ORIGINAL RESEARCH
Heavy strength training improves running and cycling
performance following prolonged submaximal work in
well-trained female athletes
Olav Vikmoen1, Bent R. Rønnestad1, Stian Ellefsen1 & Truls Raastad2
1 Section for Sport Sciences, Lillehammer University College, Lillehammer, Norway
2 Deparment of Physical Performance, Norwegian School of Sport Sciences, Oslo, Norway
Keywords
Concurrent training, cycling economy,
prolonged cycling, prolonged running,
running economy.
Correspondence
Olav Vikmoen; Norwegian Defence Research
Establishment (FFI), PO Box 26 N-2027
Kjeller, Norway.
Tel: +47 63807825
Fax: +47 63807892
Email: olav.vikmoen@fﬁ.no
Funding information
This work was supported by grant 203961
from the Regional Science Fund - Innlandet
of Norway.
Received: 10 January 2017; Accepted: 11
January 2017
doi: 10.14814/phy2.13149
Physiol Rep, 5 (5), 2017, e13149,
doi: 10.14814/phy2.13149
Abstract
The purpose of this study was to investigate the effects of adding heavy
strength training to female duathletes’ normal endurance training on both
cycling and running performance. Nineteen well-trained female duathletes
(VO2max
cycling:
54  3 ml∙kg1∙min1,
VO2max
running:
53  3 ml∙kg1∙min1) were randomly assigned to either normal endurance
training (E, n = 8) or normal endurance training combined with strength
training (E+S, n = 11). The strength training consisted of four lower body
exercises [3 9 4-10 repetition maximum (RM)] twice a week for 11 weeks.
Running and cycling performance were assessed using 5-min all-out tests, per-
formed immediately after prolonged periods of submaximal work (3 h cycling
or 1.5 h running). E+S increased 1RM in half squat (45  22%) and lean
mass in the legs (3.1  4.0%) more than E. Performance during the 5-min
all-out test increased in both cycling (7.0  4.5%) and running (4.7  6.0%)
in E+S, whereas no changes occurred in E. The changes in running perfor-
mance were different between groups. E+S reduced oxygen consumption and
heart rate during the ﬁnal 2 h of prolonged cycling, whereas no changes
occurred in E. No changes occurred during the prolonged running in any
group. Adding strength training to normal endurance training in well-trained
female duathletes improved both running and cycling performance when
tested immediately after prolonged submaximal work.
Introduction
During the last decade, increased attention has been given
to the effects of adding strength training to endurance
athletes’ normal training on running and cycling perfor-
mance (e.g., Paavolainen et al. 1999; Aagaard et al. 2011;
Ronnestad et al. 2011; Sedano et al. 2013). Improvements
in performance have been reported in both running (Paa-
volainen et al. 1999; Storen et al. 2008; Sedano et al.
2013; Damasceno et al. 2015) and cycling (Koninckx
et al. 2010; Ronnestad et al. 2010a; Aagaard et al. 2011;
Ronnestad et al. 2015). However, the literature is far from
conclusive, and numerous studies do not report such
improvements in neither running (Ferrauti et al. 2010;
Roschel et al. 2015) nor cycling (Bishop et al. 1999; Basti-
aans et al. 2001; Levin et al. 2009). Some methodological
differences may explain these equivocal ﬁndings. To posi-
tively
affect
cycling
performance,
it
seems
that
the
strength training regime needs to involve heavy loads,
typically between 10 and 4 repetition maximum (RM)
(Koninckx et al. 2010; Ronnestad et al. 2010a; Aagaard
et al. 2011; Ronnestad et al. 2015). To improve running
performance on the other hand, both explosive, plyomet-
ric and heavy strength training seems effective (Paavolai-
nen et al. 1999; Sedano et al. 2013; Damasceno et al.
2015). To the best of our knowledge, only one study has
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The Physiological Society and the American Physiological Society.
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2017 | Vol. 5 | Iss. 5 | e13149
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Physiological Reports ISSN 2051-817X
investigated the effect of strength training on performance
in both cycling and running in the same athletes. This
study reported increased time to exhaustion at VO2max in
both cycling and running (Hickson et al. 1988). However,
the study did not include an endurance training only
group, and therefore the results should be interpreted
with caution.
The observation that somewhat different strength train-
ing regimes affect performance in cycling and running
indicates that some of the performance-enhancing mecha-
nisms may differ between these sports. Suggested mecha-
nisms by which strength training can improve cycling and
running performance include changes in rate of force
development, changes in tendon stiffness, changes in
movement mechanics, and changes in muscular character-
istics such as increased muscle strength, muscle mass, and
improved
anaerobic
capacity
(Saunders
et al.
2006;
Ronnestad and Mujika 2014). Some of these factors may
be important for performance in both running and
cycling, whereas other mechanisms may affect perfor-
mance differently in these sports. For example, in run-
ning, the stretch-shortening cycle in each stride enables
the possibility to store and recoil elastic energy, whereas
in cycling, the possibilities to take advantage of stored
elastic energy is negligible. Consequently, a factor such as
muscle-tendon stiffness may play a role for running per-
formance, but likely not for cycling performance. On the
other hand, a factor like improved anaerobic capacity
should affect performance to the same degree in both
running and cycling.
Road races in cycling often consist of a long initial
period of cycling at a moderate intensity, followed by an
all-out performance at the end. Even though running
competitions are ran at a more even pace, they are also
often decided with an all-out effort in the end. During
such efforts, a quite large proportion of the energy
demand will come from anaerobic sources (Gastin 2001).
Therefore, performance during a relatively short test will
in addition to VO2max and other aerobic parameters also
be largely inﬂuenced by anaerobic capacity. Muscle mass is
an important determinant of anaerobic capacity (Bangsbo
et al. 1993). We have previously reported increased CSA of
m. quadriceps femoris after 11 weeks of heavy strength
training
in
female
endurance
athletes
together
with
increased mean and peak power during the Wingate test
(Vikmoen et al. 2016a). This indicates improved anaerobic
capacity in the same athletes included in this study. There-
fore, performance in a quite short performance test should
be positively affected by this strength training regime. In
addition to increased muscle CSA, changes in protein levels
and expression of genes coding for proteins that are
involved in the anaerobic metabolism might contribute to
increased anaerobic performance.
Performance in an all-out effort at the end of long
competitions should also be affected by the fatigue devel-
oped during the competition. In Ronnestad et al. (2011),
such performance was simulated by 3 h of submaximal
cycling followed by a 5-min all-out test. Power output
during the 5-min all-out test was improved following
12 weeks of heavy strength training in well-trained male
cyclists. This was related to improved cycling economy
and reduced physiological strain during the ﬁnal hour of
the submaximal trial, leaving the strength-trained athletes
less fatigued before the 5-min all-out test (Ronnestad
et al. 2011). However, no previous study has assessed
effects of heavy strength training on all-out performance
following a prolonged submaximal work or physiological
responses during prolonged submaximal running.
The primary purpose of this study was to investigate
the effects of 11 weeks of heavy strength training on
5-min all-out performance after separate trials of pro-
longed submaximal work in both running and cycling
and on physiological responses during the prolonged
work. We especially wanted to identify performance-
enhancing mechanisms after strength training which acts
similarly and differently on cycling and running perfor-
mance.
We hypothesized that the addition of heavy strength
training would result in improved 5-min all-out perfor-
mance in both cycling and running. Furthermore, we
hypothesized that changes in 5-min all-out performance
would be related to improved work economy during the
prolonged trials and to changes related to anaerobic
capacity such as increased muscle mass and changes in
expression of genes that are involved in anaerobic pro-
cesses. We also anticipated that some of the underlying
mechanisms for improved work economy would differ
between running and cycling.
Methods
Ethical approval
The study was approved by the Local Ethics Committee
at Lillehammer University College. Written informed con-
sent was obtained from all athletes prior to inclusion, and
the study was carried out in accordance with the Declara-
tion of Helsinki.
Participants
Twenty-eight female duathletes who fulﬁlled at least two
of Jeukendrup et al. (2000) training and race status
descriptions of a well-trained athlete were recruited to
this study. None of the athletes had performed systematic
strength training for the last 12 months leading up to the
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Strength Training and Endurance Performance
O. Vikmoen et al.
study. The athletes were matched on VO2max and ran-
domly assigned to either adding heavy strength training
to the ongoing endurance training (E + S, n = 14) or
endurance training only (E, n = 14). During the study,
three athletes in E + S left the project for reasons unre-
lated to the project protocol: one because of an injury,
one because of a prolonged period of illness during the
last part of the intervention and one because of other
medical reasons. In E, six athletes left the study for rea-
sons unrelated to the project protocol (injuries from bicy-
cle crash, pregnancy, and lack of time). Therefore, the
ﬁnal numbers of athletes in E + S and E were 11 and 8,
respectively.
Experimental overview
This study is part of a larger study investigating the effects
of heavy strength training on various aspects of cycling and
running performance. The effect on time-trial performance
and traditional performance determinants in cycling and
running has been previously reported (Vikmoen et al.
2016a,b). Whenever data from these studies are utilized for
correlation purposes or otherwise, it will be clearly speci-
ﬁed. The strength training program for the E+S group con-
sisted of two strength training sessions per week and lasted
for 11 weeks (during the competition period from April to
July). The testing before and after the intervention period
was organized in ﬁve test days. During pretests, test day 1
consisted of biopsy sampling from m. vastus lateralis for
determination of muscle ﬁber type composition and
mRNA expression of genes related to fat and anaerobic
metabolism. Test day 2 consisted of a VO2max test in
cycling followed by 1RM test in half squat. Test day 3 con-
sisted of a VO2max test in running. Test day 4 consisted of a
prolonged submaximal running trial followed by a 5-min
all-out test. Test day 5 consisted of a prolonged submaxi-
mal cycle trial followed by a 5-min all-out test. There were
at least 7 days between day 1 and 2 and 3–7 days between
the remaining test days. After the intervention period, the
only difference in test order was that muscle biopsies were
taken on the last test day.
Training
Endurance training duration and intensity were calculated
based on heart rate (HR) recordings. Endurance training
was divided into three HR zones: (1) 60%–82%, (2)
83%–87%, and (3) 88%–100% of maximal HR. For
detailed information on endurance training characteris-
tics, see Vikmoen et al. (2016a). Brieﬂy, there were no
signiﬁcant differences between groups in their average
weekly
endurance
training
duration
or
distribution
between intensity zones.
The heavy strength training for the E + S groups tar-
geted leg muscles and were performed twice per week
during the 11-week intervention period. Adherence to the
strength training was high, with E + S athletes completing
21.4  1.0 (range 19–22) of the planned 22 strength
training sessions. The strength training program was per-
formed as reported in Vikmoen et al. (2016a). Brieﬂy,
each strength training session consisted of four leg exer-
cises: half squat in a smith machine, leg press with one
leg at a time, standing one-legged hip ﬂexion, and ankle
plantar ﬂexion. Three sets were performed per exercise.
An investigator supervised the athletes at all workouts
during the ﬁrst 2 weeks and at least one workout per
week thereafter. During weeks 1–3, athletes trained with
10RM sets at the ﬁrst session and 6RM sets at the second
session. These alternating loads were adjusted to 8RM
and 5RM during weeks 4–6, and was further adjusted to
6RM and 4RM during weeks 7–11. The athletes were
encouraged
to
increase
their
RM
loads
continually
throughout the intervention period and they were allowed
assistance on the last repetition.
Physical performance tests
The athletes were instructed to refrain from intense exer-
cise the day preceding testing and to prepare for the tests
as they would have done for a competition. This included
consuming the same type of meal at the same time as
they would do if the test was a regular competition. Fur-
thermore, the participants were instructed to replicate the
preparation before every test. All cycling tests were per-
formed on a electromagnetically braked cycle ergometer
(Lode Excalibur Sport, Lode B. V., Groningen, The
Netherlands), which was adjusted according to each ath-
lete
preference
for
seat
height,
horizontal
distance
between tip of seat and bottom bracket, and handlebar
position. During all cycling tests the ergometer was in a
cadence-independent mode (constant watt-production);
so, the power output was not affected by the cyclists‘ cho-
sen cadence. The running tests were performed on a
motor-driven treadmill (Woodway Desmo Evo, Wauke-
sha, WI). The inclination of the treadmill was set to 5.3%
at all tests. All testing were performed under similar envi-
ronmental conditions (18–20°C).
VO2max in cycling
The cycling VO2max test protocol utilized in this study
and its results has been described elsewhere (Vikmoen
et al. 2016a). Brieﬂy, the test was initiated with 1-min
cycling at a power output of 100 W that was subsequently
increased by 25 W every minute until exhaustion. VO2
was
measured
(30-sec
sampling
time)
using
a
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
2017 | Vol. 5 | Iss. 5 | e13149
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O. Vikmoen et al.
Strength Training and Endurance Performance
computerized metabolic system with mixing chamber
(Oxycon Pro, Erich Jaeger, Hoechberg, Germany). The
gas analyzers were calibrated with certiﬁed calibration
gases of known concentrations before every test. The ﬂow
turbine (Triple V, Erich Jaeger, Hoechberg, Germany)
was calibrated before every test with a 3 l, 5530 series,
calibration syringe (Hans Rudolph, Kansas City, USA).
VO2max was calculated as the average of the two highest
30 sec VO2 measurements. Peak cycling performance dur-
ing the test (Wmax) was calculated as the mean power
output during the last 2 min of the incremental test. After
the test, blood [la] and HRpeak was noted. [La] were
analyzed in whole blood with a Lactate Pro LT-1710
analyzer (Arcray Inc., Kyoto, Japan). RPE was recorded
using the Borg scale (Borg, 1982). HR was measured
using a Polar S610i heart rate monitor (Polar, Kempele,
Finland).
Prolonged submaximal cycling followed by a
5-min all-out cycling test
The prolonged cycling lasted for 180 min on a power
output corresponding to 44% of Wmax (111  9 W and
116  8 W in E + S and E, respectively). The same abso-
lute power output was utilized post intervention. VO2
and HR were determined during 3-min periods every
30th min throughout the prolonged cycling and RPE and
[la] were measured every 30th min. Average values for
each hour were calculated and used for statistical analyses.
Athletes were allowed to occasionally stand in the pedals
during the prolonged cycling, but not during the 3-min
periods of measurements and not during the ﬁnal 5-min
all-out test. Athletes were allowed to consume water and
a sport drink containing 60 g/L carbohydrates, ad libitum,
in order to maintain ﬂuid balance and mimic race condi-
tions. The amount of sport drink consumed were similar
between groups and from pre to post (across groups, val-
ues were 1.24  0.57 L and 1.26  0.59 L, respectively).
After conclusion of the prolonged cycling, athletes were
allowed a 3-min rest before a 5-min all-out test for deter-
mination of cycling performance. During the ﬁrst minute
of the test, the power output was set by the investigators.
This individual selected power output was based on pilot
work and corresponded to 85% of Wmax. Thereafter, the
control unit for the power output was put next to
the ergometer and the athletes were allowed to adjust the
power output themselves with the instruction to cycle at
the highest average power output as possible. The partici-
pant received feedback regarding power output and
elapsed time, but not HR or cadence. Performance was
measured as the mean power output during the 5-min
all-out test. At the posttest, one athlete in E + S had to
withdraw during the prolonged test due to pain in the
hip. Therefore, the ﬁnal numbers included in the statisti-
cal analysis of these tests are 10 in E + S and 8 in E.
VO2max in running
The VO2max test protocol utilized in this study and its
results have been described elsewhere (Vikmoen et al.
2016b). Brieﬂy, the test was initiated with 1-min running
at 8 kmh1 that was subsequently increased by 1 kmh1
every minute until exhaustion. VO2max was calculated as
the average of the two highest 30 sec VO2 measurements.
Peak running performance during the test (Vmax) was cal-
culated as the mean running velocity during the last
2 min of the incremental test.
Prolonged submaximal running followed by a
5-min all-out running test
The prolonged running lasted for 90 min at a speed cor-
responding
to
60%
of
Vmax
(7.7  0.4 kmh1
and
7.9  0.3 kmh1 in E + S and E, respectively). Each par-
ticipant ran at the same absolute speed at both pretrial
and posttrial. VO2 and HR were measured during 3-min
periods every 15th min throughout the prolonged run-
ning and RPE and [la] were measured every 15th min.
Average values for each 30-min period were calculated
and used for statistical analyses. The athletes were allowed
to consume water and a sport drink containing 60 gL1
carbohydrates, ad libitum, in order to maintain ﬂuid bal-
ance. The amount of sport drink consumed was similar
between groups and from pre to post (across groups val-
ues were 0.76  0.27 L and 0.72  0.24 L, respectively).
After conclusion of the prolonged running, the athletes
were allowed a 3-min rest before a 5-min all-out test was
performed for determination of running performance.
During the ﬁrst minute of the test, the speed was set by
the investigators. This individual selected speed was based
on pilot work and corresponded to 85% of Vmax. There-
after, the athletes were allowed to adjust the speed them-
selves with the instruction to run as fast as possible. The
athletes received feedback on speed and elapsed time, but
not HR or distance. Performance was measured as the
distance covered during the 5-min all-out test.
1RM tests
Approximately 20 min after termination of the cycling
VO2max test, maximal strength in the legs was tested as
1RM in half squat. The 1RM protocol used has been
described elsewhere (Vikmoen et al. 2016a). Brieﬂy, the
1RM test started with a speciﬁc warm-up, consisting of
three sets with gradually increasing load (40, 75, and 85%
of expected 1RM) and decreasing number of repetitions
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ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
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Strength Training and Endurance Performance
O. Vikmoen et al.
(10?6?3). The ﬁrst attempt was performed with a load
approximately 5% below the expected 1RM. If a lift was
successful, the load was increased by approximately 5%.
The test was terminated when the athletes failed to lift
the load in 2–3 attempts and the highest successful load
lifted was noted as 1RM. Athletes were given a 3-min rest
between lifts.
Lean mass in the legs
Lean mass in the legs (LegLM) was determined by
dual-energy X-ray absorptiometry using a Lunar Prodigy
densiometer (Prodigy Advance PA+302047, Lunar, San
Francisco, CA, USA). The athletes were instructed to
refrain from training for the 24 h leading up to the mea-
surement. They were also instructed to not ingest any
food or liquid for the 3 h preceding the measurement.
The same trained technician performed all DXA scans on
each participant. Care was taken to position the body at
the same location at each measurement.
Muscle biopsy sampling
Muscle biopsies were sampled from m. vastus lateralis
using the Bergstr€om procedure and treated as previously
described (Vikmoen et al. 2016a). An appropriately sized
muscle sample was excised and selected for quantitative
real-time
PCR
(qRT-PCR)
analyses
(average
wet
weight  SD: 38  7 mg), and a similarly sized sample
was selected for immunohistochemical analyses (average
wet weight  SD: 34  13 mg). Pre- and post-biopsies
were sampled at the same time of day for each particular
athlete. Athletes were instructed to refrain from physical
activity during the last 24 h before biopsy sampling and
not to ingest any food the 3 h preceding the biopsy. Biop-
sies for qRT-PCR analyses were immersed immediately in
RNAlater and treated according to manufacturers’ proto-
col before storage at 80°C (Ambion, Foster City, CA).
Biopsies
for
immunohistochemical
analyses
were
formaldehyde ﬁxated (Chemi-teknik AS, Oslo, Norway).
Muscle biopsy analyses
Immunohistochemistry
Protocols for immunohistochemical analyses of muscle ﬁber
type composition and the results have been presented else-
where (Vikmoen et al. 2016a). Brieﬂy, formalin-ﬁxed muscle
biopsies were parafﬁn-embedded and sectioned, whereupon
transverse, serial sections were labeled for MyHCI (A4.840,
H. Blau, Stanford, USA; Developmental Studies Hybridoma
Bank), MyHCIIA (EPR5280, Nordic Biosite), and MyHCIIX
(6H1, C Lucas, Sydney, Australia; Developmental Studies
Hybridoma Bank). Determination of muscle ﬁber composi-
tion was performed using Photoshop CS6 Extended (Adobe,
San Jose, CA). The investigator performing the image analy-
ses were blinded as to which group the athlete belonged.
Muscle ﬁbers that were positive for both MyHCIIA and
MyHCIIX are referred to as muscle ﬁber type IIAX-IIX (Vik-
moen et al. 2016a). Because of technical problems with some
analyses, the number of individuals in the immunohisto-
chemistry data is eight in E + S and eight in E.
Gene expression
Gene expression was assessed for genes involved in fatty
acid oxidation and anaerobic energy metabolism. Primer
design, RNA extraction, quantitative PCR (qPCR), and
evaluation of the stability of reference genes was per-
formed as previously described (Ellefsen et al. 2014). b2-
microglobulin and ribosomal protein L32 were found to
be the two most stable references genes and were utilized
for calculation of normalization factors using GeNorm,
which were in turn utilized for calculation of target gene
expression. All genes with associated primers are presented
in Table 1.
Statistics
All data in the text, ﬁgures, and tables are presented as
mean  standard deviation, unless otherwise stated. Prior
to statistical testing, gene expression were log2-trans-
formed to maximize the likelihood of normal distribution.
Unpaired students t-tests were used to test for differ-
ences between groups at pre and post, and differences in
changes from pre to post, except for evaluating responses
during the prolonged trials. Within-group analyses were
performed using paired t-tests except for evaluating
responses during the prolonged trials.
To evaluate changes in responses during the prolonged
trials within groups (pre to post) a two-way repeated
measures analysis of variance (ANOVA) (time of inter-
vention period and time during the prolonged trials as
factors) with Sidek-Holm post hoc test was performed.
To evaluate differences in changes in the responses during
the prolonged trials between the groups, a two-way
repeated measures ANOVA (changes from pre to post in
each group and time point during the prolonged trial as
factors) with Sidek-Holm post hoc test were performed.
In addition, effect sizes for the key performance and
physiological adaptations were calculated to compare the
practical signiﬁcance between the two groups. Effects size
were calculated as Cohen’s d and the criteria to inter-
pret the magnitude were the following: 0–0.2 =
trivial,
0.2–0.6 =
small, 0.6–1.2 =
moderate, 1.2–2.0 =
large,
and ˃2 = very large (Hopkins et al. 2009).
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
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O. Vikmoen et al.
Strength Training and Endurance Performance
Correlations analyses were done using the Pearson pro-
duct-moment method and correlations coefﬁcients were
interpreted according to Hopkins et al. (2009); r ˂ 0.1
trivial, 0.1–0.3 =
small, 0.3–0.5 =
moderate, 0.5–0.7 =
large, 0.7–0.9 =
very large, 0.9 =
nearly perfect, and
1.0 = perfect.
Analyses were performed in GraphPad Prism 6 (Graph-
Pad Software Inc., CA) and Excel 2013 (Microsoft Corpo-
ration, Redmon, WA). All analyses resulting in P ≤ 0.05
were considered statistically signiﬁcant.
Results
There were no signiﬁcant differences between E + S and
E at preintervention in any of the measured variables.
Body mass, maximal strength, and legLM
Body
mass
remained
unchanged
in
E+S
(pre:
62.4  5.2 kg,
post:
63.1  5.6 kg),
but
was
slightly
reduced in E (pre: 65.6  8.4 kg, post: 64.8  8.0 kg
P < 0.05).
The
change
in
body
mass
was
different
between groups (P < 0.05).
E + S increased 1RM in half squat with 45  22%
(P < 0.01), while no change occurred in E (3  10%,
P = 0.52, Fig. 1). The change in 1RM was larger in E + S
than in E (P < 0.01) and the ES analysis revealed a very
large practical effect of E + S compared to E (ES = 2.4).
LegLM increased in E + S with 3.1  4.0% (P < 0.05),
while it decreased in E with 2.2  2.1% (P < 0.05,
Fig. 1). The change in legLM was larger in E + S than in
E (P < 0.01) with a large practical effect of E + S com-
pared to E (ES = 1.69).
Because of the reduced body mass in E, all VO2 mea-
surements are presented as body mass adjusted values.
Since power output measured using cycling ergometers
does not correctly reﬂect the inﬂuence of body mass on
outdoor cycling performance, especially during uphill
cycling (Anton et al. 2007), power outputs measurements
are reported as body mass adjusted values (Wkg1).
However, running at a treadmill is inﬂuenced by body
Table 1. Details of primers used for RT-qPCR.
Gene
Forward primer
Reverse Primer
LDHA1
ATTCAGCCCGATTCCGTTAC
TTCCACTCCATACAGGCACAC
LDHB1
CATGGATGGATTTTGGGGGAAC
AACACCTGCCACATTCACAC
MCT11
TTGGAGTCATTGGAGGTCTTGG
CCAATGGTCGCCTCTTGTAG
MCT41
AGGCAAACTCCTGGATGCG
AAAATCAGGGAGGAGGTGAGC
PFKM1
TGACCTCCAGAAAGCAGGTAAG
AACCAGGCCCACAATGTTC
GAPDH1
AAGGCTGGGGCTCATTTG
ACGAACATGGGGGCATC
CPT22
AGCAGATGATGGTTGAGTGC
TCAAAGCCCTGGCCCATTG
SLC252
GCATTGCAGGGATCTTCAACTG
ATATTTCCCAGGAGGTGCAGTC
LDHA, lactate dehydrogenase A; LDHB, lactate dehydrogenase B; MCT1, monocarboxylate transporter 1; MCT4, monocarboxylate transporter
4; PFKM, phosphofructokinase; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; CPT2, carnitine palmitoyltransferase 2; SLC 25, carnitine/
acylcarnitine translocase, member 20.
1Genes involved in anaerobic energy metabolism.
2Genes involved in fatty acid oxidation.
Figure 1. Individual values (dotted lines) and mean values (solid
lines) before (Pre) and after (Post) the intervention period for
athletes adding strength training to their normal endurance training
(E+S, n = 11) and athletes performing normal endurance training
only (E, n = 8). A: Lean mass in the legs. B: one repetition
maximum (RM) in squat. * Different than pre (P ˂ 0.05), # the
percent change from pre is different in E + S than in E (P ˂ 0.05).
2017 | Vol. 5 | Iss. 5 | e13149
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ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
Strength Training and Endurance Performance
O. Vikmoen et al.
mass to the same degree as outdoor running (McMiken
and Daniels 1976); so, no body mass adjustments are
done on the reported running distances.
Muscle ﬁber type composition
The effect of the present intervention on ﬁber type com-
position has been previously reported (Vikmoen et al.
2016a). In brief, there was a reduction in the proportions
of ﬁbers positive for both IIA and IIX MyHC from
9  7% to 0% in E+S (P < 0.01) with a concomitant
increase in type IIA ﬁbers proportions from 39  13% to
51  10% (P < 0.01).
Gene expression
Of the nine genes investigated, only mRNA levels for
CPT2
and
LDHB
increased
1.8  0.5
-fold
and
1.2  0.3–fold, respectively, in E + S (P < 0.05). The
remainder of the genes did not change expression in
response to the intervention (Fig. 2).
VO2max and Wmax/Vmax
The effect of the intervention used in this study on
VO2max and Wmax/Vmax has been previously described
(Vikmoen et al. 2016a,b). In brief, VO2max in both cycling
and running and Wmax/Vmax were unchanged in both
groups during the intervention period.
Responses during the prolonged trials
The physiological responses during the prolonged trials are
displayed in Table 2 and their percent changes are dis-
played in Figure 3. After the intervention, E + S reduced
VO2 during the last two hours of the prolonged cycling trial
(P ˂ 0.05) with no changes in E. The changes during the
last
two
hours
were
different
between
the
groups
(P ˂ 0.05). In addition, the effect size analysis revealed a
large practical effect of E + S compared to E during the last
hour of the trial (ES = 1.2). There were no changes in VO2
for neither E + S nor E during the prolonged running.
E + S had a reduced HR throughout the prolonged
cycling after the intervention (P ˂ 0.05), while E had a
reduced HR during the ﬁrst hour only (P ˂ 0.05). There
was a moderate practical effect of E + S compared to E
during the last hour of the trial (ES = 1.12). The correla-
tion between changes in VO2 and HR during the last
hour of the prolonged cycling was large (r = 0.59). Both
E+S and E had a reduced HR during the entire prolonged
running trial after the intervention period (P ˂ 0.05).
There was no difference in changes between the groups.
Compared to the pretrial, RPE was lower during the
last hour of prolonged cycling for E + S and lower during
the last two hours for E (P ˂ 0.05). However, there were
no differences in changes between the groups. RPE did
not change during the prolonged running. There were no
changes in RER in neither of the groups during the pro-
longed trial in both cycling and running. In cycling,
cadence did not change in either group during the
intervention.
5-min all-out tests
After the intervention, the mean power output during the
5-min
all-out
cycling
test
increased
by
7.0  4.5%
(P < 0.05) in E+S with no change in E (3.3  7.1%,
P = 0.27 Fig. 4). The difference between the groups was
not statistically signiﬁcant, but the practical effect of
E + S compared to E was moderate (ES = 0.62). E + S
Figure 2. Log2-fold change in mRNA expression for genes involved in fat transport and anaerobic metabolism during the intervention period
for athletes adding strength training to their normal endurance training (E + S, n = 11) and athletes performing normal endurance training only
(E, n = 8). * Different than pre (P ˂ 0.05). Values are mean  95% CI.
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
2017 | Vol. 5 | Iss. 5 | e13149
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O. Vikmoen et al.
Strength Training and Endurance Performance
increased running distance in the 5-min all-out running
test by 4.7  6.0% (P < 0.05) with no change in E
(0.6  5.0%, Fig. 4). The increase in running distance
was larger in E + S than in E (P = 0.05), and the practi-
cal
effect
of
E + S
compared
to
E
was
moderate
(ES = 0.95). Correlation analyses revealed a large correla-
tion between change in all-out cycling performance and
Wmax (r = 0.54, P ˂ 0.05) and between all-out running
performance and Vmax (r = 0.53, P ˂ 0.05). There was a
large correlation between change in all-out performance
and the training induced change in IIAX-IIX ﬁbers in
cycling (r = 0.54, P ˂ 0.05, Fig. 5) and in running
(r = 0.50, P ˂ 0.05, Fig. 5) when data from both groups
were included. When only E + S athletes were included,
the correlation got very large in cycling (r = 0.73,
P = 0.065, Fig. 5) but disappeared in running (r = 0. 28,
P = 0.547, Fig. 5). The correlation between the percent
change in running distance and mean power output in
cycling was moderate but not statistically signiﬁcant
(r = 0.40, P = 0.10).
Discussion
The main ﬁnding of this study is that addition of heavy
strength training to the regular endurance training of
female duathletes improved both running and cycling
performance measured as 5-min all-out performance
tested immediately after prolonged submaximal work. In
addition, VO2 and HR were reduced during the last two
hours of a 3-h prolonged cycling trial after the addition
of heavy strength training, whereas no effects of added
strength
training
were
observed
on
physiological
responses during prolonged submaximal running.
Strength, legLM, and muscle ﬁber type
composition
The observed increase in 1RM in half squat and legLM is
in accordance to previously observed improvements in
endurance athletes adding 8–12 weeks of heavy strength
training (e.g., Bishop et al. 1999; Storen et al. 2008;
Ronnestad et al. 2010a; Aagaard et al. 2011; Ronnestad
et al. 2015). The results lend further support to the
notion that a substantial increase in strength can be
achieved with little or no change in body mass (Storen
et al. 2008; Ronnestad et al. 2010a; Sunde et al. 2010;
Ronnestad et al. 2015). Increased body mass is usually
undesirable for performance in cycling and running and
therefore a concern among endurance athletes considering
adding strength training. The increase in legLM reported
Table 2. Responses during the prolonged trials in cycling and running for athletes adding strength training to their normal endurance training
(E + S, n = 10) and athletes performing normal endurance training only (E, n = 8).
E+S
E
Test section
First section
Middle section
Last section
First section
Middle section
Last section
VO2 (ml∙kg1∙min1)
Cycling
Pre
30.5  2.9
31.3  3.0
31.9  2.9
30.1  3.2
30.5  3.4
31.0  3.1
Post
30.0  2.5
30.2  2.9*,#
30.9  3.2*,#
29.9  2.4
30.8  2.9
31.5  3.0
Running
Pre
37.3  1.8
37.7  1.8
37.7  1.8
37.0  2.1
37.3  2.0
37.3  1.8
Post
37.0  2.2
37.5  2.0
37.6  1.9
37.4  2.0
37.4  1.5
37.4  1.4
HR (beats∙min1)
Cycling
Pre
134  12
138  14
143  14
129  11
130  9
135  7
Post
131  12*
131  14*
137  13*
125  9*
128  10
135  9
Running
Pre
158  12
163  13
165  13
152  11
157  11
158  11
Post
154  11*
158  10*
159  11*
148  13*
151  11*
153  11*
RER
Cycling
Pre
0.85  0.03
0.84  0.03
0.82  0.03
0.87  0.03
0.84  0.03
0.81  0.04
Post
0.87  0.04
0.85  0.03
0.82  0.03
0.88  0.03
0.85  0.03
0.82  0.03
Running
Pre
0.90  0.02
0.89  0.02
0.88  0.02
0.90  0.02
0.87  0.03
0.86  0.03
Post
0.91  0.03
0.88  0.03
0.86  0.03
0.90  0.02
0.88  0.03
0.86  0.03
RPE (Borg scale)
Cycling
Pre
11  1
12  1
13  1
11  2
12  2
13  2
Post
11  1
12  1
12  1*
10  2
11  1*
12  1*
Running
Pre
12  1
13  1
13  1
11  2
12  1
13  1
Post
11  1
12  1
13  1
11  1
12  1
13  1
Cadence (rev∙min1)
Cycling
Pre
84  8
83  10
83  10
83  10
81  12
80  13
Post
85  9
83  8
83  9
81  11
81  12
80  14
Running
Pre
–
–
–
–
–
–
Post
–
–
–
–
–
–
Values are mean  SD.
*Different than pre (P ˂ 0.05)
#The change from pre to post is different in E+S than in E (P ˂ 0.05).
2017 | Vol. 5 | Iss. 5 | e13149
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The Physiological Society and the American Physiological Society.
Strength Training and Endurance Performance
O. Vikmoen et al.
in this study indicates that at least some of the improved
strength was due to muscle hypertrophy. In addition, we
observed a ﬁber type shift from type IIAX-IIX toward
type IIA ﬁbers (Vikmoen et al. 2016a), a common adap-
tation to strength training among both untrained and
endurance trained individuals (Staron et al. 1994; Aagaard
et al. 2011). The increased legLM and ﬁber type shift
shows that the strength training program was effective in
inducing adaptations at the muscular level.
Physiological responses during the
prolonged trials
As
previously
observed
in
well-trained
male
cyclists
(Ronnestad et al. 2011), E+S reduced VO2 during the last
two hours of the prolonged cycling after the strength
training intervention. Therefore, although no change in
cycling economy was observed during the ﬁrst hour,
cycling economy was clearly improved when the athletes
started to get fatigued. This is highly important in cycling
where many races include prolonged submaximal intensi-
ties for several hours. Improved cycling economy have
also been reported in untrained individuals (Loveless
et al. 2005) and trained male cyclists (Sunde et al. 2010)
after strength training interventions when measured in a
nonfatigued state. However, this seems not to be the case
in highly trained to elite cyclists (Ronnestad et al. 2010a;
Aagaard et al. 2011; Ronnestad et al. 2015). The results
from this study and the study by Ronnestad et al. (2011)
indicate that after a strength training intervention, cycling
Figure 3. Percent change in responses during the prolonged trials in cycling (left panels) and running (right panels) for athletes adding
strength training to their normal endurance training (E + S, n = 10) and athletes performing normal endurance training only (E, n = 8). Values
are mean  SD. * Different than pre (P ˂ 0.05), # the percent change from pre is different in E + S than in E (P ˂ 0.05).
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
2017 | Vol. 5 | Iss. 5 | e13149
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O. Vikmoen et al.
Strength Training and Endurance Performance
economy should also be tested when the athletes are
somewhat fatigued.
HR was reduced throughout the prolonged cycling trial
after the intervention period in E + S and as for VO2 the
effect was more pronounced during the last 2 h. Conse-
quently, the reduced HR was probably because of the
reduced VO2 and hence reduced energy cost. In fact, the
reduced HR mirrored the changes in VO2 and a large
correlation between change in VO2 and change in HR
during the last hour was observed (r = 0.59).
The mechanisms behind improved cycling economy
during the last 2 h of the trial are somewhat unclear. One
explanation might be delayed recruitment of type II mus-
cle ﬁbers brought on by increased muscle strength and
muscle mass (Ronnestad et al. 2011). When the maximal
muscle strength increases and the absolute power output
and cadence remains the same, the level of force devel-
oped in each pedal thrust is reduced relatively to the
maximal force. Given the size principle of motor unit
recruitment, this implies that the more economical type I
muscle ﬁbers can account for a larger proportion of the
same
absolute
power
output
(Hickson
et al.
1988;
Ronnestad and Mujika 2014). This may also explain the
lack of changes in cycling economy during the ﬁrst hour
where the relative low power output should mainly
recruit type I muscle ﬁbers, thereby leaving little potential
for improvements. In fact, it has previously been reported
that after exercise for 60 min at an intensity requiring
43% of VO2max, glycogen breakdown mainly occurred in
the type I muscle ﬁbers (Vollestad and Blom 1985), indi-
cating limited recruitment of type II ﬁbers. However, as
the duration of the work increases and muscle ﬁbers
starts to get fatigued, additional motor units needs to be
recruited to sustain the power output (Gollnick and Arm-
strong 1973; Vollestad and Blom 1985). The suggested
mechanisms is therefore that the strength training allowed
E + S to use the more economical type I muscle ﬁbers
for a longer duration of the trial after the intervention,
leading to improved cycling economy during the last part.
Supporting this, 5 weeks of strength training has been
shown to reduce EMG activity in m. vastus lateralis dur-
ing the last hour of a 2-hour prolonged cycling trial in
well-trained triathletes (Hausswirth et al. 2010).
The ﬁber type transition from type IIAX-IIX to type
IIA in E+S might also contribute to the improved cycling
economy since it has been suggested that type IIA ﬁbers
are more economical than the type IIX ﬁbers (Westerblad
et al. 2010). However, there was no correlation between
the changes in the proportions of type IIAX-IIX and
changes in economy during the last hour of the pro-
longed cycling. This may be because the relatively low
power output did not recruit any type IIX ﬁbers during
the trial even before the intervention.
Other possible explanations for improved cycling econ-
omy during the last 2 hours of the prolonged cycling trial
could have been changes in substrate utilization toward
larger carbohydrate utilization (Mogensen et al. 2006) or
reduction in cadence (Foss and Hallen 2004). However,
there were no changes in RER or cadence during the pro-
longed cycling, making these explanations unlikely. In
fact, based on the increased mRNA levels of CPT2, a pro-
tein involved in fatty acid oxidation in the mitochondria,
an increased utilization of fat as an energy substrate
might have been expected. However, in Vikmoen et al.
(2016a), we did not ﬁnd changes in the content of the
beta-oxidation enzyme hydroxyacyl-CoA dehydrogenase
(HADH) in the very same biopsy material, supporting the
notion that rates of fatty acid oxidation did not change.
In contrast to cycling, no changes occurred in VO2
during the prolonged running. This is surprising since the
proposed mechanisms for the reduced VO2 during cycling
in theory also could reduce VO2 during the prolonged
running.
However,
some
methodological
differences
Figure 4. Individual values (dotted lines) and mean values (solid
lines) before (Pre) and after (Post) the intervention period for
athletes adding strength training to their normal endurance training
(E + S, n = 10) and athletes performing normal endurance training
only (E, n = 8). A: Running distance during the 5-min all-out
running test. B: Mean power output during the 5-min all-out
cycling test. * Different than pre (P ˂ 0.05), # the percent change
from pre is different in E + S than in E (P = 0.05).
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ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
Strength Training and Endurance Performance
O. Vikmoen et al.
might explain the different ﬁnding between cycling and
running. The prolonged running was only half as long as
the prolonged cycling and was performed at a higher rela-
tive workload (60% vs. 44% of Vmax and Wmax, respec-
tively). Because the reduced VO2 during the cycling trial
was seen during the last 2 h, it may be speculated that
the prolonged running were too short. However, running
races do seldom last as long as cycling races, and the
shorter duration was therefore chosen for the prolonged
running. To compensate for the shorter duration, the
prolonged running was performed at a higher relative
intensity than the prolonged cycling. This may have led
to a quite high recruitment of type II motor units from
the start, and the potential for reduced VO2 during the
last part of the trial may therefore have been limited. In
fact, in a glycogen breakdown study, it was estimated that
a large proportion of type IIA ﬁbers were recruited
already from the start at a power output corresponding
to 61% of VO2max (Vollestad and Blom 1985).
No changes in running economy after addition of
strength training is in conﬂict with results from previous
studies where improved running economy ranging from 3
to 8% have been reported (e.g., Paavolainen et al. 1999;
Storen et al. 2008; Sedano et al. 2013). Some method-
ological differences might explain this discrepancy. Run-
ning economy was tested with an inclination of 5.3% in
our study, and in combination with the relative low
workload, the velocity during the prolonged running was
quite low compared to previous studies. In fact, the
improvements in running economy after strength training
have been reported to be dependent on running velocity
(Saunders et al. 2006). The lack of effect on running
economy may also be because the strength training pro-
gram used did not induce any changes in patellar tendon
stiffness (Vikmoen et al. 2016b). Changes in muscle-ten-
don stiffness is a frequently proposed mechanism behind
improved running economy after strength training (Saun-
ders et al. 2006; Storen et al. 2008).
Performance during the 5-min all-out tests
The improved cycling performance observed in the 5-min
all-out test is in accordance with a similar study in male
cyclists, who found increased 5-min all-out performance
following prolonged cycling after adding strength training
to their normal endurance training (Ronnestad et al.
2011). A novel ﬁnding in this study is that 5-min all-out
running performance after a prolonged submaximal trial
also seems to be affected to the same degree as in cycling.
Improved running and cycling performance after strength
training is in accordance with previous studies in cycling
(Koninckx et al. 2010; Ronnestad et al. 2010a,b; Sunde
et al. 2010, Aagaard et al. 2011; Ronnestad et al. 2015;
Vikmoen et al. 2016a) and running (Paavolainen et al.
1999; Storen et al. 2008; Sedano et al. 2013; Damasceno
et al. 2015) when performance is measured in a more tra-
ditional way. However, other studies contradict these
ﬁndings both in cycling (Bishop et al. 1999; Bastiaans
Figure 5. A: Correlation between changes in type IIAX-IIX proportions and changes in mean power output during the 5-min all-out cycling
test. The inserted panel shows the correlation when only the athletes adding strength training to their normal endurance training are included.
B: Correlation between changes in type IIAX-IIX proportions and changes in running distance during the 5-min all-out running test. The inserted
panel shows the correlation when only the athletes adding strength training to their normal endurance training are included.
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
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O. Vikmoen et al.
Strength Training and Endurance Performance
et al. 2001; Levin et al. 2009) and running (Ferrauti et al.
2010; Roschel et al. 2015). Some methodological differ-
ences may explain these equivocal ﬁndings. To positively
affect cycling performance, it seems that the strength
training regime needs to involve heavy training load
(4-10RM), rather large volumes of training and last for
8 weeks or longer (Koninckx et al. 2010; Ronnestad et al.
2010a, Aagaard et al. 2011; Ronnestad et al. 2015). On
the other hand, both explosive, plyometric and heavy
strength training seems effective in improving running
performance (Paavolainen et al. 1999; Storen et al. 2008;
Sedano et al. 2013; Damasceno et al. 2015).
Together, these observations indicate that the mecha-
nisms behind changes in running and cycling performance
after strength training may be somewhat different. How-
ever, improvements in both cycling and running perfor-
mance may be related to typical adaptations to prolonged
periods of heavy strength training such as increased mus-
cle mass and ﬁber type transitions from type IIX to type
IIA; improvements in running performance may also rely
on adaptations such as changes in leg stiffness, rate of
force development, and other neuromuscular characteris-
tics. Therefore, mechanisms behind the improved perfor-
mance in cycling and running in this study might be
different. This is supported by the fact that the correlation
between changes in running and cycling performance
(r = 0.40) were not statistically signiﬁcant.
Since the performance tests were performed right after
the prolonged trials, changes in the physiological responses
to the submaximal exercise was expected to affect perfor-
mance. We suggest that the reduced VO2 and HR observed
during the last 2 hours of the cycling trial, indicating
reduced physiological strain and less fatigue, made the ath-
letes in E + S capable of producing higher mean power
output during the ﬁnal 5-min all-out test. Furthermore,
reduced VO2 in E + S means that the total energy con-
sumption during the prolonged cycling trial was lower after
the intervention and with no change in substrate utilization
the total carbohydrate utilization was reduced. Therefore,
some of the improved cycling performance in E + S may
be due to a better conservation of glycogen stores during
the prolonged trial. The importance of less physiological
strain during the submaximal exercise is indirectly sup-
ported by the fact that 5-min all-out performance, tested in
the rested state, was unchanged after 16 weeks of strength
training in elite cyclists (Aagaard et al. 2011).
Based on the present data, the positive effect of
strength training on performance in the 5-min all-out
running test cannot be explained by changes in physiolog-
ical responses during the submaximal running. Therefore,
the improved running performance after strength training
has to be through other mechanisms. During a 5-min
all-out test a substantial part of the energy is derived
from anaerobic metabolism (Gastin 2001). Therefore,
increased anaerobic capacity might be a mechanism
behind the improved performance in both cycling and
running.
In
fact,
endurance
performance
has
been
reported to correlate well with measurements of anaerobic
performance (e.g., Bulbulian et al. 1986; Houmard et al.
1991). Increased anaerobic capacity can be achieved
through increases in muscle mass (Bangsbo et al. 1993)
and/or through increasing amount of anaerobic enzymes.
Even though small to none changes were found in mRNA
expression of genes coding for important proteins in
anaerobic metabolic pathways in E + S, the increased
muscle mass should mean that anaerobic capacity was
improved. Anaerobic capacity should also affect perfor-
mance in Vmax/Wmax. Even though there were no signiﬁ-
cant changes in these variables, the correlation between
changes in Vmax and running performance and Wmax and
cycling performance further support that improved anaer-
obic capacity might play a role for the improved perfor-
mance in E + S. In addition, there was a very large
correlation between legLM and absolute average power
output during the 5-min all-out test before the interven-
tion (r = 0.71, data not shown) indicating that muscle
mass is important in these kinds of tests.
There were large correlations between the reduction in
muscle ﬁber type IIAX-IIX proportions and changes in
5-min all-out performance in both cycling and running.
The type IIA ﬁbers is less fatigable than the type IIX ﬁbers
(Westerblad et al. 2010), and a ﬁber type transition could
therefore improve performance. However, a correlation
between two variables does not necessarily mean a cause
and effect relationship (Greenﬁeld et al. 1998). Perhaps,
the athletes with a large reduction in ﬁber type IIAX-IIX
proportions had a large response to the strength training
and that other adaptations to the strength training actu-
ally were responsible for the improved performance.
Indeed, there was a large negative correlation (r = 0.65,
data not shown) between the change in legLM and change
in the proportion of type IIAX-IIX ﬁbers. Notably, when
only E+S was included, the correlation between 5-min
all-out performance and IIAX-IIX ﬁber transitions got
very large in cycling and disappeared in running. This
indicates that the possible performance-enhancing effects
from ﬁber type shift from type IIAX-IIX toward type IIA
was more important in cycling than in running.
The improved performance cannot be explained by
changes in VO2max since VO2max did not change in neither
cycling nor running. The lack of effect of strength training
on VO2max is not surprising and is in accordance with the
current literature (e.g., Storen et al. 2008; Aagaard et al.
2011; Ronnestad et al. 2015). Importantly, we expected no
change in VO2max in the study, as athletes were instructed
to continue their normal endurance training, having a
2017 | Vol. 5 | Iss. 5 | e13149
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ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
Strength Training and Endurance Performance
O. Vikmoen et al.
good base of training from their winter training consisting
of running, cycling, and cross-country skiing.
This is the ﬁrst controlled study to demonstrate that
adding heavy strength training to endurance training
leads to improvements in both cycling and running per-
formance in the same athletes. Performance was tested as
5-min all-out performance, measured immediately after
prolonged periods of submaximal work. The improved
cycling performance was probably related to reduced
physiological strain during the submaximal trial. This is
also the ﬁrst study reporting improved running perfor-
mance following a prolonged submaximal effort. How-
ever, there were no changes in the physiological responses
to prolonged running. Therefore, improved running per-
formance was more likely related to other mechanisms
like changes in anaerobic capacity and neuromuscular
changes. Changes in anaerobic capacity probably also
contributed to improved cycling performance. A ﬁber
type shift from type IIAX-IIX toward type IIA in the
main propulsive muscles also seemed to contribute to
the improved performance, especially in cycling. Based on
the results of this study, both runners and cyclists should
include heavy strength training in their training programs
for maximal gains in performance. This seems to be par-
ticularly important for performance during late phases of
long-lasting competitions.
Acknowledgments
The authors thank the participants for their time and
effort;
students
Kristoffer
Bergstrøm,
Øyvind
Trøen,
Roger Kristoffersen, Allan Sørgaard Nielsen, and Sondre
Prestkvern for assistance during the intervention follow-
up and data sampling. A special thanks to the Hospital
for Rheumatic Diseases at Lillehammer for performing
the DXA scans. Olav Vikmoen also thanks his current
employer, the Norwegian Defence Research Establishment
(FFI) for support during the writing process.
Conﬂict of Interests
None declared.
References
Aagaard, P., J. L. Andersen, M. Bennekou, B. Larsson, J. L.
Olesen, R. Crameri, et al. 2011. Effects of resistance training
on endurance capacity and muscle ﬁber composition in young
top-level cyclists. Scand. J. Med. Sci. Sports 21:e298–e307.
Anton, M. M., M. Izquierdo, J. Ibanez, X. Asiain, J.
Mendiguchia, and E. M. Gorostiaga. 2007. Flat and uphill
climb time trial performance prediction in elite amateur
cyclists. Int. J. Sports Med. 28:306–313.
Bangsbo, J., L. Michalsik, and A. Petersen. 1993. Accumulated
O2 deﬁcit during intense exercise and muscle characteristics
of elite athletes. Int. J. Sports Med. 14:207–213.
Bastiaans, J. J., A. B. van Diemen, T. Veneberg, and A. E.
Jeukendrup. 2001. The effects of replacing a portion of
endurance training by explosive strength training on
performance in trained cyclists. Eur. J. Appl. Physiol.
86:79–84.
Bishop, D., D. G. Jenkins, L. T. Mackinnon, M. McEniery, and
M. F. Carey. 1999. The effects of strength training on
endurance performance and muscle characteristics. Med. Sci.
Sports Exerc. 31:886–891.
Bulbulian, R., A. R. Wilcox, and B. L. Darabos. 1986. Anaerobic
contribution to distance running performance of trained
cross-country athletes. Med. Sci. Sports Exerc. 18:107–113.
Damasceno, M. V., A. E. Lima-Silva, L. A. Pasqua, V. Tricoli,
M. Duarte, D. J. Bishop, et al. 2015. Effects of resistance
training on neuromuscular characteristics and pacing during
10-km running time trial. Eur. J. Appl. Physiol. 115:1513–
1522.
Ellefsen, S., O. Vikmoen, G. Slettalokken, J. E. Whist, H.
Nygaard, I. Hollan, et al. 2014. Irisin and FNDC5: effects of
12-week strength training, and relations to muscle
phenotype and body mass composition in untrained
women. Eur. J. Appl. Physiol. 114:1875–1888.
Ferrauti, A., M. Bergermann, and J. Fernandez-Fernandez.
2010. Effects of a concurrent strength and endurance
training on running performance and running economy in
recreational marathon runners. J. Strength Cond. Res.
24:2770–2778.
Foss, O., and J. Hallen. 2004. The most economical cadence
increases with increasing workload. Eur. J. Appl. Physiol.
92:443–451.
Gastin, P. B. 2001. Energy system interaction and relative
contribution during maximal exercise. Sports Med. 31:725–
741.
Gollnick, P. D., R. B. Armstrong, C. W. T. Saubert, W. L.
Sembrowich, R. E. Shepherd, and B Saltin. 1973. Glycogen
depletion patterns in human skeletal muscle ﬁbers during
prolonged work. Pﬂugers Arch. 344:1–12.
Greenﬁeld, M. L., J. E. Kuhn, and E. M. Wojtys. 1998. A
statistics primer. Correlation and regression analysis. Am. J.
Sports Med. 26:338–343.
Hausswirth, C., S. Argentin, F. Bieuzen, Y. Le Meur, A.
Couturier, and J. Brisswalter. 2010. Endurance and strength
training effects on physiological and muscular parameters
during prolonged cycling. J. Electromyogr. Kinesiol. 20:330–
339.
Hickson, R. C., B. A. Dvorak, E. M. Gorostiaga, T. T.
Kurowski, and C. Foster. 1988. Potential for strength and
endurance training to amplify endurance performance. J.
Appl. Physiol. 65:2285–2290.
Hopkins, W. G., S. W. Marshall, A. M. Batterham, and J.
Hanin. 2009. Progressive statistics for studies in sports
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
2017 | Vol. 5 | Iss. 5 | e13149
Page 13
O. Vikmoen et al.
Strength Training and Endurance Performance
medicine and exercise science. Med. Sci. Sports Exerc.
41:3–13.
Houmard, J. A., D. L. Costill, J. B. Mitchell, S. H. Park, and T.
C. Chenier. 1991. The role of anaerobic ability in middle
distance running performance. Eur. J. Appl. Physiol. Occup.
Physiol. 62:40–43.
Jeukendrup, A. E., N. P. Craig, and J. A. Hawley. 2000. The
bioenergetics of World Class Cycling. J Sci Med Sport
3:414–433.
Koninckx, E., M. Van Leemputte, and P. Hespel. 2010. Effect
of isokinetic cycling versus weight training on maximal
power output and endurance performance in cycling. Eur. J.
Appl. Physiol. 109:699–708.
Levin, G. T., M. R. McGuigan, and P. B. Laursen. 2009. Effect
of concurrent resistance and endurance training on
physiologic and performance parameters of well-trained
endurance cyclists. J. Strength Cond. Res. 23:2280–2286.
Loveless, D. J., C. L. Weber, L. J. Haseler, and D. A. Schneider.
2005. Maximal leg-strength training improves cycling
economy in previously untrained men. Med. Sci. Sports
Exerc. 37:1231–1236.
McMiken, D. F., and J. T. Daniels. 1976. Aerobic requirements
and maximum aerobic power in treadmill and track
running. Med Sci Sports 8:14–17.
Mogensen, M., M. Bagger, P. K. Pedersen, M. Fernstrom, and
K. Sahlin. 2006. Cycling efﬁciency in humans is related to
low UCP3 content and to type I ﬁbres but not to
mitochondrial efﬁciency. J. Physiol. 571:669–681.
Paavolainen, L., K. Hakkinen, I. Hamalainen, A. Nummela,
and H. Rusko. 1999. Explosive-strength training improves
5-km running time by improving running economy and
muscle power. J. Appl. Physiol. 86:1527–1533.
Ronnestad, B. R., and I. Mujika. 2014. Optimizing strength
training for running and cycling endurance performance: a
review. Scand. J. Med. Sci. Sports 24:603–612.
Ronnestad, B. R., E. A. Hansen, and T. Raastad. 2010a. Effect
of heavy strength training on thigh muscle cross-sectional
area, performance determinants, and performance in well-
trained cyclists. Eur. J. Appl. Physiol. 108:965–975.
Ronnestad, B. R., E. A. Hansen, and T. Raastad. 2010b.
In-season strength maintenance training increases well-
trained cyclists’ performance. Eur. J. Appl. Physiol.
110:1269–1282.
Ronnestad, B. R., E. A. Hansen, and T. Raastad. 2011. Strength
training improves 5-min all-out performance following
185 min of cycling. Scand. J. Med. Sci. Sports 21:250–259.
Ronnestad, B. R., J. Hansen, I. Hollan, and S. Ellefsen. 2015.
Strength training improves performance and pedaling
characteristics in elite cyclists. Scand. J. Med. Sci. Sports 25:
e89–e98.
Roschel, H., R. Barroso, V. Tricoli, M. A. Batista, F. M.
Acquesta, J. C. Serrao, et al. 2015. Effects of strength
training associated with whole-body vibration training on
running economy and vertical stiffness. J. Strength Cond.
Res. 29:2215–2220.
Saunders, P. U., R. D. Telford, D. B. Pyne, E. M. Peltola, R. B.
Cunningham, C. J. Gore, et al. 2006. Short-term plyometric
training improves running economy in highly trained
middle and long distance runners. J. Strength Cond. Res.
20:947–954.
Sedano, S., P. J. Marin, G. Cuadrado, and J. C. Redondo.
2013. Concurrent training in elite male runners: the
inﬂuence of strength versus muscular endurance training on
performance outcomes. J. Strength Cond. Res. 27:2433–
2443.
Staron, R. S., D. L. Karapondo, W. J. Kraemer, A. C. Fry, S. E.
Gordon, J. E. Falkel, et al. 1994. Skeletal muscle adaptations
during early phase of heavy-resistance training in men and
women. J. Appl. Physiol. 76:1247–1255.
Storen, O., J. Helgerud, E. M. Stoa, and J. Hoff. 2008.
Maximal strength training improves running economy in
distance runners. Med. Sci. Sports Exerc. 40:1087–1092.
Sunde, A., O. Storen, M. Bjerkaas, M. H. Larsen, J. Hoff, and
J. Helgerud. 2010. Maximal strength training improves
cycling economy in competitive cyclists. J. Strength Cond.
Res. 24:2157–2165.
Vikmoen, O., S. Ellefsen, O. Troen, I. Hollan, M.
Hanestadhaugen, T. Raastad, et al. 2016a. Strength training
improves cycling performance, fractional utilization of
VO2max and cycling economy in female cyclists. Scand. J.
Med. Sci. Sports 26:384–396.
Vikmoen, O., T. Raastad, O. Seynnes, K. Bergstrom, S.
Ellefsen, and B. R. Ronnestad. 2016b. Effects of heavy
strength training on running performance and determinants
of running performance in female endurance athletes. PLoS
ONE 11:e0150799.
Vollestad, N. K., and P. C. Blom. 1985. Effect of varying
exercise intensity on glycogen depletion in human muscle
ﬁbres. Acta Physiol. Scand. 125:395–405.
Westerblad, H., J. D. Bruton, and A. Katz. 2010. Skeletal
muscle: energy metabolism, ﬁber types, fatigue and
adaptability. Exp. Cell Res. 316:3093–3099.
2017 | Vol. 5 | Iss. 5 | e13149
Page 14
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
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O. Vikmoen et al.

Heavy strength training improves running and cycling performance following prolonged submaximal work in well-trained female athletes.
Vikmoen, Olav,Rønnestad, Bent R,Ellefsen, Stian,Raastad, Truls