The Role of Metabolic Syndrome, Adiposity, and Inflammation in Physical Performance in the Health ABC Study
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome (MetS) and functional limitation have been linked, but whether and how specific components of MetS and associated factors, such as inflammation, drive this relationship is unknown. METHODS: Data are from 2,822 men and women, aged 70-79 years, participating in the Health, Aging, and Body Composition (Health ABC) study and followed for 5 years. Presence of MetS at baseline was defined according to the National Cholesterol Education Program Adult Treatment Panel III guidelines. Interleukin-6, C-reactive protein, and body fat mass were measured at baseline. Measures of physical performance, including 400-m walk time, 20-m walking speed, and the Health ABC physical performance battery (PPB) were obtained at baseline and examination years 2, 4, and 6. RESULTS: A total of 1,036 (37%) individuals met criteria for MetS. MetS was associated with poorer physical performance at baseline. Effect estimates between MetS and gait speed, and components of the Health ABC PPB (standing balance and repeated sit-to-stand performance) were modestly attenuated after adjustment for inflammation. All associations were attenuated to nonsignificance after adding total body fat mass to the model. Longitudinal analyses yielded similar results. Individual MetS component analysis revealed that abdominal obesity explained the largest fraction of the variation in physical performance. CONCLUSIONS: Although inflammatory biomarkers partially accounted for the relationship between MetS and aspects of physical performance, overall findings implicate adiposity as the primary factor explaining poorer physical performance in older adults with MetS.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".