CUMULATIVE EXPOSURE TO JOB STRAIN AND PREDIABETES AMONG MALE AND FEMALE WHITE-COLLAR WORKERS
Bibliographic record
Abstract
Objective: Previous literature suggests an association between psychosocial stressors at work (PSWs) and the risk of type 2 diabetes mellitus (T2DM). According to the demand-control model, the combination of high psychological demands at work and low levels of control is called job strain, which increases the risk of T2DM. Prediabetes greatly increases the risk of developing T2DM and is also independently associated with an increased mortality risk. However, the evidence regarding the association between PSWs and prediabetes is scarce. The objective of this study is to clarify the relationship between cumulative exposure to PSWs, defined according to the demandcontrol model, and both prediabetes prevalence in a longitudinal cohort. Design and method: Over 9000 white-collar workers (48.5% female) were recruited in 1991–1993 and were followed up 8 and 24 years later. Workers exposed to job strain at baseline and at the 8- year follow-up were considered exposed to chronic job strain. Glycated hemoglobin (HbA1c) was measured at the 24-year follow-up in 1461 workers and was used to measure prediabetes prevalence. Odds ratios (ORs) were computed using multiple logistic regressions which were adjusted for potential confounding factors. Results: In female workers, chronic job strain was associated more than twice the odds of prediabetes (OR = 2.21, 95% CI 1.05–4.67) compared to unexposed workers, even after adjusting for sociodemographic factors and lifestyle habits. There was no association between job strain and prediabetes in male workers. Conclusion: Our results suggest that PSWs, when they are measured with the demand-control model, are associated with an increased prediabetes prevalence. Given the increasing burden of disease of prediabetes and T2DM in Canada and in other developed countries, addressing these frequent and modifiable occupational factors could improve the health of Canadian workers, especially female workers. Therefore, workplace interventions that aim to decrease adverse PSWs should be considered to reduce glucose metabolism imbalances at the population level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".