Next Article in Journal
Mechanical Running Power and Energy Expenditure in Uphill and Downhill Running
Previous Article in Journal
Sex- and Sport-Specific Differences in Jump Strategies: Key Qualities for Jump Performance
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Does High-Intensity Interval Training Increase Muscle Strength, Muscle Mass, and Muscle Endurance? A Systematic Review and Meta-Analysis

by
Lucas Wiens
1,
Justin M. Losciale
2,3,
Matthew D. Fliss
1,
Max J. Abercrombie
1,
Darius Darabi
1,
Jedd Li
1,
Rowan Barclay
1 and
Cameron J. Mitchell
1,*
1
School of Kinesiology, Faculty of Education, The University of British Columbia, 2135 Wesbrook Mall Vancouver, Vancouver, BC V6T 1Z3, Canada
2
Informatics, Decision-Enhancement, and Analytic Sciences Center of Innovation, George E. Wahlen Department of Veterans Affairs Medical Center, 500 Foothill Dr, Salt Lake City, UT 84148, USA
3
Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
*
Author to whom correspondence should be addressed.
Sports 2025, 13(9), 293; https://doi.org/10.3390/sports13090293
Submission received: 19 June 2025 / Revised: 23 July 2025 / Accepted: 22 August 2025 / Published: 1 September 2025

Abstract

High-intensity/sprint interval training (HIIT/SIT) improves aerobic and anaerobic performance, but it is unknown if HIIT/SIT increases strength, muscle mass/size, and muscle endurance (ME). We aimed to determine if HIIT/SIT increases strength, muscle mass/size, and ME. Databases (Ovid Medline, Sport Discus, EMBASE, and CINAHL) and the gray literature (Google Scholar) were searched for original research articles investigating the impact of HIIT/SIT on strength, muscle mass/size, and ME (23 March 2025). The risk of bias (ROB) was assessed via the Cochrane ROB 2 Tool. Meta-analyses were performed when three or more randomized controlled trials compared HIIT/SIT to a common comparator. Fifty-four studies were included (N = 1136). Twenty-five studies had a high ROB, while twenty-nine had some concerns. Standardized mean differences (SMD) (95% CI) of 0.16; (−0.09, 0.40), 0.33; (−0.21, 0.87) were observed for meta-analyses comparing the effect of HIIT/SIT to moderate intensity continuous training (MICT) and non-exercise controls (CON) on FFM, respectively. A meta-analysis comparing the effect of HIIT/SIT to resistance training (RT) on leg press strength yielded a SMD of −0.82; 95% CI: (−1.97, 0.33). HIIT/SIT may induce slightly greater gains than MICT and CON for FFM, while RT is likely superior to HIIT/SIT for improving leg press strength. However, the certainty of evidence is low, and 95% CIs intersect zero for all analyses.

1. Introduction

The American College of Sports Medicine recommends 150 min of moderate-intensity aerobic activity and two sessions of muscle strengthening exercises per week [1]. ~50.5% of individuals meet aerobic exercise guidelines; however, only ~30% of individuals meet muscle strengthening guidelines, and just ~20% meet both aerobic and muscle strengthening guidelines [2]. The most cited barrier to exercise is “lack of time” [3], but if benefits associated with both resistance training (RT) and aerobic training could be achieved more efficiently, this barrier could be lifted.
A time efficient exercise method is high-intensity interval training (HIIT). HIIT intervals last 1–4 min and typically range from 80 to 95% of maximal effort, with constant power output maintained [4]. Sprint interval training (SIT) is performed at maximal effort with intervals lasting ~10–30 s, using fixed loads, with performance usually declining during subsequent efforts [4]. HIIT/SIT induces similar or greater aerobic fitness improvements relative to MICT in less time [4], improves anaerobic performance [5,6], and results in comparable levels of fatigue and metabolic stress as RT [7,8]. Therefore, HIIT/SIT may be time efficient methods to improve both muscular and aerobic fitness. It is currently unknown if HIIT/SIT promotes increases in strength, muscle mass/size, or ME.
Aerobic training is not typically considered to be an anabolic stimulus; however, some reports of hypertrophy in response to aerobic training exist given sufficient volume and intensity [9]. The two most important training variables for inducing muscle hypertrophy are training volume (reps × sets × load) and training in proximity to momentary failure (high levels of perceived effort) [10,11,12]. HIIT/SIT induce high levels of perceived effort [13], while SIT results in performance declines, indicating fatigue (task failure) [14]. Typical HIIT/SIT also demands a greater training volume relative to most RT interventions [7,8]. Therefore, if high enough intensities are achieved during HIIT/SIT, hypertrophy may result.
Despite the high-intensity nature of HIIT/SIT, minimal work has examined the impact of HIIT/SIT interventions on muscle hypertrophy, with most studies assessing whole-body changes in fat-free mass (FFM). A narrative review on this topic [15] detailing the acute and chronic impact of HIIT/SIT on muscle hypertrophy at the molecular, cellular, muscular, and whole-body level demonstrated that HIIT/SIT may activate similar hypertrophic signaling pathways as RT [16,17] and elevate both myofibrillar and sarcoplasmic protein synthesis following acute exercise bouts [18]. The authors concluded that HIIT/SIT elicits changes at the transcriptional and translational level associated with muscle hypertrophy but did not systematically review HIIT/SIT-induced changes in muscle size. The only meta-analysis examining this topic [19] compared 4 weeks or more of low-volume HIIT/SIT to MICT and found no difference in FFM, but no comparisons were made to control groups, and assessments of localized muscle hypertrophy were not included.
Improvements in muscle strength are regulated by neural adaptions and increased muscle physiological cross-sectional area, induced via mechanical tension, typically achieved via RT [20,21,22]. In practice, lifting heavier loads (a higher percentage of an individual’s one-repetition maximum (1-RM)) yields greater gains in muscle strength compared to lifting lighter loads for more repetitions [23]. However, strength gains are still observed following lower load RT [24,25,26]. Peak pedal forces during HIIT/SIT cycling are estimated to be ~200–500 N/leg [27], while peak isometric leg press force has been documented to be ~2000–2500 N/leg in similar populations [28]. Therefore, peak forces during HIIT/SIT likely range from ~10–25% of MVC/1-RM. Previous work observed strength gains from RT at ~20% 1-RM [10], suggesting that loads encountered during HIIT/SIT cycling may be sufficient to induce strength gains.
Muscle endurance (ME) is the ability of a given muscle or muscle group to resist fatigue when performing resistance exercise at submaximal loads and is vital for many activities of daily life and physical performance [29]. It can be assessed at any load but is typically tested at loads corresponding to 30–60% 1-RM and can be measured in absolute or in relative terms [29]. Absolute ME reflects training-induced changes in work capacity, while relative ME is a measure of performance fatigability [29]. Low-load RT improves both absolute and relative ME when tested at low relative loads [24]. Muscle strength, mitochondrial function and content, muscle capillarization, and habituation to exercise-induced discomfort are theorized regulatory factors of ME performance [29]. HIIT/SIT increases mitochondrial function, mitochondrial content, muscle capillarization and induces high levels of perceived exertion [4]. Therefore, HIIT/SIT may improve ME; however, minimal work has investigated this.
Due to the barrier of time, a majority of individuals do not meet exercise guidelines, especially muscle strengthening guidelines [3,30,31]. The benefits of HIIT/SIT on aerobic fitness are unequivocal and are more time efficient than MICT [4]. However, it is unknown if HIIT/SIT can increase muscle mass/size, strength, or ME. The aim of this systematic review and meta-analysis was to determine if HIIT/SIT improves muscle strength, muscle mass/size, and muscle endurance in healthy adults.

2. Methods

2.1. Protocol and Registration

This study is a systematic review and meta-analysis. The study protocol was prospectively registered on PROSPERO—(Can High-Intensity Interval Training Induce Gains in Muscle Strength, Muscle Hypertrophy, and Local Muscle Endurance)—CRD42023400067—15 February 2023, and is reported following the PRISMA guidelines [32,33] (Figure S1).

2.2. Eligibility Criteria

Studies were included if they measured the effect of a HIIT/SIT intervention(s) compared to either a non-exercise or other exercise control group(s) on either muscle strength, muscle size/mass, or ME in healthy individuals (including obese individuals), aged 18–80, and of any sex or training status. HIIT/SIT interventions were required to span a minimum duration of 6 weeks, with no fewer than 12 training sessions completed. Only aerobic training interventions (i.e., cycling, running, rowing) with intervals lasting 10 s to 4 min at an intensity ≥ 80% maximum heart rate (HR)/VO2peak/work-peak were included in this review. Only randomized control trials (RCTs) were included in the meta-analysis. No restrictions were be placed on the types of studies included in the systematic review. Only peer-reviewed studies of English language were included. Studies were excluded if HIIT/SIT was combined with resistance training, supplementation, or ergogenic aids. All studies assessed muscle strength and/or muscle mass/size and/or ME, reported as pre/post intervention values or absolute/percentage change (means with standard deviations or standard error).

2.3. Information Sources and Search Strategy

Four online databases (Ovid Medline, Sport Discus, EMBASE, and CINAHL) were systematically searched for this review/meta-analysis (14 March 2023, 23 March 2025). The search strategy was based on including (“High-intensity interval training” OR “Sprint interval training” OR “High-intensity intermittent exercise” OR “Aerobic interval training” OR “SIT” OR “HIIT”) AND ((“Muscle strength” OR “Strength”) OR (“Muscle hypertrophy” OR “Hypertrophy” OR “Muscle growth”) OR (“Muscle endurance” OR “Strength endurance” OR “Muscle fatiguability” OR “Fatigue resistance”)). The full search strategy can be found in Table S1. A gray literature search and citation searching was performed using Google Scholar (14 March 2023, 24 March 2025).

2.4. Selection Process

Seven reviewers (L.W, J.ML, D. D, R. B, M.DF, M. A, J. L) applied the eligibility criteria and selected all studies for inclusion. All reviewers screened studies independently, and studies were screened in duplicate. One reviewer (L.W) screened all studies, and the other six reviewers (J.ML, D.D, R.B, M.DF, M.A, J. L) each screened approximately one sixth of the studies (randomly assigned). Researchers were blinded to each other’s decisions. Disagreements between individuals were resolved via a group discussion once all studies had passed through the given phase of screening (title and abstract or full text). Cohen’s kappa and percentage agreement were calculated via Covidence (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. Available at www.covidence.org, Version 2) for both the abstract/title screening and full-text screening phases. For the abstract/title screening the average Cohen’s kappa and percentage agreement were 0.42 and 96.4%, respectively. A percentage agreement of 68.5% and an average Cohen’s kappa of 0.43 was observed for the full-text screening phase. Covidence (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. Available at www.covidence.org, Version 2) was used for this review.

2.5. Data Collection Process Data Items

Study details, including author(s), participant characteristics (age, training status, number of participants), training prescription (duration of intervals, intensity of intervals, rest between intervals, and number of sets), mode of training (e.g., cycling, running, rowing, etc.), control group (yes/no), measure used to quantify strength, hypertrophy or ME, and main findings of the study, were extracted in duplicate and put into a custom data file (Microsoft Excel for Mac (Version 16.87)) and stratified by outcome (i.e., FFM, local muscle hypertrophy, strength, and ME). Disagreements between individuals were resolved via group discussion. Study investigators were contacted for unreported data/additional details when unreported data were deemed pertinent to the review/meta-analysis. When data were only provided in figures and investigators were unresponsive, WebPlotDigitizer (V4.6) was used to extract relevant data.
Acceptable measurement methods for strength outcomes included: 1-RM, isometric maximal volitional contraction (MVC), and isokinetic peak torque. For muscle mass/size, limb/segment/whole-body fat-free mass (assessed using dual-energy X-ray absorptiometry (DXA)), air displacement plethysmography (ADP), bioelectrical impedance (BIA)), muscle cross-sectional area (CSA), muscle thickness and muscle volume (assessed via ultrasonography or magnetic resonance imaging (MRI)), or muscle fiber CSA were included. Measures were accepted for ME at any load in absolute or relative terms or as muscle fatiguability in the form of maximum repetitions, work, or volume completed.

2.6. Risk of Bias Assessment

The Cochrane risk-of-bias 2 tool [34] was used to assess the risk of bias for the randomization process, deviation from intended interventions, missing outcome data, measurement of the outcome, selection of the reported result, and overall analysis. The Cochrane risk-of-bias 2 tool was chosen due to its rigor, widespread use within the field, and authors previous experience with this tool [35]. Four of the authors applied the risk-of-bias assessment (L.W, M.DF. J.ML, M.A). Each study was assessed by two independent reviewers (blinded to each other’s decisions). Disagreement was settled by a third reviewer.

2.7. Certainty of Evidence

The certainty of evidence was assessed via the GRADE (grading, recommendations, assessment, development, and evaluation) quality analysis framework for studies included in the meta-analysis (Tables S2–S4) [36]. As all studies included in the meta-analysis were randomized control trials, the evidence certainty was initially set as high (study design). Certainty was downgraded if >25% of studies were deemed as having a high risk of bias (risk of bias); if there was minimal overlap in confidence intervals or considerable heterogeneity (I2 > 50%) (inconsistency); if major discrepancies existed between participant demographics, training interventions, or measured outcomes or if indirect comparisons were made (indirectness); if confidence intervals exceeded 0.5 on either side of the standardized mean difference (SMD) (imprecision); and if publication bias was detected (if Egger’s test reached significance). Evidence was upgraded if there was a large effect (SMD > 0.8), plausible residual opposing confounding, and the presence of a dose response.

2.8. Data Synthesis and Analysis

A meta-analysis was performed when there were three or more randomized controlled trials comparing HIIT/SIT and a common comparator condition. Based on available data from included studies, three meta-analyses were performed. Post-intervention outcome means (SD) pooled between group comparisons (control as reference) were made with a Hedges G meta-analysis, using a random effects model (95% CI), with inverse variance weighting (restricted maximum likelihood estimation). A random effects model was chosen given expected heterogeneity across studies and that the target of inference extends beyond the samples contained within each study [37]. A Hartung–Knapp adjustment was made for small samples. Heterogeneity was assessed as the between-study variance (τ2) and proportion of variance attributable to between-study inconsistency (I2). A prediction interval was calculated to provide insight into the range of predicted treatment effect values on an individual level in a new study setting (after accounting for heterogeneity and within and between study variability) [38]. All post-intervention means were pooled together regardless of intervention length. Due to too few studies (n < 10), publication and small study bias were not formally explored. A ‘leave-one-out’ sensitivity analysis was performed to identify influential studies (see Figures S2, S4 and S6). All analyses were performed in R (version 4.3.2, R Core Team, Vienna, Austria) using the ‘meta’ package. After meta-analyses, the overall certainty of evidence was rated using the GRADE approach as described above (see Tables S1–S3) [36].

2.9. Post Hoc Protocol Deviations

Due to a lack of common comparator groups, for strength and muscle size/mass outcomes, additional post hoc analyses were performed. Weighted effect sizes and percentage change were calculated in Microsoft Excel (Microsoft Excel for Mac (Version 16.87)) via the formulas below [39,40]. (ES = effect size, n = study sample size, N = pooled sample size, Studypre = study pre-intervention mean, Studypost = study post-intervention mean, PooledSD = pre/post pooled standard deviation.) Confidence intervals were calculated using an alpha of 0.05.
W e i g h t e d E S = n × S t u d y p r e S t u d y p o s t P o o l e d S D N
W e i g h t e d % = n × S t u d y p r e S t u d y p o s t S t u d y p r e N × 100 %

3. Results

3.1. Study Selection

14,874 studies were retrieved from the initial database search along with 34 studies from citation searching and 4 studies from the gray literature. A total of 184 full-text articles were assessed for inclusion, with 54 studies ultimately included in this review (Figure 1).

3.2. Study Characteristics

Full study characteristics are included in Table 1, Table 2, Table 3 and Table 4. Of the 54 studies included, 32 studies (41 interventions) assessed FFM/skeletal muscle mass (Table 1), 19 studies (24 interventions) assessed local muscle mass/size or muscle fiber size (Table 2), 27 studies (37 interventions) measured muscle strength (Table 3), and 5 studies (8 interventions) assessed ME/fatiguability (Table 4). Of the 54 studies included in the review, 19 studies (35.2%) included male participants only, 10 studies (18.5%) included female participants only, and 25 studies (46.3%) included both males and females. The age of participants ranged from 18–80 years old. The training status of participants varied across studies, 16 recreationally active (29.6%), 18 sedentary (33.3%), 8 untrained (14.9%), 3 trained (5.6%), and 4 of unknown training status (7.4%). Some studies of note that initially appeared to meet the inclusion criteria were excluded due to RT being incorporated into the intervention groups’ warm up [41], the use of functional HIIT exercise interventions [42,43], and the duration of the intervention/intervals [44].

3.3. Risk of Bias

Twenty-five studies were assessed as having a high risk of bias, while twenty-nine were evaluated as having some concerns of bias (Figure 2).

3.4. Meta-Analysis Results

3.4.1. FFM

A meta-analysis comparing 6 or more weeks of HITT/SIT to MICT was conducted on FFM (N = 10 studies, n = 333 participants). Seven studies used DXA [55,62,63,65,70,71,81] to assess FFM, while two used BIA [56,72], and another used ADP [59]. The analysis resulted in a standardized mean difference of 0.16 (95% CI: −0.09, 0.40), and little to no heterogeneity was detected: I2 =0.0% [95% CI; 0%; 62.4%] and τ2 = 0 [95% CI: 0.0; 0.1] (Figure 3). The leave-one-out analysis and Baujat Plot (Figure S2) suggests that Shepherd et al., 2013 [72], was the most influential on these results. The effect size varied minimally when studies were removed via the leave-one-out analysis with a range of SMD of 0.13, 0.19, indicating that these results are robust (Figure S3).
A meta-analysis comparing 6 or more weeks of HITT/SIT to CON was conducted on FFM (N = 5 studies, n = 109 participants). Two studies used DXA [74,100] to assess FFM, while three used BIA [6,56,75]. The analysis resulted in a standardized mean difference of 0.33 (95% CI: −0.21, 0.87), and little to no heterogeneity was detected: I2 = 0.0% [95% CI; 0%; 79.2%] and τ2 = 0 [95% CI: 0.0; 1.1] (Figure 4). The leave-one-out analysis and Baujat Plot (Figure S4) suggests that Ziemann et al., 2011 [6], was the most influential study on these results. The effect size varied when studies were removed via the leave-one-out analysis with a range of SMD of 0.24, 0.48 (Figure S5).

3.4.2. Leg Press 1-RM Strength

A meta-analysis comparing 6 or more weeks of HITT/SIT to RT on leg press 1-RM strength (N = 3 studies, n = 62 participants) was conducted. The analysis resulted in a standardized mean difference of −0.82 (95% CI: −1.97, 0.33), and little to no heterogeneity was detected (I2 = 0.0%, τ2 = 0) (Figure 5). The leave-one-out analysis and Baujat Plot (Figure S6) suggests that Schjerve et al., 2008 [93], was the most influential study. The effect size varied when studies were removed via the leave-one-out analysis with a range of SMD of −0.94, −0.78 (Figure S7).

3.5. Weighted Effect Size and Percentage Change

3.5.1. Weighted Effect Size and Percentage Change for Muscle Hypertrophy

Weighted effect sizes and percent changes were calculated for FFM, LLM, and quadriceps CSA (Table 5). The FFM calculation included 463 participants from 26 studies [6,45,46,47,48,49,50,51,54,55,56,58,59,60,61,62,63,64,66,70,71,72,73,74,75,81] and yielded a weighted effect size of 0.06 (−0.03, 0.15) and a weighted % of 1.17 ± 1.64%. The LLM calculation included 159 participants from seven studies [51,54,60,61,69,89,101], a weighted effect size of 0.04 (0.02, 0.07) and a weighted % of 0.61 ± 2.36% was determined. Lastly, an effect size of 0.36 (0.34, 0.37) and a weighted % 4.72 ± 1.35% of was observed for quadriceps CSA. This calculation included 71 participants from four studies [46,66,78,101]

3.5.2. Weighted Effect Size and Percentage Change for Muscle Strength

Weighted effect sizes and percent changes were calculated for three strength outcomes: leg press 1-RM, isokinetic knee extension at 60°/s, and isometric knee extension at 90° (Table 6). The leg press 1-RM calculation included 41 participants from four studies [78,92,93,96]. A weighted % 3.45 ± 2.19% and weighted effect size of 0.16 (0.13, 0.19) were determined. The calculation for isokinetic knee extension at 60°/s involved 163 participants across seven studies [46,48,73,80,91,95,101], a weighted effect size of 0.01 (−0.02, 0.04) and a weighted % of 0.35 ± 4.88% was yielded. Lastly, an effect size of 0.19 (0.15, 0.22) and a weighted % of 4.94 ± 5.82% was calculated for isometric knee extension at 90° of knee flexion. This calculation involved 108 participants from five studies [45,46,89,97,101].

4. Discussion

The main findings of the present study indicate that HIIT/SIT may induce greater gains in FFM relative to MICT and non-exercise control groups. The results also suggest that RT is likely superior to HIIT/SIT regarding increases in leg press 1-RM strength. However, these findings should be interpreted with caution due to the small samples, imprecision of the pooled estimates (i.e., wide 95% CIs), 95% CIs that intersected zero for all three meta-analyses, and the certainty of evidence being classified as “low” for all analyses (Tables S2–S4). Pre–post effect sizes also suggest that participants who underwent HIIT/SIT interventions incurred small to moderate gains in quadriceps CSA and small improvements in isometric knee extension (90°) and leg press 1-RM strength, while minute to no change was observed in FFM, LLM, and isokinetic knee extension (60°/s) (Table 4 and Table 5). These observations suggest the potential benefits of HIIT/SIT for muscle strength and muscle size; however, further investigations with non-exercise control groups are required prior to the formation of firm conclusions on this topic.

4.1. Hypertrophy

Meta-analyses comparing HIIT/SIT to non-exercise controls and MICT indicate non-significant small effect sizes in favor of HIIT/SIT for FFM. Further, evidence from the systematic review indicates that HIIT/SIT likely has a very small effect on FFM, as a pre–post weighted effect size of 0.07 CI (−0.05, 0.08) was calculated (n = 463). These results are in agreement with that of Sultana et al., 2019 [19]. However, HIIT/SIT may be more effective at increasing localized muscle size when assessed via MRI. All five interventions that assessed pre–post changes in quadriceps CSA observed increases from baseline following HIIT/SIT (Table 5), and a small–moderate pre–post weighted effect size of 0.37; 95% CI (0.31, 0.44) was determined for this outcome (n = 71). This effect size is lesser but similar to that determined by Schoenfeld and colleagues [23] for the effects of low-load (0.42; 95% CI (0.23, 0.60)) and high-load RT (0.53; 95% CI (0.30, 0.76)) on muscle hypertrophy. No meta-analysis was conducted on quadriceps CSA for HIIT/SIT due to a lack of common comparator groups, limiting the conclusions that can be made for this outcome relative to RT or to non-exercise controls.
During a RT set, initially recruited motor unit fatigue over subsequent repetitions due to the accumulation of metabolites resulting in increased motor unit recruitment, with task failure resulting when further increases in motor units or the firing rate are not possible [102,103]. Training in proximity to failure and achieving sufficient training volume are key determinants of training-induced muscle hypertrophy [12,23]. Although time efficient, a substantial volume of mechanical work is typically achieved during a HIIT/SIT session [4]. HIIT occurs at a constant high intensity (80–95% VO2max), while SIT is completed at maximal or supramaximal intensity and is characterized by a steep decline in power output over time [14], while neither typically result in momentary task failure. The lack of momentary failure achieved during HIIT/SIT may partially explain the lower calculated effect sizes for HIIT/SIT relative to that of low-load and high-load RT from Schoenfeld et al., 2017 [23]. However, this fails to explain why much smaller magnitudes of effect sizes were determined for FFM and leg lean mass relative to MRI derived quadriceps CSA.
MRI is considered the gold standard of hypertrophic assessment as near perfect correlations have been established between MRI and cadaveric measures of muscle size and volume (r = 0.99) [104,105]. When compared to MRI, ultrasound and DXA both show strong cross-sectional correlations of r = 0.99, 0.89, respectively [106,107]. ADP and BIA display a strong correlation with DXA (r = 0.94 and 0.84–0.89), respectively, when comparing cross-sectional measurements [108]. However, a correlation of only 0.49 between DXA and MRI was observed after a 10-week RT program, exemplifying lower sensitivity of DXA to detect changes in muscle size across intervention studies [108]. BIA also performs poorly compared to DXA when measuring changes in lean body mass over time [109], as a 12-week weight loss study found a correlation of only 0.24 between DXA and BIA in measurement of FFM [109]. Further, BIA, DXA, and ADP measure FFM, not muscle mass. Therefore, limited value can be placed on FFM as a proxy for local muscle hypertrophy. For example, if a 100 kg person with a quadriceps muscle volume of 5000 cm3, a leg lean mass of 10 kg, and a FFM of 60 kg completed a quadriceps dominant training protocol for 12 weeks and increased their quadriceps muscle volume by 5% (250 cm3), this would be realized by only a ~2.65% gain in leg lean mass (265 g) and only a ~0.44% change in terms of FFM (assuming no other FFM changes and a muscle density of 1.0597 g/cm3). Furthermore, the technical error of the measurement has been estimated at ~2.5% for DXA-derived thigh mass [110] and only 1.1% for MRI-based thigh muscle volume [111]. Therefore, it is unsurprising that changes are more frequently observed via MRI measures of localized hypertrophy compared to DXA even within the same intervention group [66]. This phenomenon is demonstrated in the pre–post effect sizes calculated in Table 4.

4.2. Strength

The results from the meta-analysis comparing HIIT/SIT to RT on leg press 1-RM yielded a large but non-significant effect size in favor of RT. The findings of this meta-analysis should be interpreted cautiously given its small base of only three studies and 62 participants. However, all three studies observed a moderate–large effect in favor of RT suggesting that RT is likely superior to HIIT/SIT at increasing leg press 1-RM. Though, it should be noted that HIIT/SIT may induce a small increase in strength, as a pre–post weighted percentage change of 3.45 ± 2.19% and 4.94 ± 5.82% was determined for leg press 1-RM and isometric knee extension (90°), respectively (Table 5).
Traditional RT loads range from 30 to 90% 1-RM, with higher-load RT (>70% 1-RM) typically inducing greater gains in muscle strength than low-load RT (<60% 1-RM) [23]. HIIT/SIT induces high levels of perceived exertion, but peak forces during cycling-based HIIT/SIT are estimated to be only ~10–25% 1-RM [27,28]. Findings from the studies presented in this review reveal that HIIT/SIT does not induce consistent gains in muscle strength. This can be best explained by the principal of specificity, whereby the more similar a training stimuli is to the strength assessment in terms of load and modality, the larger the resulting improvement in task performance [23,112,113]. Recently, Pallares et al., 2025, demonstrated similar strength gains between 10-week cycling- and squat-based RT training, both occurring at 70% maximal dynamic force [114]. Therefore, the most plausible reasoning for HIIT/SIT not inducing gains in strength in most studies is due to insufficient loading rather than other dissimilarities between cycling and RT. Developing HIIT/SIT interventions, which induce forces above 60% of peak force, potentially through a reduction in cadence, would likely result in greater strength gains.

4.3. Muscle Endurance

In the present review, five studies were included that assessed ME or muscle fatiguability. Bornath and Kenno, 2022 [86], utilized a battle rope-based SIT intervention over 6 weeks in recreationally active younger adults. Both the male and female groups in this study improved their number of push-ups and sit-ups completed to failure and isometric shoulder extension and flexion strength relative to baseline. Similar results were observed by Cao et al., 2024 [88], who observed an increase in the number of push-ups completed following 12 weeks of running-based SIT. In contrast, Buckley et al., 2015 [87], found no difference in squat endurance at 70% of pre-training 1-RM after 8 weeks of a rowing-based HIIT intervention. The disparity between Buckley et al., 2015 [87], and Bornath and Kenno, 2022 [86], regarding ME is likley explained by the chosen load of the test used in each study and the relative load used during training [115].
Two other HIIT/SIT Intervention studies included in the review assesed muscle fatiguability [73,77]. In these studies, a maximal knee extension exercise was performed at 120°/s and 60°/s, respectively, and a fatigue index was used to assess the drop-off in force/work over 60 repetitions in the case of Bagley et al., 2016 [77], and until less than 50% of max work was maintained in Theofilidis et al., 2021 [73]. In both studies, muscle fatuigability was improved following HIIT/SIT, exhibiting that HIIT/SIT may improve fatigue resistance.
Due to a lack of similarity between ME measurements and common comparator groups, no meta-analyses or effect size calculations were possible for ME limiting the conclusions that can be drawn regarding this outcome. However, the current evidence suggests that HIIT/SIT likely improves low-load absolute ME but not high-load absolute ME or relative ME, as the latter are primarily governed by muscle strength [29].

4.4. Limitations

The findings of the present systematic review are limited due to a lack of non-exercise control groups or common comparator interventions and a lack of standardization in methods of strength, muscle mass/size, and ME assessment. Furthermore, no inferences can be made regarding the role of HIIT/SIT on strength, muscle hypertrophy, and ME in the presence of nutritional/ergogenic supplementation or acute and chronic conditions, as studies including supplementation and participants with acute or chronic ailments were excluded.

4.5. Conclusions and Future Directions

This review demonstrates that HIIT/SIT may induce slightly greater gains than MICT and non-exercise controls for FFM, while RT is likely superior to HIIT/SIT regarding 1-RM leg press strength. However, the certainty of evidence is low, and 95% CIs intersect zero for all three analyses. Pre–post effect sizes suggest that HIIT/SIT may induce small to moderate increases in quadriceps CSA and small increases in isometric and 1-RM strength, but no firm conclusions can be drawn for localized hypertrophy, strength, or ME from this review. Further research using control groups and validated methodologies to assess muscle strength, muscle mass/size, and ME are required to increase the level of certainty and clarity in these conclusions.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/sports13090293/s1, Figure S1: PRISMA 2020 checklist; Table S1: Complete search strategy; Table S2: FFM HIIT versus MICT grade assessment; Table S3: FFM HIIT versus CON grade assessment; Table S4: Leg press 1-RM strength HIIT versus RT grade assessment; Figure S2: FFM HIIT versus MICT leave-one-out analysis; Figure S3: FFM HIIT versus MICT Baujat Plot of heterogeneity contribution; Figure S4: FFM HIIT versus CON leave-one-out analysis; Figure S5: FFM HIIT versus CON Baujat Plot of heterogeneity; Figure S6: Leg press 1-RM strength HIIT versus RT leave-one-out analysis; Figure S7: FFM HIIT versus CON Baujat Plot of heterogeneity contribution.

Author Contributions

Conceptualization—L.W., M.D.F., C.J.M. Data curation—J.M.L. Formal analysis—J.M.L., L.W., J.L., D.D., R.B., M.D.F., M.J.A. Investigation—L.W., J.M.L., J.L., D.D., R.B., M.D.F., M.J.A. Methodology—J.M.L., L.W. Project administration—L.W. Resources—J.M.L. Software—J.M.L., L.W. Supervision—C.J.M., L.W. Validation—J.M.L. Visualization—L.W. Writing—original draft Writing—L.W., J.M.L. Review and editing—L.W., C.J.M., J.M.L., M.D.F., M.J.A. All authors have read and agreed to the published version of the manuscript.

Funding

This study received no external funding.

Data Availability Statement

Data generated or analyzed during this study are provided in full within the published article and its Supplementary Materials.

Conflicts of Interest

The Authors declare that there are no competing interests.

References

  1. Garber, C.E.; Blissmer, B.; Deschenes, M.R.; Franklin, B.A.; Lamonte, M.J.; Lee, I.-M.; Nieman, D.C.; Swain, D.P.; American College of Sports Medicine. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Med. Sci. Sports Exerc. 2011, 43, 1334–1359. [Google Scholar] [CrossRef] [PubMed]
  2. Bennie, J.A.; De Cocker, K.; Teychenne, M.J.; Brown, W.J.; Biddle, S.J.H. The epidemiology of aerobic physical activity and muscle-strengthening activity guideline adherence among 383,928 U.S. adults. Int. J. Behav. Nutr. Phys. Act. 2019, 16, 34. [Google Scholar] [CrossRef]
  3. Ebben, W.; Brudzynski, L. Motivations and barriers to exercise among college students. J. Exerc. Physiol. Online 2008, 11, 5. Available online: http://www.asep.org/asep/asep/EbbenJEPonlineOctober2008.pdf (accessed on 18 March 2024).
  4. MacInnis, M.J.; Gibala, M.J. Physiological adaptations to interval training and the role of exercise intensity: Training adaptations and the nature of the stimulus. J. Physiol. 2017, 595, 2915–2930. [Google Scholar] [CrossRef] [PubMed]
  5. Foster, C.; Farland, C.V.; Guidotti, F.; Harbin, M.; Roberts, B.; Schuette, J.; Tuuri, A.; Doberstein, S.T.; Porcari, J.P. The Effects of High Intensity Interval Training vs. Steady State Training on Aerobic and Anaerobic Capacity. J. Sports Sci. Med. 2015, 14, 747–755. [Google Scholar] [PubMed]
  6. Ziemann, E.; Grzywacz, T.; Łuszczyk, M.; Laskowski, R.; Olek, R.A.; Gibson, A.L. Aerobic and Anaerobic Changes with High-Intensity Interval Training in Active College-Aged Men. J. Strength Cond. Res. 2011, 25, 1104–1112. [Google Scholar] [CrossRef] [PubMed]
  7. Mao, J.; Wang, T.; Zhang, L.; Li, Q.; Bo, S. Comparison of the acute physiological and perceptual responses between resistance-type and cycling high-intensity interval training. Front. Physiol. 2022, 13, 986920. [Google Scholar] [CrossRef]
  8. Peake, J.M.; Tan, S.J.; Markworth, J.F.; Broadbent, J.A.; Skinner, T.L.; Cameron-Smith, D. Metabolic and hormonal responses to isoenergetic high-intensity interval exercise and continuous moderate-intensity exercise. Am. J. Physiol.-Endocrinol. Metab. 2014, 307, E539–E552. [Google Scholar] [CrossRef]
  9. Konopka, A.R.; Harber, M.P. Skeletal Muscle Hypertrophy after Aerobic Exercise Training. Exerc. Sport Sci. Rev. 2014, 42, 53–61. [Google Scholar] [CrossRef]
  10. Lasevicius, T.; Schoenfeld, B.J.; Silva-Batista, C.; Barros, T.D.S.; Aihara, A.Y.; Brendon, H.; Longo, A.R.; Tricoli, V.; Peres, B.D.A.; Teixeira, E.L. Muscle Failure Promotes Greater Muscle Hypertrophy in Low-Load but Not in High-Load Resistance Training. J. Strength Cond. Res. 2022, 36, 346–351. [Google Scholar] [CrossRef] [PubMed]
  11. Schoenfeld, B.J.; Grgic, J.; Van Every, D.W.; Plotkin, D.L. Loading Recommendations for Muscle Strength, Hypertrophy, and Local Endurance: A Re-Examination of the Repetition Continuum. Sports 2021, 9, 32. [Google Scholar] [CrossRef]
  12. Schoenfeld, B.J. The Mechanisms of Muscle Hypertrophy and Their Application to Resistance Training. J. Strength Cond. Res. 2010, 24, 2857–2872. [Google Scholar] [CrossRef]
  13. Seiler, S.; Hetlelid, K.J. The impact of rest duration on work intensity and RPE during interval training. Med. Sci. Sports Exerc. 2005, 37, 1601–1607. [Google Scholar] [CrossRef] [PubMed]
  14. Vandewalle, H.; Pérès, G.; Monod, H. Standard Anaerobic Exercise Tests. Sports Med. 1987, 4, 268–289. [Google Scholar] [CrossRef] [PubMed]
  15. Callahan, M.J.; Parr, E.B.; Hawley, J.A.; Camera, D.M. Can High-Intensity Interval Training Promote Skeletal Muscle Anabolism? Sports Med. 2021, 51, 405–421. [Google Scholar] [CrossRef]
  16. Esbjörnsson, M.; Rundqvist, H.C.; Mascher, H.; Österlund, T.; Rooyackers, O.; Blomstrand, E.; Jansson, E. Sprint exercise enhances skeletal muscle p70S6k phosphorylation and more so in women than in men. Acta Physiol. 2012, 205, 411–422. [Google Scholar] [CrossRef]
  17. Rundqvist, H.C.; Montelius, A.; Osterlund, T.; Norman, B.; Esbjornsson, M.; Jansson, E. Acute sprint exercise transcriptome in human skeletal muscle. PLoS ONE 2019, 14, e0223024. [Google Scholar] [CrossRef]
  18. Bell, K.E.; Séguin, C.; Parise, G.; Baker, S.K.; Phillips, S.M. Day-to-Day Changes in Muscle Protein Synthesis in Recovery From Resistance, Aerobic, and High-Intensity Interval Exercise in Older Men. J. Gerontol. Ser. A 2015, 70, 1024–1029. [Google Scholar] [CrossRef] [PubMed]
  19. Sultana, R.N.; Sabag, A.; Keating, S.E.; Johnson, N.A. The Effect of Low-Volume High-Intensity Interval Training on Body Composition and Cardiorespiratory Fitness: A Systematic Review and Meta-Analysis. Sports Med. 2019, 49, 1687–1721. [Google Scholar] [CrossRef]
  20. Erskine, R.M.; Fletcher, G.; Folland, J.P. The contribution of muscle hypertrophy to strength changes following resistance training. Eur. J. Appl. Physiol. 2014, 114, 1239–1249. [Google Scholar] [CrossRef]
  21. Seynnes, O.R.; de Boer, M.; Narici, M.V. Early skeletal muscle hypertrophy and architectural changes in response to high-intensity resistance training. J. Appl. Physiol. 2007, 102, 368–373. [Google Scholar] [CrossRef]
  22. Taber, C.B.; Vigotsky, A.; Nuckols, G.; Haun, C.T. Exercise-Induced Myofibrillar Hypertrophy is a Contributory Cause of Gains in Muscle Strength. Sports Med. 2019, 49, 993–997. [Google Scholar] [CrossRef]
  23. Schoenfeld, B.J.; Grgic, J.; Ogborn, D.; Krieger, J.W. Strength and Hypertrophy Adaptations Between Low- vs. High-Load Resistance Training: A Systematic Review and Meta-analysis. J. Strength Cond. Res. 2017, 31, 3508–3523. [Google Scholar] [CrossRef]
  24. Fliss, M.D.; Stevenson, J.; Mardan-Dezfouli, S.; Li, D.C.W.; Mitchell, C.J. Higher- and lower-load resistance exercise training induce load-specific local muscle endurance changes in young women: A randomised trial. Appl. Physiol. Nutr. Metab. 2022, 47, 1143–1159. [Google Scholar] [CrossRef] [PubMed]
  25. Lim, C.; Kim, H.J.; Morton, R.W.; Harris, R.; Phillips, S.M.; Jeong, T.S.; Kim, C.K. Resistance Exercise–induced Changes in Muscle Phenotype Are Load Dependent. Med. Sci. Sports Exerc. 2019, 51, 2578–2585. [Google Scholar] [CrossRef]
  26. Mitchell, C.J.; Churchward-Venne, T.A.; West, D.W.D.; Burd, N.A.; Breen, L.; Baker, S.K.; Phillips, S.M. Resistance exercise load does not determine training-mediated hypertrophic gains in young men. J. Appl. Physiol. 2012, 113, 71–77. [Google Scholar] [CrossRef] [PubMed]
  27. Bini, R.; Diefenthaler, F.; Carpes, F.; Mota, C.B. EXTERNAL WORK BILATERAL SYMMETRY DURING INCREMENTAL CYCLING EXERCISE. In Proceedings of the 25 International Symposium on Biomechanics in Sports, Ouro Preto, Brazil, 23–27 August 2007. [Google Scholar]
  28. Wirth, K.; Keiner, M.; Hartmann, H.; Sander, A.; Mickel, C. Effect of 8 weeks of free-weight and machine-based strength training on strength and power performance. J. Hum. Kinet. 2016, 53, 201–210. [Google Scholar] [CrossRef] [PubMed]
  29. Hackett, D.A.; Ghayomzadeh, M.; Farrell, S.N.; Davies, T.B.; Sabag, A. Influence of total repetitions per set on local muscular endurance: A systematic review with meta-analysis and meta-regression. Sci. Sports 2022, 37, 405–420. [Google Scholar] [CrossRef]
  30. Hallal, P.C.; Andersen, L.B.; Bull, F.C.; Guthold, R.; Haskell, W.; Ekelund, U. Global physical activity levels: Surveillance progress, pitfalls, and prospects. Lancet 2012, 380, 247–257. [Google Scholar] [CrossRef]
  31. Pharr, J.R.; Terencio, M.A.M.; Bungum, T. Physical Activity Guidelines Compliance and Its Relationship With Preventative Health Behaviors and Risky Health Behaviors. J. Phys. Act. Health 2020, 17, 1003–1008. [Google Scholar] [CrossRef]
  32. Page, M.J.; Moher, D.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ 2021, 372, n160. [Google Scholar] [CrossRef]
  33. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef] [PubMed]
  34. Sterne, J.A.C.; Savović, J.; Page, M.J.; Elbers, R.G.; Blencowe, N.S.; Boutron, I.; Cates, C.J.; Cheng, H.-Y.; Corbett, M.S.; Eldridge, S.M.; et al. RoB 2: A revised tool for assessing risk of bias in randomised trials. BMJ 2019, 366, l4898. [Google Scholar] [CrossRef] [PubMed]
  35. Farrah, K.; Young, K.; Tunis, M.C.; Zhao, L. Risk of bias tools in systematic reviews of health interventions: An analysis of PROSPERO-registered protocols. Syst. Rev. 2019, 8, 280. [Google Scholar] [CrossRef] [PubMed]
  36. Schünemann, H.; Brożek, J.; Guyatt, G.; Oxman, A. (Eds.) GRADE Handbook for Grading Quality of Evidence and Strength of Recommendations; Updated October 2013; The GRADE Working Group: Hamilton, ON, Canada, 2013; Available online: https://guidelinedevelopment.org/handbook (accessed on 10 April 2024).
  37. Borenstein, M.; Hedges, L.V.; Higgins, J.P.T.; Rothstein, H.R. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res. Synth. Methods 2010, 1, 97–111. [Google Scholar] [CrossRef]
  38. Riley, R.D.; Higgins, J.P.T.; Deeks, J.J. Interpretation of random effects meta-analyses. BMJ 2011, 342, d549. Available online: https://www.bmj.com/content/342/bmj.d549 (accessed on 12 May 2025). [CrossRef]
  39. Shuster, J.J. Empirical vs. natural weighting in random effects meta-analysis. Stat. Med. 2010, 29, 1259–1265. [Google Scholar] [CrossRef]
  40. Durlak, J.A. How to Select, Calculate, and Interpret Effect Sizes. J. Pediatr. Psychol. 2009, 34, 917–928. [Google Scholar] [CrossRef]
  41. Brown, E.C.; Hew-Butler, T.; Marks, C.R.C.; Butcher, S.J.; Choi, M.D. The Impact of Different High-Intensity Interval Training Protocols on Body Composition and Physical Fitness in Healthy Young Adult Females. BioRes. Open Access 2018, 7, 177–185. [Google Scholar] [CrossRef]
  42. Hurst, C.; Weston, K.L.; Weston, M. The effect of 12 weeks of combined upper- and lower-body high-intensity interval training on muscular and cardiorespiratory fitness in older adults. Aging Clin. Exp. Res. 2019, 31, 661–671. [Google Scholar] [CrossRef]
  43. Islam, H.; Siemens, T.L.; Matusiak, J.B.L.; Sawula, L.; Bonafiglia, J.T.; Preobrazenski, N.; Jung, M.E.; Gurd, B.J. Cardiorespiratory fitness and muscular endurance responses immediately and 2 months after a whole-body Tabata or vigorous-intensity continuous training intervention. Appl. Physiol. Nutr. Metab. 2020, 45, 650–658. [Google Scholar] [CrossRef]
  44. Blue, M.N.M.; Smith-Ryan, A.E.; Trexler, E.T.; Hirsch, K.R. The effects of high intensity interval training on muscle size and quality in overweight and obese adults. J. Sci. Med. Sport 2018, 21, 207–212. [Google Scholar] [CrossRef] [PubMed]
  45. Bhati, P.; Bansal, V.; Moiz, J.A. Comparison of different volumes of high intensity interval training on cardiac autonomic function in sedentary young women. Int. J. Adolesc. Med. Health 2019, 31, 20170073. [Google Scholar] [CrossRef]
  46. Bruseghini, P.; Capelli, C.; Calabria, E.; Rossi, A.P.; Tam, E. Effects of High-Intensity Interval Training and Isoinertial Training on Leg Extensors Muscle Function, Structure, and Intermuscular Adipose Tissue in Older Adults. Front. Physiol. 2019, 10, 1260. [Google Scholar] [CrossRef] [PubMed]
  47. Buckinx, F.; Gouspillou, G.; Carvalho, L.; Marcangeli, V.; El Hajj Boutros, G.; Dulac, M.; Noirez, P.; Morais, J.; Gaudreau, P.; Aubertin-Leheudre, M. Effect of High-Intensity Interval Training Combined with L-Citrulline Supplementation on Functional Capacities and Muscle Function in Dynapenic-Obese Older Adults. J. Clin. Med. 2018, 7, 561. [Google Scholar] [CrossRef] [PubMed]
  48. Clark, A.; De La Rosa, A.B.; DeRevere, J.L.; Astorino, T.A. Effects of various interval training regimes on changes in maximal oxygen uptake, body composition, and muscular strength in sedentary women with obesity. Eur. J. Appl. Physiol. 2019, 119, 879–888. [Google Scholar] [CrossRef]
  49. Couvert, A.; Goumy, L.; Maillard, F.; Esbrat, A.; Lanchais, K.; Saugrain, C.; Verdier, C.; Doré, E.; Chevarin, C.; Adjtoutah, D.; et al. Effects of a Cycling versus Running HIIT Program on Fat Mass Loss and Gut Microbiota Composition in Men with Overweight/Obesity. Med. Sci. Sports Exerc. 2024, 56, 839–850. [Google Scholar] [CrossRef]
  50. D’Alleva, M.; Vaccari, F.; Graniero, F.; Giovanelli, N.; Floreani, M.; Fiori, F.; Marinoni, M.; Parpinel, M.; Lazzer, S. Effects of 12-week combined training versus high intensity interval training on cardiorespiratory fitness, body composition and fat metabolism in obese male adults. J. Exerc. Sci. Fit. 2023, 21, 193–201. [Google Scholar] [CrossRef]
  51. Gillen, J.B.; Martin, B.J.; MacInnis, M.J.; Skelly, L.E.; Tarnopolsky, M.A.; Gibala, M.J. Twelve Weeks of Sprint Interval Training Improves Indices of Cardiometabolic Health Similar to Traditional Endurance Training despite a Five-Fold Lower Exercise Volume and Time Commitment. PLoS ONE 2016, 11, e0154075. [Google Scholar] [CrossRef]
  52. Higgins, M.F.; James, R.S.; Price, M.J. The effects of sodium bicarbonate (NaHCO3) ingestion on high intensity cycling capacity. J. Sports Sci. 2013, 31, 972–981. [Google Scholar] [CrossRef]
  53. Hirsch, K.R.; Greenwalt, C.E.; Saylor, H.E.; Gould, L.M.; Harrison, C.H.; Brewer, G.J.; Blue, M.N.M.; Ferrando, A.A.; Huffman, K.M.; Mayer-Davis, E.J.; et al. High-intensity interval training and essential amino acid supplementation: Effects on muscle characteristics and whole-body protein turnover. Physiol. Rep. 2021, 9, e14655. [Google Scholar] [CrossRef]
  54. Holmes, A.J.; Stratton, M.T.; Bailly, A.R.; Gottschall, J.S.; Feito, Y.; Ha, P.L.; Lavigne, A.; Persaud, K.; Gagnon, H.L.; Krueger, A.; et al. Effects of plyometric- and cycle-based high-intensity interval training on body composition, aerobic capacity, and muscle function in young females: A field-based group fitness assessment. Appl. Physiol. Nutr. Metab. 2023, 48, 932–945. [Google Scholar] [CrossRef]
  55. Keating, S.E.; Machan, E.A.; O’Connor, H.T.; Gerofi, J.A.; Sainsbury, A.; Caterson, I.D.; Johnson, N.A. Continuous Exercise but Not High Intensity Interval Training Improves Fat Distribution in Overweight Adults. J. Obes. 2014, 2014, 834865. [Google Scholar] [CrossRef]
  56. Lan, C.; Liu, Y.; Wang, Y. Effects of different exercise programs on cardiorespiratory fitness and body composition in college students. J. Exerc. Sci. Fit. 2022, 20, 62–69. [Google Scholar] [CrossRef] [PubMed]
  57. Li, X.; Seo, J.-W.; Bae, J.-H.; Jiang, S.; Sung, Y.; Jamrasi, P.; Ahn, S.Y.; Han, S.; Kim, S.; Kim, C.; et al. Effects of High-Intensity Interval Walking on Cognitive and Physical Functions in Older Adults: A Randomized Pilot Study. Cureus 2024, 16, e68165. [Google Scholar] [CrossRef]
  58. Lu, Y.; Wiltshire, H.D.; Baker, J.S.; Wang, Q. The Effects of Running Compared with Functional High-Intensity Interval Training on Body Composition and Aerobic Fitness in Female University Students. Int. J. Environ. Res. Public Health 2021, 18, 11312. [Google Scholar] [CrossRef]
  59. Macpherson, R.E.K.; Hazell, T.J.; Olver, T.D.; Paterson, D.H.; Lemon, P.W.R. Run Sprint Interval Training Improves Aerobic Performance but Not Maximal Cardiac Output. Med. Sci. Sports Exerc. 2011, 43, 115. [Google Scholar] [CrossRef]
  60. Marcangeli, V.; Youssef, L.; Dulac, M.; Carvalho, L.P.; Hajj-Boutros, G.; Reynaud, O.; Guegan, B.; Buckinx, F.; Gaudreau, P.; Morais, J.A.; et al. Impact of high-intensity interval training with or without L-citrulline on physical performance, skeletal muscle, and adipose tissue in obese older adults. J. Cachexia Sarcopenia Muscle 2022, 13, 1526–1540. [Google Scholar] [CrossRef] [PubMed]
  61. Marzuca-Nassr, G.N.; Artigas-Arias, M.; Olea, M.A.; SanMartín-Calísto, Y.; Huard, N.; Durán-Vejar, F.; Beltrán-Fuentes, F.; Muñoz-Fernández, A.; Alegría-Molina, A.; Sapunar, J.; et al. High-intensity interval training on body composition, functional capacity and biochemical markers in healthy young versus older people. Exp. Gerontol. 2020, 141, 111096. [Google Scholar] [CrossRef] [PubMed]
  62. Matsuo, T.; Saotome, K.; Seino, S.; Eto, M.; Shimojo, N.; Matsushita, A.; Iemitsu, M.; Ohshima, H.; Tanaka, K.; Mukai, C. Low-volume, high-intensity, aerobic interval exercise for sedentary adults: VO2max, cardiac mass, and heart rate recovery. Eur. J. Appl. Physiol. 2014, 114, 1963–1972. [Google Scholar] [CrossRef]
  63. Matsuo, T.; Saotome, K.; Seino, S.; Shimojo, N.; Matsushita, A.; Iemitsu, M.; Ohshima, H.; Tanaka, K.; Mukai, C. Effects of a Low-Volume Aerobic-Type Interval Exercise on VO2max and Cardiac Mass. Med. Sci. Sports Exerc. 2014, 46, 42. [Google Scholar] [CrossRef]
  64. Monsalves-Álvarez, M.; Jiménez, T.; Bunout, D.; Barrera, G.; Hirsch, S.; Sepúlveda-Guzman, C.; Silva, C.; Rodriguez, J.M.; Troncoso, R.; De La Maza, M.P. High-intensity interval training prevents muscle mass loss in overweight Chilean young adults during a hypocaloric-Mediterranean diet: A randomized trial. Front. Nutr. 2023, 10, 1181436. [Google Scholar] [CrossRef]
  65. Nybo, L.; Sundstrup, E.; Jakobsen, M.D.; Mohr, M.; Hornstrup, T.; Simonsen, L.; Bülow, J.; Randers, M.B.; Nielsen, J.J.; Aagaard, P.; et al. High-Intensity Training versus Traditional Exercise Interventions for Promoting Health. Med. Sci. Sports Exerc. 2010, 42, 1951–1958. [Google Scholar] [CrossRef]
  66. Osawa, Y.; Tabata, S.; Katsukawa, F.; Ishida, H.; Oguma, Y.; Kawai, T.; Itoh, H.; Okuda, S.; Matsumoto, H.; Azuma, K. Effects of 16-week high-intensity interval training using upper and lower body ergometers on aerobic fitness and morphological changes in healthy men: A preliminary study. Open Access J. Sports Med. 2014, 5, 257–265. [Google Scholar] [CrossRef]
  67. Rabiee, M.; Daryanoosh, F.; Salesi, M.; Tahmasebi, R.; Koushkie, M. The Effect of Eight Weeks of Mediterranean Diet and High-Intensity Interval Training on Body Composition in Obese and Overweight Premenopausal Women. Int. J. Nutr. Sci. 2023, 8, 117–124. [Google Scholar] [CrossRef]
  68. Robinson, M.M.; Dasari, S.; Konopka, A.R.; Johnson, M.L.; Manjunatha, S.; Esponda, R.R.; Carter, R.E.; Lanza, I.R.; Nair, K.S. Enhanced Protein Translation Underlies Improved Metabolic and Physical Adaptations to Different Exercise Training Modes in Young and Old Humans. Cell Metab. 2017, 25, 581–592. [Google Scholar] [CrossRef] [PubMed]
  69. Ramírez-Vélez, R.; Tordecilla-Sanders, A.; Téllez-T, L.A.; Camelo-Prieto, D.; Hernández-Quiñonez, P.A.; Correa-Bautista, J.E.; Garcia-Hermoso, A.; Ramírez-Campillo, R.; Izquierdo, M. Effect of Moderate- Versus High-Intensity Interval Exercise Training on Heart Rate Variability Parameters in Inactive Latin-American Adults: A Randomized Clinical Trial. J. Strength Cond. Res. 2020, 34, 3403–3415. [Google Scholar] [CrossRef] [PubMed]
  70. Sawyer, B.J.; Tucker, W.J.; Bhammar, D.M.; Ryder, J.R.; Sweazea, K.L.; Gaesser, G.A. Effects of high-intensity interval training and moderate-intensity continuous training on endothelial function and cardiometabolic risk markers in obese adults. J. Appl. Physiol. 2016, 121, 279–288. [Google Scholar] [CrossRef]
  71. Schleh, M.W.; Ahn, C.; Ryan, B.J.; Chugh, O.K.; Luker, A.T.; Luker, K.E.; Gillen, J.B.; Ludzki, A.C.; Van Pelt, D.W.; Pitchford, L.M.; et al. Both moderate- and high-intensity exercise training increase intramyocellular lipid droplet abundance and modify myocellular distribution in adults with obesity. Am. J. Physiol.-Endocrinol. Metab. 2023, 325, E466–E479. [Google Scholar] [CrossRef] [PubMed]
  72. Shepherd, S.O.; Cocks, M.; Tipton, K.D.; Ranasinghe, A.M.; Barker, T.A.; Burniston, J.G.; Wagenmakers, A.J.M.; Shaw, C.S. Sprint interval and traditional endurance training increase net intramuscular triglyceride breakdown and expression of perilipin 2 and 5: Perilipin expression and IMTG metabolism. J. Physiol. 2013, 591, 657–675. [Google Scholar] [CrossRef]
  73. Theofilidis, G.; Bogdanis, G.C.; Stavropoulos-Kalinoglou, A.; Krase, A.A.; Tsatalas, T.; Shum, G.; Sakkas, G.K.; Koutedakis, Y.; Karatzaferi, C. The effects of training with high-speed interval running on muscle performance are modulated by slope. Physiol. Rep. 2021, 9, e14656. [Google Scholar] [CrossRef]
  74. Tsekouras, Y.E.; Magkos, F.; Kellas, Y.; Basioukas, K.N.; Kavouras, S.A.; Sidossis, L.S. High-intensity interval aerobic training reduces hepatic very low-density lipoprotein-triglyceride secretion rate in men. Am. J. Physiol.-Endocrinol. Metab. 2008, 295, E851–E858. [Google Scholar] [CrossRef]
  75. Zhang, K.; Guo, B.; Yang, M.; Jia, Y.; Zhang, K.; Wang, L. The assessment of sports performance by grip pressure using flexible piezoresistive pressure sensors in seven sports events. Sci. Rep. 2024, 14, 31750. [Google Scholar] [CrossRef]
  76. Allemeier, C.A.; Fry, A.C.; Johnson, P.; Hikida, R.S.; Hagerman, F.C.; Staron, R.S. Effects of sprint cycle training on human skeletal muscle. J. Appl. Physiol. 1994, 77, 2385–2390. [Google Scholar] [CrossRef] [PubMed]
  77. Bagley, L.; Slevin, M.; Bradburn, S.; Liu, D.; Murgatroyd, C.; Morrissey, G.; Carroll, M.; Piasecki, M.; Gilmore, W.S.; McPhee, J.S. Sex differences in the effects of 12 weeks sprint interval training on body fat mass and the rates of fatty acid oxidation and VO2max during exercise. BMJ Open Sport Exerc. Med. 2016, 2, e000056. [Google Scholar] [CrossRef] [PubMed]
  78. De Souza, E.O.; Tricoli, V.; Aoki, M.S.; Roschel, H.; Brum, P.C.; Bacurau, A.V.N.; Silva-Batista, C.; Wilson, J.M.; Neves, M.; Soares, A.G.; et al. Effects of Concurrent Strength and Endurance Training on Genes Related to Myostatin Signaling Pathway and Muscle Fiber Responses. J. Strength Cond. Res. 2014, 28, 3215–3223. [Google Scholar] [CrossRef]
  79. Estes, R.R.; Malinowski, A.; Piacentini, M.; Thrush, D.; Salley, E.; Losey, C.; Hayes, E. The Effect of High Intensity Interval Run Training on Cross-sectional Area of the Vastus Lateralis in Untrained College Students. Int. J. Exerc. Sci. 2017, 10, 137–145. [Google Scholar] [CrossRef] [PubMed]
  80. Hashida, R.; Takano, Y.; Matsuse, H.; Kudo, M.; Bekki, M.; Omoto, M.; Nago, T.; Kawaguchi, T.; Torimura, T.; Shiba, N. Electrical Stimulation of the Antagonist Muscle During Cycling Exercise Interval Training Improves Oxygen Uptake and Muscle Strength. J. Strength Cond. Res. 2021, 35, 111–117. [Google Scholar] [CrossRef]
  81. Higgins, S.; Fedewa, M.V.; Hathaway, E.D.; Schmidt, M.D.; Evans, E.M. Sprint interval and moderate-intensity cycling training differentially affect adiposity and aerobic capacity in overweight young-adult women. Appl. Physiol. Nutr. Metab. 2016, 41, 1177–1183. [Google Scholar] [CrossRef]
  82. Joanisse, S.; Gillen, J.B.; Bellamy, L.M.; McKay, B.R.; Tarnopolsky, M.A.; Gibala, M.J.; Parise, G. Evidence for the contribution of muscle stem cells to nonhypertrophic skeletal muscle remodeling in humans. FASEB J. 2013, 27, 4596–4605. [Google Scholar] [CrossRef]
  83. Ramírez-Vélez, R.; Izquierdo, M.; Castro-Astudillo, K.; Medrano-Mena, C.; Monroy-Díaz, A.L.; Castellanos-Vega, R.D.P.; Triana-Reina, H.R.; Correa-Rodríguez, M. Weight Loss after 12 Weeks of Exercise and/or Nutritional Guidance Is Not Obligatory for Induced Changes in Local Fat/Lean Mass Indexes in Adults with Excess of Adiposity. Nutrients 2020, 12, 2231. [Google Scholar] [CrossRef]
  84. Yang, X.; Li, Y.; Mei, T.; Duan, J.; Yan, X.; McNaughton, L.; He, Z. Genome-wide Association Study of Exercise-induced Skeletal Muscle Hypertrophy and the Construction of Predictive Model. Physiol. Genom. 2024, 56, 578–589. [Google Scholar] [CrossRef]
  85. Bissas, A.; Paradisis, G.P.; Nicholson, G.; Walker, J.; Hanley, B.; Havenetidis, K.; Cooke, C.B. Development and Maintenance of Sprint Training Adaptations: An Uphill-Downhill Study. J. Strength Cond. Res. 2022, 36, 90–98. [Google Scholar] [CrossRef] [PubMed]
  86. Bornath, D.P.D.; Kenno, K.A. Physiological Responses to Increasing Battling Rope Weight During Two 3-Week High-Intensity Interval Training Programs. J. Strength Cond. Res. 2022, 36, 352–358. [Google Scholar] [CrossRef] [PubMed]
  87. Buckley, S.; Knapp, K.; Lackie, A.; Lewry, C.; Horvey, K.; Benko, C.; Trinh, J.; Butcher, S. Multimodal high-intensity interval training increases muscle function and metabolic performance in females. Appl. Physiol. Nutr. Metab. 2015, 40, 1157–1162. [Google Scholar] [CrossRef]
  88. Cao, M.; Yang, B.; Tang, Y.; Wang, C.; Yin, L. Effects of low-volume functional and running high-intensity interval training on physical fitness in young adults with overweight/obesity. Front. Physiol. 2024, 15, 1325403. [Google Scholar] [CrossRef] [PubMed]
  89. Caparrós-Manosalva, C.; Garrido-Muñoz, N.; Alvear-Constanzo, B.; Sanzana-Laurié, S.; Artigas-Arias, M.; Alegría-Molina, A.; Vidal-Seguel, N.; Espinoza-Araneda, J.; Huard, N.; Pagnussat, A.S.; et al. Effects of high-intensity interval training on lean mass, strength, and power of the lower limbs in healthy old and young people. Front. Physiol. 2023, 14, 1223069. [Google Scholar] [CrossRef]
  90. Ferley, D.D.; Osborn, R.W.; Vukovich, M.D. The Effects of Incline and Level-Grade High-Intensity Interval Treadmill Training on Running Economy and Muscle Power in Well-Trained Distance Runners. J. Strength Cond. Res. 2014, 28, 1298–1309. [Google Scholar] [CrossRef]
  91. Kayhan, R.F.; Bayrakdaroğlu, S.; Ceylan, H.İ.; Eken, Ö.; Bayrakdaroğlu, Y.; Badicu, G.; Al-Mhanna, S.B.; Enoiu, R.-S.; Ardigò1, L.P. Effects of different rest intervals in high intensity interval training programs on VO2max, body composition, and isokinetic strength and power. J. Mens Health 2024, 20, 1–11. [Google Scholar]
  92. Molinari, T.; Molinari, T.; Rabello, R.; Rodrigues, R. Effects of 8 weeks of high-intensity interval training or resistance training on muscle strength, muscle power and cardiorespiratory responses in trained young men. Sport Sci. Health 2022, 18, 887–896. [Google Scholar] [CrossRef]
  93. Schjerve, I.E.; Tyldum, G.A.; Tjønna, A.E.; Stølen, T.; Loennechen, J.P.; Hansen, H.E.M.; Haram, P.M.; Heinrich, G.; Bye, A.; Najjar, S.M.; et al. Both aerobic endurance and strength training programmes improve cardiovascular health in obese adults. Clin. Sci. 2008, 115, 283–293. [Google Scholar] [CrossRef]
  94. Sheykhlouvand, M.; Arazi, H.; Astorino, T.A.; Suzuki, K. Effects of a New Form of Resistance-Type High-Intensity Interval Training on Cardiac Structure, Hemodynamics, and Physiological and Performance Adaptations in Well-Trained Kayak Sprint Athletes. Front. Physiol. 2022, 13, 850768. [Google Scholar] [CrossRef]
  95. Sökmen, B.; Witchey, R.L.; Adams, G.M.; Beam, W.C. Effects of Sprint Interval Training With Active Recovery vs. Endurance Training on Aerobic and Anaerobic Power, Muscular Strength, and Sprint Ability. J. Strength Cond. Res. 2018, 32, 624–631. [Google Scholar] [CrossRef]
  96. Song, T.; Jilikeha, J.; Deng, Y. Physiological and Biochemical Adaptations to a Sport-Specific Sprint Interval Training in Male Basketball Athletes. J. Sports Sci. Med. 2023, 22, 605–613. [Google Scholar] [CrossRef] [PubMed]
  97. Venegas-Carro, M.; Herring, J.T.; Riehle, S.; Kramer, A. Jumping vs. running: Effects of exercise modality on aerobic capacity and neuromuscular performance after a six-week high-intensity interval training. PLoS ONE 2023, 18, e0281737. [Google Scholar] [CrossRef]
  98. Wong, P.Y.; Soh, S.M.M.; Chu, W.-J.M.; Lim, M.X.C.; Jones, L.E.; Selvaraj, S.; Chow, K.M.S.; Choo, H.W.D.; Aziz, A.R. A single all-out bout of 30-s sprint-cycle performed on 5 consecutive days per week over 6 weeks does not enhance cardiovascular fitness, maximal strength, and clinical health markers in physically active young adults. Eur. J. Appl. Physiol. 2024, 124, 1861–1874. [Google Scholar] [CrossRef]
  99. Zhang, B.; Zheng, C.; Hu, M.; Fang, Y.; Shi, Y.; Tse, A.C.-Y.; Lo, S.-K.; Wong, S.H.-S.; Sun, F. The effect of different high-intensity interval training protocols on cardiometabolic and inflammatory markers in sedentary young women: A randomized controlled trial. J. Sports Sci. 2024, 42, 751–762. [Google Scholar] [CrossRef]
  100. Nybo, L.; Pedersen, K.; Christensen, B.; Aagaard, P.; Brandt, N.; Kiens, B. Impact of carbohydrate supplementation during endurance training on glycogen storage and performance. Acta Physiol. 2009, 197, 117–127. [Google Scholar] [CrossRef] [PubMed]
  101. Bagley, L.; Al-Shanti, N.; Bradburn, S.; Baig, O.; Slevin, M.; McPhee, J.S. Sex Comparison of Knee Extensor Size, Strength, and Fatigue Adaptation to Sprint Interval Training. J. Strength Cond. Res. 2021, 35, 64–71. [Google Scholar] [CrossRef] [PubMed]
  102. Joan Dawson, M.; Gadian, D.G.; Wilkie, D.R. Muscular fatigue investigated by phosphorus nuclear magnetic resonance. Nature 1978, 274, 861–866. [Google Scholar] [CrossRef]
  103. Green, H.J. Mechanisms of muscle fatigue in intense exercise. J. Sports Sci. 1997, 15, 247–256. [Google Scholar] [CrossRef]
  104. Engstrom, C.M.; Loeb, G.E.; Reid, J.G.; Forrest, W.J.; Avruch, L. Morphometry of the human thigh muscles. A comparison between anatomical sections and computer tomographic and magnetic resonance images. J. Anat. 1991, 176, 139–156. [Google Scholar]
  105. Mitsiopoulos, N.; Baumgartner, R.N.; Heymsfield, S.B.; Lyons, W.; Gallagher, D.; Ross, R. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography. J. Appl. Physiol. 1998, 85, 115–122. [Google Scholar] [CrossRef]
  106. Mechelli, F.; Arendt-Nielsen, L.; Stokes, M.; Agyapong-Badu, S. Validity of Ultrasound Imaging Versus Magnetic Resonance Imaging for Measuring Anterior Thigh Muscle, Subcutaneous Fat, and Fascia Thickness. Methods Protoc. 2019, 2, 58. [Google Scholar] [CrossRef]
  107. Tavoian, D.; Ampomah, K.; Amano, S.; Law, T.D.; Clark, B.C. Changes in DXA-derived lean mass and MRI-derived cross-sectional area of the thigh are modestly associated. Sci. Rep. 2019, 9, 10028. [Google Scholar] [CrossRef]
  108. Bolanowski, M.; Nilsson, B.E. Assessment of human body composition using dual-energy x-ray absorptiometry and bioelectrical impedance analysis. Med. Sci. Monit. 2001, 7, 1029–1033. [Google Scholar] [PubMed]
  109. Pietiläinen, K.H.; Kaye, S.; Karmi, A.; Suojanen, L.; Rissanen, A.; Virtanen, K.A. Agreement of bioelectrical impedance with dual-energy X-ray absorptiometry and MRI to estimate changes in body fat, skeletal muscle and visceral fat during a 12-month weight loss intervention. Br. J. Nutr. 2013, 109, 1910–1916. [Google Scholar] [CrossRef] [PubMed]
  110. Burkhart, T.A.; Arthurs, K.L.; Andrews, D.M. Manual segmentation of DXA scan images results in reliable upper and lower extremity soft and rigid tissue mass estimates. J. Biomech. 2009, 42, 1138–1142. [Google Scholar] [CrossRef]
  111. Nordez, A.; Jolivet, E.; Südhoff, I.; Bonneau, D.; de Guise, J.A.; Skalli, W. Comparison of methods to assess quadriceps muscle volume using magnetic resonance imaging. J. Magn. Reson. Imaging 2009, 30, 1116–1123. [Google Scholar] [CrossRef] [PubMed]
  112. Saeterbakken, A.H.; Stien, N.; Paulsen, G.; Behm, D.G.; Andersen, V.; Solstad, T.E.J.; Prieske, O. Task Specificity of Dynamic Resistance Training and Its Transferability to Non-trained Isometric Muscle Strength: A Systematic Review with Meta-analysis. Sports Med. 2025, 55, 1651–1676. [Google Scholar] [CrossRef]
  113. Schoenfeld, B.J.; Wilson, J.M.; Lowery, R.P.; Krieger, J.W. Muscular adaptations in low- versus high-load resistance training: A meta-analysis. Eur. J. Sport Sci. 2016, 16, 1–10. [Google Scholar] [CrossRef] [PubMed]
  114. Pallares, J.G.; Barranco-Gil, D.; Rodríguez-Rielves, V.; De Pablos, R.; Buendía-Romero, Á.; Martínez-Cava, A.; Franco-López, F.; Sánchez-Redondo, I.R.; Iriberri, J.; Revuelta, C.; et al. Cyclists do not need to incorporate off-bike resistance training to increase strength, muscle-tendon structure, and pedaling performance: Exploring a high-intensity on-bike method. Biol. Sport 2025, 42, 185–195. [Google Scholar] [CrossRef] [PubMed]
  115. Salzgeber, A.; Porcari, J.P.; Howard, C.; Arney, B.E.; Kovacs, A.; Gillette, C.; Foster, C. Muscle Activation During Several Battle Rope Exercises. Master’s Thesis, Wisconsin-La Crosse University, La Crosse, WI, USA, 2019. [Google Scholar]
Figure 1. PRISMA flow diagram for study inclusion.
Figure 1. PRISMA flow diagram for study inclusion.
Sports 13 00293 g001
Figure 2. Assessment Tool [6,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99]. Green, yellow, and red circles indicate a low risk of bias, some concerns for a risk of bis, or a high risk of bias, respectively, for the given domain. D1 (bias arising from the randomization process), D2 (bias due to deviations from intended intervention), D3 (bias due to missing outcome data), D4 (bias in measurement of the outcome), D5 (bias in selection of the reported result).
Figure 2. Assessment Tool [6,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99]. Green, yellow, and red circles indicate a low risk of bias, some concerns for a risk of bis, or a high risk of bias, respectively, for the given domain. D1 (bias arising from the randomization process), D2 (bias due to deviations from intended intervention), D3 (bias due to missing outcome data), D4 (bias in measurement of the outcome), D5 (bias in selection of the reported result).
Sports 13 00293 g002
Figure 3. The Forest Plot for the meta-analysis between HIIT/SIT and MICT on FFM [55,56,59,62,63,65,70,71,72,81]. Gray boxes indicate study-specific estimates. Black lines through gray boxes represent 95% CIs. The gray diamond indicates overall pooled estimate. The thick black line indicates the predication interval.
Figure 3. The Forest Plot for the meta-analysis between HIIT/SIT and MICT on FFM [55,56,59,62,63,65,70,71,72,81]. Gray boxes indicate study-specific estimates. Black lines through gray boxes represent 95% CIs. The gray diamond indicates overall pooled estimate. The thick black line indicates the predication interval.
Sports 13 00293 g003
Figure 4. The Forest Plot for the meta-analysis between HIIT/SIT and CON on FFM [6,56,65,74,99]. Gray boxes indicate study-specific estimates. Black lines through gray boxes represent 95% CIs. The gray diamond indicates overall pooled estimate. The thick black line indicates the predication interval.
Figure 4. The Forest Plot for the meta-analysis between HIIT/SIT and CON on FFM [6,56,65,74,99]. Gray boxes indicate study-specific estimates. Black lines through gray boxes represent 95% CIs. The gray diamond indicates overall pooled estimate. The thick black line indicates the predication interval.
Sports 13 00293 g004
Figure 5. The Forest Plot for the meta-analysis between HIIT/SIT and RT on leg press 1-RM [78,92,93]. Gray boxes indicate study-specific estimates. Black lines through gray boxes represent 95% CIs. The gray diamond indicates overall pooled estimate. The thick black line indicates the predication interval.
Figure 5. The Forest Plot for the meta-analysis between HIIT/SIT and RT on leg press 1-RM [78,92,93]. Gray boxes indicate study-specific estimates. Black lines through gray boxes represent 95% CIs. The gray diamond indicates overall pooled estimate. The thick black line indicates the predication interval.
Sports 13 00293 g005
Table 1. An overview of the main characteristics of included studies measuring FFM. SIT (sprint interval training), HIIT (high-intensity interval training), S (seconds), Min (minutes), (LV (low volume), HV (high volume), Per (periodized), Trad (traditional), HR max (heart rate maximum), Watt-peak (peak wattage in a ramp test), VO2max/peak (maximal/peak oxygen consumption), MAS (maximum aerobic speed), FFM (fat-free mass), SMM (skeletal muscle mass) DXA (dual X-ray absorptiometry), BIA (bioelectrical impendence analysis), ADP (air displacement plethysmography), ↑ indicates a significant increase from baseline, ↔︎ indicates no change from baseline.
Table 1. An overview of the main characteristics of included studies measuring FFM. SIT (sprint interval training), HIIT (high-intensity interval training), S (seconds), Min (minutes), (LV (low volume), HV (high volume), Per (periodized), Trad (traditional), HR max (heart rate maximum), Watt-peak (peak wattage in a ramp test), VO2max/peak (maximal/peak oxygen consumption), MAS (maximum aerobic speed), FFM (fat-free mass), SMM (skeletal muscle mass) DXA (dual X-ray absorptiometry), BIA (bioelectrical impendence analysis), ADP (air displacement plethysmography), ↑ indicates a significant increase from baseline, ↔︎ indicates no change from baseline.
StudySample
Size
Training Status/AgeGroup NameProtocolModalityDuration (Weeks)Hypertrophy OutcomeMethod(s) of Assessment
Bhati 2019
[45]
17Sedentary, Young adultsHIIT (LV)1 × (4 min at 85–95% of HR max, 3 min at 70% HR max)Running6FFM ↑BIA
Bhati 2019
[45]
15Sedentary, Younger AdultsHIIT (HV)4 × (4 min at 85–95% of HR max, 3 min at 70% HR max)Running6FF︎M ↔︎BIA
Bruseghini 2019
[46]
12Recreational, Older AdultsHIIT7 × (2 min at 85–95% VO2max, 2 min rest)Cycling8FFM ↔︎DXA
Buckinx 2018
[47]
30Sedentary Obese, Older AdultsHIIT10 × (30 s at 80–85% HR max, 90 s at 65% HR max)Elliptical12FFM ↑DXA
Clark 2019
[48]
8Sedentary Obese, AdultsHIIT (Per)6–10 × (20 s–2 min at 65–110% peak power, 1–2 min rest)Cycling6FFM ↔︎ADP
Clark 2019
[48]
9Sedentary Obese, AdultsHIIT (Trad)10 × (1 min at 70–85% peak power, 60 s rest)Cycling6FFM ↑ADP
Couvert 2024
[49]
8TS Unknown, Obese/Overweight, AdultsHIIT9 × (45 s at 80–85% HR max, 90 s active recovery)Running12FFM ↔︎DXA
Couvert 2024
[49]
8TS Unknown, Obese/Overweight, AdultsHIIT10 × (45 s at 80–85% HR max, 90 s active recovery)Cycling12FFM ↔︎DXA
D’Alleva 2023
[50]
16Sedentary, Obese, AdultsHIIT5–7 × (2 min at 95% VO2peak, 1 min at 50% VO2peak)Running12FFM ↔︎BIA
Gillen 2016
[51]
8Sedentary Obese, AdultsHIIT (Fed)10 × (1 min at 90% HR max, 1 min at 50 W)Cycling6FFM ↔︎DXA
Gillen 2016
[51]
8Sedentary Obese, AdultsHIIT (Fasted)10 × (1 min at 90% HR max, 1 min at 50 W)Cycling6FFM ↔︎DXA
Higgins 2016
[52]
23Sedentary Obese, Younger AdultsSIT4–7 × (30 s at maximal effort, 4 min of active rest)Cycling6FFM ↔︎DXA
Hirsch 2021
[53]
19Untrained Obese, AdultsHIIT6–10 × (1 min at 90% watt-max, 60 s rest)Cycling8FFM ↑DXA
Holmes 2023
[54]
15Recreational, Younger AdultsHIIT30 min (20–80 s at unknown intensity, 10–60 s rest)Cycling8FFM ↑DXA
Keating 2014
[55]
13Sedentary, AdultsHIIT4–6 × (30–60 s at 120% VO2peak, 2–3 min at 30 W)Cycling12FFM ↔︎DXA
Lan 2022
[56]
12Sedentary, Younger AdultsHIIT4 × (4 min at 85–95% HR max, 3 min at 64–76% HR max)Running8FFM ↔︎, SMM ↔︎BIA
Li 2024
[57]
13Untrained, Older AdultsHIIT5 × (3 min at 85% HR max, 3 min at 55% HR max)Walking8SMM ↑BIA
Lu 2021
[58]
10Untrained, Younger AdultsSIT4 × (30 s at max effort, 30 s restRunning12FFM ↑BIA
MacPherson 2011
[59]
10Recreational, Younger AdultsSIT4–6 × (30 s at max effort, 4 min active rest)Running6FFM ↑ADP
Marcangeli 2022
[60]
45Sedentary Obese, Older AdultsHIIT10 × (30 s at 80–85% HR max, 90 s at 65% HR max)Elliptical12FFM ↑DXA
Marzuca-Nassr 2020
[61]
10Sedentary, Younger AdultsHIIT10 × (1 min at 90% HR max, 2 min rest)Cycling12FFM ↔︎DXA
Marzuca-Nassr 2020
[61]
10Sedentary, Older AdultsHIIT10 × (1 min at 90% HR max, 2 min rest)Cycling12FFM ↔︎DXA
Matsuo 2014a
[62]
12Sedentary, AdultsHIIT3 × (3 min at 80–85% VO2max, 2 min at 50% VO2max)Cycling8FFM ↔︎DXA
Matsuo 2014b
[63]
14Sedentary, AdultsSIT7 × (30 s at 120% VO2max, 15 s rest)Cycling8FFM ↑DXA
Matsuo 2014b
[63]
14Sedentary, AdultsHIIT3 × (3 min 80–90% VO2max, 2 min at 50% VO2max)Cycling8FFM ↑DXA
Monsalves-Álvarez
[64]
11TS Unknown, Overweight/Obese AdultsHIIT10 × (1 min at 85–90% HR max, 1 min at 50 W)Cycling12FFM ↔︎DXA
Nybo 2010
[65]
8Untrained, AdultsHIIT5 × (2 min at 95% HR max, 1 min rest)Running12FFM ↔︎DXA
Osawa 2014
[66]
7Untrained, AdultsHIIT (Leg)8–12 × (1 min at >90% watt-peak, 60 s active rest)Cycling16FFM ↔︎DXA
Osawa 2014
[66]
5Untrained, AdultsHIIT (Arm/Leg)8–12 × (60 s at >90% watt-peak, 60 s active rest) (half arm, half leg)Cycling/Arm Cycling16FFM ↔︎DXA
Rabbiee 2023
[67]
9Sedentary, Obese/Overweight, AdultsHIIT4–6 × (1 min at 90–95% HR max, 1 min rest)Cycling8SMM ↔︎BIA
Robinson 2017
[68]
14Untrained, Younger AdultsHIIT (Young)4 × (4 min at >90% of VO2max, 3 min at 0 W)Cycling12FFM ↑DXA
Robinson 2017
[68]
9Untrained, Older AdultsHIIT (Old)4 × (4 min at >90% of VO2max, 3 min at 0 W)Cycling12FFM ↑DXA
Ramirez-Velez 2020a
[69]
14Sedentary, AdultsHIIT4 × (4 min at 85–95% HR max, 4 min at 65% HR max) week 3–12 max) week 3–12Run/Walk with Incline12FFM ↑DXA
Sawyer 2016
[70]
9TS Unknown Obese, AdultsHIIT10 × (1 min at 90–95% of HR max, 1 min at 25–50 W)Cycling8FFM ↔︎DXA
Schleh 2023
[71]
19Sedentary, Obese, AdultsHIIT10 × (1 min at 90% HR max, 1 min at 65% HR max)Cycling/Rowing/
Running/
Elliptical
12FFM ↔︎DXA
Shepherd 2013
[72]
42Sedentary, AdultsHIIT4–12 × (15–60 s at >90% HR max, 45–120 s active rest)Cycling10FFM ↔︎BIA
Theofilidis 2021
[73]
7Recreational, AdultsHIIT (Up)10 × (30 s at 90% MAS +10% grade, 60 s rest)Running8FFM ↔︎BIA
Theofilidis 2021
[73]
7Recreational, AdultsHIIT (Down)10 × (30 s at 90% MAS −10% grade, 60 s rest)Running8FFM ↔︎BIA
Tsekouras 2008
[74]
7Sedentary, Younger AdultsHIIT4 × (4 min at 90% VO2peak, 4 min at 60% VO2peak)Running8FFM ↔︎DXA
Zhang 2024
[75]
14Sedentary, Younger AdultsHIIT2–3 × (12–15 × 30 s at max effort, 10 s rest)Cycling8FFM ↔︎BIA
Ziemann 2011
[6]
10Recreational, Younger AdultsHIIT6 × (90 s at 80% VO2max, 3 min rest)Cycling6FF︎M ↔︎BIA
Table 2. An overview of the main characteristics of included studies measuring localized muscle hypertrophy. SIT (sprint interval training), HIIT (high-intensity interval training), S (seconds), Min (minutes), HR max (heart rate maximum), Watt-peak (peak wattage in a ramp test), VO2max/peak (maximal/peak oxygen consumption), MAS (maximum aerobic speed), CSA (cross-sectional area), LLM (leg lean mass), Quad (quadriceps), RF (rectus femoris), Thigh LM (thigh lean mass), VL (vastus lateralis), ALM (arm lean mass), LBLM (lower body lean mass), UBLM (upper body lean mass), Psoas (psoas major), Alab (anterolateral abdominal), Trunk LM (trunk lean mass), DXA (dual X-ray absorptiometry), BIA (bioelectrical impendence analysis), MRI (magnetic resonance imaging), ↑ indicates a significant increase from baseline, ↔︎ indicates no change from baseline, ↓ indicates a significant decrease from baseline.
Table 2. An overview of the main characteristics of included studies measuring localized muscle hypertrophy. SIT (sprint interval training), HIIT (high-intensity interval training), S (seconds), Min (minutes), HR max (heart rate maximum), Watt-peak (peak wattage in a ramp test), VO2max/peak (maximal/peak oxygen consumption), MAS (maximum aerobic speed), CSA (cross-sectional area), LLM (leg lean mass), Quad (quadriceps), RF (rectus femoris), Thigh LM (thigh lean mass), VL (vastus lateralis), ALM (arm lean mass), LBLM (lower body lean mass), UBLM (upper body lean mass), Psoas (psoas major), Alab (anterolateral abdominal), Trunk LM (trunk lean mass), DXA (dual X-ray absorptiometry), BIA (bioelectrical impendence analysis), MRI (magnetic resonance imaging), ↑ indicates a significant increase from baseline, ↔︎ indicates no change from baseline, ↓ indicates a significant decrease from baseline.
StudySample
Size
Training
Status/Age
Group NameProtocolModalityDuration
(Weeks)
Hypertrophy
Outcome
Method(s) of Assessment
Allemeier 1994
[76]
11Untrained,
Young Adults
SIT3 × (30 s Wingate, 20 min rest)Cycling6Type 1 CSA ↔︎, Type 2a CSA ↔︎, Type 2× CSA ↔︎Histology
Bagley 2016
[77]
15Recreational,
Adults
SIT (Female)4 × (20 s at 175–200% VO2peak, 2 min rest)Cycling12LLM ↔︎, Thigh Lean Mass ↔︎, Quad CSA ↑DXA, MRI
Bagley 2016
[77]
16Recreational,
Adults
SIT (Male)4 × (20 s at 175–200% VO2peak, 2 min rest)Cycling12LLM ↔︎,Thigh Lean Mass ↔︎, Quad CSA ↑DXA, MRI
Bruseghini 2019
[46]
12Recreational,
Older Adults
HIIT7 × (2 min at 85–95% VO2max, 2 min rest)Cycling8Quad CSA ↑, Quad Volume ↑MRI
De Souza 2014
[78]
8Recreational,
Adults
HIIT15–20 × (60 s at VO2peak, rest time/intensity not reported)Running8Thigh CSA ↔︎
Type 1 CSA ↔︎, Type 2a CSA ↔︎, Type 2× CSA ↔︎
MRI, Histology
Estes 2017
[79]
12Recreational,
Younger Adults
HIIT4 × (4 min at 90–95% HR max, 3 min rest)Running10VL CSA ↑Ultrasound
Gillen 2016
[51]
8Sedentary Obese,
Adults
HIIT (Fed)10 × (1 min at 90% HR max, 1 min at 50 W)Cycling6LLM ↑, Gynoid LM ↑DXA
Gillen 2016
[51]
8Sedentary Obese,
Adults
HIIT (Fasted)10 × (1 min at 90% HR max, 1 min at 50 W)Cycling6LLM ↑, Gynoid LM ↑DXA
Hashida 2016
[80]
15Recreational,
Younger Adults
HIIT5 × (2 min at 60–90% VO2peak, 2 min at 40% VO2peak)Cycling6RF Muscle Thickness ↔︎Ultrasound
Higgins 2016
[81]
23Sedentary Obese, Younger AdultsSIT4–7 × (30 s at maximal effort, 4 min of active rest)Cycling6LLM ↑DXA
Hirsch 2021
[53]
19Untrained Obese,
Adults
HIIT6–10 × (1 min at 90%-watt-max, 60 s rest)Cycling8Thigh LM ↑, VL CSA ↑, VL Volume ↑DXA, Ultrasound
Holmes 2023
[54]
15Recreational,
Younger Adults
HIIT30 min (20–80 s at unknown intensity, 10–60 s rest)Cycling8LLM ↔︎, ALM ↔︎, VL CSA ↔︎DXA, Ultrasound
Joanisse 2013
[82]
15Sedentary,
Adults
HIIT10 × (1 min at 90% HR max, 1 min at 50 W or passive rest)Cycling6Type 1 CSA ↔︎, Type 2 CSA ↔︎, Hybrid CSA ↔︎Histology
Marcangeli 2022
[60]
45Sedentary Obese,
Older Adults
HIIT10 × (30 s at 80–85% HR max, 90 s at 65% HR max)Elliptical12LLM ↑, ALM ↔︎DXA
Marzuca-Nassr 2020
[61]
10Sedentary,
Younger Adults
HIIT10 × (1 min at 90% HR max, 2 min rest)Cycling12LLM ↑DXA
Marzuca-Nassr 2020
[67]
10Sedentary,
Older Adults
HIIT10 × (1 min at 90% HR max, 2 min rest)Cycling12LLM ↔︎DXA
Monsalves-Álvarez 2023
[64]
11TS Unknown, Overweight/Obese AdultsHIIT10 × (1 min at 85–90% HR max, 1 min at 50 W)Cycling12RF CSA ↔︎Ultrasound
Nybo 2010
[65]
8Untrained,
Adults
HIIT5 × (2 min at 95% HR max, 1 min rest)Running12LLM ↔︎DXA
Osawa 2014
[66]
7Untrained,
Adults
HIIT (Leg)8–12 × (1 min at >90% watt-peak, 60 s active rest)Cycling16Quad CSA ↑, Hamstring CSA ↔︎, LBLM ↔︎, UBLM, ↔︎ Psoas CSA ↔︎, Alab CSA ↔︎, Spinal CSA ↔︎DXA, MRI
Osawa 2014
[66]
5Untrained,
Adults
HIIT (Arm/Leg)8–12 × (60 s at >90% watt-peak, 60 s active rest) (half arm, half leg)Cycling/Arm Cycling16Quad CSA ↑, Hamstring CSA LBLM ↔︎, UBLM ↔︎, Psoas CSA ↑, Alab CSA ↔︎, Spinal CSA ↔︎DXA, MRI
Ramirez-Velez 2020b
[83]
11Sedentary,
Adults
HIIT4 × (4 min at 85–95% HR max, 4 min at 65% HR max) week 3–12Running12LLM ↔︎, ALM ↔︎, Trunk LM ↔︎BIA
Theofilidis 2021
[73]
7Recreational,
Adults
HIIT (Uphill)10 × (30 s at 90% MAS +10% grade, 60 s rest)Hill Running8VL Thickness↓, VL Length ↓BIA, Ultrasound
Theofilidis 2021
[73]
7Recreational,
Adults
HIIT (Downhill)10 × (30 s at 90% MAS −10% grade, 60 s rest)Running8VL Thickness↓, VL Length ↓BIA, Ultrasound
Yang 2024
[84]
261Sedentary,
Younger Adults
HIIT4 × (4 min at 80–90% VO2max, 3 min recovery at 50–55% VO2max) week 5–12Running12RF Muscle Thickness ↑Ultrasound
Table 3. An overview of the main characteristics of included studies measuring strength outcomes. SIT (sprint interval training), HIIT (high-intensity interval training), S (seconds), Min (minutes), m (meters), W (Watts), RPE (rating of perceived exertion), T max (time to exhaustion), V max (maximum velocity), LV (low volume), HV (high volume), Per (periodized), Trad (traditional), HR max (heart rate maximum), VO2max/peak (maximal/peak oxygen consumption), MAS (maximum aerobic speed), ISOM (isometric), ISOK (isokinetic), 1-RM (1 repetition maximum), PF (plantar flexion), ↑ indicates a significant increase from baseline, ↔︎ indicates no change from baseline, ↓ indicates a significant decrease from baseline.
Table 3. An overview of the main characteristics of included studies measuring strength outcomes. SIT (sprint interval training), HIIT (high-intensity interval training), S (seconds), Min (minutes), m (meters), W (Watts), RPE (rating of perceived exertion), T max (time to exhaustion), V max (maximum velocity), LV (low volume), HV (high volume), Per (periodized), Trad (traditional), HR max (heart rate maximum), VO2max/peak (maximal/peak oxygen consumption), MAS (maximum aerobic speed), ISOM (isometric), ISOK (isokinetic), 1-RM (1 repetition maximum), PF (plantar flexion), ↑ indicates a significant increase from baseline, ↔︎ indicates no change from baseline, ↓ indicates a significant decrease from baseline.
AuthorSample SizeTraining Status/AgeGroup NameProtocolModalityDuration (Weeks)Strength Outcome
Bagley 2016
[77]
15Recreational, AdultsSIT (Female)4 × (20 s at 175–200% VO2peak, 2 min rest)Cycling12ISOM Knee Extension (90°) ↔︎, ISOK Knee Extension (60°/s) ↔︎, ISOK Knee Extension (120°/s) ↔︎, ISOK Knee Extension (180°/s) ↔︎, ISOK Knee Extension (240°/s)
Bagley 2016
[77]
16Recreational, AdultsSIT (Male)4 × (20 s at 175–200% VO2peak, 2 min rest)Cycling12ISOM Knee Extension (90°) ↔︎, ISOK Knee Extension (60°/s) ↔︎, ISOK Knee Extension (120°/s) ↔︎, ISOK Knee Extension (180°/s) ↔︎, ISOK Knee Extension (240°/s) ↔︎
Bhati 2019
[45]
17Sedentary, Younger AdultsHIIT (LV)1 × (4 min at 85–95% of HR max, 3 min at 70% HR max)Running6ISOM Knee Extension (90°) ↔︎
Bhati 2019
[45]
15Sedentary, Younger AdultsHIIT (HV)4 × (4 min at 85–95% HR max, 3 min at 70% HR max)Running6ISOM Knee Extension (90°) ↔︎
Bissas 2022
[85]
14Recreational, Younger AdultsSIT (Up/Down)6 × (80 m at max effort, 4–6 min rest)Running6ISOM Knee Extension (107°) ↑, ISOM Knee Flexion (107°) ↔︎
Bissas 2022
[85]
7Recreational, Younger AdultsSIT6 × (80 m at max effort, 4–6 min rest)Running6ISOM Knee Extension (107°) ↔︎, ISOM Knee Flexion (107°) ↔︎
Bornath and Kenno 2022
[86]
15Recreational, Younger AdultsSIT (Female)10 × (30 s at max effort, 60 s rest)Battle Ropes6ISOM Shoulder Flexion (90°) ↑, ISOM Shoulder Extension (90°) ↑
Bornath and Kenno 2022
[86]
18Recreational, Younger AdultsSIT (Male)10 × (30 s at max effort, 60 s rest)Battle Ropes6ISOM Shoulder Flexion (90°) ↑, ISOM Shoulder Extension (90°) ↑
Bruseghini 2019
[46]
12Recreational, Older AdultsHIIT7 × (2 min at 85–95% VO2max, 2 min rest)Cycling8ISOM Knee Extension (90°) ↔︎, ISOM Knee Extension (60°) ↑, Eccentric ISOK Knee Extension (60°/s) ↔︎, Eccentric ISOK Knee Extension (120°/s) ↔︎, ISOK Knee Extension (60°/s) ↔︎, ISOK Knee Extension (120°/s) ↔︎
Buckinx 2018
[47]
30Sedentary Obese, Older AdultsSIT10 × (30 s at 80–85% HR max, 90 s at 65% HR max)Elliptical12ISOM Knee Extension (135°) ↔︎
Buckley 2015
[87]
14Recreational, Younger AdultsHIIT6 × (1 min at RPE of 9–10/10, 3 min rest)Rowing6Squat 1-RM ↔︎, Deadlift 1-RM ↔︎
Cao 2024
[88]
12Sedentary, Younger AdultsSIT4 × (4 × 30 s at 100–120% MAS, 30 s rest at 50% MAS)Running12Back Extension Force ↑, Hand grip Strength ↑
Clark 2019
[48]
8Sedentary Obese, AdultsHIIT (Per)6–10 × (20 s–2 min at 65–110% peak power, 1–2 min rest)Cycling6ISOK Knee Extension (60°/s) ↔︎, ISOK Knee Flexion (60°/s) ↔︎
Clark 2019
[48]
9Sedentary Obese, AdultsHIIT (Trad)10 × (1 min at 70–85% peak power, 60 s rest)Cycling6ISOK Knee Extension (60°/s) ↔︎, ISOK Knee Flexion (60°/s) ↔︎
Caparrós-Manosalva 2023
[89]
9Untrained, Younger AdultsHIIT(Young)10 × (1 min at 90% HR max, 2 min rest)Cycling12ISOM Knee Extension (90°) ↑
Caparrós-Manosalva 2023
[89]
9Untrained, Older AdultsHIIT (Old)10 × (1 min at 90% HR max, 2 min rest)Cycling12ISOM Knee Extension (90°) ↑
De Souza 2014
[78]
8Recreational, Younger AdultsHIIT15–20 × (60 s at VO2peak, rest time/intensity not reported)Running8Leg Press 1RM ↔︎
Ferley 2014
[90]
12Endurance Trained, Younger AdultsSIT (Flat)4–6 × (60% T max at V max, time to 65% HR max)Running6ISOK Knee Flexion (90°/s) ↔︎, ISOK Knee Flexion (180°/s) ↑, ISOK Knee Flexion (300°/s) ↑
Ferley 2014
[90]
12Endurance Trained, Younger AdultsSIT (Up)10–14 × (30 s at V max, time to 65% HR max)Running6ISOK Knee Flexion (90°/s) ↔︎, ISOK Knee Flexion (180°/s) ↑, ISOK Knee Flexion (300°/s) ↑
Hashida 2021
[80]
15Recreational, Younger AdultsHIIT5 × (2 min at 60–90% VO2peak, 2 min 40% VO2peak)Cycling6ISOK Knee Extension (60°/s) ↔︎
Holmes 2023
[54]
15Recreational, Younger AdultsHIIT30 min (20–80 s at unknown intensity, 10–60 s rest)Cycling8ISOK Knee Extension (60°/s) ↔︎, PF Extension (60°/s) ↔︎
Kayhan 2024
[91]
9Recreational, Younger AdultsHIIT (Short rest)2 × 300 m, 2 × 300 m, 2 × 400 m, 2 × 300, 2 × 200, all at 85% HRR, rest until 45% HRRRunning8ISOK Knee Extension (60°/s) ↔︎, ISOK Knee Flexion (60°/s) ↔︎, ISOK Knee Extension (240°/s) ↔︎, ISOK Knee Flexion (240°/s) ↔︎
Kayhan 2024
[91]
10Recreational, Younger AdultsHIIT (Long rest)2 × 300 m, 2 × 300 m, 2 × 400 m, 2 × 300, 2 × 200, all at 85% HRR, rest until 35% HRRRunning8ISOK Knee Extension (60°/s) ↔︎, ISOK Knee Flexion (60°/s) ↔︎, ISOK Knee Extension (240°/s) ↔︎, ISOK Knee Flexion (240°/s) ↔︎
Li 2024
[57]
13Untrained, Older AdultsHIIT5 × (3 min at 85% HR max, 3 min at 55% HR max)Walking8Hand Grip Strength ↓
Monsalves-Álvarez 2023
[64]
11TS Unknown, Overweight/Obese AdultsHIIT10 × (1 min at 85–90% HR max, 1 min at 50 W)Cycling12Hand Grip Strength ↔︎, Quadriceps Strength ↔︎
Molinari 2022
[92]
9Resistance/Endurance Trained, Younger AdultsHIIT10 × (60 s at 85–95% HR max, 3 min walk)Running8Leg Press 1-RM ↑, Knee Extension 1-RM ↔︎
Robinson 2017
[68]
14Untrained, Younger AdultsHIIT (Young)4 × (4 min at >90% of VO2max, 3 min at 0 W)Cycling12Leg Press 1-RM ↔︎
Robinson 2017
[68]
9Untrained, Older AdultsHIIT (Old)4 × (4 min at >90% of VO2max, 3 min at 0 W)Cycling12Leg Press 1-RM ↔︎
Schjerve 2008
[93]
14TS Unknown, Obese, AdultsHIIT4 × (4 min at HRmax, 3 min at 50–60% of HR max)Running12Leg Press 1-RM ↔︎
Sheykhlouvand 2022
[94]
8Endurance Trained, Younger AdultsHIIT6 × (unknown duration at 100% VO2peak velocity, 1:1 work to rest ratio)Kayaking81-RM One Arm Cable Row ↔︎
Sökmen 2018
[95]
20Recreational, Younger AdultsSIT40 min (200 m sprint, 200 m walk)Running10ISOK Knee Extension (60°/s) ↔︎, ISOK Knee Flexion (60°/s) ↔︎, ISOK Knee Extension (300°/s) ↑, ISOK Knee Flexion (300°/s) ↑
Song 2023
[96]
10Trained, Younger AdultsSIT3 × (7–10 × 15 s at max effort, 15 s rest)Running6Leg Press 1-RM ↔︎
Theofilidis 2021
[73]
7Recreational, AdultsSIT(Up)10 × (30 s at 90% MAS +10% grade, 60 s rest)Running8ISOM Knee Extension (65°) ↔︎, ISOM Knee Flexion (30°) ↔︎, ISOK Knee Extension (60°/s) ↔︎
Theofilidis 2021
[73]
7Recreational, AdultsSIT (Down)10 × (30 s at 90% MAS −10% grade, 60 s rest)Running8ISOM Knee Extension (65°) ↔︎, ISOM Knee Flexion (30°) ↔︎, ISOK Knee Extension (60°/s) ↔︎
Venegas-Carro 2023
[97]
15Recreational, Younger AdultsSIT4–8 × (20–30 s max effort, 10–40 s rest)Running6ISOM Knee Extension (90°) ↔︎, ISOM PF ↔︎
Wong 2024
[98]
11Recreational, Younger AdultsSIT1 × (30 s at max effort) Cycling6ISOK Knee Extension (30°/s) ↔︎, ISOK Knee Flexion (30°/s) ↔︎, ISOK Knee Extension (300°/s) ↔︎, ISOK Knee Flexion (300°/s) ↔︎,
Zhang 2024
[99]
14Sedentary, Younger AdultsHIIT2–3 × (12–15 × 30 s at max effort, 10 s rest)Cycling8Grip Strength ↔︎
Table 4. An overview of the main characteristics of included studies measuring muscle endurance. SIT (sprint interval training), HIIT (high-intensity interval training), S (seconds), Min (minutes), RPE (rating of perceived exertion), VO2max/peak (maximal/peak oxygen consumption), MAS (maximum aerobic speed), ISOK (isokinetic), 1-RM (1 repetition maximum), MVC (maximal volitional contraction)), ↑ indicates a significant increase from baseline, ↔︎ indicates no change from baseline.
Table 4. An overview of the main characteristics of included studies measuring muscle endurance. SIT (sprint interval training), HIIT (high-intensity interval training), S (seconds), Min (minutes), RPE (rating of perceived exertion), VO2max/peak (maximal/peak oxygen consumption), MAS (maximum aerobic speed), ISOK (isokinetic), 1-RM (1 repetition maximum), MVC (maximal volitional contraction)), ↑ indicates a significant increase from baseline, ↔︎ indicates no change from baseline.
AuthorSample SizeTraining Status/AgeGroup NameProtocolModalityDuration (Weeks)ME Outcome
Bagley 2016
[77]
15Recreational, AdultsSIT (Female)4 × (20 s at 175–200% VO2peak, 2 min rest)Cycling12Fatigue index—60 reps at max intensity (Knee Extension ISOK 120°/s) ↑
Bagley 2016
[77]
16Recreational, AdultsSIT (Male)4 × (20 s at 175–200% VO2peak, 2 min rest)Cycling12Fatigue index—60 reps at max intensity (Knee Extension ISOK 120°/s) ↑
Bornath and Kenno 2022
[86]
15Recreational, Younger AdultsSIT (Female)10 × (30 s at max effort, 60 s rest)Battle Ropes6Sit-ups (reps completed) ↑, Push-ups (reps completed) ↑
Bornath and Kenno 2022
[86]
18Recreational, Younger AdultsSIT (Male)10 × (30 s at max effort, 60 s rest)Battle Ropes6Sit-ups (reps completed) ↑, Push-ups (reps completed) ↑
Buckley 2015
[87]
15Recreational, Younger AdultsHIIT6 × (1 min at RPE 9–10/10, 3 min rest)Rowing670% pre-training squat 1-RM (reps completed) ↔︎
Cao 2024
[88]
12Sedentary, Younger AdultsSIT4 × (4 × 30 s at 100–120% MAS, 30 s rest at 50% MAS)Running12Push-ups (reps completed) ↑
Theofilidis 2021
[73]
7Recreational, AdultsHIIT (Up)10 × (30 s at 90% MAS +10% grade, 60 s rest)Running8Work till >50% MVC not maintained (Knee Extension ISOK 60°/s) ↑
Theofilidis 2021
[73]
7Recreational, AdultsHIIT (Down)10 × (30 s at 90% MAS −10% grade, 60 s rest)Running8Work till >50% MVC not maintained (Knee Extension ISOK 60°/s) ↑
Table 5. Pooled weighted effect sizes and percentage gains in FFM, LLM, and quadriceps CSA. FFM (fat-free mass), LLM (leg lean mass), CSA (cross-sectional area), ES (effect size), CI (confidence interval).
Table 5. Pooled weighted effect sizes and percentage gains in FFM, LLM, and quadriceps CSA. FFM (fat-free mass), LLM (leg lean mass), CSA (cross-sectional area), ES (effect size), CI (confidence interval).
OutcomeWeighted ES95% CIWeighted %∆
FFM (N = 463)0.06−0.03, 0.151.17 ± 1.64%
LLM (N = 159)0.040.02, 0.070.61 ± 2.36%
Quadriceps CSA (N = 71)0.360.34, 0.374.72 ± 1.35%
Table 6. Pooled weighted effect sizes and percentage gains in leg press 1-RM, ISOK 60, and ISOM 90 strength.1-RM (one repetition maximum), ISOK 60 (isokinetic strength at 60 degrees/s), ISOM 90 (isometric strength at 90 degrees of knee flexion), ES (effect size), CI (confidence interval).
Table 6. Pooled weighted effect sizes and percentage gains in leg press 1-RM, ISOK 60, and ISOM 90 strength.1-RM (one repetition maximum), ISOK 60 (isokinetic strength at 60 degrees/s), ISOM 90 (isometric strength at 90 degrees of knee flexion), ES (effect size), CI (confidence interval).
OutcomeWeighted ESES 95% CIWeighted %∆
Leg Press 1-RM (N = 41)0.160.13, 0.193.45 ± 2.19%
ISOK 60 (N = 163)0.01−0.02, 0.040.35 ± 4.88%
ISOM 90 (N = 108)0.190.15, 0.224.94 ± 5.82%
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Wiens, L.; Losciale, J.M.; Fliss, M.D.; Abercrombie, M.J.; Darabi, D.; Li, J.; Barclay, R.; Mitchell, C.J. Does High-Intensity Interval Training Increase Muscle Strength, Muscle Mass, and Muscle Endurance? A Systematic Review and Meta-Analysis. Sports 2025, 13, 293. https://doi.org/10.3390/sports13090293

AMA Style

Wiens L, Losciale JM, Fliss MD, Abercrombie MJ, Darabi D, Li J, Barclay R, Mitchell CJ. Does High-Intensity Interval Training Increase Muscle Strength, Muscle Mass, and Muscle Endurance? A Systematic Review and Meta-Analysis. Sports. 2025; 13(9):293. https://doi.org/10.3390/sports13090293

Chicago/Turabian Style

Wiens, Lucas, Justin M. Losciale, Matthew D. Fliss, Max J. Abercrombie, Darius Darabi, Jedd Li, Rowan Barclay, and Cameron J. Mitchell. 2025. "Does High-Intensity Interval Training Increase Muscle Strength, Muscle Mass, and Muscle Endurance? A Systematic Review and Meta-Analysis" Sports 13, no. 9: 293. https://doi.org/10.3390/sports13090293

APA Style

Wiens, L., Losciale, J. M., Fliss, M. D., Abercrombie, M. J., Darabi, D., Li, J., Barclay, R., & Mitchell, C. J. (2025). Does High-Intensity Interval Training Increase Muscle Strength, Muscle Mass, and Muscle Endurance? A Systematic Review and Meta-Analysis. Sports, 13(9), 293. https://doi.org/10.3390/sports13090293

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop