Inter-set rest configuration effect on acute physiological and performance-related responses to a resistance training session in terrestrial vs simulated hypoxia

Submitted 7 January 2022 Accepted 29 April 2022 Published 18 May 2022 Corresponding author Belén Feriche, [email protected] Academic editor Jeremy Loenneke Additional Information and Declarations can be found on page 15 DOI 10.7717/peerj.13469 Copyright 2022 Benavente et al. Distributed under Creative Commons CC-BY 4.0 OPEN ACCESS Inter-set rest configuration effect on acute physiological and performance-related responses to a resistance training session in terrestrial vs simulated hypoxia Cristina Benavente1, Belén Feriche1, Guillermo Olcina2, Brad J. Schoenfeld3, Alba Camacho-Cardenosa2, Filipa Almeida1, Ismael Martínez-Guardado4, Rafael Timon2and Paulino Padial1 1Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain 2Faculty of Sport Sciences, University of Extremadura, Cáceres, Spain 3Department of Health Sciences, CUNY Lehman College, New York, United States of America 4Faculty of Education, BRABE Group, Department of Psychology. Faculty of Life and Nature Sciences, University of Nebrija, Madrid, Spain ABSTRACT Background. Metabolic stress is considered a key factor in the activation of hypertrophy mechanisms which seems to be potentiated under hypoxic conditions.This study aimed to analyze the combined effect of the type of acute hypoxia (terrestrial vs simulated) and of the inter-set rest configuration (60 vs 120 s) during a hypertrophic resistance training (RT) session on physiological, perceptual and muscle performance markers. Methods. Sixteen active men were randomized into two groups based on the type of hypoxia (hypobaric hypoxia, HH: 2,320 m asl; vs normobaric hypoxia, NH: FiO2 of 15.9%). Each participant completed in a randomly counterbalanced order the same RTsession in four separated occasions: two under normoxia and two under the corresponding hypoxia condition at each prescribed inter-set rest period. Volume-load (load ×set ×repetition) was calculated for each training session. Muscle oxygenation (SmO2) of the vastus lateralis was quantified during the back squat exercise. Heart rate (HR) was monitored during training and over the ensuing 30-min post-exercise period. Maximal blood lactate concentration (maxLac) and rating of perceived exertion (RPE) were determined after the exercise and at the end of the recovery period. Results. Volume-load achieved was similar in all environmental conditions and interset rest period length did not appreciably affect it. Shorter inter-set rest periods displayed moderate increases in maxLac, HR and RPE responses in all conditions. Compared to HH, NH showed a moderate reduction in the inter-set rest-HR (ES >0.80), maxLac (ES >1.01) and SmO2(ES >0.79) at both rest intervals. Conclusions. Results suggest that the reduction in inter-set rest intervals from 120 s to 60 s provide a more potent perceptual, cardiovascular and metabolic stimulus in all environmental conditions, which could maximize hypertrophic adaptations in longer periods of training. The abrupt exposure to a reduced FiO2at NH seems to reduce the inter-set recovery capacity during a traditional hypertrophy RTsession, at least during a single acute exposition. These results cannot be extrapolated to longer training periods. How to cite this article Benavente C, Feriche B, Olcina G, Schoenfeld BJ, Camacho-Cardenosa A, Almeida F, Martínez-Guardado I, Timon R, Padial P. 2022. Inter-set rest configuration effect on acute physiological and performance-related responses to a resistance training session in terrestrial vs simulated hypoxia. PeerJ 10:e13469 http://doi.org/10.7717/peerj.13469 Subjects Anatomy and Physiology, Sports Medicine Keywords Hypertrophy, Performance, Hypobaric hypoxia, Normobaric Hypoxia, Interval rest INTRODUCTION The increase of muscle mass and strength via resistance training (RT) is a primary goal for athletes, recreationally trained individuals, and populations interested in improving various health-related outcomes (Schoenfeld, 2010). The results of a training program may vary depending on the manipulation of several variables including training volume (sets ×repetitions ×load), inter-set rest period length, movement velocity, exercise selection, exercise sequence and training frequency (Bird, Tarpenning & Marino, 2005). Training volume and load are considered primary factors to maximize strength and hypertrophy (Kraemer & Ratamess, 2004), but other variables, such as rest intervals, also play an important role in both acute and chronic responses to RTprograms (De Salles et al., 2009). Hypertrophy training is associated with the use of short (<60) to long (>90 s) inter-set rest-intervals (Henselmans & Schoenfeld, 2014). Both, short and long rest intervals, can be used to enhance strength and muscle growth: although mechanisms remain speculative, it has been hypothesized that short rest periods induce beneficial effects via increased metabolite accumulation while long intervals provide a greater capacity to maintain high training intensities and volume load (Wernbom et al., 2007;Schoenfeld, 2010). Evidence suggests that RTperformed under hypoxic conditions may produce an added benefit to strength and muscle mass development compared to an equivalent amount of training under normoxic conditions (Nishimura et al., 2010;Manimmanakorn et al., 2013a;Manimmanakorn et al., 2013b). This benefit is purportedly linked to the heightened accumulation of metabolic byproducts in hypoxia, such as blood lactate, protons (H+), calcium and inorganic phosphorus, among others, derived from the increase in anaerobic metabolism to compensate the loss of oxygen (O2) availability (Kon et al., 2012;Schoenfeld, 2013;Kurobe et al., 2015;Scott, Slattery & Dascombe, 2015). Metabolic stress has been proposed as a factor in the activation of muscle hypertrophy-related mechanisms (i.e., activation of anabolic signaling routes) (Schoenfeld, 2010;Schoenfeld, 2013). Current evidence indicates that multiple sets of high-intensity RTlead to significant acute physiological responses (Schoenfeld, 2013;Cintineo et al., 2018) also mediated by inter-set rest configuration, both under conditions of normoxia (De Salles et al., 2009; Henselmans & Schoenfeld, 2014;Grgic et al., 2018) and hypoxia (Lockhart et al., 2020). In addition, it has been proposed that the accumulation of metabolites promotes the recruitment of additional high-threshold motor units (Miller et al., 1996;Takarada et al., 2000;Debold, 2012), increasing the total number of muscle fibers stimulated (Scott, Slattery & Dascombe, 2015). In regard to hypoxic training, it is important to consider how the type of the hypoxia and its interaction with the manipulation of training variables might influence the RT response. Systemic hypoxia can be achieved by the ascent to high altitudes (hypobaric hypoxia (HH)) or by breathing O2-depleted air (normobaric hypoxia (NH)). Current data suggest that the physiological response differs between both modalities of hypoxia due to Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 2/21 factors related to the barometric pressure and/or partial pressure of O2(Millet & Debevec, 2020). However, current literature does not sufficiently address the physiological effects of a RTperiod at terrestrial altitude and results obtained from NH studies are inconclusive. This is likely due to the methodological heterogeneity in exercise protocols and in the level of hypoxia used among studies (Feriche et al., 2017;Ramos-Campo et al., 2018). It has been hypothesized that RTin hypoxia might only provide additional benefits when relatively short inter-set rest periods are used, while longer rest periods could mitigate any effects of hypoxia on the muscle environment (Scott et al., 2015). However, the availability of studies comparing the effect of recovery time between sets in hypoxia is scarce. From the results of research using different inter-set rest periods under hypoxic conditions, shorter inter-set rest intervals (<60 s) have been shown to be effective in muscle activation and development at both acute (Kon et al., 2010) and chronic NH conditions (Nishimura et al., 2010;Kurobe et al., 2015). Contrarily, inter-set rest periods longer than 90 s did not provide benefits on the muscle response after a single RTsession (Scott, Slattery & Dascombe, 2015;Scott et al., 2015) or after a longitudinal training period at NH (Kon et al., 2014;Ho et al., 2014). Similar results were observed at acute moderate HH with 120 s of inter-set rest intervals (Feriche et al., 2020), although the effects of shorter recoveries at this type of hypoxia remain unknown. As in normoxia, higher inter-set recovery times in hypoxia may also favor intramuscular metabolite clearance, limiting the potential benefit of metabolic stress on its putative anabolic effects, which in turn may disfavor muscle hypertrophy (Scott, Slattery & Dascombe, 2015). The only previous study to examine the effects of different rest periods during RTunder H conditions (Lockhart et al., 2020) used a single-joint exercise, thus limiting the ability to draw strong inferences with regard to more complex or metabolically demanding protocols as to whether short rest intervals combined with different types of hypoxia may enhance muscular adaptations. Considering the putative role that metabolic stress plays in the hypertrophic response to resistance exercise, the duration of inter-set rest may be an important consideration in exercise program design, particularly under hypoxic conditions. The aim of this study was to compare the effect of different types of acute hypoxia (HH vs NH) combined with different inter-set rest configurations (60 s vs 120 s) during a traditional hypertrophy-oriented RT session on perceptual, physiological and muscle performance markers. The results will help to determine the influence of the inter-set rest configuration on acute stress markers, which potentially could provide insight into strategies for optimizing strength and muscle mass gains over longer training periods. We hypothesized that short rest periods would produce higher perceptual, cardiovascular and blood lactate changes, and its combination with terrestrial hypoxia would maximize this response. MATERIALS & METHODS Experimental approach to the problem Our research design allowed for comparisons of muscle performance markers to a hypertrophy training session between environmental conditions (HH vs NH) and exercise inter-set rest configuration (60 s vs 120 s) while controlling for other variables. A repeated Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 3/21 Figure 1 Study design. Full-size DOI: 10.7717/peerj.13469/fig-1 measures model was applied in two independent groups (G1 and G2), one for each type of hypoxia. All participants performed a standard hypertrophic RTsession on four different days, counterbalancing the order in terms of environmental condition and type of inter-set rest. Each session was separated by a rest period of 72 h. Thus, participants in G1 performed each of the two inter-set rest types of RTsessions at normoxia (N) and at terrestrial hypoxia (HH: 2,320 m asl; ∼570 mmHg). Participants in G1 travelled by car to the HH center (32 km), began the training session ∼30 min after arrival to altitude and then returned to normoxia after completing the session. Participants in G2 performed the same routines as G1 under equivalent simulated normobaric hypoxia (NH: <700 m asl; inspired fraction of oxygen [FiO2]=15.9%). The study design is illustrated in Fig. 1. One week before the first RTsession, subjects engaged in a preparatory session to determine their training load (70% of 1RM) for each exercise. This load was the average between two attempts with different loads separated by 15 min. Two days before the beginning of the study, participants attended the laboratory for baseline anthropometric measures (height: Seca 202; Seca Ltd., Hamburg, Germany) and body mass (Tanita BC 418 segmental; Tokyo, Japan)). Preliminary assessments were performed under normoxic conditions and participants were instructed to abstain from physical activity and alcohol intake, and to maintain their customary sleep and diet habits for 48 h before evaluations. To ensure standardized nutritional intake for performance during the RTsessions, participants fasted after midnight the evening prior to a training session and were provided with a standardized breakfast (730 kcal) and a protein bar (350 kcal) at 2 h and at 40 min prior to the start of the warm-up, respectively. Exercise was conducted in the morning at the same time of day for all participants under the conditions of ∼22 ◦C and ∼60% humidity for the N and NH conditions, or ∼22 ◦C and ∼28% humidity for the HH condition. The hypoxic environmental condition was assessed by the arterial oxygen saturation (SpO2) measured before the start of the warm-up. Participants Sixteen active, resistance-trained men (G1 [n=9]; age: 23.6 ±3.2 years; height: 177.2 ± 5.7 cm; body mass: 73.9 ±5.3 kg and G2 [n=7]; age: 26.0 ±3.0 years; height: 174.0 ± Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 4/21 5.0 cm; body mass: 73.9 ±7.8 kg) volunteered to participate in the study. Subjects had no self-reported health or muscular disorders and were not exposed to more than 3-4 consecutive days of altitudes above 1,500 m asl for at least two months before the study. Participants lived at a low altitude to ensure that responses were specific to acute hypoxia exposure. All subjects had been consistently lifting weights for at least 12 months prior to the onset of the study. Before the study, participants were provided with information detailing the purpose and requirements of the research protocol and provided signed informed consent. This study was approved by the Andalusian Government Research Ethics Committee (Ethical Application Ref: # 1540-n-18) and conducted in accordance with the Helsinki Declaration. Procedures Hypertrophic resistance training session The RTsession included six exercises that targeted movement patterns involving major muscle groups of the body in the following order: back squat, machine leg press, seated cable row, wide grip lat pulldown, bench press and barbell military press. Before the training sessions, participants undertook a standard warm-up protocol consisting of 15 min of low intensity aerobic exercise and stretching exercises, and a specific warm-up in which they performed two sets of 10 repetitions (the first with 20 kg and the second at 50% 1RM estimated from the preliminary test, 120 s rest) of the back squat, seated cable row and bench press. Each training session comprised three sets of 10 repetitions per exercise with a load of 70% of 1RM and 60 s or 120 s of inter-set and inter-exercise rest. Cadence of repetitions was carried out in a controlled fashion, with a concentric action of approximately 1 s and an eccentric action of approximately 2 s as determined by the supervising researcher. The load was reduced by 5% as needed in those cases that participants reached volitional failure before achieving the target repetition range (8–10 repetitions) with respect to the previous set (i.e., in the 2nd or 3rd set). All routines were directly supervised by the research team to ensure they were properly performed. Absolute training load by exercise (kg) and repetitions were monitored during each training session. Due to differences in training machine models between locations, only the barbell back squat and bench press were used for comparison. Total volume-load was calculated as the sum of the load lifted ×the repetitions ×set of each exercise (Scott et al., 2014). Before the warm-up of each session SpO2was measured in duplicate using a pulse oximeter (Wristox 3100; Nonin, Plymouth, MN, USA). Participants mean rest SpO2value equated to 98.4 ±0.9 and 94.3 ±0.5% for G1 (N and HH, respectively), and 98.5 ±0.5 and 90.7 ±1.0% for G2 (N and NH, respectively). Hypobaric-normobaric hypoxia conditions G1 performed the hypoxic training sessions under terrestrial hypoxic conditions at the High-Performance Center of Sierra Nevada (2320 m asl., Spain). The normobaric hypoxia condition of G2 was carried out by connecting a facial mask to participants 5 min before the start of the warm-up that maintained breathing at a reduced FiO2(15.9%) during the hypoxic training sessions. FiO2during exercise was controlled using an electronic device Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 5/21 (HANDI+, Maxtec, Salt Lake City, Utah, USA). The FiO2level was calculated according to the guidelines provided by the hypoxic generator manufacturer to equate an altitude of 2320 m. The low oxygen air was produced by a hypoxic generator with a semi-permeable filtration membrane (nitrogen filter technique; CAT 310, Louisville, Colorado, USA). Training session monitoring Metabolic and cardiovascular responses. Blood lactate concentration (Lac) was assessed before and immediately following the training session, at minutes 3, 5, 10 and 30 using a Lactate Pro 2 device (Arkray, Japan). Basic cardiovascular response was quantified from a heart rate (HR) cardiotachometer (Polar s610i; Polar Electro Oy, Kempele, Finlandia) during all training sessions and over the course of the immediate 30 min post-exercise period. The mean value of HR recorded was classified as working HR (work-HR), rest time between sets HR (rest-HR) and HR along the post-exercise recovery period (HR30). Perceptual responses. Sessional rating of perceived exertion was obtained via a Category Ratio-10 scale viewed by participants 30 min after completing the training session (RPE-30) (Day et al., 2004). Muscle oxygenation. Muscle oxygen saturation (SmO2) was measured by near-infrared spectroscopy (NIRS; Moxy, Fortiori Design, Minneapolis, Minnesota, USA) during the first exercise (back squat) of each training session. The Moxy device measures the total hemoglobin (Hb) present beneath the device, as well as calculates the percentage of Hb containing O2(SmO2) (Crum et al., 2017). SmO2reflects the dynamic balance between O2supply and consumption calculated throughout the change in total tissue oxy (+myo) hemoglobin (O2Hb) and deoxyhemo- (+myo-) globin (HHb) (McManus, Collison & Cooper, 2018). The sampling rate of the sensor was 2 Hz. SmO2values were expressed in % and calculated as follows by the device: SmO2(%) =O2Hb/[O2Hb+HHb]×100. During all testing, the system was connected to a personal computer via a software program (Seego: Realtrack Systems, Almería, Spain) that provided a graphic display of the data. The sensor was placed on the vastus lateralis of the participant’s dominant leg, halfway between the greater trochanter and lateral epicondyle of the femur, before the warm-up. This position was marked with a semi-permanent pen on the skin to reproduce the exact location in subsequent tests. To avoid issues with movement during exercise, the device was fixed to the leg with tape and wrapped with a dark elastic bandage. Maximal and minimum values were recorded for each set of the exercise. The difference between maximal and minimum values was used to calculate the SmO2of the first (SmO2S1), second (SmO2S2) and third (SmO2S3) set. The mean of the three sets was calculated to express the total mean SmO2of the exercise (SmO2T). Statistical analyses Data are presented as mean ±standard deviation (SD). Normal distributions of the data were confirmed using a Shapiro-Wilk test. A linear mixed-effects model with inter-set Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 6/21 recovery (60 s vs 120 s), environmental condition (HH and NH), and their interaction was applied for analysis. Varied intercepts were permitted by treating subject as a random effect. This model was built for the physiological variables. To ascertain the eventual effect of training load on performance of 2 comparable exercises among conditions (back squat for the lower-limbs and bench press for the upper-limbs), normoxia baseline scores were included as a covariate of no interest (Bates et al., 2015). Also, the adjusted between-group difference was calculated as the estimated marginal mean of the difference between HH and NH groups (HH group–NH group) after adjusting for N baseline differences. To quantify the magnitude of the change, we calculated 90% confidence intervals (CIs) of the adjusted effect. The standardized mean differences (i.e., Cohen’s d effect sizes) were calculated as the mean change (H-N or 120-60 s) divided by the pooled standard deviations of the change in all dependent variables or as the adjusted between-group difference divided by the pooled normoxia SD when comparing hypoxia types (Cohen, 1988). Threshold classifications were set as follows: >0.2 [small], >0.6 [moderate], >1.2 [large] and >2 [very large] (Hopkins et al., 2009). Consistent with other research in applied sports science (Almeida et al., 2021), we used an estimation-based approach to drawing inferences from our data. Accordingly, we interpreted each effect and its precision continuously (Gardner & Altman, 1986) rather than relying on null hypothesis significance testing (Amrhein, Greenland & McShane, 2019). This follows current statistical recommendations to eschew dichotomous interpretations of results in favor of models that provide estimates of practical meaningfulness (Wasserstein, Schirm & Lazar, 2019). All analyses were performed using the software package SPSS (version 26.0, IBM SPSS Statistics for Windows; IBP Corp., Armonk, NY, USA). RESULTS Resistance training session Table 1 displays the mean total volume-load accumulated during the 3 sets of the 2 free barbell exercises across conditions. The adjusted between-group effects showed no meaningful differences in volume-load between both types of hypoxia at each of the inter-set rest intervals in the 2 analyzed exercises (adjusted between-group effect from −7.64 to 51.75 kg [90% CIs from −135 to 238.53 kg] and from −43.05 to −15.55 kg [90% CIs from −110.03 to 51.21 kg], respectively for 60 and 120 s inter-set rest intervals). However, trivial to moderate increases in the total volume-load were achieved at longer inter-set rest periods in the bench press at HH (5.9%, ES =0.35, p=0.027). Cardiovascular, metabolic and perceptual responses Heart rate, blood lactate and RPE-30 responses are presented in Table 2. The results showed moderately lower mean work and rest-HR values with 120 s inter-set rest periods at normoxia (ES: from 1.01 to 1.08) and both types of hypoxia (ES: from 0.58 to 0.92). A similar work-HR response was observed between HH and NH conditions. However, we detected a lower mean rest-HR in NH during both inter-set rest intervals than in HH Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 7/21 Table 1 Total volume-load during the three training sets in both groups. Total volume-load (Kg) G1 G2 HH vs NH N HH N vs HH ES [CI 90%] p-value N NH N vs NH ES [CI 90%] p-value Adjusted differences between hypoxia types [CI 90%] ES [CI 90%] p-value 60 s 2114.4 ±517.8 2123.3 ±468.6 0.02 [−0.29; 0.33] 0.904 2142.9 ±240.5 2100.0 ±245.0 −0.18 [−0.48; 0.13] 0.594 51.75 [−135.03; 238.53] 0.14 [−0.75; 1.02] 0.629 120 s 2111.7 ±522.4 2096.1 ±520.9 −0.03 [−0.15; 0.08] 0.877 2100.0 ±245.0 2100.0 ±245.0 –−15.556 [−82.32; 51.21] −0.04 [−0.92; 0.84] 0.676 Back squat (kg) 60 vs 120 s ES [CI 90%] p-value 0.01 [−0.04; 0.05] 0.976 0.06 [−0.21; 0.32] 0.740 0.18 [−0.13; 0.48] 0.688 – 60 s 1628.3 ±353.1 1600.0 ±275.4 −0.09 [−0.28; 0.10] 0.608 1529.3 ±307.6 1522.9 ±275.0 −0.02 [−0.12; 0.07] 0.902 −7.64 [−75.77; 60.49] −0.02 [−0.91; 0.86] 0.844 120 s 1773.3 ±382.3 1700.6 ±300.4 −0.21 [−0.37; −0.05] 0.053 1537,1 ±288.4 1541.4 ±296.8 0.02 [−0.08; 0.10] 0.925 −43.05 [−110.03; 23.93] −0.13 [−1.01; 0.76] 0.277 Bench press (kg) 60 vs 120 s ES [CI 90%] p-value −0.40 [−0.66; −0.13] 0.009 −0.35 [−0.54; −0.16] 0.027 –−0.03 [−0.09; 0.03] 0.894 −0.07 [−0.21; 0.08] 0.617 – Notes. G1, Group 1; G2, Group 2; N, normoxic condition; HH, hypobaric hypoxia condition; NH, normobaric hypoxia condition; 60 s/120 s:, inter-set rest of the session; ES, effect size (calculated as mean difference (H-N or 120-60 s) ÷(pooled SD) in all dependent variables). Adjusted between-group difference is the estimated marginal mean of the difference between HH and NH groups (HH group–NH group) after adjusting for N baseline differences. CI 90%, 90% confidence interval. Intraand inter-group ES [CI 90%] are shown in bold. Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 8/21 Table 2 Mean physiological and perceptual measures recorded in both groups with different inter-set rest and conditions. G1 G2 HH vs NH N HH N vs HH ES [CI 90%] p-value N NH N vs NH ES [CI 90%] p-value Adjusted differences between hypoxia types [CI 90%] ES [CI 90%] p-value 60 s 150.7 ±14.3 147.8 ±18.5 −0.18 [−0.46; 0.10] 0.711 143.9 ±13.0 144.8 ±12.8 0.06 [−0.54; 0.67] 0.908 3.09 [−10.69; 16.87] 0.20 [−0.69; 1.08] 0.699 Work-HR (bpm) 120 s 136.2 ±17.3 136.4 ±21.3 0.01 [−0.16; 0.18] 0.984 120.2 ±22.6 136.0 ±13.9 0.87 [−0.25; 1.99] 0.097 0.40 [−15.15; 15.96] 0.02 [−0.86; 0.91] 0.964 60 vs 120 s ES [CI 90%] p-value 0.92 [0.43; 1.41] 0.082 0.58 [0.24; 0.91] 0.241 1.34 [0.15; 2.53] 0.015 0.66 [0.14; 1.17] 0.244 60 s 155.9 ±14.2 154.0 ±17.0 −0.12 [−0.38; 0.14] 0.806 139.6 ±14.7 140.5 ±15.5 0.06 [−0.60; 0.72] 0.916 13.56 [−0.85; 27.97] 0.83 [−0.09; 1.75] 0.120 Rest-HR (bpm) 120 s 139.9 ±21.0 141.2 ±22.5 0.06 [−0.12; 0.24] 0.906 110.0 ±25.8 125.1 ±18.1 0.69 [−0.43; 1.81] 0.189 16.12 [−1.73; 33.98] 0.80 [−0.12; 1.71] 0.134 60 vs 120 s ES [CI 90%] p-value 0.91 [0.47; 1.34] 0.093 0.65 [0.33; 0.97] 0.193 1.47 [0.27; 2.66] 0.008 0.92 [0.26; 1.57] 0.114 60 s 105.6 ±11.9 106.5 ±13.8 0.07 [−0.29; 0.43] 0.889 96.4 ±14.6 96.6 ±14.8 0.01 [−0.42; 0.44] 0.985 9.95 [−2.92; 22.82] 0.70 [−0.21; 1.61] 0.194 HR30 (bpm) 120 s 101.2 ±15.5 104.5 ±14.3 0.22 [−0.12; 0.56] 0.629 88.1 ±11.8 94.4 ±16.6 0.44 [−0.55; 1.44] 0.456 10.03 [−4.00; 24.05] 0.65 [−0.26; 1.56] 0.227 60 vs 120 s ES [CI 90%] p-value 0.32 [−0.09; 0.74] 0.494 0.15 [−0.04; 0.33] 0.759 0.63 [−0.31; 1.56] 0.264 0.14 [−0.22; 0.49] 0.803 60 s 20.7 ±4.3 19.6 ±3.5 −0.29 [−0.72; 0.14] 0.531 14.4 ±3.6 15.3 ±3.3 0.25 [−0.16; 0.65] 0.667 4.29 [1.24; 7.33] 1.25 [0.28; 2.22] 0.027 maxLac (mmol/l) 120 s 16.0 ±4.5 16.2 ±3.7 0.07 [−0.21; 0.34] 0.886 14.0 ±3.3 12.8 ±3.2 −0.39 [−0.89; 0.11] 0.526 3.48 [0.44; 6.52] 1.01 [0.07; 1.95] 0.064 60 vs 120 s ES [CI 90%] p-value 1.08 [0.57; 1.60] 0.018 0.93 [0.47; 1.38] 0.068 0.13 [−0.25; 0.50] 0.843 0.80 [0.18; 1.38] 0.169 60 s 8.8 ±1.1 8.2 ±1.1 −0.51 [−1.16; 0.15] 0.335 7.6 ±1.5 7.9 ±1.2 0.21 [−0.87; 1.29] 0.675 0.37 [−0.68; 1.41] 0.32 [−0.58; 1.21] 0.545 RPE-30 120 s 6.7 ±1.2 6.4 ±1.6 −0.16 [−0.52; 0.20] 0.739 6.1 ±1.1 6.0 ±1.7 −0.10 [−0.70; 0.50] 0.859 0.44 [−1.05; 1.94] 0.27 [−0.62; 1.15] 0.607 60 vs 120 s ES [CI 90%] p-value 1.82 [0.81; 2.84] 0.001 1.33 [0.36; 2.29] 0.015 1.10 [0.32; 1.90] 0.038 1.26 [0.35; 2.17] 0.041 60 s 64.1 ±6.3 61.2 ±9.6 −0.36 [−1.05; 0.33] 0.525 60.5 ±11.8 42.5 ±7.0 −1.92[−3.05; −0.78] 0.001 18.72 [11.42; 26.03] 2.26 [1.13; 3.39] 0.001 SmO2T (%) 120 s 66.3 ±10.9 61.7 ±17.2 −0.33 [−0.73; 0.08] 0.494 52.8 ±7.2 50.4 ±11.6 −0.26 [−1.22; 0.70] 0.672 11.32 [−1.38; 24.01] 0.79 [−0.13; 1.71] 0.139 (continued on next page) Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 9/21 Andalusian FEDER Operational Program: A-SEJ-246-UGR18 & B-CTS-374-UGR20. FPU pre-doctoral: FPU18/00686. Competing Interests Brad J. Schoenfeld serves on the scientific advisory board to Tonal Corporation, a manufacturer of exercise equipment. Author Contributions •Cristina Benavente performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. •Belén Feriche conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. •Guillermo Olcina conceived and designed the experiments, performed the experiments, authored or reviewed drafts of the paper, and approved the final draft. •Brad J. Schoenfeld analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. •Alba Camacho-Cardenosa performed the experiments, authored or reviewed drafts of the paper, and approved the final draft. •Filipa Almeida performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. •Ismael Martínez-Guardado performed the experiments, authored or reviewed drafts of the paper, and approved the final draft. •Rafael Timon conceived and designed the experiments, performed the experiments, authored or reviewed drafts of the paper, and approved the final draft. •Paulino Padial conceived and designed the experiments, performed the experiments, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. Human Ethics The following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers): This study was approved by the Andalusian Government Research Ethics Committee and conducted in accordance with the Helsinki Declaration. Data Availability The following information was supplied regarding data availability: The raw measurements are available in the Supplementary File. Supplemental Information Supplemental information for this article can be found online at http://dx.doi.org/10.7717/ peerj.13469#supplemental-information. Benavente et al. (2022), PeerJ, DOI 10.7717/peerj.13469 16/21 REFERENCES Almeida F, Padial P, Bonitch-Góngora J, De la Fuente B, Schoenfeld BJ, MoralesArtacho AJ, Benavente C, Feriche B. 2021. Effects of power-oriented resistance training during an altitude camp on strength and technical performance of Elite Judokas. Frontiers in Physiology 12:606191 DOI 10.3389/fphys.2021.606191. Amrhein V, Greenland S, McShane B. 2019. 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