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OBJECTIVE: This study evaluated the effectiveness of the promotion of postural shift intervention using a dynamic seat cushion on the 6-month incidence of neck and low-back pain among high-risk office workers. METHODS: In a cluster-randomized controlled trial (RCT), 133 office workers were randomly assigned, at cluster level, to intervention (N=67) and control (N=66) groups. The intervention group received a dynamic seat cushion to encourage postural shifts during sitting, while the control group received a placebo seat pad. Primary outcomes were 6-month incidence of neck and low-back pain. Secondary outcomes included sitting discomfort, pain intensity, disability, and trunk muscle performance. Analyses utilized Cox proportional hazard models. RESULTS: During the 6-month period, 15% of participants in the intervention group developed neck pain and 10% developed low-back pain. For the control group, this was 65% and 59%, respectively. Hazard rate (HR) ratios, after adjusting for biopsychosocial factors, indicated a protective effect of the intervention for neck pain [HR_adj 0.19, 95% confidence interval (CI) 0.09–0.39, P

Worldwide, work-related injury and disease form a major challenge to employers, workers’ unions, governments, and most importantly workers themselves. To combat this, a broad range of occupational health interventions has been developed that are typically aimed at preventing work-related illnesses and disease, and/or improving return-to-work after sickness absence or work disability (1). As resources are restricted, however, decision-makers increasingly call upon advisors and researchers to demonstrate that occupational health interventions are not only effective but also efficient in terms of their resource implications (2). For instance, a qualitative assessment among decision-makers in the Ontario healthcare sector showed that financial information – mostly in the form of a business case – can be a key deciding factor of whether to go forward with implementation of an intervention or occupational health service (3). In the past decades, various economic studies have been performed in the area of occupational health. These studies can be roughly divided into: (i) studies assessing the cost of ill health among workers and (ii) economic evaluations of interventions (1). Economic evaluations typically assess the cost-effectiveness and/or return-on-investment of occupational health interventions by comparing their incremental costs to their additional effects expressed in terms of physical units and monetary values, respectively. In recent years, various examples of such studies have been published in The Scandinavian Journal of Work, Environment & Health. Russo et al (4), for example, reported on the development of a cost-estimation method for work-related stress, while Finnes et al (5) assessed the long-term cost-effectiveness of return-to-work interventions for mental disorder-related absence. In another example, Lutz et al (6) summarized and critically appraised the health economic evidence on worksite physical activity and/or nutrition programs. Despite these good examples, the methodological quality of many economic evaluations in occupational health is far from optimal (6–8). To illustrate, many economic evaluations used a wide variety of – sometimes invalid – methods for estimating productivity-related costs, few economic evaluations validly assessed and/or reported on the uncertainty surrounding their results, and the follow-up duration of many economic evaluations is relatively short (6–8). Even though various efforts have been made to improve the methodological quality of economic evaluations in occupational health [eg, (2)], three issues still warrant specific attention: (i) measurement and valuation of productivity-related costs, (ii) analysis of trial-based economic evaluations, and (iii) use of modelling techniques. In the following, we will discuss these issues in greater detail and give pointers on where occupational health can benefit from cooperating with other research fields. Challenges for economic evaluations in occupational health Productivity-related costs are often the central point of focus in both cost of illness studies and economic evaluations in occupation health. This is because the impact of (work-related) injury and disease on productivity-related costs is substantial (9). Hassard et al (10), for example, found that productivity-related costs accounted for 70–90% of the total societal cost of work-related stress. Unfortunately, however, measuring and valuing productivity losses is complex and is likely even further complicated by the broad range of methods available for doing so. To illustrate, sickness absence can be measured objectively using company records or subjectively using a broad range of self-reported questionnaires (e.g. WHO-HPQ, PRODISQ). To complicate matters even further, sickness absence days can be valued using various methodological approaches (eg, the human capital or friction cost approaches) and different kinds of unit prices (eg, actual wage rates, average income) (2, 9). Reduced productivity while being at work (ie, presenteeism), on the other hand, is typically measured using simple numeric rating scales and can again be valued using a wide variety of approaches and unit prices. Consequently, economic evaluations in occupational health are highly heterogeneous in terms of their productivity-related cost estimation methods and large differences exist across studies in terms of the validity and transparent reporting of applied methods (9). We therefore agree with other authors that guidelines should be developed for measuring and valuing productivity-related costs (9). These guidelines should be specific to the field of occupational health and ideally consider cross-country differences. This is important because methods that are appropriate for a certain economic perspective and/or country are not necessarily appropriate for other perspectives and/or countries. In the Netherlands, for example, the “Dutch manual for costing studies in healthcare” recommends to only include productivity losses that occur during the period employers need to replace a sick worker (ie, friction cost approach) (11), whereas – in practice – Dutch employers are obliged to pay ≥70% of their sick workers’ wages for the duration of two years. Hence, it is questionable whether the recommended friction cost approach is appropriate from the company perspective as well. Additionally, we would like to encourage future studies to assess the appropriateness of the simple numeric rating scales that are currently being used for estimating presenteeism costs, and/or whether presenteeism cost estimates are preferably based on more detailed and validated productivity questionnaires, such as the “Individual Work Performance Questionnaire” (12). If the latter is the case, research is needed to assess how to validly convert workers’ responses to such questionnaires into monetary values. Ideally, this is done using objective information on productivity outputs, for instance by systematic worksite observations (13). The statistical quality of many economic evaluations in occupational health is poor (9, 14). Amongst others, baseline imbalances, the skewed nature of cost data, and the clustering of data are often neglected. On top of that, missing data are frequently handled using inappropriate methods, such as a complete-case analysis, and some studies do not even report on the uncertainty surrounding their cost-effectiveness and/or return-on-investment estimates (8). Inappropriate statistical methods, however, can lead to incorrect results and/or conclusions, and hence a sub-optimal allocation of available occupational health resources (9, 14). Improving the statistical quality of economic evaluations in occupational health starts with the development of recommendations on how to analyze them appropriately, accompanied by the publication of tutorial papers and annotated software codes. Also, as extensive progress has been made concerning the statistical analysis of economic evaluations in other research fields [eg, (14–16)], the quality of economic evaluations in occupational health will also benefit from an increased collaboration with health economists, biostatisticians, and/or econometricians. In the present issue, Finnes et al (5) provide a good example of such a collaboration, which in turn resulted in a state-of-the-art economic evaluation from the occupational health as well as economic perspective. Most economic evaluations in occupational health are solely based on worker-level data (6–8). Possible limitations of such an approach are that worker-level data are typically only available for a restricted number of workers, relatively short follow-up durations, and a limited number of comparators. To deal with these issues, researchers could make use of analytic modelling where economic evaluations are conducted by synthesizing information from multiple sources (eg, using Markov models) (2). Analytic modelling might, for example, be used to extrapolate economic evaluation results beyond the follow-up of a trial. This may be particularly informative for occupational health interventions that are expected to impact costs and/or effects for an extensive period of time (eg, worksite health promotion programs). Analytic modelling might also be used when researchers want to compare a number of interventions and/or when they are confronted with a large number of uncertain variables. Mofidi et al (17) recently provided a good example of analytic modelling in occupational health by assessing the cost-effectiveness of seven different combinations of silica exposure reduction interventions, while simultaneously assessing the robustness of the study results to a broad range of uncertain factors. Again, as extensive progress concerning analytic modelling has taken place in other research fields [eg, (18)], occupational health researchers aiming to use such techniques will likely benefit from collaborating with other research fields. What to do next? Economic evaluations in occupational health are confronted with various scientific challenges that need to be addressed to improve their scientific rigor, and hence the validity of their results and conclusions. To tackle some of these challenges, we encourage researchers to develop guidance and recommendations concerning the measurement and valuation of productivity-related costs as well as the statistical analysis of economic evaluations and to increasingly collaborate with researchers from other fields (eg, when aiming to use analytic modelling techniques). References 1. Burdorf A. Economic evaluation in occupational health-its goals, challenges, and opportunities. Scand J Work Environ Health 2007;33(3):161-4. https://doi.org/10.5271/sjweh.1127 2. van Dongen JM, van Wier MF, Tompa E, Bongers PM, van der Beek AJ, van Tulder MW, et al. Trial-based economic evaluations in occupational health: principles, methods, and recommendations. J Occup Environ Med 2014;56(6):563-72. https://doi.org/10.1097/JOM.0000000000000165 3. van Dongen JM, Tompa E, Clune L, Sarnocinska-Hart A, Bongers PM, van Tulder MW, et al. Bridging the gap between the economic evaluation literature and daily practice in occupational health: a qualitative study among decision-makers in the healthcare sector. Implement Sci 2013;8(1):1-12. https://doi.org/10.1186/1748-5908-8-57 4. Russo S, Ronchetti M, Di Tecco C, Valenti A, Jain A, Mennini FS, et al. Developing a cost-estimation model for work-related stress: An absence-based estimation using data from two Italian case studies. Scand J Work Environ Health 2021;47(4):318-27. https://doi.org/10.5271/sjweh.3948 5. Finnes A, Hoch JS, Enebrink P, Dahl J, Ghaderi A, Nager A, et al. Economic evaluation of return-to-work interventions for mental disorder-related sickness absence: two years follow-up of a randomized clinical trial. Scand J Work Environ Health – online first. https://doi.org/10.5271/sjweh.4012 6. Lutz N, Clarys P, Koenig I, Deliens T, Taeymans J, Verhaeghe N. Health economic evaluations of interventions to increase physical activity and decrease sedentary behavior at the workplace: a systematic review. Scand J Work Environ Health 2020;46(2):127-42. https://doi.org/10.5271/sjweh.3871 7. Grimani A, Bergström G, Casallas MIR, Aboagye E, Jensen I, Lohela-Karlsson M. Economic evaluation of occupational safety and health interventions from the employer perspective: A systematic review. J Occup Environ Med 2018;60(2):147-66. https://doi.org/10.1097/JOM.0000000000001224 8. van Dongen JM, Proper KI, van Wier MF, van der Beek AJ, Bongers PM, van Mechelen W, et al. A systematic review of the cost-effectiveness of worksite physical activity and/or nutrition programs. Scand J Work Environ Health 2012;38(5):393-408. https://doi.org/10.5271/sjweh.3275 9. Steel J, Godderis L, Luyten J. Productivity estimation in economic evaluations of occupational health and safety interventions: a systematic review. Scand J Work Environ Health 2018;44(5):458-74. https://doi.org/10.5271/sjweh.3715 10. Hassard J, Teoh KR, Visockaite G, Dewe P, Cox T. The cost of work-related stress to society: A systematic review. J Occup Health Psychol 2018;23(1):1-17. https://doi.org/10.1037/ocp0000069 11. Versteegh M, Knies S, Brouwer W. From good to better: new Dutch guidelines for economic evaluations in healthcare. Pharmacoeconomics 2016;34(11):1071-4. https://doi.org/10.1007/s40273-016-0431-y 12. Koopmans L, Bernaards C, Hildebrandt V, van Buuren S, van der Beek AJ, de Vet HC. Development of an individual work performance questionnaire. Int J Product Perform Manag 2013;62(1):6-28. https://doi.org/10.1108/17410401311285273 13. Meerding WJ, IJzelenberg W, Koopmanschap MA, Severens JL, Burdorf A. Health problems lead to considerable productivity loss at work among workers with high physical load jobs. J Clin Epidemiol 2005;58(5):517-23. https://doi.org/10.1016/j.jclinepi.2004.06.016 14. Mutubuki EN, El Alili M, Bosmans JE, Oosterhuis T, J Snoek F, Ostelo RWJG, et al. The statistical approach in trial-based economic evaluations matters: get your statistics together! BMC Health Serv Res 2021;21(1):475. https://doi.org/10.1186/s12913-021-06513-1 15. Gomes M, Grieve R, Nixon R, Edmunds WJ. Statistical methods for cost-effectiveness analyses that use data from cluster randomized trials: a systematic review and checklist for critical appraisal. Med Decis Making 2012;32(1):209-20. https://doi.org/10.1177/0272989X11407341 16. Faria R, Gomes M, Epstein D, White IR. A guide to handling missing data in cost-effectiveness analysis conducted within randomised controlled trials. Pharmacoeconomics 2014;32(12):1157-70. https://doi.org/10.1007/s40273-014-0193-3 17. Mofidi A, Tompa E, Mortazavi SB, Esfahanipour A, Demers PA. A probabilistic approach for economic evaluation of occupational health and safety interventions: a case study of silica exposure reduction interventions in the construction sector. BMC Public Health 2020;20(1):1-12. https://doi.org/10.1186/s12889-020-8307-7 18. Krijkamp EM, Alarid-Escudero F, Enns EA, Jalal HJ, Hunink MM, Pechlivanoglou P. Microsimulation modeling for health decision sciences using R: a tutorial. Med Decis Making 2018;38(3):400-22. https://doi.org/10.1177/0272989X18754513

OBJECTIVES: This study aims to provide insight into (i) how the combination of paid work and family care is longitudinally associated with gender-related differences in depressive symptoms and (ii) the role of work characteristics in this association. METHODS: Data were derived from STREAM, a Dutch prospective cohort study of older workers aged 45–64 years. Respondents were included if they were employed in at least one measurement between 2015 and 2017 (N=12 447). Mixed-models were applied to disentangle between-person (BP) and within-person (WP) effects of family caregiving on depressive symptoms. Analyses were stratified by gender. Work characteristics (social support, autonomy, emotional and mental workload) were separately added to the multivariable models. RESULTS: For older employees, family caregiving was positively associated with depressive symptoms between and within persons for both women [BP B=0.80, 95% confidence interval (CI) 0.52–1.08; WP B=0.32, 95% CI 0.08–0.56] and men (BP B=0.75, 95% CI 0.45–1.05; WP B=0.25, 95% CI 0.01–0.48). Social support at work reduced the adverse effect of family care on depressive symptoms for women (BP) and men (BP and WP). Emotional workload partly explained the effect of family care for both women and men (BP). CONCLUSIONS: The longitudinal association between family care and mental health was similar for male and female employees. Resources at work (ie, social support) could protect caregiving employees against depressive symptoms. More research is needed regarding the relative impact of the care context compared to the work context of working family caregivers.

OBJECTIVES: Emerging evidence suggests contrasting health effects for leisure-time and occupational physical activity. In this systematic review, we synthesized and described the epidemiological evidence regarding the association between occupational physical activity and cardiovascular disease (CVD) mortality. METHODS: A literature search was performed in PubMed, Embase, CINAHL, PsycINFO and Evidence-Based Medicine Reviews, from database inception to 17 April 2020. Articles were included if they described original observational prospective research, assessing the association between occupational physical activity and CVD mortality among adult workers. Reviews were included if they controlled for age and gender and at least one other relevant variable. We performed meta-analyses on the associations between occupational physical activity and CVD mortality. RESULTS: We screened 3345 unique articles, and 31 articles (from 23 studies) were described in this review. In the meta-analysis, occupational physical activity showed no significant association with overall CVD mortality for both males [hazard ratio (HR) 1.00, 95% confidence interval (CI) 0.87–1.15] and females (HR 0.95, 95% CI 0.82–1.09). Additional analysis showed that higher levels of occupational physical activity were non-significantly associated with a 15% increase in studies reporting on the outcome ischemic heart disease mortality (HR 1.15, 95% CI 0.88–1.49). CONCLUSIONS: While the beneficial association between leisure-time physical activity and CVD mortality has been widely documented, occupational physical activity was not found to have a beneficial association with CVD mortality. This observation may have implications for our appreciation of the association between physical activity and health for workers in physically demanding jobs, as occupational physical activity may not be health enhancing.

OBJECTIVE: This study evaluated the effects of the promotion of active breaks and postural shifts on new onset of neck and low-back pain during a 6-month follow-up among high-risk office workers. METHODS: A 3-arm cluster-randomized controlled trial with 6-month follow-up was conducted among healthy but high-risk office workers. Participants were recruited from six organizations in Bangkok, Thailand (N=193) and randomly assigned at cluster level into active break intervention (N=47), postural shift intervention (N=46), and control (N=100) groups. Participants in the intervention groups received a custom-designed apparatus to facilitate designated active breaks and postural shifts during work. Participants in the control group received a placebo seat pad. The primary outcome measure was new onset of neck and low-back pain during 6-month follow-up. Analyses were performed using Cox proportional hazard models. RESULTS: One-hundred and eighty-six (96%) predominantly female participants were successfully followed up over six months. New onset of neck pain during the 6-month follow-up occurred in 17%, 17%, and 44% of the participants in the active break, postural shift, and control groups, respectively. For new onset of low-back pain, these percentages were 9%, 7%, and 33%, respectively. Hazard rate (HR) ratios after adjusting for biopsychosocial factors indicated a protective effect of the active break and postural shift interventions for neck pain [HRadj 0.45, 95% confidence interval (CI) 0.20–0.98 for active break and HRadj 0.41, 95% CI 0.18–0.94 for postural shift] and low-back pain (HRadj 0.34, 95% CI 0.12–0.98 for active break and HRadj 0.19, 95% CI 0.06–0.66 for postural shift). CONCLUSION: Interventions to increase either active breaks or postural shifts reduced new onset of neck and low-back pain among high-risk office workers.

OBJECTIVES: This study investigated the effects of a national early retirement reform, which was implemented in 2006 and penalized early retirement, on paid employment and different exit pathways and examined whether these effects differ by gender, income level and health status. METHODS: This study included all Dutch individuals in paid employment born six months before (control group) and six months after (intervention group) the cut-off date of the reform (1 January 1950) that fiscally penalized early retirement. A regression discontinuity design combined with restricted mean survival time analysis was applied to evaluate the effect of penalizing early retirement on labor force participation from age 60 until workers reached the retirement age of 65 years, while accounting for secular trends around the threshold. RESULTS: The intervention group postponed early retirement by 7.41 months [95% confidence interval (CI) 6.11–8.72], and partly replaced this by remaining 4.87 months (95% CI 3.60–6.24) longer in paid employment. Workers born after the threshold, annually earning €25 000–40 000, spent 1.24 months (95% CI 0.31–2.18) more in economic inactivity than those born before. The working months lost to unemployment increased by 1.50 months (95% CI 0.30–2.71) for female workers and 1.99 months (95% CI 0.06–3.92) for workers reporting multiple chronic diseases. CONCLUSIONS: The national reform successfully prolonged working lives of older workers. However, workers with a middle income, female workers, and workers with chronic diseases were more vulnerable to premature exit from the labor market through unemployment or being without any income or benefit.

OBJECTIVES: Shift work may be associated with an increased incidence of respiratory infections. However, underlying mechanisms are unclear. Therefore, our aim was to examine the mediating role of sleep, physical activity, and diet in the association between shift work and respiratory infections. METHODS: This prospective cohort study included 396 shift and non-shift workers employed in hospitals. At baseline, sleep duration and physical activity were measured using actigraphy and sleep/activity diaries, sleep quality was reported, and frequency of meal and snack consumption was measured using food diaries. In the following six months, participants used a smartphone application to report their influenza-like illness/acute respiratory infection (ILI/ARI) symptoms daily. Mediation analysis of sleep, physical activity, and diet as potential mediators of the effect of shift work on ILI/ARI incidence rate was performed using structural equation modeling with negative binomial and logistic regression. RESULTS: Shift workers had a 23% [incidence rate ratio (IRR) 1.23, 95% CI 1.01–1.49] higher incidence rate of ILI/ARI than non-shift workers. After adding the potential mediators to the model, this reduced to 15% (IRR 1.15, 95% CI 0.94–1.40). The largest mediating (ie, indirect) effect was found for poor sleep quality, with shift workers having 29% more ILI/ARI episodes via the pathway of poorer sleep quality (IRR 1.29, 95% CI 1.02–1.95). CONCLUSIONS: Compared to non-shift workers, shift workers had a higher incidence rate of ILI/ARI that was partly mediated by poorer sleep quality. Therefore, it may be relevant for future research to focus on perceived sleep quality as an underlying mechanism in the relation between shift work and increased infection susceptibility.

OBJECTIVE: Many employees have high physical exertion at work and suffer from musculoskeletal pain (MSP) leading to sickness absence with large costs. Participatory ergonomics is a potentially effective intervention for reducing physical exertion, MSP and sickness absence. The main aim of this study was to investigate the effectiveness of a 20-week workplace participatory ergonomic intervention among childcare workers on physical exertion and MSP. METHODS: In a two-arm cluster-randomized trial, 190 workers were recruited from 16 childcare institutions and randomly assigned to either a 20-week participatory ergonomics intervention consisting of three training workshops or a control group receiving usual care. Primary outcomes were physical exertion during work, maximal pain intensity, number of pain regions, and pain-related work interference. Secondary outcomes were MSP-related sickness absence, need for recovery (NFR), employee involvement, and self-efficacy. We followed the intention-to-treat principle and adhered to the registered study protocol (ISRCTN10928313). RESULTS: After 20 weeks, half the workers noticed some positive changes in their work. However, there were no statistically discernible effects in physical exertion, maximum pain intensity, pain-related work interference, or number of pain regions. We found a significant reduction of MSP-related sickness absence in the intervention compared to the control group [-0.48 days per month (95% confidence interval (CI), -0.8– -0.1]. We found no significant effects in NRF or involvement of employees, but self-efficacy was reduced in the intervention compared to the control group [-0.2 (95% CI, -0.3– -0.0)]. CONCLUSION: This 20-week training for a participatory ergonomic intervention in childcare workers did not show effects on physical exertion and MSP, but was both feasible and effective in reducing MSP-related sickness absence.

OBJECTIVES: Weighted regression procedures can be an efficient solution for cohort studies that involve rare events or diseases, which can be difficult to predict, allowing for more accurate prediction of cases of interest. The aims of this study were to (i) predict changes in work ability at one year after approval of the work disability benefit and (ii) explore whether weighted regression procedures could improve the accuracy of predicting claimants with the highest probability of experiencing a relevant change in work ability. METHODS: The study population consisted of 944 individuals who were granted a work disability benefit. Self-reported questionnaire data measured at baseline were linked with administrative data from Dutch Social Security Institute databases. Standard and weighted multinomial logit models were fitted to predict changes in the work ability score (WAS) at one-year follow-up. McNemar’s test was used to assess the difference between these models. RESULTS: A total of 208 (22%) claimants experienced an improvement in WAS. The standard multinomial logit model predicted a relevant improvement in WAS for only 9% of the claimants [positive predictive value (PPV) 62%]. The weighted model predicted significantly more cases, 14% (PPV 63%). Predictive variables were several physical and mental functioning factors, work status, wage loss, and WAS at baseline. CONCLUSION: This study showed that there are indications that weighted regression procedures can correctly identify more individuals who experience a relevant change in WAS compared to standard multinomial logit models. Our findings suggest that weighted analysis could be an effective method in epidemiology when predicting rare events or diseases.

OBJECTIVE: Unfavorable eating patterns might contribute to the adverse health effects of shift work. Our objective was to examine differences in meal and snack frequency, as well as the quality of snacks, between shift and day workers and between different types of shifts. METHODS: Cross-sectional data from 485 healthcare workers aged 18–65 years of the Klokwerk+ cohort study was used. Dietary intake was assessed using 3-day food diaries, and meals and snacks were classified by the food-based classification of eating episodes method. Using multivariable-adjusted regression analyses, we estimated differences in meal and snack frequency and the quality of snacks between shift and day workers. Within the shift working group, eating frequency on day, evening, and night shifts were compared to work-free days. RESULTS: Meal and snack frequency as well as the quality of snacks showed no significant differences between shift and day workers (P≥0.05). Shift workers had a higher frequency of high-quality snacks [β 0.29, 95% confidence interval (CI) 0.12–0.46] and a lower frequency of low-quality snacks (β -0.29, 95% CI -0.49– -0.09) on evening shifts compared to their work-free days. Compared to work-free days, shift workers had a higher frequency of high-quality snacks on days shifts (β 0.24, 95% CI 0.10–0.38), and only those aged ≤40 years had a higher frequency of snacks on night shifts (β 0.53, 95% CI 0.06–1.00) (interaction by age P

OBJECTIVES: This study aimed to determine the extent of both multimorbidity and work productivity loss among young adults with paid work and to analyze their association. METHODS: We included 604 participants from a follow-up of the Raine Study that comprised a cohort who were 22 years at the time (Gen2-22). Information on 36 health conditions, grouped into 10 condition categories, was collected through questionnaires and physical assessments (for body mass index only). Quarterly questionnaires about work productivity, including total absenteeism, sickness absenteeism, and total presenteeism, were distributed electronically over the subsequent 12 months. Descriptive statistics were used to determine the prevalence of health conditions, condition categories, multimorbidity, and work productivity. Zero-inflated negative binomial regression analyses were used to assess the association of multimorbidity with productivity loss. RESULTS: Multimorbidity prevalence was substantially higher in females (63%) compared to males (41%). Productivity loss increased as the number of condition categories increased. For example, total absenteeism was associated with an increase in the number of health condition categories in males [incidence rate ratio (IRR) 1.20, 95% confidence interval (CI) 1.05–1.36] and females (IRR 1.13, 95% CI 1.04–1.24). Similar results were found for sickness absenteeism and presenteeism. The highest burden of productivity loss was found for musculoskeletal disorders (42 444 hours/1000 workers/year), sleep problems (33 581 hours/1000 workers/year), mental and neurological conditions (15 650 hours/1000 workers/year), and ‘other’ medical conditions (22 519 hours/1000 workers/year). CONCLUSIONS: Multimorbidity appears to be highly prevalent among young adults with paid work and is strongly related to work productivity loss. Therefore, young workers should be targeted in interventions aiming to reduce multimorbidity and its impact on work productivity.

OBJECTIVE: Emerging evidence suggests that excessive sitting has negative health effects. However, this evidence largely relies on research using self-reported sitting time, which is known to be biased. To correct this bias, we aimed at developing a calibration model estimating "true" sitting from self-reported sitting. METHODS: Occupational sitting time was estimated by self-reports (the International Physical Activity Questionnaire) and objective measurements (thigh-worn accelerometer) among 99 Swedish office workers at a governmental agency, at baseline and 3 and 12 months afterwards. Following compositional data analysis procedures, both sitting estimates were transformed into isometric log-ratios (ILR). This effectively addresses that times spent in various activities are inherently dependent and can be presented as values of only 0−100%. Linear regression was used to develop a simple calibration model estimating objectively measured "true" sitting ILR (dependent variable) from self-reported sitting ILR (independent variable). Additional self-reported variables were then added to construct a full calibration model. Performance of the models was assessed by root-mean-square (RMS) differences between estimated and objectively measured values. Models developed on baseline data were validated using the follow-up datasets. RESULTS: Uncalibrated self-reported sitting ILR showed an RMS error of 0.767. Simple and full calibration models (incorporating body mass index, office type, and gender) reduced this error to 0.422 (55%) and 0.398 (52%), respectively. In the validations, model performance decreased to 57%/62% (simple models) and 57%/62% (full models) for the two follow-up data sets, respectively. CONCLUSIONS: Calibration adjusting for errors in self-reported sitting led to substantially more correct estimates of "true" sitting than uncalibrated self-reports. Validation indicated that model performance would change somewhat in new datasets and that full models perform no better than simple models, but calibration remained effective.

OBJECTIVES: Evidence on the effect of smoking on sickness absence could guide workplace smoking cessation interventions and encourage employers to promote smoking cessation among their employees. This systematic review and meta-analysis aimed to summarize evidence on the association between smoking and sickness absence and determine whether there are differences in this association for study design, methodology, and sample characteristics. METHODS: We searched for studies that reported on smoking status and sickness absence, used empirical data, were published in a peer-reviewed journal in the last 25 years, and written in English. We conducted pooled analyses in which uni- and multivariate generalized linear regression models were applied. RESULTS: After screening 2551 unique records, 46 articles from 43 studies were included, of which 33 studies (with 1 240 723 participants) could be included in the pooled analyses. Smoking was associated with an 31% increase in risk of sickness absence compared to non-smoking (95% confidence interval (CI) 1.24–39). We did not find statistically significant different effect sizes for study location, gender, age, occupational class, study design, assessment of sickness absence, short- versus long-term sickness absence, and adjustment for relevant confounders. Furthermore, smoking was associated with 2.89 more sickness absence days per year compared to non-smoking (95% CI 2.08–3.70). CONCLUSIONS: We found robust evidence showing that smoking increases both the risk and number of sickness absence days in working populations, regardless of study location, gender, age, and occupational class. Encouraging smoking cessation at the workplace could therefore be beneficial for employers and employees.

OBJECTIVE: This opinion paper summarizes the main findings and recommendations of an advisory report on health and prolonging working life, which was requested by the Dutch Minister of Social Affairs and Employment. METHODS: The advisory report was compiled by a multidisciplinary committee of ten scientists appointed by the Health Council of The Netherlands. The committee`s aims were to (i) describe the health of the ageing population, (ii) describe how prolonging working life influences health, (iii) describe determinants, besides health, for prolonging working lives, and (iv) review the literature on interventions aimed at retaining or improving employability of older workers. RESULTS: The report was presented to the Minister on 26 June 2018. As the likelihood of health problems increases with age, prolonging working life may be difficult. In general, life expectancy increases and gains in life years and health seem mainly attributable to people aged >75 years. Work is good for mental health. However, it may be beneficial for mental health to stop working around the retirement age. Besides health, financial factors, lifestyle, motivation to work, and working conditions play a role in prolonging working life. A systematic review of the evidence indicated that interventions such as worksite health promotion or career development workshops can support older workers in this matter. CONCLUSIONS: The Health Council advised the Dutch Government to focus on worksite health promotion and career development interventions as well as the improvement of their implementation. This requires a tailored approach as there is a large diversity in health among older workers and particularly between low- and high-educated people. With this in mind, it was further recommended to explore whether flexible pension schemes might better suit this diversity.

OBJECTIVE: This study aimed to systematically review the literature on the contribution of work and lifestyle factors to socioeconomic inequalities in self-rated health among workers. METHODS: A search for cross-sectional and longitudinal studies assessing the contribution of work and/or lifestyle factors to socioeconomic inequalities in self-rated health among workers was performed in PubMed, PsycINFO and Web of Science in March 2017. Two independent reviewers performed eligibility and risk of bias assessment. The median change in odds ratio between models without and with adjustment for work or lifestyle factors across studies was calculated to quantify the contribution of work and lifestyle factors to health inequalities. A best-evidence synthesis was performed. RESULTS: Of those reviewed, 3 high-quality longitudinal and 17 cross-sectional studies consistently reported work factors to explain part (about one-third) of the socioeconomic health inequalities among workers (grade: strong evidence). Most studies separately investigated physical and psychosocial work factors. In contrast with the 12 cross-sectional studies, 2 longitudinal studies reported no separate contribution of physical workload and physical work environment to health inequalities. Regarding psychosocial work factors, lack of job resources (eg, less autonomy) seemed to contribute to health inequalities, whereas job demands (eg, job overload) might not. Furthermore, 2 longitudinal and 4 cross-sectional studies showed that lifestyle factors explain part (about one-fifth) of the health inequalities (grade: strong evidence). CONCLUSIONS: The large contribution of work factors to socioeconomic health inequalities emphasizes the need for future longitudinal studies to assess which specific work factors contribute to health inequalities.

ObjectiveSit-stand workstations have been shown to be effective in reducing sitting time in office workers. The aim of this study was to explore reasons for use and non-use of sit-stand workstations and strategies to decrease sitting and increase physical activity in the workplace from perspectives of users and non-users, as well as from managers and ergo-coaches.MethodsSix group interviews with employees who have had access to sit-stand workstations for several years were conducted in a large semi-governmental organisation in the Netherlands. Verbatim transcripts were analysed using thematic analysis. Open coding was conducted by three researchers and codes and themes were discussed within the research team.ResultsThematic analysis resulted in two major themes: 1) Reasons for use and non-use and 2) Strategies to increase standing and physical activity in the workplace. Shared and distinct reasons for use and non-use were identified between users and non-users of the sit-stand workstations. The most important reasons for use indicated by users were that they had experiencing immediate benefits, including staying alert and increasing focus; these benefits were not acknowledged by non-users. Non-users indicated that sitting was comfortable for them and that they were therefore not motivated to use the standing option. Strategies to increase the use of the standing option included an introductory phase to become familiar with working while standing and to experience the immediate benefits that come from using the standing option. Furthermore, providing reminders to use the standing option was suggested as a strategy to increase and sustain the use of sit-stand workstations. Increased use may lead to a change in the sitting culture within the organisation, as more employees would adopt active movement behaviours.ConclusionImmediate benefits of the use of the standing option-only mentioned by the users-was the most distinct reason to use sit-stand workstations. Future research should explore how to motivate potential users to adhere to an introductory phase in order to experience these immediate benefits, whether it is linked to the use of sit-stand workstations or other interventions to reduce sitting time.

OBJECTIVES: Healthcare workers frequently deal with work stress. This is a risk factor for adverse mental and physical health effects. The objective of this study was to investigate the effectiveness of a digital platform-based implementation strategy – compared to a control group – on stress, work stress determinants (ie. psychosocial work factors) and the level of implementation among healthcare workers. METHODS: By way of matching, 30 teams from a healthcare organization were assigned to the experimental (15 teams; N=252) or wait-list control (15 teams; N=221) group. The experimental group received access to the strategy for 12 months. They were asked to complete the 5-step protocol within six months. The primary outcome was stress (DASS-21) and secondary outcomes were psychological demands, social support, autonomy, and the level of implementation. Questionnaire-based data were collected at baseline, and at 6- and 12-months follow-up. Linear mixed model analyses were used to test differences between the two groups. RESULTS: In total, 210 participants completed the baseline questionnaire and at least one follow-up questionnaire. There was a significant effect of the strategy on stress in favor of the experimental group [B=-0.95, 95% confidence interval (CI) -1.81 – -0.09]. No statistically significant differences were found for any secondary outcomes. CONCLUSIONS: The strategy showed potential for primary prevention of work stress, mainly explained by an increase in stress in the control group that was prevented in the experimental group. More research is necessary to assess the full potential of the strategy.

OBJECTIVES: Shift work may alter workers’ leisure-time and occupational physical activity (PA) levels, which might be one of the potential underlying mechanisms of the negative health effects of shift work. Therefore, we compared objectively measured PA levels between hospital shift and non-shift workers. METHODS: Data were used from Klokwerk+, a cohort study examining the health effects of shift work among healthcare workers employed in hospitals. In total, 401 shift workers and 78 non-shift workers were included, all of whom wore Actigraph GT3X accelerometers for up to seven days. Time spent sedentary, standing, walking, running, stairclimbing, and cycling during leisure time and at work was estimated using Acti4 software. Linear regression was used to compare proportions of time spent in these activities between hospital shift and non-shift workers. RESULTS: Average accelerometer wear-time was 105.9 [standard deviation (SD) 14.0] waking hours over an average of 6.9 (SD 0.6) days. No differences between hospital shift and non-shift workers were found in leisure-time PA (P>0.05). At work, shift workers were less sedentary [B=-10.6% (95% CI -14.3– -6.8)] and spent larger proportions of time standing [B=9.5% (95% CI 6.4–12.6)] and walking [B=1.2% (95% CI 0.1–2.2)] than non-shift workers. However, these differences in occupational PA became smaller when the number of night shifts during accelerometer wear-time increased. CONCLUSIONS: Leisure-time PA levels of hospital shift workers were similar to those of non-shift workers, but shift workers were less sedentary and more physically active (ie, standing/walking) at work. Future research to the role of occupational activities in the health effects of shift work is recommended.

People who involuntarily leave the labor market due to health problems run the risk of entering into a vicious circle as exiting the labor market can aggravate their initial health problems, especially if accompanied by other forms of social exclusion. While this problem affects large parts of the population, especially during economic downturns, it may particularly affect those with a weak initial labor market position, such as those with low socioeconomic status (SES). This unequal burden has been documented in an interesting paper in this issue of the Scandinavian Journal of Work, Environment & Health (1). The authors report findings from five European regions showing that lower-educated persons had increased risks of exit from paid employment due to health problems compared to those with higher education levels. To document these inequalities, the authors applied a method, the population attributable fraction (PAF), which has a long tradition in public health research but remains underutilized in studies focusing on occupational health. The PAF combines information on the prevalence of the exposure of interest (in this case: poor health), with estimates on the relative risk of those exposed for the outcome of interest (in this case: exit from paid employment). Using the PAF, the authors estimated that the annual rate of labor market exit due to health problems was, for example, about 4% for intermediate-educated workers in the Continental region. This risk varied considerably according to educational level. For example, in the Continental region, it was about 2% for higher-educated workers and almost 10% for lower-educated workers [see figure 2 in (1)]. One might expect this inequality to originate to an important extent from the fact that the risk to exit paid employment due to health problems is lower for those with high versus low SES. For example, higher-educated office workers with knee osteoarthritis (OA) are able to continue working in their job, while lower-educated laborers, who lay street pavements in a kneeling position for a substantial part of their working day, are unable to do so when suffering from OA. However, this expectation was not confirmed. The authors found that relative risks to exit paid employment in case of health problems were quite similar for higher- and lower-educated workers, for reasons to be disentangled in future research. Instead, the socioeconomic inequalities in risk of exit from paid employment were primarily due to inequalities in the prevalence of poor health, with lower-educated workers having a much higher prevalence of poor self-rated health than those with a higher education. This raises the key question of how these socioeconomic inequalities in health emerge and how they can be addressed in occupational settings. Socioeconomic inequalities in self-rated health are considered to originate from a combination of material, psychosocial, and behavioral factors. The materialist explanation includes not only differences in financial resources but also worse living/housing conditions, more insecure employment status, and greater exposure to unhealthy working conditions among persons with a lower SES. The psychosocial explanation takes into account not only that negative life events and chronic strain are more common among people with low SES but also that low mastery, coping or social support are unequally distributed and thus contribute to social inequalities in health. The behavioral explanation emphasizes that unhealthy behaviors, such as smoking, substance use, low physical activity, and poor dietary habits, are more prevalent among people with lower SES. Moor and colleagues` systematic review (2) showed that all three factors contributes to explaining the socioeconomic inequalities in self-rated health. However, material factors were most important since these factors contributed to health inequalities not only through direct effects on health but also through indirect effects via psychosocial and behavioral factors. For example, an occupational setting might facilitate smoking behavior more among low compared to high SES workers through differences in company culture, influences from close colleagues, and actual opportunities to smoke at work. A review recently published in the Scandinavian Journal of Work, Environment & Health (3) found that work factors explained about one-third and lifestyle factors about one-fifth of socioeconomic inequalities in self-rated health. Schuring et al (1) also stress that physical working conditions and/or psychosocial work characteristics play a substantial role in socioeconomic inequalities in self-rated health (4). If this is indeed the case, then preventive interventions at work might have potential in reducing socioeconomic health inequalities. In many countries, socioeconomic health inequalities represents one of the most critical public health challenges. Even though measures are being taken to address these inequalities, in practice, uptake of preventive interventions remains larger among people with high compared to low SES. The occupational setting provides particular challenges and opportunities. Physical working conditions and psychosocial work characteristics are critical to the health of workers with lower SES in two ways by: (i) causing ill-health among highly exposed workers with low SES and (ii) acting as obstacles to work for these workers in case of illness. Hence, one might argue that interventions within the occupational setting have the potential to prevent or break the vicious circle between poor health and non-employment. Successful interventions may directly improve health by effects of the intervention itself but also decrease the risk of exit from employment (1), which subsequently leaves health-enhancing effects of employment active for a longer period of time (5). Workplace interventions specifically aimed at workers with lower SES may focus on the physical or psychosocial work environmental level, the individual worker level, or a combination of both. There is evidence for the effectiveness of environmental-level interventions aiming to improve physical working conditions/ergonomics (eg, 6) as well as those aiming to improve psychosocial work characteristics (7). For the individual level, scientific evidence ranges from physical activity interventions targeted at lower-educated occupational groups in general (8) to interventions focusing on specific branches of industry employing mostly lower-educated blue-collar workers, such as in the meat processing (9), construction (10), or transportation (11) industries. In general, intensive interventions tailored to the lower SES target group are far more promising than low-intensity, generic interventions using a one-size-fits-all approach. To date, however, it remains uncertain how worksite health promotion programs or interventions improving working conditions can be implemented in companies and branches of industry such that workers with lower SES optimally benefit. Therefore, our most important challenge lies in developing such programs and interventions, thus contributing to greater socioeconomic equality in chances for good health as well as paid employment. 1. Schuring M, Schram JLD, Robroek SJW, Burdorf A. The contribution of health to educational inequalities in exit from paid employment in five European regions. Scand J Work Environ Health. 2019;45(4):346-355. https://doi.org/10.5271/sjweh.3796 2. Moor I, Spallek J, Richter M. Explaining socioeconomic inequalities in self-rated health: a systematic review of the relative contribution of material, psychosocial and behavioural factors. J Epidemiol Community Health 2017;71:565-75. https://doi.org/10.1136/jech-2016-207589 3. Dieker ACM, IJzelenberg W, Proper KI, Burdorf A, Ket JCF, van der Beek AJ, Hulsegge G. The contribution of work and lifestyle factors to socioeconomic inequalities in self-rated health - a systematic review. Scand J Work Environ Health 2019;45:114-25. https://doi.org/10.5271/sjweh.3772 4. Hoven H, Siegrist J. Work characteristics, socioeconomic position and health: a systematic review of mediation and moderation effects in prospective studies. Occup Environ Med 2013;70:663-9. https://doi.org/10.1136/oemed-2012-101331 5. van der Noordt M, IJzelenberg H, Droomers M, Proper KI. Health effects of employment: a systematic review of prospective studies. Occup Environ Med 2014;71:730-6. https://doi.org/10.1136/oemed-2013-101891 6. Driessen MT, Proper KI, van Tulder MW, Anema JR, Bongers PM, van der Beek AJ. The effectiveness of physical and organizational ergonomic interventions on low back pain and neck pain: a systematic review. Occup Environ Med 2010;67:277-285. https://doi.org/10.1136/oem.2009.047548 7. Bambra C, Gibson M, Sowden AJ, Wright K, Whitehead M, Petticrew M. Working for health? Evidence from systematic reviews on the effects on health and health inequalities of organisational changes to the psychosocial work environment. Prev Med 2009;48:454-61. https://doi.org/10.1016/j.ypmed.2008.12.018 8. Cairns JM, Bambra C, Hillier-Brown FC, Moore HJ, Summerbell CD. Weighing up the evidence: a systematic review of the effectiveness of workplace interventions to tackle socio-economic inequalities in obesity. J Public Health (Oxf) 2015;37:659-70. https://doi.org/10.1093/pubmed/fdu077 9. van Holland BJ, Soer R, de Boer MR, Reneman MF, Brouwer S. Preventive occupational health interventions in the meat processing industry in upper-middle and high-income countries: a systematic review on their effectiveness. Int Arch Occup Environ Health 2015;88:389-402. https://doi.org/10.1007/s00420-014-0964-3 10. Groeneveld IF, Proper KI, van der Beek AJ, van Mechelen W. Sustained body weight reduction by an individual-based lifestyle intervention for workers in the construction industry at risk for cardiovascular disease: Results of a randomized controlled trial. Prev Med 2010;51:240-6. https://doi.org/10.1016/j.ypmed.2010.07.021 11. Puhkala J. Kukkonen-Harjula K, Mansikkamäki K, Aittasalo M, Hublin C, Kärmeniemi P, et al. Lifestyle counseling to reduce body weight and cardiometabolic risk factors among truck and bus drivers - a randomized controlled trial. Scand J Work Environ Health 2015;41:54-64. https://doi.org/10.5271/sjweh.3463

OBJECTIVES: Work-related musculoskeletal disorders (MSD) are highly prevalent and put a large burden on (working) society. Primary prevention of work-related MSD focuses often on physical risk factors (such as manual lifting and awkward postures) but has not been too successful in reducing the MSD burden. This may partly be caused by insufficient knowledge of etiological mechanisms and/or a lack of adequately feasible interventions (theory failure and program failure, respectively), possibly due to limited integration of research disciplines. A research framework could link research disciplines thereby strengthening the development and implementation of preventive interventions. Our objective was to define and describe such a framework for multi-disciplinary research on work-related MSD prevention. METHODS: We described a framework for MSD prevention research, partly based on frameworks from other research fields (ie, sports injury prevention and public health). RESULTS: The framework is composed of a repeated sequence of six steps comprising the assessment of (i) incidence and severity of MSD, (ii) risk factors for MSD, and (iii) underlying mechanisms; and the (iv) development, (v) evaluation, and (vi) implementation of preventive intervention(s). CONCLUSIONS: In the present framework for optimal work-related MSD prevention, research disciplines are linked. This framework can thereby help to improve theories and strengthen the development and implementation of prevention strategies for work-related MSD.

OBJECTIVES: No study so far has combined register-based socioeconomic information with self-reported information on health, demographics, work characteristics, and the social environment. The aim of this study was to investigate whether socioeconomic, health, demographic, work characteristics and social environmental characteristics independently predict working beyond retirement. METHODS: Questionnaire data from the Study on Transitions in Employment, Ability and Motivation were linked to data from Statistics Netherlands. A prediction model was built consisting of the following blocks: socioeconomic, health, demographic, work characteristics and the social environment. First, univariate analyses were performed (P02 days/week, higher body height, and working in healthcare predicted working beyond retirement. If respondents had a permanent contract or worked in handcraft, or had a partner that did not like them to work until the official retirement age, they were less likely to work beyond retirement. CONCLUSION: Health, work characteristics and social environment predicted working beyond retirement, but register-based socioeconomic and demographic characteristics did not independently predict working beyond retirement. This study shows that working beyond retirement is multifactorial.

OBJECTIVE: Physical inactivity has been hypothesized as an underlying factor for the association between shift work and adverse health outcomes. We compared leisure-time and occupational physical activity and sedentary behavior between day, night, and non-night shift workers. METHODS: We identified 612 day workers, 139 night shift workers and 61 non-night shift workers aged 18–65 years (54% men) in two Danish studies: the New method for Objective Measurements of physical Activity in Daily living (NOMAD) and the Danish Physical ACTivity cohort with Objective measurements (DPhacto) between 2011–2013. Sedentary behavior, light, and moderate-to-vigorous physical activity were measured using an accelerometer. Physical activity was expressed as percentage of leisure and work time spent in each activity. Linear regression analyses were used to test differences in physical activity and sedentary behavior between day, night, and non-night shift workers. RESULTS: No differences in leisure-time sedentary behavior and physical activity were observed between day and shift workers (P>0.05). Non-night shift workers spent 7.2% [95% confidence interval (95% CI) 2.3–12.1) more time in occupational sedentary behavior than day workers and 5.9% (95% CI -10.1– -1.7) and 1.9% (95% CI -3.7– -0.2) less time in occupational light and moderate-to-vigorous physical activity, respectively. Compared to day workers, night shift workers spent 4.3% (95% CI 2.4–6.1) more time at work in uninterrupted sedentary periods of ≥30 minutes. CONCLUSIONS: Shift workers had similar leisure-time physical activity patterns as day workers, but were more sedentary at work. Future research should elucidate whether occupational physical inactivity and sedentary behavior contributes to shift work-related adverse health effects.

OBJECTIVES: Before actual retirement, employees may already distance themselves from work, which could be referred to as “mental retirement”. However, trajectories of work motivation, ie, work engagement, have not been studied yet. The present study aimed to (i) identify different trajectories of work engagement among older workers approaching the retirement age, and (ii) examine their associations with actual retirement. METHODS: In total 3171 employees aged 55–62 years, who participated in the Dutch Study on Transitions in Employment, Ability and Motivation were included in this study. Participants completed questionnaires in 2010, 2011, 2012, and 2013. Latent class growth mixture modeling was performed to identify groups of employees with similar three-year trajectories in work engagement. Logistic regression analyses were performed to study whether trajectory membership was associated with retirement. RESULTS: Of the 3171 employees, 16.2% made a transition from work to (early) retirement (N=513). Four trajectories of work engagement were identified: steady high (76.3%), steady low (12.7%), decreasing (6.2%), and increasing (4.8%). A steady low work engagement trajectory was associated with retirement [odds ratio (OR) 1.46], compared to a steady high work engagement trajectory. Although not statistically significant, an increasing work engagement trajectory seemed to be associated with retirement as well (OR 1.60). CONCLUSIONS: This study did not support the concept of mental retirement before actual retirement, ie, a decrease in work engagement among those facing retirement. However, as one in eight employees did experience steady low work engagement in the years before retirement, interventions promoting work motivation are recommended to support the employability of these employees.

OBJECTIVE:Shift work has been linked to cardio-metabolic diseases, but insight into different shift work-related aspects and chronotype of shift workers and their relation with metabolic risk factors is limited. This study examined the association between current shift work status, frequency and duration of night shift work, chronotype, and metabolic risk factors in a population of health care workers. METHODS:Anthropometrics, questionnaires, and blood samples were collected from 503 shift working and 93 non-shift working health care workers employed in hospitals. Body mass index, waist circumference, cholesterol (total, HDL, LDL), triglycerides, and high-sensitivity C-reactive protein were measured. Associations of current shift work, frequency (non-night shift worker, 1-2, 3-4, ≥5 night shifts/month) and duration of night shift work (non-night shift workers,

IntroductionPrecarious employment is associated with poor health. Among employees in precarious employment, those with multiple jobs may face additional health risks, e.g. due to combining work schedules and job roles. Our research question is: do differences in health exist between multiple and single job holders in precarious employment?MethodsParticipants in the Netherlands Working Conditions Survey 2012 aged 25-64 years who were not employed through the Act on Social Work Provision and who had a precarious job were included. To select employees in precarious employment (n = 3,609), latent class analysis was performed, based on variables based on indicators described by Van Aerden. Differences in general self-perceived health, burnout complaints, musculoskeletal health, and sickness absence between multiple and single job holders were studied cross-sectionally using logistic regression analyses.ResultsNo significant differences were found between multiple and single job holders in precarious employment for self-perceived health (OR = 0.9; 95%CI = 0.7-1.3), burnout complaints (OR = 0.9; 95%CI = 0.7-1.2), and musculoskeletal health (OR = 1.1; 95%CI = 0.8-1.5). In crude analyses, multiple job holders experienced less sickness absence than single job holders (OR = 0.7; 95%CI = 0.5-0.9). In adjusted analyses, this difference was no longer statistically significant (OR = 0.8; 95%CI = 0.6-1.0).ConclusionsDespite potential health risks related to multiple job holding, we did not find health differences between multiple and single job holders in precarious employment in the Netherlands. More longitudinal research is necessary to provide recommendations for policy makers regarding multiple job holders in precarious employment.

OBJECTIVES: This systematic review aimed to explore which process variables are used in stress management intervention (SMI) evaluation research. METHODS: A systematic review was conducted using seven electronic databases. Studies were included if they reported on an SMI aimed at primary or secondary stress prevention, were directed at paid employees, and reported process data. Two independent researchers checked all records and selected the articles for inclusion. Nielsen and Randall’s model for process evaluation was used to cluster the process variables. The three main clusters were context, intervention, and mental models. RESULTS: In the 44 articles included, 47 process variables were found, clustered into three main categories: context (two variables), intervention (31 variables), and mental models (14 variables). Half of the articles contained no reference to process evaluation literature. The collection of process evaluation data mostly took place after the intervention and at the level of the employee. CONCLUSIONS: The findings suggest that there is great heterogeneity in methods and process variables used in process evaluations of SMI. This, together with the lack of use of a standardized framework for evaluation, hinders the advancement of process evaluation theory development.

OBJECTIVE: Shift work is associated with adverse health outcomes, and an unhealthy diet may be a contributing factor. We compared diet quantity and quality between day and shift workers, and studied exposure–response relationships regarding frequency of night shifts and years of shift work. METHODS: Cross-sectional general population data from the European Prospective Investigation into Cancer and Nutrition-Netherlands (EPIC-NL) cohort was used. Dietary intake was assessed in 1993–1997 among adults aged 20–70 years using a food frequency questionnaire. We calculated energy intake, the Mediterranean Diet Score (MDS) and WHO-based Healthy Diet Indicator (HDI). In 2011–2014, we retrospectively identified 683 shift workers and 7173 day workers in 1993–1997. Using multivariable-adjusted linear regression analysis, we estimated regression coefficients (β) and 95% confidence intervals (95% CI) of the differences in dietary intake between day and shift workers. RESULTS: Shift workers had a higher energy intake than day workers (β:56 kcal/d, 95% CI 10–101), and a higher consumption of grains, dairy products, meat and fish (P

BACKGROUND:With the increase of the statutory retirement age, the number of self-employed older workers will most likely increase. Therefore, this study aimed to explore: 1) the differences in self-rated health and work ability of self-employed workers and employees, 1) whether self-employment is associated with better self-rated health and work ability across three years, than employment, and 3) the role of sociodemographic, health- and work-related characteristics (e.g., mental load, physical load, and autonomy) in these relationships. METHODS:Data was used from the Study on Transitions in Employment, Ability and Motivation, where self-employed (n = 1,029) and employees (n = 12,055) aged 45-64 years were followed during 2010-2013. Linear regression and generalized estimating equations analyses were carried out to study the differences in self-rated health and work ability (i.e., self-assessed work ability in relation to an individual's resources and work demands) of self-employed and employees. To explore the role of sociodemographic, health-and work-related characteristics in these associations, we included interaction terms between these characteristics and employment status. RESULTS:The self-employed had better work ability (8.3 versus 8.2), and better self-rated health (3.4 versus 3.3) than employees. Work ability of self-employed improved over time, compared to the changes over time in work ability among employees, but not no difference in change over time in self-rated health was found. None of the interaction terms were statistically significant (p>0.05). CONCLUSION:We observed higher scores in self-rated health and work ability among the self-employed than employees. Being self-employed leads to an increase in work ability across three years. The differences in work ability can be considered small, and more research is needed to establish the role of self-employment as a potential facilitator for sustainable employment.

In their recent letter to the Editor of the Scandinavian Journal of Work, Environment & Health, Winkel & Westgaard reflected on our earlier paper (2), where we described a research framework for the development and implementation of interventions preventing work-related musculoskeletal disorders (MSD). Winkel & Westgaard argue that interventions described in our paper, such as manual handling advise, ergonomic workplace design, or job rotation, “… are unlikely to have much impact” since rationalization of production systems has a larger potential in the causal pathway to health effects. Furthermore, they stress that ergonomic interventions realized as spin-off from the ‘all-embracing process’ of rationalization of production systems should be evaluated by using either observational or quasi-experimental research designs rather than randomized controlled trials (RCT). We agree with Winkel & Westgaard that effects of system changes induced by company management generally go beyond those from standalone ergonomic adjustments in the workplace and that implementation of interventions largely occurs at company level. We disagree, however, that our research framework would not be suitable for the continuous process of rationalization resulting in ever-changing work environments, with a substantial part of these changes being the introduction of ergonomic interventions. When appraising the effects of such ergonomic spin-offs obtained from changes in the production system, a decent scientific funding of the underlying working mechanisms of the intervention (as described in steps 2–3 of our framework) remains imperative. In their conceptualization of the relation between rationalization at societal level and (musculoskeletal) health effects at individual worker level, Westgaard & Winkel themselves (3) illustrate that the rationalization process at the end of the causal pathway results in changes in exposure to occupational physical and psychosocial risk factors that eventually affect MSD. Moreover, we also agree that policy measures and interventions at the level of companies or populations may need to be evaluated in ways other than an RCT. In fact, the latter was discussed in the Scandinavian Journal of Work, Environment & Health (4), where we have listed several alternative observational research designs that may be suitable to evaluate various workplace interventions, such as interrupted time series, regression discontinuity, or multiple baseline design. Laestadius and colleagues (5) have published an illustrative example of a quasi-experimental research design in the context of MSD prevention. This study evaluated the move of approximately 1500 International Monetary Fund employees to a new office with an improved ergonomics design. In the study, workers who changed offices − which might be called rationalization − were compared to a similar group of World Bank workers that did not move. The study showed a reduction in awkward working postures as well as musculoskeletal pain and eye strain as a result of the change in workplace and individual workstation assessment. We believe that our model is well applicable to a broad range of interventions, such as the one mentioned in this example, as well as adequate methods evaluating the effectiveness of these interventions. In our framework, step 4 (development of intervention(s)), step 5 (evaluation of intervention(s)) and step 6 (implementation of effective intervention(s)) are suitable to do so and certainly not limited to traditional ergonomic interventions and/or evaluations using RCT only. Despite this, we do believe that, in case an intervention cannot be tested by performing an RCT, we should not neglect the scientific quality limitations of the alternative research designs used. Or as phrased eloquently by Kristensen (6): “There may be many good reasons for not performing a randomized controlled trial in an occupational setting. But there are no good reasons for ignoring the problems created by not applying such a design.” As a minimum requirement, we believe that evaluation studies should be longitudinal and should enable the comparison of participants receiving the intervention to an appropriate reference group not receiving the intervention. In conclusion, we thank Winkel & Westgaard for their suggestion that a production system’s approach, which goes beyond standalone adjustments in the workplace introduced by researchers or ergonomists, can be used to prevent work-related MSD and that we may need alternative research designs to evaluate this approach. We agree with these statements. However, we argue that a further development of our research framework, also accommodating interventions introduced by management and other stakeholders in real working life, is unnecessary as our framework already accommodates for this process. Therefore, we invite researchers and ergonomists to fully benefit from the input of corporate stakeholders who aim at organizational sustainability when designing interventions. Researchers should use alternative designs when testing the effectiveness of such interventions if an RCT is not possible and should also prioritize supporting relevant stakeholders in the implementation of effective interventions for the prevention of work-related MSD. 1. Winkel J, Westgaard RH. Development and implementation of interventions managing work-related musculoskeletal disorders: Inadequacy of prevalent research framework and future opportunities. Scand J Work Environ Health 2019;45(3):316-317. https://doi.org/10.5271/sjweh.3815. 2. van der Beek AJ, Dennerlein JT, Huysmans MA, Mathiassen SE, Burdorf A, van Mechelen W, et al. A research framework for the development and implementation of interventions preventing work-related musculoskeletal disorders. Scand J Work Environ Health 2017 Nov 1;43(6):526–39. https://doi.org/10.5271/sjweh.3671. 3. Westgaard RH, Winkel J. Occupational musculoskeletal and mental health: significance of rationalization and opportunities to create sustainable production systems - A systematic review. Appl Ergon 2011 Jan;42(2):261–96. https://doi.org/10.1016/j.apergo.2010.07.002. 4. Schelvis RM, Oude Hengel KM, Burdorf A, Blatter BM, Strijk JE, van der Beek AJ. Evaluation of occupational health interventions using a randomized controlled trial: challenges and alternative research designs. Scand J Work Environ Health 2015 Sep;41(5):491–503. https://doi.org/10.5271/sjweh.3505. 5. Laestadius JG, Ye J, Cai X, Ross S, Dimberg L, Klekner M. The proactive approach--is it worthwhile? A prospective controlled ergonomic intervention study in office workers. J Occup Environ Med 2009 Oct;51(10):1116–24. https://doi.org/10.1097/JOM.0b013e3181bae19d. 6. Kristensen TS. Intervention studies in occupational epidemiology. Occup Environ Med 2005 Mar;62(3):205–10. https://doi.org/10.1136/oem.2004.016097.

We are writing in regards to the review by Koranyi et al (1) on precarious employment and occupational accidents and injuries. In the review, multiple-job holding was classified as a type of precarious employment. In this letter, we argue multiple-job holding should not be considered a type of precarious employment and that multiple-job holders constitute a heterogeneous group of workers. In their review, Koranyi et al defined precarious employment as “uncertainty as to the duration of employment, multiple possible employers or a disguised or ambiguous employment relationship, a lack of access to social protection and benefits usually associated with employment, low pay, and substantial legal and practical obstacles to joining a trade union and bargaining collectively” (1). In this ILO definition, multiple-job holding is presented as a type of precarious employment. Most researchers now agree that precariousness, on the one hand, is a multi-dimensional construct, including at least four dimensions: (i) employment instability; (ii) low material rewards; (iii) control over working conditions and pace of work; and (iv) a lack of social rights and protections (2‒4). Multiple-job holding, on the other hand, is defined in the scientific literature as having two or more jobs. It does not relate to the quality of the terms of employment associated with these jobs. Previous research has shown that employees without a permanent contract are more likely to have multiple jobs (5,6). This, however, does not mean that multiple-job holding is equivalent to precarious employment. Firstly, precariousness has many dimensions, and encompasses more than "just" having a temporary contract. Secondly, multiple-job holders are a heterogeneous group of workers (7): not all multiple-job holders have temporary contracts in one or more of their jobs. Recent research on multiple-job holding has made significant progress in exploring its heterogeneity. Rouault conceptualized, but not empirically studied, four groups of multiple-job holders (8). Another study, conducted by the authors of the present letter (9), distinguished four groups using latent class analysis among 702 multi-jobbers: (i) vulnerable; (ii) indifferent; (iii) satisfied combination; and (iv) satisfied hybrid multiple-job holders. The vulnerable group was exposed to more dimensions of precariousness than the other three groups. These workers more often combined jobs with temporary contracts, for instance. Furthermore, the vulnerable multiple-job holders more often reported low autonomy and a relatively high percentage of these workers reported that their household was short of money. Cross-sectional analyses showed that the vulnerable group, on average, experienced worse physical and mental health than the three other groups of multiple-job holders (9). In contrast to this vulnerable group of multiple-job holders, other groups of multiple-job holders experienced benefits from holding multiple jobs (9). These findings have been confirmed in a qualitative study in which we found that some multi-jobbers only experienced benefits of multiple-job holding, eg, positive spill-over effects between jobs: networks established or skills learned in one job that can be used in others (10). Marucci-Wellman acknowledged the heterogeneity of multiple-job holders in her editorial on the review by Koranyi et al (11). She underscored the importance of distinguishing groups of multiple-job holders stating that, if we treat multiple-job holders as one group, health effects for the most vulnerable group may be obscured. We would argue that multiple-job holding as such should never be regarded as equivalent to precarious employment, even if a multiple-job holder has one or more jobs that can be considered precarious. Given the increasing prevalence of precarious employment and multiple-job holding as well as their potential health effects, future research on these issues is crucial. We recommend to use clear definitions of precarious employment and multiple-job holding. We propose that precariousness refers to the terms of employment and working conditions of a job, whereas multiple-job holding refers to the number of jobs a worker has, regardless of actual employment and working conditions. To conclude, it is possible, but by no means necessary, that one or more of the jobs held by a multi-job holder can be considered precarious. In fact, for some multiple-job holders, the combination of two precarious jobs may have benefits. Therefore, it is important not to study multiple-job holding as a type of precarious employment and additionally to take the heterogeneity among multiple-job holders into account in future research.

Occupational health researchers regularly conduct evaluative intervention research for which a randomized controlled trial (RCT) may not be the most appropriate design (eg, effects of policy measures, organizational interventions on work schedules). This article demonstrates the appropriateness of alternative designs for the evaluation of occupational health interventions, which permit causal inferences, formulated along two study design approaches: experimental (stepped-wedge) and observational (propensity scores, instrumental variables, multiple baseline design, interrupted time series, difference-in-difference, and regression discontinuity). For each design, the unique characteristics are presented including the advantages and disadvantages compared to the RCT, illustrated by empirical examples in occupational health. This overview shows that several appropriate alternatives for the RCT design are feasible and available, which may provide sufficiently strong evidence to guide decisions on implementation of interventions in workplaces. Researchers are encouraged to continue exploring these designs and thus contribute to evidence-based occupational health.

OBJECTIVES: Determinants in the domains health, job characteristics, skills, and social and financial factors may influence early retirement through three central explanatory variables, namely, the ability, motivation, and opportunity to work. Based on the literature, we created the Early Retirement Model. This study aims to investigate whether data support the model and how it could be improved. METHODS: Employees aged 58–62 years (N=1862), who participated in the first three waves of the Dutch Study on Transitions in Employment, Ability and Motivation (STREAM) were included. Determinants were assessed at baseline, central explanatory variables after one year, and early retirement after two years. Structural equation modeling was applied. RESULTS: Testing the Early Retirement Model resulted in a model with good fit. Health, job characteristics, skills, and social and financial factors were related to the ability, motivation and/or opportunity to work (significant β range: 0.05–0.31). Lower work ability (β=-0.13) and less opportunity to work (attitude colleagues and supervisor about working until age 65: β=-0.24) predicted early retirement, whereas the motivation to work (work engagement) did not. The model could be improved by adding direct effects of three determinants on early retirement, ie, support of colleagues and supervisor (β=0.14), positive attitude of the partner with respect to early retirement (β=0.15), and not having a partner (β=-0.13). CONCLUSIONS: The Early Retirement Model was largely supported by the data but could be improved. The prolongation of working life might be promoted by work-related interventions focusing on health, work ability, the social work climate, social norms on prolonged careers, and the learning environment.

The randomized controlled trial (RCT) is considered the gold standard in evaluative medical research for drawing causal inferences about the effects of the intervention under study. For several reasons, in occupational health research, an RCT is neither always the best study design nor the most feasible option. Alternative study designs are increasingly being used in situations of complex interventions, whereby multiple stakeholders are involved in a varying context (1). These designs, which mimic natural experiments, support innovative research in occupational health as they offer a new platform to examine the effectiveness of interventions combining an individual approach with workplace adjustment (2). A typical example is the area of return to work (RTW). A recent review on interventions to manage musculoskeletal-related sickness absence showed that various behavioral interventions have been evaluated in RCT. In general, person-oriented intervention studies can easily be randomized. For workplace-oriented interventions, this is less straightforward. It is not surprising, therefore, that considerably less RCT have been able to include workplace adjustments as workplace interventions (3). Typically, those RCT have small study populations and are limited to a few work organizations. The balance between the rigorousness of an RCT and a large-scale observational study has been nicely illustrated by studies on the effects of partial sickness absence in Finland. The RCT consisted of subjects with musculoskeletal disorders from six enterprises comparing 31 workers in the intervention group with 31 workers in the usual-care group (4). The observational study on register information with propensity score matching compared over 1000 subjects in the intervention group to >25 000 subjects in the usual-care group (5). Although the latter study has higher risk of bias, the RCT was so small that generalizability may be questioned. Thus, there is a clear need to make better use of existing possibilities of routinely collected data for evaluating the effects of particular interventions. In this issue of the Scandinavian Journal of Work, Environment & Health, Bethge (6) presents an elegant example of how register-based information can be utilized to determine the effects of graded RTW (GRTW). In Germany, this program is offered to patients who are unable to return to work at full capacity in their regular job immediately after clinical rehabilitation has finished. Several factors contributed to the decision that a randomized study was not possible. First, this GRTW service was introduced and implemented nationwide before proper scientific evaluation on its effectiveness was conducted. As researchers, we have the choice to either gnash our teeth about such developments and rue missed opportunities for evidence-based policies or try to take advantage of the large-scale implementation by studying effects in an observational study under routine conditions. Second, the GRTW service requires agreement and consent from the patient, the employer, the general practitioner, and the occupational physician. This inevitable procedure will remove one of the key advantages of an RCT, ie, blinding of the patient and all persons involved in treatment. Third, a related problem is that it will be hard to convince everyone that, after consent has been given by all parties involved, the randomization procedure will determine who will get the GRTW service and who will not get this therapeutic work resumption. The author turned the disadvantage of not being able to conduct an RCT into the advantage of carrying out a large observational study with multiple outcome measures over a prolonged follow-up period through linkage of different registers. The Bethge study presents some important results. In the GRTW intervention group, there was less sickness absence (>50 days difference compared to usual care) during the 3-year follow-up period. In addition, the risk of a disability benefit decreased by 40%. Through the linkage with other registered-based information, it was also shown that the GRTW group had a €4000 per year higher income, an important observation not often reported in occupational health studies. Through the large study population of 1875 persons in the intervention group, sufficient statistical power was available for several subgroup analyses. There were no differences across diagnostic group, suggesting that a graded RTW approach may be similarly beneficial for workers with musculoskeletal disorders, mental disorders, and cancer. The relevance of this finding cannot be underestimated, since it would have been virtually impossible for any intervention to conduct a sufficiently large RCT, or alternatively four RCT in different patient groups. Bethge stated that GRTW is “a therapeutic measure that aims to test and practice work capacity at the workplace” (6, p1). The effects of GRTW have been studied more often, using a range of different terms for more or less the same intervention: partial or part-time sick leave, adaptation in working hours, graded work exposure, and partial or therapeutic work resumption. A cohort study in six countries demonstrated that GRTW was the most commonly applied intervention among workers who were sick-listed due to low-back pain (7). Almost half of all cohort participants (46%) were offered GRTW. A study evaluating the effects of GRTW using an instrumental variable method indicated that it improved the probability of recovery to full work capacity among workers on sickness absence due to musculoskeletal disorders (8). Another study, applying econometric models to analyze combined survey and register data, also showed this beneficial effect for GRTW on return to regular working hours, irrespective of the cause of sickness absence (9). For employees sick-listed due to mental disorders, however, econometric models revealed that GRTW was not effective in promoting return to regular working hours (10) or that GRTW was only effective after >60 days of sickness absence (11). These findings correspond to a Cochrane review on workplace interventions to prevent work disability among workers on sick leave, which also showed better effects for workers with musculoskeletal disorders than for those with sickness absence due to mental disorders or cancer (12). From this perspective, the results of Bethge were more hopeful in that, with the exception of persons with cardiovascular disorders, GRTW was found to be beneficial for those with musculoskeletal disorders, mental and behavioral disorders as well as cancer (6). In conclusion, Bethge’s observational study presents evidence that (i) gradual RTW is a method to be used across most chronic diseases and (ii) timely attachment to one’s job will support workers to remain productive in their regular job and have a higher income. The latter is certainly an uplifting message for the reader of this journal. Often our studies focus on the adverse effects of work on health. The study demonstrates that for many workers with health problems, being at work promotes health and wealth!

OBJECTIVES: The aim of this study was to evaluate the effects of an mHealth intervention (intervention using mobile technology) consisting of tailored advice regarding exposure to daylight, sleep, physical activity, and nutrition, and aiming to improve health-related behavior, thereby reducing sleep problems and fatigue and improving health perception of airline pilots. METHODS: A randomized controlled trial was conducted among 502 airline pilots. The intervention group was given access to both the MORE Energy mobile application (app) with tailored advice and a website with background information. The control group was directed to a website with standard information about fatigue. Health-related behavior, fatigue, sleep, and health perception outcomes were measured through online questionnaires at baseline and at three and six months after baseline. The effectiveness of the intervention was determined using linear and Poisson mixed model analyses. RESULTS: After six months, compared to the control group, the intervention group showed a significant improvement on fatigue (β= -3.76, P

OBJECTIVES: This study aimed to assess the influence of chronic health problems on work ability and productivity at work among older employees using different methodological approaches in the analysis of longitudinal studies. METHODS: Data from employees, aged 45–64, of the longitudinal Study on Transitions in Employment, Ability and Motivation was used (N=8411). Using three annual online questionnaires, we assessed the presence of seven chronic health problems, work ability (scale 0–10), and productivity at work (scale 0–10). Three linear regression generalized estimating equations were used. The time-lag model analyzed the relation of health problems with work ability and productivity at work after one year; the autoregressive model adjusted for work ability and productivity in the preceding year; and the third model assessed the relation of incidence and recovery with changes in work ability and productivity at work within the same year. RESULTS: Workers with health problems had lower work ability at one-year follow-up than workers without these health problems, varying from a 2.0% reduction with diabetes mellitus to a 9.5% reduction with psychological health problems relative to the overall mean (time-lag). Work ability of persons with health problems decreased slightly more during one-year follow-up than that of persons without these health problems, ranging from 1.4% with circulatory to 5.9% with psychological health problems (autoregressive). Incidence related to larger decreases in work ability, from 0.6% with diabetes mellitus to 19.0% with psychological health problems, than recovery related to changes in work ability, from a 1.8% decrease with circulatory to an 8.5% increase with psychological health problems (incidence-recovery). Only workers with musculoskeletal and psychological health problems had lower productivity at work at one-year follow-up than workers without those health problems (1.2% and 5.6%, respectively, time-lag). CONCLUSIONS: All methodological approaches indicated that chronic health problems were associated with decreased work ability and, to a much lesser extent, lower productivity at work. The choice for a particular methodological approach considerably influenced the strength of the associations, with the incidence of health problems resulting in the largest decreases in work ability and productivity at work.

OBJECTIVES: This study aimed to investigate the relative contribution of health, job characteristics, skills and knowledge, and social and financial factors to the transition from work to (non-disability) early retirement. METHODS: Employees aged 59–63 years (N=2317) were selected from the Study on Transitions in Employment, Ability and Motivation in the Netherlands (STREAM). Individual characteristics, health, job characteristics, skills and knowledge, and social and financial factors were measured using a questionnaire at baseline. Information on early retirement was derived from the one-year follow-up questionnaire. Logistic regression analyses were used to identify predictors of early retirement. Population Attributable Fractions (PAF) were calculated. RESULTS: Older age [odds ratio (OR) 1.79], poor physical health (OR 1.78), a positive attitude of the partner with respect to early retirement (OR 3.85), and the financial possibility to stop working before the age of 65 (OR 10.2) predicted the transition to early retirement, whereas employees that reported high appreciation at work (OR 0.58) and higher focus on development of skills and knowledge (OR 0.54) were less likely to retire early. PAF were 0.75 for the financial possibility to stop working, 0.43 for a positive attitude of the partner with respect to early retirement, 0.27 for low appreciation at work, 0.23 for a low focus on development, and 0.21 for poor health. CONCLUSIONS: The financial possibility to stop working before the age of 65 importantly contributes to early retirement. In the context of rapidly diminishing financial opportunities to retire early in the Netherlands, the prolongation of working life might be promoted by workplace health promotion and disability management, and work-related interventions focusing on appreciation and the learning environment.

OBJECTIVE: This study aimed to investigate the effectiveness of a prevention program on work ability, health, and sick leave targeted at construction worksites. METHODS: A total of 15 departments (N=297 workers) from 6 construction companies participated in this cluster randomized controlled trial and were randomly allocated to the intervention (8 departments; N=171 workers) or control (7 departments; N=122 workers) group. The intervention consisted of two individual training sessions with a physical therapist aimed at lowering the physical workload, a rest-break tool to improve the balance between work and recovery, and two empowerment training sessions to increase the worker’s influence at the worksite. Data on work ability, physical and mental health status, and musculoskeletal symptoms were collected at baseline, and at 3, 6, and 12 months follow-up. Sick leave data were obtained from the companies. RESULTS: Overall, no differences in work ability [β 0.02, 95% confidence interval (95% CI) -0.34–0.37] or physical and mental health status (β -0.04, 95% CI -1.43–1.35, and β 0.80 95% CI -0.51–2.11, respectively) were found between the intervention and control group. The intervention showed an overall decline in musculoskeletal symptoms (ranging from OR 0.68, 95% CI 0.34–1.33, to OR 0.86, 95% CI 0.47–1.57) and long-term sick leave (OR 0.44, 95% CI 0.13–1.26) among construction workers. Both reductions were not statistically significant. CONCLUSION: The prevention program seemed to result in a beneficial but not statistically significant decline in the prevalence of musculoskeletal symptoms and long-term sick leave among construction workers, but showed no effects with regard to work ability, physical health, and mental health.

OBJECTIVE: Office workers with high levels of overcommitment and low levels of reward are thought to be more prone to arm-wrist-hand symptoms, possibly through a higher internal physical exposure. The aim of this study was to examine the effects of high overcommitment and low reward on (i) forearm muscle activity, (ii) wrist posture and kinematics, and (iii) forces applied to computer input devices during computer work in an actual work setting. METHODS: We continuously measured wrist extensor muscle activity, wrist posture and kinematics, and forces applied to the keyboard and mouse for two hours during the daily work of 120 office workers with four different levels of overcommitment and reward (low–high, high–high, low–low, and high–low). RESULTS: Wrist velocities and accelerations in radial-ulnar direction were higher for workers with high compared to low overcommitment, while their wrist range of motion was similar, possibly indicating a higher work pace. Wrist extensor muscle activity and forces applied to the keyboard and mouse were not increased by high overcommitment and/or low reward. CONCLUSION: Overall, our findings provide little support for the proposed pathway of high overcommitment and low reward in the development of arm-wrist-hand symptoms through a higher internal physical exposure.

OBJECTIVES: The aim of the study was to evaluate the cost-effectiveness, -utility, and -benefit of a newly developed participatory return-to-work (RTW) program for temporary agency and unemployed workers, sick-listed due to musculoskeletal disorders. METHODS: An economic evaluation was conducted alongside a randomized controlled trial with a 12-month follow-up. Temporary agency and unemployed workers, sick-listed for 2–8 weeks due to musculoskeletal disorders, were randomized to the participatory RTW program (N=79) or usual care group (N=84). The new RTW program was aimed at making a consensus-based RTW action plan with the possibility of a temporary (therapeutic) workplace. Effect outcomes were sustainable RTW and quality-adjusted life years (QALY). Healthcare utilization was measured from the social insurer’s perspective and societal perspective. RESULTS: Total healthcare costs in the participatory RTW program group [10 189 (standard deviation [SD] 7055) euros] were statistically significantly higher compared to care-as-usual [7862 (SD 7394) euros]. The cost-effectiveness analyses showed that the new intervention was more effective but also more costly than usual care (ie, to gain RTW one day earlier in the participatory RTW program group approximately 80 euros needed to be invested). The net societal benefit of the participatory RTW program compared to care-as-usual was 2073 euros per worker. CONCLUSIONS: The newly developed participatory RTW program was more effective but also more costly than usual care. The program enhanced work resumption and generated a net socioeconomic benefit. Hence, implementation of the participatory RTW program may have potential to achieve a sustainable contribution of vulnerable workers to the labor force.

OBJECTIVES: A worksite lifestyle intervention aiming to improve lifestyle behaviors could be an effective tool to keep older workers vital, and thereby prolong their labor participation. Therefore, this study evaluates the effectiveness of such an intervention on vitality, work engagement, productivity and sick leave. METHODS: In a randomized controlled trial design, 367 workers (control group: N=363) received a 6-month intervention, which included two weekly guided group sessions: one yoga and one workout, as well as one weekly session of aerobic exercising, without face-to-face instruction, and three individual coach visits aimed at changing workers’ lifestyle behavior by goal setting, feedback, and problem-solving strategies. Furthermore, free fruit was provided at the guided sessions. Data on work-related vitality (UWES vitality scale), general vitality (RAND-36 vitality scale), work engagement (UWES), productivity (single item scoring 0–10), and sick leave (yes/no past 3 months) were collected using questionnaires at baseline (N=730), and at 6- (N=575) and 12-months (N=500) follow-up. Effects were analyzed according to the intention-to-treat principle with complete cases (N=500) and imputed data (N=730). RESULTS: There were no significant differences in vitality, work engagement, productivity, and sick leave between the intervention and control group workers after either 6- and 12-months follow-up. Yoga and workout subgroup analyses showed a 12-month favorable effect on work-related vitality [β=0.14, 95% confidence interval (95% CI) 0.04–0.28] and general vitality (β=2.9, 95% CI 0.02–5.9) among high yoga compliers. For high workout compliers, this positive trend was also seen, but it was not statistically significant. CONCLUSIONS: Implementation of worksite yoga facilities could be a useful strategy to promote vitality-related work outcomes, but only if high compliance can be maximized. Therefore, impeding factors for participation should be investigated in more detail in future research.

BACKGROUND:Sedentary behaviour increases the risk for morbidity. Our primary aim is to determine the proportion and factors associated with objectively measured total and occupational sedentary time in three work settings. Secondary aim is to study the proportion of physical activity and prolonged sedentary bouts. METHODS:Data were obtained using ActiGraph accelerometers from employees of: 1) a financial service provider (n = 49 men, 31 women), 2) two research institutes (n = 30 men, 57 women), and 3) a construction company (n = 38 men). Total (over the whole day) and occupational sedentary time, physical activity and prolonged sedentary bouts (lasting ≥30 minutes) were calculated by work setting. Linear regression analyses were performed to examine general, health and work-related factors associated with sedentary time. RESULTS:The employees of the financial service provider and the research institutes spent 76-80% of their occupational time in sedentary behaviour, 18-20% in light intensity physical activity and 3-5% in moderate-to-vigorous intensity physical activity. Occupational time in prolonged sedentary bouts was 27-30%. Total time was less sedentary (64-70%), and had more light intensity physical activity (26-33%). The employees of the construction company spent 44% of their occupational time in sedentary behaviour, 49% in light, and 7% in moderate intensity physical activity, and spent 7% in sedentary bouts. Total time spent in sedentary behavior was 56%, 40% in light, and 4% in moderate intensity physical behaviour, and 12% in sedentary bouts. For women, low to intermediate education was the only factor that was negatively associated with occupational sedentary time. CONCLUSIONS:Sedentary behaviour is high among white-collar employees, especially in highly educated women. A relatively small proportion of sedentary time was accrued in sedentary bouts. It is recommended that worksite health promotion efforts should focus on reducing sedentary behaviour through improving light intensity physical activity.

OBJECTIVE: The aim of this study was to appraise and summarize the evidence on the cost-effectiveness of worksite physical activity and/or nutrition programs. METHODS: We searched EMBASE, MEDLINE, SportDiscus, PsycInfo, NIOSHTIC-2, NHSEED, HTA, and Econlit for studies published up to 14 January 2011. Additionally, we searched for articles by reviewing references, searching authors’ databases, and contacting authors of included studies. Two researchers independently selected articles. Articles had to include a cost-effectiveness and/or cost-utility analysis comparing a worksite physical activity and/or nutrition program to usual care or an abridged version of the program. Data were extracted on study characteristics and results. Two researchers independently assessed the risk of bias using the Consensus on Health Economic Criteria list (CHEC-list). RESULTS: Ten studies (18 programs) were included. More than 50% of the studies fulfilled 11 (58%) of the 19 CHEC-list items. From various perspectives, worksite nutrition and worksite physical activity and nutrition programs (N=6) were more costly and more effective in reducing body weight than usual care. When only intervention costs were considered, most worksite nutrition (N=4/5) and worksite physical activity and nutrition programs (N=5/6) were more costly and more effective in reducing cholesterol level and cardiovascular disease risks, respectively. CONCLUSIONS: The cost-effectiveness of more costly and more effective programs depends on the “willingness to pay” for their effects. It is unknown how much decision-makers are willing to pay for reductions in body weight, cholesterol level, and cardiovascular disease risks. Therefore, conclusions about the cost-effectiveness of worksite physical activity and/or nutrition programs cannot be made. There is substantial need for improvement of the methodological quality of studies and particular emphasis should be placed on the handling of uncertainty.

OBJECTIVES: Epidemiologic studies on physical exposure during computer use have mainly focused on average exposure duration. In this study, we aimed to relate periods of high peak exposure during computer use with the occurrence of neck–shoulder (NS) and arm–wrist–hand (AWH) symptoms. METHODS: A prospective cohort study among 1951 office workers was carried out for two years, with periodical questionnaires and continuous measurements of computer input use. To define peak exposure, a distinction was made between peak days and weeks. Peak days were defined as days with a long duration of computer (ie, ≥4 hours) or mouse use (ie, ≥2.5 hours) or days with high frequency of mouse (ie, ≥20 clicks per minute) or keyboard use (ie, ≥160 keystrokes per minute). Weeks containing ≥3 peak days were considered peak weeks. Independent variables were numbers of peak days and peak weeks during a 3-month measurement period; dependent variables were self-reported NS and AWH symptoms during the following 3-month measurement period. RESULTS: Valid data were available for 2116 measurements of 774 office workers. No relation was found between any of the peak exposure parameters and AWH symptoms or with peak exposure in duration and NS symptoms. Most parameters referring to high frequency-related peak exposure were associated with less NS symptoms, but the effect estimates were very small and the confidence intervals close to the null. CONCLUSION: In this study, we found no indication that high peaks in computer use were related to the occurrence of NS or AWH symptoms.

OBJECTIVE: The aim of this randomized controlled trial (RCT) was to investigate the effectiveness of the Stay@Work participatory ergonomics (PE) program to prevent low-back and neck pain. METHODS: A total of 37 departments were randomly allocated to either the intervention (PE) or control group (no PE). During a six-hour meeting, working groups followed the PE steps and composed and prioritized ergonomic measures aimed at preventing low-back and neck pain. Subsequently, working groups were requested to implement the ergonomic measures in the departments. The primary outcomes were low-back and neck pain prevalence and secondary outcomes were pain intensity and duration. Data were collected by questionnaires at baseline, and after 3-, 6-, 9-, and 12-months follow-up. Additionally, the course of low-back and neck pain (transitions from no symptoms to symptoms and from symptoms to no symptoms) was modeled. RESULTS: The randomization procedure resulted in 19 intervention departments (N=1472 workers) and 18 control departments (N=1575 workers). After 12 months, the intervention was not more effective than the control group in reducing the prevalence of low-back and neck pain or reducing pain intensity and duration. PE did not increase the probability of preventing low-back pain [odds ratio (OR) 1.23, 95% confidence interval (95% CI) 0.97–1.57) or neck pain (OR 1.01, 95% CI 0.74–1.40). However, PE increased the probability of recovering from low-back pain (OR 1.41, 95% CI 1.01–1.96), but not from neck pain (OR 0.95, 95% CI 0.72–1.26). CONCLUSION: PE neither reduced low-back and neck pain prevalence nor pain intensity and duration nor was it effective in the prevention of low-back and neck pain or the recovery from neck pain. However, PE was more effective in the recovery from low-back pain.

OBJECTIVE: This systematic review aims to summarize the available evidence to elucidate the effects of shift work, which includes night work, on body weight change. METHODS: A systematic search strategy using longitudinal studies was performed. Articles were included based on strict inclusion criteria; methodological quality was assessed by a standardized quality checklist. The results were summarized using a levels of evidence synthesis. RESULTS: The search strategy resulted in eight articles that met the inclusion criteria. Five of them were considered to be high- and three of them low-quality studies. Seven studies presented crude results for an association between shift work exposure and change in body weight: five high- and two low-quality studies. There was strong evidence for a crude relationship between shift work and body weight increase. Five studies presented weight-related outcomes adjusted for potentially relevant confounders (age, gender, bodyweight at baseline, and physical activity). Two studies found a significant difference between groups in the same direction. Consequently, the evidence for a confounders-adjusted relationship between shift work exposure and body weight was considered to be insufficient. CONCLUSIONS: Strong evidence for a crude association between shift work exposure and body weight increase was found. In order to further clarify the underlying mechanisms, more and better high quality studies about this subject are necessary.

OBJECTIVE: The aim of this study was to examine the adherence of occupational physicians (OP) to the Dutch guideline on the management of common mental health problems and its effect on return to work as part of the process evaluation of a trial comparing adherence to the guideline to care as usual. The first hypothesis was that guideline adherence among the “guideline group” will be higher compared to the “usual care group”. The second hypothesis was that better guideline adherence by the occupational physician will be associated with earlier return to work. METHODS: In a randomized controlled trial, five participating OP had to provide care based on the Dutch guideline to 240 police workers with common mental health problems (the “guideline group”). The same OP had to provide usual care to the participants in the control group (the “usual care” group), including minimal involvement and easy access to a psychologist. In evaluating the process, we assessed guideline adherence via an audit of medical files, using 20 guideline-based performance indicators. Mean rates of guideline adherence were related to the duration until first and full return to work, using a Cox proportional hazards model. RESULTS: The mean rate of the sum score of guideline adherence was 10 in a range of 0–20 [standard deviation (SD) 1.8] and did not significantly differ between the intervention and control group. Mean better guideline adherence showed a statistically significant association with a shorter time to first and full return to work [hazard ratio 1.1; 95% confidence interval (95% CI) 1.0–1.2], which was explained by keeping more regular contact with the worker and the work system and better monitoring of stagnation or return to work. CONCLUSIONS: No contrast in guideline adherence was found between guideline-based versus usual care. This can be explained by contamination between the guideline and usual care group. Even though guideline adherence was only average, better adherence predicted earlier return to work. Guidelines for management of common mental health problems and return to work should focus on regular contact with the worker and the work organisation.

OBJECTIVE: Using a standardized quality criteria list, we appraised the methodological quality of economic evaluations of occupational safety and health (OSH) interventions conducted from a corporate perspective. METHODS: The primary literature search was conducted in Medline and Embase. Supplemental searches were conducted in the Cochrane NHS Economic Evaluation Database, the National Institute for Occupational Safety and Health (NIOSH) database, the Ryerson International Labour, Occupational Safety and Health Index, scans of reference lists, and researchers’ own literature database. Independently, two researchers selected articles based on title, keywords, and abstract, and if needed, fulltext. Disagreements were resolved by a consensus procedure. Articles were selected based on seven criteria addressing study population, type of intervention, comparative intervention, outcome, costs, language, and perspective. Two reviewers independently judged methodological quality using the Consensus on Health Economic Criteria (CHEC-list), a 19-item standardized quality criteria list. Disagreements in judgment were also resolved by consensus. Data were analyzed descriptively. RESULTS: A total of 34 studies were included. Of these, only 44% of the studies met more than 50% of the quality criteria. Of the 19 quality criteria, 8 were met by 50% or more of the studies. The 11 least fulfilled criteria related to (i) performance of a sensitivity analysis, (ii) selection of perspective, (iii) description of study population, (iv) discussion of generalizability, (v) description of competing alternatives, (vi) presentation of the research question, (vii) measurement of outcomes, (viii) measurement of costs, (ix) valuation of costs, (x) declaration of researchers’ independence, and (xi) discussion of ethical and distributional issues. CONCLUSIONS: Apart from a few exceptions, the overall methodological quality of the economic evaluations of OSH interventions from a corporate perspective was poor. As such, there is a risk of biased results. The quality of future evaluations needs to be improved to increase the validity of their conclusions and recommendations.

OBJECTIVE: The goal of this review was to summarize the evidence for an effect of lifestyle-targeted interventions at the workplace on the main biological risk factors for cardiovascular disease (CVD). METHODS: We performed an extensive systematic literature search for randomized controlled trials (RCT) that met the following inclusion criteria: (i) targeted at workers; (ii) aimed at increasing physical activity and/or improving diet; and (iii) measured body weight, body fat, blood pressure, blood lipids and/or blood glucose. We used a nine-item methodological quality list to determine the quality of each study. A best-evidence system was applied, taking into account study quality and consistency of effects. RESULTS: Our review included 31 RCT, describing a diversity of interventions (eg counseling, group education, or exercise). Of these studies, 18 were of high quality. Strong evidence was found for a positive effect on body fat, one of the strongest predictors of CVD risk. Among populations “at risk”, there was strong evidence for a positive effect on body weight. Due to inconsistencies in results between studies, there was no evidence for the effectiveness of interventions on the remaining outcomes. CONCLUSIONS: We found strong evidence for the effectiveness of workplace lifestyle-based interventions on body fat and, in populations at risk for CVD, body weight. Populations with an elevated risk of CVD seemed to benefit most from lifestyle interventions; supervised exercise interventions appeared the least effective intervention strategy. To gain better insight into the mechanisms that led to the intervention effects, the participants’ compliance with the intervention and the lifestyle changes achieved should be reported in future studies.

OBJECTIVES: The aim of the present study was to evaluate the effectiveness of a worksite mindfulness-related multi-component health promotion intervention on work engagement, mental health, need for recovery and mindfulness. METHODS: In a randomized controlled trial design, 257 workers of two research institutes participated. The intervention group (n = 129) received a targeted mindfulness-related training, followed by e-coaching. The total duration of the intervention was 6 months. Data on work engagement, mental health, need for recovery and mindfulness were collected using questionnaires at baseline and after 6 and 12 months follow-up. Effects were analyzed using linear mixed effect models. RESULTS: There were no significant differences in work engagement, mental health, need for recovery and mindfulness between the intervention and control group after either 6- or 12-months follow-up. Additional analyses in mindfulness-related training compliance subgroups (high and low compliance versus the control group as a reference) and subgroups based on baseline work engagement scores showed no significant differences either. CONCLUSIONS: This study did not show an effect of this worksite mindfulness-related multi-component health promotion intervention on work engagement, mental health, need for recovery and mindfulness after 6 and 12 months. TRIAL REGISTRATION: Netherlands Trial Register NTR2199.