The combined effects of concurrent strength and endurance training on the endurance performance of untrained (12,16,18,19,25) or trained athletes (13,14,22,23) have been extensively studied. There is evidence to suggest that endurance training inhibits maximal strength development, mainly a few weeks after commencement of a concurrent training regime (25). It has been suggested that although strength training does not interfere with the development of the maximal oxygen uptake (V̇O2max) (11–12,18), it could lead to improvement of endurance performance of untrained (11,12,18,19,25) or moderately trained athletes (13).
It has been well documented that the speed achieved in endurance competition relies not only on the rate of energy expenditure but also on the energy cost (CR) of the considered locomotion (9). It also appears that CR is a better predictor of endurance performance than V̇O2max in a homogeneous group of athletes (8). However, the effects of concurrent strength and endurance training on economy in well-trained endurance athletes are still unclear. It has been argued that strength training improves (13,14,23) or has no influence (29) on the economy. Paavolainen et al. (22,23) investigated the effects of explosive-strength training in well-trained athletes, but the effects of concurrent heavy weight training (HWT) and endurance training on economy have not been studied in elite athletes.
At the highest submaximal intensities, above the lactate threshold, CR represents only the aerobic contribution to the total energy expenditure (9), and this aerobic part tends to rise slowly. The slow component of oxygen uptake kinetics in long-term constant-rate exercise can be described as an increase in the energy expenditure above that predicted from submaximal V̇O2-work rate relationship, leading to a reduced work efficiency (10). Several studies (5,6,10,21,24,28) have shown that endurance training results in a change in V̇O2 kinetics, so that a shorter constant time of the primary phase (21,24) and a reduced amplitude of the V̇O2 slow component occurs (5,10,28). It was proposed that around 85% of the V̇O2 slow component is located at the muscular level (10) and that central factors have only a minor influence on its amplitude. A limited V̇O2 slow component has been suggested to be an important parameter of the endurance performance (10). However, to the best of our knowledge, very little is known on the effects of strength training on the characteristics of the V̇O2 kinetics, especially the parameters that described the primary phase and the slow component (29). Therefore, the purpose of the present study was to examine the effects of a regime of maximal strength training, in combination with an existing endurance-training program, on the running economy in well-trained triathletes. Furthermore, this study was conducted to determine whether strength training influences the V̇O2 kinetics during heavy constant-rate running exercise.
Approach to the problem and experimental design.
The hypothesis that combined HWT and endurance training would lead to greater lower limb strength, power, and stiffness and be more transferable to a better running economy than endurance-only training was tested. To answer this question and compare the impacts of a combined versus an endurance-only training, we chose two different training regimes, suitable for inclusion in the winter schedule of national and international-level triathletes, over a long period of 14 wk, a duration classically observed in the endurance sports. A field-based approach was applied to evaluate both realistic central and peripheral adaptations that could influence the performance.
Fifteen well-trained subjects were randomly assigned to the endurance-strength training group (ES;N = 7) or to the endurance-only group (E;N = 8). Seven of them, practicing at an international level (elite national team), were matched in the two groups (three in ES and four in E). All the subjects agreed to participate in the study on a voluntary basis. The study was approved by the institutional ethics committee, and all subjects provided written, voluntary, informed consent before participation. The subjects were all fully familiar with testing procedures, having regularly being tested as part of their training evaluation. The physical characteristics of the two groups are shown in Table 1.
Before and after a controlled training period, all subjects performed field and laboratory-based running and muscle function tests. The first test involved an incremental running test to exhaustion to determine the maximal oxygen uptake (V̇O2max), the velocity associated with V̇O2max (VV̇O2max), the velocity associated to the second ventilatory threshold (VVT2), and the velocity associated to the intensity termed Δ25% (VΔ25%), corresponding to V̇O2 VT2 plus 25% of the difference between V̇O2 VT2 and V̇O2max. The second test comprised a 3000-m run at a controlled constant VΔ25% preceded by 6 min at 75% VV̇O2max to determine running energy cost at the two intensities (CR75% and CRΔ25%) and record breath-by-breath V̇O2 data to model V̇O2 kinetics during exercise. A third series of tests included maximal hopping tests at a 2-Hz frequency to determine the maximal mechanical hopping power and lower-limb hopping stiffness. A forth series was maximal concentric lower-limb strength measurements.
The training period lasted for 14 wk and was carried out during the winter period, when the subjects were not involved in any competitions. The training period started after a 10-wk preconditioning-orientation phase, where the subjects restarted consistent training. All athletes were experienced and members of a residential training center where they were under the control of professional trainers. Moreover, they recorded training exercises in a diary that was reviewed regularly. The vast majority of the training during this basic period was strictly aerobic, realized under 70% of V̇O2 (Table 1). Stretching remained constant (1.6 ± 0.5 h·wk−1) in the two groups.
In addition to the endurance training, the ES group performed an HWT session of lower-limb muscles twice a week. Exercises (i.e., hamstring curl, leg press, seated press, parallel squat, leg extension, and heel raise) were exclusively focused on quadriceps, hamstring, and calf muscles. Workouts consisted of two warm-up sets followed by three to five sets to failure of 3–5 reps. The training program was periodized and was composed of several 3-wk periods. In each of these periods, the number of sets increased (i.e., three in the first week, four in the second week, and five in the third week). The loads were calculated > 90% one-repetition-maximal (1RM) and were progressively increased to maintain this range of repetitions per set. Reassessment of 1RM was completed by the ES group every 3 wk to maintain maximal loads over the whole training period.
The ES and E groups were examined before training and after the training period. The testing protocol was conducted over two consecutive days on a 400-m synthetic track, then an additional day in the following week in the laboratory for concentric strength and hopping tests. ES performed supplementary maximal strength tests at week 6.
Maximal concentric lower-limb strength measurements.
Maximal concentric strength evaluation was performed using two exercises (half-squat and heel raise) by all athletes before and after the training period. After a warm-up workout, the subject’s near-maximal load was approximated by the trainer to be around 90% of the previous best load of the subject. The load was gradually increased until the subject could lift the resistance once but not twice. This load was therefore defined as 1RM. For the half-squat, the starting position was at a knee angle of 120°, and the exercise was performed in a guided strength rack, ensuring maximal security. The amplitude of the movement was controlled by the trainer. For the heel-raise exercise, the starting position was a standing position with straight legs. Because the resistance was maximal, two assistants helped the subjects to position the bar correctly over the shoulders, to prevent any accident.
Maximal vertical rebounds on both legs were executed by the subjects from a standing position at 2 Hz for 10 s before and after the training period. Subjects were instructed to rebound to the highest possible point with the smallest ground contact times and to keep hands on the hips throughout the hops (4,7). Flight time (tf) and ground contact times (tc) were recorded by an apparatus consisting of a digital timer connected to a contact mat (Powertimer, Newtest, Oulu, Finland) with an accuracy of 1/100 s. As described previously (4,7), the displacement of the center of mass during the flight (hf) and the maximal mechanical power of the positive work (P) of the subjects were calculated:MATHMATHwhere m the body mass of the subject, tt is the total time of the hop (tt = tc + tf), and g is the gravitational acceleration.
The vertical stiffness of the lower limbs (Kvert, N·m·kg−1) is the force change/length change ratio and was calculated, as described previously (7): where ωθ is the forced oscillation of the body while vertical hopping. With tf and tc as known variables, equation 4 can be solved and ωθ determined.
Track running tests.
The following respiratory gas-exchange variables were collected, using a breath-by-breath portable gas analyzer (Cosmed K4b2, Rome, Italy): V̇O2,V̇CO2, pulmonary ventilation (V̇E), ventilatory equivalents for oxygen (V̇E/V̇O2) and carbon dioxide (V̇E/V̇CO2), end-tidal PO2 (PETO2), and PCO2 (PETCO2). Calibration procedures were performed before each test according to the manufacturer’s instructions. Heart rate (HR) was recorded by the K4b2 via a portable HR monitor belt (Polar® Electro, Kempele, Finland). At the end of the tests, subjects indicated their rating of perceived exertion (RPE) using a 6–20 scale. All tests were preceded by a 5-min standing rest to determine the V̇O2 baseline (V̇O2b).
Incremental test to exhaustion.
The subjects performed first the incremental test to exhaustion on a 400-m running track to determine the maximal oxygen uptake (V̇O2max), the velocity associated with V̇O2 (VV̇O2max), and the velocity associated with the second ventilatory threshold (VVT2). In addition, the velocity (VΔ25%) corresponding to V̇O2 VT2 plus 25% of the difference between V̇O2 VT2 and V̇O2max was calculated. MATH
The initial velocity was set as 8 km·h−1 under the estimated VV̇O2max. The duration of the test was expected to be between 15 and 20 min. The increments of velocity were set at 0.5 km·h−1 for stages of 1 min. The subject adjusted his velocity to sound signals and visual marks at each 20-m interval around the track. All subjects were familiarized with this procedure, having completed similar paced exercise sessions during training. All subjects were encouraged to perform their best effort. Breath-by-breath data were averaged over 30 s, and V̇O2max was defined as the highest 30-s value reached. VV̇O2max was determined as the minimal velocity at which V̇O2max was reached. The second ventilatory threshold (VT2) was defined by 1) a systematic increase in V̇E/V̇O2, 2) a concomitant nonlinear increase in the V̇E/V̇CO2, and 3) a decrease in the ΔPETO2 (difference in the inspired and end-tidal O2 pressure). VT2 was determined by two independent observers.
3000-m test at VΔ25%.
On the second day, the subjects performed a 3000-m run at VΔ25%. The subjects warmed up 6 min at ∼60%VV̇O2max followed by 6 min at a controlled V75% velocity, where V75% = 0.75 × VV̇O2max is the intensity where a V̇O2 slow component has been previously observed (6). Before the start of the 3000 m, the subjects rested for 5 min to determine V̇O2b. CR75% and CRΔ25% (in mL O2·kg−1·km−1) were calculated from the averaged 3rd- to 4th-min V̇O2 above basal metabolic rate (BMR), at respectively the V75% warm-up and the VΔ25% 3000 m, as follows:MATHwhere V̇O2 is expressed in mL·kg-1·s−1, 0.083 mL·kg−1·s−1 is the y-intercept of the V̇O2-velocity relationship of young adults, and V is expressed in m·s−1. At posttraining, VΔ25% was reactualized per sine.
Kinematic variables and running leg stiffness.
Average stride frequency (SF, in Hz) and stride length (SL, in m) were recorded eight times, over a 100 m of each lap (SF × SL = average velocity over 100 m). The average values over the 3000-m were retained. The average posttraining running leg stiffness was approximated with the equation 3 from tf and tc, with tc measured at each lap with the contact mat (Powertimer).
To describe the V̇O2 kinetics, a classical exponential model was used (1,3). MATHwhere MATH
V̇O2b is the V̇O2 at rest, A1 and A2 are the asymptotic amplitude, td1 and td2 are the time delays after the start of the exercise, τ1 and τ2 are the constant times, respectively, for the second and third phase. Because the primary phase is not distorted by any cardiodynamic influence, the first 20 s were not taken account in the calculation of the parameters of the primary phase (τ1 and A1). The amplitude of the V̇O2 slow component was defined as A′2MATHwhere te is the time at the end of the exercise.
As described previously (3), the parameters of the model were calculated by an iterative procedure by minimizing the sum of the mean squares of the differences between the modeled V̇O2 and the measured V̇O2 (see subject 1 in Fig. 1A). The values of the measured breath-by-breath V̇O2 that were outside a three standard deviations range from the modeled V̇O2 were removed, representing less than 0.5% of the data collected. The time delay for the slow component phase (td2) was fixed to be higher than the time of the first exponential component for reaching A′1, where A′1 ≥ 99% A1. A Fisher test was used to determine the degree of significance of the exponential model. The distribution of residual errors between the modeled and the measured V̇O2 as a function of time was tested using linear and nonlinear regressions.
Paired t-tests were used to determine the significance of differences in the measured variables before versus after training. When the normality test failed, a Mann-Whitney rank sum test was performed between pre- and post-training variables. A repeated measures ANOVA was used to identify differences between the two groups of subjects, by examination of the group × time interaction. Statistical power was determined to be from 0.57 to 0.69 for the sample sizes used at the 0.05 alpha level (SigmaStat, Jandel Corporation, San Rafael, CA). Effect size (ES) was calculated for each test and displayed for every significant effect. Pearson correlation coefficients were used to examine the relationships between change of economy and change of power, stiffness, or strength variables. The results are presented as means ± SD. For all statistical analyses, a P-value of 0.05 was accepted as the level of statistical significance.
The main characteristics of the endurance training of the triathletes are presented in Table 1. No differences were observed in the training parameters between ES and E during the period studied.
Table 2 shows the effect of the 14 wk of training on the physiological variables during the incremental track-running test. VV̇O2max VT2 did not differ significantly between the groups before training. During the training period, there was a significant increase (P < 0.01) in the velocity associated with V̇O2max for ES (from 19.5 ± 1.0 to 20.0 ± 0.8 km·h−1; ES = 0.57) but not for E (from 19.3 ± 1.0 to 19.8 ± 1.2 km·h−1; ES = 0.39) (Fig. 2A). V̇O2max, VT2 (%V̇O2max), maximal heart rate, and the rating or perceived exertion remained unchanged with training in the two groups.
Table 3 shows the effects of training on the physiological variables and on the parameters of the modeled V̇O2 kinetics during the 3000-m run at Δ25% intensity. Significant group-by-training interactions were found in running economy after 14 wk of training, both below VT2 at 75%VV̇O2max (F = 5.0;P < 0.05; ES = 1.16) or above VT2 at Δ25% ≈ 92%VV̇O2max (F = 8.0;P < 0.05; ES = 1.46). Before training, both CR75% (193.6 ± 4.3 vs 189.8 ± 13.1 mL·kg−1·km−1) and CRΔ25% (196.4 ± 5.5 vs 194.6 ± 22.3 mL·kg−1·km−1) did not differ significantly between ES and E. After training, CR75% (180.2 ± 20.0 vs 203.2 ± 20.2 mL·kg-1·km−1; ES = 1.14) and CRΔ25% (185.4 ± 16.3 vs 205.2 ± 18.1 mL·kg−1·km−1; ES = 1.15) were significantly (P < 0.05) lower in ES than in E (Fig. 2B). No significant differences or changes during the training period were observed in either the ES or E groups in VΔ25% end-exercise HR or RPE during the VΔ25% 3000 m.
The kinetics of the V̇O2 response were modeled with two exponential terms (1) in all subjects, as the exercise duration was always longer than the constant time of the slow component. In other words, in the present study, the use of a linear term instead of an exponential function would have resulted in a lower fit. The coefficient of determination (R2) between the measured and the modeled V̇O2 was 0.73 ± 0.12. The sum of residual errors (< 10−4) was distributed randomly around zero (Fig. 1B) and similar in the two groups. No significant regression was found between the residuals and the time, indicating that the model was appropriate to describe the O2 uptake kinetics and that no further improvement in the model could have been proposed. Before training, ES had faster V̇O2 kinetics with smaller constant times for the second and third phases than E. However, it is of interest to note that the constant times for phase 2 were unchanged during the training period in either the ES or E group. In addition, the amplitude of the slow component remained unchanged in the two groups during the training period.
As required, the velocity was kept constant along the 3000-m test with a coefficient of variation (CV) of 1.6 ± 0.6% between the different laps. No significant differences or changes after the training period were observed in either the ES or E groups in stride frequency (1.52 ± 0.07 and 1.47 ± 0.08 Hz at pretraining, and 1.53 ± 0.08 and 1.52 ± 0.05 Hz at posttraining, respectively, for ES and E) or stride length (3.19 ± 0.24 and 3.28 ± 0.18 m at pretraining, and 3.22 ± 0.28 and 3.23 ± 0.24 m at posttraining, respectively, for ES and E) during the VΔ25% 3000 m. The method used to approximate the running leg stiffness led to a slightly greater variability in contact time (159 ± 7 vs 169 ± 9 ms, ES = 1.2; and between-measures CV = 5.4% vs 4.2%, respectively, for ES and E) and thus in stiffness (between-measures CV = 7.3 ± 1.9% vs 6.0 ± 1.9%, respectively, for ES and E). After training, ES had a significantly greater (P < 0.05) run leg stiffness (643 ± 59 vs 575 ± 58 N·m−1·kg−1; ES = 1.2) than E.
Table 4 shows the effect of training on the body weight, maximal strength, and variables measured during the hopping tests. Before training, maximal strength, contact time, hopping power, and hopping stiffness did not differ significantly between ES and E. Significant group-by-training interactions were found in the maximal strength (P < 0.01) between ES and E during the training period; ES increased significantly the maximal strength (P < 0.05) as expressed by 1RM both on the half-squat and on the calf raise exercises, whereas the values of strength did not change in the E group. Significant group-by-training interactions were found in hop height (F = 8.83;P < 0.05; ES = 0.60) and hopping power (F = 5.14;P < 0.05; ES = 0.55) during the training period. ES maintained hop height unchanged, whereas E had a significant decrease (Table 4). Hopping power was significantly lower after than before the training period in E (2625 ± 631 W and 2963 ± 535 W, respectively;P < 0.05; ES = 0.58) but not in ES (3232 ± 412 W and 3410 ± 720 W, respectively) (Fig. 2C). Although hopping stiffness (in kN·m−1) and hopping power (in W) were significantly correlated at pre- (r = 0.58;P < 0.05) and post-training (r = 0.66;P < 0.01), no significant changes or differences were found in either the ES or E group in contact time or hopping stiffness, expressed in kN·m−1 or N·m−1·kg−1. A significant (r = −0.55;P < 0.05) correlation was observed between the change of CRΔ25% and the change of hopping power during the training period.
The present study shows that additional heavy-strength training yields a positive influence on the running economy of well-trained triathletes. During the training period, the change in running economy was moderately correlated to the change of hopping power. In addition, heavy-strength training did not alter the V̇O2 kinetics in heavy constant-rate exercise.
Change of running economy.
The results of the present study are in line with previous studies (13,14,23) that reported improvement of the economy after a combined strength+endurance training in endurance athletes, whereas no change in endurance-only athletes. Paavolainen et al. (23) showed that 5-km performance, running economy, and “muscle power” of well-trained athletes improved after 9 wk of explosive-strength training, whereas no changes were observed in a control endurance-training group. However, explosive-strength training leads to different muscular adaptations than typical HWT used in the present study. For example, a greater increase in the rate of activation of the motor units (17) has been described as one of the main mechanisms for improvement of neuromuscular characteristics related to improved (23) or unchanged (22) aerobic performance characteristics.
It is well established that long-term endurance training and maturation improve running economy in nontrained athletes or sedentary subjects (8). However, because well-trained endurance athletes have a narrow margin of improvement in aerobic capacity after several years of training (23), the lack of significant running economy improvement in the two groups is not surprising. The group-by-training interaction was observed in CR during the training period without any similar interaction between groups in V̇O2max or VT2. In parallel, similar group-by-training interactions were observed in maximal strength and hopping power. These results underline a specific effect of the heavy weight training and support the view that limiting factors of endurance performance in well-trained athletes may be more strongly related to local/peripheral than to central factors (10,20,23). The importance of the so-called “muscle power” defined as the neuromuscular system’s ability to produce power at the highest exercise intensity, when the muscle contractility may be limited, is therefore emphasized (23). Several factors can be proposed to explain the improvement of running economy after strength training.
For the same level of muscle tension, Type II motor units are recruited preferentially at lower cycle frequency, when the force required at each cycle is higher. If the stride frequency remains unchanged, the improvement of maximal strength relates to a lower relative peak tension at each cycle [e.g., from 50% to 35% of the maximal force (12)] and consequently to an increased contribution of slow-twitch fibers. In the present study, because no differences in SF were observed before or after training, one could argue that these adaptations happened in the ES group and therefore that the difference of running economy change between the two groups even with the reactualized VΔ25% was partly due to this factor.
By using the spring-mass model, significant relationships between maximal hopping power and maximal running velocity (r = 0.66;P < 0.05), average treadmill power (r = 0.70;P < 0.05), and hopping stiffness (r = 0.89;P < 0.001) have been reported in young sprinters (7). In the present study, a correlation was also found between hopping stiffness and hopping power before (P < 0.05) and after training (P < 0.01). During the training period, the E group maintained the same level of maximal strength but showed a significant decrease in the maximal hopping power and hop height, whereas the ES group increased the maximal strength and maintained hopping power unchanged. The correlation (r = 0.55;P < 0.5) between the change of running economy and the change of hopping power during the training period suggests that the E group’s decrease of muscular power may have affected its running economy.
However, no direct measures of power during the VΔ25% 3000 m were recorded. These results suggest that a large volume of endurance training can lead to a decrease of the neuromuscular characteristics, becoming therefore limiting factors of endurance efficiency, even in endurance athletes.
Alteration in the leg stiffness regulation and in the storage-recoil of energy with fatigue has been proposed as a cause of the decrease in the efficiency and in the economy of runners (15). A negative correlation between the stiffness of the dominant leg and CR has been reported (7). In the present study, no changes in contact time or vertical stiffness while hopping were observed. The type of strength performed during the training period (concentric contraction; > 90% 1RM) is associated with lower mean power frequency, shift of the EMG, or rate of neural input than explosive-strength training (concentric and plyometric contractions; 40–50% 1RM), mainly caused by a slower movement velocity (17,23). Therefore, the characteristics of the strength training performed in the present study may not have been optimal for improving the stiffness in a maximal stretch-shortening cycle exercise like hopping, even if it caused a significant increase in concentric strength and power. Nevertheless, estimated running leg stiffness was higher after training in ES than in E, meaning that some adaptations could have occurred.
Change of maximal strength.
The gains in maximal strength of the ES group (25% in the half-squats and 17% in the calf raise) were similar to the improvement showed in previous studies [i.e., 14.5% in ski ergometer test (13), 19.5% in leg press (16), 27% in parallel squats (11), and 33.8% in lower-body lifts (14)], whereas the E group exhibited no strength increase, as a result of the lack of strength training and the fact that they performed low-intensity (i.e., a low percentage of the maximal voluntary force) endurance training during the period studied. It is of interest to observe that the body weight did not change in either the ES or the E group, suggesting that little (if not at all) hypertrophy was caused by the strength training in ES. HWT contributes to strength gains mainly by two type of factors, primarily neural factors (increased activation, more efficient recruitment, motor unit synchronization, and excitability of the α-motor neurons or decreased Golgi tendon organ inhibition) in the early phase and hypertrophy on a longer term. However, after 2–6 wk, hypertrophy of Type IIa and IIb but also Type I muscle fibers were observed (26). Moreover, fast-twitch fibers type conversion (from IIb to IIa) was reported to occur as an effect of combined training (16,26). The decrease in the percentage of the Type IIb and the concomitant increase of the Type IIa fibers may lead to an increase of the oxidative capacity of the trained muscles. Moreover, Sale et al. (25) showed that the increase of the activity of the main oxidative enzymes (i.e., citrate synthase) and of the percentage of slow-twitch fibers in the muscles trained was similar in endurance-only and in combined endurance-strength groups. These results suggest that, even over a long period, the oxidative capacity of the lower-limb muscle are not affected by the inclusion of strength training into endurance training, supporting the concept of a possible “additive effect” of strength and endurance training. Combined training could also cause a “compromising effect” at the cellular level for both endurance and strength capabilities attenuating the adaptations (16). For example, Kraemer et al. (16) reported no changes in Type I and IIc fibers after a 12-wk combined training program, which may be related to an overtraining status as shown by the undesirable increase in cortisol.
Change in VV̇O2max.
The ES group had a 2.7% improvement in VV̇O2max, whereas the 2.2% change was not significant in the E group. However, because the interaction group × time was not significant, this difference cannot be attributed to the training difference between the two groups. For a statistical power of 0.8 and a difference in VV̇O2max of 0.49 ± 0.66 km·h−1, the size of the group E should have been of 17 subjects for reaching the significance level of α = 0.05. Moreover, in the present study, the correlation between change in VV̇O2max and change in CR with the two groups pooled was weak (r = −0.46;P = 0.09), indicating that changes in CR would not explain to a great extent change in running speed at V̇O2max.
Unchanged V̇O2 kinetics.
Most of the previous studies investigating the effects of training on the V̇O2 kinetics used a fixed time interval (6,28,29) and not a mathematical model (5). Bearden and Moffatt (2) showed that the use of a fixed interval led to an underestimation of the slow component. In the present study, a fixed 3- to 10-min interval would have resulted in a significantly different amplitude of the slow component than with the two-exponential component model. With the fixed interval, the amplitude was significantly (P < 0.05) underestimated (1.5 ± 1.5 vs 6.7 ± 4.3, 1.6 ± 2.6 vs 5.1 ± 3.7, 1.4 ± 3.0 vs 3.7 ± 3.3, 1.2 ± 1.7 vs 4.6 ± 3.7, respectively, for ES and E at pre- and post-training) when compared with the two-exponential model finally chosen.
Although the obvious interest to better understand whether additional strength training into an endurance training regime would cause different changes in the V̇O2 kinetics, to the best of our knowledge, only one study (29) has investigated the effect of strength training on the V̇O2 kinetics. In the present study, 14 wk of training did not change the V̇O2 kinetics neither in the ES nor in the E group. The results of the present study, showing no changes during the training period in either the E or the ES group in td1, τ1, A1, td2, τ2, or A2, are in line with the study of Womack et al. (29). One could assume that the muscular adaptations induced by the additional HWT were not pronounced enough to cause changes in the V̇O2 kinetics when compared with endurance training. However, in the two groups pooled, training did cause an improvement in the velocities (P < 0.01) without any change in the associated V̇O2max or VT2, meaning that most of the induced adaptations were located at the muscular level.
Acceleration of the V̇O2 adjustments at the onset of heavy exercise after endurance training was commonly reported in previous studies (21,24) but not in all (5). The present study did not confirm that in already well-trained athletes training induces faster constant time of the primary phase. Carter et al. (5) reported no effects of training on phase 2 during heavy exercise in healthy subjects (pretraining V̇O2max = 55 ± 2 mL·min−1·kg−1) but a significant decrease of the constant time of the phase 2 (τ2) in the lowest-fit subjects (V̇O2max = 40 ± 1 mL·min−1·kg−1). In the present study, the seven subjects with the lowest V̇O2max (= 64 ± 1 mL·min−1·kg−1) had a decrease of τ2 from 21 to 14 s that did not reach significance (P = 0.16).
Similarly, no changes were observed during the training period in either E or ES group in the amplitude of the slow component. These results seem in contrast with previous studies (5,6,10,28) which showed that 6–8 wk of endurance training led to a significant reduction of the amplitude of the slow component in healthy subjects. However, in several studies (6,28), exercise intensity was not recalculated, and because LT and V̇O2max may have been improved after training, the relative posttraining intensity may have changed, even below the recalculated VT2 (6). Because exercise intensity is one of the main factors influencing the amplitude of V̇O2, the results of these studies are difficult to interpret. Moreover, Carter et al. (5) showed a significant decrease of the amplitude of the slow component at the same absolute pre- and post-training velocities but not when the relative “new” posttraining intensity was used, which is in line with the present results. Indeed, in the two groups pooled, the increase of the absolute VΔ25% (P < 0.01) was not accompanied by an increase of the amplitude of the slow component. Gaesser and Poole (10) suggested that endurance training brings a change in the motor unit recruitment pattern, with less fast-twitch fibers recruited after training. Due to the 18% lower ADP/O ratio in Type IIb mitochondria, when compared when Type I (27), it would lead to a decrease of the amplitude of the slow component after training. Moreover, a correlation between the EMG activity (i.e., mean power frequency) and the rise of the V̇O2 during the slow component phase was reported (3), suggesting that the fast-twitch motor units are progressively recruited to offset the decreased power output caused by the fatigued motor units. It is of interest to note that the major part of the V̇O2 kinetics changes, if not all, occurred very early, in the first 2 wk, and that no further change were observed in the latest part of the training period (28).
To understand whether the type of training could cause muscular adaptations leading to a change of V̇O2 kinetics, further investigations are required with aerobically paired athletes performing more distinct types of training (i.e., heavy-strength-only vs endurance-only) training, which could lead to more pronounced biochemical and histological adaptations in the trained muscles.
In conclusion, the addition of HWT to the endurance training of well-trained triathletes was associated with significant increase in running performance (i.e., VV̇O2max) and an enhancement of running economy, probably determined by an improvement in lower-limb stiffness regulation, as a result of the concurrent strength and endurance training. This hypothesis must be tested more directly in further studies. An alternative mechanism could lie in the increase of the maximal lower-limb power. In contrast with previous studies conducted with recreational athletes, neither the endurance nor the endurance+strength training changed the V̇O2 kinetics between pre- and post-training during heavy exercise, where the relative intensities were kept identical. Because additional HWT led to improve maximal strength and running economy with no significant effects on the V̇O2 kinetics pattern in heavy constant-rate exercise, its inclusion in the training program of well-trained endurance athletes is recommended.
The authors thank D. Delignières at the University of Montpellier for statistical advice, D. J. Bentley, University of Bath, and R. Hunt, Hong-Kong Sport Institute, for their review of the manuscript.
Address for correspondence: Millet Grégoire, Faculté des Sciences du Sport, Université de Montpellier 1, 700 Av. Pic Saint Loup, 34090 Montpellier, France; E-mail: email@example.com.
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