The long-term effect of job mobility on workers' mental health: a propensity score analysis.

OBJECTIVES: The main purpose of this longitudinal study was to elucidate the impact of external job mobility, due to a change of employer, on mental health. METHODS: A cohort of Belgian employees from the IDEWE occupational medicine registry was followed-up for twenty-seven years, from 1993 to 2019. The use of drugs for neuropsychological diseases was considered as an objective indicator of mental health. The covariates were related to demographic, physical, behavioural characteristics, occupational and work-related risks. Propensity scores were calculated with a Cox regression model with time-varying covariates. The PS matching was used to eliminate the systematic differences in subjects' characteristics and to balance the covariates' distribution at every time point. RESULTS: The unmatched sample included 11,246 subjects, with 368 (3.3%) that changed their job during the baseline year and 922 (8.2%) workers that left their employer during the follow-up. More than half of the matched sample were males, were aged less than 38 years old, did not smoke, were physically active, and normal weighted, were not exposed to shift-work, noise, job strain or physical load. A strong association between job mobility and neuropsychological treatment was found in the matched analysis (HR = 2.065, 95%CI = 1.397-3.052, P-value < 0.001) and confirmed in the sensitivity analysis (HR of 2.012, 95%CI = 1.359-2.979, P-value < 0.001). Furthermore, it was found a protective role of physical activity and a harmful role of job strain on neuropsychological treatment. CONCLUSIONS: Our study found that workers with external job mobility have a doubled risk of treatment with neuropsychological medication, compared to workers without job mobility.

Trends in incidence of occupational asthma, contact dermatitis, noise-induced hearing loss, carpal tunnel syndrome and upper limb musculoskeletal disorders in European countries from 2000 to 2012.

OBJECTIVES: The European Union (EU) strategy for health and safety at work underlines the need to reduce the incidence of occupational diseases (OD), but European statistics to evaluate this common goal are scarce. We aim to estimate and compare changes in incidence over time for occupational asthma, contact dermatitis, noise-induced hearing loss (NIHL), carpal tunnel syndrome (CTS) and upper limb musculoskeletal disorders across 10 European countries. METHODS: OD surveillance systems that potentially reflected nationally representative trends in incidence within Belgium, the Czech Republic, Finland, France, Italy, the Netherlands, Norway, Spain, Switzerland and the UK provided data. Case counts were analysed using a negative binomial regression model with year as the main covariate. Many systems collected data from networks of 'centres', requiring the use of a multilevel negative binomial model. Some models made allowance for changes in compensation or reporting rules. RESULTS: Reports of contact dermatitis and asthma, conditions with shorter time between exposure to causal substances and OD, were consistently declining with only a few exceptions. For OD with physical causal exposures there was more variation between countries. Reported NIHL was increasing in Belgium, Spain, Switzerland and the Netherlands and decreasing elsewhere. Trends in CTS and upper limb musculoskeletal disorders varied widely within and between countries. CONCLUSIONS: This is the first direct comparison of trends in OD within Europe and is consistent with a positive impact of European initiatives addressing exposures relevant to asthma and contact dermatitis. Taking a more flexible approach allowed comparisons of surveillance data between and within countries without harmonisation of data collection methods.

Performing DISCO-SCA to search for distinctive and common information in linked data.

Behavioral researchers often obtain information about the same set of entities from different sources. A main challenge in the analysis of such data is to reveal, on the one hand, the mechanisms underlying all of the data blocks under study and, on the other hand, the mechanisms underlying a single data block or a few such blocks only (i.e., common and distinctive mechanisms, respectively). A method called DISCO-SCA has been proposed by which such mechanisms can be found. The goal of this article is to make the DISCO-SCA method more accessible, in particular for applied researchers. To this end, first we will illustrate the different steps in a DISCO-SCA analysis, with data stemming from the domain of psychiatric diagnosis. Second, we will present in this article the DISCO-SCA graphical user interface (GUI). The main benefits of the DISCO-SCA GUI are that it is easy to use, strongly facilitates the choice of model selection parameters (such as the number of mechanisms and their status as being common or distinctive), and is freely available.

SCA with rotation to distinguish common and distinctive information in linked data.

Often data are collected that consist of different blocks that all contain information about the same entities (e.g., items, persons, or situations). In order to unveil both information that is common to all data blocks and information that is distinctive for one or a few of them, an integrated analysis of the whole of all data blocks may be most useful. Interesting classes of methods for such an approach are simultaneous-component and multigroup factor analysis methods. These methods yield dimensions underlying the data at hand. Unfortunately, however, in the results from such analyses, common and distinctive types of information are mixed up. This article proposes a novel method to disentangle the two kinds of information, by making use of the rotational freedom of component and factor models. We illustrate this method with data from a cross-cultural study of emotions.

The Impact of a Change in Employment on Three Work-Related Diseases: A Retrospective Longitudinal Study of 10,530 Belgian Employees.

BACKGROUND: The literature that has investigated to what extent a change in employment contributes to good health is contradictory or shows inconsistent results. The aim of this study was to investigate whether an association exists between a change in employment and cardiovascular, musculoskeletal and neuropsychological diseases in a sample of 10,530 Belgian workers in a seven-year follow-up study period. METHODS: The following factors were analysed: Demographic variables, a change in employment and the work-related risks. Individuals being on medication for cardiovascular, musculoskeletal, and neuropsychological diseases were used as proxies for the three health issues. Logistic regression models for autocorrelated data with repeated measures were used to examine each medication type. RESULTS: A change in employment and psychosocial load can have an important effect on the health of cardiovascular employees. Demographic variables, such as BMI and age, are risk factors for all three medications. Repetitive, manual tasks, handling static, exposure to noise levels of 87 dB, mechanical and/or manual handling with loads, and shift work were found to be positively associated with medications taken for musculoskeletal diseases. Exposure to noise 80 dB(A), managing physical loads and night work were found to be associated with being on medication for neuropsychological diseases. Physical activity and skill levels were considered to be protective factors for being on medication for neuropsychological diseases. CONCLUSIONS: Change in employment and psychosocial load were found as two important risk factors for being on medication for cardiovascular (CVD). Dealing with loads, doing shift work and being daily exposed to the noise of 87 dB correlated with being on medication for musculoskeletal (MSD). Dealing with physical loads, doing night work and being exposed to the noise of 80 dB were risk factors for being on medication for neuropsychological (NPD). While doing physical activity and reporting higher skill levels were found to be protective factors for NPD.

The effect of exposure to long working hours on stroke: A systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury.

BACKGROUND: The World Health Organization (WHO) and the International Labour Organization (ILO) are developing joint estimates of the work-related burden of disease and injury (WHO/ILO Joint Estimates), with contributions from a large network of individual experts. Evidence from mechanistic data and prior studies suggests that exposure to long working hours may cause stroke. In this paper, we present a systematic review and meta-analysis of parameters for estimating the number of deaths and disability-adjusted life years from stroke that are attributable to exposure to long working hours, for the development of the WHO/ILO Joint Estimates. OBJECTIVES: We aimed to systematically review and meta-analyse estimates of the effect of exposure to long working hours (three categories: 41-48, 49-54 and ≥55 h/week), compared with exposure to standard working hours (35-40 h/week), on stroke (three outcomes: prevalence, incidence, and mortality). DATA SOURCES: A protocol was developed and published, applying the Navigation Guide to systematic reviews as an organizing framework where feasible. We searched electronic databases for potentially relevant records from published and unpublished studies, including Ovid MEDLINE, PubMed, EMBASE, Scopus, Web of Science, CISDOC, PsycINFO, and WHO ICTRP. We also searched grey literature databases, Internet search engines, and organizational websites; hand-searched reference lists of previous systematic reviews; and consulted additional experts. STUDY ELIGIBILITY AND CRITERIA: We included working-age (≥15 years) individuals in the formal and informal economy in any WHO and/or ILO Member State but excluded children (aged < 15 years) and unpaid domestic workers. We included randomized controlled trials, cohort studies, case-control studies and other non-randomized intervention studies with an estimate of the effect of exposure to long working hours (41-48, 49-54 and ≥55 h/week), compared with exposure to standard working hours (35-40 h/week), on stroke (prevalence, incidence or mortality). STUDY APPRAISAL AND SYNTHESIS METHODS: At least two review authors independently screened titles and abstracts against the eligibility criteria at a first review stage and full texts of potentially eligible records at a second stage, followed by extraction of data from qualifying studies. Missing data were requested from principal study authors. We combined relative risks using random-effects meta-analysis. Two or more review authors assessed the risk of bias, quality of evidence and strength of evidence, using the Navigation Guide and GRADE tools and approaches adapted to this project. RESULTS: Twenty-two studies (20 cohort studies, 2 case-control studies) met the inclusion criteria, comprising a total of 839,680 participants (364,616 females) in eight countries from three WHO regions (Americas, Europe, and Western Pacific). The exposure was measured using self-reports in all studies, and the outcome was assessed with administrative health records (13 studies), self-reported physician diagnosis (7 studies), direct diagnosis by a physician (1 study) or during a medical interview (1 study). The outcome was defined as an incident non-fatal stroke event in nine studies (7 cohort studies, 2 case-control studies), incident fatal stroke event in one cohort study and incident non-fatal or fatal ("mixed") event in 12 studies (all cohort studies). Cohort studies were judged to have a relatively low risk of bias; therefore, we prioritized evidence from these studies, but synthesised evidence from case-control studies as supporting evidence. For the bodies of evidence for both outcomes with any eligible studies (i.e. stroke incidence and mortality), we did not have serious concerns for risk of bias (at least for the cohort studies). Eligible studies were found on the effects of long working hours on stroke incidence and mortality, but not prevalence. Compared with working 35-40 h/week, we were uncertain about the effect on incidence of stroke due to working 41-48 h/week (relative risk (RR) 1.04, 95% confidence interval (CI) 0.94-1.14, 18 studies, 277,202 participants, I2 0%, low quality of evidence). There may have been an increased risk for acquiring stroke when working 49-54 h/week compared with 35-40 h/week (RR 1.13, 95% CI 1.00-1.28, 17 studies, 275,181participants, I2 0%, p 0.04, moderate quality of evidence). Compared with working 35-40 h/week, working ≥55 h/week may have led to a moderate, clinically meaningful increase in the risk of acquiring stroke, when followed up between one year and 20 years (RR 1.35, 95% CI 1.13 to 1.61, 7 studies, 162,644 participants, I2 3%, moderate quality of evidence). Compared with working 35-40 h/week, we were very uncertain about the effect on dying (mortality) of stroke due to working 41-48 h/week (RR 1.01, 95% CI 0.91-1.12, 12 studies, 265,937 participants, I2 0%, low quality of evidence), 49-54 h/week (RR 1.13, 95% CI 0.99-1.29, 11 studies, 256,129 participants, I2 0%, low quality of evidence) and 55 h/week (RR 1.08, 95% CI 0.89-1.31, 10 studies, 664,647 participants, I2 20%, low quality of evidence). Subgroup analyses found no evidence for differences by WHO region, age, sex, socioeconomic status and type of stroke. Sensitivity analyses found no differences by outcome definition (exclusively non-fatal or fatal versus "mixed") except for the comparison working ≥55 h/week versus 35-40 h/week for stroke incidence (p for subgroup differences: 0.05), risk of bias ("high"/"probably high" ratings in any domain versus "low"/"probably low" in all domains), effect estimate measures (risk versus hazard versus odds ratios) and comparator (exact versus approximate definition). CONCLUSIONS: We judged the existing bodies of evidence for human evidence as "inadequate evidence for harmfulness" for all exposure categories for stroke prevalence and mortality and for exposure to 41-48 h/week for stroke incidence. Evidence on exposure to 48-54 h/week and ≥55 h/week was judged as "limited evidence for harmfulness" and "sufficient evidence for harmfulness" for stroke incidence, respectively. Producing estimates for the burden of stroke attributable to exposures to working 48-54 and ≥55 h/week appears evidence-based, and the pooled effect estimates presented in this systematic review could be used as input data for the WHO/ILO Joint Estimates. PROTOCOL IDENTIFIER: https://doi.org/10.1016/j.envint.2018.06.016. PROSPERO REGISTRATION NUMBER: CRD42017060124.

Observational Surveillance Approach to Detect Novel Work-Related Diseases and Hazards: An Application to a Belgian Occupational Health and Safety Database.

OBJECTIVES: Rapid changes in working conditions give rise to new occupational health risks. We applied the Spectrosome approach, a network-based analysis, to investigate associations between disease and multiple occupational exposures. METHODS: We investigated work and health's associations in a specific sector: the agricultural sector and for a specific and frequent health complaint: sore throat; using PRECUBE dataset of the Belgian Occupational Health and Safety, containing 381.615 occupational health observations. We compared the results of the spectrosome with classic frequency analyses. RESULTS: Spectrosome approach reports more significant signals of multiple associations of agents compare to the frequency analysis. CONCLUSION: This difference justifies the usefulness of taking into account the multiplicity of causes leading to a health event, which is a clear asset of the Spectrosome method.

Job Demands, Job Resources, Burnout, Work Engagement, and Their Relationships: An Analysis Across Sectors.

OBJECTIVE: The aim of this study was to gain insight in the importance of job demands and resources and the validity of the Job Demands Resources Model across sectors. METHODS: We used one-way analyses of variance to examine mean differences, and multi-group Structural Equation Modeling analyses to test the strength of the relationships among job demands, resources, burnout, and work engagement across the health care, industry, service, and public sector. RESULTS: The four sectors differed in the experience of job demands, resources, burnout, and work engagement, but they did not vary in how (strongly) job demands and resources associated with burnout and work engagement. CONCLUSION: More attention is needed to decrease burnout and increase work engagement, particularly in industry, service, and the public sector. The Job Demands-Resources model may be helpful in this regard, as it is valid across sectors.

The Mixed Effects Trend Vector Model.

Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical displays representing change are obtained. The methodology can be applied to both nominal and ordinal response variables. Relationships to standard statistical models for multinomial data are presented. Several empirical examples are given to show the merits of the proposed modeling framework.

DISCO-SCA and properly applied GSVD as swinging methods to find common and distinctive processes.

BACKGROUND: In systems biology it is common to obtain for the same set of biological entities information from multiple sources. Examples include expression data for the same set of orthologous genes screened in different organisms and data on the same set of culture samples obtained with different high-throughput techniques. A major challenge is to find the important biological processes underlying the data and to disentangle therein processes common to all data sources and processes distinctive for a specific source. Recently, two promising simultaneous data integration methods have been proposed to attain this goal, namely generalized singular value decomposition (GSVD) and simultaneous component analysis with rotation to common and distinctive components (DISCO-SCA). RESULTS: Both theoretical analyses and applications to biologically relevant data show that: (1) straightforward applications of GSVD yield unsatisfactory results, (2) DISCO-SCA performs well, (3) provided proper pre-processing and algorithmic adaptations, GSVD reaches a performance level similar to that of DISCO-SCA, and (4) DISCO-SCA is directly generalizable to more than two data sources. The biological relevance of DISCO-SCA is illustrated with two applications. First, in a setting of comparative genomics, it is shown that DISCO-SCA recovers a common theme of cell cycle progression and a yeast-specific response to pheromones. The biological annotation was obtained by applying Gene Set Enrichment Analysis in an appropriate way. Second, in an application of DISCO-SCA to metabolomics data for Escherichia coli obtained with two different chemical analysis platforms, it is illustrated that the metabolites involved in some of the biological processes underlying the data are detected by one of the two platforms only; therefore, platforms for microbial metabolomics should be tailored to the biological question. CONCLUSIONS: Both DISCO-SCA and properly applied GSVD are promising integrative methods for finding common and distinctive processes in multisource data. Open source code for both methods is provided.