The Bigger the Healthier: Are the Limits of BMI Risk Changing Over Time?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The body mass index (BMI) is often used as a predictor of overweight and obesity. There is, however, an important debate among international specialists as to what the risk limits should be, and where the cut-off points should be located. In the United States, for instance, adults with a BMI between 25 and 30 are considered overweight, while adults with a BMI of 30 or higher are considered obese. Nevertheless some researchers, especially in developing countries, claim that the limits established for the US are too permissive, and that the threshold to define obese adults should be set lower for other nationalities and ethnicities. This paper analyzes the mortality risks for different BMI levels of two populations of American adult men. The first population lived during the last quarter of the 19th century and the early 20th century. These men were drawn from a random sample of Union Army veterans who fought during the American Civil War (1861-1865). A contemporary sample of men was drawn from the first wave of the National Health and Nutrition Examination Survey (NHANES I) conducted between 1971 and 1975. The results indicate that the frontier of overweight and obesity are expanding over time, such that the potential risk is nowadays associated with higher levels of BMI. The finding may imply that differences in BMI cut-off points are not only cross ethnic, but also occur for similar ethnicities across time.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it