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High-Intensity Interval Resistance Training (HIRT) influences resting energy
expenditure and respiratory ratio in non-dieting individuals
Journal of Translational Medicine 2012, 10:237 doi:10.1186/1479-5876-10-237
Antonio Paoli (antonio.paoli@unipd.it)
Tatiana Moro (tatiana.moro.phd@gmail.com)
Giuseppe Marcolin (giuseppe.marcolin@unipd.it)
Marco Neri (neri@cervia.com)
Antonino Bianco (antonino.bianco@unipa.it)
Antonio Palma (antonio.palma@unipa.it)
Keith Grimaldi (keith.grimaldi@gmail.com)
ISSN 1479-5876
Article type Research
Submission date 29 September 2012
Acceptance date 21 November 2012
Publication date 24 November 2012
Article URL http://www.translational-medicine.com/content/10/1/237
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© 2012 Paoli et al.
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High-Intensity Interval Resistance Training (HIRT)
influences resting energy expenditure and
respiratory ratio in non-dieting individuals
Antonio Paoli
1*
*
Corresponding author
Email: antonio.paoli@unipd.it
Tatiana Moro
1
Email: tatiana.moro.phd@gmail.com
Giuseppe Marcolin
1
Email: giuseppe.marcolin@unipd.it
Marco Neri
2
Email: neri@cervia.com
Antonino Bianco
3
Email: antonino.bianco@unipa.it
Antonio Palma
3
Email: antonio.palma@unipa.it
Keith Grimaldi
4
Email: keith.grimaldi@gmail.com
1
Department of Biomedical Sciences, Physiological Laboratory, University of
Padova, via Marzolo 3, Padova 35131, Italy
2
Italian Fitness Federation, Ravenna, Italy
3
Department of Sports and Exercise Science (DISMOT), University of Palermo,
Palermo, Italy
4
Biomedical Engineering Laboratory, Institute of Communication and Computer
Systems, National Technical University of Athens, Athens, Greece
Abstract
Background
The benefits of exercise are well established but one major barrier for many is time. It has
been proposed that short period resistance training (RT) could play a role in weight control
by increasing resting energy expenditure (REE) but the effects of different kinds of RT has
not been widely reported.
Methods
We tested the acute effects of high-intensity interval resistance training (HIRT) vs. traditional
resistance training (TT) on REE and respiratory ratio (RR) at 22 hours post-exercise. In two
separate sessions, seventeen trained males carried out HIRT and TT protocols. The HIRT
technique consists of: 6 repetitions, 20 seconds rest, 2/3 repetitions, 20 secs rest, 2/3
repetitions with 2′30″ rest between sets, three exercises for a total of 7 sets. TT consisted of
eight exercises of 4 sets of 8–12 repetitions with one/two minutes rest with a total amount of
32 sets. We measured basal REE and RR (TT
0
and HIRT
0
) and 22 hours after the training
session (TT
22
and HIRT
22
).
Results
HIRT showed a greater significant increase (p < 0.001) in REE at 22 hours compared to TT
(HIRT
22
2362 ± 118 Kcal/d vs TT
22
1999 ± 88 Kcal/d). RR at HIRT
22
was significantly lower
(0.798 ± 0.010) compared to both HIRT
0
(0.827 ± 0.006) and TT
22
(0.822 ± 0.008).
Conclusions
Our data suggest that shorter HIRT sessions may increase REE after exercise to a greater
extent than TT and may reduce RR hence improving fat oxidation. The shorter exercise time
commitment may help to reduce one major barrier to exercise.
Keywords
Resistance training, Resting energy expenditure, Interval training, Respiratory ratio
Background
Daily energy expenditure may be divided into different components that can be categorized
as a) resting metabolism, b) thermic effects of food and c) the energy expenditure of physical
activity associated with exercise and non-exercise movement [1,2]. An analysis of the
literature shows that in Western countries the mean ratio of daily energy expenditure and
resting energy expenditure (REE) is 1.66; this means that only 40% of energy is expended on
activity while the remaining 60% is expended at rest [3]. It has been calculated that three 30
min sessions of vigorous exercise per week increase energy demands by 1,039 Kcal/week
(i.e. only 5.3% of the average weekly expenditure 19,562 Kcal/week) [3] but to achieve a
level of energy expenditure comparable with that of humans living in primitive societies it
would be necessary to exercise at high intensity for 90 minutes every day. It is evident that
this amount of time cannot be proposed to the average population, even exercising 30
minutes per day, three times a week involves a high rate of drop out [4]. Notwithstanding
these considerations, clinical practice and data from the literature consistently point to the
beneficial effect of even just some exercise on fat loss and other health aspects [5]. The only
way to reconcile the apparently contradictory evidence between experimental and clinical
data is to hypothesize that other exercise related factors are involved in the fat-loss effect
other than the simple increase in energy expenditure during exercise. Hence we should
consider basically three fundamental mechanisms that may play a role in this complex
interrelationship, a) exercise might reduce hunger, b) exercise might improve fitness levels
and consequently might change behaviour related to non-exercise activity thermogenesis such
as walking, stair climbing, etc. [2,5], c) a positive effect of exercise on resting metabolism -
the latter is the subject of our study. As underlined above resting energy expenditure (REE) is
the largest component of the daily energy budget and, consequently, any increase in REE in
response to exercise could potentially have a great impact on health promotion and weight
control. In recently published weight control guidelines resistance training (RT) has been
incorporated as an important component of exercise protocols [6,7]. RT acts in a substantially
different way compared to endurance training (ET), it increases muscle mass in the long term
[8] but also increases excess post-exercise oxygen consumption (EPOC) immediately after
the training session [9]. As Gaesser and Brooks identified in 1984 oxygen consumption
(VO
2
) decreases exponentially following an exercise session, starting from this observation
they defined the recovery period in which an increase in oxygen uptake is observed as
“excess post-exercise oxygen consumption” (EPOC) [10]. This elevated post-exercise
metabolism plays a part in the energy cost of exercise and influences the thermic effect of
activity. Numerous studies have demonstrated the effect of endurance training on basal
metabolic rate and on respiratory ratio, but data from research on resistance training and
EPOC are conflicting. The difficulty in measuring energy expenditure during non-steady-
state intermittent physical activity may be one of the reasons for this lack of a substantial
body of literature, but the main point is that several different types of RT training protocols
are confounded under the umbrella name of “resistance exercise” (e.g. circuit training or
multiple sets), so it is difficult to quantify how the particular type of weights, sets, repetitions,
and length of rest periods utilised [11,12], influence the energy cost of the exercise [13].
Recently increased interest has been shown in the concept of HIT (High-Intensity Interval
Training) investigated by Gibala and his group [14]. Low-volume HIT is characterized by
brief repeated ‘bursts’ of vigorous exercise interspersed with periods of rest or low-intensity
exercise for recovery. It is notable from these studies and the evidence that demonstrates the
close connection between EPOC and exercise intensity that there are surprisingly few reports
comparing the different kinds of strength training techniques. The aim of our study was to
investigate whether and how two different kinds of resistance training, a traditional and a
high-intensity resistance protocol, affect resting energy expenditure and respiratory ratio 22
hours after the training session.
Methods
Study participants
18 resistance-trained males (28 ± 4.5 yrs old, 4–6 yrs training experienced), height 174 cm
(±3), weight 84 Kg (±3) responded to an invitation to participate in the study. Respondents
provided written informed consent and were screened for the presence of disease or
conditions that could place them at risk of an adverse response to exercise. Subjects were not
taking any medications and had medium experience in resistance training (±3.5 years) so
familiarization sessions were not necessary. Muscle and fat quantities & percentages were
assessed by skin fold measurements which are highly correlated with percent body fat in fit
and healthy young men [15]. We used software (Fitnext®, Caldogno, Vicenza, Italy) that
includes 9 skinfolds (triceps, biceps, pectoral, subarmpit, subscapular, iliac crest, mid-
abdominal, anterior thigh, medial calf), 6 bone circumferences (arm, forearm, waist, hip,
thigh, calf), 4 bone diameters (elbow, wrist, knee, ankle), waistline and hip circumference
measurements [8]. Anthropometric measurements were performed according to the
Anthropometric Standardization Reference Manual [16]. Weight was measured to the nearest
0.1 kg using an electronic scale (Tanita BWB-800 Medical Scales, USA), and height to the
nearest 1 cm using a Harpenden portable stadiometer (Holtain Ltd, UK). Skinfolds were
measured to the nearest 1 mm using a Holtain caliper, and circumferences to the nearest 1
mm using an anthropometric tape. All measurements were taken by the same operator (LC)
before and during the study according to standard procedures [16]. One subject withdrew
from the study for personal reasons. The study was approved by the Ethical Board of the
University of Padova Department of Biomedical Sciences and conformed to standards for the
use of human subjects in research as outlined in the current Declaration of Helsinki.
Investigators explained the purpose of the study, the protocol to be followed, and the
experimental procedures to be used prior to allowing participants to enter the study (Table 1).
Table 1 Physical and anthropometrical characteristics of the subjects
variable
mean
SD
Age (years) 28 4.5
Height (cm) 174 3
Body mass (Kg) 84 3
Body fat (%) 8.5 4.7
Muscle (Kg) 51 6.2
Study design
The 17 subjects performed a 6-RM test with the various exercises included in the training
schedule as described elsewhere [17]. A 6 RM test is suitable for testing maximal strength in
subjects with little or no previous resistance training experience. Data obtained from the
initial test was used to determine an appropriate starting level for resistance training. This
technique has been shown to have high reproducibility (r = 0.99). Subsequently subjects did a
specific warm-up for each 1RM test by performing 5 repetitions with a weight they could
normally lift 10 times. Using procedures described elsewhere [18] the weight was gradually
increased until failure occurred in each of the exercises tested for rest pause (leg press, bench
press, traction at dorsal machine). The higher load was considered the 1 RM [18]. The test-
retest reliability in our laboratory for 1RM varies from 0.92 to 0.97 (ICC). A 10 minutes
warm up (treadmill run at 10 Km/h) was performed prior to training. The following week
exercise trials were carried out to determine the appropriate load to complete 6 repetitions in
the HIRT exercise. Using a trial and error modified methodology [18] starting with 40% and
then after 5 minutes rest increasing the resistance by 5%. All subjects were able to complete 6
repetitions at 80–85% of the 1RM. The same methodology was used to assess the load that
enabled the subjects to perform 12 repetitions (65–70% 1RM). The HIRT technique consisted
of three series of 6RM followed by rest for 20 seconds; then the subject lifts the same weight
until reaching the point of failure (habitually 2 repetitions) followed by 20 seconds rest then
another 2/3 repetitions [8,19-21]. This sequence counted as one set, then subjects rested 2′30″
before performing a second and third set. Leg exercise included 3 sets with 2′30″ of rest
between sets [21,22] whilst pectoral and latissimus dorsi consisted of two sets. The training
session lasted approximately 32 minutes (including the warm up period).
In the TT session, using a modified exercise protocol [23], subjects performed four sets of
eight different weight-lifting exercises and the intensity of each lift was set between 70% and
75% of their pre-established 1-RM. Subjects were instructed to perform as many repetitions
as possible in a set, the usual number of lifts before failure was between 8 and 12 with one
minute of rest between sets for single-joints exercises and two minutes for multiple-joint
exercises. The protocol included: bench press, dorsal machine, military press, bicep curls and
triceps extensions, leg press and leg curls, and sit-ups [6]. The training session lasted
approximately 62 minutes (including the warm up period). The cadence between repetitions
during both protocols was controlled [19]. As expected the of muscle action velocityvaried
between subjects due to their different anatomical leverage, also there was a slight difference
between repetitions for the same subject. However the average time of movement was
superimposable and it was calculated as approximately 1.0 seconds for the concentric phase
and 2.0 seconds for the eccentric phase.
On the first day measurements were taken of anthropometrics, basal REE and RR as
described below. After a standard breakfast (described elsewhere, see Paoli et al. 2011 [24],
they randomly performed the traditional training (TT
0
) or the high-intensity interval training
(HIRT
0
); immediately after which blood lactate was measured. After 22 hours the subjects
were recalled in the laboratory to repeat the basal condition measurements of REE and RR
(HIRT
22
or TT
22
.) The study was a cross-over design and one week later, under similar
conditions, the subjects that performed TT in the first session carried out HIRT in the second,
and vice versa. During the three days before each training session and during the day after,
participants were provided a standard diet that provided approximately 20% fat, 55% CHO
and 25% protein. The diet was designed to meet the free-living energy requirement estimate
(REE x 1.4-1.8 according to self-reported physical activity levels) [25] (Figure 1).
Figure 1 Scheme of experimental design
Measurements
Resting energy expenditure (REE) was analyzed using oxygen uptake (V’O
2
), carbon dioxide
production (V’CO
2
) and respiratory ratio (RR) measurements with an Ergocard®
ergospirometer (Pacific Medical Systems, Hong Kong , S.A.R) and a ‘pitot tube’
pneumotacograph equipped with standard gas analysers [24]. The gas analysis was performed
in the morning before breakfast (7–8 am), while the subjects were seated. The room was
dimly lit, quiet and approximately 24 C. Oxygen uptake was measured (ml/min) and also
normalized to body weight (ml/kg/min) and the respiratory exchange ratio (RR) was
determined. After resting for 15 minutes, data was collected for 30 min and only the last 20
minutes were used to calculate the respiratory gas parameters [26]. The system was calibrated
before each measure using calibration syringes and precision oxygen and carbon dioxide gas
mixtures. Subjects were requested to abstain from caffeine or alcohol consumption for 24 h
prior to the measurement. V’O2 data were converted to REE expressed in Kcal/d using
appropriate RR values and established tables based on the Weir equation [27].
Blood Lactate was measured using SensLab Lactate Scout – Test strips (Bautzner Staβe 67;
Leipzig, Germany) based on the capillary blood lactate [18] oxidised by redox reaction via
electrode mediation. Blood samples were taken from earlobe after 5 and 10 minutes after the
end of training sessions to measure the lactate peak [28]. To verify that none of the subjects
modified their nutritional behaviour during the intervention protocol (the day before and
during the test day) an assessment of dietary intake was performed and analysed using
DietComp® (Caldogno, Vicenza, Italy) software demonstrating a substantial similarity [24].
Statistical analysis
Data is expressed as mean and standard deviation. Bland-Altman plots and comparison of the
test-retest measurements performed in our laboratory confirmed good reproducibility of the
measurements for RR and V’O
2
(ICC >0.85 and >0.9 respectively with p < 0.05). The
sequence of the training sessions (HIRT or TT) was generated by a random function. Data
analysis was performed using the software package GraphPad Prism version 4.00 for
Windows, GraphPad Software, San Diego California USA. An ANOVA repeated
measurements was conducted since in this kind of experimental design subjects serve as their
own control and assuming four different time points [29]. The substantial overlapping of
basal condition was checked by a paired t-test to exclude a carryover effect. Whenever
significant differences in values occurred, a Bonferroni test post-hoc was used. P-values was
set at 0.05.
Results
The total volume of work performed in the resistance training (loads x sets x repetitions) was
significantly lower (P < 0.001) during the HIRT (3872.4 ± 624 Kg ) compared to the TT
(7835.2 ±1013 kg). The mean level of maximal post-exercise blood lactate (Table 2) after
HIRT (10.5 ± 2.1 mmol⋅L
-1
) was significantly greater (p < 0.05) than after TT (5.1 ± 1.2
mmol L
-1
). Table 3 describes Resting Energy Expenditure and Respiratory Ratio data during
the recovery and 22 hours after the two training exercise interventions. No significant
differences were measured between TT
0
and HIRT
0
. As showed in Figure 2 there was a
significant difference in energy expenditure for the TT exercise protocol (TT
0
1901 ± 93
Kcal/d vs TT
22
1999 ± 88 Kcal/d), and for HIRT where the difference even more marked
(HIRT
0
1910 ± 89 Kcal/d vs HIRT
22
2362 ± 118 Kcal/d; p < 0.001). The comparison between
TT22 and HIRT22 also demonstrated a significant difference (p < 0.001). At basal
conditions, the values of RR in the two experimental conditions were similar (TT
0
0.826 ±
0.009; HIRT
0
0.827 ± 0.006) whilst a significant difference (P < 0.001) was found 22 hours
after the training session in HIRT
22
(0.798 ± 0.010) compared to both HIRT
0
(0.827 ± 0.006)
and TT
22
(0.822 ± 0.008).
Table 2 La (blood lactate) mean values and SD before and after training
TT
before
TT
afer
P value
HIRT
before
HIRT
after
P value P value
TT
after
vs
HIRT
after
La (mmol/L)
0.8 ± 0.2 5.1 ± 1.2 <0.001
0.8 ± 0.2 10.5 ± 2.1 <0.001 <0.001
P values of Bonferroni post hoc test are reported for before and after training sessions
Table 3 REE (resting energy expenditure) and RR (respiratory ratio) mean values and
SD at baseline and 22 hours after training sessions
TT
0
TT
22
P value
HIRT
0
HIRT
22
P value P value
TT
22
Vs
HIRT
22
REE (Kcal/d)
1901 ± 93 1999 ± 89 <0.001
1910 ± 90 2362 ± 118 <0.001 <0.001
RR
0.826 ± 0.009
0.822 ± 0.008 n.s. 0.827 ± 0.006
0.798 ± 0.010
<0.001 <0.001
P values of Bonferroni post hoc test are reported for within and between training sessions
Figure 2 Resting energy expenditure REE and respiratory ratio RR before and 22 after
high-intensity interval training and traditional training. ** = p < 0.001
Discussion
To the best of our knowledge this is the first study to compare the effects of acute high-
intensity interval resistance training with a traditional widely used training routine. The most
interesting finding in this investigation was that V’O2 following HIRT remained significantly
elevated even at 22 h post exercise and that this elevation was greater than has been reported
before for other training protocols. Our results are in line with those of Schuenke et al. [9]
except that in our case we observed a higher post exercise elevation of REE. Although the
beneficial effect on health and weight control of a 24 hour increase in metabolism is evident
[30] the optimal amount and type of exercise routine remains to be established. We recently
proposed that resistance training should be investigated more thoroughly and rigorously by
taking into account the variables involved including 1) muscle action used, 2) type of
resistance used, 3) volume (total number of sets and repetitions), 4) exercises selected and
workout structure (e.g. the number of muscle groups trained), 5) the sequence of exercise
performance, 6) rest intervals between sets, 7) repetition velocity and 8) training frequency
[11,12,21]. In the present study we chose a specific method of resistance training in order to
simplify the interpretation and clarify the effect of RT on post exercise metabolism [11,12].
In recent years the HIT (high-intensity interval training) methodology has been widely
studied by Gibala’s group [14] but HIT is based on a substantially cyclic, endurance type
movement (e.g. cycling). Most commonly the sprints are performed on a stationary cycle
ergometer at an intensity approaching 90% of maximal oxygen uptake (V˙O2max). The most
common protocol in published research is the Wingate test which consists of 30s of an all-out
hard resistance sprint and subjects typically perform the Wingate test 4 to 6 times separated
by 4 min of rest [14]. There are several reports that weight training may require more energy
and a longer duration for recovery [31,32] compared to endurance training but despite this
there are surprisingly few studies published on the specific influence of high intensity
resistance training on metabolism. There are many factors that influence EPOC including for
example the exercise order [33] but in particular the intensity and duration of exercise
appears to be of greater importance. As Knuttgen asserted, the EPOC increased exponentially
as a function of exercise intensity, whereas it increased linearly as a function of exercise
duration [34]. Other studies reported that higher intensity resistance exercise generates
greater EPOC than lower intensity resistance exercise [35,36]. Many authors [9,13,37]
explain the basis of the greater increase in EPOC after more intense exercise as involving a
perturbation of energy homeostasis. This consideration could help to explain the conflicting
data between our study plus others reporting similar REE increases of between 16-20%
[9,38,39] and several that reported a more modest increases (4–10%) [23,40-42]. Schuenke
demonstrated an increase of 21.2% in 24 hours metabolism after a resistance training using a
8–12 repetitions per set with 2 minutes of rest between exercises [9] in circuits whilst a recent
paper by Heden [41] has documented that one set or three set whole body training has the
same effect on REE at 24 h post training (about 5%). This study used the ACSM guidelines:
10 repetitions, 10 exercises, divided into three circuit rotations each consisting of three or
four different exercises with 30 sec of rest between each exercise. This kind of circuit training
imposes by necessity a low total intensity of exercise. Our training protocol, on the contrary
was performed at very high intensity [8,21] which can be demonstrated by the greater
increase in maximal blood lactate levels and it is well known that lactate plays a role in the
total increase of post exercise energy expenditure [43]. The greater level of lactate during the
recovery phase in HIRT is evidence of a major metabolic stress derived from high intensity
resistance training and may reflect the utilization of lactate as fuel in the aerobic pathway.
But lactate removal may only be part of the process, in fact if lactate is infused during the
post-exercise period it does not elicit a further increase in EPOC [44]. Lactate may explain,
together with an increase in body temperature and the triacylglycerol cycle, only the short
term component of EPOC [10,45]. Of the two phases in which EPOC can be divided: short
term and long term, only the latter can explain the increase of resting energy expenditure
registered 20–24 hours after training [46].
It is noteworthy that in our study, HIRT22 as well as registering a significantly higher REE
also showed a lower RR. Regarding the latter Bahr et al. [45] taking into account the total
energy expenditure and the rate of fatty acid oxidation from measurements of O
2
uptake,
respiratory exchange ratio, and urinary nitrogen excretion and the observation of a
prolongation of the EPOC beyond one hour, claimed that triacylglycerol/fatty acid cycling is
an important supporter of the energy cost in the prolonged component of EPOC because it is
an indicator that the organism is using fatty acids rather than glycogen to satisfy the energy
cost of exercise. Poehlman and Melby [47] added that the elevated fat oxidation noted during
the recovery from any kind of resistance training seems to be a compensatory sparing of
glycogen. Hence the significant lowering of RR after 22 hour after HIRT reflects an
increased lipolytic effect. The Respiratory Ratio is a good way to identify the origin of energy
substrates: when RR is close to 0.7 it means that the major energy source is lipids while when
the ratio is near 1 carbohydrates are the main source of energy; in consideration of this, the
results of our study, including a significant decrease of RR (from 0.827 ± 0.006 to 0.798 ±
0.010) 22 hours after HIRT whereas TT appeared to remain substantially unaltered, suggests
that the HIRT might improve lipid metabolism at rest. The cause of this RR lowering could
be explained in several ways: the more classical, cited above, is that glucose metabolic
pathways are directed to replenish glycogen stores first [48] instead of being used for energy
supply. This means that glucose and all gluconeogenic precursors will be spared from further
oxidation and will be converted to glucose and glycogen, so lipids become the preferred
oxidation substrate; the higher intensity of HIRT compared to TT is logically expected to
produce a greater decrease of muscle glycogen. One intriguing hypothesis involves the
AMPK/ACC (AMP kinases/ Acetyl CoA Carboxylase) relationship. It has been demonstrated
that intense exercise [49] increases AMPK, thus AMPK can phosphorylate ACC decreasing
its activity; the decreased ACC activity leads to a decrease in the rate of the synthesis of
MalonylCoA and consequently there is a release of inhibition of CPT1 (Carnitine
palmitoyltransferase I) activity leading to an increase in lipid oxidation [50]. Also the
increase of ANP (atrial natriuretic peptide) stimulated by exercise could play a role in the
increased rate of lipid oxidation; production of ANP is related to the intensity of exercise
[51,52] and it has been demonstrated that ANP increases lipolysis [53], this pathway appears
to be more suitable than the increase in catecholamines that have a very short half-life and
appears not to be related to lipolysis after RT [54]. Growth hormone increase also could
explain a part of the increase in lipid oxidation; it was demonstrated by Bottaro et al. [55] that
intense exercise with incomplete recovery might stimulate GH production in significant
manner. An exciting new hypothesis suggests that some cytokines and other peptides
(myokines) that are produced and released by muscle fibres can exert autocrine, paracrine or
endocrine effects that might influence the metabolic effect of exercise [56]. A recent paper
describes a new polypeptide hormone, irisin, which is regulated by PGC1-α, it is secreted
from muscle into the bloodstream and may activate thermogenic mechanisms in adipose
tissue - this might also play a role in short time reported to lower RR [57]
As stated before reported REE after resistance training varies from 5-10% to 20%. These
inconsistent results can be attributed to the different intensity and technique of RT used in the
various studies. Our investigation showed an increase in basal metabolism after resistance
exercise which we were also able to detect 22 hours after the training session. The increase of
REE after TT was about 5% whilst after HIRT it was 23% and these data suggest an
important effect on metabolism corresponding to 452 Kcal per day. Our data are consistent
with those of Shuenke [9] and Melanson [38,39] but with higher values compared to previous
studies. This difference may be explained by the higher intensity of our protocol although the
physiological basis underlying this long lasting effect is still not completely understood. The
effect on REE of an increase of muscle mass can be assessed only with longer training
periods and not after a single bout of exercise. Some reports suggests that the β–adrenergic
system may be involved in such an increase [42], while another explanation could be
hormonal variations [9]. In fact, in response to exercise-induced trauma an increase of
metabolic hormonal concentration is seen (e.g., cortisol, catecholamines, and thyroid
hormone) that could increase metabolism. More likely increased protein re-synthesis due to
post-exercise muscle damage is energy expensive (approximately 20% increase in resting
metabolism) [58] and could contribute to greater EPOC after high intensity resistance training
[43,59]. It could be speculated that the eccentric component of movement might have a much
greater influence on the protein re-synthesis expense compared to the concentric movement
but since in our protocol both exercise executions were superimposable regarding
eccentric/concentric contractions, this aspect should be investigated further. The present
study has a number of strengths. One is the novelty of our approach: the comparison between
traditional and high intensity resistance training - to our knowledge this is the first report
about the metabolic effects of High Intensity resistance Training. Our data demonstrate that
one training session of HIRT appeared to have a more positive effect on metabolism during
the day following the training session as the elevation of resting energy expenditure was
maintained 22 hours after HIRT and at a higher level than for the TT session. The 22 hour
Respiratory Ratio was lower in HIRT with respect to TT, reflecting an increased lipid
oxidation at rest. Another strength of this study is that we propose a suitable protocol, with a
small time commitment and significantly low volume, producing important metabolic and
cardiovascular adaptations that could be a positive aid for weight control and fat loss and that
may be useful in overweight subjects. HIRT is an atypical RT protocol: in HIRT subjects use
heavy loads that induce mechanical effects on muscle but also use very short recovery
periods comparable to an high intensity endurance training (like Hit). The main limitations of
this study is that our subjects were mediumly trained and (as Laforgia notes “The utility of
supramaximal interval training for weight loss is nevertheless limited because this type of
training is beyond the capabilities of non-athletes” [13] could raise some concerns about the
transfer of the methodology and results to sedentary/overweight subjects. In this regard, we
and others [8,60], have demonstrated that it is possible, after a familiarization period, for
previously untrained persons to successfully perform this kind of training – however it would
be correct to exert appropriate caution when applying this protocol to overweight/obese
subjects. Our next steps will be to verify the suitability of HIRT on a larger overweight/obese
[8].
Conclusions
Our results suggest that high-intensity interval resistance training increases excess post
exercise energy consumption to a significantly greater extent than traditional resistance
training. This exercise methodology allows subjects to improve metabolism and, at the same
time, muscle mass and strength all of which are promoted as beneficial by many guidelines.
In Western society leisure time is lacking and motivation to perform daily exercise is
uncommon resulting in low overall levels of daily lifestyle related physical activity. In this
situation a short intense training that enables elevation of basal metabolism whilst lowering
RR (i.e. increase fat consumption at rest) may be an interesting and attractive alternative to
more traditional and time consuming exercise and could be a useful tool in the physician’s
hand. While the results of this study are encouraging further investigation is needed to
explain the molecular pathways involved in such responses and the hormonal adaptation to
HIRT.
Abbreviations
HIRT, High-intensity interval resistance training; TT, Traditional training; REE, Resting
energy expenditure; RR, Respiratory ratio; EPOC, Excess post-exercise oxygen consumption
Competing interests
Authors declare no competing interests
Authors’ contributions
AP was the main researcher and was responsible for study design, statistical analysis and
interpretation of data and draft of manuscript, conceived the study, participated in its design,
drafted the manuscript and performed the statistical analysis. TM was responsible for study
design and acquisition of data, GM was responsible for acquisition of data and participated in
the statistical analysis, MN conceived the study and participated in its design, AB conceived
the study and participated in its design, AP helped to draft the manuscript, KG participated in
design of the study and helped to draft the manuscript. All authors read and approved the
final manuscript.
Funding
This study was supported by laboratory research funds at University of Padova.
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22 h
Lactate
breakfast
HIRT
or
TT
5
min
Lactate
30
REE and RR
REE and RR
30
22 h
Lactate
breakfast
HIRT
or
TT
5
min
Lactate
30
REE and RR
REE and RR
30
1 week
Figure 1
1500
2500
**
**
**
REE (Kcal/day)
0.7
0.8
0.9
**
**
RR
TT
0
TT
22
HIRT
0
HIRT
22
TT
0
TT
22
HIRT
0
HIRT
22
Figure 2
