Job Strain, Overweight, and Diabetes: A 13-Year Prospective Study Among 12,896 Men and Women in Ontario
Bibliographic record
Abstract
OBJECTIVE: The American Diabetes Association recently called for research on social and environmental determinants of diabetes to intensify primary prevention. Recent epidemiological evidence suggests that frequent and modifiable psychosocial stressors at work might contribute to the development of diabetes, but more prospective studies are needed. We evaluated the relationship between job strain and diabetes incidence in 12,896 workers followed up over a 13-year period in Ontario, Canada. We also examined the modifying effect of body mass index in this relationship. METHODS: Data from Ontario respondents (35-74 years of age) to the 2000-2001, 2002, and 2003 cycles of the Canadian Community Health Survey were prospectively linked to the Ontario Health Insurance Plan database for physician services and the Canadian Institute for Health Information Discharge Abstract Database for hospital admissions. The sample consisted of actively employed participants with no previous diagnosis for diabetes. Cox proportional hazard regression models were performed to evaluate the relationship between job strain, obesity, and the incidence of diabetes. RESULTS: Overall, job strain was not associated with the incidence of diabetes (hazard ratio [HR] = 1.05; 95% confidence interval [CI] = 0.83-1.34). Among women, job strain was associated with an elevated risk of diabetes, although this finding did not reach statistical significance (HR = 1.36; 95% CI = 0.94-1.96). Among men, no association was observed (HR = 0.89; 95% CI = 0.65-1.22). Also, job strain increased the risk of diabetes among women with obesity (HR = 1.88; 95% CI = 1.14-3.08), whereas these stressors reduced the risk among men with obesity (HR = 0.58; 95% CI = 0.36-0.95). CONCLUSIONS: The current study suggests that lowering job strain might be an effective strategy for preventing diabetes among women, especially the high-risk group comprising women with obesity.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".