep time on free days (MSF) based on their exact shift schedules. Another 26 evening-shift nurses were monitored with actigraphy for at least two consecutive evening shifts and the following two free days. Burnout was evaluated using the Copenhagen Burnout Inventory. We found that MSF^E_SC, MSF^E and mid-sleep time on workdays (MSW^E) had normal distributions and correlated significantly with MEQ scores (r = ? 0.47, ?0.45 and ?0.47, respectively; all p < 0.001). MSW was more closely correlated with actigraphy-derived mid-sleep time on the free day before workdays than that on workdays (r = 0.61 and 0.48, respectively, p < 0.05). Sleep duration was significantly longer on workdays among evening-shift workers who slept late on workdays than those who slept early (β = 0.59, p < 0.001). After demographic and work characteristics were adjusted for in linear regression models, late chronotype and high social jetlag were associated with burnout scores in evening-shift workers. In conclusion, the Chinese-version MCTQ^shift is a valid tool for chronotype assessment. Interventions to improve sleep in shift workers should be tailored to chronotype due to variations in sleep behavior. Late chronotype may be an inherent feature of mental health problems, because the association with burnout was significant in both day workers in previous studies and shift workers.     

Coping with shift work-related circadian disruption: A mixed-methods case study on napping and caffeine use in Australian nurses and midwives

ABSTRACT

Introduction: Two of the most ubiquitous fatigue countermeasures used by shift-working nurses are napping and caffeine. This mixed-methods case study investigated the ways nurses and midwives utilised napping and caffeine countermeasures to cope with shift work, and associated sleep, physical health and psychological health outcomes.

Materials and Methods: N = 130 Australian shift-working nurses and midwives (mean age = 44 years, range = 21–67, 115F, 15M) completed the Standard Shiftwork Index. A sub-set of 22 nurses and midwives completed an in-depth interview.

Results: Nearly 70% of participants reported napping. Those who napped during night shifts had significantly less total sleep time before (F_2,75 = 5.5, p < 0.01) and between days off (F_2,82 = 3.9, p < 0.05). By the end of the night shift, average hours of time awake were significantly less for prophylactic and on-shift nappers compared to non-nappers (F_2,85 = 97.2, p < 0.001). Since starting shift work, the percentage of high caffeine consumers (>400 mg/day) increased from 15% to 33% of the sample and an average of 4 (SD = 2) caffeinated beverages per day was reported. Increased caffeine consumption was associated with greater sleep disturbance (r = 0.26, p < 0.05), psychological distress (r = 0.37, p < 0.001), abdomen pain (r = 0.27, p < 0.05) and weight gain since starting shift work (r = 0.25, p < 0.05). Interviews confirmed these relationships and revealed that caffeine consumption on night shift was common, whereas napping on night shift was dependent on a number of factors including ability to sleep during the day.

Conclusion: This study identified reasons shift workers chose to engage in or abstain from napping and consuming caffeine, and how these strategies related to poor sleep and health outcomes. Further research is required to help develop recommendations for shift workers regarding napping and caffeine consumption as fatigue countermeasures, whilst taking into account the associated hazards of each strategy.     

Permanent night workers´ sleep and psychosocial factors in hospital work. A comparison to day and shift work

ABSTRACT

We aimed to study whether permanent night workers sleep and psychosocial factors differ from day workers and shift workers. The participants (n = 9 312, 92% females, average age 45 years, most commonly nurses and departmental secretaries) were day workers (DW, n = 2 672), shift workers (SW, n = 6 486) and permanent night workers (PNW, n = 154). The Finnish Public Sector survey responses from six hospital districts from 2012 were combined to payroll data from 91 days preceding the survey. The data were analyzed using Pearson χ²-test, one-way ANOVA and multinomial logistic regression analysis. The PNWs reported slightly longer average sleep length than the SWs or the DWs (7:27 vs. 7:13 and 7:10 h, p < 0.001). The PNWs reported least often difficulties in maintaining sleep (p < 0.001) compared to the SWs and the DWs. The PNWs reported most often difficulties to fall asleep and fatigue during free-time (p-values <0.001). The DWs and PNWs experienced less often work-life conflict than the SWs (25 and 26 vs. 38%, p < 0.001). The PNWs were more often satisfied with autonomy at work and appreciation and fair treatment by colleagues than the DWs or the SWs (p < 0.001). The SWs and PNWs reported remarkably higher occurrence of verbal (p < 0.001, OR 3.71, 95% CI 3.23–4.27 and OR 7.67, 95% CI 5.35–10.99, respectively) and physical workplace violence (p < 0.001, OR 9.24, 95% CI 7.17–11.90 and OR 28.34, 95% CI 16.64–43.06, respectively) compared to DWs. Conclusively, PNWs reported contradictory differences in sleep quality compared to DWs and SWs. PNWs are more often satisfied with their colleagues and autonomy at work than DWs or SWs but face workplace violence remarkably more often.     

IMPLEMENTATION OF 12-HOUR SHIFTS IN A BRAZILIAN PETROCHEMICAL PLANT: IMPACT ON SLEEP AND ALERTNESS

A recent worldwide trend in chemical and petrochemical industries is to extend the duration of shifts. Optimization of the labor force to reduce costs is one reason to increase the length of working time in a shift. Implementation of 12h shifts is a controversial decision for managers and scientists. Literature reviews show alertness is lower during the nighttime hours, and sleep duration is reduced and worse during the daytime. The main objective of this study was to evaluate the impacts of 12h shifts on alertness and sleep. To evaluate the duration and quality of sleep and alertness during work, 22 male shift workers on a continuous rotating schedule at a petrochemical plant completed activity logs and estimated alertness using analog 10-cm scales for 30 consecutive days, three times (at 2h, 6h, and 10h of the shift) every work shift. Statistical tests (analysis of variance [ANOVA] and Tukey) were performed to detect differences between workdays and off days. The shift schedule was 2 days/3 nights/4 off days, followed by 3 days/2 nights/5 off days, followed by 2 days/2 nights/5 off days. Sleep duration varied significantly (p <. 001) among the work shifts and off days. Comparing work nights, the shortest mean sleep occurred after the second night (mean = 311.4 minutes, SD = 101.7 minutes), followed by the third night (mean = 335.3 minutes, SD = 151.2 minutes). All but one shift (sleep after the first work night) were significantly different from sleep after the first 2 workdays (p <. 002). Tukey tests showed no significant differences in sleep quality between workdays and nights, with the exception of sleep after the third day compared to sleep after night shifts. However, significant differences were detected between off days and work nights (p <. 01). ANOVA analysis showed borderline differences among perceived alertness during day shifts (p =. 073) and significant differences among the hours of theshifts(p =. 0005), especially when comparing the 2nd hour of the first day with the 10th hour of all the day shifts. There were no significant differences in perceived alertness during night work among the first, second, and third nights (p =. 573), but there were significant differences comparing the times (2nd, 6th, 10th hour) of the night shifts (p ≤. 001). The evaluation of sleep (duration and quality) and level of alertness have been extensively used in the literature as indicators of possible performance decrements at work. The results of this study show poorer sleep after and significantly decreased alertness during night work. Shifts of 12h are usually implemented for technical and economic reasons. These results point out the necessity of a careful trade-off between the financial and technical gains longer shifts might bring and the possible losses due to incidents or accidents from performance decrements during work. (Chronobiology International, 17(4), 521–537, 2000)     

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.     

Sleep,Sleepiness, Fatigue,and Performance of 12-Hour-Shift Nurses

Nurses working 12-h shifts complain of fatigue and insufficient/poor-quality sleep. Objectively measured sleep times have not been often reported. This study describes sleep, sleepiness, fatigue, and neurobehavioral performance over three consecutive 12-h (day and night) shifts for hospital registered nurses. Sleep (actigraphy), sleepiness (Karolinska Sleepiness Scale [KSS]), and vigilance (Performance Vigilance Task [PVT]), were measured serially in 80 registered nurses (RNs). Occupational fatigue (Occupational Fatigue Exhaustion Recovery Scale [OFER]) was assessed at baseline. Sleep was short (mean 5.5?h) between shifts, with little difference between day shift (5.7?h) and night shift (5.4?h). Sleepiness scores were low overall (3 on a 1–9 scale, with higher score indicating greater sleepiness), with 45% of nurses having high level of sleepiness (score ?>?7) on at least one shift. Nurses were progressively sleepier each shift, and night nurses were sleepier toward the end of the shift compared to the beginning. There was extensive caffeine use, presumably to preserve or improve alertness. Fatigue was high in one-third of nurses, with intershift fatigue (not feeling recovered from previous shift at the start of the next shift) being most prominent. There were no statistically significant differences in mean reaction time between day/night shift, consecutive work shift, and time into shift. Lapsing was traitlike, with rare (39% of sample), moderate (53%), and frequent (8%) lapsers. Nurses accrue a considerable sleep debt while working successive 12-h shifts with accompanying fatigue and sleepiness. Certain nurses appear more vulnerable to sleep loss than others, as measured by attention lapses. (Author correspondence: jgeiger@son.umaryland.edu)     

Building‐Site Camps and Extended Work Hours: A Two‐Week Monitoring of Self‐Reported Physical Exertion,Fatigue, and Daytime Sleepiness

Large‐scale construction work often requires people to work longer daily hours and more than the ordinary five days in a row. In order to minimize transportation times and optimize the use of personnel, workers are sometimes asked to live in temporary building‐site camps in the proximity of the work site. However, little is known about the biological and psychological effects of this experience. The objective of the present study was to investigate whether exposure to long work hours and extended workweeks while living in building‐site camps in between work shifts was associated with a build‐up of increased complaints of poor sleep, daytime sleepiness, physical exertion, and fatigue across a two‐week work cycle. Two groups of construction workers were examined. The camp group of 13 participants (mean age: 42±11 S.D. yrs) lived in building‐site camps and worked extended hours (between 07:00 and 18:00 h) and extended workweeks (six days in a row, one day off, five days in a row, nine days off). The home group of 16 participants (mean age 40±9 yrs) worked ordinary hours between 07:00 and 15:00 h and returned home after each workday. Self‐ratings of daytime sleepiness (Karolinska Sleepiness Scale), physical exertion (Borg CR‐10), and mood were obtained six or seven times daily during two workweeks. Fatigue ratings were obtained once daily in the evening, and ratings of sleep disturbances were obtained once daily in the morning with the Karolinska Sleep Diary. Data were evaluated in a repeated measures design. The results showed that both groups reported a similar level of daytime sleepiness, physical exertion, and mood across workdays and time points within a workday (all three‐way interactions had p>0.898). Although the home group reported earlier wake‐up times, the pattern of sleep disturbance ratings across the workdays did not differ between the groups. Both groups reported few sleep disturbances and good mood. However, the camp group reported higher physical exertion already at the start of work and showed a more gentle increase in ratings during the work shift and a smaller decline between the end of work and bedtime. The camp group also reported higher fatigue scores than the home group. However, none of the groups showed signs of increasing ratings in the progress of the two workweeks. For both groups, the ratings of daytime sleepiness formed a U‐shaped pattern, with the highest scores at awakening and at bedtime. Yet, the camp group reported higher daytime sleepiness than the home group at lunch break and at the second break in the afternoon. In conclusion, there were no signs of fatigue build‐up or accumulation of daytime sleepiness, physical exertion, or sleep disturbances in either group. Despite the fact that the camp group showed some signs of having trouble in recuperating in between work shifts, as indicated by the higher physical exertion ratings at the start of work, higher fatigue scores, and higher daytime sleepiness, the results constitute no real foundation for altering the camp group's current work schedule and living arrangements.     

Sleep, sleepiness, fatigue, and performance of 12-hour-shift nurses

Nurses working 12-h shifts complain of fatigue and insufficient/poor-quality sleep. Objectively measured sleep times have not been often reported. This study describes sleep, sleepiness, fatigue, and neurobehavioral performance over three consecutive 12-h (day and night) shifts for hospital registered nurses. Sleep (actigraphy), sleepiness (Karolinska Sleepiness Scale [KSS]), and vigilance (Performance Vigilance Task [PVT]), were measured serially in 80 registered nurses (RNs). Occupational fatigue (Occupational Fatigue Exhaustion Recovery Scale [OFER]) was assessed at baseline. Sleep was short (mean 5.5?h) between shifts, with little difference between day shift (5.7?h) and night shift (5.4?h). Sleepiness scores were low overall (3 on a 1-9 scale, with higher score indicating greater sleepiness), with 45% of nurses having high level of sleepiness (score >?7) on at least one shift. Nurses were progressively sleepier each shift, and night nurses were sleepier toward the end of the shift compared to the beginning. There was extensive caffeine use, presumably to preserve or improve alertness. Fatigue was high in one-third of nurses, with intershift fatigue (not feeling recovered from previous shift at the start of the next shift) being most prominent. There were no statistically significant differences in mean reaction time between day/night shift, consecutive work shift, and time into shift. Lapsing was traitlike, with rare (39% of sample), moderate (53%), and frequent (8%) lapsers. Nurses accrue a considerable sleep debt while working successive 12-h shifts with accompanying fatigue and sleepiness. Certain nurses appear more vulnerable to sleep loss than others, as measured by attention lapses.     

Sleep on the Job Partially Compensates for Sleep Loss in Night‐Shift Nurses

Nursing personnel in Brazil are usually submitted to fixed 12 h shifts with no consecutive working days or nights. Moonlighting is common in this group, with a consequent increase in the number of working hours. The possibility of sleeping on the job during the night shift in the studied hospitals had already been described. The present study aims to analyze whether the time devoted to daily activities (sleep, rest, leisure, housework, commuting, personal needs, care of children or other people, non‐paid work, and study) is related to the number of worked hours and to nap‐taking during the night shift. The field study took place at two public hospitals in Rio de Janeiro, Brazil. Workers filled out a structured form on time devoted to the above‐mentioned activities for at least four consecutive days. The time devoted to sleep was analyzed according to its occurrence at home or on the job. Workers were classified according to the number of jobs (one job/two jobs) and the time dedicated to work according to the median of the whole series (below the median/above the median). All workers who had at least one working night were analyzed as to nap‐taking on the job. They were classified according to the sleep occurrence during the night shift—the sleep group and the non‐sleep group, both of which were compared to daytime workers. Statistical treatment of data included non‐parametrical procedures. The study group comprised 144 workers (mean age: 35.7±10.5 years old; 91% women; 78% nurse assistants, the remainder registered nurses). They recorded their daily activities for 4–11 days; 829 cumulative days were analyzed for the whole group. A total of 165 working nights were analyzed; sleep or rest occurred during 112 (68%) of them, with mean sleep/rest duration of 141±86 min. Time devoted to sleep and leisure varied according to the number of working hours, being significantly reduced in those submitted to longer work hours (p<0.001 and p=0.002, respectively). Results close to significance point to a reduction in the time dedicated to housework among workers with long work hours (p=0.053). The time spent on sleep/rest per working night did not differ according to the number of worked hours (p=0.490). A tendency was observed for those who have two jobs to devote more time to sleep/rest on the job (p=0.058). The time of personal needs was significantly lower among those who did not sleep on the job as compared to day workers (p=0.036). The total sleep time was significantly lower among those who did not sleep on the job, as compared to day workers and to those who slept on the job (p=0.004 and p=0.05, respectively). As to home sleep length, workers who slept and those who did not sleep on the job were similar and slept significantly less than exclusively daytime workers (p<0.001 and p=0.002, respectively). Sleeping on the job during the night shift seems to partially compensate for the shorter sleep at home among night workers and may play a beneficial effect in coping with two jobs.     

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.     

Fatigue and Mood Correlates of Sleep Length in Three Age‐Social Groups: School Children,Students, and Employees

The aim of the study was to trace the consequences of insufficient sleep, in terms of chronic sleep reduction rather than acute sleep deprivation, on fatigue, mood, cognitive performance self‐estimations, and daytime sleepiness in different age‐social groups. The age group of the subjects reflects their social situation and their working time organization: adolescents (n=191) obeyed the strict school schedules with starting times often before 08:00 h; university students (n=115) had more flexible timetables; young employees (n=126) were engaged in regular morning schedules or irregular daytime hours or day and night shifts. A questionnaire study determined the declared need of sleep, self‐reported sleep length, chronic fatigue (using a scale comprised of eight fatigue symptoms and four mood and three cognitive items), and daytime sleepiness (Epworth Sleepiness Scale). The declared need for sleep decreased in subsequent age groups from 9 h 23 min in school children to 8 h 22 min in university students and to 7 h 37 min in young employees. Consequently, the discrepancy between preferred and real sleep length (sleep deficit) was the largest in adolescents: 106 min. Females showed a greater need of sleep than males (p=.025) and significantly more fatigue, mood, and cognitive problems; they also exhibited higher level of daytime sleepiness (p<.000). The sleep index (reported sleep length related to requirements) correlated significantly with all health issues in women (p<.000), while only with fatigue symptoms in men (p=.013). Actual sleep length was unrelated to mood and fatigue issues; the declared individual need of sleep and sleep index showed significant associations, especially in the group of adolescents. The most frequent complaints of adolescents included tiredness on awakening (46%), nervousness, and general weakness; university students reported excessive drowsiness (50%), tension, and nervousness; employees suffered mostly from negative moods, such as tension (49%), nervousness, and irritability. The findings of the study indicate that chronic sleep loss seems to affect females more severely than males. The associations of fatigue and mood with sleep need and sleep index were more pronounced in younger subjects. Surprisingly, fatigue symptoms in school children and university students were as frequent as in hard‐working adults. Because the problem of insufficient sleep is already present in youngsters, their work time organization needs more attention.     

Sleep and Sleepiness of Fishermen on Rotating Schedules

Seafaring is a hazardous occupation with high death and injury rates, but the role of seafarer fatigue in these events is generally not well documented. The International Maritime Organization has identified seafarer fatigue as an important health and safety issue. Most research to date has focused on more regularly scheduled types of operations (e.g., merchant vessels, ferries), but there is relatively little information on commercial fishing, which often involves high day‐to‐day and seasonal variability in work patterns and workload. The present study was designed to monitor the sleep and sleepiness of commercial fishermen at home and during extended periods at sea during the peak of the hoki fishing season, with a view to developing better fatigue management strategies for this workforce. Sleep (wrist actigraphy and sleep diaries) and sleepiness (Karolinska Sleepiness Scale [KSS] before and after each sleep period) of 20 deckhands were monitored for 4–13 days at home and for 5–9 days at sea while working a nominal 12 h on/6 h off schedule. On the 12 h on/6 h off schedule, there was still a clear preference for sleep at night. Comparing the last three days at home and the first three days at sea showed that fishermen were more likely to have split sleep at sea (Wilcoxon signed ranks p<0.001), but the median sleep/24 h did not differ significantly by location (5.9 h at sea vs. 6.7 h at home). However, on 23% of days at sea, fishermen obtained<4 h total sleep/24 h, compared to 3% of days at home (p(χ²)<0.01). Sleep efficiency, mean activity counts/min sleep, and subjective ratings of sleep quality did not differ significantly between the last three days at home and the first three days at sea. However, sleepiness ratings remained higher after sleep at sea (Wilcoxon signed ranks p<0.05), with fishermen having post‐sleep KSS ratings ≥7 on 24% of days at sea vs. 9% of days at home (Wilcoxon signed ranks p<0.01). This work adds to the limited number of studies that objectively monitored the sleep of seafarers. It has the strength of operational fidelity but the weakness that large inter‐ and intra‐individual variability in sleep, combined with the small sample size, limited the power of the study to detect statistically significant differences between sleep at home and at sea. The clear preference for sleep at night during the 12 h on/6 h off schedule at sea is consistent with the expectation that this 18 h duty/rest cycle is outside the range of entrainment of the circadian pacemaker. High levels of acute sleep loss, and residual sleepiness after sleep, were much more common at sea than at home. The longer duration of trips during the peak of the fishing season increases the risk of performance impairment due to greater cumulative sleep loss than would be expected on typical three‐day trips. Key fatigue management strategies in this environment include that fishermen report to work as well rested as possible. Once at sea, the day‐to‐day variability in activities due to uncontrollable factors, such as fishing success, repairing gear, and weather conditions, mean that contingency planning is required for managing situations where the entire crew have experienced long periods of intensive work with minimum recovery opportunities.     

When Does Stress End? Evidence of a Prolonged Stress Reaction in Shiftworking Truck Drivers

This study aimed to analyze individual cortisol levels in relation to work conditions, sleep, and health parameters among truck drivers working day shifts (n?=?21) compared to those working irregular shifts (n?=?21). A total of 42 male truck drivers (39.8?±?6.2 yrs) completed questionnaires about sociodemographics, job content, work environment, health, and lifestyle. Rest-activity profiles were measured using actigraphy, and cardiovascular blood parameters were collected. Salivary cortisol samples were obtained: (i) at waking time, (ii) 30?min after waking, and (iii) at bedtime, during both one workday and one day off from work. Irregular-shift workers, compared to day-shift workers, showed significantly higher waist-hip ratio, very-low-density lipoprotein (VLDL) cholesterol, tiredness after work, years working as a driver, truck vibration, and less job demand (p?<?.05). High cortisol levels in irregular-shift workers were correlated with certain stressors, such as short sleep duration and low job satisfaction, and to metabolic parameters, such as total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), VLDL, and triglycerides. Day-shift workers had higher cortisol levels collected 30?min after waking (p?=?.03) and a higher cortisol awakening response (CAR; p?=?.02) during workdays compared to off days. Irregular-shift workers had higher cortisol levels on their off days compared to day-shift workers (p?=?.03). In conclusion, for the day-shift workers, a higher cortisol response was observed on workdays compared to off days. Although no direct comparisons could be made between groups for work days, on off days the irregular-shift workers had higher cortisol levels compared to day-shift workers, suggesting a prolonged stress response in the irregular-shift group. In addition, cortisol levels were correlated with stressors and metabolic parameters. Future studies are warranted to investigate further stress responses in the context of irregular work hours. (Author correspondence: crmoreno@usp.br)     

Delaying and Extending Sleep During Weekends: Sleep Recovery or Circadian Effect?

There is a well-known tendency to delay and prolong our sleep during weekends (Saturday and Sunday), with an advance and reduction of sleep during workdays (Monday to Friday). The objective of this work was to determine if the changes of sleep during weekends are produced by a partial sleep deprivation or a lack of entraining of circadian rhythms to an advanced phase, during workdays. The subjects were 52 undergraduate female students, mean age = 17.5 years, SD = 1.32. All students attended school following a regular schedule, from Monday to Friday. Two groups of students were studied: one attended school from 07:00 to 12:00 h (morning group, n = 30); the other attended school from 14:00 to 18:00 (afternoon group, n = 22). None of the students worked or was engaged in other activity with a fixed schedule. All kept a sleep-wake diary for 2 weeks, in which they recorded their bedtimes, wakeup times, and sleep-onset latencies. The morning group delayed 47.4 min [t(29) = 4.72, p < 0.0001] and prolonged their sleep 118.2 min [t(29) = 9.4, p < 0.0001] during weekends. Although the afternoon group had the opportunity to maintain a delayed phase and a long sleep time throughout the week, they delayed their bedtime by 24 min [t(21) = 2.99, p < 0.01] during weekends, without changing their sleep duration. The findings suggest that the prolonged sleep during weekends is due to reduction of sleep during workdays, whereas the delay of bedtime seems to be associated with a tendency of the human circadian system to maintain a delayed phase     

Social jetlag negatively correlates with academic performance in undergraduates

Discrepancies between sleep timing on workdays and weekends, also known as social jetlag (SJL), affect the majority of the population and have been found to be associated with increased health risk and health-impairing behaviors. In this study, we explored the relationship between SJL and academic performance in a sample of undergraduates of the Semmelweis University. We assessed SJL and other sleep-related parameters with the Munich ChronoType Questionnaire (MCTQ) (n?=?753). Academic performance was measured by the average grade based on weekly test results as well as scores acquired on the final test (n?=?247). The average mid-sleep point on free days in the Hungarian sample fits well the regression line plotted for longitudes within the Central European Time Zone and chronotypes, confirming that sunlight has a major impact on chronotype. Multivariate analysis showed negative effect of SJL on the weekly average grade (p?=?0.028, n?=?247) during the lecture term with its highly regular teaching schedules, while this association disappeared in the exam period (p?=?0.871, n?=?247) when students had no scheduled obligations (lower SJL). We also analyzed the relationship between the time of the weekly tests and academic performance and found that students with later sleep times on free days achieved worse in the morning (p?=?0.017, n?=?129), while the inverse tendency was observed for the afternoon test-takers (p?=?0.10, n?=?118). We did not find significant association between academic performance and sleep duration or sleep debt on work days. Our data suggest that circadian misalignment can have a significant negative effect on academic performance. One possible reason for this misalignment is socially enforced sleep times.     

Time preference of headache attack and chronotype in migraine and tension-type headache

ABSTRACT

Migraine attacks have a time preference of headache attack (TPHA). Chronotype is the propensity for an individual to sleep at a particular time during a 24-h period. However, limited evidence exists regarding the association between TPHA and chronotype in individuals with migraine or tension-type headache (TTH). The aim of the present study is to investigate TPHA and chronotype in individuals with migraine and TTH, which are two of the most common primary headaches. One hundred sixty-nine first-visit migraine and TTH participants were consecutively enrolled. Information on sleep onset time and wake up time on workdays and free days, and TPHA were investigated with a face-to-face interview using a questionnaire booklet. Chronotype was assessed, using the midpoint of sleep on free days, corrected for sleep extension on free days (MSFsc), by subtracting one-half of the average weekly sleep duration. Headache frequency per month, headache intensity, impact of headache, sleep quality, daytime sleepiness, insomnia severity, and mood status were also assessed. Time preference of headache attack was reported for 45.5% and 44.8% of participants with migraine and TTH, respectively. Migraineurs with TPHA had an earlier MSFsc than did migraineurs without TPHA (1:18 a.m. ± 282 min vs. 4:18 a.m. ± 186 min; p = .022). Among migraineurs with TPHA, a later MSFsc was associated with a later preferential time of attack (β = 1.3, 95% confidence interval [CI] = 0.6–2.1, p = .004). A later MSFsc was significantly correlated with a higher headache frequency per month among migraineurs with TPHA (β = 1.9, 95% CI = 0.3–3.4, p = .023), but was not significantly correlated among migraineurs without TPHA (β = 1.4, 95% CI ?1.7–4.4, p = .332). Among TTH participants with TPHA, MSFsc was not significantly associated with a preferential time of attack (β = ?0.2, 95% CI = ?1.0 to 0.6, p = .611). Headache frequency was not associated with MSFsc among TTH participants with TPHA (β = 0.2, 95% CI = ?1.2 to 1.6, p = .792) or among TTH participants without TPHA (β = 0.4, 95% CI = ?0.5 to 1.3, p = .354). In conclusion, approximately one-half of participants with migraine and TTH reported having TPHA. Migraineurs with TPHA had an earlier chronotype than did migraineurs without TPHA. A later chronotype was associated with increased headache frequency and a later time of attack among migraineurs with TPHA. Among participants with TTH, TPHA and headache frequency were not significantly associated with chronotype.     

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.