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EFFECTS OF LOW-VS.HIGH-CADENCE INTERVAL
TRAINING ON CYCLING PERFORMANCE
CARL D. PATON,
1,2
WILL G. HOPKINS,
2
AND CHRISTIAN COOK
3
1
Health and Sport Science, Eastern Institute of Technology, Napier, New Zealand;
2
Institute of Sport and Recreation Research,
AUT University, Auckland, New Zealand; and
3
Human Performance Group, HortResearch, Hamilton, New Zealand
ABSTRACT
Paton, CD, Hopkins, WG, and Cook, C. Effects of low- vs. high-
cadence interval training on cycling performance. J Strength
Cond Res 23(6): 1758–1763, 2009—High-resistance interval
training produces substantial gains in sprint and endurance
performance of cyclists in the competitive phase of a season.
Here, we report the effect of changing the cadence of the
intervals. We randomized 18 road cyclists to 2 groups for
4 weeks of training. Both groups replaced part of their usual
training with 8 30-minute sessions consisting of sets of
explosive single-leg jumps alternating with sets of high-intensity
cycling sprints performed at either low cadence (60–70 min
21
)
or high cadence (110–120 min
21
) on a training ergometer.
Testosterone concentration was assayed in saliva samples
collected before and after each session. Cycle ergometry before
and after the intervention provided measures of performance
(mean power in a 60-s time trial, incremental peak power, 4-mM
lactate power) and physiologic indices of endurance perfor-
mance (maximum oxygen uptake, exercise economy, fractional
utilization of maximum oxygen uptake). Testosterone concen-
tration in each session increased by 97% 639% (mean 6
between-subject SD) in the low-cadence group but by only
62% 623% in the high-cadence group. Performance in the
low-cadence group improved more than in the high-cadence
group, with mean differences of 2.5% (90% confidence limits,
64.8%) for 60-second mean power, 3.6% (63.7%) for peak
power, and 7.0% (65.9%) for 4-mM lactate power. Maximum
oxygen uptake showed a corresponding mean difference of
3.2% (64.2%), but differences for other physiologic indices
were unclear. Correlations between changes in performance
and physiology were also unclear. Low-cadence interval
training is probably more effective than high-cadence training
in improving performance of well-trained competitive cyclists.
The effects on performance may be related to training-
associated effects on testosterone and to effects on maximum
oxygen uptake.
KEY WORDS athlete, economy, endurance, lactate threshold,
peak power
INTRODUCTION
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. Unfortu-
nately, 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 ses-
sions, 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
Research conducted at the Waikato Institute of Technology, Hamilton,
New Zealand.
Address correspondence to Dr. Carl D. Paton, CPaton@eit.ac.nz.
23(6)/1758–1763
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Ó2009 National Strength and Conditioning Association
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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 per-
formance (4-7%) when added to the usual training of cyclists
in their competitivephase (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 per-
formance and physiologic measures associated with endur-
ance performance with well-trained competitive cyclists.
METHODS
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.
Subjects
Eighteen male cyclists with a minimum of 3 years com-
petitive 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
21
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 per-
formance 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.
Exercise Tests
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 environ-
ment (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 recom-
mended 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
21
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 (
_
VO
2
max) was
defined as the highest
_
VO
2
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 perfor-
mance 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 cor-
responding 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.
Training
Before the study, all cyclists had completed several months of
precompetition training; in the weeks immediately prior, the
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cyclists were implementing traditional interval sessions in
their training programs under the direction of their individual
coaches. Subjects were informed that there was no demon-
strated 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 5 330-second maximal
intensity cycling efforts at a cadence of either 60 to 70 min
21
or 110 to 120 min
21
with 30-second recovery between repeti-
tions. 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
TABLE 1. Characteristics and baseline measures of
performance of cyclists in low- and high-cadence
training groups.
Low
cadence
(n=9)
High
cadence
(n=9)
Age (yr) 26.8 67.4 24.9 66.2
Body mass (kg) 81.1 67.7 81.2 65.5
Resting testosterone
concentration
(pgmL
21
)
312 661 302 652
60-s mean power (W) 553 668 565 663
Peak incremental
power (W)
389 629 386 663
Power at 4-mM
lactate (W)
304 660 303 634
Maximum oxygen
uptake (Lmin
21
)
4.35 60.34 4.56 60.64
Fractional utilization†
at 4-mM lactate (%)
78 667968
_
VO
2
at 80% peak
power (Lmin
21
)
3.93 60.36 4.18 60.74
_
VO
2
at 50% peak
power (Lmin
21
)
2.78 60.20 2.91 60.49
*Data are mean 6between subject SD.
†4-mM power as percent of peak power.
Figure 1. Change in salivary testosterone concentration across each
training session and mean power in training session for low-cadence and
high-cadence training groups.
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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 220°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 immu-
noassay kit, Salimetrics, State College, PA, USA). Assay plates
were read using a plate reader (Organon Teknika 230 S,
Durham, NC, USA).
Statistical Analyses
Simple group statistics are shown as means 6between-
subject SDs. Mean effects of training and their 90%
confidence limits were estimated with a spreadsheet (2) by
way of the unequal-variances tstatistic 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 corre-
sponding 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 (
_
VO
2
max, fractional utilization,
exercise economy). The correlations between changes in
the measures of performance themselves were also calcu-
lated. Confidence limits for correlations were derived by way
of the Fisher ztransformation using an Excel spreadsheet
(available at newstats.org/xcl).
RESULTS
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% 639%
(mean 6between-subject SD) in the low-cadence group and
62% 623% 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% 65.4%
(mean 6SD) in the low-cadence group and by 8.3% 62.1%
in the high-cadence group.
TABLE 2. Changes in performance and physiologic measures in low- and high-cadence training groups and qualitative
inferences about effects on performance of low- in comparison with high-cadence training.
Change in measure (%)
Qualitative inference
Low cadence,
mean 6SD
High cadence,
mean 6SD
Low-high difference,
690% confidence limit
60-s mean power 5.6 65.3 3.0 66.4 2.5 64.8 Unclear
Peak incremental power 6.0 64.0 2.3 65.0 3.6 63.7 Likely beneficial
Power at 4-mM lactate 10.6 68.0 3.3 66.2 7.0 65.9 Very likely beneficial
Maximum oxygen uptake 4.5 63.9 1.1 65.6 3.3 64.1 Likely beneficial
Fractional utilization at 4-mM lactate 0.7 64.8 20.2 66.7 0.9 64.9 Unclear
Exercise economy at 80% peak power 2.2 64.3 2.0 65.6 0.2 64.1 Unclear
Exercise economy at 50% peak power 4.1 63.1 21.1 67.7 5.1 64.9 Likely beneficial
Body mass 21.3 61.4 20.6 62.0 20.7 61.4 Likely trivial
*690% confidence limit: add and subtract this number to mean effect to obtain the 90% confidence limits for true difference.
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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 60.60) with
changes in 60-second power and changes in peak in-
cremental 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 approx-
imately 2–5%, but there was too much uncertainty in these
estimates (90% confidence limits approximately 66%) 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
60.6 (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.
DISCUSSION
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 in-
cremental 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
_
VO
2
max 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.
PRACTICAL APPLICATIONS
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
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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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