Effects of Creatine and β-Alanine Co-Supplementation on Exercise Performance and Body Composition: A Systematic Review
Bibliographic record
Abstract
Background/Objectives: Creatine and β-alanine are two widely used dietary supplements known to enhance exercise performance and improve body composition; however, less is known regarding the synergistic effects of combining the two supplements. Methods: A systematic search was conducted across PubMed/MEDLINE, Scopus, and Web of Science databases for randomized controlled trials (RCTs) published up to March 2025. Eligible studies included adult participants receiving creatine and β-alanine together compared to creatine or β-alanine alone for at least four weeks and assessed measures of exercise performance and/or body composition. Study quality was assessed using the Cochrane Risk of Bias tool. Results: A total of 7 randomized controlled trials (n = 263 participants; 231 males and 32 females) met the inclusion criteria. Collectively, the combination of creatine and β-alanine supplementation enhanced high-intensity exercise performance, particularly anaerobic power and repeated-bout performance, compared to creatine or β-alanine alone. Co-ingestion of creatine and β-alanine supplementation did not increase measures of maximal strength compared to creatine alone. The effects of creatine and β-alanine supplementation on body composition were equivocal, with one study reporting greater lean mass gains and fat mass reductions compared to creatine and β-alanine supplementation individually, while another found no significant improvements. Additionally, no significant improvements in aerobic endurance capacity (VO2max, lactate threshold, or time to exhaustion) were observed from creatine and β-alanine supplementation co-ingestion. Conclusions: The combination of creatine and β-alanine supplementation may be effective for enhancing high-intensity exercise performance but has no greater effect on maximal strength, body composition, or measures of aerobic capacity compared to creatine or β-alanine alone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".