Body mass index trajectories among the Canadian workforce and their association with work environment trajectories over 17 years
Bibliographic record
Abstract
OBJECTIVE: To determine the number of latent body mass index (BMI) trajectories from 1994 to 2010 among working Canadians and their association with concurrent trajectories in work environment exposures. METHODS: were used. Group-based trajectory modelling was used to determine the number of latent BMI trajectories and concurrent psychosocial work environment trajectories. A multinomial logistic regression of BMI trajectory membership on trajectories in work environment dimensions (skill discretion, decision latitude, psychological demands, job insecurity, social support, physical exertion) was then explored. RESULTS: ) over the 17-year period. A higher decision authority trajectory was associated with lower odds of belonging to the overweight and obese trajectories when compared with the normal weight trajectory. A decreasing physical exertion trajectory was associated with higher odds of belonging to the very obese trajectory when compared with the normal weight trajectory. CONCLUSIONS: Four BMI trajectories are present in the Canadian workforce; all trajectories saw increased body weight over time. Declining physical exertion and lower decision authority in the work environment over time is associated with increased likelihood of being in overweight and obese trajectories.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".