Secondary Logo

Journal Logo

Original Research

Does Concurrent Training Intensity Distribution Matter?

Varela-Sanz, Adrián1; Tuimil, José L.1; Abreu, Laurinda2; Boullosa, Daniel A.3

Author Information
Journal of Strength and Conditioning Research: January 2017 - Volume 31 - Issue 1 - p 181-195
doi: 10.1519/JSC.0000000000001474
  • Free

Abstract

Introduction

Concurrent training (CT) is a mode of training that simultaneously develops various physical capacities (e.g., endurance and strength) (12). The last American College of Sports Medicine (ACSM) Position Stand for improving fitness in healthy adults recommended the implementation of both endurance and resistance training modes (i.e., CT) with a minimum weekly frequency of 3 days (16). Additionally, previous evidence supports the use of CT in endurance-sports as a means for greater performance improvements (35,38,43). However, the simultaneous training of high-intensity endurance and strength capacities could compromise the long-term optimal development of strength and power, the so-called “interference phenomenon” (4,12).

Some factors have been suggested to affect specifically CT beyond the variables that typically characterize a training program (e.g., volume, intensity, and frequency): training design (i.e., CT performed simultaneously during the same workout, in the same day or in different days, or during specific training cycles) (25), and intrasession training sequence (e.g., endurance + strength [E + S] vs. strength + endurance [S + E]) (10). Previous studies focused on the CT sequence effects on health and performance (10,25) concluded that optimal training sequence was determined by the individual objectives of the training program. However, each training sequence will have unique advantages and disadvantages which must be properly managed by the strength and conditioning professional. It has been suggested that an E + S training sequence could potentiate endurance improvements in a great manner, whereas an S + E training sequence seems to be more appropriate to promote strength gains (25).

Another training variable that may influence CT adaptations is intensity distribution. It is well established that training intensity distribution during endurance training plays an important role for subsequent adaptations (14,39,42). Thus, it has been consistently suggested that polarized training is the most effective training intensity distribution for improving performance in different endurance-sport disciplines (14,39,42). This greater effectiveness could be linked to the physical activity (PA) pattern of our ancestors for survival (6). In this regard, the recent ACSM guidelines recommend moderate-to-vigorous intensity aerobic exercise on most days of the week (16). Similarly, strength training intensity distribution may influence performance improvements (21), particularly when endurance and strength training are combined (12). Previous studies in sport settings support that low-volume high-intensity strength training (e.g., maximum strength training or plyometric/explosive strength training) could induce greater improvements in endurance and strength performance than moderate-volume and intensity strength training (38,43). Furthermore, based on the model proposed by Docherty and Sporer (12), it could be hypothesized that low-volume high-intensity strength training alternated with high-volume low-intensity strength training would be the most effective training intensity distribution for minimizing the “interference phenomenon.” Subsequently, the alternation of different intensity training loads (i.e., low-volume high-intensity combined with high-volume low-intensity training) in both endurance and strength training may be the most appropriate to optimize physiological adaptations. Furthermore, one of the most important limitations when concurrent endurance and strength training programs are compared is the equality of the training loads. Although few studies have addressed this question when comparing endurance or strength training programs alone (1,45), there has been no study, to the best of our knowledge, that has compared 2 CT programs with different intensity distribution and externally equated loads. This examination may provide a better understanding of the relationship between external (e.g., volume × intensity) and internal loads (i.e., the biological stress imposed by the training session) (33).

Determination of the optimal dose and intensity distribution to minimize the interference phenomenon and maximize training outcomes in different populations during combined endurance and strength training would be important for strength and conditioning coaches. Thus, the main objective of this study was to compare the effects of 2 endurance and strength CT programs with different training intensity distribution but externally equated loads on different training outcomes including physical, physiological, and perceptual variables in young, healthy, and physically active individuals.

Methods

Experimental Approach to the Problem

Concurrent strength and endurance training, when appropriately combined, can produce greater benefits in both endurance and neuromuscular performances than the isolated training of each capacity. However, the distribution of the training loads of both capacities must be carefully planned to minimize the so-called “interference phenomenon.” Another problem which must be solved is the comparison of external training loads. Thus, our independent variable and focus was training intensity distribution with an equivalent total external load (i.e., volume × intensity) of both training programs. A training group performed a combination of strength and endurance training aligned with the current ACSM recommendations of intensity distribution, whereas another group performed the same amount of external workload but with a polarized intensity distribution. Both experimental groups were evaluated before and after an 8-week training period (weekly training frequency of 3 days) and compared with a control group. To examine the effectiveness of the different training regimes, the following physical (i.e., jump capacity, upper- and lower-body strength, running performance, and body composition), physiological (i.e., heart rate variability [HRV]), and perceptual variables (i.e., rate of perceived exertion, training impulse, and Feeling Scale) were examined as dependent variables.

Subjects

Thirty-five sport science students (30 men and 5 women[ages 18−27; mean ± SD 21.87 ± 2.58]) agreed to participate in this investigation. All were moderately active and met the following criteria: (a) undertake voluntary PA of no more than 2 days per week apart from their academic activities which included a variable amount of PA on a daily basis; (b) lack of any type of injury or pathology at the beginning of the study; and (c) were not training regularly or undertaking competitive sport. Participants were informed about the study's procedures and the benefits and risks it would entail, and provided written informed consent before participation. The study was approved by the institutional research Ethics Committee (CE 014/2012, University of La Coruña).

The 35 participants were randomly assigned to one of the 3 groups with women allocated as evenly as possible: Traditional-based training group (TT) (n = 12; 10 men and 2 women), polarized training group (PT) (n = 12; 10 men and 2 women), and control group (CG) (n = 11; 10 men and 1 women). All subjects signed and informed written consent before participation.

Procedures

This was a randomized controlled trial. An experimental design schedule is presented in Figure 1.

Figure 1.
Figure 1.:
Experimental design schedule. HRV: heart rate variability; CMJmax: maximum countermovement jump; RM: repetition maximum; MAS: maximum aerobic speed; TUMTT: final time in the Université de Montréal track test; HRmax: maximum heart rate; V̇o 2max: maximum oxygen consumption.

Before data collection and training intervention, all participants underwent a 2-week familiarization period that consisted of 3 sessions per week. First, they performed a 5-minute running warm-up at ∼60% of their estimated maximum heart rate (HRmax), followed by 4 submaximal countermovement jumps (CMJs) separated by 30 seconds of rest. The main part of the session consisted of alternate upper and lower limb resistance exercises performed in a circuit manner. Participants completed 3 sets of 15, 10, and 8 repetitions with a perception of effort (via OMNI Scale) of 2, 3, and 3–4, respectively (37). The recovery time was ∼30 seconds between exercises and 1–2 minutes between sets. The exercises for the upper limbs were bench press, seated pull-over, and standing biceps curl. The exercises for the lower limbs were half squat, prone leg curl, and seated leg extension. Before each set of all exercises, participants performed 25 abdominal crunches. Cooling down exercises consisted of 2–3 sets of 15 seconds of stretching exercises of the muscle groups involved during the session.

Physical and physiological evaluations were performed before and after the 8-week training intervention. All evaluations were conducted during three sessions over 10–14 days with at least 24 hours of rest before each evaluation session. Participants came to the laboratory approximately at 8 am. They were instructed to attend after an overnight fast to minimize digestion influences on the cardiac and anthropometric variables' measurement.

Heart Rate Variability

Participants wore a heart rate (HR) monitor with a HR band (RS800; Polar Electro Oy, Kempele, Finland) for the evaluation of HRV and cardiac autonomic control responses during an orthostatic test (23). The R-R intervals were filtered using the HR monitor's software (Polar Pro Trainer 5; Kempele OY, Finland) and subsequently analyzed via a custom-specific HRV software package (Kubios HRV 2.1; Kuopio, Finland). Time (HR, standard deviation of all normal R-R intervals [SDNN], and root-mean-square of successive differences between normal sinus R-R intervals [RMSSD]) and frequency domain (low-frequency power and high-frequency power) parameters were obtained (26,27,30,46).

Anthropometric Measurements

Body mass and height (Añó, Sayol, Spain) were obtained from each participant using standardized procedures. Skinfolds were also evaluated using a skinfold caliper (Holtain Crymych, United Kingdom), and the sum of 4 skinfolds was calculated as previously described (13).

Jump Capacity

Participants warmed up by performing aerobic exercise for 5 minutes at ∼60% of the estimated HRmax, followed by 4 submaximal CMJs with a 30-second recovery between attempts. After 3 minutes of rest, explosive strength levels of the lower limbs were evaluated by performing 2 maximal CMJs (CMJmax). Valid attempts were separated by at least 30 seconds and performed on a force plate (Quattro Jump; Kistler, Winterthur, Switzerland) with a sampling rate of 500 Hz. Various kinetic parameters were examined (8) with only the highest jump using the impulse-momentum method.

Muscular Strength

Participants performed a specific warm-up for bench press and half squat exercises consisting of 2 sets of 15 and 10 repetitions with a perception of effort (OMNI Scale) (37) of 2 and 3, respectively, and with a recovery of 3 minutes between sets. After 5 minutes of rest, participants underwent a test until muscular failure with a load that allowed them to perform 7–10 repetition maximum (RM) with proper technique. This load was then used to estimate the participants' 1RM through validated equations in the same population for bench press (32) and half squat (47) exercises. The test protocol was repeated with a higher load after 5 minutes when the participants were able to perform more than 10 repetitions.

Aerobic Capacity

Participants wore a HR monitor with a HR band (Polar Electro OY) during the test and completed the Université de Montréal Track Test (UMTT) to determine their maximum aerobic speed (MAS), HRmax, and estimated maximum oxygen consumption (V̇o2max) (29). The cadence of the test was similar to the original (i.e., 1 km·hour−1 every 2 minutes) (28), but the initial velocity commenced at 5 km·hour−1. The velocity of the UMTT was dictated by a cyclist with a velocimeter that was previously calibrated according to the manufacturer's recommendations (7). To determine the MAS more precisely, a value of 0.5 km·hour−1 was added to the MAS when participants completed an extra 1 minute of the next 2-minute completed stage with the final time of the test (TUMTT) also recorded (7,8,45). Participants were encouraged to continue until volitional exhaustion with the following criteria attained to confirm maximal effort: (a) reported perception of effort ≥8 (via CR-10 scale) and (b) attainment of a HR ≥95% of the estimated HRmax.

Concurrent Training Period

Experimental groups underwent an 8-week CT program of externally equated loads but with different intensity distributions. The TT group followed a training program that was based on the recent ACSM recommendations for improving cardiorespiratory and neuromuscular fitness in healthy adults (16). The PT group followed a CT program with the same external load but with a polarized intensity distribution for cardiorespiratory and resistance exercises (Figure 2). All participants were instructed to avoid modifications in their daily lifestyle routines during the training period, especially for incidental PA levels, sleep, and nutrition patterns.

Figure 2.
Figure 2.:
Training design of the experimental groups during the 8-week training period. Continuous-line and dotted-line circles represent the different training session modalities for the PT and TT groups, respectively. PT: polarized training group; TT: traditional-based training group; BW: brisk walking; RM: repetition maximum; RNG: running; IST: intermittent sprint training.

The training programs were conducted during spring (i.e., April and May) and consisted of 3 sessions per week (i.e., Monday, Wednesday, and Friday) that lasted ∼120 minutes each on Monday and Friday and ∼60 minutes on Wednesday. All sessions were monitored by the main investigator. Each participant trained at the same time of the day (at morning or at afternoon) to avoid the effect of circadian rhythms on performance and subsequent adaptations. Training sessions on Mondays and Fridays consisted of cardiorespiratory exercise training (i.e., brisk walking or running) followed by resistance exercise training; meanwhile on Wednesdays participants only performed cardiorespiratory exercise training.

Each training session started with a standardized warm-up that consisted of 5 minutes of calisthenics followed by 5 minutes of brisk walking at 30% of the MAS. Before resistance exercises, participants also performed a specific warm-up that consisted of 2 sets of 8 repetitions of the resistance circuit they performed during the familiarization period with an OMNI Scale perception of effort of 2–3 (37). Cooling down exercises consisted of 2–3 sets of 15 seconds of stretching exercises of the muscle groups involved during the session. Subsequently, participants reported their session's sensations via the Feeling Scale (20), and ratings of perceived exertion (RPE) (5) were collected for subsequent calculation of training impulses (TRIMPS) according to Foster et al. (15).

Cardiorespiratory Exercise Training

The TT group performed 24–37 minutes of running at 65–75% of the MAS per session. The PT group performed 35–65 minutes of brisk walking at 35–40% of the MAS per session. On Wednesdays, participants of the PT group combined brisk walking plus high-intensity training (HIT) with a work-to-rest ratio of 1:1. Intermittent sprint training consisted of 2 sets of 10–12 repetitions of 15 seconds at ∼120% of the MAS with a passive recovery of 15 seconds between repetitions and 2 minutes between sets.

The running and brisk walking paces and distance to cover in each training session were individually calculated and equated using a previously described equation (45). The equation multiplies the volume (expressed in minutes) by the intensity (expressed in % of the MAS). Individualized HIT distance was therefore calculated by multiplying the velocity (expressed in ms−1) by the time required per repetition.

Resistance Exercise Training

The bench press and half squat exercises were selected as the most appropriate upper and lower limb exercises (16) for this population. Based on the conclusions of Simão et al. (40), the order of resistance exercises was alternated each week to minimize the effects of fatigue developed in the previous training session component.

The TT group performed 3–5 sets of 10–12RM with 3 minutes of rest between sets. The PT group performed 3–5 sets of 5RM on Mondays and 2–4 sets of 15RM on Fridays. The rest between sets was always 3 minutes. Resistance exercise workloads were equated based on a previous study (1). Thus, total load volume (i.e., sets × repetitions) was calculated and multiplied by load intensity (i.e., RM determined for every training session). Finally, a weighted average was calculated to obtain a similar number of RM in each training microcycle for both experimental groups. The main objective of each resistance exercise training session was to develop the number of repetitions while maintaining a proper technique. Each participant added or subtracted enough load to achieve this objective during sets under the supervision of the main investigator. All training workouts were individualized for each participant, based on the pretest results, and were increased during the microcycles by ∼2–10% when the participants could perform one to 2 repetitions over the planned workload (3).

Statistical Analyses

Data analyses were performed using SPSS 15.0 for Windows (Chicago, IL, USA). The Kolmogorov-Smirnov test was conducted to check the normal distribution of the variables. Analysis of variance (ANOVA) repeated measures with 2 factors (time × group) were performed to evaluate the differences between groups and between planned and performed exercise training workloads. A repeated-measures ANOVA with 3 factors was conducted to analyze HRV variables (time × group × position) and the differences between experimental groups during the 8-week training period (group × mesocycles × microcycles). A one-way ANOVA was performed to identify differences between groups for changes in pre-post values (expressed as percentage, ∆%). When the variables did not follow a normal distribution, the nonparametric Kruskal-Wallis test was performed. Games Howell post hoc tests with Bonferroni correction were performed as required. Cohen's d was also calculated to determine the effect size (ES) with the following thresholds: 0.20 “small,” 0.50 “medium,” and 0.80 “large.” The statistical significance was set at 0.05.

Results

Thirty-one of the 35 participants who started the study completed all the evaluations and performed, at least, ∼85% of the training sessions under the supervision of the main investigator. Four participants dropped out because of different circumstances (i.e., injuries not related to the study, personal reasons, or not meeting the inclusion criteria). Characteristics of the groups that were involved in the analyses were as follows: TT (n = 11; 9 men and 2 women; 22.36 ± 2.62 years; 177.46 ± 7.66 cm), PT (n = 10; 8 men and 2 women; 21 ± 2.71 years; 174.39 ± 6.1 cm), and CG (n = 10; 9 men and 1 woman; 22.2 ± 2.44 years; 175.82 ± 9.68 cm). There were no significant differences (p > 0.05) between training groups for total workload (i.e., volume × intensity) in each microcycle. Changes in body composition for all groups after the training period are presented in Table 1.

Table 1.
Table 1.:
Anthropometric characteristics before (Pre) and after (Post) the training period.*

Heart Rate Variability

Heart rate variability parameters, before and after the training period, are presented in Table 2. Only the TT group exhibited a significant training-induced decrease in resting HR in both supine and standing positions. When supine and standing positions were compared, there were significant differences between groups, before and after the training period (Table 2).

Table 2.
Table 2.:
Heart rate variability parameters during supine rest and standing position, before (Pre) and after (Post) the training period.*
Table 2-A.
Table 2-A.:
Heart rate variability parameters during supine rest and standing position, before (Pre) and after (Post) the training period.*

Neuromuscular Performance

Table 3 shows the explosive strength levels (i.e., assessed via CMJ) and maximum strength levels (i.e., estimated 1RM) of both upper and lower limbs. Regarding lower limb explosive strength, only the PT group was able to maintain jump height levels after the training period. There was a significant interaction effect for estimated 1RM of bench press and half squat exercises (p = 0.000 for both) with the PT and TT groups significantly improving estimated 1RM levels after the training period. These improvements were significantly greater for both PT and TT groups when compared with CG (p < 0.01 for all, Table 3).

Table 3.
Table 3.:
Neuromuscular variables before (Pre) and after (Post) the training period.*
Table 3-A.
Table 3-A.:
Neuromuscular variables before (Pre) and after (Post) the training period.*

Aerobic Capacity

There was a significant interaction effect for MAS (p = 0.048), TUMTT (p = 0.016), and estimated V̇o2max (p = 0.048) with both experimental groups significantly improving MAS, TUMTT, and estimated V̇o2max after the training period (Table 4).

Table 4.
Table 4.:
Running performance variables before (Pre) and after (Post) the training period.*

Perceptual Variables

Rate of perceived exertion, Feeling Scale scores, and TRIMPS over the 8-week training period are presented in Figures 3A–C, respectively. Overall, both training programs were perceived similarly by the training groups.

Figure 3.
Figure 3.:
Perceptive variables over the training period: (A) rate of perceived exertion, (B) Feeling Scale scores, and (C) training impulses. *Significant differences between TT and PT (p ≤ 0.05); † significant differences between the microcycles of the second mesocycle compared with the same microcycles of the first mesocycle (p ≤ 0.05); significant differences between microcycles in each mesocycle: a differences between microcycles 1 and 2 (p ≤ 0.05); b differences between microcycles 1 and 3 (p ≤ 0.05); c differences between microcycles 1 and 4 (p ≤ 0.05); d differences between microcycles 2 and 3 (p ≤ 0.05); e differences between microcycles 2 and 4 (p ≤ 0.05). PT: polarized training group; TT: traditional-based training group; Micro: microcycle; RPE: ratings of perceived exertion; TRIMPS: training impulses. f differences between microcycles 3 and 4 (p ≤ 0.05).

Discussion

The main findings of this study were that CT programs of different intensity distribution, but equated loads, produced similar improvements in neuromuscular and cardiorespiratory fitness in a group of young, healthy, and physically active individuals. Maximum strength was developed without interference by both experimental groups. However, only the PT group was able to maintain lower limb explosive power (jump capacity). However, cardiorespiratory fitness improvements reached by the PT group (e.g., performing brisk walking and sprint training) were similar to those exhibited by the TT group (e.g., performing moderate-intensity continuous running). The TT and PT training programs were perceived similarly by both groups. These findings were important and novel given that these training programs were performed at a volume (only 3 days a week over a 2-month period) that was far below the training volume of most previous studies (9,10,22,26,43).

Our results from the orthostatic test showed that only the TT group experienced a significant (∼12.5%) decrease in HR during supine rest and standing after the training period. However, the CG group experienced a significant (∼13%) increase in resting HR during standing. These HR changes were significantly greater for TT when compared with CG during both supine rest and standing, but not significantly different to the PT group. Our results are in accordance with previous studies which have consistently demonstrated long-term resting bradycardia after an aerobic training period (30,46). This bradycardia could be a result of a decrease in the cardiac intrinsic rate (46) with resting bradycardia without concomitant changes in HRV reported after a 16-week aerobic training period (30). The lack of significant change in some HRV components after the current training period could have been due to the training design. However, it should be pointed out that the TT group exhibited greater ES for time and frequency domain HRV parameters compared with the PT group. Training program duration and training frequency, intensity, and volume have been reported to influence changes in HRV, suggesting a dose-response relationship (46). Therefore, inclusion of a higher training frequency and higher training program duration may have resulted in significant changes in HRV components, and even between groups. Additionally, vagal saturation may have impacted on training-induced HRV changes (27) as participants from the current study were physically active before the training period, with reported basal HR levels compatible with this phenomenon (19). Evaluation of cardiac autonomic control during submaximal steady-state exercise (26) may also reveal some autonomic adaptations after CT with further studies needed to elaborate on this. Nevertheless, the enhanced bradycardia exhibited by the TT group after the training period reflects a cardioprotective result (30).

After the training period, only the PT group significantly increased body mass (1.83%) and body mass index (BMI) (2.31%) with no evident changes in body fat (i.e., the sum of skinfolds). It has been consistently demonstrated that body fat distribution plays an important role in the prognosis of chronic diseases and related risk factors. Recent studies have demonstrated that CT produces greater improvements for body composition than the isolated training of strength and endurance physical capacities (22). Furthermore, it has been suggested that high-intensity training is more efficient for abdominal fat reduction than that performed at lower intensities (44). Our results do not support this view as no significant changes in body fat were observed for any group after the training period. Nonetheless, TT experienced a greater nonsignificant reduction (ES: 0.18) in this variable compared with PT (ES: 0.05), indicating that a higher, weekly, training frequency and a longer training period could contribute to substantial changes in body fat composition. Additionally, the increase of body mass and BMI with no changes in body fat for PT may suggest an increase in lean body mass for this group, although this component of body composition was not assessed currently. Further studies may elucidate the impact of longer training periods (e.g., 12 weeks) of similar training regimens on different body composition components (e.g., muscle mass and bone mineral density).

Our results showed that brisk walking combined with HIT, and low- and very high–intensity strength training (i.e., PT group), did not interfere with short-term, lower limb explosive strength performance as observed in the other groups. Furthermore, this preservation in vertical jump capacity was achieved despite a significant increase in body mass. Previously, it was suggested that concurrent endurance and strength training could compromise explosive strength development (12), particularly when endurance training was performed with a high frequency (i.e., ≥4 days a week) or at high intensity (i.e., ≥80% V̇o2max) (4). In contrast, previous studies have suggested that the “interference phenomenon” is consistently minimized, when high-volume endurance training is concurrently performed with low-volume high-intensity strength training (e.g., maximum strength training and explosive strength/plyometric training) (38,43) with a weekly frequency up to 3 days (4). Our results confirm previous scientific evidence because only the PT group was able to maintain jump performance. It should be noted thought that the training loads in our study were far less than the training loads of previous studies. Moreover, the maintenance of jump capacity in the current study was accompanied by a significant decrease in Fmax after the training period, thus suggesting an increase of elastic energy recoil (8). Recently, it was suggested that short-term (i.e., 12 weeks) endurance training of different volume and intensity (i.e., continuous running and HIT) did not impair vertical jump performance in untrained subjects (24). In this regard, our results suggest that the polarized distribution of training attenuates the “interference phenomenon” in respect to neuromuscular performance. In contrast, TT experienced a significant decrease in jump height (7.26%) after the training period, which was similar to that showed by the CG (−8.3%). The loss of jump capacity for the CG group was surprising and may be explained by the uncontrolled PA patterns derived from the academic activities performed by all participants. Moreover, the influence of mental fatigue could have impacted on jump performance; however, recent evidence suggested no influence of acute mental fatigue on anaerobic performances (31). All participants were at the end of the semester (i.e., final examinations) at the time of postevaluations with no evidence, to the best of our knowledge, apparent of the possible negative influence of chronic mental fatigue on neuromuscular performance (personal observations). Nevertheless, our results reinforce the less “interference phenomenon” of training on jump capacity by the PT group.

However, TT and PT training programs produced significant and similar improvements in upper and lower limb muscular strength. It has been recently suggested that high- to very high–intensity strength training produces greater strength gains than low- or moderate-intensity strength training. However, when training volume was equated in the current study, differences between programs were not significant and similar to previous evidence (36). Previous studies have demonstrated strength gains in upper and lower limbs after a low-volume, high-intensity, strength training program (2,34) in young healthy individuals with previous experience in strength training. The fact that our training programs have produced greater strength gains (∼40–47%) than those reported in previous studies (∼12–22%) (2,34) could be partially due to the training background of participants with the current groups having no previous experience in strength training. Nevertheless, it should be pointed out that the experimental groups in the current study performed both strength and endurance training; therefore, a synergistic effect of both training modes could be expected.

In relation to cardiorespiratory fitness, our results showed a significant improvement for MAS (∼4%) in TT and PT groups. It has been previously demonstrated that V̇o2max could be reliably estimated from MAS (29) with a high correlation between laboratory and field values. Therefore, an improvement of MAS may indicate an increase in V̇o2max levels of nonendurance runners' populations like those in the current study. Recent scientific evidence has suggested that HIT is as effective as continuous aerobic training (18), or even more (17,41), for cardiorespiratory fitness improvement. Our results suggest that both training regimens improved cardiorespiratory fitness to a similar extent. The performance of HIT once a week, combined with brisk walking (i.e., 35–40% MAS), was sufficient to produce improvements that were comparable with those derived from running at moderate intensity (i.e., 65–75% MAS), when both programs were combined with strength training. Similar to our results, a recent study conducted by Cantrell et al. (9) suggested that performing concurrent sprint interval and strength training did not compromise strength gains and also improved V̇o2max. Moreover, recent studies suggest that sprint training has a greater effectiveness than continuous aerobic training in improving running performance (e.g., 3000-m time-trial, repeated sprint ability, and 40-m sprint performance) (11). The fact that our results did not identify differences between training programs could be explained by the low frequency of HIT performed by PT. Potentially, the conduction of HIT twice a week could have resulted in significant differences in performance between TT and PT groups, as previous studies have demonstrated a greater effectiveness of HIT when HIT weekly frequency was greater than 2 days (11,17,41). However, when endurance training loads are externally equated between continuous and interval training methods, differences were nonsignificant, even when training frequency was 3 days a week (45).

Another important finding was that TT and PT reported similar perceptions of effort, sensations, and internal load levels over the 8-week training period. Briefly, RPE and TRIMPS increased progressively along the 8-week training period. These perceptual levels demonstrated an increase in external load during the third microcycle compared with the first and second microcycles of each mesocycle. Possibly, the higher RPE and TRIMPS levels were related with the lower scores of the Feeling Scale. Previous studies have reported that RPE and TRIMPS are valid tools for monitoring exercise intensity (15). However, other researchers (20) have argued that exercise RPE can represent different affective values. Despite this, the current findings suggest that different CT regimes of equated loads could be similarly perceived by participants.

Our study presents with some limitations. First, there were a low number of female participants with a need for some caution of generalization of our results to women. Second, the methods used for detecting changes in different components of body composition were not optimal with the absence of nutritional control also a noticeable limitation. Third, determination of RM for both exercises was estimated from specific formulas; however, this approach was selected for a standardization of evaluations in participants not experienced in resistance training. Fourth, V̇o2max values were estimated from a specific formula. Nevertheless, gains in MAS for nonrunners have been reported to result from improvements in V̇o2max values, although alterations in running economy should not be discarded. Finally, given the necessity of equating external loads in both training regimens for appropriate comparisons, the PT group did not perform a common polarized training as investigated in the previous literature (39). This consideration is important given that the PA pattern of our ancestors included an important volume of low-intensity PA and submaximal running (6).

In summary, our results suggest the appropriateness of implementing CT programs of different training intensity distribution for improving fitness in healthy adults. The absence of important differences between programs could be due to the training designs and the equated loads. However, it is important to note that in PT, brisk walking combined with HIT showed, at least, as many cardiorespiratory benefits as those experienced by TT with a more specific training modality. Additionally, a significant reduction in resting HR was observed only for TT with no significant changes in HRV parameters. Furthermore, the alternation of low-intensity with high-intensity strength training loads for PT was as effective as moderate-intensity strength training loads for improving muscular strength for TT. However, PT was more effective for the maintenance of jump capacity. Further studies are needed to evaluate if a longer (i.e., >8 weeks) polarized CT with the inclusion of moderate intensity running and other resistance exercises (e.g., full squats) could be a more effective strategy to optimize these benefits.

Practical Applications

Based on our results and conclusions, an 8-week CT program with a polarized intensity distribution was as effective as training traditionally recommended for improving fitness, when both programs were externally equated. Furthermore, the perception of effort and sensations of this training intensity distribution were comparable with those reported by a concurrent traditional-based intensity distribution, showing a good tolerance of training loads and similar adherence. Therefore, strength and conditioning professionals could select indistinctly these intensity distributions for CT depending on individuals' interests and possibilities. The performance of PT may be better for a reduced interference in neuromuscular performance, whereas TT would be more appropriate for cardiac health. The identification of significant improvements with young, healthy, and physically active individuals in the current study indicates that sedentary individuals could experience greater benefits with CT, while longer periods of training maximizing them.

Acknowledgments

The authors thank the participants and collaborators of this study, especially Dr. Manolo Giráldez. They also thank Dr. Anthony Leicht for the English revision of the article. They also acknowledge Begano S.L. (La Coruña, Spain), who supplied drinks along the training and evaluation periods. The results of the present study do not constitute endorsement of the product by the authors or the National Strength and Conditioning Association.

References

1. Ahtiainen JP, Pakarinen A, Alen M, Kraemer WJ, Häkkinen K. Short vs. long rest period between the sets in hypertrophic resistance training: Influence on muscle strength, size, and hormonal adaptations in trained men. J Strength Cond Res 19: 572–582, 2005.
2. Alcaraz PE, Perez-Gomez J, Chavarrias M, Blazevich AJ. Similarity in adaptations to high-resistance circuit vs. traditional strength training in resistance-trained men. J Strength Cond Res 25: 2519–2527, 2011.
3. American College of Sport Medicine. American College of Sport Medicine position stand. Progression models in resistance training for healthy adults. Med Sci Sports Exerc 41: 687–708, 2009.
4. Baar K. Using molecular biology to maximize concurrent training. Sports Med 44(Suppl 2): S117–S125, 2014.
5. Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 14: 377–381, 1982.
6. Boullosa DA, Abreu L, Varela-Sanz A, Mujika I. Do olympic athletes train as in the Paleolithic era? Sports Med 43: 909–917, 2013.
7. Boullosa DA, Tuimil JL. Postactivation potentiation in distance runners after two different field running protocols. J Strength Cond Res 23: 1560–1565, 2009.
8. Boullosa DA, Tuimil JL, Alegre LM, Iglesias E, Lusquiños F. Concurrent fatigue and potentiation in endurance athletes. Int J Sports Physiol Perform 6: 82–93, 2011.
9. Cantrell GS, Schilling BK, Paquette MR, Murlasits Z. Maximal strength, power, and aerobic endurance adaptations to concurrent strength and sprint interval training. Eur J Appl Physiol 114: 763–771, 2014.
10. Chtara M, Chamari K, Chaouachi M, Chaouachi A, Koubaa D, Feki Y, Millet GP, Amri M. Effects of intra-session concurrent endurance and strength training sequence on aerobic performance and capacity. Br J Sports Med 39: 555–560, 2005.
11. Cicioni-Kolsky D, Lorenzen C, Williams MD, Kemp JG. Endurance and sprint benefits of high-intensity and supramaximal interval training. Eur J Sport Sci 13: 304–311, 2013.
12. Docherty D, Sporer B. A proposed model for examining the interference phenomenon between concurrent aerobic and strength training. Sports Med 30: 385–394, 2000.
13. Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: Measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 32: 77–97, 1974.
14. Esteve-Lanao J, Foster C, Seiler S, Lucia A. Impact of training intensity distribution on performance in endurance athletes. J Strength Cond Res 21: 943–949, 2007.
15. Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, Doleshal P, Dodge C. A new approach to monitoring exercise training. J Strength Cond Res 15: 109–115, 2001.
16. Garber CE, Blissmer B, Deschenes MR, Franklin BA, Lamonte MJ, Lee IM, Nieman DC, Swain DP. 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 43: 1334–1359, 2011.
17. Gillen JB, Gibala MJ. Is high-intensity interval training a time-efficient exercise strategy to improve health and fitness? Appl Physiol Nutr Metab 39: 409–412, 2014.
18. Gist NH, Fedewa MV, Dishman RK, Cureton KJ. Sprint interval training effects on aerobic capacity: A systematic review and meta-analysis. Sports Med 44: 269–279, 2014.
19. Goldberger JJ, Challapalli S, Tung R, Parker MA, Kadish AH. Relationship of heart rate variability to parasympathetic effect. Circulation 103: 1977–1983, 2001.
20. Hardy C, Rejeski W. Not what, but how one feels: The measurement of affect during exercise. J Sport Exerc Physiol 11: 304–317, 1989.
21. Harries SK, Lubans DR, Callister R. Systematic review and meta-analysis of linear and undulating periodized resistance training programs on muscular strength. J Strength Cond Res 29: 1113–1125, 2015.
22. Ho SS, Dhaliwal SS, Hills AP, Pal S. The effect of 12 weeks of aerobic, resistance or combination exercise training on cardiovascular risk factors in the overweight and obese in a randomized trial. BMC Public Health 12: 704, 2012.
23. Hynynen E, Konttinen N, Kinnunen U, Kyröläinen H, Rusko H. The incidence of stress symptoms and heart rate variability during sleep and orthostatic test. Eur J Appl Physiol 111: 733–741, 2011.
24. Jakobsen MD, Sundstrup E, Randers MB, Kjær M, Andersen LL, Krustrup P, Aagaard P. The effect of strength training, recreational soccer and running exercise on stretch-shortening cycle muscle performance during countermovement jumping. Hum Mov Sci 31: 970–986, 2012.
25. Kang J, Ratamess N. Which comes first? Resistance before aerobic exercise or vice versa? ACSMS Health Fit J 18: 9–14, 2014.
26. Karavirta L, Costa MD, Goldberger AL, Tulppo MP, Laaksonen DE, Nyman K, Keskitalo M, Häkkinen A, Häkkinen K. Heart rate dynamics after combined strength and endurance training in middle-aged women: Heterogeneity of responses. PloS One : e72664, 2013.
27. Kiviniemi AM, Hautala AJ, Mäkikallio TH, Seppänen T, Huikuri HV, Tulppo MP. Cardiac vagal outflow after aerobic training by analysis of high-frequency oscillation of the R-R interval. Eur J Appl Physiol 96: 686–692, 2006.
28. Léger L, Boucher R. An indirect continuous running multistage field test: The Université de Montréal track test. Can J Appl Sport Sci 5: 77–84, 1980.
29. Léger L, Mercier D. Energy cost of treadmill and track running.[In French] Mot Hum 2: 66–69, 1983.
30. Leicht AS, Allen GD, Hoey AJ. Influence of age and moderate-intensity exercise training on heart rate variability in young and mature adults. Can J Appl Physiol 28: 446–461, 2003.
31. Martin K, Thompson KG, Keegan R, Ball N, Rattray B. Mental fatigue does not affect maximal anaerobic exercise performance. Eur J Appl Physiol 115: 715–725, 2015.
32. Mayhew J, Ball T, Arnold M, Bowen J. Relative muscular endurance performance as a predictor of bench press strength in college men and women. J Appl Sport Sci Res 6: 200–206, 1992.
33. Mujika I. The alphabet of sport science research starts with Q. Int J Sports Physiol Perform 8: 465–466, 2013.
34. Otto WH 3rd, Coburn JW, Brown LE, Spiering BA. Effects of weightlifting vs. kettlebell training on vertical jump, strength, and body composition. J Strength Cond Res 26: 1199–1202, 2012.
35. Paavolainen L, Häkkinen K, Rusko H. Effects of explosive type strength training on physical performance characteristics in cross-country skiers. Eur J Appl Physiol 62: 251–255, 1991.
36. Raymond MJ, Bramley-Tzerefos RE, Jeffs KJ, Winter A, Holland AE. Systematic review of high-intensity progressive resistance strength training of the lower limb compared with other intensities of strength training in older adults. Arch Phys Med Rehabil 94: 1458–1472, 2013.
37. Robertson RJ, Goss FL, Rutkowski J, Lenz B, Dixon C, Timmer J, Frazee K, Dube J, Andreacci J. Concurrent validation of the OMNI perceived exertion scale for resistance exercise. Med Sci Sports Exerc 35: 333–341, 2003.
38. Rønnestad BR, Mujika I. Optimizing strength training for running and cycling endurance performance: A review. Scand J Med Sci Sports 24: 603–612, 2014.
39. Seiler KS, Kjerland GØ. Quantifying training intensity distribution in elite endurance athletes: Is there evidence for an “optimal” distribution? Scand J Med Sci Sports 16: 49–56, 2006.
40. Simão R, de Salles BF, Figueiredo T, Dias I, Willardson JM. Exercise order in resistance training. Sports Med 42: 251–265, 2012.
41. Sloth M, Sloth D, Overgaard K, Dalgas U. Effects of sprint interval training on VO2max and aerobic exercise performance: A systematic review and meta-analysis. Scand J Med Sci Sports 23: e341–e352, 2013.
42. Stöggl T, Sperlich B. Polarized training has greater impact on key endurance variables than threshold, high intensity, or high volume training. Front Physiol 5: 33, 2014.
43. Taipale RS, Mikkola J, Vesterinen V, Nummela A, Häkkinen K. Neuromuscular adaptations during combined strength and endurance training in endurance runners: Maximal versus explosive strength training or a mix of both. Eur J Appl Physiol 113: 325–335, 2013.
44. Trapp EG, Chisholm DJ, Freund J, Boutcher SH. The effects of high-intensity intermittent exercise training on fat loss and fasting insulin levels of young women. Int J Obes 32: 684–691, 2008.
45. Tuimil JL, Boullosa DA, Fernández-del-Olmo MA, Rodríguez FA. Effect of equated continuous and interval running programs on endurance performance and jump capacity. J Strength Cond Res 25: 2205–2211, 2011.
46. Tulppo MP, Hautala AJ, Mäkikallio TH, Laukkanen RT, Nissilä S, Hughson RL, Huikuri HV. Effects of aerobic training on heart rate dynamics in sedentary subjects. J Appl Physiol 95: 364–372, 2003.
47. Wathan D. Load assignment. In: Essentials of Strength Training and Conditioning. Baechle TR, ed. Champaign, IL: Human Kinetics, 1994. pp. 435–439.
Keywords:

endurance training; strength training; resistance training; sprint training; multimodal training

© 2016 National Strength and Conditioning Association