Cumulative exposure to shift work and sickness absence: associations in a five-year historic cohort

The effect of shift work on body mass index: A systematic review and meta-analysis of observational studies

CONTEXT

Shift work involves working outside the standard working hours of 9 am to 5 pm Monday to Friday and may include working evening, night, weekend, or rotating shift patterns. Since shift workers sleep less and their circadian rhythms are disrupted, they are reported to have higher body weight than day workers.

OBJECTIVE

This meta-analysis aims to determine whether shift workers (SW) are more prone to higher body mass index (BMI) than their day workers (DW) counterparts. It also addresses the question of whether the duration of shift work exposure, sex, or occupational type affect BMI value.

METHODS

Four databases that is PubMed, EBSCO Host, Scopus, and Web of Science were searched for reports published up to October 2023.

RESULTS

Sixty-three studies involving a total of 693 449 participants met our inclusion criteria. Meta-analyses showed a significant effect of shift work on BMI value (standard mean difference; SMD: 0.10 kg/m2 [95% confidence interval; 95% CI: 0.07; 0.13; p < .001]) as compared with non-shift counterparts. Subgroup analysis revealed that shift work significantly increased BMI for studies where male working on this job schedule (SMD: 0.10 kg/m2 [95% CI: 0.04; 0.17; p = .0018]) for studies where shift workers worked ≥13 years (calculated as the median of shift work experience; SMD: 0.14 kg/m2 [95% CI: 0.10; 0.18; p < .001]) as well as for studies where industrial (SMD: 0.12 kg/m2 [95% CI: 0.05; 0.19; p = .0012]) and other type of occupations were dominated (0.12 kg/m2 [95% CI: 0.07; 0.16; p < .001]).

CONCLUSIONS

We found that in general working on a shift schedule increases BMI as compared with day workers, especially in case of male employed in this job schedule, for shift workers working for long periods of time (≥13 years), and for shift workers employed in industry and other type of occupations(e.g., airline workers, firefighters, police officers, blue collar, security personnel, bus drivers, garbage collectors, railway workers, postal, oil and gas workers).

Circadian misalignment alters resting-state functional connectivity of the salience network in rotating shift workers

STUDY OBJECTIVES

This study compared resting-state functional connectivity (rsFC) of the salience network (SN) between rotating shift workers (RSWs) and controls. Furthermore, we examined whether rsFC of the SN was correlated with sleep, emotion, cognition, and attention.

METHODS

The 60 RSWs and 57 controls enrolled in this study completed self-report questionnaires and sleep diaries to assess subjective sleep quality, and polysomnography and actigraphy to evaluate objective sleep and 24-hour rest-activity rhythm parameters. The participants also underwent resting-state functional magnetic resonance imaging and structural T1 scans. We performed a seed-based rsFC analysis of the SN using the anterior cingulate cortex (ACC) and anterior insula (AI) as seed regions. Furthermore, AI and ACC rsFC were compared in RSWs and controls, and we analyzed correlations between rsFC and variables of interest showing significant group differences.

RESULTS

Compared with controls, RSWs showed reduced rsFC between the ACC and right insula, and increased rsFC of the ACC with the left occipital lobe and right superior frontal gyrus extending to the supplementary motor area (SFG/SMA). Moreover, RSWs showed reduced rsFC between the right AI and right superior parietal lobule (SPL). Finally, rsFC between the ACC and right AI was correlated with 24-hour rest-activity rhythmicity.

CONCLUSIONS

Although RSWs did not show sleep disturbance, emotional distress, cognitive impairment, or attention deficits, alterations of right insula, left occipital lobe, right SFG/SMA, and right SPL rsFC in the SN indicate that impairments in salience detection and top-down attentional control may emerge in shift workers over time.

The relation between routines for shiftwork scheduling and sickness absence at a Norwegian hospital: A cross-sectional study

BACKGROUND

Shift work is associated with negative health outcomes. Routines for scheduling of shift work can help reduce negative health outcomes of shift work and improve work-life balance and social well-being for nurses working shift work.

OBJECTIVE

To investigate the association between organizational units' routines for shift work scheduling and nurses' sickness absence at the unit level.

DESIGN

Cross-sectional study design combining quantitative questionnaire data on shift work scheduling routines with data of mean percentage of sickness absence at the unit, mean level of exhaustion at the unit, mean age and percentage of women working at the unit.

PARTICIPANTS

A total of 126 leaders at organizational units with nurses working shift work schedule at Oslo University Hospital answered a questionnaire about shift work scheduling.

MEASURES

Three aspects of health-promoting shift work scheduling (fatigue-reducing scheduling, organizational health measures, and individual adaptation) and the extent to which operational considerations were made during shift work scheduling were used as independent variables. Covariates were mean age of nurses at each unit, mean percent female nurses, and mean exhaustion at unit level. Percent sickness absence was used as a dependent variable.

METHODS

Questionnaire data on shift work scheduling routines was merged with information on average age of employees in the unit, ratio female nurses, and units' average score on exhaustion. Multivariable linear regression analyses were used to assess the contribution of routines for shift work scheduling after controlling for mean level of exhaustion, average age, and proportion of women at each unit.

RESULTS

The factors "fatigue reducing scheduling", "organizational health measures" and "operational considerations" had no observed total effect on mean sickness absence. Individual adjustment in shift work scheduling had a direct negative association with sickness absence after controlling for other shift work scheduling routines, exhaustion, age, and gender.

CONCLUSIONS

There is a relationship between the units' routines for shift work scheduling and mean sickness absence at the unit, and the possibility of individual adjustment was the only aspect of shift work scheduling that had an above-zero association with sickness absence.

Night and evening shifts and risk of calling in sick within the next two days - a case-crossover study design based on day-to-day payroll data

OBJECTIVE

Night and evening work is associated with risk of sickness absence, but little is known about the acute effects of these types of shifts on sickness absence. The aim of the current study is therefore to examine the risk of calling in sick within two days after a night or an evening shift.

METHODS

By use of a case-crossover design, odds of calling in sick within two days after a night or an evening shift compared to day shifts were analyzed within the same person. Day-to-day information on shifts and sickness absence were derived from the Danish Working Hour Database on 44 767 cases. Data were analyzed using conditional logistic regression. The analyses were supplemented by extensive testing of methodological choices.

RESULTS

Analyses showed higher odds of calling in sick after a night shift [odds ratio (OR) 1.22, 95% confidence intervak (CI) 1.14-1.30] and lower odds after an evening shift (OR 0.89, 95% CI 0.84-0.93) compared to day shifts within the same person. Testing of methodological choices suggested that in particular the duration of case and control periods, time between these periods along with the number of control periods affected the results.

CONCLUSION

This large and unique within-person study among Danish hospital employees indicate that the risk of calling in sick is affected by the types of shifts, independently of sex, age, and time-invariant confounding. Extensive testing identified important methodological choices eg, length and number of included periods to consider when choosing the case-crossover design.

Night Work and Sustainable Working Life-A Prospective Trajectory Analysis of Swedish Twins

The aim was to investigate the changes in sustainable working life over 10-13 years of follow-up and the effect of baseline night work. Data from the Swedish national registers were used to define sustainable working life. Survey data in the 1998-2003 "SALT" with 34,680 twins or in the 2004-2006 "STAGE" with 19,637 twins were utilized to assess night work at baseline. Group-based trajectory and multinomial regression models were applied. The results of the SALT cohort yielded five trajectory solutions: stable sustainable working life (40%), stable lack of sustainable working life (25%), later decreasingly sustainable working life (15%), increasingly sustainable working life (14%), and early decreasingly sustainable working life (7%). In the STAGE cohort, four trajectories were detected: stable sustainable working life (83%), decreasingly sustainable working life (7%), stable lack of sustainable working life (5%), and increasing sustainable working life (5%). Night work was associated with the decreasing or increasing sustainable working life in the trajectory groups. To conclude, the largest parts of both cohorts followed trajectories of stable sustainable working lives. Night work was associated with both the trajectories of decreasing and increasing sustainable working lives.

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.

Risk factors for absenteeism due to musculoskeletal diseases in workers in the judiciary sector

Introduction

Musculoskeletal diseases represent an important health problem for workers, due to the degree of suffering caused by pain and to the high frequency of absenteeism.

Objectives

To identify risk factors for absenteeism due to musculoskeletal disease in employees at a judiciary court and to describe incidence, frequency, and duration of sick leaves.

Methods

This is a 6-year follow-up study conducted in the state of Bahia, Brazil. The dependent variable was absenteeism, measured by the time of the first sick leave in the period. The Kaplan-Meier method was used to estimate survival functions, whereas risk factors for absenteeism were obtained by Cox regression.

Results

Overall, 594 workers took sick leaves, with an incidence of 23% at the end of the period. The most frequent diagnoses were back pain (38.5%), shoulder lesions (11.7%), and synovitis and tenosynovitis (8.8%). Cases of one episode of sick leave per worker over the 6 years predominated (42.8%). Cox regression multivariate analysis identified the following variables as posing the greatest risk for sick leave: female sex (hazard ratio 1.39), age older than 40 years (hazard ratio 2.57), judicial technician workers (hazard ratio 1.48), and administrative workers (hazard ratio 1.30).

Conclusions

Women, older adults, and individuals who hold technical positions are worthy of attention from health management department of the court, since they presented the highest rates of incapacity to work during the study period. Back pain was the main reason for musculoskeletal disability.

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.

Impact of a change in rostering practices on absenteeism: An observational descriptive study

Background:

There was a change in rostering practice from a regular three-shift system to an irregular three-shift system.

Objective:

This study observed the trend of absenteeism before and after a change in rostering practice.

Methods:

An observational design was used to collect sick-leave data from six months before the change in rostering practice to 12 months after. The average number of sick-leave days per month before and after the change were compared. Data for nursing hours per patient day (NHPPD) were also collected.

Results:

An increase in the number of sick-leave days was seen in three out of five wards following the change in rostering practice. Average sick leave across the five wards increased from 173.7 days per month before the change to 213.4 days per month after the change. Data for NHPPD showed no drastic change in manpower (e.g. resignation/training leave) during this period.

Conclusions:

There was an observed increase in absenteeism following the change in the rostering practice of nurses.

The Association between Shift Work and Health-Related Productivity Loss due to Either Sickness Absence or Reduced Performance at Work: A Cross-Sectional Study of Korea

Background: The purpose of the present study was to investigate the association between shift work and health-related productivity loss (HRPL) due to either sickness absence or reduced performance at work. Methods: From January 2020 to February 2020, data were collected using the web-based questionnaire. Workers in Korea (n = 4197) were selected with the convenience sampling method. To evaluate HRPL, the Korean version of the “Work Productivity and Activity Impairment Questionnaire” was used. The nonparametric association between shift work and HRPL was determined. To estimate productivity loss by shift work, generalised linear models were used, and the productivity loss of workers who did not do shift work was used as the reference. Contrasts between the reference (non-shift work) and shift work, including the shift work subtype, were demonstrated. In the adjusted model, age, gender, and occupation were included as covariates. To test whether there were differences in this association by gender, a gender-stratified analysis was conducted. Results: Shift work significantly reduced productivity (2.5% points; 95% CI: 0.2–4.6). The fixed night shift had the largest productivity loss (7.7% points; 95% CI: 1.8–13.7), and the relationship between HRPL and shift work was more prominent among female workers. Conclusions: Shift work is related to an increase in HRPL, and there are gender differences in this association. Our study further indicated that a fixed night shift is most detrimental to workers’ health and productivity.

Sickness absenteeism, work performance, and healthcare use due to respiratory infections for shift and non-shift workers

This study aimed to compare sickness absenteeism, work performance, and healthcare use due to respiratory infections, as well as general sickness absenteeism and work performance between shift and non-shift workers. In this study, 589 shift and non-shift workers employed in hospitals were included. For 6 months, participants kept a daily record of their influenza-like illness/acute respiratory infection (ILI/ARI) symptoms using a diary application. After an episode of ILI/ARI symptoms ended, participants (n = 531) were questioned about their sickness absenteeism (occurrence and duration in hours), work performance (on a 10 point scale), and healthcare use during the ILI/ARI episode. At the end of the 6 months follow-up, participants (n = 498) were also asked about general sickness absenteeism and work performance in the past 4 weeks. Mixed-model and regression analyses were used to compare absenteeism, work performance, and healthcare use between shift and non-shift workers. No differences were found in sickness absenteeism [Odds Ratio (OR) = 1.00 (95%‒Confidence Interval (CI): 0.61‒1.64)] and work performance [Regression coefficient (B) = -0.19 (95%‒CI: -0.65‒0.26)] due to ILI/ARI between shift and non-shift workers. In addition, healthcare use due to ILI/ARI was similar between shift and non-shift workers. Furthermore, similar general sickness absenteeism rates and work performance levels were found between shift and non-shift workers. As this is the first study that examined the associations with shift work due to ILI/ARI, further studies are needed to confirm our findings.

Modeling sickness absence data: A scoping review

The identification of sick leave determinants could positively influence decision making to improve worker quality of life and to reduce consequently costs for society. Sick leave is a research topic of interest in economics, psychology, health and social behaviour. The question of choosing an appropriate statistical tool to analyse sick leave data can be challenging. In fact, sick leave data have a complex structure, characterized by two dimensions: frequency and duration, and involve numerous features related to individual and environmental factors. We conducted a scoping review to characterize statistical approaches to analyse individual sick leave data in order to synthesise key insights from the extensive literature, as well as to identify gaps in research. We followed the PRISMA methodology for scoping reviews and searched Medline, World of Science, Science Direct, Psycinfo and EconLit for publications using statistical modeling for explaining or predicting sick leave at the individual level. We selected 469 articles from the 5983 retrieved, dated from 1981 to 2019. In total, three types of model were identified: univariate outcome modeling using for the most part count models (438 articles), bivariate outcome modeling (14 articles), such as multistate models and structural equation modeling (22 articles). The review shows that there was a lack of evaluation of the models as predictive accuracy was only evaluated in 18 articles and the explanatory accuracy in 43 articles. Further research based on joint models could bring more insights on sick leave spells, considering both their frequency and duration.

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.

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.

The contribution of physical working conditions to sickness absence of varying length among employees with and without common mental disorders

Aims: The aim was to examine whether the contribution of physical work exposures to the risk of sickness absence (SA) is different between those with and without common mental disorders (CMD). Methods: We used questionnaire data on four work exposures and CMD from 6159 participants of the Helsinki Health Study cohort with 12,458 observations from three surveys (2000–2002, 2007 and 2012). We formed combination exposures for the work exposures (hazardous exposures, physical workload, computer and shift work) with CMD. Associations with SA of different length were examined with negative binomial regression models. Results: We observed stronger associations for CMD with SA than for the individual work exposures. The strength of the associations for hazardous exposures and physical workload increased with length of SA, especially when the participant also had CMD. The strongest associations for the combined exposures were observed for SA ⩾15 days, the rate ratios being 2.63 (95% CI 2.27–3.05) among those with hazardous exposure and CMD, and 3.37 (95% CI 2.93−3.88) among those with heavy physical workload and CMD. Conclusions: Employees with hazardous exposures or physical workload combined with CMD were at the highest risk of SA compared with those without these exposures or with only one exposure.

Exposure to working-hour characteristics and short sickness absence in hospital workers: A case-crossover study using objective data

INTRODUCTION

Shift work characteristics, such as the number of night shifts or quick returns, are linked to disturbed sleep and greater work-life conflict, but little is known about their association with short sickness absences. Studies utilizing objective working-hour characteristic data can provide knowledge on specific shift work characteristics that may associate with sick leave. We investigated the association between working-hour characteristics in shift work and the incidence of short (1-3 days) sickness absences.

PARTICIPANTS AND METHODS

The individual-level data were collected from the employers' electronic working time records of the Finnish Public Sector study. The final analytical sample was restricted to the first incidence of short sickness absence (1-3 days) from January 1, 2008 to the end of 2015. We studied employees with shift work contracts (n = 12 156) and day work contracts (n = 6225). Of these, 89% were female workers, with a mean age of 37.1 years, and 12% worked part-time. We calculated type of shift (morning, day, evening, and night), quick returns (< 11 h between two work shifts), length of work shift and weekly working time. We utilized case-crossover study design to compare the working-hour characteristics of the 28 days preceding sickness absence (exposure window) and those of the 28 days before the exposure window (control window), using conditional logistic regression models for odds ratios with 95% Confidence Intervals (95%CI).

RESULTS

Exposure to ≥ 2, and especially ≥ 4 consecutive night shifts associated with an increased likelihood of short sickness absence (OR 1.24, 95%CI 1.12-1.38 and OR 1.54, 95%CI 1.10-2.15, respectively) among shift workers, whereas a high number (> 25%) of evening shifts and having ≥ 2 consecutive evening shifts associated with lower odds of sickness absence. Over 40-hour weeks (OR 1.29, 95%CI 1.20-1.39), over 48-hour weeks (OR 1.24, 95%CI 1.01-1.54) and quick returns (OR 1.02, 95%CI 1.01-1.02) increased the likelihood of sickness absence. Having only a few (0-1 or 2-3) quick returns over 28 days decreased the likelihood of sickness absence (ORs 0.46 and 0.67), whereas having ≥ 5 quick returns over 28 days increased it (OR 1.88, 95%CI 1.76-1.99). These associations were similar among both shift and day workers.

CONCLUSIONS

Long working hours, several consecutive night shifts and quick returns increase the risk of short sickness absence. These working-hour characteristics should be avoided in shift scheduling to minimize sickness absence and increased costs for the employer.

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

PURPOSE

The aim of this study was to investigate the effects of long working hours (≥ 12 h shifts) on sick leave using objective records of shift work exposure and of sick leave.

METHODS

A total of 1538 nurses (mean age 42.5, SD 12.0; response rate 42%) participated. Payroll and archival sick leave data over a 4-year period were retrieved from employers' records and aggregated over every third calendar month. A multilevel negative binomial model was used to investigate the effects of exposure to long working hours, on subsequent sick leave rates the following 3 months. Covariates included prior sick leave, number of shifts worked, night and evening shifts, personality, and demographic characteristics.

RESULTS

Exposure to long working hours was associated with fewer sick leave days in the subsequent 3 months [adjusted model, incidence rate ratio (IRR) = 0.946, 95% CI 0.919-0.973, p < 0.001]. The interaction long working hours by a number of work days showed that sick leave days the subsequent 3 months was higher by long shifts when number of shifts was high compared to when number of shifts was low [adjusted model, IRR 1.002, 95% CI 1.000-1.004, p < 0.05].

DISCUSSION

Long working hours was associated with fewer sick leave days. The restorative effects of extra days off with long working hours are discussed as possible explanations to this relationship.

Bio-mathematical fatigue models predict sickness absence in hospital nurses: An 18 months retrospective cohort study

This study examined the associations between bio-mathematical fatigue-risk scores and sickness absence (SA) in hospital nurses over 18 months. Work schedules and SA data were extracted from the hospital's attendance system. Fatigue-risk scores were generated for work days using the Fatigue Audit InterDyne (FAID) and Fatigue Risk Index (FRI). Over the study period, 5.4% of the shifts were absence shifts. FAID-fatigue ranged from 7 to 154; scores for a standard 9-5 work schedule can range from 7 to 40. Nurses with high FAID-scores were more likely to be absent from work when compared to standard FAID-scores (41-79, OR = 1.38, 95%CI = 1.21-1.58; 80-99, OR = 1.63, 95%CI = 1.37-1.94 and ≥ 100, OR = 1.73, 95%CI = 1.40-2.13). FRI-fatigue ranged from 0.9 to 76.8. When FRI-scores were >60, nurses were at 1.58 times (95%CI = 1.05-2.37) at increased odds for SA compared to scores in the 0.9-20 category. Nurse leaders can use these decision-support models to adjust high-risk schedules or the number of staff needed to cover anticipated absences from work.

The Relationship Between Shift Work and Men's Health

BACKGROUND

More than 21 million Americans and nearly 20% of the U.S. workforce are shift workers. Non-standard shift work, defined as work that falls outside of 6 am-6 pm, can lead to poor diet, exercise, and sleep habits that lead to decreased productivity, increased workplace accidents, and a variety of negative health outcomes.

AIM

To investigate the associations between shift work exposure and chronic medical conditions such as metabolic syndromes, cardiovascular disease, gastrointestinal disturbances, and depression as well as urologic complications including hypogonadism, male infertility, lower urinary tract symptoms, and prostate cancer with a focus on the effects of shift work sleep disorder (SWSD) on the severity of these negative health outcomes.

METHODS

We reviewed the literature examining effects of shift work and SWSD on general and urologic health.

OUTCOMES

We produced a summary of effects of shift work on health with focus on the increased risk of negative health outcomes in non-standard shift workers, particularly those with SWSD, when compared to daytime workers or workers without SWSD.

RESULTS

Studies have associated non-standard shift work schedules and poor health outcomes, including increased risks of diabetes mellitus, dyslipidemia, hypertension, heart disease, peptic ulcer disease, and depression, in shift workers. However, few studies have focused on the role that shift work plays in men's urologic health. Current evidence supports associations between non-standard shift work and increased hypogonadal symptoms, poor semen parameters, decreased fertility, lower urinary tract symptoms, and prostate cancer. These associations are strengthened by the presence of SWSD, which affects up to 20% of shift workers. Unfortunately, interventions, such as planned naps, timed light exposure, melatonin, and sedative hypnotics, aimed at alleviating excessive nighttime sleepiness and daytime insomnia in non-standard shift workers experiencing SWSD, are limited and lack strong evidence to support their efficacy.

CONCLUSIONS

Non-standard shift work has been associated with a variety of negative health outcomes and urologic complications, especially with concurrent SWSD. Recognition of these increased risks among shift workers can potentially aid in more effective screening of chronic health and urologic conditions. Non-pharmacologic treatment of SWSD focuses on behavioral therapy and sleep hygiene while melatonin, hypnotics, and stimulants are used to alleviate insomnia and excessive sleepiness of SWSD. Further research into both pharmacologic and non-pharmacologic therapies for SWSD is needed to establish more definitive guidelines in the treatment of SWSD in order to increase productivity, minimize workplace accidents, and improve quality of life for shift workers. Deng N, Kohn TP, Lipshultz LI, et al. The Relationship Between Shift Work and Men's Health. Sex Med Rev 2018;6:446-456.