Abstract
Background:
Creatine is a highly marketed ergogenic aid that has strengthening and high-intensity training effects. However, past meta-analyses have often grouped together heterogeneous training modalities, and it was not known if the training context has a modifying effect on body composition and performance.
Methods:
This systematic review and meta-analysis pooled RCT evidence in healthy men aged 18–30 years old to quantify the effects of creatine supplementation in terms of body composition, maximal strength, and exercise performance. All the databases were searched up to 1 October 2025, and 39 eligible trials were discovered. The context of training was prespecified—RT vs. non-RT, and used as the main comparison. Pooled estimates were made using random effects models for FFM, LBM, and Wingate peak and mean power, CMJ, and 1RM outcomes. The exploratory subgroup analyses were done to investigate whether training condition and intervention duration moderated the effects.
Results:
The number of trials that were considered according to the inclusion criteria was thirty-nine. When using RT, creatine supplementation led to significant gains in FFM (+3.39 kg) and LBM (+2.70 kg), but not to significant gains in non-RT conditions. Wingate peak and mean power both increased in both contexts (peak power +71.27 W; mean power +39.69 W), with no evidence that training context modified these results. CMJ showed a pooled improvement of 2.87 cm; however, this estimate should be interpreted with caution due to high heterogeneity (I2 = 88.5%). Exploratory analyses suggested that more consistent effects may occur in interventions lasting at least 8 weeks.
Conclusion:
The supplementation with creatine leads to an increase in anaerobic power regardless of the training environment, but the gains in body composition depend on parallel RT. In practice, creatine in association with RT is recommended for lean mass gains, while either anaerobic performance benefit could be obtained in different training modalities.
Systematic review registration:
The study was prospectively registered in PROSPERO (CRD420261283973). The registration URL is: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=1283973.
1 Introduction
Creatine is an inborn nitrogen-containing compound, of which approximately 95% is present in the skeletal muscle; smaller quantities are found in tissues such as the brain, myocardium, and testes (1, 2). Regular dietary supplementation accounts for 60–80% of the overall body creatine and phosphocreatine (PCr), and exogenous creatine nutritional supplementation can further increase intramuscular creatine and PCr levels by between 20 and 40% (3, 4). The phosphocreatine-creatine kinase system is involved in the rapid extraction of a phosphate group of adenosine diphosphate to restore adenosine triphosphate (ATP) during high-power output and demands short-duration, high-intensity muscle contractions (5–7). It is on this mechanistic explanation that creatine supplementation is largely used as an ergogenic aid within the sport and exercise setting.
Randomized controlled trials and meta-analyses have been performed to study the effects of creatine on maximal strength, anaerobic performance, and body composition. For strength outcomes, previous syntheses are quite consistent in showing that benefits from creatine supplementation are greatest when creatine supplementation is coupled with structured resistance training (RT) (8, 9). This type of pattern is often attributed to improvements in training quality, tolerance to high-intensity loading, and recovery that have been shown with creatine, which may in turn lead to enhanced neuromuscular adaptations to training (10).
Creatine impacts body composition, with a wider variety of effects, particularly on the outcome of lean mass. Several systematic reviews and meta-analyses have found modest increases in lean body mass or fat-free mass; however, some have also found large between-study variability (11, 12). Differences in participants, supplementation protocols, training modalities, and assessment methods have all been put forward as contributing to this heterogeneity (13, 14). Training modality is often studied only as part of post hoc subgroup analyses, often as part of reviews including mixed sex and broad age ranges. As such, both the specificity and translational relevance of conclusions are limited. One such source is the training context, which is especially relevant, as it is through this context that the mechanisms underlying the expected adaptations operate and, at the same time, are actionable within the framework of program design.
Training context is a potentially likely effect modifier of creatine supplementation. The nature of the training stimulus will dictate the targeted muscle groups, loading conditions, cumulative training volume, and adaptive pathways used (15, 16). RT, in particular, offers a dramatic and progressive hypertrophic stimulus that might enable the metabolic benefits of creatine to result in measurable increases in lean mass (17, 18). Conversely, however, non-resistance training (non-RT) situations involve a wide variety of modalities whose loading patterns have a wider range of heterogeneity and can suppress or dilute such effects (19, 20). One outcome of this is that anaerobic outcomes are potentially different between modalities due to differences in neuromuscular demands and work-rest structures, which determine how enhanced availability of PCr is translated into measurable high-intensity performance.
Despite the relevance of training context, the existing evidence syntheses have several limitations. First, most reviews have confounded different groups of individuals and training approaches, downplaying the inferential debate on specific groups (11, 17). Second, the training context is often treated as a secondary or exploratory factor rather than being taken as a prespecified analytical framework, which makes inference on moderation weak (21). Third, performance and body composition outcomes are frequently evaluated in isolation, limiting integrated interpretation for exercise prescription (22). Thus, it is not established whether training context moderates creatine’s effects on performance and lean mass in young men.
This systematic review and meta-analysis synthesized RCTs in healthy men aged 18–30 years. It evaluated the effects of creatine supplementation on maximal strength, anaerobic performance, and lean mass outcomes (LBM and FFM). The training context was prespecified as RT versus non-RT and served as the primary analytical framework to test whether the training stimulus moderates creatine’s effects. Where data allowed, exploratory subgroup analyses were conducted to investigate heterogeneity while limiting the likelihood of spurious associations.
2 Methods
2.1 Registration and reporting standards
This systematic review and meta-analysis followed PRISMA reporting guidelines and the methodological recommendations of the Cochrane Handbook (23). The protocol was prospectively registered in PROSPERO (CRD420261283973) (24). Primary outcomes and the training context–stratified analytical framework (RT vs. non-RT) were prespecified.
2.2 Search strategy
Two reviewers independently searched PubMed, Web of Science, Scopus, Embase, the Cochrane Library, and SPORTDiscus from inception to 1 October 2025 (Supplementary File 1). The search combined controlled vocabulary, such as MeSH and Emtree terms, with free-text terms for creatine supplementation and RCT filters, such as random*, trial*, and placebo. To reduce the risk of missed studies, reference lists of all included articles were screened manually. Only full-text articles published in English were eligible, with no restriction on publication year.
2.3 Study selection and screening process
All records were imported into reference management software, and duplicates were removed. Study selection followed a two-stage process based on prespecified inclusion and exclusion criteria (25). Screening was performed independently by two reviewers, with disagreements resolved through discussion or adjudication by a third reviewer.
2.4 Eligibility criteria
2.4.1 Inclusion criteria
Participants: Healthy young men aged 18–30 years. Only studies with exclusively male samples were eligible.
Intervention: Creatine supplementation at any dose and regimen. A clearly defined training stimulus during the intervention period was required.
Comparators: A creatine-free control condition, including placebo or no creatine supplementation. When an exercise intervention was implemented, the control group was required to follow the same training program as the intervention group, with training frequency, intensity, periodization, and supervision matched as closely as possible. Apart from creatine, conditions were kept comparable where feasible.
Outcomes: Studies had to report at least one of the following primary outcomes with extractable data suitable for pooling: (1) maximal lower-body strength, such as one-repetition maximum (1RM) or an equivalent maximal strength test, including leg press or squat; (2) countermovement jump (CMJ) performance; (3) Wingate power indices, including peak and/or mean power; (4) lean mass outcomes, specifically LBM or FFM, with the assessment method recorded.
Study design: Randomized controlled trials.
2.4.2 Exclusion criteria
Studies were excluded if they were nonrandomized or lacked a control group; did not include exclusively male participants; enrolled participants outside the 18–30 year range or did not provide sufficient information to confirm eligibility; involved clinical or other special populations; failed to report outcome data usable for meta-analysis and such data could not be obtained after contacting authors; or included important cointervention differences between groups beyond creatine that could not be reasonably evaluated (such as an additional supplement provided only to one group).
During data extraction, included trials were classified by training context as RT or non-RT for stratified analyses.
2.5 Data extraction and data handling
Two reviewers independently extracted data using a standardized form, including author and publication year, sample size, participant age and training status or competitive level, creatine protocol (dose, duration, and whether a loading phase was used), comparator details, training content during the intervention and the corresponding training-context classification (RT or non-RT), and extractable data for the prespecified outcomes. Training context (RT vs. non-RT) was defined a priori. RT was defined as structured, progressive exercise using external resistance aimed at improving strength and/or hypertrophy. Trials were classified as non-RT if the primary training stimulus did not meet this definition, based on the predominant training modality described in each study. Discrepancies were resolved through discussion and, when necessary, adjudication by a third reviewer. To avoid duplicate weighting, each study contributed at most one effect estimate per prespecified outcome. Lean mass outcomes were extracted as reported in the original trials; therefore, LBM and FFM were not combined, and the assessment method was recorded for each. For all continuous outcomes, post-intervention values (means and standard deviations) were extracted and used for meta-analysis. Change scores were not employed.
2.6 Risk of bias and methodological quality assessment
Risk of bias was evaluated using the Cochrane Risk of Bias 2 (RoB 2) tool (26). RoB 2 covers five domains: the randomization process, deviations from intended interventions, missing outcome data, outcome measurement, and selection of the reported result. Each domain was rated as low risk, some concerns, or high risk, and an overall judgment was assigned accordingly. Two reviewers independently assessed risk of bias; discrepancies were resolved by consensus and, when necessary, adjudication by a third reviewer. Findings were summarized graphically.
2.7 Certainty of evidence (GRADE)
The certainty of evidence for each outcome was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework (27). Evidence was rated as high, moderate, low, or very low across five domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias. As all included studies were randomized controlled trials, certainty started at high and was downgraded where appropriate. Two reviewers assessed GRADE independently, with disagreements resolved by consensus.
2.8 Statistical analysis
All meta-analyses used random-effects models to account for anticipated between-study variation in participant characteristics, training protocols, and testing methods (28). Continuous outcomes were pooled as mean differences (MDs) with 95% confidence intervals (CIs). Because outcome units were consistent across studies, MDs were used rather than standardized mean differences (SMDs) to preserve interpretability in the original units. Meta-analyses were conducted only when outcomes were measured on comparable scales.
Statistical heterogeneity was quantified using I2 and interpreted alongside differences in study design, training context, and outcome assessment (29). I2 values of approximately 25, 50, and 75% were considered to represent low, moderate, and high heterogeneity, respectively.
The primary analyses were stratified by training context (RT vs. non-RT). When both strata contained a sufficient number of studies, effects were pooled within each stratum, and between-group differences were tested to evaluate potential moderation by training context.
Sensitivity analyses were conducted with the use of a leave-one-out approach, where each study was removed individually, and its influence was determined on the pooled estimates. Fixed-effect and random-effects models were also compared to test for robustness.
If an outcome was informed by at least 10 studies, publication bias was assessed using funnel plots and, where possible, Egger’s regression test (30). A two-sided p-value of <0.05 was considered statistically significant. Statistical analyses were performed using R (version 4.3.3) via RStudio, primarily employing the meta package for data pooling and the tidyverse for data handling and visualization.
3 Results
3.1 Study selection
There were 2,472 records identified in the databases. After removing 1,449 duplicates, 1,023 records were screened, and 909 records were excluded. Full-text reports were requested for 114 records; 6 of these reports could not be retrieved, and 108 reports were evaluated for eligibility. The total number of reports excluded was 69 due to the following reasons: lack of an eligible control group (n = 26), lack of prespecified outcomes (n = 16), inadequate data to conduct calculations of the effect size (n = 19), and inappropriate study design (n = 8). Ultimately, 39 studies were considered for the review (see Figure 1).
Figure 1
3.2 Study characteristics
A total of 39 such RCTs were included, consisting of 25 studies in RT settings and 14 in non-RT settings (14, 31–68). Not all outcomes were reported in some studies, but in every study, at least one prespecified outcome was noted. Mean ages were between 18.0 and 29.5 years, and training status ranged from sedentary or untrained to well-trained, competitive, and elite athletes. RT was the most common modality (about 64% of studies), with other protocols that included team sports (rugby or American football, soccer, handball, and basketball), individual sports (canoeing or rowing and sprinting), cycling-based protocols (including Wingate testing), and those related to strength- or power-related performance assessment.
Most supplementation protocols used either a loading phase followed by a maintenance phase or a fixed daily dose. The most common loading regimen was 20 g/day, administered in divided doses for 5–7 days, followed by a maintenance dose typically ranging from 2 to 10 g/day. Alternative approaches included body mass–based dosing (approximately 0.07–0.3 g/kg/day), higher fixed doses (25–35 g/day), and polyethylene glycol–bound creatine (1.25–2.50 g/day). Intervention duration ranged from 4 days to 12 weeks, with most trials lasting 4–10 weeks.
Control conditions most frequently consisted of carbohydrate-based comparators (such as glucose, dextrose, maltodextrin, or sucrose-based beverages) or inert placebos (such as cellulose or silica). A small number of studies used protein or carboxymethylcellulose as the comparator.
The primary outcomes included maximal strength (one-repetition maximum (1RM) in the squat or leg press), anaerobic or explosive performance (Wingate power outcomes and CMJ height), and body composition indices (FFM and LBM) (see Table 1).
Table 1
| Study citation | Mean age (years) | Sport/exercise modality | Subject level | Intervention protocol (dosage and frequency) | Duration | Control | Outcome measures |
|---|---|---|---|---|---|---|---|
| Ahmun et al. (31) | 20.6 | Rugby union | Highly trained | 20 g/d (4 × 5 g) | 5 days | Dextrose | Wingate power |
| Arciero et al. (32) | 21 | Resistance training | Healthy active (resistance-untrained) | 20 g/d (5 days) + 10 g/d (23 days) | 28 days | Dextrose | 1RM Leg Press, FFM |
| Becque et al. (33) | 21.5 | Arm flexor strength training | ≥1 year of weight training experience | Loading: 20 g/d (5 g × 4) for 5 days; maintenance: 2 g/d | 6 weeks | Flavored sucrose drink | FFM |
| Bemben et al. (34) | 19.2 | American football | NCAA Division I athletes (Redshirt) | 20 g/d (5 days) + 5 g/d (Maintenance) | 9 weeks | Glucose | 1RM squat, Wingate power, LBM |
| Bonilla et al. (35) | 26.6 | Cluster-set resistance training | Resistance-trained (>2 years experience) | 0.1 g/kg/d (post-workout) | 8 weeks | Protein | 1RM squat, CMJ, LBM |
| Camic et al. (36) | 22.1 | Anaerobic Performance Tests | Untrained (in resistance exercise) | 1.25 or 2.50 g/d PEG-creatine (1 dose/d) | 28 days | Cellulose | CMJ, FFM |
| Cribb et al. (37) | 24 | Bodybuilding | Recreational male bodybuilders | 1.5 g/kg/d Supplement (~0.3 g/kg load + 0.1 g/kg Maint) | 11 weeks | Glucose | 1RM squat, FFM |
| Del Favero et al. (38) | 24 | Strength/power tests | Untrained (not engaged in RT) | 20 g/d (2 × 10 g) | 10 days | Dextrose | 1RM squat, LBM |
| Earnest et al. (39) | 29.5 | Bench press and Wingate bike tests | ~11 years of training experience | 20 g/d (5 g × 4) during the supplementation period | 28 days | Glucose placebo | FFM |
| Griffen et al. (40) | 21.6 | Cycling (Wingate) | Well-trained men | 20 g/d (4 × 5 g) | 7 days | Placebo | Wingate power |
| Havenetidis et al. (41) | 29.4 | Cycling (Wingate) | Sprint Trained Males | 10–35 g/d (divided doses) | 4 days | Placebo | Wingate power |
| Herda et al. (42) | 21 | Resistance exercise/Wingate | Recreationally active | 5 g/d (1 dose/d) | 30 days | Placebo | Wingate power |
| Hoffman et al. (43) | 19 | American football | Collegiate athletes | 10.5 g/d (2 doses/d) | 10 weeks | Placebo | 1RM squat, Wingate power |
| Izquierdo et al. (44) | 22 | Handball | Trained athletes | 20 g/d (4 × 5 g) | 5 days | Placebo | 1RM squat, CMJ |
| Javierre et al. (45) | 22.9 | Running (sprints) | Physically active | 20 g/d (4 × 5 g) | 5 days | Placebo | CMJ |
| Kaviani et al. (46) | 23 | Resistance training | Sedentary/inactive | 0.07 g/kg/d (2 doses/d) | 8 weeks | Placebo | 1RM leg press |
| Kelly et al. (47) | 26.8 | Powerlifting | Competitive | 20 g/d (Load) + 5 g/d (Maint) | 26 days | Glucose | LBM |
| Kilduff et al. (48) | 24 | Isometric bench-press | At least 2 years of structured training experience | 20 g/d (10 g × 2) mixed with 180 g dextrose for 5 days | 5 days | 200 g/d glucose polymer | FFM |
| Law et al. (49) | 23.1 | Basketball | Trained athletes | 20 g/d (4 × 5 g) | 5 days | Maltodextrin | 1RM squat, Wingate power |
| Mujika et al. (50) | 20.3 | Soccer | Highly trained | 20 g/d (4 × 5 g) | 6 days | Maltodextrin | CMJ |
| Noonan et al. (51) | 19.4 | Weight training and speed drills | NCAA division II football team | Loading: 20 g/d (5 g × 4) for 5 days; Maintenance: 100 or 300 mg/kg FFM | 8 weeks | Dextrose placebo | FFM |
| Nunes et al. (14) | 22.7 | Resistance training | Resistance trained | 0.3 g/kg/d (Load) + 0.03 g/kg/d (Maint) | 8 weeks | Maltodextrin | LBM |
| Ostojic (52) | 16.6 | Soccer (skills/sprints) | Young competitive | 30 g/d (3 × 10 g) | 7 days | Cellulose | CMJ |
| Peeters et al. (53) | 21.2 | Resistance training | Experienced (>2 yrs) | 20 g/d (Load) + 10 g/d (Maint) | 6 weeks | Maltodextrin | 1RM leg press, LBM |
| Percário et al. (54) | 17.1 | Handball/resistance training | Elite athletes | 20 g/d (Load) + 5 g/d (Maint) | 32 days | Maltodextrin | LBM |
| Saremi et al. (55) | 23.4 | Resistance training | Healthy untrained | 0.3 g/kg/d (Load) + 0.05 g/kg/d (Maint) | 8 weeks | Cellulose | 1RM leg press, LBM |
| Stone et al. (56) | 18.5 | American football | Collegiate athletes | 0.22 g/kg/d (3 doses/d) | 5 weeks | Placebo (Silica) | 1RM squat, CMJ, Wingate power, LBM |
| Stout et al. (57) | 19.6 | American football | Collegiate athletes | 21 g/d (Load) + 10.5 g/d (Maint) | 8 weeks | Glucose (CHO) | CMJ |
| Syrotuik et al. (58) | 22.1 | Resistance training | Resistance trained | 0.3 g/kg/d (Load) + 0.03 g/kg/d (Maint) | 37 days | Placebo | 1RM Leg Press |
| Taylor et al. (59) | 21.3 | Resistance training | Resistance trained | 5 g/d (1 dose/d) | 8 weeks | Placebo | 1RM Leg press, Wingate power, LBM |
| Trexler et al. (60) | 21.2 | Resistance training | Recreationally Trained | 5 g/d (1 dose/d) | 28 days | Placebo | 1RM Leg Press |
| van Loon et al. (61) | 20.6 | Repeated supramaximal sprint and endurance cycling | No history of regular exercise training | Loading: 20 g/d for 5 days; Maintenance: 2 g/d for 37 days | 6 weeks | Placebo without creatine | FFM |
| Volek et al. (62) | 23.4 | Resistance training | Resistance trained | 25 g/d (Load) + 5 g/d (Maint) | 12 weeks | Placebo | 1RM squat, FFM |
| Volek et al. (63) | 20.3 | Resistance training (overreaching) | Resistance Trained | 0.3 g/kg/d (Load) + 0.03 g/kg/d (Maint) | 4–5 weeks | Placebo | 1RM squat, LBM |
| Wang et al. (65) | 21.1 | Complex training (squat/jump) | University Athletes | 20 g/d (Load) + 2 g/d (Maint) | 30 days | CMC | 1RM squat |
| Wang et al. (64) | 20.2 | Kayak/canoe | High school/uni athletes | 20 g/d (4 × 5 g) | 6 days | CMC | 1RM squat, CMJ, FFM |
| Wilder et al. (66) | 19.3 | American football | Collegiate athletes | 20 g/d (Load) + 5 g/d (Maint) | 10 weeks | Glucose polymers | 1RM squat, FFM |
| Willoughby & Rosene (67) | 20.4 | Resistance training | Untrained males | 6 g/d (1 dose/d) | 12 weeks | Dextrose | FFM |
| Zuniga et al. (68) | 22.5 | Resistance training | Resistance trained | 20 g/d (4 × 5 g) | 7 days | Maltodextrin | Wingate power |
Characteristics of included studies.
1RM, one-repetition maximum; CMJ, countermovement jump; FFM, fat-free mass; LBM, lean body mass; RT, resistance training; CHO, carbohydrate; PEG, polyethylene glycol (PEG-creatine); CMC, carboxymethylcellulose; g/d, grams/day; g/kg/d, grams/kg/day. Loading and maintenance denote high-dose initiation followed by a lower-dose phase; post-workout indicates intake immediately after training.
3.3 Risk of bias results
Risk of bias was evaluated using the Cochrane RoB 2 tool. Among the 39 trials, 25 (64.1%) were deemed to be at low risk of bias, 11 (28.2%) raised some concerns, and 3 (7.7%) were considered to be at high risk. Some concerns most commonly arose from deviations from intended interventions (D2), with fewer studies flagged for missing outcome data (D3) or selective reporting (D5). Outcome measurement (D4) was regarded as low risk in nearly all trials (38/39), consistent with predominantly objective performance and body-composition outcomes (see Figure 2).
Figure 2
3.4 Overall effects
Compared with control conditions, the pooled effect favored creatine supplementation for squat 1RM (16 studies, N = 300; MD = 11.9 kg, 95% CI 7.60 to 16.20; p < 0.001; I2 = 43.1%), whereas no significant pooled effect was observed for leg press 1RM (12 studies, N = 273; MD = 3.58 kg, 95% CI −7.85 to 15.01; p = 0.539; I2 = 39.1%).
For countermovement jump, the pooled effect favored creatine supplementation (12 studies, N = 293; MD = 2.87 cm, 95% CI 0.47 to 5.27; p = 0.019; I2 = 88.5%). The high heterogeneity indicates substantial variability across the included studies, which may reduce the stability of the pooled estimate. For anaerobic performance, significant pooled effects were observed for Wingate peak power (12 studies, N = 246; MD = 71.27 W, 95% CI 38.09 to 104.45; p < 0.001; I2 = 13.8%) and Wingate mean power (11 studies, N = 218; MD = 39.69 W, 95% CI 15.83 to 63.56; p = 0.001; I2 = 40.5%).
Significant pooled effects favoring creatine supplementation were also observed for FFM (15 studies, N = 327; MD = 2.32 kg, 95% CI 0.76 to 3.89; p = 0.004; I2 = 13.6%) and LBM (18 studies, N = 378; MD = 1.61 kg, 95% CI 0.34 to 2.88; p = 0.013; I2 = 36.3%).
Forest plots are summarized in Figure 3; the corresponding outcome-specific plots are presented in Figure A1.
Figure 3
3.5 Subgroup analysis by training context (RT versus non-RT)
For squat 1RM, significant pooled effects were observed in both RT (12 studies, N = 219; MD = 9.58 kg, 95% CI 4.47 to 14.70; p < 0.001; I2 = 42.4%) and non-RT studies (4 studies, N = 81; MD = 17.57 kg, 95% CI 11.68 to 23.47; p < 0.001; I2 = 0%), with evidence of a between-subgroup difference (p = 0.022; I2 = 81.0%).
For countermovement jump, the pooled effect was not significant in RT studies (5 studies, N = 88; MD = 4.19 cm, 95% CI − 1.28 to 9.66; p = 0.133; I2 = 95.2%), whereas a significant pooled effect was observed in non-RT studies (7 studies, N = 205; MD = 1.89 cm, 95% CI 0.18 to 3.59; p = 0.030; I2 = 38.3%); the between-subgroup difference did not reach conventional statistical significance (p = 0.068; I2 = 69.9%) (see Figure 4).
Figure 4
For Wingate peak power, significant pooled effects were observed in RT (7 studies, N = 158; MD = 61.35 W, 95% CI 29.61 to 93.09; p < 0.001; I2 = 0%) and non-RT studies (5 studies, N = 88; MD = 119.72 W, 95% CI 28.40 to 211.04; p = 0.010; I2 = 51.4%), with no evidence of a between-subgroup difference (p = 0.236; I2 = 23.7%). For Wingate mean power, significant pooled effects were also observed in RT (6 studies, N = 130; MD = 36.33 W, 95% CI 4.12 to 68.54; p = 0.027; I2 = 40.6%) and non-RT studies (5 studies, N = 88; MD = 45.33 W, 95% CI 3.80 to 86.85; p = 0.032; I2 = 52.3%), with no evidence of a between-subgroup difference (p = 0.902; I2 = 0%).
For body composition outcomes, a significant pooled effect was observed for FFM in RT studies (12 studies, N = 228; MD = 3.39 kg, 95% CI 1.77 to 5.02; p < 0.001; I2 = 0%), but not in non-RT studies (3 studies, N = 99; MD = −0.89 kg, 95% CI −3.94 to 2.15; p = 0.566; I2 = 24.0%), with evidence of a between-subgroup difference (p = 0.009; I2 = 85.4%). LBM showed a significant pooled effect in RT studies (12 studies, N = 279; MD = 2.70 kg, 95% CI 1.56 to 3.85; p < 0.001; I2 = 0%), whereas no significant pooled effect was observed in non-RT studies (6 studies, N = 99; MD = −0.60 kg, 95% CI −1.76 to 0.56; p = 0.311; I2 = 0%); the between-subgroup difference was significant (p < 0.001; I2 = 93.6%).
3.6 Subgroup analyses for CMJ
When stratified by intervention duration, the pooled effect was not significant in studies lasting <8 weeks (9 studies, N = 247; MD = 1.06 cm, 95% CI − 0.61 to 2.73; p = 0.214; I2 = 64.7%), whereas a significant pooled effect was observed in studies lasting ≥8 weeks (3 studies, N = 46; MD = 8.06 cm, 95% CI 3.87 to 12.25; p < 0.001; I2 = 79.4%); a between-subgroup difference was observed (p = 0.002; I2 = 78.4%) (see Figure 5).
Figure 5
When stratified by competitive level, a significant pooled effect was observed in competitive participants (8 studies, N = 194; MD = 3.55 cm, 95% CI 0.51 to 6.59; p = 0.022; I2 = 92.0%), whereas no significant pooled effect was observed in recreational participants (4 studies, N = 99; MD = 1.17 cm, 95% CI −1.77 to 4.12; p = 0.435; I2 = 39.3%); no significant between-subgroup difference was detected (p = 0.272; I2 = 17.8%).
When stratified by supplementation frequency, a significant pooled effect was observed in studies with daily supplementation (9 studies, N = 165; MD = 3.02 cm, 95% CI 0.18 to 5.86; p = 0.037; I2 = 91.5%), whereas no significant pooled effect was observed in studies with non-daily supplementation (3 studies, N = 128; MD = 2.52 cm, 95% CI −0.53 to 5.57; p = 0.105; I2 = 9.0%); no evidence of a between-subgroup difference was observed (p = 0.813; I2 = 0%).
3.7 Sensitivity analysis
Sensitivity analyses using leave-one-out procedures and fixed-effect versus random-effects models produced consistent pooled estimates, with no single study materially influencing results. This pattern also held for CMJ despite substantial heterogeneity in the main analysis.
3.8 Assessment of publication bias
Visual inspection of funnel plots revealed no clear asymmetry, and Egger’s tests were non-significant across outcomes (squat 1RM, p = 0.915; leg press 1RM, p = 0.397; CMJ, p = 0.981; Wingate peak power, p = 0.340; Wingate mean power, p = 0.724; FFM, p = 0.213; LBM, p = 0.222). These findings indicate no evidence of small-study effects or publication bias (see Figure 6).
Figure 6
3.9 Certainty of evidence (GRADE)
The certainty of evidence for the primary outcomes is summarized in Table 2. High-certainty evidence was found for Wingate peak power, based on consistent and precise results across studies. Moderate-certainty evidence was observed for squat 1RM, FFM, LBM, and Wingate mean power, primarily due to moderate inconsistency or imprecision between studies. Evidence for leg press 1RM and CMJ was rated as low, due to serious imprecision in leg press 1RM and significant inconsistency compounded by imprecision in CMJ outcomes. These downgrades reflect variability in study designs, measurement protocols, and reporting practices, which affected the reliability of the effect estimates.
Table 2
| Outcome | Participants (RCTs) | Risk of bias | Inconsistency | Indirectness | Imprecision | Publication bias | Effect estimate (MD (95% CI)) | Overall certainty |
|---|---|---|---|---|---|---|---|---|
| Squat 1RM | 300 (16 RCTs) | Not serious | Serious | Not serious | Not serious | None detected | 11.9 (7.60, 16.20) | ⨁⨁⨁◯ Moderate |
| Leg press 1RM | 273 (12 RCTs) | Not serious | Serious | Not serious | Very serious | None detected | 3.58 (−7.85, 15.01) | ⨁⨁◯◯ Low |
| FFM | 327 (15 RCTs) | Not serious | Not serious | Not serious | Not serious | None detected | 2.32 (0.76, 3.89) | ⨁⨁⨁◯ Moderate |
| LBM | 378 (18 RCTs) | Not serious | Serious | Not serious | Not serious | None detected | 1.61 (0.34, 2.88) | ⨁⨁⨁◯ Moderate |
| Wingate peak power | 246 (12 RCTs) | Not serious | Not serious | Not serious | Not serious | None detected | 71.27 (38.09, 104.45) | ⨁⨁⨁⨁ High |
| Wingate mean power | 218 (11 RCTs) | Not serious | Serious | Not serious | Not serious | None detected | 39.69 (15.83, 63.56) | ⨁⨁⨁◯ Moderate |
| CMJ | 293 (12 RCTs) | Not serious | Very serious | Not serious | Serious | None detected | 2.87 (0.47, 5.27) | ⨁⨁◯◯ Low |
Certainty of evidence (GRADE framework) for primary outcomes.
MD, mean difference. Certainty of evidence was assessed using GRADE for continuous outcomes. For CMJ, certainty was downgraded due to very high heterogeneity (I2 = 88.5%) and variability in testing protocols.
4 Discussion
4.1 Main findings
This systematic review and meta-analysis included 39 randomized controlled trials in healthy men aged 18–30 years and examined whether training context modifies the effects of creatine supplementation. Training context (RT vs. non-RT) was prespecified as the primary analytical framework to assess contextual dependence. Lean mass outcomes (FFM and LBM) increased significantly only when creatine was combined with RT, whereas no significant effects were observed in non-RT settings. In contrast, Wingate peak and mean power improved significantly in both contexts, with little evidence that training type moderated these outcomes. CMJ showed a small overall improvement, but the high heterogeneity (I2 = 88.5%) warrants a cautious interpretation, as it limits the robustness and stability of this pooled estimate. Training context did not significantly moderate this effect. For maximal strength, squat 1RM improved in both contexts, whereas leg press 1RM showed no significant overall effect.
4.2 Comparison with previous evidence
The present findings are broadly consistent with prior meta-analyses reporting positive effects of creatine supplementation on strength and anaerobic performance (69). Additionally, the results extend this literature by explicitly testing training context as a prespecified moderator within a narrowly defined population. Previous reviews have frequently pooled mixed-sex samples and wide age ranges and have often examined training modality only through post hoc subgroup analyses (11). By restricting inclusion to healthy young men and stratifying analyses a priori by RT and non-RT, the current study enhances interpretability and translational relevance.
For body composition, the observed increases in FFM and LBM under RT conditions align with earlier syntheses reporting modest lean mass gains with creatine supplementation (15). However, the absence of significant effects in non-RT settings highlights the importance of a sufficiently robust resistance-based stimulus for translating creatine’s metabolic effects into measurable changes in lean mass (2). It should also be noted that increases in FFM or LBM, particularly in shorter-duration interventions, may partly reflect creatine-induced intracellular water retention rather than solely contractile tissue accretion.
With respect to anaerobic performance, the consistent improvements in Wingate peak and mean power across both training contexts support the view that creatine’s ergogenic effects on short-duration, high-intensity output are relatively independent of training modality (70). These findings are consistent with the established role of the phosphocreatine system in rapid ATP resynthesis and indicate that concurrent RT is not required to realize improvements in anaerobic power (2).
4.3 Interpretation and potential mechanisms
RT is mechanistically distinct because it provides planned progressive overload with high mechanical tension and sufficient training volume to reach hypertrophy-relevant thresholds. In contrast, non-RT modalities are more heterogeneous, and the magnitude and distribution of these stimuli across target muscles are often less consistent. The outcome-specific pattern of effects likely reflects complementary acute and chronic pathways. Increased intramuscular phosphocreatine availability likely contributes to improvements in short maximal efforts such as the Wingate test. By comparison, body composition changes are more indicative of longer-term adaptations that may be facilitated by greater training load and recovery capacity during RT.
Under non-RT conditions, training stimuli are more heterogeneous in terms of intensity, loading patterns, and targeted musculature, which may limit the extent of any creatine-related metabolic advantages being translated into consistent increases in lean mass (71). Accordingly, creatine appears to function as a training stimulus amplifier rather than an independent driver of increases in FFM or LBM (72).
The high variance noted in CMJ outcomes likely reflects that CMJ is a multi-factorial, skill-dependent performance outcome. CMJ height depends not only on energy availability but also on maximal strength (73), neuromuscular coordination, stretch–shortening cycle efficiency, technical execution, and testing protocols (74–76). The more consistent effects observed in longer interventions suggest that sufficient time may be required for creatine-related metabolic support to interact with training-induced neuromuscular adaptations (77, 78). Accordingly, pooled CMJ effects should be interpreted with caution, even when statistically significant.
The larger effect size for squat one-repetition maximum observed in the non-RT subgroup should be interpreted cautiously. This subgroup included a limited number of studies and participants, and differences in baseline training status, technical learning effects, and testing familiarity may have contributed (79, 80). This finding should not be interpreted as evidence that non-RT contexts are superior for strength development with creatine supplementation. In addition, strength improvements observed under non-RT conditions may reflect testing specificity, neural adaptations, or learning effects rather than true hypertrophic adaptations. In the absence of a structured resistance-based hypertrophic stimulus, increases in 1RM may predominantly reflect neuromuscular or task-specific adaptations rather than measurable changes in muscle mass.
4.4 Practical implications
For healthy young men seeking to increase lean mass, the present findings support the combined use of creatine supplementation with structured RT (2). In the absence of an adequate resistance-based stimulus, creatine alone should not be expected to produce reliable improvements in body composition (11).
Improvements in short-duration anaerobic power may be achieved across a range of training modalities (81), supporting the use of creatine in both RT and non-RT contexts when anaerobic performance is a primary goal (8).
For practitioners looking to enhance CMJ performance, the usage of creatine should be viewed as an adjunct in well-designed explosive or strength-oriented training programs that are undertaken over a sufficient duration of time (22). Therefore, emphasis should be placed on training quality and standardization of protocols over short-term supplementation only (73, 82). A summary of these outcome-specific patterns is provided in Table 3.
Table 3
| Outcome | RT context | Non-RT context | Between-subgroup difference | Practical takeaway |
|---|---|---|---|---|
| FFM | Significant increase | Not significant | Significant (p = 0.009) | Lean mass goals: creatine + RT |
| LBM | Significant increase | Not significant | Significant (p < 0.001) | Lean mass goals: creatine + RT |
| Squat 1RM | Significant increase | Significant increasea | Significant (p = 0.022) | Interpret non-RT gains cautiously |
| Wingate peak power | Significant increase | Significant increase | Not significant (p = 0.236) | Anaerobic goals: effective across modalities |
| Wingate mean power | Significant increase | Significant increase | Not significant (p = 0.902) | Anaerobic goals: effective across modalities |
| CMJ | Not significant | Pooled improvementb (non-RT subgroup) | Not significant (p = 0.068) | Skill-dependent; interpret cautiously |
Summary of outcome-specific effects by training context (RT vs. non-RT).
FFM, fat-free mass; LBM, lean body mass; RT, resistance training; CMJ, countermovement jump; 1RM, one-repetition maximum. Significant/not significant refers to the pooled meta-analytic effect (p < 0.05) within each training-context subgroup.
Larger effect size observed in the non-RT subgroup, but this is based on limited studies and participants (see Section 4.3).
High heterogeneity (I2 = 88.5%) warrants cautious interpretation of the CMJ finding.
4.5 Strengths, limitations, and future directions
Key strengths of this review include its focus on a narrowly defined population, the prespecified use of training context as the primary analytical framework, and the synthesis of strength, performance, and body composition outcomes within a single analysis. Limitations include the heterogeneity of non-RT training modalities, the limited number of studies in some subgroups, and the predominance of short- to medium-term interventions. Future research should include longer-duration trials, more granular classification of training stimuli, and standardized assessment protocols, particularly for explosive performance outcomes.
5 Conclusion
In healthy men aged 18–30 years, creatine supplementation produced outcome-specific effects that were partially dependent on training context. Lean mass outcomes (FFM and LBM) increased only when creatine was combined with RT, whereas anaerobic power (Wingate peak and mean power) improved in both RT and non-RT settings. Squat 1RM improved in both settings, leg press 1RM showed no significant overall effect, and CMJ showed a small pooled improvement with substantial heterogeneity and uncertain moderation by training context. This a priori training-context framework provides more direct evidence regarding the contextual dependence of creatine’s effects and is consistent with pairing creatine with RT when lean mass gain is the primary goal.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.
Author contributions
JG: Data curation, Funding acquisition, Validation, Methodology, Supervision, Conceptualization, Project administration, Writing – review & editing, Software, Resources, Writing – original draft, Investigation, Formal analysis, Visualization. YL: Investigation, Conceptualization, Methodology, Validation, Resources, Writing – review & editing, Formal analysis, Visualization, Supervision, Data curation, Project administration, Writing – original draft, Software, Funding acquisition. JX: Writing – review & editing, Software, Resources, Project administration, Conceptualization. YZ: Conceptualization, Validation, Investigation, Supervision, Software, Methodology, Writing – review & editing, Visualization, Resources, Data curation, Writing – original draft, Formal analysis, Project administration, Funding acquisition.
Funding
The author(s) declared that financial support was not received for this work and/or its publication.
Acknowledgments
The authors thank the investigators whose studies were included in this review and meta-analysis.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that Generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2026.1800546/full#supplementary-material
References
1.
BufordTWKreiderRBStoutJRGreenwoodMCampbellBSpanoMet al. International society of sports nutrition position stand: creatine supplementation and exercise. J Int Soc Sports Nutr. (2007) 4:6. doi: 10.1186/1550-2783-4-6,
2.
KreiderRBKalmanDSAntonioJZiegenfussTNWildmanRCollinsRet al. International Society of Sports Nutrition position stand: safety and efficacy of creatine supplementation in exercise, sport, and medicine. J Int Soc Sports Nutr. (2017) 14:18. doi: 10.1186/s12970-017-0173-z,
3.
HarrisRCSöderlundKHultmanE. Elevation of creatine in resting and exercised muscle of normal subjects by creatine supplementation. Clin Sci (Lond). (1992) 83:367–74. doi: 10.1042/cs0830367,
4.
HultmanESöderlundKTimmonsJACederbladGGreenhaffPL. Muscle creatine loading in men. J Appl Physiol. (1996) 81:232–7. doi: 10.1152/jappl.1996.81.1.232,
5.
GreenhaffPL. The nutritional biochemistry of creatine. J Nutr Biochem. (1997) 8:610–8. doi: 10.1016/s0955-2863(97)00116-2
6.
WallimannTTokarska-SchlattnerMSchlattnerU. The creatine kinase system and pleiotropic effects of creatine. Amino Acids. (2011) 40:1271–96. doi: 10.1007/s00726-011-0877-3,
7.
WyssMKaddurah-DaoukR. Creatine and creatinine metabolism. Physiol Rev. (2000) 80:1107–213. doi: 10.1152/physrev.2000.80.3.1107
8.
KazeminasabFKerchiABSharafifardFZarrehMForbesSCCameraDMet al. The effects of creatine supplementation on upper- and lower-body strength and power: a systematic review and meta-analysis. Nutrients. (2025) 17:2748. doi: 10.3390/nu17172748,
9.
WangZQiuBLiRHanYPetersenCLiuSet al. Effects of creatine supplementation and resistance training on muscle strength gains in adults <50 years of age: a systematic review and meta-analysis. Nutrients. (2024) 16:3665. doi: 10.3390/nu16213665,
10.
RawsonESPerskyAM. Mechanisms of muscular adaptations to creatine supplementation. Int SportMed J. (2007) 8:43–53.
11.
DelpinoFMFigueiredoLMForbesSCCandowDGSantosHO. Influence of age, sex, and type of exercise on the efficacy of creatine supplementation on lean body mass: a systematic review and meta-analysis of randomized clinical trials. Nutrition. (2022) 103-104:111791. doi: 10.1016/j.nut.2022.111791,
12.
Pashayee-KhameneFHeidariZAsbaghiOAshtary-LarkyDGoudarziKForbesSCet al. Creatine supplementation protocols with or without training interventions on body composition: a GRADE-assessed systematic review and dose-response meta-analysis. J Int Soc Sports Nutr. (2024) 21:2380058. doi: 10.1080/15502783.2024.2380058,
13.
BurkeRPiñeroAColemanMMohanASapuppoMAugustinFet al. The effects of creatine supplementation combined with resistance training on regional measures of muscle hypertrophy: a systematic review with meta-analysis. Nutrients. (2023) 15:2116. doi: 10.3390/nu15092116,
14.
NunesJPRibeiroASSchoenfeldBJTomeleriCMAvelarATrindadeMCet al. Creatine supplementation elicits greater muscle hypertrophy in upper than lower limbs and trunk in resistance-trained men. Nutr Health. (2017) 23:223–9. doi: 10.1177/0260106017737013,
15.
SchoenfeldBJGrgicJKriegerJ. How many times per week should a muscle be trained to maximize muscle hypertrophy? A systematic review and meta-analysis of studies examining the effects of resistance training frequency. J Sports Sci. (2019) 37:1286–95. doi: 10.1080/02640414.2018.1555906,
16.
SuchomelTJComfortPStoneMH. Weightlifting pulling derivatives: rationale for implementation and application. Sports Med. (2015) 45:823–39. doi: 10.1007/s40279-015-0314-y,
17.
ChilibeckPDKavianiMCandowDGZelloGA. Effect of creatine supplementation during resistance training on lean tissue mass and muscular strength in older adults: a meta-analysis. Open Access J Sports Med. (2017) 8:213–26. doi: 10.2147/oajsm.S123529,
18.
RawsonESVolekJS. Effects of creatine supplementation and resistance training on muscle strength and weightlifting performance. J Strength Cond Res. (2003) 17:822–31. doi: 10.1519/1533-4287(2003)017<0822:eocsar>2.0.co;2
19.
CandowDGForbesSCChilibeckPDCornishSMAntonioJKreiderRB. Effectiveness of Creatine supplementation on aging muscle and bone: focus on falls prevention and inflammation. J Clin Med. (2019) 8:488. doi: 10.3390/jcm8040488,
20.
DevriesMCPhillipsSM. Creatine supplementation during resistance training in older adults-a meta-analysis. Med Sci Sports Exerc. (2014) 46:1194–203. doi: 10.1249/mss.0000000000000220,
21.
GrgicJSchoenfeldBJOrazemJSabolF. Effects of resistance training performed to repetition failure or non-failure on muscular strength and hypertrophy: a systematic review and meta-analysis. J Sport Health Sci. (2022) 11:202–11. doi: 10.1016/j.jshs.2021.01.007,
22.
SuchomelTJNimphiusSBellonCRStoneMH. The importance of muscular strength: training considerations. Sports Med. (2018) 48:765–85. doi: 10.1007/s40279-018-0862-z
23.
PageMJMcKenzieJEBossuytPMBoutronIHoffmannTCMulrowCDet al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. (2021) 372:n71. doi: 10.1136/bmj.n71
24.
BoothAClarkeMDooleyGGhersiDMoherDPetticrewMet al. The nuts and bolts of PROSPERO: an international prospective register of systematic reviews. Syst Rev. (2012) 1:2. doi: 10.1186/2046-4053-1-2,
25.
SchardtCAdamsMBOwensTKeitzSFonteloP. Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med Inform Decis Mak. (2007) 7:16. doi: 10.1186/1472-6947-7-16,
26.
SterneJACSavovićJPageMJElbersRGBlencoweNSBoutronIet al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. (2019) 366:l4898. doi: 10.1136/bmj.l4898
27.
GuyattGHOxmanADVistGEKunzRFalck-YtterYAlonso-CoelloPet al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. (2008) 336:924–6. doi: 10.1136/bmj.39489.470347.AD,
28.
DerSimonianRLairdN. Meta-analysis in clinical trials. Control Clin Trials. (1986) 7:177–88. doi: 10.1016/0197-2456(86)90046-2,
29.
HigginsJPThompsonSG. Quantifying heterogeneity in a meta-analysis. Stat Med. (2002) 21:1539–58. doi: 10.1002/sim.1186,
30.
EggerMDavey SmithGSchneiderMMinderC. Bias in meta-analysis detected by a simple, graphical test. BMJ. (1997) 315:629–34. doi: 10.1136/bmj.315.7109.629,
31.
AhmunRPTongRJGrimshawPN. The effects of acute creatine supplementation on multiple sprint cycling and running performance in rugby players. J Strength Cond Res. (2005) 19:92–7. doi: 10.1519/13573.1,
32.
ArcieroPJHannibalNS3rdNindlBCGentileCLHamedJVukovichMD. Comparison of creatine ingestion and resistance training on energy expenditure and limb blood flow. Metabolism. (2001) 50:1429–34. doi: 10.1053/meta.2001.28159,
33.
BecqueMDLochmannJDMelroseDR. Effects of oral creatine supplementation on muscular strength and body composition. Med Sci Sports Exerc. (2000) 32:654–8. doi: 10.1097/00005768-200003000-00016,
34.
BembenMGBembenDALoftissDDKnehansAW. Creatine supplementation during resistance training in college football athletes. Med Sci Sports Exerc. (2001) 33:1667–73. doi: 10.1097/00005768-200110000-00009,
35.
BonillaDAKreiderRBPetroJLRomanceRGarcía-SilleroMBenítez-PorresJet al. Creatine enhances the effects of cluster-set resistance training on lower-limb body composition and strength in resistance-trained men: a pilot study. Nutrients. (2021) 13:2303. doi: 10.3390/nu13072303,
36.
CamicCLHoushTJZunigaJMTraylorDABergstromHCSchmidtRJet al. The effects of polyethylene glycosylated creatine supplementation on anaerobic performance measures and body composition. J Strength Cond Res. (2014) 28:825–33. doi: 10.1519/JSC.0b013e3182a361a5,
37.
CribbPJWilliamsADStathisCGCareyMFHayesA. Effects of whey isolate, creatine, and resistance training on muscle hypertrophy. Med Sci Sports Exerc. (2007) 39:298–307. doi: 10.1249/01.mss.0000247002.32589.ef,
38.
del FaveroSRoschelHArtioliGUgrinowitschCTricoliVCostaAet al. Creatine but not betaine supplementation increases muscle phosphorylcreatine content and strength performance. Amino Acids. (2012) 42:2299–305. doi: 10.1007/s00726-011-0972-5,
39.
EarnestCPSnellPGRodriguezRAlmadaALMitchellTL. The effect of creatine monohydrate ingestion on anaerobic power indices, muscular strength and body composition. Acta Physiol Scand. (1995) 153:207–9. doi: 10.1111/j.1748-1716.1995.tb09854.x,
40.
GriffenCRogersonDRanchordasMRuddockA. Effects of creatine and sodium bicarbonate coingestion on multiple indices of mechanical power output during repeated Wingate tests in trained men. Int J Sport Nutr Exerc Metab. (2015) 25:298–306. doi: 10.1123/ijsnem.2014-0146,
41.
HavenetidisKBourdasD. Creatine supplementation: effects on urinary excretion and anaerobic performance. J Sports Med Phys Fitness. (2003) 43:347–55.
42.
HerdaTJBeckTWRyanEDSmithAEWalterAAHartmanMJet al. Effects of creatine monohydrate and polyethylene glycosylated creatine supplementation on muscular strength, endurance, and power output. J Strength Cond Res. (2009) 23:818–26. doi: 10.1519/JSC.0b013e3181a2ed11,
43.
HoffmanJRatamessNKangJMangineGFaigenbaumAStoutJ. Effect of creatine and beta-alanine supplementation on performance and endocrine responses in strength/power athletes. Int J Sport Nutr Exerc Metab. (2006) 16:430–46. doi: 10.1123/ijsnem.16.4.430,
44.
IzquierdoMIbañezJGonzález-BadilloJJGorostiagaEM. Effects of creatine supplementation on muscle power, endurance, and sprint performance. Med Sci Sports Exerc. (2002) 34:332–43. doi: 10.1097/00005768-200202000-00023,
45.
JavierreCBarbanyJRBonjornVMLizárragaMAVenturaJLSeguraR. Creatine supplementation and performance in 6 consecutive 60 meter sprints. J Physiol Biochem. (2004) 60:265–71. doi: 10.1007/bf03167072,
46.
KavianiMAbassiAChilibeckPD. Creatine monohydrate supplementation during eight weeks of progressive resistance training increases strength in as little as two weeks without reducing markers of muscle damage. J Sports Med Phys Fitness. (2019) 59:608–12. doi: 10.23736/s0022-4707.18.08406-2,
47.
KellyVGJenkinsDG. Effect of oral creatine supplementation on near-maximal strength and repeated sets of high-intensity bench press exercise. J Strength Cond Res. (1998) 12:109–15. doi: 10.1519/00124278-199805000-00010
48.
KilduffLPVidakovicPCooneyGTwycross-LewisRAmunaPParkerMet al. Effects of creatine on isometric bench-press performance in resistance-trained humans. Med Sci Sports Exerc. (2002) 34:1176–83. doi: 10.1097/00005768-200207000-00019,
49.
LawYLOngWSGillianYapTLLimSCVon ChiaE. Effects of two and five days of creatine loading on muscular strength and anaerobic power in trained athletes. J Strength Cond Res. (2009) 23:906–14. doi: 10.1519/JSC.0b013e3181a06c59,
50.
MujikaIPadillaSIbañezJIzquierdoMGorostiagaE. Creatine supplementation and sprint performance in soccer players. Med Sci Sports Exerc. (2000) 32:518–25. doi: 10.1097/00005768-200002000-00039,
51.
NoonanDBergKLatinRWWagnerJCReimersK. Effects of varying dosages of oral creatine relative to fat free body mass on strength and body composition. J Strength Cond Res. (1998) 12:104–8.
52.
OstojicSM. Creatine supplementation in young soccer players. Int J Sport Nutr Exerc Metab. (2004) 14:95–103. doi: 10.1123/ijsnem.14.1.95,
53.
PeetersBMLantzCDMayhewJL. Effect of oral creatine monohydrate and creatine phosphate supplementation on maximal strength indices, body composition, and blood pressure. J Strength Cond Res. (1999) 13:3–9.
54.
PercárioSDominguesSPTeixeiraLFVieiraJLde VasconcelosFCiarrocchiDMet al. Effects of creatine supplementation on oxidative stress profile of athletes. J Int Soc Sports Nutr. (2012) 9:56. doi: 10.1186/1550-2783-9-56,
55.
SaremiAGharakhanlooRSharghiSGharaatiMRLarijaniBOmidfarK. Effects of oral creatine and resistance training on serum myostatin and GASP-1. Mol Cell Endocrinol. (2010) 317:25–30. doi: 10.1016/j.mce.2009.12.019
56.
StoneMHSanbornKSmithLLO'BryantHSHokeTUtterACet al. Effects of in-season (5 weeks) creatine and pyruvate supplementation on anaerobic performance and body composition in American football players. Int J Sport Nutr. (1999) 9:146–65. doi: 10.1123/ijsn.9.2.146,
57.
StoutJEckersonJNoonanDMooreGCullenD. Effects of 8 weeks of creatine supplementation on exercise performance and fat-free weight in football players during training. Nutr Res. (1999) 19:217–25. doi: 10.1016/S0271-5317(98)00185-7
58.
SyrotuikDGBellGJBurnhamRSimLLCalvertRAMacleanIM. Absolute and relative strength performance following creatine monohydrate supplementation combined with periodized resistance training. J Strength Cond Res. (2000) 14:182–90.
59.
TaylorLPooleCPenaELewingMKreiderRFosterCet al. Effects of combined creatine plus fenugreek extract vs. creatine plus carbohydrate supplementation on resistance training adaptations. J Sports Sci Med. (2011) 10:254–60.
60.
TrexlerETSmith-RyanAERoelofsEJHirschKRPerskyAMMockMG. Effects of coffee and caffeine anhydrous intake during creatine loading. J Strength Cond Res. (2016) 30:1438–46. doi: 10.1519/jsc.0000000000001223,
61.
van LoonLJOosterlaarAMHartgensFHesselinkMKSnowRJWagenmakersAJ. Effects of creatine loading and prolonged creatine supplementation on body composition, fuel selection, sprint and endurance performance in humans. Clin Sci (Lond). (2003) 104:153–62. doi: 10.1042/cs20020159,
62.
VolekJSDuncanNDMazzettiSAStaronRSPutukianMGómezALet al. Performance and muscle fiber adaptations to creatine supplementation and heavy resistance training. Med Sci Sports Exerc. (1999) 31:1147–56. doi: 10.1097/00005768-199908000-00011
63.
VolekJSRatamessNARubinMRGómezALFrenchDNMcGuiganMMet al. The effects of creatine supplementation on muscular performance and body composition responses to short-term resistance training overreaching. Eur J Appl Physiol. (2004) 91:628–37. doi: 10.1007/s00421-003-1031-z,
64.
WangCCFangCCLeeYHYangMTChanKH. Effects of 4-week creatine supplementation combined with complex training on muscle damage and sport performance. Nutrients. (2018) 10:1640. doi: 10.3390/nu10111640,
65.
WangCCYangMTLuKHChanKH. The effects of Creatine supplementation on explosive performance and optimal individual postactivation potentiation time. Nutrients. (2016) 8:143. doi: 10.3390/nu8030143,
66.
WilderNGildersRHagermanFDeivertRG. The effects of a 10-week, periodized, off-season resistance-training program and creatine supplementation among collegiate football players. J Strength Cond Res. (2002) 16:343–52.
67.
WilloughbyDSRoseneJ. Effects of oral creatine and resistance training on myosin heavy chain expression. Med Sci Sports Exerc. (2001) 33:1674–81. doi: 10.1097/00005768-200110000-00010
68.
ZunigaJMHoushTJCamicCLHendrixCRMielkeMJohnsonGOet al. The effects of creatine monohydrate loading on anaerobic performance and one-repetition maximum strength. J Strength Cond Res. (2012) 26:1651–6. doi: 10.1519/JSC.0b013e318234eba1,
69.
BranchJD. Effect of creatine supplementation on body composition and performance: a meta-analysis. Int J Sport Nutr Exerc Metab. (2003) 13:198–226. doi: 10.1123/ijsnem.13.2.198,
70.
CooperRNaclerioFAllgroveJJimenezA. Creatine supplementation with specific view to exercise/sports performance: an update. J Int Soc Sports Nutr. (2012) 9:33. doi: 10.1186/1550-2783-9-33,
71.
RobertsMDMcCarthyJJHornbergerTAPhillipsSMMackeyALNaderGAet al. Mechanisms of mechanical overload-induced skeletal muscle hypertrophy: current understanding and future directions. Physiol Rev. (2023) 103:2679–757. doi: 10.1152/physrev.00039.2022,
72.
SchoenfeldBJGrgicJOgbornDKriegerJW. Strength and hypertrophy adaptations between low- vs. high-load resistance training: a systematic review and meta-analysis. J Strength Cond Res. (2017) 31:3508–23. doi: 10.1519/jsc.0000000000002200,
73.
SuchomelTJNimphiusSStoneMH. The importance of muscular strength in athletic performance. Sports Med. (2016) 46:1419–49. doi: 10.1007/s40279-016-0486-0
74.
LiZMaWZhangLZhuWXieQSunY. The validity and reliability of the force plates and the linear position transducer in measuring countermovement depth and velocity during countermovement jump. Sensors (Basel). (2025) 25:6542. doi: 10.3390/s25216542,
75.
McErlain-NaylorSKingMPainMT. Determinants of countermovement jump performance: a kinetic and kinematic analysis. J Sports Sci. (2014) 32:1805–12. doi: 10.1080/02640414.2014.924055,
76.
XuJTurnerAComfortPHarryJRMcMahonJJChavdaSet al. A systematic review of the different calculation methods for measuring jump height during the countermovement and drop jump tests. Sports Med. (2023) 53:1055–72. doi: 10.1007/s40279-023-01828-x,
77.
RongWGeokSKSamsudinSZhaoYMaHZhangX. Effects of strength training on neuromuscular adaptations in the development of maximal strength: a systematic review and meta-analysis. Sci Rep. (2025) 15:19315. doi: 10.1038/s41598-025-03070-z,
78.
TillinNAPainMTFollandJP. Short-term training for explosive strength causes neural and mechanical adaptations. Exp Physiol. (2012) 97:630–41. doi: 10.1113/expphysiol.2011.063040,
79.
GrgicJLazinicaBSchoenfeldBJPedisicZ. Test-retest reliability of the one-repetition maximum (1RM) strength assessment: a systematic review. Sports Med Open. (2020) 6:31. doi: 10.1186/s40798-020-00260-z,
80.
MickeFIsenmannEGeislerSHeldS. Effects of repeated 1RM testing on strength, velocity, and load-velocity profiling: a repeated measurement trial. J Sports Sci Med. (2025) 24:303–10. doi: 10.52082/jssm.2025.303,
81.
AbreuROliveiraCBCostaJABritoJTeixeiraVH. Effects of dietary supplements on athletic performance in elite soccer players: a systematic review. J Int Soc Sports Nutr. (2023) 20:2236060. doi: 10.1080/15502783.2023.2236060,
82.
ComfortPCuthbertMRipleyNJ. "Strength, power, and plyometric training". In: Conditioning for Strength and Human Performance, Chandler TJ, Chandler WB, Bishop C, editors. London: Routledge (2024). p. 361–85.
Appendix A outcome-specific forest plots
Figure A1
Summary
Keywords
anaerobic performance, body composition, creatine, meta-analysis, resistance training, supplementation
Citation
Gu J, Li Y, Xiao J and Zhang Y (2026) Creatine supplementation in young men under resistance versus non-resistance training: a systematic review and meta-analysis of strength, performance, and lean mass. Front. Nutr. 13:1800546. doi: 10.3389/fnut.2026.1800546
Received
31 January 2026
Revised
15 February 2026
Accepted
11 March 2026
Published
08 April 2026
Volume
13 - 2026
Edited by
Adam Jajtner, Kent State University, United States
Reviewed by
Axel Zevallos-Aquije, Universidad Cesar Vallejo, Peru
Leonardo Lubis, Padjadjaran University, Indonesia
Updates
Copyright
© 2026 Gu, Li, Xiao and Zhang.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yu Zhang, 1163572919@qq.com
†These authors have contributed equally to this work
ORCID: Yu Zhang, orcid.org/0009-0009-4012-6015
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.