SummaryBackgroundPublished work assessing psychosocial stress (job strain) as a risk factor for coronary heart disease is inconsistent and subject to publication bias and reverse causation bias. We analysed the relation between job strain and coronary heart disease with a meta-analysis of published and unpublished studies.MethodsWe used individual records from 13 European cohort studies (1985–2006) of men and women without coronary heart disease who were employed at time of baseline assessment. We measured job strain with questions from validated job-content and demand-control questionnaires. We extracted data in two stages such that acquisition and harmonisation of job strain measure and covariables occurred before linkage to records for coronary heart disease. We defined incident coronary heart disease as the first non-fatal myocardial infarction or coronary death.Findings30 214 (15%) of 197 473 participants reported job strain. In 1·49 million person-years at risk (mean follow-up 7·5 years [SD 1·7]), we recorded 2358 events of incident coronary heart disease. After adjustment for sex and age, the hazard ratio for job strain versus no job strain was 1·23 (95% CI 1·10–1·37). This effect estimate was higher in published (1·43, 1·15–1·77) than unpublished (1·16, 1·02–1·32) studies. Hazard ratios were likewise raised in analyses addressing reverse causality by exclusion of events of coronary heart disease that occurred in the first 3 years (1·31, 1·15–1·48) and 5 years (1·30, 1·13–1·50) of follow-up. We noted an association between job strain and coronary heart disease for sex, age groups, socioeconomic strata, and region, and after adjustments for socioeconomic status, and lifestyle and conventional risk factors. The population attributable risk for job strain was 3·4%.InterpretationOur findings suggest that prevention of workplace stress might decrease disease incidence; however, this strategy would have a much smaller effect than would tackling of standard risk factors, such as smoking.FundingFinnish Work Environment Fund, the Academy of Finland, the Swedish Research Council for Working Life and Social Research, the German Social Accident Insurance, the Danish National Research Centre for the Working Environment, the BUPA Foundation, the Ministry of Social Affairs and Employment, the Medical Research Council, the Wellcome Trust, and the US National Institutes of Health.

BackgroundAdverse 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.MethodWe 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.ResultsWe 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).ConclusionsJob strain may precipitate clinical depression among employees. Future intervention studies should test whether job strain is a modifiable risk factor for depression.

The objective of this study was to review and summarise the published evidence for an association between circulating concentrations of C reactive protein (CRP) and cancer through a systematic review. 90 discrete studies were identified. 81 (90%) were prevalent case-control or cross-sectional studies, and only 9 studies had a prospective design. In most prevalent studies, CRP concentrations were found to be higher in patients with cancer than in healthy controls or controls with benign conditions. Of the nine large prospective studies identified in this review, four reported no relationship between circulating CRP levels and breast, prostate or colorectal cancers, and five studies found that CRP was associated with colorectal or lung cancers. Most of the studies evaluating CRP as a diagnostic marker of cancer did not present relevant statistical analyses. Furthermore, any association reported in the prevalent studies might reflect reverse causation, survival bias or confounding. The prospective studies provided no strong evidence for a causal role of CRP in cancer. Instead of further prevalent studies, more large prospective studies and CRP gene-cancer association studies would be valuable in investigating the role of CRP in cancer.

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Unfavorable work characteristics, such as low job control and too high or too low job demands, have been suggested to increase the likelihood of physical inactivity during leisure time, but this has not been verified in large-scale studies. The authors combined individual-level data from 14 European cohort studies (baseline years from 1985–1988 to 2006–2008) to examine the association between unfavorable work characteristics and leisure-time physical inactivity in a total of 170,162 employees (50% women; mean age, 43.5 years). Of these employees, 56,735 were reexamined after 2–9 years. In cross-sectional analyses, the odds for physical inactivity were 26% higher (odds ratio = 1.26, 95% confidence interval: 1.15, 1.38) for employees with high-strain jobs (low control/high demands) and 21% higher (odds ratio = 1.21, 95% confidence interval: 1.11, 1.31) for those with passive jobs (low control/low demands) compared with employees in low-strain jobs (high control/low demands). In prospective analyses restricted to physically active participants, the odds of becoming physically inactive during follow-up were 21% and 20% higher for those with high-strain (odds ratio = 1.21, 95% confidence interval: 1.11, 1.32) and passive (odds ratio = 1.20, 95% confidence interval: 1.11, 1.30) jobs at baseline. These data suggest that unfavorable work characteristics may have a spillover effect on leisure-time physical activity.

The authors aggregated the results of observational studies examining the association between long working hours and coronary heart disease (CHD). Data sources used were MEDLINE (through January 19, 2011) and Web of Science (through March 14, 2011). Two investigators independently extracted results from eligible studies. Heterogeneity between the studies was assessed using the I2 statistic, and the possibility of publication bias was assessed using the funnel plot and Egger's test for small-study effects. Twelve studies were identified (7 case-control, 4 prospective, and 1 cross-sectional). For a total of 22,518 participants (2,313 CHD cases), the minimally adjusted relative risk of CHD for long working hours was 1.80 (95% confidence interval (CI): 1.42, 2.29), and in the maximally (multivariate-) adjusted analysis the relative risk was 1.59 (95% CI: 1.23, 2.07). The 4 prospective studies produced a relative risk of 1.39 (95% CI: 1.12, 1.72), while the corresponding relative risk in the 7 case-control studies was 2.43 (95% CI: 1.81, 3.26). Little evidence of publication bias but relatively large heterogeneity was observed. Studies varied in size, design, measurement of exposure and outcome, and adjustments. In conclusion, results from prospective observational studies suggest an approximately 40% excess risk of CHD in employees working long hours.

OBJECTIVEThe status of psychosocial stress at work as a risk factor for type 2 diabetes is unclear because existing evidence is based on small studies and is subject to confounding by lifestyle factors, such as obesity and physical inactivity. This collaborative study examined whether stress at work, defined as “job strain,” is associated with incident type 2 diabetes independent of lifestyle factors.RESEARCH DESIGN AND METHODSWe extracted individual-level data for 124,808 diabetes-free adults from 13 European cohort studies participating in the IPD-Work Consortium. We measured job strain with baseline questionnaires. Incident type 2 diabetes at follow-up was ascertained using national health registers, clinical screening, and self-reports. We analyzed data for each study using Cox regression and pooled the study-specific estimates in fixed-effect meta-analyses.RESULTSThere were 3,703 cases of incident diabetes during a mean follow-up of 10.3 years. After adjustment for age, sex, and socioeconomic status (SES), the hazard ratio (HR) for job strain compared with no job strain was 1.15 (95% CI 1.06–1.25) with no difference between men and women (1.19 [1.06–1.34] and 1.13 [1.00–1.28], respectively). In stratified analyses, job strain was associated with an increased risk of diabetes among those with healthy and unhealthy lifestyle habits. In a multivariable model adjusted for age, sex, SES, and lifestyle habits, the HR was 1.11 (1.00–1.23).CONCLUSIONSFindings from a large pan-European dataset suggest that job strain is a risk factor for type 2 diabetes in men and women independent of lifestyle factors.

SummaryBackgroundObesity increases the risk of several chronic diseases, but the extent to which the obesity-related loss of disease-free years varies by lifestyle category and across socioeconomic groups is unclear. We estimated the number of years free from major non-communicable diseases in adults who are overweight and obese, compared with those who are normal weight.MethodsWe pooled individual-level data on body-mass index (BMI) and non-communicable diseases from men and women with no initial evidence of these diseases in European cohort studies from the Individual-Participant-Data Meta-Analysis in Working Populations consortium. BMI was assessed at baseline (1991–2008) and non-communicable diseases (incident type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease) were ascertained via linkage to records from national health registries, repeated medical examinations, or self-report. Disease-free years from age 40 years to 75 years associated with underweight (BMI <18·5 kg/m2), overweight (≥25 kg/m2 to <30 kg/m2), and obesity (class I [mild] ≥30 kg/m2 to <35 kg/m2; class II–III [severe] ≥35 kg/m2) compared with normal weight (≥18·5 kg/m2 to <25 kg/m2) were estimated.FindingsOf 137 503 participants from ten studies, we excluded 6973 owing to missing data and 10 349 with prevalent disease at baseline, resulting in an analytic sample of 120 181 participants. Of 47 127 men, 211 (0·4%) were underweight, 21 468 (45·6%) normal weight, 20 738 (44·0%) overweight, 3982 (8·4%) class I obese, and 728 (1·5%) class II–III obese. The corresponding numbers among the 73 054 women were 1493 (2·0%), 44 760 (61·3%), 19 553 (26·8%), 5670 (7·8%), and 1578 (2·2%), respectively. During 1 328 873 person-years at risk (mean follow-up 11·5 years [range 6·3–18·6]), 8159 men and 8100 women developed at least one non-communicable disease. Between 40 years and 75 years, the estimated number of disease-free years was 29·3 (95% CI 28·8–29·8) in normal-weight men and 29·4 (28·7–30·0) in normal-weight women. Compared with normal weight, the loss of disease-free years in men was 1·8 (95% CI −1·3 to 4·9) for underweight, 1·1 (0·7 to 1·5) for overweight, 3·9 (2·9 to 4·9) for class I obese, and 8·5 (7·1 to 9·8) for class II–III obese. The corresponding estimates for women were 0·0 (−1·4 to 1·4) for underweight, 1·1 (0·6 to 1·5) for overweight, 2·7 (1·5 to 3·9) for class I obese, and 7·3 (6·1 to 8·6) for class II–III obese. The loss of disease-free years associated with class II–III obesity varied between 7·1 and 10·0 years in subgroups of participants of different socioeconomic level, physical activity level, and smoking habit.InterpretationMild obesity was associated with the loss of one in ten, and severe obesity the loss of one in four potential disease-free years during middle and later adulthood. This increasing loss of disease-free years as obesity becomes more severe occurred in both sexes, among smokers and non-smokers, the physically active and inactive, and across the socioeconomic hiera...