Heterogeneous effects of old age on human muscle oxidative capacity in vivo: a systematic review and meta-analysis
Bibliographic record
Abstract
Despite intensive efforts to understand the extent to which skeletal muscle mitochondrial capacity changes in older humans, the answer to this important question remains unclear. To determine what the preponderance of evidence from in vivo studies suggests, we conducted a systematic review and meta-analysis of the effects of age on muscle oxidative capacity as measured noninvasively by magnetic resonance spectroscopy. A secondary aim was to examine potential moderators contributing to differences in results across studies, including muscle group, physical activity status, and sex. Candidate papers were identified from PubMed searches (n = 3561 papers) and the reference lists of relevant papers. Standardized effects (Hedges’ g) were calculated for age and each moderator using data from the 22 studies that met the inclusion criteria (n = 28 effects). Effects were coded as positive when older (age, ≥55 years) adults had higher muscle oxidative capacity than younger (age, 20–45 years) adults. The overall effect of age on oxidative capacity was positive (g = 0.171, p < 0.001), indicating modestly greater oxidative capacity in old. Notably, there was significant heterogeneity in this result (Q = 245.8, p < 0.001; I2 = ∼70%–90%). Muscle group, physical activity, and sex were all significant moderators of oxidative capacity (p ≤ 0.029). This analysis indicates that the current body of literature does not support a de facto decrease of in vivo muscle oxidative capacity in old age. The heterogeneity of study results and identification of significant moderators provide clarity regarding apparent discrepancies in the literature, and indicate the importance of accounting for these variables when examining purported age-related differences in muscle oxidative capacity.
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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 | 0.027 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".