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Objective: Extended working lives due to an ageing population will necessitate the maintenance of work ability across the life course. This systematic review aimed to analyze whether workplace interventions positively impact work ability. Methods: We searched Medline, PsycINFO, CINAHL and Embase databases using relevant terms. Work-based interventions were those focused on individuals, the workplace, or multilevel (combination). Work ability - measured using the work ability index (WAI) or the single-item work ability score (WAS) - was the outcome measure. Grading of Recommendations Assessment, Development ＆ Evaluation (GRADE) criteria was used to assess evidence quality, and impact statements were developed to synthesize the results. Meta-analysis was undertaken where appropriate. Results: We reviewed 17 randomized control trials (comprising 22 articles). Multilevel interventions (N=5) included changes to work arrangements and liaisons with supervisors, whilst individual-focused interventions (N=12) involved behavior change or exercise programs. We identified only evidence of a moderate quality for either individual or multilevel interventions aiming to improve work ability. The meta-analysis of 13 studies found a small positive significant effect for interventions on work ability [overall pooled mean 0.12, 95% confidence interval (CI) 0.03-0.21] with no heterogeneity for the effect size (Chi^2=11.28, P=0.51; I^2=0%). Conclusions: The meta-analysis showed a small positive effect, suggesting that workplace interventions might improve work ability. However, the quality of the evidence base was only moderate, precluding any firm conclusion. Further high quality studies are require to establish the role of interventions on work ability.

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. 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, <10, 10-19, ≥20 years), and shift workers' chronotype, with metabolic risk factors were studied using linear regression analysis. Compared to non-shift workers, shift workers' total cholesterol level was 0.38 mmol/L lower (95%-CI = -0.73 --0.04) and LDL cholesterol was 0.34 mmol/L lower (95%-CI = -0.60 --0.08). For all other metabolic risk factors, no differences were found. The association between shift work and LDL cholesterol was especially found among shift workers working night shifts for ≥20 years (B = -0.49 (95%-CI = -0.78 --0.19)). No differences were found for night shift frequency and chronotype. In this population of health care workers employed in hospitals, no evidence for differences in metabolic risk factors was observed that could underlie a link between shift work and cardio-metabolic diseases. Further research using different aspects of shift work to study the association with metabolic risk factors is recommended.

PurposeShift work has been related to obesity and diabetes, but the potential mediating role of lifestyle is yet unknown. Our aim was to investigate this mediating role of physical activity, diet, smoking, and sleep quality in the relationships between shift work, and obesity and diabetes.MethodsIn this cross-sectional study, 3188 shift workers and 6395 non-shift workers participated between 2013 and 2018 in periodical occupational health checks. Weight and height were objectively measured to calculate obesity (BMI ≥ 30 kg/m2). Diabetes status, physical activity, diet, smoking, and sleep quality were assessed using standardized questionnaires. Structural equation models adjusted for relevant confounders were used to analyze the mediating role of lifestyle in the relationships between shift work, and obesity and diabetes.ResultsShift workers were more often obese (OR: 1.37, 95% CI 1.16–1.61) and reported more often to have diabetes (OR:1.35, 95% CI 1.003–1.11) than non-shift workers. Shift workers had lower physical activity levels, ate fruit and vegetables less often, smoked more often, and had poorer sleep quality (p < 0.05). Mediation analysis revealed that shift workers had a higher odds of obesity (OR: 1.07, 95% CI 1.01–1.15) and diabetes (OR: 1.13, 95% CI 1.02–1.27) mediated by poorer sleep quality. Lower physical activity levels (OR: 1.11, 95% CI 1.05–1.19) and lower intake of fruit and vegetables (OR: 1.04, 95% CI 1.01–1.15) were also mediators in the relationship between shift work and obesity, but not in the relationship between shift work and diabetes (p ≥ 0.05).ConclusionThese results imply that interventions targeting diet, physical activity and in particular sleep problems specifically developed for shift workers could potentially reduce the adverse health effects of shift work.

Background Despite the large body of research on interventions aimed at preventing sick leave, the evidence is scattered and a comprehensive overview is lacking. Therefore, this scoping review of reviews aims to provide an overview of evidence-based interventions to prevent sick leave. Methods Embase and PsycInfo were systematically searched for reviews published between January 2000–January 2024. A review was included when at least one of the included original intervention studies fulfilled three criteria: (1) target group was active workers not on sick leave, (2) sick leave was studied as outcome, and (3) the intervention was evaluated using a controlled design. Results were descriptively summarized and grouped based on the cause of sick leave and type of intervention they focused on. Furthermore, the effectiveness in preventing sick leave was reported. Results Twenty-eight reviews were included. Eight reviews focused on preventing sick leave due to physical health problems, ten on mental health problems, and ten on all-cause sick leave. Overall, the reviews identified a lack of effective interventions to prevent sick leave. However, multi-component interventions consisting of both individual and environmental components aimed at workers’ lifestyle and aimed at mental health were promising to prevent sick leave in the general working population (e.g. workplace mental health promotion intervention). Furthermore, certain specific interventions targeting workers at risk were effective. Examples are cognitive behavioral therapy programs for workers with anxiety and depression, and consultation with occupational medical staff for workers at high risk for sick leave. Lastly, exercise programs were most effective in preventing sick leave due to physical health problems (e.g. exercise for low back pain prevention). Conclusions This scoping review identified reviews on sick leave prevention across a broad scope of health problems, types of interventions, and target groups. Although a few effective interventions for preventing sick leave were identified, the included reviews indicate a limited availability of effective interventions. Therefore, more randomized controlled trials with long-term follow-up that include sick leave as outcome are needed. To develop more effective interventions, further research is needed on better integrating the workplace environment, and on understanding barriers and facilitators to successful implementation.

OBJECTIVES: A growing body of research on infection susceptibility among night-shift workers has emerged, particularly since the COVID-19 pandemic. However, a comprehensive overview is still lacking. Therefore, this review aimed to synthesize the evidence on the association between night-shift work and susceptibility to infectious diseases. METHODS: Embase and PsycINFO were systematically searched for studies published up to September 2024. Studies were included if they comprised a working population, night-shift workers were compared to non-shift workers, and the outcome was an infectious disease. Results were descriptively synthesized for common respiratory infections (flu and common cold), SARS-CoV-2 infection, and other infections. Pooled effect estimates were calculated using random-effects meta-analysis. RESULTS: In total, 16 articles describing 14 studies among 191 320 workers were included. Based on 4 studies, night-shift work was not associated with a significantly increased risk of common respiratory infections [odds ratio (OR) 1.11, 95% confidence interval (CI) 0.97–1.27, I 2 =65.8%[. However, night-shift workers had a higher risk of SARS-CoV-2 infection than non-shift workers (OR 1.31, 95% CI 1.09–1.58, I 2 =92.2%, N=10 studies). This association was stronger in higher-quality studies and studies conducted in the first year of the COVID-19 pandemic. For other infections, insufficient studies were available to conduct a meta-analysis. The certainty of evidence was graded very low due to a limited number of (prospective cohort) studies and high inconsistency in the available studies. CONCLUSIONS: This systematic review and meta-analysis showed that night-shift work was associated with an increased risk of SARS-CoV-2 infection, but not of common respiratory infections. To address the lack of high-certainty evidence, more studies are needed that apply a prospective design with appropriate adjustment for confounding factors and more extensive information on night-shift work exposure.

Night shift work is associated with increased health risks. Here we examined the association of metabolic risk factors and immune cell counts, with both night shift work and particular characteristics thereof: frequency, duration and consecutive night shifts. We performed a cross-sectional study using data from 10,201 non-shift workers and 1062 night shift workers of the Lifelines Cohort study. Linear regression analyses, adjusted for demographic, lifestyle and occupational factors, were used to study associations of night shift work characteristics with metabolic risk factors and immune cell counts. Night shift workers had an increased BMI, waist circumference and immune cell counts compared to non-shift workers. This was especially seen in night shift workers who had a higher frequency of night shifts per month (≥ 5: BMI: B = 0.81 kg/m 2 (95%-CI = 0.43–1.10); waist circumference: B = 1.58 cm (95%-Cl = 0.34–1.71; leukocytes: B = 0.19 × 10 9 cells/L (95%-CI = 0.04–0.34 × 10 9 )) and worked more consecutive night shifts (> 3: BMI: B = 0.92 kg/m 2 (95%-CI = 0.41–1.43); waist circumference: B = 1.85 cm (95%-Cl = 0.45–3.24); leukocytes: B = 0.32 × 10 9 cells/L (95%-CI = 0.09–0.55 × 10 9 )). This association was less pronounced in long-term night shift workers (≥ 20 years). Our findings provide evidence for the association between night shift work characteristics and BMI, waist circumference and leukocytes (including, monocytes, lymphocytes, and basophil granulocytes).

OBJECTIVES: Many employees combine their work with informal care responsibilities for family and friends, potentially impacting their well-being and sustained employability. This study aimed to investigate the effectiveness of a workplace participatory approach (PA) intervention in supporting working caregivers to prevent and solve problems related to balancing work, private life, and informal care tasks. METHODS: We conducted a two-armed randomized controlled trial (ISRCTN15363783) in which working caregivers either received the PA (N=57), under guidance of an occupational professional serving as process facilitator, or usual care (N=59). We recruited 125 working caregivers from four Dutch organizations. Questionnaire-based measurements were assessed at baseline, 4, and 7 months. The primary outcome was work–life imbalance. Secondary outcomes were perceived social support from supervisors and colleagues, role overload, distress and perceived burden of combining work and informal care. Intervention effects were analyzed using intention-to-treat analysis and linear mixed models. RESULTS: The PA was not effective in reducing work–life imbalance, improving support from colleagues or reducing role overload, distress and perceived burden of combining work and informal care. However, the PA significantly improved perceived social support from supervisors at 4 months [β=0.54, 95% confidence interval (CI) 0.21–0.88] and 7 months (β=0.36, 95% CI 0.02–0.70). Interaction effects indicated that improvement in supervisor support varied depending on the organization. CONCLUSION: The PA improved supervisor support but not work–life imbalance. Further research should explore PA effects on working caregivers with and without balance issues and the role of supervisor support in reducing work–life conflict.

Background Digital interventions are potential tools for reducing and limiting occupational sedentary behaviour (SB) in sedentary desk-based jobs. Given the harmful effects of sitting too much and sitting for too long while working, the aim of this systematic review and meta-analysis was to examine the effectiveness of workplace interventions, that incorporated digital elements, to reduce the time spent in SB in office workers. Methods Randomised control trials that evaluated the implementation of workplace interventions that incorporated digital elements for breaking and limiting SB among desk-based jobs were identified by literature searches in six electronic databases (PubMed, Web of Science, Scopus, CINAHL, PsycINFO and PEDro) published up to 2023. Studies were included if total and/or occupational SB were assessed. Only studies that reported pre- and postintervention mean differences and standard deviations or standard errors for both intervention arms were used for the meta-analysis. The meta-analysis was conducted using Review Manager 5 (RevMan 5; Cochrane Collaboration, Oxford, UK). Risk of bias was assessed using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields QUALSYST tool. Results Nineteen studies were included in the systematic review. The most employed digital elements were information delivery and mediated organisational support and social influences. Multicomponent, information, and counselling interventions measuring total and/or occupational/nonoccupational SB time by self-report or via device-based measures were reported. Multicomponent interventions were the most represented. Eleven studies were included in the meta-analysis, which presented a reduction of 29.9 (95% CI: -45.2, -14.5) min/8 h workday in SB (overall effect: Z = 3.81). Conclusions Multicomponent interventions, using a wide range of digital features, have demonstrated effectiveness in reducing time spent in SB at the workplace among desk-based employees. However, due to hybrid work (i.e., work in the office and home) being a customary mode of work for many employees, it is important for future studies to assess the feasibility and effectiveness of these interventions in the evolving work landscape. Trial registration The review protocol was registered in the Prospero database (CRD42022377366).

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 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.