Energy cost of isolated resistance exercises across low- to high-intensities
Energy cost of isolated resistance exercises across low- to high-intensities
Victor Machado Reis 0 1
Nuno Domingos Garrido 0 1
Jeferson Vianna 1
Ana Catarina Sousa 0 1
JoseÂ VilacË a Alves 0 1
MaÂ rio Cardoso Marques 0 1 2
0 Research Center in Sports Sciences, Health Sciences & Human Development, CIDESD, Vila Real, Portugal, 2 University of TraÂs-os-Montes & Alto Douro, Vila Real, Portugal, 3 Federal University at Juiz de Fora, Minas Gerais, Brazil, 4 Polytechnic Institute of Viana do Castelo , Viana do Castelo , Portugal
1 Editor: Tiago M. Barbosa, Nanyang Technological University , SINGAPORE
2 University of Beira Interior, Department of Sport Sciences , Covilhã , Portugal
This study aimed to estimate the energy cost across various intensities at eight popular resistance exercises: half squat, 45Ê inclined leg press, leg extension, horizontal bench press, 45Ê inclined bench press, lat pull down, triceps extension and biceps curl. 58 males (27.5 ± 4.9 years, 1.78 ± 0.06 m height, 78.67 ± 10.7 kg body mass and 11.4 ± 4.1% estimated body fat) were randomly divided into four groups of 14 subjects each. For each group, two exercises were randomly assigned and on different days, they performed four bouts of 5-min constant-intensity for each of the two assigned exercises: 12%, 16%, 20% and 24% 1-RM. Later, the subjects performed exhaustive bouts at 80% 1-RM in the same two exercises. The mean values of VO2 at the last 30s of exercise at 12, 16, 20 and 24% 1RM bouts were plotted against relative intensity (% 1-RM) in a simple linear regression mode. The regressions were then used to predict O2 demand for the higher intensity (80% 1-RM). Energy cost rose linearly with exercise intensity in every exercise with the lowest mean values were found in biceps curl and the highest in half squat exercise (p<0.001). Half squat exercise presented significant (p<0.001) higher values of energy cost in all intensities, when compared with the remaining exercises. This study revealed that low-intensity resistance exercise provides energy cost comprised between 3 and 10 kcal min-1. Energy cost rose past 20 kcal min-1 at 80% 1-RM in leg exercise. In addition, at 80% 1-RM, it was found that upper body exercises are less anaerobic than lower-body exercises.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
Funding: The authors received no specific funding
for this work.
Competing interests: The authors have declared
that no competing interests exist.
Resistance exercise (RE) has been progressively more and more popular and is now included
in programs which are designed to address weight loss and to target recommended energy
cost values [
]. Before time was often supported by non-empirical data about a possible higher
energy cost at RE, as compared with typical aerobic activities such as running, cycling or
]. Comparisons of the excess-post exercise oxygen consumption in RE, with that
involved in typical aerobics, showed higher magnitude in RE [
], which also contributed to
Estimates of the energy cost at RE usually reflect mean values during a whole exercise
session (thereby including exercise and recovery periods), ranging considerable between 3 and 11
kcal min-1 in adult males [4±7]. This large variability is explained by the amount of possible
combinations of different exercises, movement cadences, intensities, number of repetitions
and also the type of equipment that is used (i.e. machines vs. free weights) [
]. Past research
has also addressed the energy costs involved in programs were RE and aerobics combined in
the same session, with mean values of 6±7 kcal.min-1 while performing the RE, and of 12±14
kcal min-1 while performing the aerobics [
]. In fact, this is now a popular type of program
which seems to match most of the populations attending fitness centres. A common ground
among the aforementioned studies is the use of typical high-intensity loads (above 70% 1-RM)
performed until exhaustion.
Very few studies have addressed the energy cost during isolated RE performed across various
intensities. Robergs et al. [
] produced the first paper based in the accumulated oxygen deficit
method for RE, combining aerobic and anaerobic estimates from gas exchanges. They studied
solely the squat and the bench press exercises, estimating energy cost ranging between 11 and 18
kcal min-1 and from 8 to 16 kcal min-1, respectively (40 to 70% 1-RM). Also, Scott and co-workers
presented a series of studies on isolated exercises, in which they combine aerobic estimates from
gas exchange with anaerobic estimates from blood lactate (50 to 90% 1-RM). Their calculations
ranged between 3 and 16 kcal min-1 at bench press [10±12], between 3 and 7 kcal min-1 at biceps
curl; and between 6 and 9 kcal min-1 at leg press [
]. In all the above, aerobic energy release
during RE was measured through indirect calorimetry, but the anaerobic estimates vary between
studies, with the blood lactate energy equivalent being predominant in the literature [10±12].
Current evidence on rate-based energy cost measurements in isolated RE is still scarce, and
especially, at low-intensity loads. Despite other models proved more suitable for intermittent
], more data from the typical rate (per minute) energy cost measurements seem needed
to foster subsequent counterpoints and different approaches. Due the growing interest of
lowintensity RE (i.e. to address the elderly or some pathologies) it is necessary to accumulate data
on the specific energy cost of the most popular exercises and, in the future, to use such data to
build technology that enables accurate calorie count during RE.
The aim of the present study was to estimate the energy cost across various low-intensities at
eight popular resistance exercises: half squat, 45Ê inclined leg press, seated leg extension,
horizontal bench press, 45Ê inclined bench press, wide grip front lat pull down, standing triceps
extension on high-pulley and seated arm curl in Scott bench with Z bar. This was achieved by
combining measurements of oxygen uptake and anaerobic estimates by the accumulated
oxygen deficit method. It was hypothesized that energy cost would be higher in lower body
exercises and that it would rise linearly with intensity.
Materials and methods
A total of 58 males (27.5 ± 4.9 years, 1.78 ± 0.06 m height, 78.67 ± 10.7 kg body mass and
11.4 ± 4.1% estimated body fat), engaged in RE training for at least one year with three or
more training sessions per week, volunteered and included the sample. They were recruited
among the population engaged in resistance exercise in four fitness centers. Individuals who
used medication which could influence their cardiorespiratory response were not included
in the sample. After medical approval, the volunteers received the explanations about the
procedures, as well as the risks and discomforts involved in the study and signed the written
consent form. All procedures were approved by the Review Board of the University of
TraÂs-osMontes & Alto Douro and were conducted according to the principles expressed in the
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Declaration of Helsinki. The volunteers were told to refrain from any resistance exercise
during the period of the experiment.
Two exercises were randomly assigned to each subject, so that each and every one was
evaluated in two RE. Hence, a total of 15 subjects performed each exercise. All testing was
performed in the afternoon (except for the anthropometric measurements), at a temperature
between 20-25CÊ and 35±45% relative air humidity. Each and every subject was submitted to
seven testing sessions, as follows.
On the first day, height, weight and several skin folds (chest, mid-axillary, tricipital, sub
scapular, abdominal, supra iliac, and thigh) were measured. A calibrated caliper (Lange,
Cambridge Scientific Industries, USA) and a digital medical scale with stadiometer (Seca 763, USA)
were used for all measurements. Body density was calculated using the equation proposed by
Jackson and Pollock [
] and Siri's equation was used to convert the density in percentage of
fat mass. These measurements were performed in the morning. In the afternoon of the same
day, the subjects performed the 1-RM test at the two assigned exercises using the protocol
described elsewhere [
], which was repeated on the second visit (72 hours later). The highest
1-RM with less than 5% difference was considered as the true 1-RM.
On the third to the sixth visit (with 48-hour intervals), the subjects performed (on each
visit) two bouts of 4-min constant-intensity exercise -one bout for each of the two assigned
exercises. Exercise order for each individual was random and so was the intensity. At each and
every RE four intensities were used: 12%, 16%, 20% and 24% 1-RM, amounting a total of four
bouts for each exercise All exercises were performed with trademark standardized machines
(Panatta Sport, Apiro, Italy).
On the last visit (48 hour later) the subjects performed exhaustive bouts at 80% 1-RM in the
same two exercises (in random order and with 1-hour recovery between them).
No warm-up was performed before any of the four low-intensity bouts of exercise. Before
the 80% 1-RM bout, 2x 15 repetitions with a 24% 1-RM load were used as warm-up, 20 and
10-min before the experimental bout. The cadence of 15 repetitions per minute (2 s on the
eccentric and 2 seconds on the concentric phase) was paced by an electronic metronome
sound in the four low-intensity bouts. In the higher-intensity bout, cadence was freely chosen
by the participant.
During all exercises, expired gases were measured breath-by-breath continuously by open air
circuit analyzer (COSMED1 K4b2, Rome, Italy). To guarantee accuracy of the gas analysis and
minimize respiratory artifacts the participants were instructed avoid unintentional Valsalva
maneuvers and inadequate breathing [
]. The gas analyzer was calibrated following the
manufacturer's specifications before each testing [
]. The mean values of oxygen uptake (VO2)
at the last 30 s of exercise with 10 s averaging procedure  at 12, 16, 20 and 24% 1-RM bouts
were plotted against relative intensity (% 1-RM) in a simple linear regression mode. A
minimum duration of 4 min was required for a bout to enter this analysis and only steady-state
averaging values were included in the regression (variation less than 2 ml kg-1 min-1). In
addition, a zero-load VO2 (individual resting measurement) was also included in the regression by
a non-forced procedure. The regressions were then used to predict O2 demand for the higher
intensity (80% 1-RM). Anaerobic energy release was calculated by the accumulated oxygen
deficit method, as explained elsewhere [
]. For final data presentation in this paper, measured
O2 was converted into energy units (calorie) by a conversion factor of 1 ml O2 = 5 calorie.
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The sample dimension analysis was performed using G Power 3.1 software [
]. Under a
framework assuming an estimation error of α = 0.05, power = 80%, having 5 measures
(intensities) x 8 exercises, an n of 16 was necessary to reach statistical power of 80.8%. Therefore, 20
subjects were initially assigned to each exercise. After drop-out and discard of poor data, the
amount per exercise varied between 14 and 17 valid cases. It was decided to favour the same
size for each exercise, thereby having a final n = 14. Repeated measures ANOVA was used to
analyze energy cost values (8 exercises x 5 intensities), followed by BonferroniÂs post-hoc,
whenever necessary. Normality, homogeneity and Sphericity assumptions were confirmed with
Shapiro-Wilk, LeveneÂs and Mauchly tests, respectively. The partial eta squared (ηp2) was used
as effect size and interpreted according to Cohen [
]. Overall data for each exercise are
presented as means, standard deviations and 95% confidence interval. Significance was set at 5%.
Table 1 presents mean and standard deviations of the energy cost in the eight exercises at the
various low intensities. Energy cost increased steadily with exercise intensity in every exercise.
The lowest mean values were found in biceps curl and the highest in half squat exercise. It was
observed a intensity effect (F(4, 416) = 796.337; p < 0.001; ηp2 = 0.88) and also an exercise effect
on energy cost (F(7, 104) = 62.451; p < 0.001; ηp2 = 0.81). A significant interaction exercise x
intensity was also found (F(28, 416) = 37.077; p < 0.001; ηp2 = 0.71). Half squat exercise
presented significant (p<0.001) higher values of energy cost in all intensities, when compared
with the remaining exercises. Table 2 displays data from the high-intensity bout. This was an
exhaustive bout and time to exhaustion varied from 26 second in the horizontal bench press
and 56 second in the leg press. Energy cost at this intensity presented significant (p<0.001)
higher values, when compared with the remaining intensities in every exercise. Fig 1, Fig 2 and
Fig 3 depicts energy cost at two intensities (20% and 80% 1RM) in the eight exercises. At the
higher intensity, biceps curl was the single exercise with mean values below 10 kcal min-1,
whereas energy cost attained values above 30 kcal min-1 in half squat (ηp2 = 0.81). Fig 4 shows
the anaerobic fraction of energy release at the 80% 1-RM bout in the eight exercises. Aerobic
energy was predominant in biceps curl and in front lat pull down.
The aim of the present study was to estimate the energy cost in resistance exercises performed
at low intensities (12%, 16%, 20%, 24% 1RM) during 4-min steady-state exercise; Moreover,
the former estimates were extrapolated for 80% 1RM exercise intensity. From the eight popular
resistance exercises selected for this study, the half squat and leg extension were the ones
which involved higher energy cost (~11 and ~8 kcal min-1, respectively), contrasting with the
biceps curl and lat pull down (~3 and ~4 kcal min-1, respectively) at all intensities studied. In
addition, we can conclude that, even at a high intensity± 80% of 1-RM, energy cost of the
upper limbs may be mainly aerobic whereas those of the lower limbs are evidently anaerobic.
Energy cost at lower intensities
The majority of studies conducted used a typical high-intensity loads (above 70% 1-RM), and
therefore, very few studies have addressed the energy cost during isolated RE performed across
various low-intensities. To the best of our knowledge, a single study [
] used a similar method
to this study (linear extrapolation of RE using 4 or 5-minute steady state values of oxygen
uptake) reporting a energy cost of 8 kcal min-1 for bench press and 11 kcal min-1 for squat at
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H = horizontal; I = inclined; ext = extension.
ωÐp<0.02 compared with all exercises with exception of H Bench press and Leg press
χÐp = 0.001 compared with Biceps curl
fÐp<0.0001 compared with all exercises with exception of I Bench press and Leg press
ϕÐp<0.02 compared with all exercises with exception of Leg press
$Ðp<0.0001 compared with all exercises
ψÐp<0.0001 compared with all exercises with exception of the Leg press
#Ðp<0.05 compared with 12% 1-RM; βÐp<0.03 in relation to Lat pull down, Biceps curl and Triceps ext
+Ðp<0.05 compared with 12% and with 16% 1-RM
ΩÐp<0.0001 compared with all exercises with exception of I Bench press and Leg press
?±p<0.01 compared with 20% 1-RM
&Ðp<0.0001 compared with all exercises with exception of I Bench press.
40% 1RM. In the present study, we found lower values at intensities up to 24% 1RM: 4.8
kcal min-1 for horizontal bench press and 6.5 kcal min-1 for inclined bench press. However,
the value reported for squat exercise (11.7 kcal min-1) corroborated the previous suggested.
Buitrago et al. [
], though with chest press machine exercise, provided evidence in favour of
the linearity of power and energy cost, especially with aerobic energy cost. Although using a
different methodÐpeak blood lactate accumulation post effort, some reported similar energy
cost values to ours: 2.7, 5.3 and 7.26 kcal min-1when performing bench press at 50% 1RM with
7, 14 and 21 repetitions, respectively [
]. In the present study, the eight RE showed values
between 3.87 kcal min-1 and 11.70 kcal min-1 when performed at low intensity (24% 1-RM). A
circuit RE including exercises at moderate intensity (~43% 1-RM) also showed energy cost ~9
] Collectively, these studies suggest that even at low intensities, RE could be an
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efficient method to weight loss purposes. In fact, typical reference values of 3 METs and 8.5
METs are described for walking at 4km h-1 and running at 8 km h-1, respectively, in one
subject with body weight similar to those in the present study [
Fig 1. Energy cost (kcal.min-1) in two intensities (20% and 80% 1RM) at horizontal and inclined bench
press. The 10 kcal min-1 reference line is shown.
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Fig 2. Energy cost (kcal.min-1) in two intensities (20% and 80% 1RM) at leg press, leg extension and
half squat. The 10 kcal min-1 reference line is shown.
Energy cost and anaerobic energy release at high-intensity
When using O2 demand to predict energy cost at the higher intensity (80% 1-RM) by simple
linear regression mode, we found values that are close to those reported with the same method
] in bench press exercise at 70% of 1-RM. However, when the squat exercise is taking into
account, our values are 50% higher than those reported (36 kcal min-1 vs.18 kcal min-1,
respectively). The large variation of the results found could be related, in one hand, with of the
standard error of the regression line between VO2 and work. In fact, this latter was larger in the
half squat (~19 ml kg min-1), compared with the other exercises. On the other hand, the
different intensities used in the studies (70% and 80% of 1-RM) and difference between
subjectsalthough we watched carefully for variations in technique or rate, each subject can present
different changes with volume, intensity or fatigue, may have contributed to the differences
found between studies. Although not yet investigated in RE, the lack of linearity between work
rate and oxygen uptake throughout all intensities, due to some potential mechanics
(intensification of respiratory muscle activity increased muscle temperature, increased activation of
additional muscle groups, recruitment of type II muscle fibers, lactate and proton
accumulation) may have also played an important role [
The accumulated oxygen deficit allows the quantification of the aerobic and anaerobic
fraction of energy release in relation to the overall energy cost. This method, rarely used in RE, is
considered as the most reliable available measure of anaerobic energy release during high
intensity exercise [
]. In RE the quantification of anaerobic energy release by the blood lactate
equivalent has been more popular [10±12]. However, blood lactate on and off-kinetics during
RE is still poorly understood, and therefore prone to the several sources of error pointed out
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Fig 3. Energy cost (kcal.min-1) in two intensities (20% and 80% 1RM) at biceps curl, lat pull down and
triceps extension (lower panel). The 10 kcal min-1 reference line is shown.
for cycling [
]. Moreover, this method also requires another assumption (not measure) as to
the alactic fraction of energy release.
In the present study, the anaerobic fraction of energy release at the 80% of 1-RM presented
a higher percentage in the majority of the exercises, as expected, due to limited ATP and
creatine phosphate stores within working skeletal muscle [
]. However, the biceps curl and lat
pull down exercises had an anaerobic fraction under 50%, with the triceps extension exercise
showing a little up of the reference line. Collectively, these results suggest that even at a higher
intensity, energy cost of the upper limbs may be mainly aerobic whereas those of the lower
limbs are evidently anaerobic. Considering the latter, we suggest that a larger recovery is
needed after lower limb exercises for similar exercise intensity.
Not consistent with this hypothesis, is the horizontal and 45Ê inclined bench press exercises.
In fact, the anaerobic energy cost of the latter was ~13 and 17 kcal min-1 (respectively)
representing from 70 to 77% of total energy release, which confirms previous data [
] at 37 to 90%
1-RM. This apparent inconsistency could be related with the muscle mass involved. Therefore,
when upper limbs exercises involve small muscle masses, a higher fraction of aerobic energy
seems to be present, and vice versa. This fact suggests that not only which members are
involved in the exercise, attention must be driven also to the amount of muscle mass involved.
Moreover, the upper-body has a higher proportion of fast-twitch fibres [
], being these
related with an increased inefficiency compared with lower body-exercise [
]. In fact, Muraki
et al. [
] by studying triceps brachii muscle oxygen saturation using Near Infra Red
Spectometry during arm cranking and cycling exercise in young women, noted a faster increase in the
respiratory exchange ratio and a lower ventilatory threshold in arm compared with leg
exercise, suggesting accelerated anaerobic glycolysis. Notwithstanding the previously mentioned,
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Fig 4. Anaerobic fraction of energy release at the 80% 1-RM bout in the eight different exercises. The
50% reference line is shown. PH = press horizontal; PI = press inclined.
the potential mechanism behind the energy cost in RE involving both lower and upper body
limbs, with small and higher fractions of total muscle mass has, to date, not been investigated.
This study revealed that resistance exercise may provide energy cost compatible with weight
loss purposes, even if low-intensity and large-volume workout is performed. In addition, at
high-intensity, is seems that upper body exercises are less anaerobic than lower-body exercises.
This better knowledge about energy cost during RE can help professionals to predict
accumulated energy cost during a session based in the eight popular exercises herein. In the future and
with further data on various exercises and various populations, hopefully one can accurately
design new technology (wearable or attached to weight machines) that enables accurate calorie
count during resistance exercise.
Despite the fact that the accumulated oxygen deficit method does not requires
measurements of low-intensity blood lactate, this may be viewed as a possible limitation of this
experiment. The analysis herein can be improved, at least theoretically, by including low-intensity
blood lactate measures. The results herein were obtained with a population of male, apparently
healthy well-trained individuals and therefore may not apply to less-trained individuals or to
special other populations.
The results herein confirm the hypothesis that energy cost during resistance exercise rises
linearly with intensity. They also confirm the hypothesis that lower body exercise present higher
energy cost when compared with upper body exercise. Half squat and leg extension involved
the highest energy cost (~11 and ~8 kcal min-1, respectively), contrasting with biceps curl and
lat pull down (~3 and ~4 kcal min-1, respectively). These values refer to low-intensity exercise
(between 12 and 24% 1-RM).
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S1 Dataset. Dataset used in this research.
Conceptualization: Victor Machado Reis, MaÂrio Cardoso Marques.
Data curation: Jeferson Vianna.
Formal analysis: JoseÂ VilacËa Alves.
Funding acquisition: Victor Machado Reis, MaÂrio Cardoso Marques.
Investigation: Victor Machado Reis, Nuno Domingos Garrido, Jeferson Vianna.
Methodology: Victor Machado Reis, JoseÂ VilacËa Alves.
Project administration: Victor Machado Reis, MaÂrio Cardoso Marques.
Supervision: Victor Machado Reis.
Validation: Victor Machado Reis.
Visualization: Nuno Domingos Garrido, Ana Catarina Sousa.
Writing ± original draft: Victor Machado Reis, Nuno Domingos Garrido, Jeferson Vianna,
JoseÂ VilacËa Alves.
Writing ± review & editing: Ana Catarina Sousa, MaÂrio Cardoso Marques.
10 / 11
1. American College of Sports Medicine. Position stand: Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise . Med Sci Sports Exerc . 2011 ; 43 : 1334 ± 1359 . https://doi.org/ 10.1249/MSS.0b013e318213fefb PMID: 21694556
2. Di Prampero PE , Ferretti G. The energetics of anaerobic muscle metabolism: A reappraisal of older and more recent concepts . Respir Physiol . 1999 ; 118 : 103 ± 115 . PMID: 10647856
3. Drummond M , Vehrs P , Schaalje G , Parcell A . Aerobic and resistance exercise sequence affects excess postexercise oxygen consumption . J Strength Cond Res . 2005 ; 19 : 332 ± 337 . https://doi.org/ 10.1519/R-14353.1 PMID: 15903371
4. Ballor D , Becque M , Katch V . Energy output during hydraulic resistance circuit exercise for males and females . J Strength Cond Res . 1989 ; 3 : 7± 12 .
5. Pichon C , Hunter G , Morris M , Bond R , Metz J . Blood Pressure and heart rate response and metabolic cost of circuit versus traditional weight training . J Strength Cond Res . 1996 ; 10 : 153 ± 156 .
6. Hunter G , Seelhorst D , Snyder S. Comparison of metabolic and heart rate responses to super slow vs. traditional resistance training . J Strength Cond Res . 2003 ; 17 : 76 ± 80 . PMID: 12580660
7. Vilaca-Alves J , Saavedra F , Simão R , Novaes JS , Rhea MR , Green D , et al. Does aerobic and strength exercise sequence in the same session affect the oxygen uptake during and postexercise? J Strength Cond Res . 2012 ; 26 : 1872 ± 1878 . https://doi.org/10.1519/JSC.0b013e318238e852 PMID: 21986689
8. Garnacho-Castaño MV , Dominguez R , MateÂ-Muñoz JL . Understanding the meaning of lactate threshold in resistance exercises . Int J Sports Med . 2015 ; 36 : 371 ± 377 . https://doi.org/10.1055/s-0034- 1398495 PMID: 25680073
9. Robergs RA , Gordon T , Reynolds J , Walker TB . Energy expenditure during bench press and squat exercises . J Strength Cond Res . 2007 ; 21 : 123 ± 130 . https://doi.org/10.1519/R-19835.1 PMID: 17313290
10. Scott CB . Contribution of blood lactate to the energy expenditure of weight training . J Strength Cond Res . 2006 ; 20 : 404 ± 415 . https://doi.org/10.1519/R-17495.1 PMID: 16686572
11. Scott CB , Croteau A , Ravlo T. Energy expenditure before, during, and after the bench press . J Strength Cond Res . 2009 ; 23 : 611 ± 618 . https://doi.org/10.1519/JSC.0b013e31818c2845 PMID: 19197214
12. Scott CB , Leighton BH , Ahearn KJ . Aerobic, anaerobic, and excess postexercise oxygen consumption energy expenditure of muscular endurance and strength: 1-set of bench press to muscular fatigue . J Strength Cond Res . 2011 ; 25 : 903 ± 908 . https://doi.org/10.1519/JSC.0b013e3181c6a128 PMID: 20703175
13. Scott CB , Reis VM . Steady state models provide an invalid estimate of intermittent resistance-exercise energy costs . Eur J Human Movement . 2014 ; 33 : 70 ± 78 .
14. Jackson AS , Pollock ML . Generalized equations for predicting body density of men . Br J Nutr . 1978 ; 40 : 497 ± 504 . PMID: 718832
15. Kraemer WJ , Fry AC . Strength testing: development and evaluation of methodology . In: Maud P and Nieman DC , editors. Fitness and sports medicine: a health-related approach . Palo Alto: Bull Publishing; 1995 . pp. 115 ± 138 .
16. Buitrago S , Wirtz N , Yue Z , Kleinoder H , Mester J . Mechanical load and physiological responses of four different resistance training methods in bench press exercise . J Strength Cond Res . 2013 ; 27 : 1091 ± 1100 . https://doi.org/10.1519/JSC.0b013e318260ec77 PMID: 22692106
17. McLaughlin JE , King GA , Howley ET , Basset DR Jr, Ainsworth BE. Validation of the COSMED K4 b2 portable metabolic system . Int J Sports Med . 2001 ; 22 : 280 ± 284 . https://doi.org/10.1055/s-2001 -13816 PMID: 11414671
18. Welch WA , Strath SJ , Swartz AM . Congruent validity and reliability of two metabolic systems to measure resting metabolic rate . Int J Sports Med . 2015 ; 36 : 414 ± 418 . https://doi.org/10.1055/s-0034- 1398575 PMID: 25700097
19. Tian Y , He Z , Xu C , Huang C , Lee JH , Li R , et al. Energy expenditure and fitness responses following once weekly hill climbing at low altitude . Int J Sports Med . 2015 ; 36 : 357 ± 364 . https://doi.org/10.1055/ s-0034-1395520 PMID: 25607522
20. Reis VM , Marinho DA , Policarpo FB , Reis AM , Guidetti L , Silva AJ . Examining the Accumulated Oxygen Deficit Method in Breaststroke swimming . Eur J Appl Physiol . 2010 ; 109 : 1129 ± 1135 . https://doi.org/ 10.1007/s00421-010 -1460-4 PMID: 20373107
21. Faul F , Erdfelder E , Lang AG , Buchner A. G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences . Behav Res Methods 2007 ; 392 : 175 ± 191 .
22. Cohen J . Statistical power analysis for the behavioral sciences ( 2nd Ed .). Hillsdale, NJ: Lawrence Erlbaum Associates; 1988 .
23. Buitrago S , Wirtz N , Flenker U , Kleinoder H . Physiological and metabolic responses as function of the mechanical load in resistance exercise . Appl Physiol Nutr Metab . 2014 ; 39 : 345 ± 350 . https://doi.org/ 10.1139/apnm-2013 -0214 PMID: 24552376
24. Benito PJ , AlvareÂs-Sanchez M , Diaz V , Morencos E , Peinado AB , Cupeiro R et al. Cardiovascular fitness and energy expenditure response during a combined aerobic and circuit weight training protocol . PLoS ONE . 2016 ; 11 : e0164349. https://doi.org/10.1371/journal.pone. 0164349 PMID: 27832062
25. Ainsworth BE , Haskell WL , Herrmann SD , Meckes N , Bassett DR Jr., Tudor-Locke C , et al. Compendium of physical activities: A second update of codes and MET values . Med Sci Sports Exerc . 2011 ; 43 : 1575 ± 1581 . https://doi.org/10.1249/MSS.0b013e31821ece12 PMID: 21681120
26. Robergs RA , Pearson DR , Costill DL , Fink WJ , Pascoe DD , Benedict MA , et al. Muscle glycogenolysis during differing intensities of weight-resistance exercise . J Appl Physiol . 1991 ; 70 : 1700 ± 1706 . PMID: 2055849
27. Gastin P. Quantification of anaerobic capacity . Scand J Med Sci Sports . 1994 ; 4 : 91 ± 112 .
28. Bernasconi S , Tordi N , Perrey S , Parratte B , Monnier G . Is the VO2 slow component in heavy armcranking exercise associated with recruitment of type II muscle fibers as assessed by an increase in surface EMG? Appl Physiol Nutr Metab . 2006 ; 31 : 414 ± 422 . https://doi.org/10.1139/h06-021 PMID: 16900231
29. Koppo K , Bouckaert J , Jones AM . Oxygen uptake kinetics during high-intensity arm and leg exercise . Respir Physiol Neurobiol . 2002 ; 133 : 241 ± 250 . PMID: 12425971
30. Muraki S , Tsunawake N , Yamasaki M. Limitation of muscle deoxygenation in the triceps during incremental arm cranking in women . Eur J Appl Physiol . 2004 ; 91 : 246 ± 252 . https://doi.org/10.1007/ s00421-003 -0962-8 PMID: 14566566
31. Medbo JI , Toska K. Lactate release, concentration in blood, and apparent distribution volume after intense bycicling . J Appl Physiol . 2001 ; 51 : 303 ± 312 .