Dynapenic Abdominal Obesity and Metabolic Risk Factors in Adults 50 Years of Age and Older
Bibliographic record
Abstract
OBJECTIVES: To investigate the additive effect of dynapenia and abdominal obesity on metabolic risk factors in older adults. METHOD: A total of 3,007 men and women from the National Health and Nutrition Examination Survey (NHANES) study were categorized as follows: (a) non-dynapenic/non-abdominally obese (N-DYN/N-AO), (b) dynapenic/non-abdominally obese (DYN/N-AO), (c) non-dynapenic/abdominally obese (N-DYN/AO), (d) dynapenic/ abdominally obese (DYN/AO) based on waist circumference (WC) and leg muscle strength tertiles. Dependent variables were lipids, glucose, blood pressure, and other chronic conditions. RESULTS: The DYN/AO group had lower plasma HDL-chol and higher triglyceride and glucose levels than N-DYN/N-AO and DYN/N-AO groups (all p ≤ .01). Higher plasma triglyceride was observed in the DYN/AO group compared with N-DYN/AO group (p ≤ .01). The odds of having metabolic syndrome, cardiovascular diseases, and type II diabetes were higher in DYN/AO compared with DYN/N-AO and N-DYN/N-AO. CONCLUSION: DYN/AO older adults might be at greater risk of metabolic alterations than those displaying dynapenia alone or those with neither abdominal obesity nor dynapenia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".