Effects of Exercise Modality During Additional “High-Intensity Interval Training” on Aerobic Fitness and Strength in Powerlifting and Strongman Athletes : The Journal of Strength & Conditioning Research

Secondary Logo

Journal Logo

Advanced Search
Original Research

Effects of Exercise Modality During Additional “High-Intensity Interval Training” on Aerobic Fitness and Strength in Powerlifting and Strongman Athletes

Androulakis-Korakakis, Patroklos1; Langdown, Louis1; Lewis, Adam1; Fisher, James P.1; Gentil, Paulo2; Paoli, Antonio3; Steele, James1

Author Information

1School of Sport, Health and Social Sciences, Southampton Solent University, United Kingdom;

2Faculty of Physical Education and Dance, Federal University of Goias, Brazil; and

3Department of Biomedical Sciences, University of Padova, Italy

Address correspondence to James Steele, [email protected].

Journal of Strength and Conditioning Research 32(2):p 450-457, February 2018. | DOI: 10.1519/JSC.0000000000001809
  • Free

Abstract

Introduction

Powerlifters and strongman athletes have a need for aerobic and anaerobic fitness. Authors have previously suggested that performing activities such as pushing/pulling a car can cause athletes to reach 44–49% of their V̇o2max and 90–92% of their maximal heart rate (5). As such, high numbers (e.g., ∼90%; [68]) of these athletes are incorporating aerobic and anaerobic conditioning into their training practices to supplement their strength training. However, performance of concurrent aerobic and strength training has suggested that including traditional aerobic training activities (e.g., cycling, running, and swimming) might reduce strength adaptations (67).

It has been suggested that high-intensity interval training (HIIT) can be an efficient and effective way of increasing aerobic fitness and strength in both untrained and trained individuals (9). Furthermore, HIIT has been popularized mostly for its time-efficient ability to induce adaptation without requiring any specific equipment as long as a high intensity of effort is maintained (25,26). A typical HIIT protocol will consist of bouts of high effort followed by an active or passive recovery period (56). However, HIIT has typically been employed with exercise modes considered traditionally as “aerobic” (e.g., running, cycling etc.; [2,37]). In a recent publication by the American College of Sports Medicine (ACSM), HIIT was presented as a tool that can improve aerobic fitness and can be “performed on all exercise modes” but without any mention of possible strength improvements or reference to any resistance training mode of exercise (35). As HIIT gains momentum in both research and application, particularly with regard to its potential health benefits (7), the effect of exercise mode on adaptations has also begun to receive more attention. Resistance training with multijoint exercises such as the squat and deadlift could be used to perform a HIIT protocol as they consist of bouts of maximal or near maximal effort followed by a recovery period. Indeed, HIIT has been examined using resistance training for its effects on acute energy expenditure (51) and both strength, body composition, blood lipids (44), and aerobic fitness (9,14,59). However, controlled comparison of exercise modes during HIIT has received little investigation (9).

An issue with the present body of research considering modality during HIIT is a lack of appropriate definition and control of “intensity.” It has recently been argued with respect to resistance training that “intensity” may be best defined as relative effort (i.e., proximity to momentary failure; [20,61]) rather than relative load (e.g., %1 repetition maximum [RM]), as it has previously been referred to in a resistance training context (23,54,66). Consideration of how “intensity” has been defined has implications for interpretation of studies examining HIIT. Indeed, though health benefits might occur in naive participants from exercise performed at any intensity of effort, it has been argued that adaptations (e.g., muscular strength and hypertrophy, aerobic fitness, and health measures) might be similar across exercise modes if the effort is high (22). Fatiguing contractions (irrespective of exercise mode) result in increased relative effort and subsequent sequential motor unit recruitment to meet the required force demands of the task being performed (1,12,16,64). Previous studies comparing traditional aerobic modalities of exercise and resistance training–based HIIT have not clearly controlled intensity of effort (15,59). In addition, other studies investigating the effect of different exercise modes using HIIT often report only 1 physiological adaptation such as strength or aerobic fitness without assessing and comparing both (18,59).

Improvements in both aerobic fitness in addition to strength and hypertrophy may be possible with a range of independent exercise modes as long as effort is high (22). Ozaki et al. (49) report increased aerobic fitness as a result of resistance training, and Steele et al. (63) conclude that resistance training performed at maximal effort (e.g., reaching momentary failure) may optimize these improvements. Lundberg et al. (40) have also reported augmented hypertrophic outcomes from the performance of maximal effort cycling, and a range of other authors have reported improved strength and hypertrophy from aerobic modalities (34,48,50).

In light of the above, there is a relative dearth of literature investigating concurrent training in powerlifting and strongman athletes for concurrent strength and aerobic adaptations. Furthermore, examining the effect of exercise mode and the importance of effort may allow for increased flexibility when selecting mode of exercise for powerlifters and strongman athletes as well as for untrained persons. With this in mind, the aim of this study was to compare ecologically valid HIIT protocols matched approximately for effort and volume, each employing a different mode of exercise (aerobic or resistance training). Both intervention strategies were compared for their effects on aerobic fitness and strength over an 8-week training intervention in well-trained male participants. It was hypothesized that, when effort is controlled and matched, both modes would result in similar adaptations in aerobic fitness and strength.

Methods

Experimental Approach to the Problem

To investigate the hypothesis that exercise mode during additional HIIT would produce similar aerobic fitness and strength adaptations, a randomized trial with 2 experimental groups was adopted. Well-trained subjects (powerlifters and strongman athletes) performed an 8-week HIIT exercise intervention 2×/week, employing 1 of 2 different exercise protocols based on 2 different exercise modes: An aerobic mode of exercise (cycling; [AM]) and a strength training mode of exercise (resistance training; [SM]). At least 48 hours separated each HIIT session. Subjects were not instructed to avoid any external training sessions. Thus, the HIIT intervention was performed in addition to their existing training which they were asked to maintain at the same frequency, volume, loadings and effort, for any resistance or aerobic training they were currently performing (see below). The outcome measures included were strength and aerobic fitness. The independent variable in this study therefore, was the group to which subjects were randomly assigned (AM or SM), and the dependent variable was the change in each of the outcome measures (strength and aerobic fitness). The study received the approval of the Health, Exercise and Sports Science Ethics Committee of Southampton Solent University (Reference No. 456).

Subjects

Sixteen trained men aged 24 ± 3 years (range 21–28 years) with resistance training experience of at least 2 years, including engagement and competition in strength sports (powerlifting, strongman etc.), were recruited from a local strength-sports gym to participate in this study. All subjects were asked to provide information regarding their training experience, as it was important to clarify whether they had been previously engaging in resistance training, aerobic training, or both. A significant proportion of subjects (75%) reported their primary experience was with resistance training and strength-based sports, whereas a few subjects reported that they had been engaging in both aerobic and resistance training. The subjects reported themselves to currently be in a hypertrophy/general strength training cycle, and their current training was reported as being performed at a frequency of 2–5×/week, using loads ranging from 60 to 85% 1RM, with a 7–8.5 rating of perceived effort (RPE) for working sets, and a 8 RPE for aerobic sessions. The participants were assigned by random number generation to the AM (n = 8) and SM (n = 8) group. All participants were familiar with the equipment used in the study, which was important to minimize any learning effects from affecting outcome measures. All subjects were provided with an information sheet describing the details of the study including the benefits and risks of participation and given time to read it and ask the investigators questions. After the subjects and investigators were satisfied that subjects had an understanding of what they would be asked to do, subjects were provided with and signed institutionally approved informed consent documents to participate. The study was approved by the Health, Exercise, and Sport Science Ethics Committee at Southampton Solent University.

Procedures

Testing

Both groups were required to undertake tests to assess aerobic fitness and lower-body strength preintervention and postintervention. Pretesting and posttesting were conducted at the same time of day both preintervention and postintervention, and subjects instructed to maintain normal levels of hydration to ensure they did not make any changes to their diet and to avoid training or ingestion of stimulants or alcohol for at least 48 before testing. The aerobic fitness test used was the YMCA 3 minutes step test as it is a valid and reliable test that is easy to set up and predicts V̇o2max with r = 0.83 (6). The YMCA 3 minutes step test was used both as an independent test examining participants' heart rate (YMCAhr) response and as a predictor of V̇o2max (YMCA V̇o2max) using the formula from McArdle (42). Strength testing was performed on a G7-S71 leg extension machine (Matrix Fitness, Stoke-on-Trent, United Kingdom). The baseline strength level of all participants did not allow for 1RM testing as all were able to perform ≥2 repetitions with the leg extension machines' maximum load (117 kg). Thus, a 4–6RM test was used to predict their 1RM using Dohoney's (17) formula, which has been shown to be accurate for estimating 1RM in the leg extension machine (19). The step test and, in particular, the leg extension machine were chosen as test modes that neither group was performing in their current training or respective training interventions, thus mitigating any possible learning effects on strength gains (10,21).

Training

The AM group was assigned a ∼20-minute HIIT protocol based on the U7xi cycle ergometer (Matrix Fitness, United Kingdom) for 2 sessions a week. Effort was assessed through a combination of age-predicted maximum heart rate ([MHR]; 220-age) and the Borg CR10 RPE scale (8) as it can be a valid tool to measure perceived effort in trained individuals (53). Maximum heart rate was predicted by the equation 220-age. The AM group warmed up at 60% MHR/5–6 RPE for the first 5 minutes before beginning the HIIT protocol. The AM group HIIT protocol consisted of a high effort bout at 85% MHR/RPE 8–9 for 30 seconds followed by a recovery period of 1 minute and 30 seconds at 50–60% MHR/5–6 RPE. The above interval was repeated 7 times and was then followed by a cool down for 5 minutes at 50% MHR/RPE 4–5. The participants' RPE was recorded throughout the protocol to ensure that intensity of effort targets was met.

The SM group was assigned a ∼20-minute HIIT protocol based on the barbell deadlift and squat exercises. The SM group was required to perform 1 squat and 1 deadlift session per week totaling 2 sessions a week. The participants were allowed to self-select their squat stance and bar placement as long as it allowed them to squat to the point where the anterior surface of the thigh at the hip joint was lower than the top of their knees. The participants were also allowed to self-select their deadlift stance, as long as they were comfortable with maintaining their stance until the targeted RPE was reached. The SM group warmed up by performing squats or deadlifts by performing 1 set of 5 repetitions with 30, 40, and 50% of their 1RM using a ∼1 second concentric and ∼1 second eccentric repetition duration. The participants' 1RM was either based on a self-reported 1RM or was calculated based on a formula developed by Baechle and Earle (4). The high-intensity bout in the SM group consisted of repetitions with 60% of 1RM using a ∼1 second concentric and ∼1 second eccentric repetition duration. Participants performed repetitions until they felt they were at an RPE of 8–9. The resulting repetition range was 8–15 with sets lasting ∼16–30 seconds. This was followed by a recovery period of 1 minute and 30 seconds of passive rest. The above interval was repeated for 7 sets. The SM group then performed a cool down on the Matrix T7xe treadmill at a pace that allowed participants to remain at an RPE of 4–5 for 5 minutes.

Statistical Analyses

The independent variable in this study was the group to which subjects were randomly allocated (SM or AM), and the dependent variables were the absolute change (post minus pre-test values) in each of the outcome measures (change in aerobic fitness and strength). Thus, between-group comparisons were conducted examining the effect of the independent variable on the dependent variables. Assumptions of normality of distribution were met when the data were tested using the Kolmogorov-Smirnov test (31). Demographic characteristics and change in aerobic fitness and strength were compared using an independent t-test to examine between-group differences. 95% confidence intervals (CIs) were calculated in addition to within-participant effect size (ES) using Cohen's d (13) which allowed for comparison of the magnitude of effects between groups. An ES of 0.20–0.49 was considered as small, 0.50–0.79 as moderate, and >0.80 as large. Statistical analysis was performed using IBM SPSS Statistics for Windows (version 20; IBM Corp., Portsmouth, Hampshire, United Kingdom), and significance was accepted at p ≤ 0.05.

Results

Participants Baseline Data

Baseline participant demographics, aerobic fitness, and strength are shown in Table 1. There was a significant between-groups difference in body mass (t(14) = −2.249, p = 0.041), and both YMCAhr (t(14) = 3.102, p = 0.008) and YMCA V̇o2max (t(14) = −3.102, p = 0.008) though all other demographic variables did not differ between groups at baseline.

T1
Table 1.:
Baseline participant demographics.*†

Aerobic Fitness

Table 2 shows mean changes, 95% CIs, and ESs for aerobic fitness outcomes. 95% CIs indicated that both groups significantly improved in both YMCAhr and YMCA V̇o2max test. Significant between-group differences were found for aerobic fitness in both the YMCAhr (t(14) = −2.88, p = 0.01) and the YMCA V̇o2max test (t(14) = −2.88, p = 0.01). Effect sizes for aerobic fitness changes were considered large for both groups.

T2
Table 2.:
Aerobic Fitness changes.*†

Strength

Table 3 shows mean changes, 95% CIs, and ESs for strength outcomes. 95% CIs indicated that both groups significantly improved in predicted 1RM. There was no between-group difference for strength changes (t(14) = 0.324, p = 0.75). Effect sizes for strength changes were considered large for both groups.

T3
Table 3.:
Strength changes.*†

Discussion

The aim of this study was to examine the effect of exercise mode in HIIT on selected measures of aerobic fitness and strength in powerlifters and strongman athletes. The results suggest that aerobic fitness and strength can be simultaneously improved using HIIT irrespective of exercise mode. The hypothesis was partly supported as both the AM and SM groups improved significantly in aerobic fitness and strength; however, changes in aerobic fitness were significantly greater for the AM group. These results further support the idea that sufficiently high effort may be able to elicit physiological responses which are largely independent of exercise modality (i.e., strength improvements from an aerobic mode of exercise, or aerobic improvements from a strength mode of exercise; [22]). This seems to be the first study to directly compare aerobic and resistance training modes for both aerobic fitness and strength changes while attempting to match for effort and volume.

That both AM and SM groups significantly improved in aerobic fitness is supportive of our hypothesis that where intensity of effort is controlled, similar adaptations are likely. It is unsurprising that the AM group improved in this outcome as a recent meta-analysis supports large aerobic fitness improvements from HIIT interventions using aerobic exercise modes such as cycling (43). However, previous authors have suggested that resistance training seems unlikely to improve aerobic fitness (33). Thus, the large significant improvement for the SM group is interesting. Several recent reviews have concluded that aerobic adaptations can indeed occur as a result of resistance training (49,63), particularly if the intensity of effort is sufficiently high (63). Butcher et al. (11) have reported high RPE values for resistance training–based HIIT and other recent works have suggested that HIIT interventions including resistance training–based modes can improve aerobic fitness (9,14,15,59). The large improvements in aerobic fitness in the SM group in this study might therefore be a result of the high intensity of effort employed. Indeed in this study, participants trained to a value of 8–9 on the CR10 RPE scale. Although not to momentary failure, it is likely that participants were at close proximity to maximal effort and thus enhanced the acute stimuli that might impact aerobic adaptations (e.g., increased local oxygen utilization, lactate production, adenosine monophosphate protein kinase [AMPK] activation, peripheral vascular shear stress; [63]).

Previous mechanistic research offers insight and allows for speculation as to why similar adaptations may have occurred. For example, AMPK plays an important role in inducing mitochondrial biogenesis (i.e., mitochondrial proliferation and up regulation of mitochondrial enzymes; [52,69]), stimulating slow twitch fiber phenotype transformation (39), and inducing formation of oxidative properties in type IIx fibers (3). Furthermore, higher effort exercise (i.e., to failure) has been evidenced to result in greater drop in ATP:AMP ratio in addition to metabolite production when compared with lower effort exercise (27). AMPK is active independent of modality as long as effort is high due to its role as a key sensor of cellular energy requirements (i.e., a change in ATP:AMP ratio; [29,30]). During high effort exercise, the ATP:AMP ratio is decreased because of the increased rate of ATP use (32,55,60) and thus, AMPK is activated. Recruitment of type IIx muscle fibers during high effort muscular contraction produces greater depletion of ATP because of the fibers' greater myosin ATPase activity (55). Furthermore, AMPK activation is also greatest in type IIx fibers after exercise (38). As such, there is a molecular basis for both modalities producing aerobic adaptation when effort is sufficiently high.

However, though aerobic fitness ESs were large for both groups, the AM group had significantly larger improvements in aerobic fitness. Even trained individuals may experience larger than expected improvements when introduced to a different training stimulus, especially when that stimulus' nature differs significantly from their usual training (24). Because the present participants were not accustomed to a HIIT cycle task, this might explain why ESs were larger than those for the SM group.

Both groups also showed significant improvements in strength with large ESs, and in contrast to aerobic fitness, there were no between-group differences. We might consider that any strength adaptations may have been a result of the pre-existing, and continuing resistance training protocols. However, if this is the case, then it seems that neither SM nor AM HIIT hindered strength adaptations. Because participants were all well-trained, competitive powerlifters, or strongman athletes, we might consider that there was likely only a limited margin for potential strength increases. As such, we should not discount that HIIT protocols served to further enhance strength adaptations. Previous research supports that high effort resistance training performed as HIIT can result in strength adaptations (9). Although improvements in strength as a result of aerobic-based exercise modes, particularly higher effort protocols, have been reported, they are considered to be greatest in untrained and older populations (34,48,50). We might consider that aerobic exercise, if performed to a high effort, might provide a stimulus akin to the performance of low load resistance training, which evidence suggests is efficacious in increasing strength and hypertrophy when also performed to a high effort (i.e., momentary failure; [45,57,58]). The size principle would suggest that during fatiguing contractions, effort increases and so too does motor unit recruitment (1,12,16,64). This may be a mechanism through which high effort aerobic exercise modes can increase strength though other stimuli such as “metabolic stress” and cellular swelling might be responsible (47).

Though there seem to differences in magnitude and selective protein responses to resistance training and aerobic modalities (possibly due to studies poorly controlling and matching effort between modes) both active anabolic pathways (47). For example, both elevate Akt-mTOR-p70S6K pathway phosphorylation and myofibrillar protein synthesis in untrained persons, though this elevation is more pronounced and prolonged in resistance training, and after a training intervention, there is little stimulus from AMs (65). Aerobic modalities in previous molecular studies though, have not typically been performed to a very high intensity of effort. However, some have combined AM exercise with vascular occlusion, thus increasing the effort required and under these conditions, mitogen-activated protein kinase signaling pathways have been found to increase in their phosphorylation (46). Again, this suggests a molecular basis for strength and hypertrophic adaptations to occur from both modes with greater congruence of responses when effort is high.

The similar results from both AM and SM groups present several potential practical implications. The significant improvements observed in this study suggest that HIIT can be an effective, efficient, and flexible training protocol for both trained and untrained persons. Flexible is to be interpreted as meaning that exercise modality does not seem to have a meaningful effect on changes in aerobic fitness or strength in response to HIIT. Instead, using a high effort emerges as the major factor. Powerlifters and strongman athletes as well as other athletes, coaches, and trained individuals wishing to use or perform HIIT may therefore choose a range of different exercise modes based on personal preference (36), accessibility, or availability. For untrained individuals, the implications are also considerable. Not only does HIIT represent an approach which might overcome time related barriers (7) but, because availability of equipment can also be a barrier to exercise (41), flexibility in how HIIT might be used might serve to overcome this (22). However, participants in this study were well-trained strength-sports athletes, all proficient in the technical elements of the squat and deadlift. Untrained persons unfamiliar with these exercises might be exposed to a higher risk of injury if undertaking them without supervision/coaching or to such a high degree of effort. Further research is needed comparing different modes of HIIT in untrained persons and with alternative resistance training exercises (i.e., resistance machines).

The strengths and limitations of this study should be acknowledged. Firstly, this study adds to the relatively sparse literature that has examined competitive powerlifters/strongman athletes. Furthermore, that large ESs were found in this population for all outcomes suggests that similar results might be possible in other populations, and greater results in less well-trained participants. However, the use of this population presented a limitation in that predictive measures of both aerobic fitness and strength were only available to be examined. This was for logistical reasons as participants were recruited from, tested, and trained at the gym they were members of; thus, equipment available for testing was limited. A step-based submaximal test was used as participants were unable to travel for lab-based direct measures of aerobic fitness (i.e., V̇o2max). Predicted V̇o2max seemed unusually high in our sample (baseline range 62.61–75.21 ml·kg−1·min−1) compared with other studies of strength-based sports athletes using direct measures of aerobic capacity (∼41.9–50.8 ml·kg−1·min−1; [28]). This may be a consequence of our test over predicting V̇o2max in our sample. Furthermore, to have participants perform a strength test they were naive to (i.e., was not being performed in either their current training or used in the interventions), the leg extension was used. However, participants' high baseline strength levels prohibited performance of a 1RM, and so a 4–6RM was performed and predicted 1RM calculated. It should also be noted that, though the testing methods have been shown to be valid and reliable, we did not collect our own reliability data (6,17). Lastly, participants were reluctant to participate if this required cessation of their current training. Thus, participants also continued with their current training protocols and, though they were instructed to not make any changes to these, their inclusion may have influenced the results.

In conclusion, exercise modality does not seem to have a meaningful effect on improvements in aerobic fitness and strength in response to HIIT. The results of this study further support the importance of properly assessing and ensuring high effort is reached in HIIT as it seems to be a primary contributor to aerobic and strength improvements. The differences in aerobic improvements between the 2 groups suggest that an aerobic mode of exercise may cause greater aerobic improvements in aerobically untrained individuals after a HIIT protocol. Nonetheless, the significant aerobic and strength improvements made by both groups suggest that strength and aerobic fitness can be improved simultaneously if high to maximum effort is reached, regardless of the mode of exercise.

Practical Applications

The results from this study suggest that persons engaged in strength sports (powerlifting, strongman, etc.) can include alongside their current training programs a HIIT intervention and improve both aerobic fitness and strength. This seems to be the case whether the HIIT intervention is using a resistance training or aerobic training exercise mode. Thus, athletes and coaches can use flexibility in their program designs to accommodate other factors. For example, personal preference may be a factor affecting adherence, and so the choice of mode might be dictated by this. In addition, injury might prohibit the performance of a particular exercise, and so flexibility in exercise modality may permit persons to continue training to achieve their desired goals while switching the exercise mode. Furthermore, if such adaptations are possible in a well-trained population such as that examined here, then these considerations may also apply to untrained persons.

Acknowledgments

There are no potential conflicts of interest that the authors of this study are aware of. No funding was received in support of this study. The results of the present study do not constitute endorsement of the product by the authors or the NSCA.

References

1. Adam A, De Luca CJ. Recruitment order of motor units in human vastus lateralis muscle is maintained during fatiguing contractions. J Neurophysiol 90: 2919–2927, 2003.
2. Alahmadi M. High-intensity interval training and obesity. J Obes 4: 211, 2014.
3. Arany Z, Lebrasseur N, Morris C, Smith E, Yang W, Ma Y, Chin S, Spiegelman BM. The transcriptional coactivator PGC-1 [beta] drives the formation of oxidative type IIX fibers in skeletal muscle. Cell Metab 5: 35–46, 2007.
4. Baechle T, Earle R. Essentials of Strength Training and Conditioning. Champaign, IL: Human Kinetics, 2008.
5. Berning JM, Adams KJ, Climstein M, Stamford BA. Metabolic demands of “junkyard” training: Pushing and pulling a motor vehicle. J Strength Cond Res 21: 853–856, 2007.
6. Beutner F, Ubrich R, Zachariae S, Engel C, Sandri M, Teren A, Gielen S. Validation of a brief step-test protocol for estimation of peak oxygen uptake. Eur J Prev Cardiol 22: 503–512, 2015.
7. Biddle SJH, Batterham AM. High-intensity interval exercise training for public health: A big HIT or shall we HIT it on the head? Int J Behav Nutr Phys Act 12: 95, 2015.
8. Borg G. Borg's Rating of Perceived Exertion and Pain Scales. Champaign, IL: Human Kinetics, 1998.
9. 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 40: 1157–1162, 2015.
10. Buckner SL, Jessee MB, Mattocks KT, Mouser JG, Counts BR, Dankel SJ, Loenneke JP. Determining strength: A case for multiple methods of measurement. Sports Med 47: 193–195, 2016.
11. Butcher S, Judd T, Benko C, Horvey K, Pshyk A. Relative intensity of two types of crossfit exercise: Acute circuit and high-intensity interval exercise. J Fit Res 4: 3–15, 2015.
12. Carpinelli R. The size principle and a critical analysis of the unsubstantiated heavier-is-better recommendation for resistance training. J Exerc Sci Fit 6: 67–86, 2008.
13. Cohen J. A power primer. Psychol Bull 112: 155–159, 1992.
14. Cook A, Hastings B, Gottschall J. Time in 85–100% heart rate zone increases lean body mass and Vo2 Max in NCAA division 1 soccer players. J Fit Res 3: 12, 2014.
15. Cook K, Cathcart A, Scott R, Easton C. High intensity interval training increases aerobic and anaerobic capacity in collegiate female soccer players. Med Sci Sports Exerc 42: 698–699, 2010.
16. Denny-Brown D, Pennybacker JB. Fibrillation and fasciculation in voluntary muscle. Brain 61: 311–312, 1938.
17. Dohoney P. Prediction of one repetition maximum (1-RM) strength from a 4-6 RM and a 7-10 RM submaximal strength test in healthy young adult males. J Exerc Physiol Online 5: 54–59, 2002.
18. Easton C, Scott R, Cathcart A. A novel high intensity interval training intervention increases aerobic and anaerobic capacity in soccer players. Med Sci Sports Exerc 42: 698–699, 2010.
19. Eston R, Evans HJL. The validity of submaximal ratings of perceived exertion to predict one repetition maximum. J Sports Sci Med 8: 567–573, 2009.
20. Fisher J, Smith D. Attempting to better define “intensity” for muscular performance: Is it all wasted effort? Eur J Appl Physiol 112: 4183–4185, 2012.
21. Fisher J, Smith D, Steele J. High- and low-load resistance training; interpretation and practical application of current research findings. Sports Med 47: 393–400, 2017.
22. Fisher J, Steele J. Questioning the resistance/aerobic training dichotomy: A commentary on physiological adaptations determined by effort rather than exercise modality. J Hum Kinet 44: 137–142, 2014.
23. Fry A. The role of resistance exercise intensity on muscle fibre adaptations. Sports Med 34: 663–679, 2004.
24. Gamble P. Strength and Conditioning for Team Sports. Abingdon, Oxon: Routledge, 2010.
25. Gibala M, McGee S. Metabolic adaptations to short-term high-intensity interval training. Exerc Sport Sci Rev 36: 58–63, 2008.
26. Gillen J, Gibala M. Is high-intensity interval training a time-efficient exercise strategy to improve health and fitness? Appl Physiol Nutr Metab 39: 409–412, 2014.
27. Gorostiaga EM, Navarro-Amezqueta I, Calbet JAL, Hellsten Y, Cusso R, Guerrero M, Granados C, Gonzalez-Izal M, Ibanez J, Izquierdo M. Energy metabolism during repeated sets of leg press exercise leading to failure or not. PLoS One 7: e40621, 2012.
28. Hakkinen K, Alen M, Komi PV. Neuromuscular, anaerobic, and aerobic performance characteristics of elite power athletes. Eur J Appl Physiol 53: 97–105, 1984.
29. Hardie DG, Sakamoto K. AMPK: A key sensor of fuel and energy status in skeletal muscle. Physiology 21: 48–60, 2006.
30. Hardie DG, Salt IP, Hawkley SA, Davies SP. AMP-activated protein kinase: And ultrasensitive system for monitoring cellular energy change. Biochem J 338: 717–722, 1999.
31. Hazewinkel M. Encyclopaedia of Mathematics. Dordrecht, Netherlands: Kluwer Academic Publishers, 1997.
32. Hultman E, Sjoholm H. Energy metabolism and contraction force of human skeletal muscle in Situ during electrical stimulation. J Physiol 345: 525–532, 1983.
33. Jung AP. The impact of resistance training on distance running performance. Sport Med 33: 539–552, 2003.
34. Konopka A, Harber M. Skeletal muscle hypertrophy after aerobic exercise training. Exerc Sport Sci Rev 42: 53–61, 2014.
35. Kravitz L. High-Intensity Interval Training [ebook] (1st ed.), 2014. Available at: https://www.acsm.org/docs/brochures/high-intensity-interval-training.pdf. Accessed: January 5, 2016.
36. Lane A, Jackson A, Terry P. Preferred modality influences on exercise-induced mood changes. J Sports Sci Med 4: 195–200, 2005.
37. Laursen P, Jenkins D. The scientific basis for high-intensity interval training. Sports Med 32: 53–73, 2002.
38. Lee-Young RS, Canny BJ, Myers DE, McConell GK. AMPK activation is fiber type specific in human skeletal muscle: Effects of exercise and short-term exercise training. J Appl Physiol 107: 283–289, 2008.
39. Lin J, Wu H, Tarr PT, Zhang CY, Wu Z, Boss O, Michael LF, Puigserver P, Isotani E, Olson EN, Lowell BB, Bassel-Duby R, Spiegleman BM. Transcriptional co-activator PGC-1 alpha drives the formation of slow-twitch muscle fibers. Nature 418: 797–801, 2002.
40. Lundberg T, Fernandez-Gonzalo R, Gustafsson T, Tesch P. Aerobic exercise does not compromise muscle hypertrophy response to short-term resistance training. J Appl Physiol Respir Environ Exerc Physiol 114: 81–89, 2013.
41. Martínez-Lemos R, Puig-Ribera A, García-García O. Perceived barriers to physical activity and related factors in Spanish university students. OJPM 4: 164–174, 2014.
42. McArdle W, Katch F, Katch V. Essentials of Exercise Physiology. Philadelphia, PA: Lippincott Williams & Wilkins, 2000.
43. Milanovic Z, Sporis G, Weston M. Effectiveness of high-intensity interval training (HIT) and continuous endurance training for VO2max improvements: A systematic review and meta-analysis of controlled trials. Sports Med 45: 1469–1481, 2015.
44. Moro T, Marcolini G, Gottardi A, Reggiani C, Paoli A. Local and systemic effects of High Intensity Interval Resistance Training (HIIRT) in a population of older adults. In: Proceeding of the Physiological Society, Human Physiology Abstracts, Ageing and Degeneration. Edinburgh, United Kingdom, 2015.
45. Morton RW, Oikawa SY, Wavell CG, Mazaram N, McGlory C, Quadrilatero J, Baechler BL, Baker SK, Phillips SM. Neither load nor systemic hormones determine resistance training-mediated hypertrophy or strength gains in resistance-trained young men. J Appl Physiol 121: 129–138, 2016.
46. Ozaki H, Kakigi R, Kobayashi H, Loenneke JP, Abe T, Naito H. Effects of walking combined with restricted leg blood flow on mTOR and MAPK signalling in young men. Acta Physiol 211: 97–106, 2014.
47. Ozaki H, Loenneke JP, Buckner SL, Abe T. Muscle growth across a variety of exercise modalities and intensities: Contributions of mechanical and metabolic stimuli. Med Hypotheses 88: 22–26, 2016.
48. Ozaki H, Loenneke JP, Thiebaud RS, Abe T. Possibility of leg muscle hypertrophy by ambulation in older adults: A brief review. Clin Interv Aging 8: 369–375, 2013.
49. Ozaki H, Loenneke JP, Thiebaud RS, Abe T. Resistance training induced increase in VO2max in young and older subjects. Eur Rev Aging Phys Act 10: 107–116, 2013.
50. Ozaki H, Loenneke JP, Thiebaud RS, Abe T. Cycle training induces muscle hypertrophy and strength gain: Strategies and mechanisms (Review). Acta Physiol Hung 102: 1–22, 2015.
51. Paoli A, Moro T, Marcolin G, Neri M, Bianco A, Palma A, Grimaldi K. High-intensity interval resistance training (HIIRT) influences resisting energy expenditure and respiratory ratio in non-dieting individuals. J Transl Med 10: 237, 2012.
52. Reznick RM, Shuman GL. The role of AMP-activated protein kinase in mitochondrial biogenesis. J Physiol 574: 33–39, 2006.
53. Ritchie C. Rating of Perceived Exertion (RPE). J Physiother 58: 62, 2012.
54. Sakamoto A, Sinclair P. Muscle activations under varying lifting speeds and intensities during bench press. Eur J Appl Physiol 112: 1015–1025, 2011.
55. Sargeant AJ. Structural and functional determinants of muscle power. Exp Physiol 92: 323–331, 2007.
56. Schoenfeld B, Dawes J. High-intensity interval training: Applications for general fitness training. Strength Cond J 31: 44–46, 2009.
57. Schoenfeld B, Peterson MD, Ogborn D, Contreras B, Sonmez GT. Effects of low- versus high-load resistance training on muscle strength and hypertrophy in well-trained men. J Strength Cond Res 29: 2954–2963, 2015.
58. Schoenfeld B, Wilson JM, Lowery RP, Krieger JW. Muscular adaptations in low-versus high-load resistance training: A meta-analysis. Eur J Sport Sci 20: 1–10, 2016.
59. Smith M, Sommer A, Starkoff B, Devor S. Crossfit-based high-intensity power training improves maximal aerobic fitness and body composition. J Strength Cond Res 27: 3159–3172, 2013.
60. Spriet LL, Soderlund K, Bergstrom M, Hultman E. Anaerobic energy release in skeletal muscle during electrical stimulation in men. J Appl Physiol 62: 611–615, 1987.
61. Steele J. Intensity; in-ten-si-ty; noun. 1. Often used ambiguously within resistance training. 2. Is it time to drop the term altogether? Br J Sports Med 48: 1586–1588, 2014.
62. Steele J, Fisher J. Scientific rigour: A heavy or light load to carry? Sports Med 44: 141–142, 2013.
63. Steele J, Fisher J, McGuff D, Bruce-Low S, Smith D. Resistance training to momentary muscular failure improves cardiovascular fitness in humans: A review of acute physiological responses and chronic adaptations. J Exerc Phys 15: 53–80, 2012.
64. Westad C, Westgaard RH, De Luca CJ. Motor unit recruitment and derecruitment induced by brief increase in contraction amplitude of the human trapezius muscle. J Physiol 552: 645–656, 2003.
65. Wilkinson SB, Phillips SM, Atherton PJ, Patel R, Yarasheski KE, Tarnopolsky MA, Rennie MJ. Differential effects of resistance and endurance exercise in the fed state on signalling molecule phosphorylation and protein synthesis in human muscle. J Physiol 586: 3701–3717, 2008.
66. Willardson J, Burkett L. The effect of different rest intervals between sets on volume components and strength gains. J Strength Cond Res 22: 146–152, 2008.
67. Wilson JM, Marin PJ, Rhea MR, Wilson SMC, Loenneke JP, Anderson JC. Concurrent training: A meta-analysis examining interference of aerobic and resistance exercises. J Strength Cond Res 26: 2293–2307, 2012.
68. Winwood PW, Keogh JWL, Harris NK. The strength and conditioning practices of strongman competitors. J Strength Cond Res 25: 3118–3128, 2011.
69. Wu Z, Puigserver P, Andersson U, Zhang C, Adelmant G, Mootha V, Troy A, Ciniti S, Lowell B, Scarpulla RC, Spiegelman BM. Mechanisms controlling mitochondrial biogenesis and respiration through the thermogenic coactivator PGC-1. Cell 98: 115–124, 1999.
Keywords:

HIIT; resistance training; aerobic training; cycling; effort

© 2017 National Strength and Conditioning Association