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Original Research

An Examination of the Differences Between Two Methods of Estimating Energy Expenditure in Resistance Training Activities

Vezina, Jesse W.; Der Ananian, Cheryl A.; Campbell, Kathryn D.; Meckes, Nathanael; Ainsworth, Barbara E.

Author Information
Journal of Strength and Conditioning Research: April 2014 - Volume 28 - Issue 4 - p 1026-1031
doi: 10.1519/JSC.0000000000000375
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The health-related benefits of physical activity (PA) have been widely established (9,14,18,20,31). Meeting the recommended guidelines for moderate (3–6 metabolic equivalents [METs]) and/or vigorous intensity (>6 METs) PA is associated with reduced risk of many chronic diseases and risk factors, including cardiovascular disease, thrombolytic stroke, hypertension, type 2 diabetes mellitus, osteoporosis, obesity, and breast and colon cancer (12,17). Recent PA guidelines for adults recommend that all adults engage in at least 30 minutes of moderate PA on at least 5 days per week or engage in 20 minutes of vigorous activity on 3 or more days per week (12).

The U.S. Department of Health and Human Services recommends participating in resistance training (RT) on at least 2 days each week and suggests targeting each of the large muscle groups in the body (12). Recent studies have found RT to be associated with improved vascular function, inflammatory marker (HbA1c) levels, blood-pressure, triglyceride levels, and physical function (8,11,21,24,26). Quantifying the dose-response relationship between RT and health outcomes would provide further evidence of the health-related benefits of RT. Currently, most literature examining the relationship between RT and health outcomes defines the dose of RT as the number of repetitions and sets and the amount of weight used, as opposed to energy expended. Obtaining a better understanding of the energy expenditure (EE) associated with strength-training will help to further elucidate the relationship between RT and health outcomes.

To date, few studies have evaluated the EE of RT, and the majority of these studies have focused on a full RT workout or circuit training (6,7,16,22,25) instead of individual RT exercises. The Compendium of Physical Activities, developed in 1993 and updated in 2000 and 2011 (1–3), provides a comprehensive list of the EE (MET values) associated with a vast array of PA modes; however, information about the EE of RT exercises is limited. The RT exercises in the compendium are general examples of RT rather than specific exercises. For example, Entry 02050 is classified as RT: weightlifting (free weight, nautilus, or universal type), power lifting, or body building—vigorous effort (1). This single entry is grouping machine weights, free weights, bodybuilding, and power lifting into 1 category. The body adapts differently to each of these activities, and each will induce a very different muscular and metabolic response (10), thereby suggesting the need to study the EE of individual RT exercises rather than examining the exercises globally.

Another potential limitation in the literature regarding the EE associated with RT is that the majority of studies have used traditional calorimetry to measure the EE. Methodologically, this is of concern because RT is an intermittent activity involving many anaerobic bursts and so uses different metabolic pathways to produce energy. Thus, there are inherent problems with trying to aerobically measure the EE of RT. Specifically, anaerobic activities initially use glucose stores and phosphocreatine degradation to produce adenosine tri-phosphate (ATP) during short, intense bursts of energy rather than oxygen, which is used to produce ATP in the in the mitochondria during steady-state submaximal aerobic activity (15,32). Furthermore, RT is, by nature, an intermittent activity. It consists of brief, intense bouts of activity followed by short rest periods. During this activity, intense contractions take place that limit blood flow and oxygen uptake by the working muscles. This limited oxygen delivery requires the muscles to rely on anaerobic metabolism during the activity (30); the intensity of the exercise and the fatigue experienced in the muscle are both associated with oxygen consumed during recovery (5). Without accounting for the heavy reliance on anaerobic metabolism (i.e., glucose and phosphocreatine degradation) and instead using aerobic models to evaluate the EE of RT, it is possible that EE for RT exercises will be significantly underestimated (28).

Because of the intense, intermittent nature of RT and the differences in substrates providing energy for RT, Scott (28) suggested that measuring postexercise recovery O2 consumption may be a better method to assess RT EE than O2 consumption during activity. Nevertheless, no studies have looked at whether the estimated EE for RT activities differs based on the calculations used (i.e., traditional calorimetry vs. postexercise recovery oxygen consumption). Given the potential health-related benefits of RT, understanding the true EE of various modes of RT will better enable researchers to evaluate dose-response dynamics, and practitioners to prescribe RT as a part of a PA program. Therefore, the purpose of this study was to evaluate the EE of 4 common RT activities (push-ups, curl-ups, pull-ups, and lunges) and to examine potential differences between EE estimates calculated through traditional aerobic methods (13) and EE estimates calculated based on postexercise O2 recovery using the methods suggested by Scott (28). We hypothesized that the EE estimates obtained from the postexercise O2 recovery calculations (28) would provide significantly higher estimates of EE than would the EE calculated using traditional methods (13).


Experimental Approach to the Problem

This study used a single-group, cross-sectional design to evaluate the EE of 4 modes of RT in healthy young men. Each participant performed 1 randomly assigned circuit consisting of the 4 exercises 3 times. Traditional calorimetry was used to measure oxygen uptake continuously throughout the trial, including the recovery period between exercises. After data collection, total EE for each of the 4 exercises was estimated using 2 different calculations: one evaluating oxygen uptake during activity and another evaluating oxygen uptake during recovery. Differences in the mean EE for each RT exercise based on the 2 calculation methods were examined.


Twelve healthy men (mean age: 23.6 ± 2.84 years [range, 18–29 years]; mean body mass index [BMI]: 24.63 ± 2.63; mean percentage of body fat: 12.03 ± 4.44%; non-Hispanic white n = 9) volunteered to participate in this study. Inclusion criteria for participation included a minimum of 1 year of self-reported continuous RT experience, age between 18 and 30 years, the ability to demonstrate proper technique in each RT activity, and body fat less than 25%. Exclusion criteria were the presence of chronic disease, the use of any medication that could affect performance or metabolic output, smoking, and the inability to read or write English. The participants self-reported a mean of 5.7 ± 3.42 years of experience with RT. Each participant provided written informed consent before participation. This study was approved by Arizona State University's Institutional Review Board.


Each participant completed 1 study visit that lasted approximately 90 minutes during which each participant engaged in the RT exercises. All testing occurred in a climate-controlled laboratory (22° C) during the spring of 2011. Participants were scheduled for testing at their convenience to enhance compliance with testing instructions. The most common testing times were early mornings or late afternoons. Subjects were asked not to eat any food or drink any liquids for at least 4 hours before testing, to refrain from ingesting caffeine for 8 hours before testing, and to sleep for at least 7 hours on the night before testing.

Before beginning the exercise trial, each participant was randomly assigned to 1 of 4 possible circuits. Each circuit contained 4 RT exercises in a specified order, to ensure that pull-ups and push-ups did not occur sequentially (Table 1). After randomization, each participant was equipped with a Polar Electro OY Heart Rate Monitor (Kempere, Finland) and connected to a portable, indirect calorimetry unit, the Oxycon Mobile (CareFusion, San Diego, CA, USA). After the equipment was fitted, participants were instructed to remain seated for 4 minutes while resting metabolic data were collected. After this short rest period, the exercise trial began. Participants completed 3 circuits consisting of each of the 4 exercises. The participant did each individual RT exercise for a maximum of 60 seconds or until he was unable to continue with proper form, as determined by the research team, or remain on cadence. The cadence for all exercises was set by a metronome at a rate of 40 b·min−1. Based on this cadence, 20 repetitions of the exercise would be completed in 60 seconds. If a subject did not remain on cadence, he was given 1 opportunity to return to the proper cadence before the exercise was stopped. If a participant was unable to finish an individual exercise during a circuit, he was still instructed to attempt the exercise in the next circuit. After the participant completed each exercise, he returned to a seated, resting position until his metabolic rate returned to within 1.0 ml·kg−1·min−1 of his initial resting rate. The first circuit was used as a warm-up/familiarization circuit, and these data were not included in the final analysis. The purpose of using the first circuit as a warm-up was to allow the individual to become more efficient at performing the exercise and to adjust for physiological changes that occurred after the body properly warmed up. Individuals will experience an increased oxygen uptake if allowed to actively warm up before engaging in intense activity (19).

Table 1:
Order of exercise sequences (circuits).

The 4 RT exercise modes in this study were chosen to represent a total-body workout, similar to what may be performed in a gym or home setting. Bodyweight exercises were selected to minimize the use of equipment and to control for weight differences in participants without having to adjust weights based on percentage of 1 repetition maximum (1RM) or percentage of body weight. Upper-body exercises included the push-up and pull-up, the core musculature was represented by the curl-up, and the lower-body musculature was represented by the alternating lunge. Push-ups were performed in a standard position (i.e., they could not perform the push-ups from their knees). Pull-ups were performed from a pull-up bar placed at a height such that the participants could not simultaneously touch the bar and the floor. Participants were required to move through the full range of motion for the repetition to count. Lunges were performed in place, while alternating legs. The participants were instructed to lower themselves until their back knee lightly touched the ground. Finally, the curl-ups were performed according to the protocol described by American College of Sports Medicine (ACSM) (4). Participants were instructed to lie supine on the floor with their arms resting by their sides and knees flexed. A piece of tape was placed at their fingertips and 6 inches below that point. The participant would flex at the torso while keeping his hands on the floor and sliding from one piece of tape to the other in beat with the metronome.



Height (in cm) and weight (in kg) were measured at baseline to calculate BMI (in kg/m2) and the relative EE (ml·kg−1·min−1). Height was measured to the nearest quarter cm using a wall-mounted stadiometer. Weight was measured using a Tanita body-composition analyzer (TF-300; Arlington Heights, IL, USA).

Body Composition Assessment

Percentage of body fat was assessed using whole-body, air-displacement plethysmography. This measurement was performed using the Bod Pod (Life Measurements, Concord, CA, USA), which has been found to be both a valid and reliable measure of body composition when compared with hydrostatic weighing (23). Body composition was estimated using the Siri (1961) model, designed to estimate percentage of fat using predicted lung volumes. This model has been approved for use in the general population.

Energy Expenditure

EE (ml·kg−1·min−1) and heart rate (in b·min−1) were recorded every 5 seconds throughout the trial by the OxyCon Mobile (CareFusion) and Polar Heart Rate Monitor, respectively. The OxyCon Mobile has been found to be a valid and reliable measurement tool for assessing O2 expenditure at submaximal levels (27). When compared with a Douglas Bag, Rosdahl et al (27) found no significant differences were seen between the 2 measures at most submaximal levels (p > 0.05). Recovery EE was recorded after each exercise and used to calculate final EE based on the equation 1 L O2 = 4.7 kcal (28).

Statistical Analyses

Statistical analysis was performed using SAS version 9.2 (SAS Institute, Cary, NC, USA). Both the recorded exercise EE and recovery EE were converted to kcal·min−1·kg−1. The average EE values during exercise were calculated using the TEC of 1 L O2 to 5.0 kcal (13), whereas the average EE during recovery (NEC) was calculated using the Scott (28) conversion of 1 L O2 to 4.7 kcal. To ensure consistency, only the fast phase (first 2 minutes) of recovery was evaluated for each participant. Short and Sedlock (29) demonstrated that about 80% of O2 debt is recovered in this time frame after exercise (29). Before data analysis, the Shapiro-Wilk test was used to assess normality. Dependent t-tests were used to evaluate mean differences in the average EE values between the TEC calculated values and NEC values. The α level for p was set at 0.05 for all analyses.


All 12 participants completed 3 circuits of the exercises, with a mean time of 72 ± 5.9 minutes; however, no participant was able to complete a full set of 20 pull-ups during any circuit. Additionally, 1 participant was unable to complete his third trial of push-ups before reaching volitional fatigue. The mean repetitions for push-ups (19.8 ± 0.49) and pull-ups (9.8 ± 2.13) fell below the full 20 repetitions; however, each participant completed 20 curl-ups and 20 lunges. The average resting metabolic rate for all participants was 0.02 ± 0.005 kcal·min−1·kg−1. Mean EE for each exercise using both calculation methods are provided in Table 2. For each of the exercises, the calculated recovery EE was found to be significantly higher than the traditionally recorded value (p < 0.001).

Table 2:
Average energy expenditure for each of the 4 exercises using traditional and nontraditional calculations.*

Mean for each exercise was converted to METs to evaluate the intensity. All 4 exercises were classified as moderate-intensity exercises when the TEC values were used (push-ups, 3.47 METs; curl-ups, 3.30 METs; lunges, 4.26 METs; pull-ups, 3.26 METs). When the recovery values were evaluated; however, only the curl-ups (5.87 METs) remained a moderate-intensity activity. The push-ups (6.91 METs), lunges (7.52 METs), and pull-ups (8.03 METs) were all classified as vigorous-intensity activities.


This study examined the EE of 4 individual modes of RT (push-ups, curl-ups, lunges, and pull-ups) using indirect calorimetry and compared the energy estimates obtained using 2 different methods of data analysis. The first method examined the traditionally measured aerobic values of each activity, whereas the second method examined the EE observed during the immediate postactivity recovery time (28). In our study, the recovery method yielded significantly higher values for EE than did values obtained with traditional measures (p < 0.001). The EE calculated from the recovery method indicated that 3 of the 4 modes of RT may be perceived as vigorous-intensity activity (>6 METs), whereas the traditional aerobic measurements estimated that the EE was in the moderate-intensity range (3–6 METs).

These findings suggest that if researchers continue to estimate the EE of RT exercise using the same calculations and methods used for aerobic activities, they may be underestimating the EE of RT. This is likely because of the traditional calculation failing to account for the influence of phosphocreatine and glucose metabolism on EE, particularly during intermittent bursts of intense activity (15). Accurately quantifying the EE of RT is essential for quantifying the relationship between RT and health outcomes.

Although the evidence for the health-related benefits of RT is not as extensive as it is for regular participation in PA (9,14,18,20,31), RT has commonly been associated with more functional measures of health such as increased muscle mass, bone-mineral density, and functional performance (25). Recently, researchers have begun reporting some of the other health-related benefits of RT. It is important to continue to measure the energy cost of RT to fully understand all the benefits associated with it. Many published studies that have investigated the energy cost of RT have evaluated entire workout protocols (6,7,16,22,25). Although knowing the energy cost of full RT protocols is helpful, it fails to account for the variance in sets and repetitions within a workout program. Given the intermittent nature of RT, and the differences in sets and repetitions used in RT programs, evaluating the EE of individual exercises would give researchers a far better understanding of the EE achieved while performing RT.

Although, this study is the first that we know of to use the method suggested by Scott (28) for calculating the EE of anaerobic activities, other published studies have attained EE values similar to what was recorded before using the conversion of 1 L O2 to 4.7 kcal. Despite using a slightly different protocol, Phillips and Ziuritis (25) found that a single set of RT after the ACSM recommendations resulted in a mean intensity of 3.9 METs. This is very close to the mean of 3.6 METs (for all activities) recorded in this study. Phillips and Ziuritis used a similar repetition range (15–20 repetitions are recommended for training muscular endurance); however, their study was performed on machines and attempted to have the participant achieve a 15RM on each attempt. There are a number of differences between using machines and performing bodyweight exercises, including the use of stabilization muscles. Additionally, participants in the Phillips and Ziuritis study were intentionally attempting to reach volitional fatigue on each set, whereas participants in this study were not. Finally, the difference in metabolic output may be caused by the continuous nature of their program design, in which they did not allow participants to return to rest between each set.

Bloomer (7) compared the EE of RT (squatting) to that of an aerobic activity (cycling). The 2 activities were matched for duration (30 minutes) and relative intensity (70% of V[Combining Dot Above]O2max and 70% of 1RM). Bloomer's results indicate that 30 minutes of cycling yielded a greater total EE than a 30-minute squat workout (p < 0.001). However, participants managed to squat for an average of only 6.21 ± 1.34 minutes of the 30-minute protocol. If the absolute EE had been assessed based on time spent doing each activity, it is likely that the squatting protocol would have shown significantly greater EE than the aerobic protocol. Likewise, if a participant had been able to continuously squat for the entire 30-minute protocol, the likely result would have been a rather large increase in total EE.

Because there are countless numbers of sets, repetitions, and weight combinations, many methods have been incorporated to evaluate the energy cost of RT. Without independently assessing the energy cost of each possible combination, the next best thing is to measure the energy cost of each individual exercise. Furthermore, identifying a method better capable of accurately assessing the energy cost of these activities would provide researchers and practitioners with a far more accurate assessment of overall EE.

This study contributes to the growing body of literature supporting RT's role in promoting general health and well-being by reporting the energy cost of several RT activities and by demonstrating how researchers may be able to use a novel method to more accurately assess the energy cost of RT. Although, further studies are needed to evaluate the endless array of available RT activities, this study has laid the framework to evaluate the energy cost accurately and efficiently.

Practical Applications

The results of this study indicate that using traditional calorimetry may significantly underestimate the energy cost of RT. As seen in our results, using the procedures suggested by Scott (28), shifted EE estimates for a group of RT exercises from moderate to vigorous PA. This relatively simple technique may be able to provide a more accurate method of evaluating EE in RT than traditional calculations and is much simpler and less invasive than other methods, such as blood assays to evaluate blood lactate levels.

Although RT activities are traditionally short in duration, they are often intense and regularly end in volitional fatigue. When compared with results obtained using more traditional methods, the results of our study seem to better represent this higher intensity. Furthermore, the information provided in this study may be of considerable interest to field practitioners who may want to estimate to energy cost of workouts to better suit the needs of their clients or athletes. This information can potentially be used to design more effective programs to elicit optimal results. Whether an individual is training for performance or for general health, gauging the relative intensity of the work being performed will help to maximize the potential benefit of the program.

The knowledge gained from this study suggests that these relatively light RT exercises are, in fact, vigorous-intensity activities. Given this information, it is likely that other forms of RT traditionally thought of as light to moderate intensity may also be significantly underestimated. This information is crucial particularly when planning rest and recovery between workouts for athletes and the general population as well.


This study received no outside funding. There is no conflict of interest or financial benefit to any party involved in this study. The results of this study do not constitute endorsement of any product by the authors or the National Strength and Conditioning Association. Thank you to Drs. Glenn Gaesser and Pamela Swan for allowing us the use of the OxyCon Mobile and Bod Pod as well as laboratory space to conduct the trials.


1. Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR Jr, Tudor-Lock C, Leon AS. Compendium of physical activities: A second update of codes and MET values. Med Sci Sports Exerc 43: 1575–1581, 2011.
2. Ainsworth BE, Haskell WL, Leon AS, Jacobs DR Jr, Montoye HJ, Sallis JF, Paffenbarger RS Jr. Compendium of physical activities: Classification of energy costs of human physical activities. Med Sci Sports Exerc 25: 71–80, 1993.
3. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, Leon AS. Compendium of physical activities: An update of activity codes and MET intensities. Med Sci Sports Exerc 32: S498–S516, 2000.
4. American College of Sports Medicine. ACSM's Guidelines for Exercise Testing and Prescription (8th ed.). Baltimore, MD: Lippincott Williams & Wilkins, 2010.
5. Bahr R. Excess postexercise oxygen consumption-magnitude, mechanisms and practical implications. Acta Physiol Scand 144: 1–70, 1992.
6. Beckham SG, Earnest CP. Metabolic cost of free weight circuit weight training. J Sports Med Phys Fitness 40: 118–125, 2000.
7. Bloomer RJ. Energy cost of moderate-duration resistance and aerobic exercise. J Strength Cond Res 19: 878–882, 2005.
8. Bweir S, Al-Jarrah M, Almalty A, Maayah M, Smirnova IV, Novikova L, Stehno-Bittel L. Resistance exercise training lowers HbA1c more than aerobic training in adults with type 2 diabetes. Diabetol Metab Syndr 1: 27, 2009.
9. Byberg L, Melhus H, Gedeborg R, Sundstrom J, Ahlbom A, Zethelius B, Michaelsson K. Total mortality after changes in leisure time physical activity in 50 year old men: 35 year follow-up of population based cohort. Br J Sports Med 43: 482, 2009.
10. Coburn JW, Malek MH. NSCA's Essentials of Personal Training (2nd ed.). Champaign, IL: Human Kinetics, 2012.
11. Cornelissen VA, Fagard RH. Effect of resistance training on resting blood pressure: A meta-analysis of randomized controlled trials. J Hypertens 23: 251–259, 2005.
12. Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans. Washington, DC: Author, 2008.
13. di Prampero PE, Ferretti G. The energetics of anaerobic muscle metabolism: A reappraisal of older and more recent concepts. Respir Physiol 118: 855–866, 1999.
14. Fagard RH. Exercise characteristics and the blood pressure response to dynamic physical training. Med Sci Sports Exerc 33: S484–S492, 2001.
15. Gaitanos GC, Williams C, Boobis LH, Brooks S. Human muscle metabolism during intermittent maximal exercise. J Appl Physiol (1985) 75: 712–719, 1993.
16. Haddock BL, Wilkin LD. Resistance training volume and post exercise energy expenditure. Int J Sports Med 27: 143–148, 2006.
17. Haskell WL, Lee I, Pate RR, Powell KE, Blair SN, Franklin BA, Bauman A. Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 39: 1423–1434, 2007.
18. Houmard JA, Tanner CJ, Slentz CA, Duscha BD, McCartney JS, Kraus WE. Effect of the volume and intensity of exercise training on insulin sensitivity. J Appl Physiol (1985) 96: 101–106, 2004.
19. Ingier F, Stromme SB. Effects of active, passive or no warm-up on the physiological response to heavy exercise. Eur J Appl Physiol Occup Physiol 40: 273–282, 1979.
20. Jeon CY, Hu FB, Lokken RP, van Dam RM. Physical activity of moderate intensity and risk of type 2 diabetes. Diabetes Care 30: 744–752, 2007.
21. Maeda S, Otsuki T, Lemitsu M, Kamioka M, Sugawara J, Kuno S, Tanaka H. Effects of leg resistance training on arterial function in older men. Br J Sports Med 40: 867–869, 2006.
22. Mazzetti S, Douglass M, Yocum A, Harber M. Effect of explosive versus slow contractions and exercise intensity on energy expenditure. Med Sci Sports Exerc 39: 1291–1301, 2007.
23. McCrory MA, Gomez TD, Bernauer EM, Molé PA. Evaluation of a new air displacement plethysmograph for measuring human body composition. Med Sci Sports Exerc 27: 1686–1691, 1995.
24. Phillips SM, Winett RA. Uncomplicated resistance training and health-related outcomes: Evidence for a public health mandate. Curr Sports Med Rep 9: 208–213, 2010.
25. Phillips WT, Ziuraitis JR. Energy cost of the ACSM single-set resistance training protocol. J Strength Cond Res 17: 350–355, 2003.
26. Ratamess NA, Alvar BA, Evetoch TK, Housh TJ, Kibler WB, Kraemer WJ, Triplett T. Progression models in resistance training for healthy adults. Med Sci Sports Exerc 41: 687–708, 2009.
27. Rosdahl H, Gullstrand L, Salier-Eriksson J, Johansson P, Schantz P. Evaluation of the Oxycon Mobile metabolic system against the Doublas bag method. Eur J Appl Physiol 109: 159–171, 2010.
28. Scott CB. Quantifying the immediate recovery energy expenditure of resistance training. J Strength Cond Res 25: 1159–1163, 2011.
29. Short KR, Sedlock DA. Excess postexercise oxygen consumption and recovery rate in trained and untrained subjects. J Appl Physiol (1985) 83: 153–159, 1997.
30. Tamaki T, Uchiyama S, Tamura T, Nakano S. Changes in muscle oxygenation during weight lifting exercise. Eur J Appl Physiol Occup Physiol 68: 465–469, 1994.
31. Yang X, Telama R, Hirvensalo M, Mattsson N, Viikari JSA, Raitakari OT. The longitudinal effects of physical activity history on metabolic syndrome. Med Sci Sports Exerc 40: 1424–1431, 2008.
32. Zatsiorsky VM, Kraemer WJ. Science and Practice of Strength Training (5th ed.). Champaign, IL: Human Kinetics, 2006.

strength; physical activity; metabolic equivalent

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