Influence of Age on the Association Between Various Measures of Obesity and All‐Cause Mortality
Bibliographic record
Abstract
OBJECTIVES: To determine whether the association between various simple measures of obesity and risk for all-cause mortality differs between younger and older men and women. DESIGN: Prospective cohort study with 8.7 +/- 0.2 years of follow-up for mortality linkage. SETTING: Third National Health and Nutrition Examination Survey, 1988 to 1994. PARTICIPANTS: Four thousand, four hundred thirty-seven men and 5,166 women. MEASUREMENTS: Measures of obesity included body mass, waist circumference, waist-to-hip ratio, hip circumference, sum of skinfolds, and bioelectrical impedance. RESULTS: Overall and abdominal obesity are associated with greater mortality risk in younger adults (<65) (P<.05), whereas the associations between obesity and mortality are null or inverse in older adults (>65). In general, the association was stronger with measures of abdominal obesity than with measures of overall obesity or fat-free mass. CONCLUSION: The adverse effects of obesity on mortality risk are apparent only in adults younger than 65. Obesity as characterized using several different measures was not generally associated with greater mortality risk in older adults. Although weight loss is beneficial for reducing morbidity in obese adults of any age, it is unclear whether weight loss is equally beneficial for reducing mortality risk in older adults.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".