A case‐crossover study of age group differences in objective working‐hour characteristics and short sickness absence

Differential impacts of reduced worktime on work-life balance in Korea

This study analyzes the heterogenous effects of reducing weekly work hour on workers' quality of life in Korea. Using longitudinal household data from the Korean Labor and Income Panel Study (KLIPS) from 2001 to 2017, this study aims to shed light on how the work hour reduction policy may differently affect workers with different levels of resources and support by demographic and socioeconomic status. Our estimates from the difference-in-differences approach exploiting the staggered implementation of the work hour reduction policy indicate that the policy increased leisure satisfaction of female workers with low educational level and female workers in regular or inflexible work setting. Given Korea's exceedingly long working hours and inequities in the labor market, a better understanding of the complex factors that affect work-life balance can be helpful in developing policies supportive of healthy work-life balance for workers. This study, to our knowledge, is the first to investigate the composition of workers in the Korean labor market and examine differential impacts of the workhour reduction policy by demographic and socioeconomic status.

A Longitudinal Study on Trajectories of Night Work and Sickness Absence among Hospital Employees

This study aimed to investigate trajectories of night shift work in irregular shift work across a 12-year follow-up among hospital employees with and without sickness absence (SA). The payroll-based register data of one hospital district in Finland included objective working hours and SA from 2008 to 2019. The number of night shifts per year was used in group-based trajectory modeling (GBTM). The results indicate that, among those who had any sickness absence episodes, the amount of night work decreased prior to the first SA. In general, trajectories of night shift work varied from stably high to low-but-increasing trajectories in terms of the number of shifts. However, a group with decreasing pattern of night work was identified only among those with sickness absence episodes but not among those without such episodes. To conclude, the identified trajectories of night work with or without sickness absences may indicate that, among those with sickness absence episodes, night work was reduced due to increasing health problems. Hence, the hospital employees working night shifts are likely a selected population because the employees who work at night are supposed to be healthier than those not opting for night work.

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.

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.

Association of rotating shift work schedules and the use of prescribed sleep medication: A prospective cohort study

We examined whether working rotating shifts, with or without night work, is associated with the purchase of prescribed sleep medication, and whether the association is dependent on age. Data were obtained from a longitudinal cohort study of Finnish public sector employees who responded to questions on work schedule and background characteristics in 2000, 2004 and 2008. The data were linked to national register data on redeemed prescriptions of hypnotic and sedative medications, with up to 11 years of follow-up. Age stratified Cox proportional hazard regression models were computed to examine incident use of medication comparing two groups of rotating shift workers (those working shifts that included night shifts and those whose schedules did not include night shifts) with day workers who worked in a similar range of occupations. Shift work with night shifts was associated with increased use of sleep medication in all age groups, after adjustments for sex, occupational status, marital status, alcohol consumption, smoking and physical activity levels (hazard ratio [HR], [95% confidence interval, CI] 1.14 [1.01-1.28] for age group ≤39 years; 1.33 [1.19-1.48] for age group 40-49 years; 1.28 [1.13-1.44] for age group ≥50 years). Shift work without nights was associated with medication use in the two older age groups (HR [95% CI] 1.14 [1.01-1.29] and 1.17 [1.05-1.31] for age groups 40-49 years and >50 years, respectively). These findings suggest that circadian disruption and older age puts rotating shift workers, and especially those who work nights, at increased risk of developing clinically significant levels of sleep problems.

The associations of working hour characteristics with short sickness absence among part- and full-time retail workers

Objective:

This study aimed to determine the associations of working hour characteristics with short (1–3 days) sickness absence (SA) among retail workers.

Methods:

As part of “RetailHours-project”, 4046 employees of 338 Finnish retail stores were included. Registry-based data on working hour characteristics and short SA were utilized. A case-crossover design was used and the odds ratios (OR) were controlled for the clustering effect and working hour characteristics.

Results:

There were strong dose–response relationships between percent of short (<11 hours) shift intervals and short SA among part- and full-time workers, men and women, and younger and older workers. Compared to workers without short shift intervals, the risk of SA was 1.47 times [95% confidence interval (CI) 1.29–1.68] higher among workers who had short shift intervals <10% of work times, 2.39 times (95% CI 2.03–2.82) higher among workers who had 10–25% of work times, and 4.03 times (CI 2.34–6.93) higher among workers who had short shift intervals >25% of work times. Weekly working hours >40 hours were associated with SA among part-time workers [odds ratio (OR) 2.22, CI 1.65–2.98], women (OR 1.62, CI 1.27–2.07) and among workers <30 years of age (OR 1.68, CI 1.20–2.35) as well as among workers aged ≥30 years (OR 1.43, CI 1.07–1.92). Furthermore, working mainly night shifts was associated with SA among full-time workers (OR 2.41, 95% CI 0.99–5.86) and women (OR 1.72, CI 1.02–2.89).

Conclusions:

A short shift interval is an important risk factor for short SA. Improving intervals between shifts and shortening long weekly working hours could reduce the risk of short SA among retail workers.

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.

Night work for hospital nurses and sickness absence: a retrospective study using electronic rostering systems

There is conflicting evidence on the effect of night work on sickness absence. Most previous studies used self-reporting to identify shift patterns and measure levels of sickness absence. In contrast, this study used objective data from electronic rosters to explore the association of nurses' patterns of night work and sickness absence. This was a retrospective longitudinal study of nurse roster data from 32 general medical and surgical wards in a large acute hospital in England. We used data from 3 years and included both registered nurses and unregistered nursing assistants. We used generalized linear-mixed models to explore the association between night work and the subsequent occurrence of sickness absence. Of 601,282 shifts worked by 1944 nursing staff, 38,051 shifts were lost due to sickness absence. After controlling for potential confounders including proportion of long (≥12 h) shifts worked, proportion of overtime shifts, proportion of shifts worked in the past 7 days, and staff grade, we found that staff working more than 75% of their shifts in the past 7 days as night shifts were more likely to experience sickness absence (aOR = 1.12; 95% CI: 1.03-1.21), compared to staff working on day only schedules. Sub-group analysis found that an association between a high proportion of night shifts worked and long-term sickness (aOR = 1.31; 95% CI: 1.15-1.50), but not short-term sickness. Working high proportions of night shifts, likely representing permanent night work schedules, is associated with a higher risk of long-term sickness absence for nurses working in inpatient adult wards in acute hospitals. The higher sickness absence rates associated with permanent night shifts could result in additional costs or loss of productivity for hospitals. This study challenges the assumption that permanent night schedules maximize circadian adjustment and, therefore, reduce health problems.