Familial Risk of Overweight and Obesity in the Canadian Population using the WHO/NIH Criteria
Bibliographic record
Abstract
OBJECTIVE: To determine the familial risk of overweight and obesity in Canada. RESEARCH METHODS AND PROCEDURES: The sample was comprised of 15,245 participants from 6377 families of the Canada Fitness Survey. The risk of overweight and obesity among spouses and first-degree relatives of individuals classified as underweight, normal weight, pre-obese, or obese (Class I and II) according to the WHO/NIH guidelines for body mass index (BMI) was determined using standardized risk ratios. RESULTS: Spouses and first-degree relatives of underweight individuals have a lower risk of overweight and obesity than the general population. On the other hand, the risk of Class I and Class II obesity (BMI 35 to 39.9 kg/m2) in relatives of Class I obese (BMI 30 to 34.9 kg/m2) individuals was 1.84 (95% CI: 1.27, 2.37) and 1.97 (95% CI: 0.67, 3.25), respectively, in spouses, and 1.44 (95% CI:1.10, 1.78) and 2.05 (95% CI: 1.37, 2.73), respectively in first-degree relatives. Further, the risk of Class II obesity in spouses and first-degree relatives of Class II obese individuals was 2.59 (95% CI: -0.91, 6.09) and 7.07 (95% CI: 1.48, 12.66) times the general population risk, respectively. DISCUSSION: There is significant familial risk of overweight and obesity in the Canadian population using the BMI as an indicator. Comparison of risks among spouses and first-degree relatives suggests that genetic factors may play a role in obesity at more extreme levels (Class II obese) more so than in moderate obesity.
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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 | 0.002 | 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 | 0.000 |
| 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".