Socioeconomic patterns of obesity in Canada: modeling the role of health behaviour
Bibliographic record
Abstract
Among Canadians, previous research has associated obesity with indicators of socioeconomic position. Several health behaviours have demonstrated similar variation, suggesting that social patterning of obesity may be partially explained by behavioural differences. The objective of this study was to examine obesity in relation to income and education among Canadians, and to characterize the indirect associations potentially occurring through fruit and vegetable intake, leisure-time physical activity (LTPA), and smoking. The present secondary analysis of the 2004 Canadian Community Health Survey was restricted to adults (25-64 y) with measured height and weight data (men, n = 3767; women, n = 3823). Interrelationships among socioeconomic indicators, behaviours, and BMI groups were examined by age-adjusted path analysis. For men, obesity was positively associated with income directly and through current smoking. Obesity was also negatively associated with education, directly and through fruit and vegetable intake, and was negatively associated with income through LTPA (r2 = 0.17). For women, obesity was negatively associated with education both directly and indirectly through LTPA and with fruit and vegetable intake. No direct association was observed between income and obesity for women, but an indirect negative association existed via LTPA and fruit and vegetable intake (r2 = 0.15). The direct and indirect associations between obesity and socioeconomic indicators were consistently inverse among women, but this relationship was not the case in men, suggesting that clearer social patterns of adiposity exist for Canadian women. The limited amount of variance explained by these models likely reflects the complexity of obesity development.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".