Smoking among Shift Workers: More Than a Confounding Factor

In studies on the cardiovascular disease risk among shift workers, smoking is considered to be a confounding factor. In a study of 239 shift and 157 daytime workers, it was found that shift work was prospectively related to increased cigarette consumption, indicating that smoking might be in the causative pathway; however, the number of study subjects was too low to warrant sound conclusions. Therefore, data from the Maastricht Cohort study were used to investigate the longitudinal relation between smoking and shift work in a much larger population. In this study, a total of 12,140 employees were followed for two years by means of self‐administered questionnaires. The authors compared workers who normally worked during daytime hours only (74%) with those who worked other than day shifts (26%). Logistic regression analyses were performed, adjusting for demographic factors of age, gender, and educational level to evaluate the risk of starting to smoke (n=25) in the group of non‐smoking workers and the risk of quitting (n=318) in the group of smoking workers. Logistic regression analysis showed a significant association between shift work and taking up smoking during the two‐year follow‐up (odds ratio: 1.46, p=0.03). The risk to stop smoking was somewhat lower in shift workers (odds ratio: 0.91) but not statistically significant (p=0.5). To conclude, this study showed that, independent of educational level, shift workers are more prone to start smoking. This finding might have important implications for studies on the health effects of shift workers and for possible interventions aimed at the reduction of the excess health risk among shift workers.     

Who Is Too Old for Shift Work? Developing Better Criteria

Demographic and social trends in industrialized countries are expected to lead to increasing numbers of older shift workers, raising concerns about possible health and safety risks. For older night workers, the International Labour Organization has recommended options for transferring to day work or early retirement, but few States have adopted these measures. For commercial air transport pilots, the International Civil Aviation Organization has implemented a series of regulatory measures that could manage the risks associated with aging, including a mandatory retirement age, regular medical assessments for fitness to fly, and limits on the duration of duty and rest. Each of these approaches has strengths and weaknesses. The mandatory retirement age is effectively arbitrary, has been controversial, and was recently increased from 60 to 65 yrs for one member of a two‐person cockpit crew. Medical assessments offer a more individualized approach, but to improve safety, they must address aspects of health and physical or mental function that affect work performance and safety outcomes. The traditional focus has been on cardiovascular risk factors, although cardiac incapacitation is not a cause of accidents in a two‐person cockpit aircraft. On the other hand, while pilot fatigue is an acknowledged cause of accidents, there is currently no requirement to consider issues associated with fatigue or sleep problems in fitness‐to‐fly medical assessments. Older long‐haul pilots show greater sleep fragmentation than their younger colleagues and those in the general population. Sleep becomes more fragmented with increasing age, but the functional significance of this remains unclear. Among younger adults, experimental sleep fragmentation leads to increased sleepiness and degradation of performance and mood. Greater sleep loss is reported by older long‐haul pilots, as well as other older shift workers, compared to younger people working similar duty patterns. Experimental sleep restriction causes a degradation of performance and mood that is cumulative and dose‐dependent. In addition, a recent large‐scale flight simulation study indicates that the duration of sleep obtained by individual pilots is an independent predictor of crew performance in a two‐person cockpit. Based on these considerations, we propose that fatigue and sleep‐related issues should become a standard part of fitness‐for‐work medical assessments, particularly for older shift workers. A multi‐layered approach is proposed, with a routine structured sleep history leading to referral to specialist sleep services where appropriate. Criteria for specialist referral and medical retirement should be related to the workplace risk represented by an older worker. Additional research is needed to develop and validate sleep‐related criteria for assessing fitness for work. For example, a better understanding of the effects of sleep fragmentation on the waking function of older workers might lead to a fragmentation threshold for fitness for work. The potential negative effects of unemployment and early retirement also need to be taken into account when considering the options for managing the occupational health and safety needs of older shift workers.     

Measuring Phase Shifts in Humans Following a Simulated Time‐Zone Transition: Agreement Between Constant Routine and Purification Methods

Twelve healthy participants were studied in an Isolation Unit. For the first 7 (control) days, subjects lived on UK time. Then the clock was advanced by 8 h, mimicking an eastward time‐zone transition, and for days 8 to 12, participants lived on this new local time. Two constant routines (participants were not allowed to sleep, were restricted in movement, and ate regular, identical snacks) were undertaken, during the control days (days 3 to 4) and at the end of the experiment (days 11 to 12). Rectal temperature and activity were measured throughout, with activity used to correct the measured temperatures for the direct (masking) effects of the sleep‐wake cycle. Phase changes of the temperature rhythm between the constant routines were assessed by cross‐correlation and cosinor analysis. During days 8 to 10, the measured temperatures and those that had been corrected (purified) for masking were assessed by the same two methods, and the shifts were extrapolated to predict the values expected during the second constant routine. Individuals differed widely in the phase shifts of the temperature rhythm, but the correlations between the changes measured by constant routines and those estimated by the purification methods were high (r=0.771 to 0.903), and the differences between them were not significantly different from zero (p>0.24). Phase shifts of the measured (masked) temperature rhythm were poorer predictors of the shift obtained from the constant routines (r≤0.605; mean±SD of differences >3±4.5 h). Limitations of the methods due to the variability of results are discussed, but we conclude that the mean phase shifts obtained from purified, but not raw, temperature data show acceptable agreement with those found using our version of the constant routine.     

Sleep Length as a Function of Morning Shift‐Start Time in Irregular Shift Schedules for Train Drivers: Self‐Rated Health and Individual Differences

Forty‐six male train drivers (mean age=46.5, SD=5.1) were recruited to participate in a diary study for 14 consecutive days with questions about their sleep and working hours. A polynomial mixed‐effect regression model showed a curvilinear relation (p <. 001) between shift‐start time and sleep duration for shifts starting at 03∶00–12∶00 h and with a near linear increase for ones starting between 04∶30 and 09∶00 h of approximately 0.7 h for every 1 h the shift was delayed. The longest sleeps were estimated at ～8 h before shifts that started at ～10∶00 h. The shortest sleeps were found for shifts that started before 04∶30 h and were estimated at ～5 h. Individual differences were estimated with a random-effect standard deviation of 0.51 h, independent of shift‐start time (p =.005). One‐half of the between‐subject variance was explained by subjective health. A one‐step decrease in health was associated with a 26 min increase in sleep length. The results have practical implications for constructing shift schedules. Early morning shifts reduced sleep length substantially and should be mixed with later start hours to avoid the accumulation of sleep dept. Delaying the shift‐start past 10∶00 h had little effect on sleep opportunity; however, delaying shift‐start to between 04∶30 and 9∶00 h had a strong impact on sleep length, with 70% of the extra time used for sleep, suggesting large positive effects for this range of shift‐start times.     

Sleep Disturbances Among Female Nurses: Comparing Shift to Day Work

Recently, attention has focused in Israel on the possible legal and health consequences of shift work. We decided to study sleep disorders among female nursing personnel working a shift schedule, in comparison with day nurses, in a large metropolitan general hospital. The study population was composed of 131 female certified nurses working shifts and 44 working days only. Inclusion criteria for the survey was at least 1 year of shift work alternating between day, evening, and night shifts, or at least 1 year of day work. All participants completed a self-report sleep questionnaire encompassing (a) demographic data, (b) sleep survey, and (c) employment details. Statistical analysis was performed using the Pearson correlation test and analysis of variance multiple range test (according to Scheffe's procedure). No significant correlation was found between sleep disorders and age of subjects. No sleep disorders were reported by 19.8% of shift workers versus 76.5% of day workers. Statistically significant findings were that the number of shifts per week >4.1 (p = 0.001) and duration of shift work >13.6 years (p = 0.007) correlated with the presence of sleep disorders. An additional significant finding (p = 0.014) was the impact of evening shifts on sleep disorders. The present small study confined to women supports the growing body of data on sleep complaints among shift workers.     

Psychosocial Work Characteristics Predicting Daytime Sleepiness in Day and Shift Workers

Characteristics of work organization other than working time arrangements may contribute importantly to daytime sleepiness. The present study was designed to identify the psychosocial factors at work that predict daytime sleepiness in a sample of day and shift workers. Participants working at a pulp and chemical factory completed an annual questionnaire regarding psychosocial factors at work using the U.S. National Institute for Occupational Safety and Health Generic Job Stress Questionnaire (i.e., quantitative workload, variance in workload, job control, support from supervisor, coworkers, or family/friends, job satisfaction, and depressive symptoms), as well as daytime sleepiness (through the Epworth Sleepiness Scale [ESS]) and sleep disturbances for three years starting in 2002 (response rates, 94.6–99.0%). The present analysis included 55 day workers (11 women) and 57 shift workers (all men) who participated in all three years of the study, worked under the same work schedule throughout the study period, and had no missing data on any of the daytime sleep items. A repeated‐measures analysis of covariance (ANCOVA) was used to test the effects of work schedule (day vs. shift work) and psychosocial factors at work in 2002 on the ESS scores in subsequent years, with sleep duration, insomnia symptoms, chronic diseases, and sleepiness levels at baseline as covariates. Given significant and near‐significant interactions of work schedules with psychosocial factor or study year, the ANCOVA, with the factors of psychosocial work characteristics and study year, was performed by type of work schedule. The results indicated a significant main effect of psychosocial work characteristics (p=0.010, partial ?²=0.14) and an almost significant main effect of study year (p=0.067, partial ?²=0.06) and interaction between psychosocial work characteristics and study year (p=0.085, partial ?²=0.06) for variance in workload among the day work group. The day workers reporting high variance in workload in 2002 exhibited significantly higher ESS scores in 2003 and 2004 than did those reporting low variance in workload. The ANCOVA for the shift work group showed a main effect of psychosocial work characteristics for job satisfaction (p=0.026, partial ?²=0.10) and depressive symptoms (p=0.094, partial ?²=0.06) with the interaction between psychosocial work characteristics and study year for job satisfaction (p=0.172, partial ?²=0.04) and depressive symptoms (p=0.035, partial ?²=0.07). The shift workers with low job satisfaction and high symptoms of depression in 2002 showed significantly greater ESS scores in 2003 and/or 2004 than did those with opposite characteristics. These results may suggest a potential predictive value of variance in workload for day workers as well as job satisfaction and depressive symptoms for shift workers with respect to daytime sleepiness. The present findings may imply that redesigning these aspects of work environment would be of help in managing daytime sleepiness.     

打桩水下噪声对长江江豚影响初探

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Chronobiotic effects of the melatonin agonist LY 156735 following a simulated 9h time shift: results of a placebo-controlled trial

Introduction: The melatonin agonist LY 156735 (LY) is a new investigational drug under development to treat circadian rhythm disorders. The present study assessed the efficacy of LY to alleviate the symptoms of shift lag and to enhance readaptation of desynchronized circadian rhythms to a new time zone.

Subjects and methods: Eight healthy male volunteers of age 25-35 yr participated in three identical trials of 13d duration in a temporal isolation unit separated by washout intervals. A high dose (HD) of 5 mg and a low dose (LD) of 0.5 mg of LY and placebo (PL) were administered double-blinded in a three-period cross-over design. Each trial consisted of an adaptation period, a pre-shift period for baseline measurements, a simulated 9h phase-advance shift, and a post-shift period for follow-up. The time shift was performed at 23:00h of day 6 by advancing the laboratory time to 08:00h of day 7. Double-blind study medication was administered at 14:30h on day 6, and at 22:30h on days 7-10. Subjective ratings of jet lag, alertness, tenseness, and daytime fatigue were assessed using visual analog scales (VAS) and standardized questionnaires. The objective markers of readaptation included core body temperature, wrist actigraphy, cortisol and electrolyte excretion, and a battery of computerized performance tests.

Results: HD but not LD enhanced the readaptation speed of all physiological rhythms investigated, as demonstrated by a significantly faster movement of acrophases towards the post-shift target time. HD (p=0.05) significantly blunted the post-shift deterioration of performance in those tests that were sensitive to shift lag. Parameters of subjective well-being were not significantly affected by either dose.

Conclusion: This pilot study demonstrates the chronobiotic efficacy of LY when taken at a dose of 5 mg/d.     

A Shift Algorithm for Exact Computation in Sequential Tests with Binary Outcome

A simple shift algorithm is described enabling the exact determination of power functions and sample size distributions for a large variety of closed sequential two‐sample designs with a binary outcome variable. The test statistics are assumed to be based on relative frequencies of successes or failures, but the number of interim analyses, the monitoring times, and the continuation regions may be specified as desired. To give examples, exact properties of designs proposed by the program package EaSt (Cytel , 1992) are determined, and plans with interim analyses are considered where decisions are based on the conditional power given the observations obtained so far.     

Smoking among shift workers: More than a confounding factor

In studies on the cardiovascular disease risk among shift workers, smoking is considered to be a confounding factor. In a study of 239 shift and 157 daytime workers, it was found that shift work was prospectively related to increased cigarette consumption, indicating that smoking might be in the causative pathway; however, the number of study subjects was too low to warrant sound conclusions. Therefore, data from the Maastricht Cohort study were used to investigate the longitudinal relation between smoking and shift work in a much larger population. In this study, a total of 12,140 employees were followed for two years by means of self-administered questionnaires. The authors compared workers who normally worked during daytime hours only (74%) with those who worked other than day shifts (26%). Logistic regression analyses were performed, adjusting for demographic factors of age, gender, and educational level to evaluate the risk of starting to smoke (n=25) in the group of non-smoking workers and the risk of quitting (n=318) in the group of smoking workers. Logistic regression analysis showed a significant association between shift work and taking up smoking during the two-year follow-up (odds ratio: 1.46, p=0.03). The risk to stop smoking was somewhat lower in shift workers (odds ratio: 0.91) but not statistically significant (p=0.5). To conclude, this study showed that, independent of educational level, shift workers are more prone to start smoking. This finding might have important implications for studies on the health effects of shift workers and for possible interventions aimed at the reduction of the excess health risk among shift workers.