The psychosocial work environment and incident diabetes in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Relatively few longitudinal studies have explored the relationship between psychosocial work conditions and diabetes incidence. Given the increasing global burden of diabetes this is an important area for public health research. AIMS: To examine the relationships between dimensions of the psychosocial work environment on the subsequent incidence of diabetes among men and women in Ontario, Canada over a 9 year period. METHODS: We used data from Ontario respondents (35 to 60 years of age) to the 2000-01 Canadian Community Health Survey linked to the Ontario Health Insurance Plan database for physician services and the Canadian Institute for Health Information Discharge Abstract Database for hospital admissions. Our sample of actively employed labour market participants with no previous diagnoses for diabetes was followed for a 9 year period to ascertain incident diabetes. RESULTS: There were 7443 participants. Low levels of job control were associated with an increased risk of diabetes among women, but not among men. Counter to our hypotheses high levels of social support were also associated with increased diabetes risk among women, but not among men. No relationship was found between any psychosocial work measure and risk of diabetes among men. CONCLUSIONS: Given the increasing prevalence of diabetes worldwide, job control could potentially be an import ant modifiable risk factor to reduce the incidence of diabetes among female, but not among male, workers. More research is needed to understand the pathways through which low social support may protect against the development of diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".