Supplementation with the Leucine Metabolite β-hydroxy-β-methylbutyrate (HMB) does not Improve Resistance Exercise-Induced Changes in Body Composition or Strength in Young Subjects: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
β-hydroxy-β-methylbutyrate (HMB) is a leucine metabolite that is purported to increase fat-free mass (FFM) gain and performance in response to resistance exercise training (RET). The aim of this systematic review and meta-analysis was to determine the efficacy of HMB supplementation in augmenting FFM and strength gains during RET in young adults. Outcomes investigated were: total body mass (TBM), FFM, fat mass (FM), total single repetition maximum (1RM), bench press (BP) 1RM, and lower body (LwB) 1RM. Databases consulted were: Medical Literature Analysis and Retrieval System Online (Medline), Excerpta Medica database (Embase), The Cumulative Index to Nursing and Allied Health Literature (CINAHL), and SportDiscus. Fourteen studies fit the inclusion criteria; however, 11 were analyzed after data extraction and funnel plot analysis exclusion. A total of 302 participants (18-45 y) were included in body mass and composition analysis, and 248 were included in the strength analysis. A significant effect was found on TBM. However, there were no significant effects for FFM, FM, or strength outcomes. We conclude that HMB produces a small effect on TBM gain, but this effect does not translate into significantly greater increases in FFM, strength or decreases in FM during periods of RET. Our findings do not support the use of HMB aiming at improvement of body composition or strength with RET.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.024 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".