Age-Related Declines in Lower Limb Muscle Function are Similar in Power and Endurance Athletes of Both Sexes: A Longitudinal Study of Master Athletes
Bibliographic record
Abstract
The age-related decline in muscle function, particularly muscle power, is associated with increased risk of important clinical outcomes. Physical activity is an important determinant of muscle function, and different types of physical activity e.g. power-based versus endurance-based exercise appear to have differential effects on muscle power. Cross-sectional studies suggest that participation in power-based exercise is associated with greater muscle power across adulthood but this has not been investigated longitudinally. We recruited eighty-nine male and female power and endurance master athletes (sprint and distance runners respectively, baseline age 35-90y). Using jumping mechanography, we measured lower limb muscle function during a vertical jump including at least two testing sessions longitudinally over 4.5 ± 2.4y. We examined effects of time, discipline (power/endurance) and sex in addition to two- and three-way interactions using linear mixed-effects models. Peak relative power, relative force and jump height, but not Esslingen Fitness Index (indicating peak power relative to sex and age-matched reference data) declined with time. Peak power, force, height and EFI were greater in power than endurance athletes. There were no sex, discipline or sex*discipline interactions with time for any variable, suggesting that changes were similar over time for athletes of both sexes and disciplines. Advantages in lower limb muscle function in power athletes were maintained with time, in line with previous cross-sectional studies. These results suggest that improvements in lower limb function in less active older individuals following power-based training persist with continued adherence, although this requires further investigation in interventional studies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".