It is well known that endurance athletes include various forms of high-intensity sessions as part of their training regimes to enhance competitive performance. In a recent review of the training literature, Paton and Hopkins (7) summarized the different types of interval and strength training used by athletes and studied by researchers. Surprisingly, there is little published research into the type of training that is most effective in enhancing performance with competitive cyclists. In particular, there are few studies comparing the efficacy of one interval-training method over another. In one of the few comparative studies, Stepto et al. (10) found that 6 sessions of long-duration submaximal intervals and short-duration supramaximal intervals gave similar improvements (approximately 3%) in 40-km cycling time trial performance with well-trained cyclists. Unfortunately, these authors included no physiologic measures, so it was not possible to attribute the performance improvements to changes in a specific physiologic mechanism. In a similar study, Laursen et al. (4) reported that 3 different interval-training routines produced substantial increases in speed of 4.3-5.6% in a 40-km cycle time trial after 8 training sessions; these training-induced changes in speed during the time trial were associated with changes in the athletes' peak oxygen uptake.
Most published studies examine the effectiveness of 1 type of high-intensity training regime in isolation or when added to an ongoing endurance program. Lindsay et al. (6) had cyclists complete sessions consisting of 6 to 8 repetitions of 5 minutes at 80% of their peak aerobic power. After 6 sessions, cyclists improved mean power in a 40-km time trial by 8.3% (or approximately 3.5% in speed); the improved performance was associated with a 4.3% increase in peak aerobic power and a 3% increase in fractional utilization of peak power. In a further study, Laursen et al. (5) reported increases of 4.7% in peak and ventilatory-threshold power of trained cyclists after completing just 4 high-intensity interval sessions.
Although it is apparent that relatively few training sessions can lead to substantial gains in performance, none of the previous studies have reported or examined the effects of performing the training intervals at different pedal cadences. Competitive cyclists are well known to vary their training cadence in the belief that this may facilitate a more optimal training response. For example, training at lower cadences on climbs is often performed in the belief that this may improve a cyclist's strength (personal observation). In the only study to examine the effects of training at lower than normal cadences, 12 sessions of a high-resistance interval-training regime produced substantial gains in sprint performance (∼8%) and several measures associated with endurance performance (4-7%) when added to the usual training of cyclists in their competitive phase (7) compared with a control group.
Although several studies conclude that high-intensity cycle interval training is likely to be beneficial for performance, no one has investigated how changes in training cadence and therefore force development affect performance gains when cyclists perform the same type of training but at different cadences. Therefore, in the present study, we have evaluated the effects of varying the cadence during training on performance and physiologic measures associated with endurance performance with well-trained competitive cyclists.
Experimental Approach to the Problem
The study was a controlled trial in which match-paired subjects were assigned to either a high-cadence or a low-cadence training group on the basis of peak power output achieved in a pretraining incremental exercise test. Subjects completed a set of exercise tests for evaluation of physiologic measures associated with endurance performance in the week before and after a 4-week training period.
Eighteen male cyclists with a minimum of 3 years competitive experience volunteered for this study. The study was performed in the main competitive phase of the year, during which all cyclists were competing in endurance (>60 min) road or mountain-bike races at least once per week throughout the study. During the period of the study, the cyclists spent approximately 10 to 15 h.wk−1 training and competing. None of the cyclists had participated in any gym-based strength training in the 3 months before the beginning of the study. The characteristics and baseline exercise performance of the cyclists are shown in Table 1. All cyclists were informed of the purpose and risks associated with participation before giving their written informed consent. The study was approved by the Waikato Institute of Technology ethics committee.
All cyclists had previously participated in laboratory cycle-ergometer testing and were familiar with general exercise testing procedures. Cyclists were instructed to refrain from hard physical activity for 24 hours and from eating for 3 hours before the exercise trials. All tests and experimental training sessions were performed in a controlled laboratory environment (20° C and 50-60% relative humidity).
Exercise tests were performed on similarly equipped and individually sized road racing bicycles (Giant, Taiwan) fitted with SRMpro power measuring cranksets (Schoberer-Rad-Messtechnik, Konigskamp, Germany). Bicycles were mounted on a wind-braked ergometer (Kingcycle Mk3, Kingcycle, High Wycombe, United Kingdom), which was calibrated in accordance with the manufacturer's recommended procedures. The Kingcycle provided the means to control the experimental loading; however, power data were recorded directly from the SRM cranks at 2-second intervals.
Cyclists initially performed a 10-minute warm-up at a self-selected intensity followed by 5 minutes at a fixed power of 100 W. Thereafter, power output was increased continuously at a rate of 33 W.min−1 until the cyclist reached volitional exhaustion. Finger-tip capillary blood was sampled initially at 150 W and thereafter at 100 W increments; whole blood lactate was assayed immediately using an automated analyzer (YSI 1500 Sport, Yellow Springs, OH, USA). During the test, oxygen uptake was measured continuously with a calibrated metabolic cart (Vmax29, SensorMedics, Yorba, CA, USA). Maximum oxygen consumption (O2max) was defined as the highest O2 measured over a 30-second period during the test. Peak power output was defined as the highest 60-second mean power output recorded on the SRM crankset during the test.
Several other measures associated with endurance performance were derived from the maximal incremental test. For each cyclist, the power output corresponding to a fixed blood lactate concentration of 4 mM was calculated from log-log plots, as previously described (6). In addition, we determined the fractional (percentage) utilization of peak power corresponding to the power at 4 mM. Finally, we derived surrogate measures of economy by determining the oxygen cost of exercise at 2 fixed work intensities corresponding to 50% and 80% of each individual's peak power output.
Twenty minutes after completing the incremental power test, cyclists performed a maximal effort 60-second time trial to determine mean power output. The test began with a 2-minute countdown during which the cyclists were required to maintain a constant power output of 50 W. Thereafter, cyclists completed the time trial at as high a power as possible. The only information available to the cyclists during the time trial was time remaining.
Before the study, all cyclists had completed several months of precompetition training; in the weeks immediately prior, the cyclists were implementing traditional interval sessions in their training programs under the direction of their individual coaches. Subjects were informed that there was no demonstrated advantage of either experimental training and the study was simply comparing the 2 types of training. Both training groups continued with their usual competition program but replaced part of their usual training with 8 30-minute sessions in a controlled laboratory environment under the supervision of one of the researchers. Cyclists were required to schedule their experimental training sessions for a similar time on each occasion to control for diurnal variation and to complete only light training in the 24 hours preceding an experimental training session. Cyclists were requested to maintain their normal diet for the duration of the study and not to use potentially performance-enhancing aids (caffeine, creatine, etc.) before the experimental training sessions. In addition, cyclists were asked to present in a euhydrated state and to eat a preferred light carbohydrate meal/snack 2 hours before each training session. Throughout the training sessions, cyclists were cooled with standing floor fans and permitted water as desired.
The training sessions were preceded and followed by a 10-minute warm-up and cool-down at a self-selected intensity. Training sessions were performed twice per week, with a minimum of 48 hours between sessions and consisted of 3 sets of maximal effort single-leg jumps alternating with 3 sets of maximal intensity cycling efforts, as previously described (7). The jump phase of the training required subjects to perform 20 explosive step-ups off of a 40-cm box. The jump efforts were completed for the right and then left legs consecutively over a 2-minute period. The cycling phase required the cyclist to complete 5 × 30-second maximal intensity cycling efforts at a cadence of either 60 to 70 min−1 or 110 to 120 min−1 with 30-second recovery between repetitions. A transition period of 2 minutes separated each cycle and jump set. The training sets were performed on the same bicycles used for testing, mounted to magnetically braked cycle ergometers (Elite Volare, Lomagna, Italy). Cyclists could rapidly adjust the resistance of the ergometer to maintain the appropriate cadence range by way of a handlebar-mounted friction lever. The SRM cranksets were set to record power during the training session every 2 seconds.
Saliva samples were collected immediately before and after each training session to assay testosterone concentration. Saliva samples (approximately 5 mL) were collected by passive drool into a 10 mL graduated centrifuge tube. Samples were subsequently stored at −20°C until assay. Samples were analyzed in duplicate for free testosterone concentration using enzyme-linked immunosorbent assay methods under the manufacturer's instructions (salivary testosterone immunoassay kit, Salimetrics, State College, PA, USA). Assay plates were read using a plate reader (Organon Teknika 230 S, Durham, NC, USA).
Simple group statistics are shown as means ± between-subject SDs. Mean effects of training and their 90% confidence limits were estimated with a spreadsheet (2) by way of the unequal-variances t statistic computed for change scores between pre- and post-tests in the 2 groups. Each subject's change score was expressed as a percent of baseline score by way of analysis of log-transformed values to reduce bias arising from nonuniformity of error. Individual responses expressed as coefficients of variation were estimated with the spreadsheet. The spreadsheet also computes chances that the true effects are substantial when a value for the smallest worthwhile change is entered. We used a value of 1% for the performance measures because this represents the smallest worthwhile enhancement for cyclists competing in track and time-trial events (9). We also assumed 1% was the smallest worthwhile change in the physiologic measures associated with endurance performance because a 1% change in these measures would produce a 1% change in performance. We do not know how a change in body mass or testosterone concentration would affect cycling performance, so we chose 0.20 standardized units (change in mean divided by the between subject SD in the pretest) as the smallest worthwhile change (1). For each effect, we have shown the qualitative assessment of the chances of benefit when the chances of benefit were greater than 5% and the chances of harm less than 5%. Effects for which chances of benefit and harm were greater than 5% were interpreted as unclear.
Mechanisms of the effects of training on performance were investigated by plotting changes in performance against change scores of potential mediators and calculating corresponding correlations. The measures of performance were 60-second mean power, peak incremental power, and power at 4-mM lactate; the potential mediators were testosterone in the training sessions averaged over all 8 sessions, changes in power output in the training sessions between sessions 1 and 8, and the changes in physiologic measures associated with endurance performance (O2max, fractional utilization, exercise economy). The correlations between changes in the measures of performance themselves were also calculated. Confidence limits for correlations were derived by way of the Fisher z transformation using an Excel spreadsheet (available at newstats.org/xcl).
The effects of the training sessions on salivary testosterone concentration and the mean power in the training sessions are shown in Figure 1. The change in testosterone concentration averaged over all sessions for each subject was 97% ± 39% (mean ± between-subject SD) in the low-cadence group and 62% ± 23% in the high-cadence group. The factor difference of 1.22% or 22% (90% confidence limits, 6-40%) represents a moderate effect. Power output in the interval sets over the training period (session 1-8) increased by 11.0% ± 5.4% (mean ± SD) in the low-cadence group and by 8.3% ± 2.1% in the high-cadence group.
The mean changes in performance and in physiologic measures showed either unclear or beneficial effects of low-cadence in comparison with high-cadence training (Table 2). The greatest effects and greatest difference between the groups occurred with power at 4-mM lactate. However, changes in this variable had trivial or small correlations (<0.30, 90% confidence limits approximately ±0.60) with changes in 60-second power and changes in peak incremental power in each group, whereas the correlations between the latter 2 variables were moderate or large (0.46 and 0.78 in the slow- and fast-cadence groups, respectively).
Standard deviations of the change scores in each group for all measures in Table 2 indicate relatively greater variation in the response to high-cadence training in this sample; the derived SDs representing individual responses were approximately 2-5%, but there was too much uncertainty in these estimates (90% confidence limits approximately ±6%) to permit any clear conclusion about relative variation. Plots and correlations of change scores of performance vs. change scores of mean testosterone or change scores of training mean power also failed to reveal any clear relationships (data not shown); the correlations in each training group were all less than 0.40 in magnitude with uncertainty approximately ±0.6 (90% confidence limits). There was more evidence of positive relationships between changes in peak incremental power and changes in physiologic measures of associated with endurance, but the highest correlations were still only approximately 0.5 and unclear.
The main aim of this study was to compare the effects on measures associated with endurance performance cycling when part of normal competitive-season training was replaced with sessions of high-intensity resistance training in which the resistance of the cycling intervals was set to produce a cadence either similar to or approximately half that of high-intensity efforts in races. The gains in performance with low-cadence training (6-11%) were similar to those in a previous study using the same kind of training (8), but the gains with high-cadence training were smaller (2-3%). The likelihood of greater benefit with low-cadence training was greatest for power at 4-mM lactate, but in our opinion, there should have been higher correlations between changes in this variable and changes in 60-second mean and peak incremental power. We are therefore skeptical about the validity of changes in power at 4-mM lactate as a measure of performance change. On the basis of the effects with 60-second and peak incremental power, it is likely that the low-cadence training is superior to high-cadence training.
The gains were achieved with only 8 training sessions over a 4-week period, and the time course of adaptation in the sessions (Figure 1) does not show any obvious plateau for either type of training. If we assume that gains in performance in the training sets translate into gains in the exercise tests, there would probably be additional benefit from more sessions over a longer period. We doubt whether the gap between the effects of the 2 types of training would close with additional training.
One difference between the 2 types of training, as obvious in Figure 1, is the greater mean power achieved with the lower cadence. The resulting difference in training load as a fraction of total training appears unlikely to be sufficient to explain the difference in gains in the 2 groups. We suspect that some other adaptation resulting directly or indirectly from the higher forces in the muscle was responsible. Substantial differences in the mean changes in testosterone concentration in the training sessions are consistent with a role for testosterone. Indeed, testosterone as a key anabolic hormone has been strongly associated with strength gains in numerous training studies (3). It is possible that the larger testosterone concentration, in response to the higher forces developed during low-cadence training, leads to more favorable strength adaptations and therefore performance. Stronger evidence for such a role would have been provided by a positive correlation between individual differences in performance and testosterone changes, but these correlations had unclear magnitudes. The magnitude of the correlation observed between change scores depends on the true underlying correlation and on the relative magnitudes of true individual responses and errors of measurement. If the true correlation was 1.00, and the errors of measurement were equal in magnitude to the individual responses, it is easy to show from first principles that the expected value of the observed correlation would be only 0.33. The sample size in the present study was not adequate to make confident conclusions about correlations of this magnitude.
Errors of measurement in the physiologic measures relative to individual responses in those measures were presumably also responsible for the lack of any clear correlation between changes in these measures and changes in peak power and 60-second mean power. The changes in the means of the physiologic measures were consistent with a change in O2max being the main physiologic component of the change in performance. Improvement in exercise economy at 50% of peak power was also clearly higher in the low-cadence group after training, but the difference between the groups was unclear at the higher intensity more typical of a competitive event. Other researchers have argued that changes in economy contribute to changes in endurance performance after resistance training (6,8). On the basis of the uncertainty in the estimates of mean change in this study, any of the physiologic measures could have been the main or only contributor to the changes in performance. More research is needed to resolve this issue.
The results of the present investigation show that training at a low cadence produces greater gains in tests related to cycling endurance performance than training at a similar intensity at high cadence with well-trained competitive cyclists. The larger effects of low-cadence training may be related to the higher pedal forces produced and appear to be associated with increases in testosterone and possibly to improvements in maximum oxygen uptake. Our findings will presumably translate into practical benefit for cyclists taking part in real-life competitions.
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