The association between the use of shift schedule evaluation tool with ergonomics recommendations and occupational injuries: A 4-year prospective cohort study among healthcare workers.

OBJECTIVE: This study aimed to find out whether utilizing a shift schedule evaluation tool with ergonomics recommendations for working hours has favorable effects on the incidence of occupational injuries. METHODS: This 4-year prospective cohort study (2015-2018) consisted of a dynamic cohort of healthcare shift workers (N=29 237) from ten hospital districts and six cities in Finland. Working hour characteristics and occupational injuries were measured with daily registry data. Multilevel generalized linear model was used for the analyses, and the estimates were controlled for hierarchical structure of the data and confounders. RESULTS: Ward heads of the cities used the shift schedule evaluation tool 3.2 times more often than ward heads of the hospital districts. Overall incidence of workplace and commuting injuries did not differ between users and non-users of the evaluation tool. The incidence of dislocations, sprains, and strains was lower in the users than non-users [adjusted odds ratio (OR) 0.88, 95% confidence interval (CI) 0.78-0.99]. Approximately 13% of this association was mediated by increase in realized shift wishes and 10% by increase in single days off. In subgroup analyses, the incidence of workplace injury (OR 0.83, 95% CI 0.69-0.99), and among types of injuries, the incidence of dislocations, sprains, and strains (OR 0.69, 95% CI 0.55-0.85) and falling, slipping, tripping, or overturning (OR 0.75, 95% CI 0.58-0.99) were lower in users than non-users among employees of the cities, but no association was found among employees of the hospital districts. CONCLUSION: The use of ergonomics recommendations for working hours is associated with a reduced risk of occupational injuries.

The Time-Varying Effect of Participatory Shift Scheduling on Working Hour Characteristics and Sickness Absence: Evidence from a Quasi-Experiment in Hospitals.

Participatory shift scheduling for irregular working hours can influence shift schedules and sickness absence. We investigated the effects of using participatory shift scheduling and shift schedule evaluation tools on working hour characteristics and sickness absence. We utilized a panel data for 2015-2019 with 16,557 hospital employees (6143 in the intervention and 10,345 in the control group). Difference-in-differences regression with ward-level clustered standard errors was used to estimate the average treatment effect on the treated coefficients relative to timing of the intervention with 95% confidence intervals (CI). Using participatory scheduling tool increased long working hours and weekend work and had delayed effects on the short (1-3 days) sickness absences. Increased effects were observed: 0.2 [95% CI 0.0-0.4] days for the second, and 0.8 [95% CI 0.5-1.0] for the third year after the onset of intervention. An average increase of 0.5 [95% CI 0.1-0.9] episodes on all sickness absence episodes was observed for the third year. Using the shift schedule evaluation tool with the participatory shift scheduling tool attenuated the adverse effects. To conclude, participatory shift scheduling increased some potentially harmful working hour characteristics but its effects on sickness absence were negligible, and further attenuated by using the shift schedule evaluation tool.

Hospital physicians´ working hour characteristics and sleep quality: a cross-sectional analysis of realized working hour and survey data.

BACKGROUND: Hospital physicians' work includes on-call duties to provide 24/7 health care. Previous studies using self-reported survey data have associated long working hours and on-call work with sleep difficulties. To reduce recall bias, we complemented survey data with payroll-based objective data to study whether hospital physicians' realized working hours are associated with sleep. METHODS: The study was nested within the Finnish Public Sector study. We used survey data on 728 hospital physicians (mean age 43.4 years, 62% females) from 2015 linked to realized daily working hour data from 3 months preceding the survey. The associations of working hour characteristics with sleep quantity and quality were studied with multinomial logistic regression analysis adjusted for demographics, overall stressfulness of life situation, control over scheduling of shifts, and hospital district. RESULTS: One fourth (26%) of the participants reported short (≤6.5 h) average sleep duration. Frequent night work (> 6 shifts/91 days) was associated with short sleep (OR 1.87 95%CI 1.23-2.83) compared to no night work. Approximately one third (32%) of the physicians reported insufficient sleep. Physicians with long weekly working hours (> 48 hours) had higher odds for insufficient sleep (OR 1.78 95%CI 1.15-2.76) than physicians with short weekly working hours (< 40 hours). Insufficient sleep was also associated with frequent on-call duties (> 12 shifts/3 months OR 2.00 95%CI 1.08-3.72), frequent night work (OR 1.60 95%CI 1.09-2.37), and frequent short shift intervals (≤11 hours; > 12 times/3 months OR 1.65 95%CI 1.01-2.69) compared to not having these working hour characteristics. Nearly half of the physicians (48%) reported at least one sleep difficulty at least two times a week and frequent night work increased odds for difficulties in initiating sleep (OR 2.43 95%CI 1.04-5.69). Otherwise sleep difficulties were not associated with the studied working hour characteristics. CONCLUSION: We used realized working hour data to strengthen the evidence on on-call work and sleep quality and our results advice to limit the frequency of night work, on-call shifts, short shift intervals and long weekly working hours to promote hospital physicians' sufficient sleep.

National recommendations for shift scheduling in healthcare: A 5-year prospective cohort study on working hour characteristics.

BACKGROUND: National recommendations to decrease the health and safety risks of working hours are often given based on the increasing knowledge of the associations between working hour characteristics and health. However, the utilization of the recommendations, and their potential to change the actual working time patterns in healthcare sector is unclear. OBJECTIVE: We investigated the extent to which the national recommendations are utilized in shift scheduling, when they are integrated as a shift schedule evaluation tool into the shift scheduling software. Second, we examined whether the use of the tool results in changes that are in line with the recommendations. DESIGN: A prospective cohort study with a 5-year follow-up. PARTICIPANTS: A total of 36,663 healthcare workers with objective data on daily working hours in 10 hospital districts and 6 large cities. METHODS: We investigated the annual use of the evaluation tool, and the effects of using the tool on annual changes in working hour characteristics from 2015 to 2019 while adjusting for the hierarchical structure of the data, age, sex, shift work, night work, work contract days and the type of shift scheduling software. Utilizing intention-to-treat principle, the employees in wards using the tool were compared to non-users by multi-level generalized linear models. RESULTS: Continuous use (during at least 10 scheduling periods) of the evaluation tool increased from 2% in 2015 to 20% in 2018. In the fully adjusted model, the use of the evaluation tool was associated with the decrease of >6 consecutive workdays (OR 0.73, 95% CI 0.66, 0.81), >4 consecutive night shifts (OR 0.86, 95% CI 0.77, 0.95), and proportion of <11-hour shift intervals (difference 0.63, 95% CI 0.43, 0.83). The proportion of single days off (difference 0.33, 95% CI 0.15, 0.51), and >40-hour work weeks (OR 1.16, 95% CI 1.10, 1.22), as well as the proportion of ≥12-hour work shifts (OR 1.22, 95% CI 1.07, 1.38) increased. Realized shift wishes decreased (difference 0.76, 95% CI 0.12, 1.41). The use of the tool was associated with more frequent changes towards the recommendations in the cities compared to the hospital districts, and among the older age groups compared to the ≤30-year-old employees. CONCLUSIONS: National recommendations embedded in the shift schedule evaluation tool were used continuously by one fifth of the employees, and were associated with several, albeit modest changes towards the given recommendations. Changes in working hour characteristics depended on organization indicating for differences in the implementation of the recommendations. TWEETABLE ABSTRACT: The national recommendations for safer working hour characteristics embedded in a shift schedule evaluation tool are associated with several, albeit modest changes in working hour characteristics.

Working hours, on-call shifts, and risk of occupational injuries among hospital physicians: A case-crossover study.

OBJECTIVE: To investigate the association of hospital physicians' working hours and on-call shifts with the risk of occupational injuries. METHODS: In this nested cohort study of 556 Finnish hospital physicians, we linked electronic records from working-hour and on-call duty payroll data to occupational injury data obtained from the Finnish Workers' Compensation Center for the period 2005-2019. We used a case-crossover design with matched intervals for a 7-day 'case window' immediately prior to occupational injury and a 'control window' 7 days prior to the beginning of the case window, and analyzed their associations using conditional logistic regression models. RESULTS: We noted 556 occupational injuries, 281 at the workplace and 275 while commuting. Having three to four long (>12 h) work shifts on the preceding 7 days was associated with a higher probability of an occupational injury (odds ratio [OR] 2.14, 95% confidence interval [CI] 1.11, 4.09), and the OR for three to four on-call shifts was 3.54 (95%CI 2.11, 5.92) in comparison to having none of these work shift types. A higher number of several consecutive working days was associated with a higher probability of injury in a dose-response manner. Moreover, increasing weekly working hours was associated with an increased likelihood of injury (OR 1.03, 95%CI 1.01, 1.04), whereas the number of normal (≤12 h) work shifts reduced this likelihood (OR 0.79, 95%CI 0.64, 0.98). CONCLUSIONS: Our findings suggest that accumulated working-hour load, as opposed to single, very long (>24 h) work shifts, may increase the risk of occupational injury among hospital physicians.

Sleep, sleepiness and need for recovery of industrial employees after a change from an 8- to a 12-hour shift system.

Employees often prefer 12-hour work shifts but they can increase sleepiness and injury risk. We assessed whether sleep, sleepiness, satisfaction and need for recovery changed after changing from an 8-hour to a 12-hour shift system. The participants were 178 employees of the paper, pulp and chemical industries. Using a quasi-experimental controlled intervention design, 83 employees, who changed from an 8-hour shift schedule to a 12-hour shift schedule were compared to those who remained in the 8-hour shift schedule (n=95). Participants filled in a survey on sleep, sleepiness, satisfaction and need for recovery at baseline and 9-12 months after the shift schedule change. We used generalized estimation equation models adjusted for age, sex, shift work experience in years and baseline shift system. Sleep length was longer in the 12-hour shift schedule before the first morning shift and between morning shifts. Sleepiness during morning shifts was less frequent and satisfaction with the shift system was more prevalent in the 12-hour shift schedule. Also, perceived negative associations of the current shift system with work-life balance were less common in the 12-hour shift schedule. The differences found between the shift systems were minor and the results did not indicate significant disadvantages of the 12-hour fast forward-rotating shift system.

Association of working hour characteristics and on-call work with risk of short sickness absence among hospital physicians: A longitudinal cohort study.

Physicians often work long hours and on-call shifts, which may expose them to circadian misalignment and negative health outcomes. However, few studies have examined whether these working hour characteristics, ascertained using objective working hour records, are associated with the physicians' risk of sickness absence. We investigated the associations of 14 characteristics of payroll-based working hours and on-call work with the risk of short sickness absence among hospital physicians. In this cohort study, 2845 physicians from six Finnish hospital districts were linked to electronic payroll-based records of daily working hours, on-call duty and short (1-3 days) sickness absence between 2005 and 2019. A case-crossover design was applied using conditional logistic regression with the 28 day case and control windows to estimate odds ratios (ORs) and 95% confidence intervals (CI) for short sickness absence. After controlling for weekly working hours and the number of normal (≤12 h) shifts, a higher number of long (>12 h) shifts (ORs for ≥5 versus none: 2.54, 95% CI 1.68-3.84), very long (>24 h) shifts (ORs for ≥5 versus none: 2.62, 95%CI 1.61-4.27), and on-call shifts (OR for ≥5 versus none: 2.15, 95% CI 1.44-3.21) and a higher number of short (<11 h) shift intervals (OR for ≥5 versus none: 12.61, 95% CI 8.88-17.90) were all associated with the increased risk of short sickness absence. These associations did not differ between male and female physicians or between age groups. To conclude, the findings from objective working hour records show that long work shifts, on-call shifts and short shift intervals are related to the risk of short (1-3 days) sickness absence among hospital physicians.

Night shift work and the risk of metabolic syndrome: Findings from an 8-year hospital cohort.

OBJECTIVES: Studies concerning the risk of metabolic syndrome associated with night work have shown inconsistent findings, due to imprecise working time data and cross-sectional design. We used register-based daily working time data to examine the risk of incident metabolic syndrome associated with night shift work. METHODS: Working time data collected between 2010 and 2018 of 5775 Taiwanese hospital workers were used to identify night shift workers and to calculate the number of night shifts. Metabolic syndrome was identified by annual occupational health examination results, which were linked to the working time data. Logistic regression models and generalized estimating equations were used to examine the association between night shift work and metabolic syndrome and the 5 components of metabolic syndrome. RESULTS: Night shift work is associated with a higher risk of developing metabolic syndrome (adjusted OR = 1.36, 95% CI = 1.04 to 1.78) and high waist circumference (adjusted OR = 1.27, 95% CI = 1.07 to 1.78) compared to day work. Among night shift workers, increased number of night shifts was associated with high blood pressure (adjusted OR = 1.15, 95% CI = 1.01 to 1.31). CONCLUSIONS: Night shift work is associated with metabolic risk factors. Long-term effects of circadian rhythm disruption on metabolic disturbances needs to be further studied.

The Effect of Using Participatory Working Time Scheduling Software on Employee Well-Being and Workability: A Cohort Study Analysed as a Pseudo-Experiment.

Shift workers are at increased risk of health problems. Effective preventive measures are needed to reduce the unfavourable effects of shift work. In this study we explored whether use of digital participatory working time scheduling software improves employee well-being and perceived workability by analysing an observational cohort study as a pseudo-experiment. Participants of the Finnish Public Sector cohort study with payroll records available between 2015 and 2019 were included (N = 2427). After estimating the propensity score of using the participatory working time scheduling software on the baseline characteristics using multilevel mixed-effects logistic regression and assigning inverse probability of treatment weights for each participant, we used generalised linear model to estimate the effect of using the participatory working time scheduling software on employees' control over scheduling of shifts, perceived workability, self-rated health, work-life conflict, psychological distress and short sleep (≤6 h). During a 2-year follow-up, using the participatory working time scheduling software reduced the risk of employees' low control over scheduling of shifts (risk ratio [RR] 0.34; 95% CI 0.25-0.46), short sleep (RR 0.70; 95% CI 0.52-0.95) and poor workability (RR 0.74; 95% CI 0.55-0.99). The use of the software was not associated with changes in psychological distress, self-rated health and work-life conflict. In this observational study, we analysed as a pseudo-experiment, the use of participatory working time scheduling software was associated with increased employees' perceived control over scheduling of shifts and improved sleep and self-rated workability.

Ageing shift workers' sleep and working-hour characteristics after implementing ergonomic shift-scheduling rules.

We studied whether implementing binding ergonomic shift-scheduling rules change ageing (≥45 years) social and healthcare employees' (mean age 52.5 years, 95% women) working-hour characteristics (e.g. weekly working hours, number and length of night shifts, and short shift intervals) and sleep. We compared an intervention group (n = 253) to a control group (n = 1,234) by survey responses (baseline 2007/2008, follow-up 2012) and objective working-hour characteristics (intervention group n = 159, control group n = 379) from 91 days preceding the surveys. Changes in working-hour characteristics were analysed with repeated measures general linear models. The fully adjusted model (sociodemographics and full-/part-time work) showed that proportion of short shift intervals (<11 hr, p = .033) and weekend work (p = .01) decreased more in the intervention than in the control group. Changes in sleep outcomes were analysed with generalised logit model to binomial and multinomial variables. The fully adjusted model (sociodemographics, full-/part-time work, job strain, health behaviours, and perceived health) revealed higher odds in the intervention group for long sleep (≥9 hr; odds ratio [OR] 5.53, 95% confidence interval [CI] 2.21-13.80), and lower odds of short sleep (<6 hr; OR 0.72, 95% CI 0.57-0.92), having at least two sleep difficulties often (OR 0.55, 95% CI 0.43-0.70), and more specifically difficulties in falling asleep (OR 0.56, 95% CI 0.41-0.77), waking up several times per night (OR 0.43, 95% CI 0.34-0.55), difficulties in staying asleep (OR 0.64, 95% CI 0.49-0.82), and non-restorative sleep (OR 0.70, 95% CI 0.54-0.90) than the control group. In conclusion, implementation of ergonomic shift-scheduling rules resulted in minor changes in ageing employees' objective working hours and a consistent buffering effect against worsening of sleep.

The effects of using participatory working time scheduling software on sickness absence: A difference-in-differences study.

BACKGROUND: Participatory working time scheduling is a collaborative approach to scheduling shift work. As a potential way of improving work time control, it may provide a means to reducing sickness absence in shift work. So far, experimental and quasi-experimental studies on the effects of increased work time control on sickness absence are lacking. OBJECTIVE: To investigate the effects of using digital participatory working time scheduling software on ward-level sickness absence among Finnish hospital employees. PARTICIPANTS AND METHODS: This quasi-experimental study compared the amount of sickness absence in hospital wards using a participatory working time scheduling software (n=121 wards) and those continuing with traditional working time scheduling (n=117 wards) between 2014 and 2017. We used continuous panel data from 238 hospital wards with a total number of 9000 hospital employees (89% of women, primarily nursing staff). The ward-level measures consisted of number of employees, working hours, sickness absence spells per employee, and short (1-3) sickness absence days per employee. Two-way fixed effects and event study regressions with clustered standard errors were used to estimate the effect of using participatory scheduling software on sickness absence. RESULTS: Sickness absence spells and short (1-3) sickness absence days decreased by 6% and 7%, respectively in the wards using participatory scheduling compared to those using traditional scheduling. The effect became stronger as the time measured in quarters of using the participatory working time scheduling software increased. CONCLUSIONS: The effects of using participatory working time scheduling software indicated less ward-level sickness absence measured as spells and days in comparison to continuing with traditional scheduling. The encouraging findings are relevant not only to the health care sector but also to other sectors in which irregular shift work is a necessity. This study was registered with ClinicalTrials.gov (NCT02775331) before starting the intervention phase.

The effects of using participatory working time scheduling software on working hour characteristics and wellbeing: A quasi-experimental study of irregular shift work.

BACKGROUND: Studies in the health care sector indicate that good work time control is associated with better perceived wellbeing but also with non-ergonomic work schedules, such as compressed work schedules. Participatory working time scheduling is a collaborative approach to scheduling shift work. Currently, there is a lack of information on whether working hour characteristics and employees' wellbeing in irregular shift work change after implementing participatory working time scheduling. OBJECTIVE: To investigate the effects of using digital participatory working time scheduling software on working hour characteristics and well-being among Finnish hospital employees. PARTICIPANTS AND METHODS: We compared changes in objective working hour characteristics and wellbeing between 2015 and 2017 among employees (n = 677, mainly nurses and practical nurses) when using participatory working time scheduling software (participatory scheduling, n = 283) and traditional shift scheduling (traditional scheduling, n = 394). The statistical analyses were conducted using the repeated measures general linear model and the generalized logit model for binomial and multinomial variables adjusted for age, sex, education, shift work experience, control over scheduling of shifts at baseline (where applicable) and hospital district. RESULTS: The proportion of long work shifts (≥ 12 h) increased to a greater extent (F = 4.642, p = 0.032) with the participatory scheduling than with the traditional scheduling. In comparison to traditional scheduling, the perceived control over scheduling of shifts increased (OR 3.24, 95% CI 1.73-6.06) and excessive sleepiness in connection with evening shifts decreased (OR 0.40, 95% CI 0.16-0.99) significantly with participatory scheduling. None of the other wellbeing variables showed statistically significant changes in the adjusted models. CONCLUSIONS: The proportion of long work shifts and perceived control over scheduling of shifts increased more among employees using participatory working time scheduling than among those using traditional scheduling. Otherwise, using participatory working time scheduling software had little effect on both objectively measured working hour characteristics and perceived wellbeing in comparison to traditional scheduling. The results merit confirmation in a larger sample with a longer follow-up. Tweetable abstract Participatory working time scheduling combines individual flexibility and staffing requirements in shift work.

Working time dimensions and well-being: a cross-national study of Finnish and German health care employees.

Health care professionals often face irregular working hours and high work pace. We studied associations of the five working time dimensions duration (weekly working hours), timing (shift work and weekend work), on-call work, working time autonomy, and work tempo (deadline and performance pressure) with well-being among health care employees in Finland and Germany. We used data on working time dimensions and indicators of well-being (work-life conflict, poor perceived health, sleep difficulties, and fatigue) from a cohort of 5050 hospital employees (Working Hours in the Finnish Public Sector Study 2015, WHFPS) and 1450 employees in the health care sector in Germany responding to the German BAuA-Working Time Survey in 2015 (BAuA-WTS). Findings from logistic regression analyses showed that high work tempo was associated with increased work-life conflict (WHFPS: odds ratio [OR] = 3.64, 95%CI 3.04-4.36 and BAuA-WTS: OR = 2.29, 95%CI 1.60-3.27), sleep difficulties (OR = 1.75, 95%CI 1.43-2.15 and OR = 1.33, 95%CI 1.03-1.71) and fatigue (OR = 2.13, 95%CI 1.77-2.57 and OR = 1.64, 95%CI 1.29-2.10) in both datasets. Weekend work was associated with increased work-life conflict (OR = 1.48, 95%CI 1.27-1.72 and OR = 1.61, 95%CI 1.12-2.32); and high working time autonomy with decreased work-life conflict (control over the timing of breaks: OR = 0.65, 95%CI 0.55-0.78 and OR = 0.52, 95%CI 0.33-0.81). The associations between other working time dimensions and well-being were less consistent. These results suggest that tight deadlines, performance pressure, weekend work and lack of working time autonomy are linked to impaired well-being among health care employees.

Employees with shift work disorder experience excessive sleepiness also on non-work days: a cross-sectional survey linked to working hours register in Finnish hospitals.

A considerable proportion of shift workers have work schedule-related insomnia and/or excessive sleepiness, a phenomenon described as shift work disorder (SWD). There is yet a lack of evidence on whether or not employees recover from symptoms of SWD between work shifts. We studied whether SWD and its subtypes are associated with insomnia and excessive sleepiness during weekly non-work days and with 24-h sleep time. Hospital employees answered a survey on SWD, insomnia and excessive sleepiness on weekly non-work days, and 24-h sleep. To identify shift workers with night shifts (n=2,900, 18% with SWD) and SWD, we linked survey responses to employers' register on working hours. SWD included three subtypes: insomnia only (SWD-I, 4%, n=102), excessive sleepiness only (SWD-Es, 8%, n=244), and both insomnia and excessive sleepiness (SWD-IEs, 6%, n=183). Based on regression analyses, SWD was associated with excessive sleepiness on non-work days (OR: 1.42, 95% CI: 1.07-1.88) and with insomnia on non-work days (0.53, 0.31-0.91). SWD-I was associated with excessive sleepiness on non-work days (2.25, 1.31-3.87) and with shorter sleep (7-7.5 h: 1.96, 1.06-3.63; ≤6.5h: 2.39, 1.24-4.59; reference: ≥8 h). The results suggest that especially employees with SWD-I may need longer time to overcome excessive sleepiness than allowed by their roster.

Prevalence of shift work disorder among hospital personnel: A cross-sectional study using objective working hour data.

The prevalence of shift work disorder (SWD) has been studied using self-reported data and the International Classification of Sleep Disorders, Second Edition (ICSD-2) criteria. We examined the prevalence in relation to ICSD-2 and ICSD-3 criteria, work schedules and the number of non-day shifts (work outside 06:00-18:00 hours) using objective working-hours data. Secondly, we explored a minimum cut-off for the occurrence of SWD symptoms. Hospital shift workers without (n = 1,813) and with night shifts (n = 2,917) and permanent night workers (n = 84) answered a survey (response rate 69%) on SWD and fatigue on days off. The prevalence of SWD was calculated for groups with ≥1, ≥3, ≥5 and ≥7 monthly non-day shifts utilizing the working hours registry. ICSD-3-based SWD prevalence was 2.5%-3.7% (shift workers without nights), 2.6%-9.5% (shift workers with nights) and 6.0% (permanent night workers), depending on the cut-off of non-day shifts (≥7-1/month, respectively). The ICSD-2-based prevalence was higher: 7.1%-9.2%, 5.6%-33.5% and 16.7%, respectively. The prevalence was significantly higher among shift workers with than those without nights (p-values <.001) when using the cut-offs of ≥1-3 non-day shifts. Shift workers with nights who had ≥3 days with ICSD-3-based SWD symptoms/month more commonly had fatigue on days off (49.3%) than those below the cut-off (35.8%, p < .05). The ICSD-3 criteria provided lower estimates for SWD prevalence than ISCD-2 criteria, similarly to exclusion of employees with the fewest non-day shifts. The results suggest that a plausible cut-off for days with ICSD-3-based SWD symptoms is ≥3/month, resulting in 3%-6% prevalence of SWD.

Shift work and physical inactivity: findings from the Finnish Public Sector Study with objective working hour data.

Objectives Shift work is a risk factor for chronic diseases, and physical inactivity can have an influence on this association. We examined whether intra-individual changes in working time characteristics were associated with changes in physical inactivity and examined the risk factors for physical inactivity among shift workers in a 17-year longitudinal study cohort. Methods Study participants were 95 177 employees from the Finnish public sector. Work schedule information was based on questionnaire responses and additional register-based working time characteristics for 26 042 employees. The associations between working time characteristics and physical inactivity were examined using a fixed-effects logistic model. To investigate the risk factors for physical inactivity among shift workers, the odds ratios (OR) of worktime control and having small children were calculated. Results Compared with day work, shift work without night shifts was associated with physical inactivity among men [OR 1.38, 95% confidence interval (CI) 1.09-1.74], whereas shift work with night shifts was negatively associated with physical inactivity among women (OR 0.85, 95% CI 0.76-0.96). Register-based working time data confirmed that workers with a higher percentage of night shifts had a lower risk of physical inactivity. Having small children was associated with physical inactivity among shift workers (OR 1.47, 95% CI 1.32-1.65). Conclusions Both survey and objective working hour data revealed that workers having work schedules with night shifts were more likely to be physically active. Having small children was a risk factor for physical inactivity among shift workers.

Shift work with and without night work as a risk factor for fatigue and changes in sleep length: A cohort study with linkage to records on daily working hours.

We examined shift work with or without night work as a risk factor for fatigue and short or long sleep. In a prospective cohort study with 4- and 6-year follow-ups (the Finnish Public Sector study), we linked survey responses of 3,679 full-time hospital employees on sleep duration and fatigue to records on daily working hours in 2008 (baseline), 2012 and 2014. We used logistic regression to estimate risk ratios and their confidence intervals to examine whether continuous exposure to shift work or changes between shift work and day work were associated with short (≤6.5 hr) or long (≥9.0 hr) sleep over 24 hr and fatigue at work and during free days. Compared with continuous day work and adjusting for age, gender, education and fatigue/sleep duration at baseline, continuous shift work with night shifts was associated with increased fatigue during free days (risk ratio = 1.38, 95% confidence interval 1.17-1.63) and long sleep (risk ratio = 8.04, 95% confidence interval 2.88-22.5, without adjustment for education) after 6-year follow-up. Exposure to shift work without night shifts increased only long sleep after 6 years (risk ratio = 5.87, 95% confidence interval 1.94-17.8). A change from day work to shift work with or without night shifts was associated with an increased risk for long sleep, and a change from shift work to day work with a decreased risk for long sleep and fatigue. This study suggests that irregular shift work is a modifiable risk factor for long sleep and increased fatigue, probably reflecting a higher need for recovery.

Employee control over scheduling of shifts and objectively measured working hour characteristics: a cross-sectional analysis of linked register and survey data.

We aimed to study the association of perceived control over scheduling of shifts with objectively measured working hour characteristics in shift workers. The participants were 5128 hospital employees (91% women, 85% nursing personnel, average age 43 years) in period-based work (114:45h/3 weeks) from the 2015 Finnish Public Sector study. Survey responses to a measure of control over scheduling of shifts were linked to payroll data on working hour characteristics during the 91 days preceding the survey. We used multinomial logistic regression to assess differences in dichotomized proportion of working hour characteristics (being full-time worker, number of work shifts, long work weeks (>40h and >48h/week), long work shifts (>12-h), evening and night shifts, quick returns (<11h shift interval), single days off, weekend work, >4 consecutive work shifts, and variability of shift length with cut points at 10% or 25% between employees with high, intermediate, or low control over scheduling of shifts. Analyses were adjusted for age, sex, education, full-/part-time work (where applicable), duration of shift work experience, perceived work ability, children < 18 years in the household, and overall stressfulness of the life situation. Differences between age groups, men and women, and levels of work ability were examined using interaction terms. In adjusted analyses, the proportion of full-time workers was lower among employees with intermediate control over scheduling of shifts compared to those with high control (OR 0.78, 95% CI 0.61-0.98). High proportion (>25%) of weekend work was lower among employees with low control over scheduling of shifts compared to high control (OR 0.75, 95% CI 0.61-0.93). High proportion (>25%) of having >4 consecutive work shifts was associated with lower control over scheduling of shifts (OR 1.35, 95% CI 1.13-1.62). Variability of shift length was lower among employees with intermediate and low control over scheduling of shifts compared to those with high control (OR 0.78, 95% CI 0.66-0.93; OR 0.62, 95% CI 0.51-0.75, respectively). No association was observed between the level of control over scheduling of shifts and high proportion of long work weeks (>25% of >40h weeks and >10% of >48h weeks), long work shifts (>25%), quick returns (>25%), single days off (>25%), and evening or night shifts (>10%) in the whole sample. In subgroup analyses, women with low control over scheduling shifts had lower odds ratio (OR 0.58, 95% CI 0.37-0.91) and men had higher odds ratio (OR 2.97, 95% CI 1.26-6.98) for large proportion of >12-h shifts. In conclusion, the employees with high control over scheduling of shifts had slightly more often unsocial working hour characteristics than those with intermediate or low control over scheduling of shifts. The findings, however, suggest that good work time control in shift work can be possible without compromising shift ergonomics.

Sleep and alertness in shift work disorder: findings of a field study.

PURPOSE: Although shift work disorder (SWD) affects a major part of the shift working population, little is known about its manifestation in real life. This observational field study aimed to provide a detailed picture of sleep and alertness among shift workers with a questionnaire-based SWD, by comparing them to shift workers without SWD during work shifts and free time. METHODS: SWD was determined by a questionnaire. Questionnaires and 3-week field monitoring, including sleep diaries, actigraphy, the Karolinska Sleepiness Scale (KSS), EEG-based sleep recordings, and Psychomotor Vigilance Tasks (PVT), were used to study 22 SWD cases and 9 non-SWD workers. RESULTS: The SWD group had a shorter subjective total sleep time and greater sleep debt before morning shifts than the non-SWD group. Unlike the non-SWD group, the SWD group showed little compensatory sleep on days off. The SWD group had lower objective sleep efficiency and longer sleep latency on most days, and reported poorer relaxation at bedtime and sleep quality across all days than the non-SWD group. The SWD group's average KSS-sleepiness was higher than the non-SWD group's sleepiness at the beginning and end of morning shifts and at the end of night shifts. The SWD group also had more lapses in PVT at the beginning of night shifts than the non-SWD group. CONCLUSIONS: The results indicate that SWD is related to disturbed sleep and alertness in association with both morning and night shifts, and to less compensatory sleep on days off. SWD seems to particularly associate with the quality of sleep.

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

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.