Relationship Between Obesity and Obesity-Related Morbidities Weakens With Aging
Bibliographic record
Abstract
BACKGROUND: A weak relationship exists between obesity and mortality risk in older populations, however, the influence of age on the relationship between obesity and morbidity is unclear. The objective of this study was to determine the influence of age on the relationship between obesity and cardiovascular disease, type 2 diabetes, dyslipidemia, and hypertension. METHODS: Data from the Third National Health and Nutrition Examination Survey (1988-1994) were used. Individuals were classified into specific age (young: 18-40; middle: 40-65; old: 65-75; and very old: ≥75 years) and body mass index (BMI; 18.5-24.9, >25-29.9, ≥ 30kg/m(2)) categories. Cardiovascular disease, type 2 diabetes, dyslipidemia, and hypertension were categorized using measured metabolic risk factors, physician diagnosis, or medication use. RESULTS: Age modified the relationship between BMI and cardiovascular disease (Age × BMI interaction, p = .049), dyslipidemia (Age × BMI interaction, p = .035 for men, p < .001 for women), and hypertension (Age × BMI interaction, p = .023) in women but not in men (p = .167). However, age did not modify the relationship between BMI and type 2 diabetes (Age × BMI interaction, p = .177). BMI was strongly associated with increased relative risk of cardiovascular disease, dyslipidemia, type 2 diabetes, and hypertension in the young and middle aged, however, the association between BMI and these metabolic conditions were much more attenuated with increasing age. CONCLUSION: A stronger association between obesity and prevalent metabolic conditions exists in young and middle-aged populations than in old and very old populations. Longitudinal studies are needed to verify these findings and to confirm the benefits of weight loss on health across the life span.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".