POPULATION INCREASES IN OBESITY APPEAR TO BE PARTLY DUE TO GENETICS
Bibliographic record
Abstract
Studies have documented substantial increases in obesity throughout most of the industrialized world in recent decades. The majority of explanations for these increases have centred around environmental factors such as the increasing availability of high-fat, high-carbohydrate foods and sedentary lifestyles. This study sought to determine if genetic factors might be contributing to the increases in the proportions of North Americans who are obese and overweight. The body mass index (BMI) for a large sample of two generations of United States and Canadian subjects was correlated with family fertility indicators. Small but highly significant positive correlations were found between the BMIs of family members and their reproduction rates, especially in the case of women. For instance, mothers in the sample (most of whom were born in the 1940s and 50s) who were in the normal or below normal range had an average of 4.3 siblings and 3.2 children, compared with 4.8 siblings and 3.5 children for mothers who were overweight or obese. When combined with evidence from twin and adoption studies indicating that genes make substantial contributions to obesity, this study suggests that recent increases in obesity are partially the result of overweight and obese women having more children than is true for average and underweight women. It is speculated that improvements in medical treatments for conditions associated with obesity--particularly diabetes and heart disease--are making it possible for overweight women to live longer and to be more fertile than was true historically.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".