Long working hours are inversely related to sick leave in the following 3 months: a 4-year registry study

Airport security personnel's working hour characteristics and associations with sickness absence-a retrospective cohort study in 2016-2019

We aimed to investigate the associations of working hour characteristics based on the international and local definitions with sickness absence (SA) among airport security personnel. The payroll-based registry data of daily working hours for 2016-2019 at one airport was limited to those with ≥30 work shifts in a year (n=377-687 employees). The conditional Poisson model for incidence rate ratios (IRR) with 95% confidence intervals (CI) was used for analyses. Based on the international definitions, only a few associations were found: each one-unit increase in weekly working hours and the number of consecutive working days were associated with a lower likelihood of SA. The local definitions were more consistently associated with SA: Each one-unit increase in shift length and time between shifts, higher variation in shift length, and the number of consecutive evening and night shifts were associated with a higher likelihood of SA. To conclude, especially the local definitions of working hour characteristics seem to be important limits for short SA. Thus, high variability of shift lengths and prolonged shifts could be avoided to reduce the risk of SA. Overall, keeping the working hours within any of the recommendations among airport security personnel could support well-being and health.

Intensity of Interprofessional Collaboration and related factors in Intensive Care Units. A descriptive cross-sectional study with an analytical approach

OBJECTIVE

To determine the Intensity of Collaboration between the intensive care professionals of a third level hospital.

METHOD

Descriptive cross-sectional study with an analytical approach.

SETTING

6 intensive care units of a third level hospital.

SAMPLE

nurses and doctors. Consecutive type non-probabilistic sampling.

DATA COLLECTION

sociodemographic, economic, motivation and professional satisfaction variables, and the intensity of collaboration using the "Scale of Intensity of Interprofessional Collaboration in Health."

RESULTS

A total of 102 health professionals (91 nurses and 11 doctors) were included. The mean overall Intensity of Collaboration (IoC) was moderate. Men showed higher scores in all factors (p<.05). The IoC global score was higher in the group of professionals with ≤10 years of experience (p=.043) and those who were highly satisfied with the profession (p=.037). Physicians presented higher scores in the global IdC (p=.037) and in the Collaboration mean (p=.020) independently in the multivariate models. A negative linear relationship (rho: -0,202, p=.042) was observed between age and the overall IoC score. Professionals aged ≤30years reported a higher perception of Shared Activities (p=.031). Negative linear relationships were observed between years of experience and total IoC score (rho: -0,202, p=.042) and patients' Perception score (rho: -0.241, p=0.015). The research activity also showed to be a variable related to a greater degree of Collaboration at a global level and in some of the factors (p<.05). The scale of IoC obtained a Cronbach's α of 0,9.

CONCLUSIONS

The intensity of interprofessional collaboration in ICUs is moderate. Professionals with experience of ≤10 years, a higher level of satisfaction and participation in research activities show a greater intensity of collaboration. Doctors perceive collaboration more intensely than nurses. All factors contribute equally to the internal consistency of the questionnaire.

Consequences of Shift Work and Night Work: A Literature Review

Nonstandard work schedules such as shift work and night work tend to trigger problems for workers in different areas. To illustrate the diversity of areas affected and the relative interest of the scientific community, we conducted a literature review of the effects of shift work and night work on workers. In particular, we intended to identify the main variables addressed in the field of health, the family sphere, and the organizational context. The literature review was carried out using the Web of Science with the following terms: "shift work", "rotating shifts", and "night work". Inclusion criteria incorporated empirical studies and articles written in Portuguese or English published in 2019. We selected 129 of the 619 articles identified. Regarding the impacts of shift work and night work, there existed a high discrepancy of focus between the three defined areas: health, family life, and organizational context. Specifically, health-related variables were the most studied (83.4%), followed by organizational variables (9.2%), and, lastly, family variables (7.4%). Based on these results, it is essential to extend the study of the two underrepresented impacts to other crucial areas, not only for the worker but also for organizations.

Sequence analysis of the combinations of work shifts and absences in health care - comparison of two years of administrative data

BACKGROUND

In health care, the shift work is arranged as irregular work shifts to provide operational hours for 24/7 care. We aimed to investigate working hour trends and turnover in health care via identification of time-related sequences of work shifts and absences among health care employees. The transitions between the work shifts (i.e., morning, day, evening, and night shifts), and absences (days off and other leaves) over time were analyzed and the predictors of change in irregular shift work were quantified.

METHODS

A longitudinal cohort study was conducted using employer-owned payroll-based register data of objective and day-to-day working hours and absences of one hospital district in Finland from 2014 to 2019 (n = 4931 employees). The working hour data included start and end of work shifts, any kind of absence from work (days off, sickness absence, parental leave), and employee's age, and sex. Daily work shifts and absences in 2014 and 2019 were used in sequence analysis. Generalized linear model was used to estimate how each identified sequence cluster was associated with sex and age.

RESULTS

We identified four sequence clusters: "Morning" (60% in 2014 and 56% in 2019), "Varying shift types" (22% both in 2014 and 2019), "Employee turnover" (13% in 2014 and 3% in 2019), and "Unstable employment (5% in 2014 and 19% in 2019). The analysis of transitions from one cluster to another between 2014 and 2019 indicated that most employees stayed in the same clusters, and most often in the "Varying shift types" (60%) and "Morning" (72%) clusters. The majority of those who moved, moved to the cluster "Morning" in 2019 from "Employee turnover" (43%), "Unstable employment" (46%) or "Varying shift types" (21%). Women were more often than men in the clusters "Employee turnover" and "Unstable employment", whereas older employees were more often in "Morning" and less often in the other cluster groups.

CONCLUSION

Four clusters with different combinations of work shifts and absences were identified. The transition rates between work shifts and absences with five years in between indicated that most employees stayed in the same clusters. The likelihood of a working hour pattern characterized by "Morning" seems to increase with age.

Length of exposure to long working hours and night work and risk of sickness absence: a register-based cohort study

Background

There is inconsistent evidence that long working hours and night work are risk factors for sickness absence, but few studies have considered variation in the length of exposure time window as a potential source of mixed findings. We examined whether the association of long working hours and night work with sickness absence is dependent on the length of exposure to the working hour characteristics.

Methods

We analysed records of working hours, night work and sickness absence for a cohort of 9226 employees in one hospital district in Finland between 2008 and 2019. The exposure time windows ranged from 10 to 180 days, and we used Cox’s proportional hazards models with time-dependent exposures to analyse the associations between working-hour characteristics and subsequent sickness absence.

Results

Longer working hours for a period of 10 to 30 days was not associated with the risk of sickness absence whereas longer working hours for a period of 40 to 180 days was associated with a lower risk of sickness absence. Irrespective of exposure time window, night work was not associated with sickness absence.

Conclusions

It is important to consider the length of exposure time window when examining associations between long working hours and sickness absence, whereas the association between night work and sickness absence is not similarly sensitive to exposure times.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07231-4.

Patterns of working hour characteristics and risk of sickness absence among shift-working hospital employees: a data-mining cohort study

OBJECTIVES

Data mining can complement traditional hypothesis-based approaches in characterizing unhealthy work exposures. We used it to derive a hypothesis-free characterization of working hour patterns in shift work and their associations with sickness absence (SA).

METHODS

In this prospective cohort study, complete payroll-based work hours and SA dates were extracted from a shift-scheduling register from 2008 to 2019 on 6029 employees from a hospital district in Southwestern Finland. We applied permutation distribution clustering to time series of successive shift lengths, between-shift rest periods, and shift starting times to identify clusters of similar working hour patterns over time. We examined associations of clusters spanning on average 23 months with SA during the following 23 months.

RESULTS

We identified eight distinct working hour patterns in shift work: (i) regular morning (M)/evening (E) work, weekends off; (ii) irregular M work; (iii) irregular M/E/night (N) work; (iv) regular M work, weekends off; (v) irregular, interrupted M/E/N work; (vi) variable M work, weekends off; (vii) quickly rotating M/E work, non-standard weeks; and (viii) slowly rotating M/E work, non-standard weeks. The associations of these eight working-hour clusters with risk of future SA varied. The cluster of irregular, interrupted M/E/N work was the strongest predictor of increased SA (days per year) with an incidence rate ratio of 1.77 (95% confidence interval 1.74-1.80) compared to regular M/E work, weekends off.

CONCLUSIONS

This data-mining suggests that hypothesis-free approaches can contribute to scientific understanding of healthy working hour characteristics and complement traditional hypothesis-driven approaches.

Overtime Work and the Incidence of Long-term Sickness Absence Due to Mental Disorders: A Prospective Cohort Study

Background

Methods

Results

Conclusion

Working time characteristics and long-term sickness absence among Danish and Finnish nurses: A register-based study

BACKGROUND

Working time regimes in Denmark and Finland share many similarities such as nursing personnel working in highly irregular shift systems. Yet, there are also differences for example in policy on when and how the employers are compensated for sickness absence.

OBJECTIVE

We aimed to investigate the association between different working hour characteristics and long-term sickness absence and whether these associations differed within various age groups in two large datasets of nursing personnel from Denmark and Finland.

DESIGN

Based on objective payroll data we used Poisson regression models to calculate incidence rate ratios with 95% confidence intervals to prospectively assess the risk of long-term sickness absence in relation to annual working hour characteristics. The analyses were adjusted for age, sex, short-term sickness absence, and weekly working hours.

SETTING(S)

Danish and Finnish nursing personnel.

PARTICIPANTS

31,729 Danish and 6970 Finnish nursing personnel with ≥ 0.5 Whole-Time Equivalent, registered in the database ≥ 1 year, 18-67 years of age with less than 30 days sickness absence in baseline year 2008.

METHODS

Working hour characteristics were assessed for 2008: time of day; day; evening; night. Duration of shift; long shifts (9-12 h); very long shifts (12-24 h); quick returns (< 11 h between two shifts); long weeks (> 40 h/week); very long weeks (> 48 h/week); and consecutive night shifts (≥ 5 night shifts). Long-term sickness absence was assessed as first incidence of 30 or more consecutive days off in 2009-2015.

RESULTS

The Danish data showed having evening work or five or more consecutive night shifts were associated with higher risk of long-term sickness absence. When excluding pregnant women, night work was also associated to higher risk of sickness absence. When stratifying on age groups, we observed a lower risk of sickness absence in the youngest age groups and a higher risk among the oldest. The Finnish results showed a higher risk of sickness absence when working nights, longs shifts, quick returns, and long work weeks. When stratifying on age groups, the results showed similar tendencies as the Danish.

CONCLUSIONS

The results show that the scheduling of working hours is likely to affect the risk of long-term sickness absence and that the risk differs in different age groups. No consistent picture was found for the results from Denmark and Finland. Differences may be due to contextual differences thus comparison of risk of sickness absence in relation to working hours between countries should be performed with caution. Tweetable abstract: A recent study from Denmark and Finland shows higher risk for long sickness absence among nurses with five or more consecutive night shifts.