Sample description (N = 13695).

<p>Sample description (N = 13695).</p

Policy indicators.

<p>Note. ^a For the analyses, we followed previous procedures [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121573#pone.0121573.ref049" target="_blank">49</a>] and weighted measures (% of GDP) according to existing unemployment rates. This prevents the possibility that country's higher expenditures were simply related to higher levels of unemployment [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121573#pone.0121573.ref050" target="_blank">50</a>].</p><p>Policy indicators.</p

Predicted levels of work stress by education at different levels of policy indicators.

<p>Note. Expenditures into active (ALMP) and passive labour market policies (PLMP) are weighted by unemployment rate. Results are based on <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121573#pone.0121573.t004" target="_blank">Table 4</a>, model 2.</p

Educational differences in work stress (low vs. high education) and ALMP (expenditure into active labour market programmes).

<p>Note. Mean differences are adjusted for age, sex, self-employment and work time (based on <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121573#pone.0121573.t002" target="_blank">Table 2</a>). Expenditures into active labour market policies (ALMP) are based on % of GDP (weighted by unemployment rate).</p

Associations between education and work stress scores by country: Results of linear regression models (unstandardized regression coefficients and p-values).

<p>Note. All models are adjusted for sex, age groups, employment status and work time.</p><p>Associations between education and work stress scores by country: Results of linear regression models (unstandardized regression coefficients and p-values).</p

Association between policy indicators and work stress (model 1) and interactions between education and policy indicators (model 2): Results of random intercept linear multilevel regressions. Unstandardized regression coefficients (p-values).

<p>Note. All models are adjusted for sex, age groups, employment status and work time. Expenditures into active (ALMP) and passive labour market policies (PLMP) are weighted by unemployment rate.</p><p>Association between policy indicators and work stress (model 1) and interactions between education and policy indicators (model 2): Results of random intercept linear multilevel regressions. Unstandardized regression coefficients (p-values).</p

Adjusted Odds Ratios (95% CI) for the Association Between Job Strain and Diabetes (N = 44,818 in All Models), the IPD-Work Consortium, 1984–2003.

<p>Adjusted Odds Ratios (95% CI) for the Association Between Job Strain and Diabetes (N  =  44,818 in All Models), the IPD-Work Consortium, 1984–2003.</p

Participant Characteristics According to Study, the IPD-Work Consortium, 1984–2003.

<p>Participant Characteristics According to Study, the IPD-Work Consortium, 1984–2003.</p

Participant and study summary.

<p>SD: standard deviation.</p>1<p>Study acronyms: DWECS: Danish Work Environment Cohort Study; FPS: Finnish Public Sector Study; HeSSup: Health and Social Support; HNR: Heinz Nixdorf Recall study; IPAW: Intervention Project on Absence and Well-being; POLS: Permanent Onderzoek Leefsituatie; PUMA: Burnout, Motivation and Job Satisfaction study; WOLF: Work Lipids and Fibrinogen. ² Participants with complete data on job strain, age, sex and socioeconomic position.</p>2<p>Moderate drinking (women: 1–14 drinks/week, men: 1–21 drinks/week); intermediate drinking (women: 15–20 drinks/week, men: 22–27 drinks/week); heavy drinking (women: > = 21 drinks/wk, men: > = 28 drinks/week).</p

Longitudinal associations between job strain and reducing alcohol intake to moderate or no alcohol, among baseline excessive drinkers (n = 4 981)¹².

1<p>Excessive drinker: an individual who drinks more than recommended amounts of alcohol (intermediate or heavy drinker).</p>2<p>Studies and follow-up times: Belstress (4–7 years), FPS (2–4 years), HeSSup (5 years) and Whitehall II (3–9 years.).</p>3<p>Odds ratios (ORs) from a mixed effects logistic model, adjusted for baseline age, sex and baseline socioeconomic position, with study as the random effect.</p