Synergy of BMI and family history on diabetes: the Humboldt Study
Bibliographic record
Abstract
OBJECTIVE: To examine the joint effect of family history and BMI on diabetes. DESIGN: Cross-sectional study. SETTING: A rural community in Saskatchewan, Canada. SUBJECTS: The analysis was based on data from 2081 adults, 18-79 years of age, who participated in the Humboldt Study conducted in 2003. Doctor-diagnosed diabetes and family history of diabetes of biological parents and siblings were self-reported. Body weight and height were objectively measured. The interaction of family history and BMI on diabetes was assessed on an additive scale. RESULTS: The prevalence of diabetes was 7.9 %, and BMI and history of diabetes were two important predictors. The adjusted prevalence ratios were 1.76 (95 % CI 1.37, 2.27) and 2.59 (95 % CI 2.05, 3.31) for those with a BMI of 25.0-29.9 kg/m2 and of at least 30 kg/m2, respectively, compared with a BMI of less than 25 kg/m2, and was 2.41 (95 % CI 2.08, 2.80) for those with a family history of diabetes v. those without. The data indicated an additive interaction of family history and BMI on diabetes. CONCLUSIONS: When exposed to both family history and overweight/obesity, individuals would have an increased risk that was greater than the sum of their single effects. Reduction of BMI would also reduce the risk of diabetes associated family history.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".