Associations of job strain and lifestyle risk factors with risk of coronary artery disease: a meta-analysis of individual participant data
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Bibliographic record
Abstract
BACKGROUND: It is unclear whether a healthy lifestyle mitigates the adverse effects of job strain on coronary artery disease. We examined the associations of job strain and lifestyle risk factors with the risk of coronary artery disease. METHODS: We pooled individual-level data from 7 cohort studies comprising 102 128 men and women who were free of existing coronary artery disease at baseline (1985-2000). Questionnaires were used to measure job strain (yes v. no) and 4 lifestyle risk factors: current smoking, physical inactivity, heavy drinking and obesity. We grouped participants into 3 lifestyle categories: healthy (no lifestyle risk factors), moderately unhealthy (1 risk factor) and unhealthy (2-4 risk factors). The primary outcome was incident coronary artery disease (defined as first nonfatal myocardial infarction or cardiac-related death). RESULTS: There were 1086 incident events in 743,948 person-years at risk during a mean follow-up of 7.3 years. The risk of coronary artery disease among people who had an unhealthy lifestyle compared with those who had a healthy lifestyle (hazard ratio [HR] 2.55, 95% confidence interval [CI] 2.18-2.98; population attributable risk 26.4%) was higher than the risk among participants who had job strain compared with those who had no job strain (HR 1.25, 95% CI 1.06-1.47; population attributable risk 3.8%). The 10-year incidence of coronary artery disease among participants with job strain and a healthy lifestyle (14.7 per 1000) was 53% lower than the incidence among those with job strain and an unhealthy lifestyle (31.2 per 1000). INTERPRETATION: The risk of coronary artery disease was highest among participants who reported job strain and an unhealthy lifestyle; those with job strain and a healthy lifestyle had half the rate of disease. A healthy lifestyle may substantially reduce disease risk among people with job strain.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it