Scandinavian journal of work, environment & health最新文献

Objectives: The aim was to conduct a systematic review and meta-analysis investigating the association between occupational mechanical exposures and hip osteoarthritis.

Methods: The study was registered in PROSPERO. A systematic literature search was conducted in six databases to identify relevant articles. Two authors independently excluded articles, extracted data, assessed the risk of bias of each included article, and graded the level of evidence. We conducted a meta-analysis using random-effects model and performed a sensitivity analysis stratifying articles based on the risk of bias assessment, study design, and the outcome measurement.

Results: Twenty-four articles were eligible for inclusion. The highest pooled odds ratio (OR) was found for combined mechanical exposures [OR 1.7, 95% confidence interval (CI) 1.4-2.0], non-neutral postures (OR 1.7, 95% CI 1.4-2.1), lifting/carrying loads (OR 1.6, 95% CI 1.3-1.9), and climbing stairs (OR 1.6, 95% CI 1.1-2.2). The range of pooled OR for the remaining mechanical exposures (eg, standing, walking, kneeling, squatting, and sitting) was 0.6-1.6. Grading the quality of evidence, a moderate level of evidence was found for the combined mechanical exposures and for lifting/carrying loads. The remaining exposure categories were graded as having either low or very low levels of evidence.

Conclusions: Considerable heterogeneity was observed across the included studies, and high-quality literature using objective exposure measurements is warranted. Despite various limitations affecting the comparability, occupational mechanical exposures seem to influence the likelihood of developing hip osteoarthritis.

Objective: This paper discusses the past and present highlights of working hours and health research and identifies key research needs for the future.

Method: We analyzed over 220 original articles and reviews on working hours and health in the Scandinavian Journal of Work, Environment & Health published during the last 50 years. Key publications from other journals were also included.

Results: The majority of identified articles focussed on the effects of shift and night work, with fewer studying long and reduced working hours and work time control. We observed a transition from small-scale experimental and intensive field studies to large-scale epidemiological studies utilizing precise exposure assessment, reflecting the recent emergence of register-based datasets and the development of analytic methods and alternative study designs for randomized controlled designs. The cumulative findings provide convincing evidence that shift work and long working hours, which are often associated with night work and insufficient recovery, increase the risk of poor sleep and fatigue, sickness absence, occupational injuries, and several chronic health conditions such as cardiovascular diseases and cancer. The observed risks are strongly modified by individual and work-related factors.

Conclusions: Although the observed health risks of shift work and long working hours are mostly low or moderate, the widespread prevalence of exposure and the hazardousness of the many associated potential outcomes makes such working time arrangements major occupational health risks. Further research is needed to identify exposure-response associations, especially in relation to the chronic health effects, and to elucidate underlying pathways and effective personalized intervention strategies.

Objectives: Long working hours and overwork are growing public health concerns in the Western-Pacific region. We explored the relationship between working hours and smoking behaviors of Korean workers.

Methods: This study included 284 782 observations (50 508 workers) from four nationwide cohort studies in Korea. Using generalized estimating equations, we estimated the associations of working hours with current smoking status, smoking initiation, and smoking cessation within each cohort. Cohort-specific estimates were combined through random-effect meta-analysis. Effect sizes were presented as odds ratios (OR) and 95 confidence intervals (CI).

Results: The overall smoking prevalence was 26.8% within the cohorts. The adjusted OR (95% CI) of the association between working hours and current smoking were 1.01 (0.94-1.08) for <35 hours/week, 1.04 (1.01-1.09) for 41-48 hours/week, 1.06 (1.01-1.10) for 49-54 hours/week, and 1.07 (1.04-1.10) for ≥55 hours/week compared with 35-40 hours/week. The adjusted OR (95% CI) of the association between working hours and smoking cessation in the follow-up were 0.93 (0.85-1.02) for <35 hours/week, 0.89 (0.83-0.96) for 41-48 hours/week, 0.87 (0.81-0.95) for 48-54 hours/week, and 0.91 (0.85-0.98) for ≥55 hours/week compared with 35-40 hours/week. No clear associations were observed between working hours and smoking initiation.

Conclusion: Long working hours are associated with high current smoking risk and reduced likelihood of smoking cessation among Korean workers. Policy interventions are required to promote smoking cessation and reduce excess overwork for individuals experiencing long working hours.

Objective: This study aimed to determine if there is an increased risk of incident cardiovascular diseases (CVD) resulting from cumulative night shift work in the German population-based Gutenberg Health Study (GHS).

Methods: We examined working participants of the GHS at baseline and after five years. Cumulative night shift work in the 10 years before baseline was assessed and categorized as low (1-220 nights ≙ up to 1 year), middle (221-660 nights ≙ 1-3 years), and high (>660 nights ≙ more than 3 years) night shift exposure. Hazard ratios (HR) were estimated for incident "quality-assured CVD events" using Cox proportional hazard models.

Results: At baseline, 1092 of 8167 working participants performed night shift work. During the follow-up, 202 incident cardiovascular events occurred. The crude incidence rates for CVD per 1000 person-years were 6.88 [95% confidence interval (CI) 4.80-9.55] for night shift workers and 5.19 (95% CI 4.44-6.04) for day workers. Cumulative incidence curves showed a higher cumulative incidence in workers exposed to night shift work compared to day workers after five years. The adjusted HR for incident CVD events were 1.26 (95% CI 0.68-2.33), 1.37 (95% CI 0.74-2.53) and 1.19 (95% CI 0.67-2.12) for employees in the low, middle and high night shift categories compared to employees without night shift work, respectively.

Conclusions: The observed tendencies indicate that night shift work might be negatively associated with cardiovascular health. We expect the continued follow-up will clarify the long-term impact of night shift work.

Objectives: This study aimed to estimate the validity of self-reported information on ever-night shift work among women with and without breast cancer and illustrate the consequences for breast cancer risk estimates.

Methods: During 2015-2016, 225 women diagnosed with breast cancer and 1800 matched controls without breast cancer employed within the Danish hospital regions during 2007-2016 participated in a questionnaire-based survey. Their reported night shift work status was linked with objective payroll register day-by-day working hour data from the Danish Working Hour Database and the Danish Cancer Registry. For the breast cancer patients and their matched controls, we estimated sensitivity and specificity for ever-working night shifts using the payroll data as the gold standard. We also used quantitative bias analysis to estimate the impact on relative risk estimates for a hypothetical population.

Results: For breast cancer patients, we observed a sensitivity of ever-night shifts of 86.2% and a specificity of never-night shifts of 82.6%. For controls, the sensitivity was 80.6% and the specificity 83.7%. Odds ratio for breast cancer in a hypothetical population decreased from 1.12 [95% confidence interval (CI) 1.03-1.21] to 1.05 (95% CI 0.95-1.16) when corrected by the sensitivity and specificity estimates.

Conclusion: This study shows that female breast cancer patients had slightly better recall of previous night shift work than controls. Additionally, both breast cancer patients and controls recalled previous never-night shift work with low specificity. The net effect of this misclassification is a small over-estimation of the relative breast cancer risk due to night shift work.

Objectives: SARS-CoV-2 infections were unequally distributed during the pandemic, with those in disadvantaged socioeconomic positions being at higher risk. Little is known about the underlying mechanism of this association. This study assessed to what extent educational differences in SARS-CoV-2 infections were mediated by working from home.

Methods: We used data of the German working population derived from the seroepidemiological study "Corona Monitoring Nationwide - Wave 2 (RKI-SOEP-2)" (N=6826). Infections were assessed by seropositivity against SARS-CoV-2 antigens and self-reports of previous PCR-confirmed infections from the beginning of the pandemic until study participation (November 2021 - February 2022). The frequency of working from home was assessed between May 2021 and January 2022.We used the Karlson-Holm-Breen (KHB) method to decompose the effect of education on SARS-CoV-2 infections.

Results: Individuals with lower educational attainment had a higher risk for SARS-CoV-2 infection (adjusted prevalence ratio of low versus very high = 1.76, 95% confidence interval 1.08-2.88; P=0.023). Depending on the level of education, between 27% (high education) and 58% (low education) of the differences in infection were mediated by the frequency of working from home.

Conclusions: Working from home could prevent SARS-CoV-2 infections and contribute to the explanation of socioeconomic inequalities in infection risks. Wherever possible, additional capacities to work remotely, particularly for occupations that require lower educational attainment, should be considered as an important measure of pandemic preparedness. Limitations of this study are the observational cross-sectional design and that the temporal order between infection and working from home remained unclear.

Objective: Poor cardiorespiratory fitness and health is common among childcare workers. We designed the `Goldilocks-games` according to the Goldilocks Work principle to provide high-intensity physical activity for childcare workers. We investigated the effectiveness of this Goldilocks Work intervention in increasing occupational high-intensity physical activity and improving work-related health.

Methods: In a two-arm cluster randomized trial, 16 childcare institutions with 142 workers were randomly allocated to either an 8-week Goldilocks Work intervention or a control group. The primary outcome was occupational time in high-intensity physical activity. Secondary outcomes were occupational time in active physical behaviors, heart rate during sleep, pain, physical exhaustion, energy at work, work productivity, and need for recovery.

Results: The intervention was successfully delivered and received. Both groups had a low amount of occupational high-intensity physical activity at baseline, and the intervention group reported playing the games 3.1 [standard deviation (SD) 1.5] times/week for a duration of 112.2 (SD 175.0) min/week. However, the intervention did not increase high-intensity physical activity or the secondary outcomes, except for energy at work, measured on a scale from 0-10, increasing 0.65 [95% confidence interval (CI) 0.08-1.21], and need for recovery, measured on a scale from 1-5, decreasing -0.32 (95% CI, -0.54- -0.09).

Conclusion: The intervention was successfully delivered and received, but did not increase high-intensity physical activity. The intervention group increased their energy at work and decreased their need for recovery, but not the other health-related outcomes. Further research on how to design and implement health-promoting work environment interventions in childcare is needed.

Objective: This study aimed to assess the causal effect of a change in employment status on suicidal ideation and depressive symptoms by applying marginal structural models (MSM) with machine-learning (ML) algorithms.

Methods: We analyzed data from the 8-15^th waves (2013-2020) of the Korean Welfare Panel Study, a nationally representative longitudinal dataset. Our analysis included 13 294 observations from 3621 participants who had standard employment at baseline (2013-2019). Based on employment status at follow-up year (2014-2020), respondents were classified into two groups: (i) maintained standard employment (reference group), (ii) changed to non-standard employment. Suicidal ideation during the past year and depressive symptoms during the past week were assessed through self-report questionnaire. To apply the ML algorithms to the MSM, we conducted eight ML algorithms to build the propensity score indicating a change in employment status. Then, we applied the MSM to examine the causal effect by using inverse probability weights calculated based on the propensity score from ML algorithms.

Results: The random forest algorithm performed best among all algorithms, showing the highest area under the curve 0.702, 95% confidence interval (CI) 0.686-0.718. In the MSM with the random forest algorithm, workers who changed from standard to non-standard employment were 2.07 times more likely to report suicidal ideation compared to those who maintained standard employment (95% CI 1.16-3.70). A similar trend was observed in the analysis of depressive symptoms.

Conclusions: This study found that a change in employment status could lead to a higher risk of suicidal ideation and depressive symptoms.

Objectives: The quantitative job-exposure matrix SYN-JEM consists of various dimensions: job-specific estimates, region-specific estimates, and prior expert ratings of jobs by the semi-quantitative DOM-JEM. We analyzed the effect of different JEM dimensions on the exposure-response relationships between occupational silica exposure and lung cancer risk to investigate how these variations influence estimates of exposure by a quantitative JEM and associated health endpoints.

Methods: Using SYN-JEM, and alternative SYN-JEM specifications with varying dimensions included, cumulative silica exposure estimates were assigned to 16 901 lung cancer cases and 20 965 controls pooled from 14 international community-based case-control studies. Exposure-response relationships based on SYN-JEM and alternative SYN-JEM specifications were analyzed using regression analyses (by quartiles and log-transformed continuous silica exposure) and generalized additive models (GAM), adjusted for age, sex, study, cigarette pack-years, time since quitting smoking, and ever employment in occupations with established lung cancer risk.

Results: SYN-JEM and alternative specifications generated overall elevated and similar lung cancer odds ratios ranging from 1.13 (1st quartile) to 1.50 (4th quartile). In the categorical and log-linear analyses SYN-JEM with all dimensions included yielded the best model fit, and exclusion of job-specific estimates from SYN-JEM yielded the poorest model fit. Additionally, GAM showed the poorest model fit when excluding job-specific estimates.

Conclusion: The established exposure-response relationship between occupational silica exposure and lung cancer was marginally influenced by varying the dimensions of SYN-JEM. Optimized modelling of exposure-response relationships will be obtained when incorporating all relevant dimensions, namely prior rating, job, time, and region. Quantitative job-specific estimates appeared to be the most prominent dimension for this general population JEM.