Population‐Based Analysis of Obesity and Workforce Participation
Bibliographic record
Abstract
OBJECTIVE: To describe the relationship between obesity class and workforce participation and the influence of demographic, socioeconomic, and comorbid disease states on this relationship using population-based Canadian data. RESEARCH METHODS AND PROCEDURES: Responses from 73,531 adults surveyed in the Canadian Community Health Survey 2000 to 2001 who provided complete information regarding variables of interest were analyzed. Workforce participation was defined as individuals reporting that they held and were present at a job or business in the week before survey administration. The association between obesity and workforce participation was explored using logistic regression after adjusting for demographic, socioeconomic, and obesity-related comorbidities. RESULTS: In univariate analysis, obese individuals had lower odds of participating in the workforce. In the fully adjusted model, increasing obesity was associated with decreasing odds of workforce participation, with Class I, II, and III obesity having odds ratios (95% confidence interval) of 0.94 (0.89 to 0.99), 0.85 (0.77 to 0.94), and 0.66 (0.57 to 0.78), respectively. Obese individuals were also less likely to be employed and more likely to be absent from work. DISCUSSION: Obesity is associated with lower workforce participation. This association appears to be independent of associated comorbidity and sociodemographic factors. These results indicate that the economic impact of obesity alone on workforce productivity is larger than previous reports suggest.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".