ArticlePDF Available

Abstract and Figures

Background One of the most popular high-intensity interval exercises is the called “Tabata Protocol”. However, most investigations have limitations in describing the work intensity, and this fact appears to be due to the protocol unfeasibility. Furthermore, the physiological demands and energetic contribution during this kind of exercise remain unclear. Methods Eight physically active students (21.8 ± 3.7 years) and eight well-trained cycling athletes (27.8 ± 6.4 years) were enrolled. In the first visit, we collected descriptive data and the peak power output (PPO). On the next three visits, in random order, participants performed interval training with the same time structure (effort:rest 20s:10s) but using different intensities (115%, 130%, and 170% of PPO). We collected the number of sprints, power output, oxygen consumption, blood lactate, and heart rate. Results The analysis of variance for multivariate test (number of sprints, power output, blood lactate, peak heart rate and percentage of maximal heart rate) showed significant differences between groups ( F = 9.62; p = 0.001) and intensities ( F = 384.05; p < 0.001), with no interactions ( F = 0.94; p = 0.57). All three energetic contributions and intensities were different between protocols. The higher contribution was aerobic, followed by alactic and lactic. The aerobic contribution was higher at 115%PPO, while the alactic system showed higher contribution at 130%PPO. In conclusion, the aerobic system was predominant in the three exercise protocols, and we observed a higher contribution at lower intensities.
Content may be subject to copyright.
Submitted 18 February 2020
Accepted 31 July 2020
Published 12 October 2020
Corresponding author
Gabriel V. Protzen,
Academic editor
Daniela Foti
Additional Information and
Declarations can be found on
page 11
DOI 10.7717/peerj.9791
2020 Protzen et al.
Distributed under
Creative Commons CC-BY 4.0
Physiological aspects and energetic
contribution in 20s:10s high-intensity
interval exercise at different intensities
Gabriel V. Protzen1, Charles Bartel1,4, Victor S. Coswig2, Paulo Gentil3and
Fabricio B. Del Vecchio1
1Physical Education College, Federal University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
2Faculty of Physical Education, Federal University of Para, Castanhal, Pará, Brazil
3Faculty of Physical Education and Dance, Federal University of Goias, Goiânia, Goiás,
4Physical Education Center Admiral Adalberto Nunes, Brazilian Navy, Rio de Janeiro, Brazil
Background. One of the most popular high-intensity interval exercises is the called
‘‘Tabata Protocol’’. However, most investigations have limitations in describing
the work intensity, and this fact appears to be due to the protocol unfeasibility.
Furthermore, the physiological demands and energetic contribution during this kind
of exercise remain unclear.
Methods. Eight physically active students (21.8 ±3.7 years) and eight well-trained
cycling athletes (27.8 ±6.4 years) were enrolled. In the first visit, we collected descriptive
data and the peak power output (PPO). On the next three visits, in random order,
participants performed interval training with the same time structure (effort:rest
20s:10s) but using different intensities (115%, 130%, and 170% of PPO). We collected
the number of sprints, power output, oxygen consumption, blood lactate, and heart
Results. The analysis of variance for multivariate test (number of sprints, power output,
blood lactate, peak heart rate and percentage of maximal heart rate) showed significant
differences between groups (F=9.62; p=0.001) and intensities (F=384.05; p<
0.001), with no interactions (F=0.94; p=0.57). All three energetic contributions
and intensities were different between protocols. The higher contribution was aerobic,
followed by alactic and lactic. The aerobic contribution was higher at 115%PPO, while
the alactic system showed higher contribution at 130%PPO. In conclusion, the aerobic
system was predominant in the three exercise protocols, and we observed a higher
contribution at lower intensities.
Subjects Biochemistry, Anatomy and Physiology, Metabolic Sciences
Keywords High-intensity interval exercise, High-intensity interval training, Energy system
contribution, Physiological aspects, Anaerobic capacity, Tabata protocol
High-intensity interval exercise (HIIE) is repeated efforts with intensity above 90% of
the intensity related to maximal oxygen consumption (iV·O2MAX) followed by active or
passive recovery (Buchheit & Laursen, 2013b;MacInnis & Gibala, 2017). Effort and recovery
duration and intensity are the mainly manipulated variables during HIIE, which distinctly
How to cite this article Protzen GV, Bartel C, Coswig VS, Gentil P, Del Vecchio FB. 2020. Physiological aspects and energetic contribu-
tion in 20s:10s high-intensity interval exercise at different intensities. PeerJ 8:e9791
affect acute and chronic metabolic responses (MacInnis & Gibala, 2017). However, the
inconsistency and variability in HIIE protocols may limit its external validity and the data
extrapolation to different populations (Viana et al., 2018b).
One of the most popular HIIE structure (Tabata, 2019) was proposed by Tabata et al.,
(1996), which is also one of the most inconsistently applied protocols (Gentil et al., 2016). It
is seven to eight repetitions of 20 s of effort and 10 s of passive recovery (20s:10s) performed
until the participant was unable to keep at least 85 rpm. This HIIE model is at an intensity
equivalent to 1.7 times the measured V·O2MAX, which was calculated by the extrapolation
of the linear relationship between submaximal exercise intensity and oxygen uptake (7-8x
20s @170V·O2MAX: 10s of passive recovery). Previously, in this type of HIIE, acute studies
observed high oxygen consumption (Viana et al., 2018c), elevated glycolysis, pronounced
glycogen depletion (Scribbans et al., 2014), and high parasympathetic inhibition (Schaun
& Del Vecchio, 2018). Intermittent efforts at 170% of iV·O2MAX, obtained with a graded
exercise test, are indicated for sprint interval training or repeated sprint training, but not
for short HIIE (Buchheit & Laursen, 2013b). In a study carried out with physically active
young men on magnetic bikes, Viana et al. (2018c) verified that the 170% of iV·O2MAX
intensity allowed an average of only four repetitions, and induced a very short period at
high oxygen consumption rates. However, to date, the effect of this type of exercise in
highly trained cycling athletes habituated to this exercise model is unknown.
Notwithstanding, HIIE models based on Tabata et al. (1996) have been widely used
to improve the metabolic profile or increase physical fitness (Bonafiglia et al., 2017;
Domaradzki et al., 2020;Logan et al., 2016;Ma et al., 2013;McRae et al., 2012;Scribbans
et al., 2014). However, many investigations (Domaradzki et al., 2020;Logan et al., 2016;
Ma et al., 2013;Scribbans et al., 2014) have limitations in describing effort intensity, using
all-out efforts or different from the intensity corresponding to 170% of iV·O2MAX, therefore,
differs from the original protocol (Tabata et al., 1996;Viana et al., 2018a).
Regarding energetic responses, the authors claimed that the 20s:10s protocol reached
maximal aerobic and anaerobic demands (Tabata, 2019;Tabata et al., 1996). This statement
was because, at the end of the protocol, the subjects reached their maximal accumulated
oxygen deficit (MAOD) and an oxygen uptake equal to their V·O2MAX. However, the
model applied has been previously questioned (Bangsbo, 1992), and the acute physiological
impact of different intensities in 20s:10s HIIE on cardiorespiratory and neuromuscular
variables is unknown. Information about the contribution of energetic systems during the
20s:10s protocol is essential to understand its physiological demands, and to date, we are
aware of no studies have analysed such responses.
Therefore, considering that this knowledge is relevant to the exercise organisation, as
it allows to drive physiological stimuli according to the training status, the objectives of
the present study were to measure the physiological demands (oxygen uptake, heart rate,
and blood lactate), to assess the contribution of energy systems, as well as neuromuscular
parameters (total sprint number, mean, and maximum power output) in the 20s:10s HIIE
protocol in three different intensities, in cycling athletes and non-athletes.
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 2/15
Experimental approach to the problem
The study involved four visits, with minimum rest of 48 h and a maximum of 72 h between
them. Participants were instructed not to ingest caffeine or alcohol and not practice
intense physical exercises in the 48 h before each trial. On the first day, the ethical research
aspects, body mass measurement (Soehnle R
, Backnang, Denmark), and height (Standard,
Sanny R
, São Paulo, Brazil) were collected. On the same day, participants completed an
incremental maximal effort test to identify: (i) maximal oxygen consumption (V·O2MAX);
(ii) maximum heart rate (HRMAX); (iii) power associated with the maximum oxygen
consumption (pV·O2MAX) for sample characterisation and determination of training load.
In the following days, the participants performed the HIIE training sessions in three
different intensities in a random order, separated by a minimum and maximum interval
of 48 to 72 h, respectively. Subjects performed the training in a mechanical braking cycle
ergometer (Biotec 2100, Cefise R
, São Paulo, Brazil). Specific software was used to calculate
the power output based on wheel speed and previously informed load (Ergometric 6.0,
Cefise R
, São Paulo, Brazil). The sessions were conducted by previously trained researchers,
following the institutional safety manual.
We based the sample size calculation on data from Lopes-Silva et al. (2015). The authors
observed that the mean difference for aerobic contribution during HIIE between the
two conditions (placebo or substance) was 3%, with standard deviation from means of
2.5%. Seven individuals per group would be required, when assuming 80% power and 5%
significance level in a two-tailed test. Considering sample loss of 10%, eight individuals
participated per group. The inclusion criteria were: (i) to be physically active (more
than 150 min of physical activity per week); (ii) have no musculoskeletal, respiratory, or
cardiovascular problems; (iii) non-smoker; (iv) declare not to be anabolic androgenic
steroids user. Besides, cyclists should: (i) practice road cycling or mountain bike marathon
for more than two years and (ii) have a relative V·O2MAX equal to or greater than 50
mL. kg1.min1. The sample consisted of 16 males, of whom eight sports-engaged physical
education students (age: 21.8 ±3.7; body mass: 65.5 ±5.4 kg; HRMAX : 192.7 ±2.6
bpm; V·O2MAX: 3375.5 ±331.4 mLO2·min1; pV·O2MAX : 238.1 ±18.0 W) and eight
road cycling or mountain-bike athletes (age: 27.8 ±6.4; body mass: 70.3 ±9.5 kg; HRMAX:
188.4 ±4.5 bpm; V·O2MAX: 4122.2 ±506.7 mLO2·min1; pV·O2MAX : 351.8 ±42.6 W). All
cyclists reported doing at least eight hours of weekly training. All subjects filled informed
consent, and the Federal University of Pelotas Research Ethical Committee approved the
research project (protocol number 77729517.1.0000.5313).
Incremental maximal effort test
The incremental test started with a 2-min continuous warm-up with 0.5 kgf load. After
warming up, we increased the load every minute by 0.25 kgf, which corresponds to
approximately 25 w, until the participant reached exhaustion, or was not able to maintain
the minimum cadence of 90 rpm.
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 3/15
Training protocols
The experimental sessions began with a 5-min warm-up using a 0.5 kgf load with a cadence
between 90 and 100 rpm.
The training protocol followed the previously published pattern of effort:pause of the
20s:10s proposed by Tabata et al. (1996), and was performed using the following intensities:
(i) 115%; (ii) 130%; (iii) 170% of iV·O2MAX(denominated 115%PPO, 130%PPO, and
170%PPO, respectively), with a cadence control between 90 and 100 rpm. The subjects
were oriented to perform as many sprints as possible and to remain seated on the bicycle.
The handlebar and saddle were individually adjusted, and we used the same settings in all
experimental sessions. The training was interrupted when the subject could not maintain
the minimum predefined cadence of 90 rpm or declared voluntary exhaustion.
Gas exchanges collection
The V·O2was estimated at every three breaths using an open-circuit gas analyser
(V·O2000TM, Medical Graphics, Minnesota, US), previously calibrated and following
the manufacturer’s guidelines. In order to collect gas exchange, a NeopreneTM mask with
a high flow pneumotachograph was connected by an umbilical to V·O2000.
Gas exchanges were recorded with the participant sitting on the cycle ergometer for
5 min (Campos et al., 2012), to measure oxygen consumption associated with relative rest
before the maximal incremental test. This monitoring also occurred during the test to
identify the V·O2MAX, which was considered as the mean of last-minute values. During
training, were collected V·O2data in three different moments in each exercise protocols:
(i) relative rest, (ii) during the whole activity, and (iii) after the end of the exercise, for
seven minutes (Brooks & Mercier, 1994).
Blood lactate analysis
A sample of 15µL of blood was obtained from the finger, drained to a heparinised capillary,
and transferred to a microtube (EppendorfTM) with 30µL of EDTA anticoagulant to
measure the blood lactate concentration ([La]). We performed the analysis on a lactate
analyser (YSI 2300TM Stat Plus, Yellow Springs, Ohio, US). Blood was collected in relative
rest and minutes 1, 3, 5, and 7 after the end of each training protocols, in order to obtain
the peak lactate concentration ([La]PEAK).
Heart rate data collection
The heart rate was measured by a specific monitor (V800TM, Polar Electro, Kempele, FI),
previously validated (Giles, Draper & Neil, 2016). Participants wore a thoracic strip with
a cardiac sensor and data recorded in the watch. These procedures were used during the
incremental test to obtain maximal heart rate (HRMAX) and during each trial (115%PPO,
130%PPO, and 170%PPO) to obtain the peak heart rate (HRPEAK) in order to characterise
the cardiovascular requirements of an exercise model.
Calculation of energy system contributions
We presented the energy contribution in relative (%) and absolute (kilocalories and
kilojoules) values. We assumed that one litre of oxygen is calorically equivalent to 20.9
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 4/15
kilojoules and 5 kilocalories. Aerobic energy was estimated using the V·O2during exercise
protocols subtracted by the V·O2rest through the trapezoidal method (Bertuzzi et al., 2007).
The V·O2rest was obtained five minutes before the beginning of the protocol, with the
subjects seated. The difference between the [La]peak and the [La]rest was used in the
equation to estimate the energy production from the anaerobic lactic system, assuming that
the accumulation of 1 mmol.L1is equivalent to 3 ml.O2. kg1of body mass (Di Prampero
& Ferretti, 1999;Margaria et al., 1963). The fast component of the excess post-exercise
oxygen consumption (EPOCfast), which is similar to maximal accumulated oxygen deficit
(Zagatto et al., 2019), was used to estimate the production of alactic energy (Di Prampero &
Ferretti, 1999;Haseler, Hogan & Richardson, 1999). We observed that the slow component
of the bi-exponential model was insignificant. Therefore, we used the monoexponential
model (Eq. (1)), and the estimation was calculated by the integration of the exponential
part (Eq. (2)). These procedures were applied in previous research (Bertuzzi et al., 2007;
Campos et al., 2012) and follow previously described assumptions (Di Prampero & Ferretti,
1999). We used specific software (GEDAE-LaB, São Paulo, Brazil) to calculate the energetic
contributions. The procedure was tested and validated against traditional calculations, with
an intraclass correlation coefficient of 0.94 for energy expenditure and energy contribution
calculation (Bertuzzi et al., 2016). Following, we provided the equations used by the
software and their respective description; according to Bertuzzi et al. (2016).
V·O2(t) =V·O2rest +A[e(t/t)](1)
where ALENERGY is alactic system contribution estimated by the fast component of excess
post-exercise oxygen consumption, V·O2(t) is the oxygen uptake at time t, V·O2rest is the
rest oxygen uptake, Ais the amplitude, and tis the time constant.
Statistical analysis
A Shapiro–Wilk test confirmed the data normality distribution, and we present data
as mean and standard deviation (SD). Independent t-tests compared subjects’ physical
characteristics. We compared training protocols, energy systems, and power output with
a two-way analysis of variance (variable ×group) with repeated measures. We tested the
sphericity of the data by Mauchly’s test, and, when violated, applied Greenhouse-Geisser
correction. Bonferroni posthoc identified the significant differences in power output, and
Scheffé posthoc determined the differences between training protocols and energy systems.
Independent t-tests indicated that athletes had lower maximal heart rate (p=0.04)
and higher absolute oxygen uptake (p=0.02), age (p=0.04), and peak power output
(p<0.001) than non-athletes.
The analysis of variance for the multivariate test (number of sprints, power output,
blood lactate, peak heart rate, and percentage of maximal heart rate) resulted in significant
differences between groups (F=9.62; p=0.001) and intensities (F=384.05; p<0.001),
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 5/15
Table 1 Descriptive data from mechanical and physiological variables (n=16).
Athletes (n=8) Total Group Intensity Interaction
Variable Mean ±SD Mean ±SD Mean ±SD F (p) F (p) F (p)
Number of sprints (reps)*1.2 (0.28) 173.3 (<0.001) 0.2 (0.79)
115%PPO 17.13 ±3.60 15.50 ±3.34 16.31 ±3.46
130%PPO 9.13 ±2.53 8.13 ±1.81 8.63 ±2.19
170%PPO 4.63 ±1.60 3.88 ±1.25 4.25 ±1.44
Mean power output (w)*18.2 (0.001) 104.5 (<0.001) 4.0 (0.65)
115%PPO 339.75 ±28.69 411.25 ±52.21 375.50 ±54.95
130%PPO 392.88 ±44.05 515.38 ±60.18 454.13 ±81.22
170%PPO 503.00 ±50.50 653.38 ±110.10 578.19 ±113.48
Blood lactate (mmol.L1) 13.9 (0.002) 4.46 (0.021) 1.9 (0.16)
115%PPO 12.07 ±0.82 14.37 ±1.53 13.22 ±1.68
130%PPO 12.99 ±1.53 13.66 ±0.88 13.32 ±1.25
170%PPO 11.28 ±1.60 13.07 ±1.21 12.17 ±1.65
Peak heart rate (bpm)#2.3 (0.15) 309.6 (<0.001) 0.3 (0.74)
115%PPO 180.88 ±9.19 187.50 ±8.72 184.19 ±9.30
130%PPO 180.63 ±9.78 185.25 ±9.15 182.94 ±9.45
170%PPO 174.13 ±12.32 178.00 ±10.45 176.06 ±11.22
Heart rate (%HRmax) 1.5 (0.24) 162.2 (<0.001) 0.02 (0.98)
115%PPO 93.88 ±4.63 99.49 ±4.02 96.68 ±5.09
130%PPO 93.76 ±5.28 98.28 ±4.17 96.02 ±5.16
170%PPO 90.37 ±6.27 94.41 ±4.34 92.39 ±5.61
*all intensities are different between them (p<0.001)
#difference between 115% and 170% (p<0.001)
with no interactions. The results of univariate tests indicated that the number of sprints
and peak heart rate were higher in lower intensities, while peak power output was higher at
higher intensities (Table 1). The mean duration of each protocol was: 488, 258 and 127 s,
for 115%PPO, 130%PPO, and 170%PPO, respectively. Besides, athletes reached higher
levels of blood lactate concentration than non-athletes.
Considering absolute contribution (Fig. 1C), there were significant differences between
energetic systems (F=20.86; p<0.001) and intensities (F=12.65; p=0.001), with no
interactions between systems and groups, intensities and groups, nor systems ×intensities
×groups. Pairwise comparisons using Bonferroni posthoc test localised differences between
the three energetic systems, with a p-value lower than 0.01, as well as between the three
intensities, with p-values lower than 0.001. Repeated measures showed a linear trend for
decrease the participation of energetic system contribution (aerobic, lactic, and alactic)
for kcal (F=98.49; p<0.001), kJ (F=98.48; p<0.001) and litres of O2(F=98.45;
p<0.001), as well as a linear reduction of kcal amount (F=110.2; p<0.001), kJ amount
(F=110.22; p<0.001) and litres of O2consumed (F=109.87; p<0.001) considering
all intensities (115%, 130%, and 170%). For the total amount of kcal, kJ, and litres of O2,
no differences were found between non-athletes and athletes, but there were significant
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 6/15
Figure 1 Energetic system contribution during the 20s:10s protocol at different intensitities (n=16).
(A) The relative contribution of the energetic system in all subjects. (B) Comparison between athletes and
non-athletes of the relative contribution of the energetic system. (C) The absolute contribution of the en-
ergetic systems in non-athletes, athletes, and all subjects. * =different from lactic contribution; # =differ-
ent from alactic contribution; a, b, c =different from 115%PPO, 130%PPO, and 170%PPO respectively,
considering each energetic system; =different from cycling athletes, for the same intensity and energetic
system; PPO =peak power output.
Full-size DOI: 10.7717/peerj.9791/fig-1
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 7/15
differences between intensities (F=22.81; p<0.001), with no interactions between groups
and intensity. As a partial analysis by each energetic system, in total amount were found
a linear trend for intensity in kcal (F=106.52; p<0.001), kJ (F=106.52; p<0.001) and
litres of O2(F=109.9; p<0.001), with p-values lower than 0.001 for all comparisons
(115%PPO vs 130%PPO; 115%PPO vs 170%PPO and 130%PPO vs 170%PPO).
Concerning relative energetic contribution system, there was no effect of group (non-
athletes vs cycling athletes), but there were significant differences between intensities
(F=39.3; p<0.001), and systems (F=411.0; p<0.001), with no significant interactions
between group and intensity, group and energetic system. There was no interaction between
intensity and energetic systems contribution (F=47.81; p<0.001). Finally, we found no
interaction between group, intensity, and energetic system.
Considering the intensity and energetic systems (Fig. 1A), at 115%PPO and 130%PPO,
the aerobic contribution was higher than lactic (p<0.001) and alactic (p<0.001), with
no difference between lactic and alactic. At 170%PPO, the aerobic contribution was
different from lactic (p<0.001) and alactic (p=0.02), and lactic was different from alactic
(p=0.04). Additionally, the aerobic contribution was different considering the three
selected intensities, 115%PPO was higher than both 130%PPO (p<0.001) and 170%PPO
(p<0.001), and 130%PPO was higher than 170%PPO (p<0.001). The lactic contribution
was higher at 170%PPO in comparison to 115%PPO, and alactic contribution was higher
at 170%PPO in comparison to 115%PPO (p<0.001) and 130%PPO (p=0.02).
In absolute values (Fig. 2A), we found significant differences for intensity (F=8.35;
p=0.05), with increased O2consumption at 130%PPO (p-value =0.005 in comparison
to 115%PPO and 170%PPO), and higher O2consumption in athletes (F=6.20; p=0.02),
with no interactions between intensities and groups (F=4.36; p=0.05). Figure 2B shows
that the three intensities reached different relative values to V·O2MAX (F=3.25; p=0.05),
and the post-hoc test pointed difference between 115%PPO and 130%PPO (p=0.008),
with no differences between non-athletes and athletes, nor interactions. Additionally, there
was a quadratic trend in these relative values (F=11.30; p=0.005).
The present study aimed to analyse and compare the energetic system contribution in the
20s:10s HIIE with three different intensities in cycling athletes and non-athletes. As main
findings, we found: (i) the relative dominance of the aerobic system in all three intensities
when compared with lactic and alactic systems; (ii) the inability to perform the initially
proposed number of sprints associated with 170%PPO when the load is calculated from
graded exercise test; (iii) the 130%PPO promoted higher oxygen consumption, but only
in cyclists.
Previously, Gaitanos et al. (1993) showed that the lactic system participation reduced
significantly from the first to the tenth sprint of 6s:30s, and, at the end of the exercise,
the energy was predominantly from the alactic system, followed by an increase in aerobic
contribution. Trump et al. (1996) applied intermittent exercise with different effort:pause
structure (30s:240s). However, the results have a similar reduction in anaerobic systems
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 8/15
Figure 2 Oxygen consumption during the 20s:10s exercise at different intensities (n=16). (A) Rel-
ative to body mass and (B) relative to the maximal oxygen consumption, at 115%PPO, 130%PPO, and
170%PPO, in non-athletes and athletes. PPO =Peak power output.
Full-size DOI: 10.7717/peerj.9791/fig-2
participation and an increase in the aerobic system participation. Recently, Panissa et al.
(2018) studied a short-form of HIIE, and their findings also reinforced the raising of aerobic
contribution during HIIE. Most of the findings regarding energy systems contributions
could be related to training volume, total effort duration, or, specifically in HIIE, the sum of
repeated efforts (Buchheit & Laursen, 2013b). As these variables increase, the contribution
of the aerobic system also rises (Gastin, 2001;Glaister, 2005;Trump et al., 1996).
Based on this, it was not surprising that the protocols showed high aerobic contribution
(Gaitanos et al., 1993). Even the low exercise duration, found in the 170%PPO condition,
had an average length of approximately 120 s. About 1/3 of this time involved pause periods,
in which aerobic contribution is very high (Brooks & Mercier, 1994). The more substantial
aerobic contribution found in the 115%PPO would be explained by the relatively lower
required anaerobic contribution for lower exercise intensities. Furthermore, 115%PPO
allowed more repetitions, contributing to a longer duration in the session (488 s, vs 258
and 128 in 130%PPO and 170%PPO, respectively). We also observed that, as the intensity
increases, the anaerobic systems exert a higher relative, but not absolute, contribution.
This higher relative contribution might have occurred because, when exercising at higher
intensities, it allowed a lower number of bouts, reducing the total duration of the effort.
Despite the high blood [La-], frequently higher than 11 mmol.L1, the relative glycolytic
contribution was not so high, probably since each lactate unit corresponds to only 3 ml.O2.
kg1(Bertuzzi et al., 2016;Bertuzzi et al., 2007;Campos et al., 2012), and the participants
had higher oxygen consumption than accumulated lactate, even after respective conversion.
This fact reinforces the hypothesis that measuring the glycolytic contribution of a given
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 9/15
exercise considering only the blood [La-] might not be recommended (Bertuzzi et al.,
2016), or the glycolytic contribution is quite small during some HIIE (Gaitanos et al., 1993;
Trump et al., 1996). Another possibility is that a greater amount of lactate was metabolised
within the muscle when the exercise was longer (Brooks, 1986); possibly reducing the lactic
contribution. It is important to highlight that the assumption of equating 1 mmol.L1of
lactate to 3 ml.O2. kg1stands for submaximal exercises. However, many other studies
used that to assess supramaximal exercises lactic contribution (Bertuzzi et al., 2007;Campos
et al., 2012;Lopes-Silva et al., 2015). Further comparisons using direct measurements (i.e.,
muscle biopsy) should be made to confirm the reliability and replicability of this method.
The athletes presented higher blood [La] for all intensities, therefore, also presented
a higher absolute lactic contribution, this occurred probably due to the greater anaerobic
capacity of this population (Ponorac et al., 2007), which contributed to the higher power
output during the efforts. Regarding oxygen consumption in athletes, the highest value
was in 130%PPO. Considering that maintaining higher V·O2values during exercise is
essential for V·O2MAX increase (Midgley & Mc Naughton, 2006), the optimal intensity
for aerobic power development in athletes, in this time structure, would be near to
130%PPO. Previously, on a treadmill, other studies demonstrated that for 30s:15s training
in active young men and 15s:15s in middle-aged runners, the intensities of 110%vV·O2MAX
and100%vV·O2MAX, respectively, presented the higher oxygen consumption (Aguiar et al.,
2013;Billat et al., 2001). Otherwise, subjects maintained the V·O2closed to 90–95% of the
V·O2MAX, which is lower than the 100% reached in the original study and questioned the
author’s statement that the ’Tabata training’ should be considered as ‘‘one of the most
energetically effective exercise training protocols for maximally improving both the aerobic
and anaerobic energy-supplying systems’’ (Tabata, 2019).
Interestingly, at the initially suggested intensity of 170% V·O2MAX (Tabata et al., 1996),
most of the athletes and non-athletes were unable to complete the 7-8 sprints. This aspect
was previously questioned (Viana et al., 2018c), and these incompatibilities are possibly
due to the differences between the tests used to obtain the training loads (Tabata, 2019),
which put some light in this debatable point from the findings of the present investigation.
While Tabata et al. (1996) used an obsolete, unpractical and questionable protocol that
requires a large number of 10-min visits to the laboratory (Bangsbo, 1992;Medbo et al.,
1988), Viana et al. (2018c) we used the traditional, worldwide-used, and very practical
maximal graded exercise test (Buchheit & Laursen, 2013b).
Even using a similar graded testing protocol, our findings are different from those found
by Viana et al. (2018c), in which the intensity of 115%PPO allowed the accomplishment of
7±1 sprints, our results suggest that it is possible to perform this same number of bouts at
a higher intensity (130% PPO). Probably this difference is due to the type of ergometer used
since previous authors used a magnetic locking model. In contrast, the present study used
a mechanical braking device, similar to that used by Tabata et al. (1996). Such differences
further reinforce the problem of generalisation of interval protocols reported in previous
studies (Viana et al., 2018c), especially regarding the protocol proposed by Tabata et al.
(Tabata et al., 1996;Viana et al., 2018a).
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 10/15
There seems to be an apparent conflict in the structural variables of the HIIE protocol
with the 20s:10s effort:pause structure as commonly used (Tabata et al., 1996). According
to previous studies, we classify as a short HIIE model (effort and pause block lasting less
than one minute). However, the intensity close to 170%V·O2MAX is characteristic of Sprint
Interval Training models (Buchheit & Laursen, 2013a). Notwithstanding, the effort:pause
ratio for sprint interval training is 1:4-8 due to the need to recover anaerobic pathways to
maintain an elevated power output (Brooks & Mercier, 1994;Glaister, 2005), whereas in the
classic 20s:10s protocol this ratio is 2:1. This conflict might explain why it was not possible
to reach 7–8 bouts when using 20s:10s, with a load equivalent to 170%V·O2MAX, even in
Finally, despite the methodological issues that we should consider regarding this specific
HIIE protocol (Gentil et al., 2016;Tabata et al., 1996;Viana et al., 2018c), its potential to
induce positive physiological changes should be recognised (Ma et al., 2013;Miyamoto-
Mikami et al., 2018;Scribbans et al., 2014;Tabata et al., 1996). Both ‘‘classical’’ studies by
the ‘‘Tabata’’ group showed that participants could achieve relevant aerobic and anaerobic
improvements in a very high time-efficient manner (Tabata et al., 1996). More recently, the
same group showed that this protocol could significantly increase aerobic power, maximal
accumulated oxygen deficit, and thigh muscle cross-sectional area (Miyamoto-Mikami
et al., 2018). Further longitudinal studies should investigate this 20s:10s protocol at an
intensity range of 115 to 130%PPO in order to raise the time near and at V·O2MAX.
In conclusion, to a 20s:10s HIIE protocol, the aerobic contribution is predominant,
independently of the intensity applied in a range from 115%PPO to 170%PPO. Despite
that, the lower the intensity, the higher is the aerobic contribution, and 130%PPO is the
suggested intensity to induce higher V·O2 in trained cyclists. Finally, to reach about eight
sprints, we propose the intensity of 130% the power at V·O2MAX obtained in a graded test,
either for athletes or non-athletes.
The authors would like to acknowledge Dr Marlos R. Domingues and Dr Airton Rombaldi
for the contributions to the paper and the participants of the study for all commitment.
The authors received no funding for this work.
Competing Interests
The authors declare there are no competing interests.
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 11/15
Author Contributions
Gabriel V. Protzen conceived and designed the experiments, performed the experiments,
analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the
paper, and approved the final draft.
Charles Bartel, Victor S. Coswig and Paulo Gentil conceived and designed the
experiments, authored or reviewed drafts of the paper, and approved the final draft.
Fabricio B. Del Vecchio conceived and designed the experiments, analyzed the data,
prepared figures and/or tables, authored or reviewed drafts of the paper, and approved
the final draft.
Human Ethics
The following information was supplied relating to ethical approvals (i.e., approving body
and any reference numbers):
The Federal University of Pelotas Ethical Committee approved this research project
Data Availability
The following information was supplied regarding data availability:
All data are available in the Supplementary Files.
Supplemental Information
Supplemental information for this article can be found online at
Aguiar R, Schlickmann J, Turnes T, Caputo F. 2013. Efeito da intensidade do exercício
de corrida intermitente 30s:15s no tempo de manuten¸
cão no ou próximo do
VO2max. Motriz 19:207–216 DOI 10.1590/S1980-65742013000100021.
Bangsbo J. 1992. Is the O2 deficit an accurate quantitative measure of the anaerobic en-
ergy production during intense exercise? Journal of Applied Physiology 73:1207–1209
DOI 10.1152/jappl.1992.73.3.1207.
Bertuzzi RC, Franchini E, Kokubun E, Kiss MA. 2007. Energy system contributions
in indoor rock climbing. European Journal of Applied Physiology and Occupational
Physiology 101:293–300 DOI 10.1007/s00421-007-0501-0.
Bertuzzi R, Melegati J, Bueno S, Ghiarone T, Pasqua LA, Gaspari AF, Lima-Silva AE,
Goldman A. 2016. GEDAE-LaB: a free software to calculate the energy system
contributions during exercise. PLOS ONE 11:e0145733
DOI 10.1371/journal.pone.0145733.
Billat VL, Slawinksi J, Bocquet V, Chassaing P, Demarle A, Koralsztein JP. 2001. Very
short (15s-15s) interval-training around the critical velocity allows middle-aged
runners to maintain VO2 max for 14 min. International Journal of Sports Medicine
22:201–208 DOI 10.1055/s-2001-16389.
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 12/15
Bonafiglia JT, Edgett BA, Baechler BL, Nelms MW, Simpson CA, Quadrilatero J, Gurd
BJ. 2017. Acute upregulation of PGC-1alpha mRNA correlates with training-induced
increases in SDH activity in human skeletal muscle. Applied Physiology, Nutrition,
and Metabolism 42:656–666 DOI 10.1139/apnm-2016-0463.
Brooks GA. 1986. The lactate shuttle during exercise and recovery. Medicine and Science
in Sports and Exercise 18:360–368 DOI 10.1249/00005768-198606000-00019.
Brooks GA, Mercier J. 1994. Balance of carbohydrate and lipid utilization during
exercise: the crossover concept. Journal of Applied Physiology 76:2253–2261
DOI 10.1152/jappl.1994.76.6.2253.
Buchheit M, Laursen PB. 2013a. High-intensity interval training, solutions to the
programming puzzle. Part II: anaerobic energy, neuromuscular load and practical
applications. Sports Medicine 43:927–954 DOI 10.1007/s40279-013-0066-5.
Buchheit M, Laursen PB. 2013b. High-intensity interval training, solutions to the pro-
gramming puzzle: Part I: cardiopulmonary emphasis. Sports Medicine 43:313–338
DOI 10.1007/s40279-013-0029-x.
Campos FA, Bertuzzi R, Dourado AC, Santos VG, Franchini E. 2012. Energy demands
in taekwondo athletes during combat simulation. European Journal of Applied
Physiology and Occupational Physiology 112:1221–1228
DOI 10.1007/s00421-011-2071-4.
Di Prampero PE, Ferretti G. 1999. The energetics of anaerobic muscle metabolism:
a reappraisal of older and recent concepts. Respiration Physiology 118:103–115
DOI 10.1016/S0034-5687(99)00083-3.
Domaradzki J, Cichy I, Rokita A, Popowczak M. 2020. Effects of tabata training during
physical education classes on body composition, aerobic capacity, and anaerobic
performance of under-, normal- and overweight adolescents. International Journal of
Environmental Research and Public Health 17:876–887 DOI 10.3390/ijerph17030876.
Gaitanos GC, Williams C, Boobis LH, Brooks S. 1993. Human muscle metabolism
during intermittent maximal exercise. Journal of Applied Physiology 75:712–719
DOI 10.1152/jappl.1993.75.2.712.
Gastin PB. 2001. Energy system interaction and relative contribution during maximal
exercise. Sports Medicine 31:725–741 DOI 10.2165/00007256-200131100-00003.
Gentil P, Naves JP, Viana RB, Coswig V, Dos Santos Vaz M, Bartel C, Del Vecchio FB.
2016. Revisiting Tabata’s protocol: does it even exist? Medicine and Science in Sports
and Exercise 48:2070–2071 DOI 10.1249/MSS.0000000000001023.
Giles D, Draper N, Neil W. 2016. Validity of the Polar V800 heart rate monitor to
measure RR intervals at rest. European Journal of Applied Physiology and Occupational
Physiology 116:563–571 DOI 10.1007/s00421-015-3303-9.
Glaister M. 2005. Multiple sprint work: physiological responses, mechanisms
of fatigue and the influence of aerobic fitness. Sports Medicine 35:757–777
DOI 10.2165/00007256-200535090-00003.
Haseler LJ, Hogan MC, Richardson RS. 1999. Skeletal muscle phosphocreatine recovery
in exercise-trained humans is dependent on O2 availability. Journal of Applied
Physiology 86:2013–2018 DOI 10.1152/jappl.1999.86.6.2013.
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 13/15
Logan GR, Harris N, Duncan S, Plank LD, Merien F, Schofield G. 2016. Low-active male
adolescents: a dose response to high-intensity interval training. Medicine and Science
in Sports and Exercise 48:481–490 DOI 10.1249/MSS.0000000000000799.
Lopes-Silva JP, Silva Santos JFD, Branco BHM, Abad CCC, Oliveira LFD, Loturco I,
Franchini E. 2015. Caffeine ingestion increases estimated glycolytic metabolism dur-
ing taekwondo combat simulation but does not improve performance or parasympa-
thetic reactivation. PLOS ONE 10:e0142078 DOI 10.1371/journal.pone.0142078.
Ma JK, Scribbans TD, Edgett BA, Boyd JC, Simpson CA, Little JP, Gurd BJJOJOM,
Physiology I. 2013. Extremely low-volume, high-intensity interval training im-
proves exercise capacity and increases mitochondrial protein content in human
skeletal muscle. Open Journal of Molecular and Integrative Physiology 3:202–210
DOI 10.4236/ojmip.2013.34027.
MacInnis MJ, Gibala MJ. 2017. Physiological adaptations to interval training and the role
of exercise intensity. Journal de Physiologie 595:2915–2930 DOI 10.1113/JP273196.
Margaria R, Cerretelli P, Diprampero PE, Massari C, Torelli G. 1963. Kinetics and
mechanism of oxygen debt contraction in man. Journal of Applied Physiology
18:371–377 DOI 10.1152/jappl.1963.18.2.371.
McRae G, Payne A, Zelt JG, Scribbans TD, Jung ME, Little JP, Gurd BJ. 2012. Extremely
low volume, whole-body aerobic-resistance training improves aerobic fitness and
muscular endurance in females. Applied Physiology, Nutrition, and Metabolism
37:1124–1131 DOI 10.1139/h2012-093.
Medbo JI, Mohn AC, Tabata I, Bahr R, Vaage O, Sejersted OM. 1988. Anaerobic capac-
ity determined by maximal accumulated O2 deficit. Journal of Applied Physiology
64:50–60 DOI 10.1152/jappl.1988.64.1.50.
Midgley AW, Mc Naughton LR. 2006. Time at or near VO2max during continuous
and intermittent running. A review with special reference to considerations for the
optimisation of training protocols to elicit the longest time at or near VO2max.
Journal of Sports Medicine and Physical Fitness 46:1–14.
Miyamoto-Mikami E, Tsuji K, Horii N, Hasegawa N, Fujie S, Homma T, Uchida M,
Hamaoka T, Kanehisa H, Tabata I, Iemitsu M. 2018. Gene expression profile of
muscle adaptation to high-intensity intermittent exercise training in young men.
Scientific Reports 8:16811 DOI 10.1038/s41598-018-35115-x.
Panissa VLG, Fukuda DH, Caldeira RS, Gerosa-Neto J, Lira FS, Zagatto AM, Franchini
E. 2018. Is oxygen uptake measurement enough to estimate energy expenditure
during high-intensity intermittent exercise? Quantification of anaerobic contribution
by different methods. Frontiers in Physiology 9:868 DOI 10.3389/fphys.2018.00868.
Ponorac N, Matavulj A, Rajkovaca Z, Kovacevic P. 2007. [The assessment of anaer-
obic capacity in athletes of various sports]. Medicinski Pregled 60:427–430
DOI 10.2298/MPNS0710427P.
Schaun GZ, Del Vecchio FB. 2018. High-intensity interval exercises’ acute impact
on heart rate variability: comparison between whole-body and cycle ergome-
ter protocols. The Journal of Strength and Conditioning Research 32:223–229
DOI 10.1519/JSC.0000000000002180.
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 14/15
Scribbans TD, Edgett BA, Vorobej K, Mitchell AS, Joanisse SD, Matusiak JB, Parise
G, Quadrilatero J, Gurd BJ. 2014. Fibre-specific responses to endurance and low
volume high intensity interval training: striking similarities in acute and chronic
adaptation. PLOS ONE 9:e98119 DOI 10.1371/journal.pone.0098119.
Tabata I. 2019. Tabata training: one of the most energetically effective high-intensity
intermittent training methods. Journal of Physiological Sciences 69:559–572
DOI 10.1007/s12576-019-00676-7.
Tabata I, Nishimura K, Kouzaki M, Hirai Y, Ogita F, Miyachi M, Yamamoto K. 1996.
Effects of moderate-intensity endurance and high-intensity intermittent training
on anaerobic capacity and VO2max. Medicine and Science in Sports and Exercise
28:1327–1330 DOI 10.1097/00005768-199610000-00018.
Trump ME, Heigenhauser GJ, Putman CT, Spriet LL. 1996. Importance of muscle
phosphocreatine during intermittent maximal cycling. Journal of Applied Physiology
80:1574–1580 DOI 10.1152/jappl.1996.80.5.1574.
Viana RB, De Lira CAB, Naves JPA, Coswig VS, Del Vecchio FB, Gentil P. 2018a. Tabata
protocol: a review of its application, variations and outcomes. Clinical Physiology and
Functional Imaging 39:1–8 DOI 10.1111/cpf.12513.
Viana RB, De Lira CAB, Naves JPA, Coswig VS, Del Vecchio FB, Ramirez-Campillo R,
Vieira CA, Gentil P. 2018b. Can we draw general conclusions from interval training
studies? Sports Medicine 48:2001–2009 DOI 10.1007/s40279-018-0925-1.
Viana RB, Naves JP, De Lira CA, Coswig VS, Del Vecchio FB, Vieira CA, Gentil
P. 2018c. Defining the number of bouts and oxygen uptake during the Tabata
protocol performed at different intensities. Physiology and Behavior 189:10–15
DOI 10.1016/j.physbeh.2018.02.045.
Zagatto AM, Redkva PE, De Poli RAB, Gonzalez JAM, Brandani JZ, Penedo T,
Bertuzzi RCM. 2019. 3-min all-out effort on cycle ergometer is valid to esti-
mate the anaerobic capacity by measurement of blood lactate and excess post-
exercise oxygen consumption. European Journal of Sport Science 19:645–652
DOI 10.1080/17461391.2018.1546338.
Protzen et al. (2020), PeerJ, DOI 10.7717/peerj.9791 15/15
... On the training protocols with highintensity efforts, we could observe a higher peak and average heart rate. Other studies showed that similar high-intensity protocols could elicit a peak HR near 90% HRmax (Buchheit and Laursen, 2013;Protzen et al., 2020). Still, reestablishing steady HR values after efforts takes considerable time, depending on the subject's physical fitness (Imai et al., 1994). ...
... However, there were no significant difference in average V̇O2. Considering that previous investigation shown that the execution of four bouts at 170% V̇O2max requires just around 4.5 L of oxygen (Protzen et al., 2020), we suppose that this exercise protocol is not able to increase statistically the average V̇O2 of the whole session. The anaerobic lactic system is importantly used to perform high-intensity efforts, and the [LAC] indicates its utilization (Di Prampero and Ferretti, 1999). ...
... We found higher [LAC] during exercises with high-intensity efforts, similar to the findings of Gunnarsson et al. (2019), who also tested MICT with and without the inclusion of high-intensity bouts and found the same pattern. However, they reported slightly lower values, probably due to the protocol characteristics since our [LAC] values were similar to Protzen et al. (2020) during the 170% intermittent exercise. The higher [LAC] was an expected result since higher intensities require higher anaerobic contributions to be sustained (Ferguson et al., 2018). ...
Full-text available
To assess the physiological demand of including high-intensity efforts during continuous exercise, we designed a randomized crossover study, where 12 physically active young males executed three different exercises in random order: FATmax - continuous exercise at the highest fat oxidation zone (FATmax); 2min-130% - FATmax interspersed by a 2-min bout at 130% of the maximal oxygen uptake associated intensity (iV̇O2max); and 20s:10s-170% - FATmax interspersed by four 20-s bouts at 170%iV̇O2max interpolated by 10s of passive recovery. We measured oxygen uptake (V̇O2), blood lactate concentration ([LAC]), respiratory exchange rate (RER), fat and carbohydrate (CHO) oxidation. For statistical analyses, repeated measures ANOVA was applied. Although no differences were found for average V̇O2 or carbohydrate oxidation rate, the post-exercise fat oxidation rate was 37.5% and 50% higher during 2min-130% and 20s:10s-170%, respectively, compared to FATmax, which also presented lower values of RER during exercise compared to 2min-130% and 20s:10s-170% (p<0.001 in both), and higher values post-exercise (p=0.04 and p=0.002, respectively). The [LAC] was higher during exercise when high-intensity bouts were applied (p<0.001 for both) and higher post-exercise on the intermittent one compared to FATmax (p=0.016). The inclusion of high-intensity efforts during moderate-intensity continuous exercise promoted higher physiological demand and post-exercise fat oxidation. Novelty bullets • The inclusion of 2-min efforts modifies continuous exercise demands • Maximal efforts can increase post-exercise fat oxidation • 2-min maximal efforts, continuous or intermittent, presents similar demands.
Full-text available
Physical education classes often fail to include sufficient exercise intensity to induce changes in body tissue composition and physical fitness. Short-term high-intensity interval training protocols incorporated into physical education lessons are one possible solution to this problem. Existing studies have not examined how individuals differing in body mass index (e.g., normal-weight, underweight) respond to high-intensity interval training exercises. Therefore, this study aimed to evaluate the effects of a Tabata protocol on body composition measurements, aerobic capacity, and motor performance in underweight and overweight adolescents (the experimental groups) vs normal-weight adolescents (here regarded as the control group). The sample included 58 adolescents (28 boys, mean age = 16.2 years; 30 girls, mean age = 16.2 years) who completed the high-intensity interval training and the following set of measurements pre-and post-intervention: height, weight, body fat percentage and waist-to-hip ratio, physical efficiency index (based on the Harvard Step Test), agility (in 4 × 10 shuttle run test), and lower-limb muscle power in vertical jump. The results showed that high-intensity interval training was effective in reducing body weight, waist-to-hip ratio, and body fat percentage only in overweight individuals. Improvement in aerobic capacity was found only in underweight and overweight boys. Further research should focus on the development of customized exercise protocols and their adaptation to girls and assess the sustainability of the changes induced.
Full-text available
For decades, high-intensity interval/intermittent exercise training methods have been used by elite athletes to improve their performance in sports. One of the most effective training methods, i.e., ‘Tabata training,’ is reviewed herein from the viewpoint of the energetics of exercise. The prior research describing the metabolic profile and effects of Tabata training is also summarized, with some historical anecdotes. © 2019, The Physiological Society of Japan and Springer Japan KK, part of Springer Nature.
Full-text available
The purpose of this study was to investigate the use of a single 3-min all-out maximal effort to estimate anaerobic capacity (AC) through the lactate and excess post-exercise oxygen consumption (EPOC) response methods (AC[La-]+EPOCfast) on a cycle ergometer. Eleven physically active men (age = 28.1 ± 4.0 yrs, height = 175.1 ± 4.2 cm, body mass = 74.8 ± 11.9 kg and ⩒O2max = 40.7 ± 7.3 mL kg-1 min-1), participated in the study and performed: i) five submaximal efforts, ii) a supramaximal effort at 115% of intensity of ⩒O2max, and iii) a 3-min all-out maximal effort. Anaerobic capacity was estimated using the supramaximal effort through conventional maximal accumulated oxygen deficit (MAOD) and also through the sum of oxygen equivalents from the glycolytic (fast component of excess post-exercise oxygen consumption) and phosphagen pathways (blood lactate accumulation) (AC[La-]+EPOCfast), while during the 3-min all-out maximal effort the anaerobic capacity was estimated using the AC[La-]+EPOCfast procedure. There were no significant differences between the three methods (p > 0.05). Additionally, the anaerobic capacity estimated during the 3-min all-out effort was significantly correlated with the MAOD (r = 0.74; p = 0.009) and AC[La-]+EPOCfast methods (r = 0.65; p = 0.029). Therefore, it is possible to conclude that the 3-min all-out effort is valid to estimate anaerobic capacity in physically active men during a single cycle ergometer effort.
Full-text available
Abstract High-intensity intermittent exercise training (HIIT) has been proposed as an effective approach for improving both, the aerobic and anaerobic exercise capacity. However, the detailed molecular response of the skeletal muscle to HIIT remains unknown. We examined the effects of the HIIT on the global gene expression in the human skeletal muscle. Eleven young healthy men participated in the study and completed a 6-week HIIT program involving exhaustive 6–7 sets of 20-s cycling periods with 10-s rests. In addition to determining the maximal oxygen uptake ($${\dot{{\rm{V}}}{\rm{O}}}_{2{\rm{\max }}}$$ V˙O2max ), maximal accumulated oxygen deficit, and thigh muscle cross-sectional area (CSA), muscle biopsy samples were obtained from the vastus lateralis before and after the training to analyse the skeletal muscle transcriptome. The HIIT program significantly increased the $${\dot{{\rm{V}}}{\rm{O}}}_{2{\rm{\max }}}$$ V˙O2max , maximal accumulated oxygen deficit, and thigh muscle CSA. The expression of 79 genes was significantly elevated (fold-change >1.2), and that of 73 genes was significantly reduced (fold-change
Full-text available
Purpose: The aim of the present study was to compare the contributions of the anaerobic pathway as determined by two different methods and energy expenditure during a typical high-intensity intermittent exercise (HIIE) protocol. Methods: A descriptive research design was utilized in which thirteen physically active men performed six experimental sessions consisting of an incremental test (session 1), submaximal tests at 40, 50, 60, 70, 75, 80, 85, 90% of velocity associated with maximum oxygen uptake (vV˙O2max) with two intensities per session (sessions 2–5), and the HIIE protocol (session 6; 10 efforts of 1 min at vV˙O2max interspersed by 1 min of passive recovery). The estimation of anaerobic energy system contribution was calculated by: (a) the excess post-exercise oxygen consumption plus delta lactate method and (b) the accumulated oxygen deficit method using the difference between predicted oxygen demand from the submaximal tests of varying intensities and accumulated oxygen uptake during HIIE. Estimation of aerobic energy system contribution was calculated through the measurement of oxygen consumption during activity. Total EE during the entire HIIE protocol (efforts + recovery) and for the efforts only were calculated from each method. Results: For efforts + recovery and efforts only, anaerobic contribution was similar for both methods, and consequently total EE was also equivalent (p = 0.230 for both comparisons). During efforts + recovery, aerobic:anaerobic energy system contribution was (68 ± 4%: 32 ± 4%), while efforts only was (54 ± 5%: 46 ± 5%) with both situations demonstrating greater aerobic than anaerobic contribution (p < 0.001 for both). Conclusion: Anaerobic contribution seems to be relevant during HIIE and must to be taken into account during total EE estimation; however, the type of method employed did not change the anaerobic contribution or total EE estimates.
Full-text available
Interval training (IT) has been used for many decades with the purpose to increase performance and promote health benefits while demanding a relatively small amount of time. IT can be defined as intermittent periods of intense exercise separated by periods of recovery and has been divided into high-intensity interval training (HIIT), sprint interval training (SIT) and repeated sprint training (RST). IT use resulted in the publication of many studies and many of them with conflicting results and positions. The aim of this article was to move forward and understand studies’ protocol in order to draw accurate conclusions, as well as to avoid previous mistakes and effectively reproduce previous protocols. When analyzing the literature, we found many inconsistencies, such as, the controversial concept of ‘supramaximal’ effort, a misunderstanding regarding the term ‘high intensity’ and the use of different strategies to control intensity. The adequate definition and interpretation of training intensity seems to be vital, since the results of IT are largely dependent on it. These observations are only a few examples of the complexity involved with IT prescription, discussed to illustrate some problems with the current literature regarding IT. Therefore, it is our opinion that it is not possible to draw general conclusions about IT without considering all variables used in IT prescription, such as, exercise modality, intensity, effort andrest times and participants’ characteristics. In order to help guide researchers and health professionals in their practices it is important that experimental studies report their methods in as much detail as possible and future reviews and meta-analyses should critically discuss the articles included in light of their methods to avoid inadequate generalizations.
Full-text available
Study aimed to compare the effects of two high-intensity interval exercises (HIIT) protocols on heart rate variability (HRV). Twelve young adult males (23.3 ± 3.9 years, 177.8 ± 7.4 cm, 76.9 ± 12.9 kg) volunteered to participate. In a randomized cross-over design, subjects performed two HIIT protocols, one on a cycle ergometer (TBT; eight 20 s bouts at 170% Pmax interspersed by 10 s rest) and another with whole-body calisthenic exercises (MCR; eight 20 s all-out intervals interspersed by 10 s rest). HRV outcomes in the time, frequency and non-linear domains were assessed on three moments: (a) pre-session; (b) immediately post-session; and (c) 24h post-session. Results revealed that RRmean, Ln rMSSD, Ln HF, Ln LF were significantly reduced immediately post-session (p < 0.001) and returned to baseline 24h after both protocols. Additionally, LF/HF ratio was reduced 24h post-session (p < 0.01) and SD2 was significantly lower immediately post-session only in TBT. Our main finding was that responses from HR autonomic control were similar in both protocols, despite different modes of exercise performed. Specifically, exercises resulted in a high parasympathetic inhibition immediately after session with subsequent recovery within one day. These results suggest that subjects were already recovered the day after and can help coaches to better program training sessions with such protocols.
Full-text available
The purpose of the present study was to determine if acute responses in pgc-1α, vegfa, sdha, and gpd1/2 mRNA expression predict their associated chronic skeletal muscle molecular (SDH/GPD activity and substrate storage) and morphological (fibre type composition and capillary density) adaptations following training. Skeletal muscle biopsies were collected from fourteen recreationally active men (age: 22.0 ± 2.4 years) before (PRE) and 3 hours after (3HR) the completion of an acute bout of SIT (eight, 20-second intervals at ~170% VO2peak work rate separated by 10 seconds of recovery). Participants then completed 6 weeks of SIT 4 times per week with additional biopsies after 2 (MID) and 6 (POST) weeks of training. Acute increases in pgc-1α mRNA strongly predicted increases in SDH activity (a marker of oxidative capacity) from PRE and MID to POST (PRE-POST: r = 0.81, r2 = 0.65, p < 0.01; MID-POST: r = 0.79, r2 = 0.62, p < 0.01) and glycogen content from MID to POST (r = 0.60, r2 = 0.36, p < 0.05). No other significant relationships were found between acute responses in pgc-1α, vegfa, sdha, and gpd1/2 mRNA expression and chronic adaptations to training. These results suggest that acute upregulation of pgc-1α mRNA relates to the magnitude of subsequent training-induced increases in oxidative capacity, but not other molecular and morphological chronic skeletal muscle adaptations. Additionally, acute mRNA responses in pgc-1α correlated with vegfa, but not sdha, suggesting a coordinated upregulation between pgc-1α and only some of its proposed targets in human skeletal muscle.
It is usually reported that the Tabata protocol (TP) is performed with eight bouts of 20:10 intervals at a load equivalent to 170% of iV̇O2max. However, the feasibility of accumulating 160 s of work at 170% iV̇O2max has been questioned. This article tested the intensity that would allow the performance of the original TP on a cycle ergometer, and measured the highest value of oxygen consumption (V̇O2) obtained during the TP and the time spent above 90% of the maximal oxygen uptake (V̇O2max) during the TP performed at different intensities. Thirteen young active males (25.9 ± 5.5 years, 67.9 ± 9.2 kg, 1.70 ± 0.06 m, 23.6 ± 3.1 kg·m-2) participated in the study. Participants performed a graded exertion test (GXT) on a cycle ergometer to obtain maximum oxygen consumption (V̇O2max) and the intensity associated with V̇O2max (iV̇O2max). V̇O2, maximal heart rate (HRmax), and number of bouts performed were evaluated during the TP performed at 115%, 130%, and 170% of i V̇O2max. V̇O2max, HRmax, and iV̇O2max were 51.8 ± 8.0·min-1, 186 ± 10 bpm, and 204 ± 26 W, respectively. The number of bouts performed at 115% (7 ± 1 bouts) was higher than at 130% (5 ± 1 bouts) and 170% (4 ± 1 bouts) (p < .0001). The highest V̇O2 achieved at 115%, 130%, and 170% of iV̇O2max was 54.2 ± 7.9 mL·kg-1·min-1, 52.5 ± 8.1 mL·kg-1·min-1, and 49.6 ± 7.5 mL·kg-1·min-1, respectively. Non significant difference was found between the highest V̇O2 achieved at different intensities, however qualitative magnitude-inference indicate a likely small effect between 115% and 170% of iVO2max. Time spent above 90% of the V̇O2max during the TP at 115% (50 ± 48 s) was higher than 170% (23 ± 21 s; p < 0.044) with a probably small effect. In conclusion, our data suggest that the adequate intensity to perform a similar number of bouts in the original TP is lower than previously proposed, and equivalent to 115% of the iV̇O2max. In addition, intensities between 115 and 130% of the iV̇O2max should be used to raise the time spent above 90% V̇O2max.