The effects of high adiposity on concentric and eccentric muscle performance of upper and lower limb musculature in young and older adults
Bibliographic record
Abstract
The present study uniquely examined the influence of old age and adiposity on maximal concentric and eccentric torque and fatigue of the elbow and knee (KF, KE) flexors and extensors. Forty males were recruited and categorised into young (n = 21, 23.7 ± 3.4) and old (n = 19, 68.3 ± 6.1) and then further into normal (young = 16.9 ± 2.5%, old = 20.6 ± 3.1%) and high adiposity (young = 28.9 ± 5.0%, old = 31.3 ± 4.2%) groups. Handgrip strength, sit-to-stand performance, and isokinetic assessments of peak torque at 60°, 120° and 180°·s−1 were measured. Older men produced significantly less concentric and eccentric peak torque (P < 0.016) but this was not influenced by adiposity (P > 0.055). For KE and KF, high adiposity groups demonstrated reduced peak torque normalised to body mass (P < 0.021), and muscle and contractile mode specific reduction in torque normalised to segmental lean mass. Eccentric fatigue resistance was unaffected by both age and adiposity (P > 0.30) and perceived muscle soreness, measured up to 72 hours after, was only enhanced in the upper body of the young group following eccentric fatigue (P = 0.009). Despite the impact of adiposity on skeletal muscle function being comparable between ages, these results suggest high adiposity will have greater impact on functional performance of older adults. Novelty: Irrespective of age, high adiposity may negatively impact force to body mass ratio and muscle quality in a muscle and contractile mode specific manner. Whilst the magnitude of adiposity effects is similar across ages, the impact for older adults will be more substantial given the age-related decline in muscle function.
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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".