Combat sports (CS) are primarily characterized by 2 competitors attempting to physically engage and defeat each other within the confines of the individual sport's rules and time limits (21). Each CS can be classified as a striking event (e.g., taekwondo, boxing, and fencing), in which the competitors strike each other with their limbs to score points or achieve a knockout (KO) (30,43), a grappling event (e.g., wrestling and Brazilian jiu jitsu), in which the competitors attempt to control each other's movements to achieve a dominant position on the ground or a submission (through forced hyperextension of their opponent's joints or a chokehold) (2,44), or a combined event in which the competitors use a combination of striking and grappling techniques (37), such as sambo and sanda. Of the internationally recognized CS, judo, taekwondo, Greco-Roman wrestling, freestyle wrestling, boxing, and fencing are included in the current Olympic program (32), accounting for 20–25% of all Olympic medals awarded because of the multiple weight divisions used in each (19). Two other modalities, wushu and karate, are being actively considered for inclusion in future Olympic programs (33,59). In addition, there are other modalities which are not currently being considered for Olympic inclusion, but are becoming increasingly popular on a global scale, including Brazilian jiu jitsu, muay Thai, and mixed martial arts (MMA).
Although there are many differences between each CS, a common element is their intermittent nature, where the competitors will engage each other for 2–5 minutes and then have a 30-second to 1-minute rest period followed by a further 1 to 11 rounds (20,37). Because of the similar competition formats and performance requirements between the different CS, James et al. (35) conducted a systematic review of different CS physiological studies, and found that whereas strength can distinguish between competitive CS athletes and recreational athletes, it generally does not do so between groups of competitive CS athletes stratified by success or attainment levels. Occasions where strength did discriminate between high- and low-level competitors, it tended to be in grappling-based CS rather than striking CS (35). Regarding aerobic profile in CS, the previously named review found that boxing ranking was related to V̇O2max. In contrast, the conclusions of studies related to judo, karate, and wrestling were generally evenly split between V̇O2max being related to success and no effect, with a similar pattern found for studies related to muscular and strength endurance. One area of performance that was found to consistently distinguish between higher- and lower-level CS competitors was maximal neuromuscular power output, assessed by measures including bench press force-velocity profiling, counter movement jump height, and squat jump height (35).
Considering studies of metabolic substrate production in CS, lactate measurements ([LAC]) have been found to vary between striking, grappling, and mixed CS, with greater magnitudes in grappling sports such as wrestling (20 ± 0.7 mmol·L−1) (42) and judo (12.3 ± 0.8 mmol·L−1) (14) than in striking sports, such as taekwondo (7.5 ± 3.8 mmol·L−1) (45) and muay Thai (9.72 ± 0.6 mmol·L−1) (13). Mixed martial art has been found to have a wider range of [LAC] production, potentially because of both striking and grappling being used in this CS (from 9.25 ± 2.96 to 19.7 ± 1.41 mmol·L−1) (1,38). When considering these results alongside the findings of the James et al. (35) review, it could be concluded that success in CS depends on the ability to repeatedly produce high-force, high-velocity movements in succession with recovery being achieved within a small time-frame. This effort profile induces a significant amount of stress on the athlete's metabolic recovery pathways, suggesting that an appropriate amount of a CS athlete's training should be targeted toward optimizing this physiological adaptation.
High-intensity interval training (HIIT) can be described as any high-intensity, short-duration activity in which efforts are close to maximum, maximum or supramaximum, intercepted by brief passive or active recovery periods (28). The aerobic and anaerobic adaptations of this method are widely documented and include an increased blood pH tolerance, an increase in the size of muscle mitochondria, and an increase in anaerobic capacity (26,28,56). The research and training literature currently organize HIIT into 3 categories: traditional HIIT, sprint interval training (SIT) and repeated sprint training (RST) (9,29). High-intensity interval training refers to short- or long-duration effort activities (>10 seconds and <8 minutes), with controlled intensity above 90% of the maximal capacity of a controlled variable and recovery periods with similar durations. Sprint interval training generally refers to maximal activities of short duration (up to 30 seconds) with long recovery periods (from 60 to 300 seconds) (29). Repeated sprint training refers to supramaximal activities of very short duration (≤10 seconds) and short recuperation periods (≤60 seconds). High-intensity interval training protocols have been assessed in several populations, demonstrating its effects on body composition (57) and physical performance (34,60). These studies have included subjects engaged in CS (6,23,25,29), leading to a number of studies suggesting HIIT protocols for specific CS training (31,41).
Regardless of striking or grappling characteristics, CS have an intermittent nature (21). Because of the intermittent, round-based structure common to each CS (46), alongside the physiological results discussed above, and the physiological adaptations common to HIIT (23,24,50), it may be suggested that HIIT could be an appropriate training method to enhance the physiological capabilities of the athletes involved, to bring about the physiological adaptation required to achieve high-level performance (17). The effects of including HIIT sessions in CS athletes' preparation have been tested in several modalities. Recently, Franchini et al. (20) systematically reviewed literature about this topic among Olympic CS. Even though the study condensed important information about this topic, data about non-Olympic CS and a meta-analysis quantifying the effect size of HIIT intervention are lacking. Therefore, the aim of this study was to assess the currently available HIIT-related research in CS and perform a systematic review and meta-analysis of the chronic effects of HIIT protocols on CS athletes to better inform researchers and practitioners working within these sports.
Experimental Approach to the Problem
This systematic review with meta-analysis was conducted using PRISMA protocol and was previously registered in the PROSPERO database (protocol number 79141). The search was performed in the following databases: PubMed, Science Direct, and Google Scholar. In addition, gray literature was considered. The search was performed in February 2017 and updated in February 2019. The following Boolean combination of terms was inserted in the above-mentioned databases: (“CS” OR “martial arts” OR “judo” OR “taekwondo” OR “jiu jitsu” OR “boxing” OR “karate” OR “wrestling” OR “wushu” OR “kung fu”) AND (“HIIT” OR “intermittent exercise” OR “SIT” OR “RST”). No date limits were inserted.
To be included in this review, studies should be original, involve CS athletes, present one or more HIIT intervention protocols (HIIT, SIT, or RST), and analyze chronic physiological outcomes. The search processes, including screening, eligibility, and inclusion, were performed by 2 independent reviewers. Data extraction was performed by 2 reviewers, and meta-analysis was performed by one reviewer. Physiological and body composition outcomes were considered. Physiological outcomes were heart rate (HR), blood lactate concentration ([LAC]), anaerobic power (AP), aerobic power (V̇O2max), and aerobic capacity (AC). Body composition outcomes were body mass (BM) and percentage of body fat (%BF). Only V̇O2max, peak, and mean AP, BM, and %BF were analyzed by meta-analysis.
Risk of Bias in Individual Studies
Each study's methodological quality was tested using the TESTEX scale (53), which was used only to characterize the studies' methodological quality, and not as an exclusion criterion. Publication bias was also calculated for each outcome.
The meta-analysis was conducted from the nonadjusted odds ratio (OR) calculation considering random effect, based on sample number and each outcome mean and standard deviation before and after intervention. Statistical heterogeneity between studies was evaluated using Cochran's Q and I2 tests, considering heterogeneity for I2 above 50%. Publication bias was visually verified using funnel plots. All analyses were performed using the Review Manager version 5.3.5 (The Nordic Cochrane Center, The Cochrane Collaboration, 2014).
The search process is detailed in Figure 1. A total of 2,209 studies were found in the identification phase (PubMed = 22, Science Direct = 7, Google Scholar = 2,180). Two other studies were included from other sources, totalizing 2,111 records in the identification phase. During the screening phase, all records were evaluated by title. The exclusion criteria by title were: (a) not original research, (b) not among CS athletes, (c) no HIIT intervention, and (4) no chronic physiological effects measured. After title evaluation, 28 potentially relevant records remained; however, 6 were duplicated and excluded, leaving 22 records remaining. During the full-text analysis, 10 records were excluded. Therefore, 12 studies were included in the systematic review and meta-analysis. The selected studies are summarized in Table 1.
The selected studies were submitted to the TESTEX methodological quality scale. Two studies obtained score 10/12 (18,51), 5 studies obtained 9/12 (23,24,36,47,50), one obtained 6/12 (5), 3 obtained 5/12 (7,8,40), and one obtained 4/12 (58). Table 2 displays the complete and detailed TESTEX scale score of each study.
All the selected studies had experimental designs, with 6 being randomized (5,23,24,36,47,51) and 6 nonrandomized (7,8,18,40,50,58). As for the modalities, 6 studies investigated judo (7,8,23,24,36,40), one Brazilian jiu-jitsu (51), one karate (50), 2 taekwondo (5,47), one muay Thai (58), and one wrestling (18).
For the interventions, 4 studies used HIIT protocols, one being of short duration (50), 2 of long duration (7,51) and one mixed, using short and long duration sessions (47). Four studies used RST protocols (8,18,23,24), one used SIT protocols (36), and one used an intermittent protocol that could not be classified among these methods because of the lack of methodological description (40).
Only 3 studies recruited athletes from both genders (7,47,58), and the other 9 recruited only male athletes. The samples were composed of athletes from a range of performance standards, with an age range of 18–26 years. Including all studies, a total of 255 subjects were assessed. Sample sizes varied from 8 to 35 (mean = 20.7 ± 11.26) CS athletes. Concerning the subject's competitive level, 2 studies assessed international-level athletes (7,50), 3 assessed national-level athletes (5,36,58), one assessed national- and regional-level athletes (18), 2 involved state-level athletes (23,24), and 4 could not be clearly identified—college athletes (40,47); high-level athletes (8); and distinct graduation athletes (51).
The Aerobic Capacity was measured in 2 studies. One measured AC through the power production at the anaerobic threshold during an incremental test using cycle ergometers for upper and lower limbs, with no differences between moments found (23). The other study measured the speed at the anaerobic threshold (SAT) during an incremental treadmill test (Bruce protocol), finding higher values of SAT after the intervention (pre = 12.25 ± 1.4 km·h−1, post = 13.98 ± 0.9 km·h−1 (8).
Heart rate measures occurred using several methods. Four studies presented the Maximum HR (HRmax). Monks et al. (47) found a decrease in HRmax during incremental test using a treadmill in taekwondo athletes (Bruce protocol, pre = 186 ± 1.95 b·min−1, post = 178.9 ± 2.65 b·min−1; p < 0.001). Three other studies, 2 measuring the same variable with the same treadmill protocol (5,36) and another through incremental tests using upper- and lower-limb cycle ergometry (23) found no significant differences between moments. One study measured the mean HR (HRmean) in simulated judo matches, with no differences being observed after intervention (24). Another study measured the HR immediately after judo matches, and found no differences between moments (36). An intervention presented the HR at the anaerobic threshold in an incremental treadmill test (Bruce protocol), and also found no differences between moments (8).
Relating to aerobic power, 5 studies detected improvements to V̇O2max (5,18,47,50,51). Among striking modalities, an increase from 58.7 ± 3.1 to 61.4 ± 2.6 ml·kg−1·min−1 (p < 0.05) in karate athletes was observed (50), and in taekwondo athletes, from 50.13 ± 3.81 to 53.16 ± 2.00 ml·kg−1·min−1 (p < 0.05) (5) and from 56.1 ± 1.38 to 60.8 ± 1.58 ml·kg−1·min−1 (p = 0.013) (47). Among grappling CS, high-level wrestling athletes presented 49.3 ± 4.4 ml·kg−1·min−1 before and 52 ± 3.4 ml·kg−1·min−1 (p = 0.01) after just 4 weeks of SIT training (18). A significant increase from 39.8 ± 11.9 to 46.3 ± 7.0 ml·kg−1·min−1 (p = 0.001) was also observed among Brazilian jiu-jitsu athletes (51). Three other studies with judo athletes did not find any significant differences for V̇O2max (7,23,36). The statistical analysis showed an increase in V̇O2max, with mean difference (MD) = 2.83 L·kg−1·min−1 (CI 95% = 0.40–5.25; p < 0.001) for striking athletes, and 2.36 L·kg−1·min−1 (CI 95% = 1.05–3.66; p < 0.001) for grappling athletes (Figure 2).
The Wingate test was used to measure the anaerobic component in 4 studies. For the test using lower limbs, 3 studies found an increase in peak power and mean power. For peak power, Farzad et al. (18) found an increase from 954.5 ± 314 to 1,137.2 ± 446.3 W (p < 0.05) among wrestlers. Kim et al. (36) found an increase from 12.84 ± 1.33 to 15.33 ± 1.34 W·kg−1 in 4 weeks (p < 0.001) and to 15.46 ± 1.68 W·kg−1 in 8 weeks (p < 0.001), with no differences between outcomes at 4 and 8 weeks in judo athletes. Regarding mean power, Farzad et al. (18) found an increase from 461.4 ± 119.9 to 490.6 ± 135.1 W (p < 0.05) in wrestlers. Kim et al. (36) found an increase from 9.43 ± 1.10 to 11.37 ± 1.85 W·kg−1 in 4 weeks (p = 0.044) and to 12.14 ± 2.12 W·kg−1 in 8 weeks (p = 0.024), whereas Monks et al. (47) observed an increase from 479.1 ± 42.14 to 534.8 ± 24.68 W (p < 0.001) among taekwondo athletes. Franchini et al. (23) applied the Wingate test for both upper and lower limbs; however, they did not find any differences relating to power production in either test after a 4-week intervention. Statistical analyses showed no differences in peak power for striking, with an MD of 0.67 W (CI 95% = −0.43 to 1.77; p = 0.23) (Figure 3, panel A), but differences for grapplers with an MD of 0.51 W (CI 95% = 0.03–0.98; p = 0.04) (Figure 3, panel B), after HIIT interventions was found. For mean power there were no significant differences found (MD −0.04 W (CI 95% = −0.45 to 0.36; p = 0.83)) (Figure 4).
Two studies performed successive Wingate tests, comprised of 4 tests separated by 4 minutes of rest (18), and 3 minutes of rest in between (23). Regarding peak power, Farzad et al. (18) found increases at the first and second tests for lower limbs (first: pre = 954.5 ± 314 W, post = 1,137.2 ± 446.3 W, p < 0.05; second: pre = 871.6 ± 316.5 W, post = 1,191.9 ± 451 W, p < 0.05). Franchini et al. (23) did not detect significant differences for upper limbs; however, for lower limbs an increase was observed in the fourth test only for the groups who participated in HIIT with lower limbs (pre = 7.56 ± 1.01 W·kg−1, post = 9.3 ± 1.89 W·kg−1; p < 0.05) and specific protocol using Uchi-komi (Uchi-komi is a specific kind of Judo training in which successive applications of the same motor action are realized, without throws in all repetitions. In the study, a throw was performed at the end of each set of 20s) (pre = 7.85 ± 1.45 W·kg−1, post = 9.01 ± 1.16 W·kg−1; p < 0.05). Regarding mean power among wrestlers, Farzad et al. (18) found increases at the first and second tests for lower limbs (first: pre = 461.4 ± 119.9 W, post = 490.6 ± 135.1 W, p < 0.05; second: pre = 380 ± 82.1 W, post = 414.7 ± 83.4 W, p < 0.05). Among judo athletes, Franchini et al. (23) reported no significant differences for Wingate tests with upper limbs; however, an increase during the fourth test of the lower limbs was identified for the HIIT intervention group (pre = 8.36 ± 0.92 W·kg−1, post = 8.51 ± 0.92 W·kg−1; p < 0.05).
[LAC] was analyzed in 7 studies. Four of them presented [LAC] values after the incremental treadmill test, and 2 found an increased [LAC] concentration after the intervention period, from 12.6 ± 3.7 to 19.3 ± 4.1 mmol·L−1 (p < 0.05) (50) and from 10.49 ± 1.88 to 12.03 ± 1.92 mmol·L−1 (p < 0.05) (5), whereas the other 2 studies did not find any significant difference (7,36). Two studies analyzed [LAC] after Wingate tests. Franchini et al. (23) analyzed [LAC] after successive tests with upper and lower limbs, and no differences were observed regarding upper limbs after intervention. Among the lower-limb tests, the values after the second, third, and fourth trials were lower after the intervention in the Uchi-komi group (second: pre = 11.90 ± 1.06, post = 10.42 ± 0.95 mmol·L−1; third: pre = 13.28 ± 0.97, post = 11.90 ± 0.95 mmol·L−1; fourth: pre = 13.60 ± 0.99, post = 12.64 ± 0.91 mmol·L−1; p > 0.05). Farzad et al. (18) did not find a significant difference at peak [LAC] after a single lower-limb Wingate test. Similarly, a study analyzing [LAC] variation after a judo match did not find significant differences after the intervention (24).
Seven studies analyzed anthropometric variables. Regarding BM, 3 studies measured decreases in this variable. Among Brazilian jiu jitsu athletes, Ribeiro et al. (51) identified a decrease from 90.1 ± 23.2 to 84.6 ± 19.9 kg (p = 0.003), whereas Monks et al. (47) observed a decrease from 68.4 ± 2.35 to 67 ± 2.32 kg (p < 0.001) among taekwondo athletes. Ugras (58) found a decreased BM in male (pre = 68.7 ± 13.0 kg, post = 68.0 ± 12.7 kg [p < 0.01]) and female (pre = 57.2 ± 7.5 kg, post = 56.8 ± 7.5 kg [p < 0.01]) muay Thai athletes. When measuring anthropometric changes in terms of percentage of body fat (%BF), the above-mentioned studies presented divergent fingings. Although Ribeiro et al. (51) pointed to a %BF decrease (from 17.3 ± 5.9 to 16.1 ± 5.6%; p = 0.004), Monks et al. (47) found a slight increase (16.3 ± 0.65 to 16.8 ± 0.63%; p = 0.01). Four studies did not identify any differences between pre and postintervention measurements (7,23,36,40). Statistical analyses showed differences for BM in striking CS, with MD −0.93 kg (CI 95% = −1.68 to −0.19; p = 0.01) (Figure 5, panel A) and no differences for BM in grappling CS, with MD −0.09 kg (CI 95% = −2.80 to 2.62; p = 0.95) (Figure 5, panel B). Furthermore, after HIIT interventions, differences were found for %BF in striking CS with MD 0.50% of body fat (CI 95% = 0.30–0.70; p < 0.001) (Figure 6, panel A) and no differences for grappling CS, with difference −0.87% (CI 95% = −1.77 to 0.03; p = 0.06) (Figure 6, panel B).
The funnel plots concerning AP, peak AP, mean AP, BM, and %BF are presented in Figure 7.
The present study aimed to perform a systematic review and meta-analysis concerning chronic adaptations in response to HIIT among CS athletes. The main finding was that V̇O2max and AP are the variables most affected by this training method when compared with other variables, such as AC, HR, [LAC], and anthropometric outcomes, especially BM and %BF.
The aerobic outcomes investigated in these studies were AC, HR, and V̇O2max. Only 2 studies measured the AC, neither of which found any differences in this variable after the intervention period (8,23) Furthermore, it was not possible to conduct inferences about AC in the current article because of the low number of studies investigating this variable. Aerobic capacity is considered an important variable in a CS athlete's performance, because it may delay fatigue and accelerate the recovery process (14,22), suggesting that this would be a key area for further research to focus on for this population. Between the 7 studies which investigated HR, only one found differences related to HIIT chronic effects (47), and these results suggest that HIIT may not produce significant effects in HR in CS athletes. From the 8 studies which analyzed V̇O2max, 5 found improvements ranging from 4.6% up to 16.3% in this variable in response to a HIIT intervention (5,18,47,50,51), and these results suggest that HIIT may be used to develop the V̇O2max of CS athletes. It is important to highlight that the V̇O2max is relevant to CS athletes, because a more developed cardiorespiratory capacity contributes to sustained efforts during bouts through faster recovery between efforts, rounds, and matches (15). Therefore, interventions that increase aerobic fitness, such as HIIT, seem desirable for CS athletes, because these modalities demand a high oxidative contribution and a fast creatine phosphate resynthesis. This would result in a faster recovery between rounds and between high-intensity interactions during the bout (14,15,21,61).
The anaerobic component has been shown to be important in CS, being a discriminant factor between different competitive levels in several CS modalities, such as wrestling (61), judo (22), and taekwondo (10). Since anaerobic fitness is the key for maintaining periods of high-intensity movements (such as repeated punch and kick combinations in striking CS (10), or grip disputes and scrambles in grappling CS (22,61)), interventions which increase anaerobic fitness, such as HIIT, may be highly recommended. In this sense, anaerobic tests such as the Wingate test (22) are widely used to measure the anaerobic profile of CS athletes. The anaerobic outcomes investigated in this study were power output in Wingate tests (single and successive trials) and [LAC] concentrations. From the 4 studies which investigated a single Wingate test, 3 observed increased power output (18,36,47), and other 2 studies investigated the power output in successive tests, again finding improvements in the athlete's performance (18,23). These findings indicate that HIIT may be successfully used to enhance CS athletes' AP production. From 7 studies which investigated [LAC] after aerobic and anaerobic efforts, only 3 found changes after intervention. Two found increases in peak [LAC] after a treadmill incremental test (5,50), whereas the other one found lower values after successive Wingate tests (23). This can indicate that HIIT may improve the anaerobic/alactic energy pathway by inducing higher blood lactate peaks, in turn decreasing recovery time through improved lactate clearance and buffering in the muscle cell (12,27), leading to lower lactate levels in successive Wingate tests. The other 4 studies which investigated [LAC] did not observe any changes in aerobic or anaerobic tests after HIIT interventions (7,18,24,36). Despite some studies involving other populations finding increases in [LAC] after an HIIT intervention (55), this effect seems to be less prevalent amongst CS athletes, maybe because of the high competitive level and advanced training age of most of the subjects included in the analyses, many of whom already displayed a high peak [LAC] (18).
Regarding anthropometric variables, especially BM and %BF, for the most part, the included studies did not report any significant changes after HIIT intervention (7,23,36,40). This may have 2 possible explanations: i) the HIIT models applied in the studies may not be adequate to cause body composition modifications, or ii) the intervention period may not be long enough to observe these changes. Several studies have already shown that these variables are sensitive to HIIT (54) and a recent meta-analysis found that 12 weeks of HIIT are enough to positively change the %BF of overweight and obese people (4). In addition, among endurance athletes it was observed that a 9-week intervention with several sessions per week using a long HIIT protocol could significantly reduce BM by 3.7 ± 3.0% (54). These divergences may be because of the high level of most athletes from the studies of this review, and the fact that CS are weight-regulated events (37,45,61), meaning CS athletes will maintain relatively low %BF during the course of their training and competition (19), making it less likely that these variables—%BF and BM—would display influences from HIIT interventions.
To date, most studies involving HIIT and CS use running (18,50) and cycling modalities (23,24). However, some studies tried to structure HIIT protocols using CS-specific movements and techniques. In this sense, based on time–motion analyses of CS matches, HIIT can be designed based on the effort:pause ratio of the CS in question. Briefly, time–motion analysis studies have observed effort:pause ratios of 1:1 in kick boxing (48), 2:3 in muay Thai (52), 1:8 in taekwondo (16), 2:1 in judo (46) and wrestling (61), and 8:1 in Brazilian jiu jitsu (3). In MMA, an effort:pause ratio near 1:1 in sparring (39) and a high:low intensity ratio near 2:1 in competition (17) have been reported.
Only one research group analyzed the HIIT effects on specific performance—in the special judo fitness test (SJFT) and match simulation, with some relevant differences in SJFT (24). In addition, it was previously investigated whether sport-specific HIIT training protocols could accurately mimic the efforts of competitive bouts (11,49) and highlighted the specificity of the sport's training applied to CS. In this sense, both pathways must be investigated properly, and any physiological adaptations to sport-specific HIIT protocols must be compared with changes from traditional ambulatory HIIT protocols to assess their efficacy in sports performance.
In summary, any inferences made in the present review have some limitations, such as the low number of studies, the use of distinct protocols and athlete performance levels, and the lack of female athletes' data. New studies should evaluate HIIT effects in competitive performance, or at least, in simulated matches. These protocols may consider the number of applied strikes and technical skills used in each CS and should be designed to elicit the same physiological responses as ambulatory HIIT protocols. In conclusion, HIIT interventions produce positive chronic effects predominantly in V̇O2max and AP in CS athletes, with a minor effect on body composition.
Combat sports are intermittent in nature, consisting of alternating periods of high- and low-intensity efforts, and pauses during matches. Despite the scarce number of studies investigating the effects of HIIT in athletes from these modalities, studies considering karate, wrestling, judo, Brazilian jiu jitsu, muay Thai, and taekwondo show that HIIT can be performed using general or specific movements. In the former, running (on treadmill or track) and cycling are the most common choices, and grappling and striking actions were frequently used in the latter. As shown in this review, including HIIT in CS athletes' programs may be useful to improve their aerobic and anaerobic fitness, allowing them to maintain high intensity effort periods and quickly recover between these periods, rounds, and bouts. Since CS athletes are divided by weight categories and HIIT may not significantly affect CS athletes' body composition, adding HIIT to these athletes' routine should not affect this aspect of the athlete's preparations. Therefore, HIIT may be desirable when improvements in aerobic and anaerobic fitness are needed without altering the athlete's weight category. Based on the findings of the studies included and discussed in this review, training periods from 10 days to 12 weeks involving progressive HIIT (using effort:pause of 30:90–20:10 seconds, and 1:1 minute), using percentages of maximal aerobic speed, and SIT, using successive 35 m all-out sprints interspersed by a 10-second recovery, and 30-second supramaximal bouts with 4-min recovery periods, seem effective in improving physical fitness in CS athletes, in particular aerobic and AP.
B.B. Vasconcelos, G.V. Protzen, L.M. Galliano, C. Kirk, and F.B. Del Vecchio declare that they have no potential conflicts of interest that are directly relevant to the content of this article. Funding: No funding was received for conduct of the work or for preparation of the manuscript.
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