Allometric scaling of strength in an independently living population age 55–86 years
Bibliographic record
Abstract
Most physiological functions vary allometrically with body size; however, few investigators have examined the relationship between strength and body size with allometric scaling. Thus, we hypothesized that allometric analysis would reveal that both the amount and quality of muscle are significant determinants of strength in the elderly. Allometric analyses were used to determine the influence of limb cross-sectional area (CSA), physical activity, demispan (distance between index-middle finger web and the sternal notch), leg length, and sex on grip and plantar flexor strength in men (n = 188) and women (n = 205) age 55-86 years. Physical activity was measured using a self-reporting questionnaire (Taylor et al. [1978] J Chron Dis 31:741-755). Forearm and leg CSA was estimated from anthropometry. There was an age-related decline in grip strength, independent of forearm CSA, demispan, and sex, equal to approximately 12% per decade, whereas plantar flexor strength adjusted for leg CSA, physical activity, and sex was reduced at a rate of approximately 15% per decade. The allometric models explained 71.4% (r = 0.845) and 38.8% (r = 0.623) of the variance in grip and plantar flexor strength, respectively. Model parameters were identified using multiple linear regression (P < 0.05). Thus, grip strength = forearm CSA(0.435). demispan(0.161). exp(3.905 - 0.012 age + 0.413 sex) and plantar flexor strength = leg CSA(0.223). physical activity (0.115). exp(5.867 - 0.015 age + 0.366 sex). These findings indicate that age-related reductions in muscle CSA do not fully account for strength declines with age. Physical activity is also important and partially explains these reductions.
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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 | 0.003 |
| 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 | 0.000 |
| 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".