Resistance training, skeletal muscle hypertrophy, and glucose homeostasis: how related are they? A Systematic review and Meta-analysis
Bibliographic record
Abstract
Resistance training (RT) promotes skeletal muscle (Skm) hypertrophy, increases muscular strength, and improves metabolic health. Whether changes in fat-free mass (FFM; a surrogate marker of muscle hypertrophy) moderate RT-induced improvements in glucose homeostasis has not been determined, despite extensive research on the benefits of RT for health and performance. The aim of this meta-analysis is to examine whether RT-induced Skm hypertrophy drives improvements in glucose metabolism and to explore confounders, such as biological sex and training parameters. Random-effects meta-analyses were performed using variance random effects. Meta-regressions were performed for confounding factors depending on the heterogeneity ( I2). Analyses from 33 intervention studies revealed significant within-study increases in FFM with a moderate effect size (within-studies: (effect size; ES = 0.24 [0.10; 0.39]; p = 0.002; I2 = 56%) and a tendency for significance when compared with control groups (ES = 0.42 [−0.04–0.88]; p = 0.07). Within-study significant increases in glucose tolerance (2 h glucose: ES = −0.3 [−0.50; −0.11]; p < 0.01; I2 = 43%; glucose area under the curve (AUC): −0.40 [−0.66; −0.13] I2 = 76.1%; p < 0.01) and insulin sensitivity (ES = 0.38 [0.13; 0.62]; I2 = 53.0%; p < 0.01) were also apparent with RT. When compared to control groups, there was no significant difference in 2 h glucose, nor in glucose AUC from baseline in RT intervention groups. Meta-regression analyses failed to consistently reveal increases in FFM as a moderator of glucose homeostasis. Other mixed-effect models were also unsuccessful to unveil biological sex or training parameters as moderators of FFM increases and glucose homeostasis changes. Although Skm hypertrophy and improvements in glycemic control occur concurrently during RT, changes in these variables were not always related. Well-controlled trials including detailed description of training parameters are needed to inform RT guidelines for improving metabolic health. Registration and protocol number (Prospero): CRD42023397362.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.029 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".