Frailty, Body Mass Index, and Abdominal Obesity in Older People
Bibliographic record
Abstract
BACKGROUND: Frailty has been conceptualized as a wasting disorder with weight loss as a key component. However, obesity is associated with disability and with physiological markers also recently linked with frailty, for example, increased inflammation and low antioxidant capacity. We aimed to explore the relationship between frailty and body mass index (BMI) in older people. METHODS: Data were from 3,055 community-dwelling adults aged 65 years and older who participated in the English Longitudinal Study of Ageing. Frailty was defined both by an index of accumulated deficits and by the Fried phenotype. BMI was divided into five categories, and waist circumference 88 cm or more (for women) and 102 cm or more (for men) was defined as high. Analyses were adjusted for sex, age, wealth, level of education, and smoking status. RESULTS: The association between BMI and frailty showed a U-shaped curve. This relationship was consistent across different frailty measures. The lowest frailty index (FI) scores and lowest prevalence of Fried frailty were in those with BMI 25-29.9. At each BMI category, and using either measure of frailty, those with a high waist circumference were significantly more frail. CONCLUSIONS: Both the phenotypic definition of frailty and the FI show increased levels of frailty among those with low and very high BMIs. In view of the rise in obesity in older populations, the benefits and feasibility of diet and exercise for obese older adults should be a focus of urgent inquiries. The association of frailty with a high waist circumference, even among underweight older people, suggests that truncal obesity may be an additional target for intervention.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".