Work and non-work stressors, psychological distress and obesity: evidence from a 14-year study on Canadian workers
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate the contribution of work, non-work and individual factors to obesity with regard to gender-related differences, and to clarify the mediating role that psychological distress plays in these dynamics in Canada from 1994 to 2008 using the Canadian National Population Health Survey (NPHS). DESIGN: Longitudinal. SETTINGS: The NPHS is a randomised longitudinal cohort study with biennial interviews of the Canadian adult population from 18 to 64. PARTICIPANTS: 5925 non-obese workers in cycle 1 (49% were women). MEASUREMENTS: Obesity was measured using the body mass index (BMI), with a threshold of BMI >30 kg/m(2). BMI was corrected in accordance with the recommendations of Connor Gorber et al to adjust for gender bias in responses. RESULTS: Of the work characteristics evaluated, only decision authority was associated with obesity for women but not for men. Living as a couple, child-related strains, psychotropic drug use, hypertension, being physically inactive and low psychological distress were obesity risk factors but were not moderated by gender. Overall, psychological distress did not mediate the associations that work factors have on obesity. CONCLUSIONS: Our study suggests that men and women differ little in the extent to which work, non-work and individual factors predict obesity. However, for women, the level of decision authority is associated with a lower obesity risk. In addition, psychological distress did not mediate the contribution of work factors and actually seems, contrary to expectations, to decrease the obesity risk when work, non-work and individual factors are taken into account.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".