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Objectives The study aims to explore the prospective associations of the psychosocial work exposures of the job strain model with cardiovascular mortality, including mortality for ischemic heart diseases (IHD) and stroke, using various time-varying exposure measures in the French working population of employees. Methods The study was based on a cohort of 798 547 men and 697 785 women for which job history data from 1976 to 2002 were linked to mortality data and causes of death from the national death registry. Psychosocial work exposures from the validated job strain model questionnaire were assessed using a job-exposure matrix (JEM). Three time-varying measures of exposure were studied: current, cumulative, and recency-weighted cumulative exposure. Cox proportional hazards models were used to examine the associations between psychosocial work exposures and cardiovascular mortality. Results Within the 1976-2002 period, there were 19 264 cardiovascular deaths among men and 6181 among women. Low decision latitude, low social support, job strain, iso-strain, passive job, and high strain were associated with cardiovascular mortality. Most of these associations were also observed for IHD and stroke mortality. The comparison between the different exposure measures suggested that current exposure may be more important than cumulative (or past) exposure. The population fractions of cardiovascular mortality attributable to job strain were 5.64% for men and 6.44% for women. Conclusions Psychosocial work exposures of the job strain model may play a role in cardiovascular mortality. The estimated burden of cardiovascular mortality associated with these exposures underlines the need for preventive policies oriented toward the psychosocial work environment.

Introduction Although evidence has been provided on the associations between psychosocial work exposures and morbidity outcomes in the literature, knowledge appears much more sparse on mortality outcomes. The objective of STRESSJEM is to explore the prospective associations between psychosocial work exposures and mortality outcomes among the national French working population. In this paper, we describe the study protocol, study population, data sources, method for exposure assessment, data analysis and future plans. Methods and analysis Data sources will include: the data from the national SUMER survey from DARES on the evaluation of psychosocial work exposures and the data from the COSMOP programme from Santé publique France linking job history (DADS data from INSEE) and mortality according to causes of death (data from the national death registry, INSERM-CépiDc). A sample of 1 511 456 individuals will form the studied prospective cohort for which data are available on both job history and mortality over the period 1976–2002. Psychosocial work exposures will be imputed via a job-exposure matrix using three job title variables that are available in both the SUMER and COSMOP data sets. Our objectives will be to study the associations between various psychosocial work exposures and mortality outcomes. Psychosocial work exposures will include the job strain model factors as well as other psychosocial work factors. Various measures of exposure over time will be used. All-cause and cause-specific mortality will be studied. Ethics and dissemination Both the SUMER survey and the COSMOP programme have been approved by French ethics committees. Dissemination of the study results will include a series of international peer-reviewed papers and at least one paper in French. The results will be presented in national and international conferences. This project will offer a unique opportunity to explore mortality outcomes in association with psychosocial work exposures in a large

Objectives This review aimed to quantify suicide risk among agricultural, forestry, and fishery workers and study potential variations of risk within this population. Methods We conducted a systematic literature review and meta-analysis from 1995 to 2016 using MEDLINE and following the PRISMA guidelines. A pooled effect size of suicide risk among the population of interest was calculated using meta-analysis. Subgroup analyses were conducted to investigate whether effect size differed according to population or study characteristics. Meta-regression was used to identify sources of heterogeneity. Results The systematic review identified 65 studies, of which 32 were included in the meta-analysis. Pooled effect size was 1.48 [95% confidence interval (CI) 1.30–1.68] representing an excess of suicide risk among the population of interest. Subgroup analysis showed that this effect size varied according to geographic area, with a higher effect size in Japan. The following study characteristics were found to contribute to the between-study variance: reference group, measure of effect size, and study design. Conclusions Our findings suggest an excess of suicide risk among agricultural, forestry, and fishery workers and demonstrated that this excess may be even higher for these groups in Japan. This review highlights the need for suicide prevention policies focusing on this specific population of workers. More research is also needed to better understand the underlying factors that may increase suicide risk in this population.

Background: Adverse psychosocial working environments characterized by job strain (the combination of high demands and low control at work) are associated with an increased risk of depressive symptoms among employees, but evidence on clinically diagnosed depression is scarce. We examined job strain as a risk factor for clinical depression. Method: We identified published cohort studies from a systematic literature search in PubMed and PsycNET and obtained 14 cohort studies with unpublished individual-level data from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium. Summary estimates of the association were obtained using random-effects models. Individual-level data analyses were based on a pre-published study protocol. Results: We included six published studies with a total of 27 461 individuals and 914 incident cases of clinical depression. From unpublished datasets we included 120 221 individuals and 982 first episodes of hospital-treated clinical depression. Job strain was associated with an increased risk of clinical depression in both published [relative risk (RR) = 1.77, 95% confidence interval (CI) 1.47–2.13] and unpublished datasets (RR = 1.27, 95% CI 1.04–1.55). Further individual participant analyses showed a similar association across sociodemographic subgroups and after excluding individuals with baseline somatic disease. The association was unchanged when excluding individuals with baseline depressive symptoms (RR = 1.25, 95% CI 0.94–1.65), but attenuated on adjustment for a continuous depressive symptoms score (RR = 1.03, 95% CI 0.81–1.32). Conclusions: Job strain may precipitate clinical depression among employees. Future intervention studies should test whether job strain is a modifiable risk factor for depression.

OBJECTIVE: Previous research suggests that psychosocial job stressors may be plausible risk factors for suicide. This study assessed the relationship between psychosocial job stressors and suicide mortality across the Australian population. METHODS: We developed a job exposure matrix to objectively measure job stressors across the working population. Suicide data came from a nationwide coronial register. Living controls were selected from a nationally representative cohort study. Incidence density sampling was used to ensure that controls were sampled at the time of death of each case. The period of observation for both cases and controls was 2001 to 2012. We used multilevel logistic regression to assess the odds of suicide in relation to 2 psychosocial job stressors (job control and job demands), after matching for age, sex, and year of death/survey and adjusting for socioeconomic status. RESULTS: Across 9,010 cases and 14,007 matched controls, our results suggest that low job control (odds ratio [OR], 1.35; 95% confidence interval [CI], 1.26-1.44; p < .001) and high job demands (OR, 1.36; 95% CI, 1.26-1.46; p < .001) were associated with increased odds of male suicide after adjusting for socioeconomic status. High demands were associated with lower odds of female suicide (OR, 0.81; 95% CI, 0.72-0.92; p = .002). CONCLUSIONS: It seems that adverse experiences at work are a risk factor for male suicide while not being associated with an elevated risk among females. Future studies on job stressors and suicide are needed, both to further understand the biobehavioral mechanisms explaining the link between job stress and suicide, and to inform targeted prevention initiatives.

BACKGROUND: Adverse psychosocial working environments characterized by job strain (the combination of high demands and low control at work) are associated with an increased risk of depressive symptoms among employees, but evidence on clinically diagnosed depression is scarce. We examined job strain as a risk factor for clinical depression.METHOD: We identified published cohort studies from a systematic literature search in PubMed and PsycNET and obtained 14 cohort studies with unpublished individual-level data from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium. Summary estimates of the association were obtained using random-effects models. Individual-level data analyses were based on a pre-published study protocol.RESULTS: We included six published studies with a total of 27 461 individuals and 914 incident cases of clinical depression. From unpublished datasets we included 120 221 individuals and 982 first episodes of hospital-treated clinical depression. Job strain was associated with an increased risk of clinical depression in both published [relative risk (RR) = 1.77, 95% confidence interval (CI) 1.47-2.13] and unpublished datasets (RR = 1.27, 95% CI 1.04-1.55). Further individual participant analyses showed a similar association across sociodemographic subgroups and after excluding individuals with baseline somatic disease. The association was unchanged when excluding individuals with baseline depressive symptoms (RR = 1.25, 95% CI 0.94-1.65), but attenuated on adjustment for a continuous depressive symptoms score (RR = 1.03, 95% CI 0.81-1.32).CONCLUSIONS: Job strain may precipitate clinical depression among employees. Future intervention studies should test whether job strain is a modifiable risk factor for depression.

Introduction A Job Exposure Matrix (JEM) for psychosocial job stressors allows assessment of these exposures at a population level. JEMs are particularly useful in situations when information on psychosocial job stressors were not collected individually and can help eliminate the biases that may be present in individual self-report accounts. This research paper describes the development of a JEM in the Australian context. Methods The Household Income Labour Dynamics in Australia (HILDA) survey was used to construct a JEM for job control, job demands and complexity, job insecurity, and fairness of pay. Population median values of these variables for all employed people (n = 20,428) were used to define individual exposures across the period 2001 to 2012. The JEM was calculated for the Australian and New Zealand Standard Classification of Occupations (ANZSCO) at the four-digit level, which represents 358 occupations. Both continuous and binary exposures to job stressors were calculated at the 4-digit level. We assessed concordance between the JEM-assigned and individually-reported exposures using the Kappa statistic, sensitivity and specificity assessments. We conducted regression analysis using mental health as an outcome measure. Results Kappa statistics indicate good agreement between individually-reported and JEM-assigned dichotomous measures for job demands and control, and moderate agreement for job insecurity and fairness of pay. Job control, job demands and security had the highest sensitivity, while specificity was relatively high for the four exposures. Regression analysis shows that most individually reported and JEM measures were significantly associated with mental health, and individually-reported exposures produced much stronger effects on mental health than the JEM-assigned exposures. Discussion These JEM-based estimates of stressors exposure provide a conservative proxy fo

INTRODUCTION: A Job Exposure Matrix (JEM) for psychosocial job stressors allows assessment of these exposures at a population level. JEMs are particularly useful in situations when information on psychosocial job stressors were not collected individually and can help eliminate the biases that may be present in individual self-report accounts. This research paper describes the development of a JEM in the Australian context. METHODS: The Household Income Labour Dynamics in Australia (HILDA) survey was used to construct a JEM for job control, job demands and complexity, job insecurity, and fairness of pay. Population median values of these variables for all employed people (n = 20,428) were used to define individual exposures across the period 2001 to 2012. The JEM was calculated for the Australian and New Zealand Standard Classification of Occupations (ANZSCO) at the four-digit level, which represents 358 occupations. Both continuous and binary exposures to job stressors were calculated at the 4-digit level. We assessed concordance between the JEM-assigned and individually-reported exposures using the Kappa statistic, sensitivity and specificity assessments. We conducted regression analysis using mental health as an outcome measure. RESULTS: Kappa statistics indicate good agreement between individually-reported and JEM-assigned dichotomous measures for job demands and control, and moderate agreement for job insecurity and fairness of pay. Job control, job demands and security had the highest sensitivity, while specificity was relatively high for the four exposures. Regression analysis shows that most individually reported and JEM measures were significantly associated with mental health, and individually-reported exposures produced much stronger effects on mental health than the JEM-assigned exposures. DISCUSSION: These JEM-based estimates of stressors exposure provide a conservative proxy for individual-level data, and can be applied to a range of health and organisa