When Work Calls—Associations Between Being Contacted Outside of Regular Working Hours for Work-Related Matters and Health

Boundaries between work and private life are diminishing, but little is known on how this influences worker health. Therefore, we examined the association between work-related contacts outside of regular working hours by e-mail or phone and self-reported health in a representative sample of European employees (n?=?23 760). The risk of reporting ≥1 health problem(s) was increased in workers contacted sometimes (odds ratio [OR]: 1.16, 95% confidence interval [CI]: 1.06–1.27) or often (OR: 1.23, 95% CI: 1.12–1.34) as compared with never, controlling for several demographic and workplace characteristics. Further research is needed to quantify work and nonwork patterns and their health effects.     

Factors associated with sleep duration in Brazilian high school students

The aim of this study was to investigate the factors associated with short sleep duration on southern Brazilian high school students. Our study was comprised of 1,132 adolescents aged 14 to 19 years, enrolled in public high schools in São José, Brazil. The students answered a questionnaire about working (work and workload), health perception, smoking, school schedule, sleep (duration and daytime sleepiness), and socio-demographics data. The results showed that more than two thirds of adolescent workers had short sleep duration (76.7%), and those with a higher workload (more than 20 hours) had a shorter sleep duration (7.07 hours) compared to non-workers (7.83 hours). In the analysis of factors associated with short sleep duration, adolescents who worked (OR = 2.12, 95% CI 1.53 to 2.95) were more likely to have short sleep duration compared to those who did not work. In addition, older adolescents (17–19 years) and students with poor sleep quality were 40% and 55% more likely to have short sleep duration compared to younger adolescents (14–16 years) and students with good sleep quality, respectively. Adolescents with daytime sleepiness were more likely to have short sleep duration (OR = 1.49, 95% CI 1.06 to 2.07) compared to those without excessive daytime sleepiness. In addition students of the morning shift (OR = 6.02, 95% CI 4.23 to 8.57) and evening shift (OR = 2.16, 95% CI 1.45 to 3.22) were more likely to have short sleep duration compared to adolescents of the afternoon shift. Thereby adolescents who are workers, older, attended morning and evening classes and have excessive daytime sleepiness showed risk factors for short sleep duration. In this sense, it is pointed out the importance of raising awareness of these risk factors for short sleep duration of students from public schools from São José, located in southern Brazil.     

Association of Sickness Absence with Poor Sleep and Depressive Symptoms in Shift Workers

A cross-sectional study was conducted to evaluate the contribution of daily sleep habits and depressive symptoms to sickness absences of shift workers. A self-administered questionnaire that solicited answers about sleep, symptoms of depression, sickness absence, diseases/injuries, and lifestyle factors was submitted to a sample of 522 rotating shift workers between the ages of 18–59 (mean 27) yrs of an electric equipment manufacturing company. The seven features of sleep queried were daily hours of sleep, time to fall asleep, awakening during sleep, early morning awakening, sleep well at night, sufficiency of sleep, and excessive daytime sleepiness at work. The responses were assessed over the subject's previous 1-yr period. Each sleep feature, except daily sleeping hours, was dichotomized by the following responses: (1) taking more than 30 min to fall asleep (difficulty initiating sleep; DIS), (2) awakening during sleep almost every day (difficulty maintaining sleep; DMS), (3) early morning awakening almost every day (EMA), (4) sleeping very poorly or not so well at night, (5) definite or somewhat insufficient nightly sleep, and (6) excessive daytime sleepiness at work almost every day (EDS). Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression (CES-D) scale. Sickness absence was calculated by asking subjects “How many days in total have you been absent from work due to sickness, including paid vacation, in the last 1-yr period?” The responses were divided into three groups that included no (0 days) sickness absences (reference group, n = 235 subjects), 1 to 4 days (short-term, n = 199 subjects), and 5 days or more (long-term, n = 88 subjects). Compared to the prevalence of sleep features of the reference group, workers with short-term absence showed a significantly higher prevalence of EMA with an odds ratio (OR) of 5.3, 95% confidence interval (CI) 1.3–22.0. Long-term absence was significantly associated with DMS (OR = 2.1, 95%CI 1.0–4.6), EMA (OR = 5.6, 95%CI 1.0–28.7), sleeping poorly at night (OR = 2.6, 95%CI 1.4–5.0), and high depressive symptoms (OR = 2.0, 95%CI 1.0–3.7) according to the CES-D score of ≥16, after adjusting for multiple confounding variables. These data point to an association between both the parameters of poor sleep and symptoms of deep depression when self-reported sickness absence is frequent. The association is particularly strong with long-term absence in male shift workers.     

Effects of 6/6 and 4/8 Watch Systems on Sleepiness among Bridge Officers

During the last ten years, severe sleepiness or falling asleep by watch keeping officers has been a direct or a contributing factor in a number of maritime accidents. This study examined the relationship between two watch systems and its impact on fatigue and sleepiness in bridge officers. A questionnaire and a sleep/work diary were sent to a representative sample of the Finnish Maritime Officer Association. In all, 185 bridge officers answered the questionnaire on sleep, work hours, and safety, including the Skogby Excessive Daytime Sleepiness index (SEDS); 42% of the bridge officers worked two 4 h watches (4/8) per day, while 26% worked two 6 h watches per day (6/6). Ninety‐five of the participants completed a sleep diary for seven consecutive days while at sea. The timing of the watch duties and sleep was recorded, as was subjective sleepiness every 2 h using the Karolinska Sleepiness Scale (KSS). 17.6% of the participants had fallen asleep at least once while on duty during their career. Compared to the 4/8 watch system, the officers working the 6/6 watch system reported shorter sleep durations, more frequent nodding‐off on duty (7.3% vs. 1.5%), and excessive sleepiness (32% vs. 16% with SEDS>14). Based on a logistic regression analysis, high SEDS was significantly related with probable obstructive sleep apnea (OR 5.7), the 6/6 watch system (OR 4.0), and morningness‐eveningness while controlling simultaneously several individual and sleep‐related factors. Subjective sleepiness (KSS) was highest at 04:00 and 06:00 h. In a multivariate analysis, the KSS was significantly related to time of day, time after awaking, sleep length, and interactions of the watch systems with age, morningness‐eveningness, and Epworth sleepiness scale (ESS) score. Severe sleepiness at 04:00–06:00 h was especially problematic in the 6/6 watch system among evening types and among the bridge officers with high ESS. The results suggest the 6/6 watch system is related to a higher risk of severe sleepiness during the early morning hours compared to the 4/8 and the other watch systems assessed.     

Health effects of supplemental work from home in the European Union

Internationalization and technological developments have changed the work organization in developed and developing industrial economies. Information and communication technologies, such as computers and smartphones, are increasingly used, allowing more temporal and spatial flexibility of work. This may lead to an increase in supplemental work, i.e. constant availability or working in addition to contractually agreed work hours. This in turn extends work hours and leads to work hours in evenings and weekends, causing interferences of work hours with biological and social rhythms for sleep, recovery and social interaction. However, empirical findings on the effects of supplemental work and work hours on occupational health are rather scarce. Therefore, the aim of this study was to investigate the association between (1) work-related contacts outside of regular work hours and (2) working in the free time with self-reported work-related health impairments in the fourth and fifth European Working Conditions Surveys (EWCS 2005, EWCS 2010). Out of these cross-sectional, large-scale surveys, data on n?=?22?836 and n?=?34?399 employed workers were used for weighted logistic regression analyses. About half of the sample reported at least occasional supplemental work. The results showed an increased risk of reporting at least one health problem for employees who had been contacted by their employer (EWCS 2005), or worked in their free time to meet work demands (EWCS 2010) in the last 12 months, compared to those reporting no supplemental work or work-related contacts during free time. These results were controlled for demographic variables, physical and mental work load, worker autonomy, and several work hours characteristics (e.g. hours per week, unusual and variable hours). The risk of reporting health problems was increased by being contacted both sometimes (Odds Ratio [OR] 1.26, 95% Confidence Interval [CI] 1.14–1.39) and often (OR 1.13, 95% CI 1.02–1.25), whereas the frequency of working in the free time showed a clear dose-response effect (sometimes: OR 1.14, 95% CI 1.04–1.24; often: OR 1.60, 95% CI 1.47–1.75), both compared to the category “never”. The findings, thus, indicate that even a small amount of supplemental work beyond contractually agreed work hours may increase the risk of work-related health impairments. Working in the free time was associated with a substantial risk increase and might be a better indicator for actual work load than being contacted by the employer outside of contractually agreed work hours. Thus, in order to minimize negative health effects, availability requirements for employees outside their regular work hours should be minimized. While these effects definitely need further study, especially regarding a quantification of actual supplemental work and its temporal location, addressing the company culture and using incentives and policies might be options to reduce the amount of supplemental work and maintain the risks of health impairments in the working population at a lower level.     

Sleep and Sleepiness among Working and Non‐Working High School Evening Students

The aim of this study was to evaluate patterns of sleepiness, comparing working and non‐working students. The study was conducted on high school students attending evening classes (19:00–22:30 h) at a public school in São Paulo, Brazil. The study group consisted of working (n=51) and non‐working (n=41) students, aged 14–21 yrs. The students answered a questionnaire about working and living conditions and reported health symptoms and diseases. For seven consecutive days, actigraphy measurements were recorded, and the students also filled in a sleep diary. Sleepiness ratings were given six times per day, including upon waking and at bedtime, using the Karolinska Sleepiness Scale. Statistical analyses included three‐way ANOVA and t‐test. The mean sleep duration during weekdays was shorter among workers (7.2 h) than non‐workers (8.8 h) (t=4.34; p<.01). The mean duration of night awakenings was longer among workers on Tuesdays and Wednesdays (28.2 min) and shorter on Mondays (24.2 min) (t=2.57; p=.03). Among workers, mean napping duration was longer on Mondays and Tuesdays (89.9 min) (t=2.27; p=.03) but shorter on Fridays and Sundays (31.4 min) (t=3.13; p=.03). Sleep efficiency was lower on Fridays among non‐workers. Working students were moderately sleepier than non‐workers during the week and also during class on specific days: Mondays (13:00–15:00 h), Wednesdays (19:00–22:00 h), and Fridays (22:00–00:59 h). The study found that daytime sleepiness of workers is moderately higher in the evening. This might be due to a work effect, reducing the available time for sleep and shortening the sleep duration. Sleepiness and shorter sleep duration can have a negative impact on the quality of life and school development of high school students.     

Relationships between daytime sleepiness and sleep quality,duration, and phase among school-aged children: a cross-sectional survey

A cross-sectional survey was conducted to simultaneously evaluate sleep quality, duration, and phase in school-aged children and correlations between each dimension of sleep and daytime sleepiness were comprehensively examined. A cross-sectional survey was conducted with school-aged children enrolled in four public elementary schools in Joetsu city, Niigata prefecture in Japan (n = 1683). Among the collected responses (n = 1290), 1134 valid responses (547 boys and 587 girls) were analyzed (valid response rate was 87.90%). Data on daytime sleepiness, sleep quality (problems in sleeping at night), sleep duration (the average sleeping time during a week), and sleep phase (sleep timing: bedtime and rising time on weekdays, and sleep regularity: differences in bedtime and rising time between on weekdays and weekends) were collected. The results of multivariate logistic regression analysis indicated that the following dimensions were significantly correlated with daytime sleepiness: the decline in sleep quality [adjusted odds ratio (AOR) = 2.62, 95% confidence interval (CI) = 1.71–4.00], bedtime after 21:30 on weekdays (AOR = 1.58, 95% CI = 1.15–2.18), bedtime delay on weekends, compared to weekdays (AOR = 1.75, 95% CI = 1.27–2.41), and bedtime advance on weekends, compared to weekdays (AOR = 3.33, 95% CI = 1.78–6.20). Sleep dimensions that significantly affected daytime sleepiness in school-aged children are sleep quality, bedtime-timing, and regularity of bedtime. It is important to detect problems in night sleep and establish treatments, as well as to provide support for early bedding on weekdays and for a regular bedtime both on weekdays and on weekends to prevent daytime sleepiness in school-aged children.

     

Effects of 6/6 and 4/8 watch systems on sleepiness among bridge officers

During the last ten years, severe sleepiness or falling asleep by watch keeping officers has been a direct or a contributing factor in a number of maritime accidents. This study examined the relationship between two watch systems and its impact on fatigue and sleepiness in bridge officers. A questionnaire and a sleep/work diary were sent to a representative sample of the Finnish Maritime Officer Association. In all, 185 bridge officers answered the questionnaire on sleep, work hours, and safety, including the Skogby Excessive Daytime Sleepiness index (SEDS); 42% of the bridge officers worked two 4 h watches (4/8) per day, while 26% worked two 6 h watches per day (6/6). Ninety-five of the participants completed a sleep diary for seven consecutive days while at sea. The timing of the watch duties and sleep was recorded, as was subjective sleepiness every 2 h using the Karolinska Sleepiness Scale (KSS). 17.6% of the participants had fallen asleep at least once while on duty during their career. Compared to the 4/8 watch system, the officers working the 6/6 watch system reported shorter sleep durations, more frequent nodding-off on duty (7.3% vs. 1.5%), and excessive sleepiness (32% vs. 16% with SEDS>14). Based on a logistic regression analysis, high SEDS was significantly related with probable obstructive sleep apnea (OR 5.7), the 6/6 watch system (OR 4.0), and morningness-eveningness while controlling simultaneously several individual and sleep-related factors. Subjective sleepiness (KSS) was highest at 04:00 and 06:00 h. In a multivariate analysis, the KSS was significantly related to time of day, time after awaking, sleep length, and interactions of the watch systems with age, morningness-eveningness, and Epworth sleepiness scale (ESS) score. Severe sleepiness at 04:00-06:00 h was especially problematic in the 6/6 watch system among evening types and among the bridge officers with high ESS. The results suggest the 6/6 watch system is related to a higher risk of severe sleepiness during the early morning hours compared to the 4/8 and the other watch systems assessed.     

The impact of a delayed sleep–wake schedule on depression is greater in women – A web-based cross-sectional study in Japanese young adults

Sleep-related problems, such as symptoms of insomnia, daytime sleepiness, shorter sleep duration, or a delayed sleep–wake schedule, are known to be risk factors for depression. In general, depression is more prevalent in women than in men, but sleep-related problems do not necessarily show similar gender predominance. Hence, it can be speculated that the impact of sleep-related problems on the development process of depression differs between genders; however, so far, few studies have focused on this issue. The aim of this study was to clarify gender differences in the rates of depression of people with the above sleep-related problems, and to examine gender differences in factors associated with depression in Japanese young adults. A web-based questionnaire survey comprising assessments of demographic variables, sleep-related variables (bed time, wake time, sleep onset latency, frequency of difficulty in initiating sleep and that in maintaining sleep, i.e. symptom components of insomnia, and daytime sleepiness), and the 12-item version of the Center for Epidemiologic Studies Depression Scale was administered to 2502 participants (males:females?=?1144:1358, age range?=?19–25 years). Female predominance in the rate of depression was observed only in subjects with a delayed sleep–wake schedule (χ²₍₁₎?=?15.44, p?<?0.001). In men, daytime sleepiness and difficulty in initiating sleep were significantly associated with depression (odds ratio [OR]?=?2.39, 95% confidence interval [CI]?=?[1.69, 3.39], p?<?0.001; OR?=?3.50, 95% CI?=?[2.29, 5.35], p?<?0.001, respectively), whereas in women, significant associations were found between depression and a delayed sleep–wake schedule (OR?=?1.75, 95% CI?=?[1.28, 2.39], p?<?0.001), daytime sleepiness (OR?=?2.13, 95% CI?=?[1.60, 2.85], p?<?0.001), and difficulty in initiating sleep (OR?=?4.37, 95% CI?=?[3.17, 6.03], p?<?0.001). These results indicate that in younger generations, the impact of a delayed sleep–wake schedule on the development of depression is greater in women; specifically, women are vulnerable to depression when they have an eveningness-type lifestyle, which is possibly attributable to the female-specific intrinsic earlier and shorter circadian rhythm. These results suggest the necessity of gender-based approaches to treating sleep-related problems for alleviating or preventing depressive symptoms in young adults.     

Differences in Sleep,Light, and Circadian Phase in Offshore 18:00–06:00 h and 19:00–07:00 h Shift Workers

Complaints concerning sleep are high among those who work night shifts; this is in part due to the disturbed relationship between circadian phase and the timing of the sleep‐wake cycle. Shift schedule, light exposure, and age are all known to affect adaptation to the night shift. This study investigated circadian phase, sleep, and light exposure in subjects working 18:00–06:00 h and 19:00–07:00 h schedules during summer (May–August). Ten men, aged 46±10 yrs (mean±SD), worked the 19:00–07:00 h shift schedule for two or three weeks offshore (58°N). Seven men, mean age 41±12 yrs, worked the 18:00–06:00 h shift schedule for two weeks offshore (61°N). Circadian phase was assessed by calculating the peak (acrophase) of the 6‐sulphatoxymelatonin rhythm measured by radioimmunoassay of sequential urine samples collected for 72 h at the end of the night shift. Objective sleep and light exposure were assessed by actigraphy and subjective sleep diaries. Subjects working 18:00–06:00 h had a 6‐sulphatoxymelatonin acrophase of 11.7±0.77 h (mean±SEM, decimal hours), whereas it was significantly later, 14.6±0.55 h (p=0.01), for adapted subjects working 19:00–07:00 h. Two subjects did not adapt to the 19:00–07:00 h night shift (6‐sulphatoxymelatonin acrophases being 4.3±0.22 and 5.3±0.29 h). Actigraphy analysis of sleep duration showed significant differences (p=0.03), with a mean sleep duration for those working 19:00–07:00 h of 5.71±0.31 h compared to those working 18:00–06:00 h whose mean sleep duration was 6.64±0.33 h. There was a trend to higher morning light exposure (p=0.07) in the 19:00–07:00 h group. Circadian phase was later (delayed on average by 3 h) and objective sleep was shorter with the 19:00–07:00 h than the 18:00–06:00 h shift schedule. In these offshore conditions in summer, the earlier shift start and end time appears to favor daytime sleep.     

The impact of shift starting time on sleep duration,sleep quality,and alertness prior to injury in the People’s Republic of China

Early shift start time and night shifts are associated with reduced sleep duration and poor sleep quality that often lead to increased fatigue levels, performance decrements and adverse safety and health outcomes. This study investigates the impact of shift starting time on sleep patterns, including the duration and quality of sleep and alertness/sleepiness at the time of injury, in a large epidemiological field study of hospitalized adults with severe work-related hand injury in the People’s Republic of China (PRC) from multiple industries with severe work-related traumatic hand injury were recruited from 11 hospitals in three industrially-developed cities in the PRC: Ningbo, Liuzhou and Wuxi. Analysis of covariance (ANCOVA) was used to compare sleep duration, sleep quality and alertness/sleepiness across 3?h increments of shift start time, while adjusting for age, gender, work hours, shift duration, day of injury and several transient work-related factors. Effect modification by gender was also evaluated. Seven-hundred and three hospitalized adults (96.4%) completed a face-to-face interview within 4 days of injury; 527 (75.0%) were male, with a mean (±SEM) age of 31.8?±?0.4 years. Overall, these adults worked relatively long weekly (55.7?±?0.6?h) and daily hours (8.6?±?0.07?h). Average sleep duration prior to injury was 8.5?h (±0.07), and showed significant variations (p value <0.05) across shift starting time increments. Overall mean prior sleep duration was shortest for individuals starting shifts from “21:00–23:59” (5.6±0.8?h) followed by midnight “00:00–02:59” (6.1?±?0.6?h). However, a statistically significant interaction (p?<?0.05) was observed between gender and shift starting time on mean sleep duration. For males the shortest sleep duration was 5.6?h (“21:00–23:59”) and for females the shortest was 4.3?h (“24:00–02:59” and “15:00–17:59”). Sleep quality (generally quite well) and alertness/sleepiness based on the KSS (generally alert) did not vary significantly across shift starting time. Results suggest that sleep duration is shortest among injured PRC adults starting shifts late night and early morning. However, with more than 8.5?h of sleep on average work days, Chinese slept much longer than typical US day workers (Sleep in America Poll, 2012, 6:44 on workdays, 7:35 on free days), and this may help to explain higher than expected alertness/sleepiness scores at the time of injury.     

Sleepiness and Performance in Response to Repeated Sleep Restriction and Subsequent Recovery during Semi‐Laboratory Conditions

There is an ongoing debate of how best to measure the effects of sleep loss in a reliable and feasible way, partly because well controlled laboratory studies and field studies have come to different conclusions. The aims of the present study were to investigate both sleepiness and performance in response to long‐term sleep restriction and recovery in a semi‐laboratory environment, investigate order effects (i.e., whether levels return to baseline) in a study with seven days of recovery, and characterize individual differences in tolerance to restricted sleep. Nine healthy men (age 23–28 yrs) participated in the protocol, which included one habituation day (sleep 23:00–07:00 h), two baseline days (23:00–07:00 h), five days with restricted sleep (03:00–07:00 h), and seven recovery days (23:00–07:00 h). Participants went outdoors at least twice each day. Reaction‐time tests were performed at 08:00, 14:00, and 20:00 h each day in the laboratory. Sleepiness was self‐rated by the Karolinska Sleepiness Scale (KSS) after each test. The mixed‐effect regression models showed that each day of restricted sleep resulted in an increase of sleepiness by 0.64±.05 KSS units (a nine‐step scale, p<.001), increase of median reaction times of 6.6±1.6 ms (p=.003), and increase of lapses/test of 0.69±.16 ms (p<.001). Seven days of recovery allowed participants to return to the baseline for sleepiness and median reaction time, but not for lapses. The individual differences were larger for performance measures than for sleepiness; the between‐subject standard deviation for the random intercept was in the magnitude of the effects of 1.1 days of restricted sleep for sleepiness, 6.6 days of restricted sleep for median reaction time, and 3.2 days for lapses. In conclusion, the present study shows that sleepiness is closely related to sleep pressure, while performance measures, to a larger extent, appear determined by specific individual traits. Moreover, it is suggested to measure sleepiness in a standardized situation so as to minimize the influences of contextual factors.     

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.     

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.     

Correlations between sleep patterns and cardiovascular diseases in a Chinese middle-aged population

Epidemiological and animal studies have suggested an association between habitual sleep patterns and cardiovascular (CV) disease, but the results are still controversial. Therefore, the aims of this study are to investigate the relationships between habitual sleep patterns and CV disease based on Prospective Urban Rural Epidemiology (PURE) China study. PURE China study recruited 46 285 participants, aged 35–70, from 12 provinces and 115 communities in China. Habitual sleep patterns and CV disease were self-reported. Multilevel logistic regression was used in our analysis. In this study, 39 515 participants were eligible in our analysis, including 23 345 (59.1%) women and 16 170 (40.9%) men. Sleeping ≥9 h per day was associated with increased odds of CV disease (OR = 1.16, 95% CI: 1.01–1.32, p = 0.033) compared with sleeping 7–8 h per day. Taking daytime naps was also associated with an increased odds of CV disease, and the CV odds increased with increasing napping duration (p for trend < 0.001). For the sleeping < 6 h per day, we only found an association with coronary artery disease (CAD) (OR = 1.58, 95% CI: 1.01–2.48, p = 0.046). Participants with only 7–8 h sleep per night had lowest prevalence of CV disease (OR = 0.77, 95% CI: 0.65–0.90, p = 0.001) compared with other sleep patterns. Napping, long and short duration of habitual sleep may increase the odds of CV disease. Only participants sleeping 7–8 hours at night are recommended in this study, and large longitudinal studies are needed to confirm these results.     

Variation in sleepiness during early morning shifts: a mixed model approach to an experimental field study of train drivers

The present study aimed to experimentally evaluate the effect of early morning shifts on sleep and sleepiness of train drivers during normal working conditions. A total of 17 experienced train drivers were studied during a 4.5 h drive in two directions with a 2.5 h break in between on three different shifts: an early shift that started at 05:49 h (train left at 06:18 h) and ended at 17:41h, a day shift (07:49-19:41 h), and an evening shift (09:49-21:41 h). Retrospective (since the last stop) ratings of mean sleepiness and peak sleepiness (Karolinska Sleepiness Scale--KSS: 1 = very alert, 9= very sleepy, fighting sleep, difficulty staying awake) were assessed at each stop during the drive. The results showed that sleep length was reduced (p <0.001) by 1 h and 2h, respectively, by the early shift compared to the day and evening shifts. The prevalence of severe sleepiness (KSS > or = 7) was high, especially during the early shift when 14 (82%) subjects reported at least one event during the drive. Application of the Generalized Linear Mixed Models (GLMM) to the sleepiness data showed that there was an increased risk for severe sleepiness during the early shift (OR = 4.9) that increased further with the length of the drive between stops (OR = 1.9, 15 min), suggesting an interaction between early morning shift and monotony. The findings have practical implications in risk assessment. Long drives without stops and other monotonous situations should have a higher risk rating for severe sleepiness in shifts with an early start before 06:00 h, compared to shifts that begin 2 h later.     

Sleepiness and Sleep in a Simulated “Six Hours On/Six Hours Off” Sea Watch System

Ships are operated around the clock using rapidly rotating shift schedules called sea watch systems. Sea watch systems may cause fatigue, in the same way as other irregular working time arrangements. The present study investigated subjective sleepiness and sleep duration in connection with a 6 h on/6 h off duty system. The study was performed in a bridge simulator, very similar to those found on ships. Twelve officers divided into two groups participated in the study that lasted 66 h. Half of the subjects started with the 06:00–12:00 h watch and the other half with the 12:00–18:00 h watch. The subjects alternated between off‐duty and on‐duty for the remainder of the experimental period. Approximately halfway through the experiment, the 12:00–18:00 h watch was divided into two 3 h watches/off‐duty periods. The effect of this was to reverse the on‐duty/off‐duty pattern between the two groups. This enabled all subjects to work the four possible watches (00:00–06:00 h, 06:00–12:00 h, 12:00–18:00 h, and 18:00–24:00 h) in an order that was essentially counterbalanced between groups. Ratings of sleepiness (Karolinska Sleepiness Scale; KSS) were obtained every 30 min during on‐duty periods and if subjects were awake during off‐duty periods. The subjectively rated duration of sleep was recorded after each off‐duty period that preceded watch periods when KSS was rated. The results showed that the average level of sleepiness was significantly higher during the 00:00–06:00 h watch compared to the 12:00–18:00 h and 18:00–24:00 h watches, but not to the 06:00–12:00 h watch. Sleepiness also progressed significantly from the start toward the end of each watch, with the exception of the 06:00‐12:00 h watch, when levels remained approximately stable. There were no differences between groups (i.e., the order between watches). Sleep duration during the 06:00–12:00 h off‐duty period (3 h 29 min) was significantly longer than during the 12:00–18:00 h period (1 h 47 min) and the 18:00–24:00 h period (2 h 7 min). Sleep during the 00:00–06:00 h period (4 h 23 min) was longer than all sleep periods except the 06:00–12:00 h period. There were no differences between groups. In spite of sufficient opportunities for sleep, sleep was on the average around 1–1 h 30 min shorter than the 7–7 h 30 min that is considered “normal” during a 24 h period. This is probably a consequence of the difficulty to sleep during daytime due to the alerting effects of the circadian rhythm. Also, sleepiness during the night and early mornings reached high levels, which may be explained by a combination of working close to or during the circadian trough of alertness and the relatively short sleep periods obtained. An initial suppression of sleepiness was observed during all watches, except for the 06:00–12:00 h watch. This suppression may be explained by the “masking effect” exerted by the relative high levels of activity required when taking over the responsibility of the ship. Toward the end of watches, the levels of sleepiness progressively increased to relatively high levels, at least during the 00:00–06:00 h watch. Presumably, initially high levels of activity are replaced by routine and even boredom.     

Working “out-of-phase” with reference to chronotype compromises sleep quality in police officers

The aim of this work was to study the sleep characteristics, blood pressure (BP) and heart rate (HR) of the police officers working during out-of-phase (OP) and in-phase (IP) duty schedules with respect to their chronotypes. Adult male and female police officers (n = 85) were asked to answer Hindi/English version of different questionnaires to assess their chronotype (morningness–eveningness questionnaire; MEQ), PSQI scores (Pittsburgh sleep quality index), daytime sleepiness (Epworth sleepiness scale, ESS) and fatigue levels (fatigue severity scale, FSS) and fill a sleep log. Based on their PSQI scores, the participating subjects (n = 85) were divided into two categories: good sleepers (58/85) and poor sleepers (27/85). Of these 85 subjects, 23 subjects (good sleepers n = 13; poor sleepers n = 10) volunteered for the next part of the study. At the beginning of the study, the existing duty schedule of these subjects was OP and lasted for 4 days (OP1). Thereafter, they were allotted their preferred (IP) duty schedule for 4 days, followed by OP2 for further 4 days. Over the 12-day period, subjects were monitored for their BP and sleep–wake cycle. Results showed that the poor sleepers improved their sleep quality and HR during IP duty schedule; however, good sleepers were not affected significantly.     

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.     

DAILY SLEEP,WEEKLY WORKING HOURS,AND RISK OF WORK-RELATED INJURY: US NATIONAL HEALTH INTERVIEW SURVEY (2004–2008)

The impact on health and safety of the combination of chronic sleep deficits and extended working hours has received worldwide attention. Using the National Health Interview Survey (NHIS), an in-person household survey using a multistage, stratified, clustered sample design representing the US civilian, non-institutionalized population, the authors estimated the effect of total daily self-reported sleep time and weekly working hours on the risk of a work-related injury. During the survey period 2004–2008, 177,576 persons (ages 18–74) sampled within households reported that they worked at a paid job the previous week and reported their total weekly work hours. A randomly selected adult in each household (n?=?75,718) was asked to report his/her usual (average) total daily sleep hours the prior week; complete responses were obtained for 74,415 (98.3%) workers. Weighted annualized work-related injury rates were then estimated across a priori defined categories of both average total daily sleep hours and weekly working hours. To account for the complex sampling design, weighted multiple logistic regression was used to independently estimate the risk of a work-related injury for categories of usual daily sleep duration and weekly working hours, controlling for important covariates and potential confounders of age, sex, race/ethnicity, education, type of pay, industry, occupation (proxy for job risk), body mass index, and the interaction between sleep duration and work hours. Based on the inclusion criteria, there were an estimated 129,950,376 workers annually at risk and 3,634,446 work-related medically treated injury episodes (overall injury rate 2.80/100 workers). Unadjusted annualized injury rates/100 workers across weekly work hours were 2.03 (≤20 h), 3.01 (20–30 h), 2.45 (31–40 h), 3.45 (40–50 h), 3.71 (50–60 h), and 4.34 (>60 h). With regards to self-reported daily sleep time, the estimated annualized injury rates/100 workers were 7.89 (<5 h sleep), 5.21 (5–5.9 h), 3.62 (6–6.9 h), 2.27 (7–7.9 h), 2.50 (8–8.9 h), 2.22 (9–9.9 h), and 4.72 (>10 h). After controlling for weekly work hours, and aforementioned covariates, significant increases in risk/1 h decrease were observed for several sleep categories. Using 7–7.9 h sleep as reference, the adjusted injury risk (odds ratio [OR] for a worker sleeping a total of <5 h/day was 2.65 (95% confidence interval [CI]: 1.57–4.47), for 5–5.9 h 1.79 (95% CI: 1.22–2.62), and for 6–6.9 h 1.40 (95% CI: 1.10–1.79). No other usual sleep duration categories were significantly different than the reference; however, for >10 h of usual daily sleep, the OR was marginally significantly elevated, 1.82 (95% CI: 0.96–3.47). These results suggest significant increases in work-related injury risk with decreasing usual daily self-reported sleep hours and increasing weekly work hours, independent of industry, occupation, type of pay, sex, age, education, and body mass (Author correspondence: david.lombardi@libertymutual.com)