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Content uploaded by Rune Kjøsen Talsnes
Author content
All content in this area was uploaded by Rune Kjøsen Talsnes on Oct 06, 2021
Content may be subject to copyright.
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Effects of increased load of low- vs. high-intensity endurance training on
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performance and physiological adaptations in endurance athletes
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Original investigation
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Rune Kjøsen Talsnes1,2, Roland van den Tillaar2 and Øyvind Sandbakk3
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1Meråker High School, Trøndelag County Council, Steinkjer, Norway.
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2Department of Sports Science and Physical Education, Nord University, Bodø, Norway.
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3Centre for Elite Sports Research, Department of Neuromedicine and Movement Science,
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Norwegian University of Science and Technology, Trondheim, Norway.
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Corresponding Author:
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Rune Kjøsen Talsnes
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Department of Sports Science and Physical Education
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Nord University
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8026 Bodø, Norway
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E-mail: rune.k.talsnes@nord.no
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Phone: +47 99430935
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Running head
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Endurance training intensity
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Abstract Word Count
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250
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Text-Only Word Count
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3358
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Number of Figures and Tables
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Figures: 4 Tables: 4
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Abstract
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Purpose: To compare the effects of increased load of low- vs. high-intensity endurance training
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on performance and physiological adaptations in well-trained endurance athletes.
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Methods: Following an 8-week pre-intervention period, fifty-one (36 men and 15 women)
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junior cross-country skiers and biathletes were randomly allocated into a low-intensity (LIG,
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n=26) or high-intensity training group (HIG, n=25) for an 8-week intervention period, load-
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balanced using the overall training impulse (TRIMP)-score. Both groups performed an uphill
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running time-trial and were assessed for laboratory performance and physiological profiling in
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treadmill running and roller-ski skating pre- and post-intervention.
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Results: Pre- to post-intervention changes in running time-trial did not differ between groups
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(p=0.44), with significant improvements in HIG (-2.3±3.2%, p=0.01) but not in LIG (-
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1.5±2.9%, p=0.20). There were no differences between groups in peak speed changes when
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incremental running and roller-ski skating to exhaustion (p=0.30 and p=0.20, respectively),
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with both modes being significantly improved in HIG (2.2±3.1% and 2.5±3.4%, both p<0.01)
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and in roller-ski skating for LIG (1.5±2.4%, p<0.01). There was a between-group difference in
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running VO2max changes (p=0.04), tending to improve in HIG (3.0±6.4%, p=0.09) but not in
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LIG (-0.7±4.6%, p=0.25). Changes in roller-ski skating VO2peak differed between groups
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(p=0.02), with significant improvements in HIG (3.6±5.4%, p=0.01) but not in LIG (-
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0.1±0.17%, p=0.62).
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Conclusion: There were no significant difference in performance adaptations between
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increased load of low- vs. high-intensity training in well-trained endurance athletes although
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both methods improved performance. However, increased load of high-intensity training
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elicited better VO2max adaptations compared to increased load of low-intensity training.
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Keywords: biathlon, endurance performance, maximal oxygen uptake, training intensity
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distribution, training volume, XC skiing
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Introduction
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Endurance training involves the manipulation of training intensity, duration, frequency and
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mode, with the goal of maximizing physiological adaptations and performance.1,2 Accordingly,
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the organization and optimization of endurance training, and in particular training volume and
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intensity distribution, is widely debated among both sports scientists and practitioners.1-3 Most
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elite endurance athletes adopt a training model consisting of high volumes of low-intensity
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training (LIT) combined with low-to-moderate amounts of moderate- (MIT) and high-intensity
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training (HIT).1-3 However, the exact volume and training intensity distribution depends on the
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demands of the given endurance sport, individual requirements, as well as the phase of the
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annual training cycle.1,3,4
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Endurance athletes progress their overall training stimulus throughout the annual cycle, which
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might be achieved through increased load of LIT or by performing a larger load of MIT and/or
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HIT.1 While LIT is seen as an important stimulus for inducing peripheral adaptations such as
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increased mitochondrial biogenesis and capillary density of the skeletal muscle,5,6 central
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adaptations such as increased stroke volume of the heart, leading to improved maximal oxygen
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uptake (VO2max), are regarded as more responsive to HIT.5-7 However, LIT and HIT have many
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similarities (e.g., upregulating PGC-1α) and both intensities seem to elicit complex and
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integrated adaptations.1,5
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To better understand how progression in endurance training load by different intensity
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distributions influence performance and physiological adaptations in endurance athletes, valid
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methods for the matching of training load is required. The majority of previous intervention
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studies where training load has been matched for total work or oxygen consumption (iso-
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energetic method) emphasizes the superiority of HIT for maximizing physiological
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adaptations.7-9 However, such studies are not realistic from the perspective of how endurance
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athletes train and perceive stress,3 since endurance athletes can perform far more work, both
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energetically and in terms of total work at a lower autonomic disturbance, with LIT compared
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to HIT.10 Accordingly, progressing the overall training stimulus with increased load of LIT may
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be advantageous for optimizing adaptative responses at a tolerable level of stress, although most
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experimental evidence suggests superior adaptations while adopting a more polarized intensity
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distribution11 with greater training intensification.12
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Therefore, the present study compared the effects of increased load of LIT vs. HIT during an
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8-week intervention period on performance and physiological adaptations in well-trained
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endurance athletes. This was done by matching the increase of LIT and HIT for overall load by
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the training impulse method (TRIMP), in which we hypothesized that more HIT would elicit
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superior VO2max adaptations and thereby greater performance improvements compared to more
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LIT over 8 weeks.
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Methods
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Participants
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Fifty-one (36 men and 15 women; Table 1) national-level junior cross-country skiers and
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biathletes volunteered to participate in the study. All athletes were students at a Norwegian high
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school with a specialized study program for cross-country skiing (n=41) and biathlon (n=10).
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The Regional Committee for Medical and Health Research Ethics waived the requirement for
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ethical approval for this study. Therefore, the ethics of the study are in accordance with the
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institutional requirements, and approval for data security and handling obtained from the
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Norwegian Centre for Research Data (NSD). All athletes were fully informed of the nature of
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the study and its experimental risks before providing written consent. Several athletes (n=21)
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were <18 years, and therefore, the parents were asked to provide parental consent. Some
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athletes dropped out of the study (low-intensity training group [LIG]=2; high-intensity training
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group [HIG]=5) due to sickness (n=3), injury (n=2), or other reasons (n=2). In addition, two
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athletes from LIG were excluded from the final analyses due to lack of 85% compliance with
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the prescribed training.
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**Table 1 around here**
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Design
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Following an 8-week pre-intervention period, the athletes were randomly allocated into either
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a group with increased load of LIT (LIG, n=26) or a group with increased load of HIT (HIG,
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n=25) for an 8-week intervention during their late preparation period (September–November).
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The training was balanced for overall load using a TRIMP score, and groups were matched for
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sport, age, sex, physiological indices, and pre-intervention training characteristics. Both groups
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performed an uphill running time-trial (TT) in the field and were assessed for laboratory
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performance and physiological profiling in treadmill running and roller-ski skating before (pre)
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and after (post) the intervention.
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Methodology
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Pre-intervention period
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Prior to the intervention, all athletes followed an 8-week baseline period consisting of the same
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training guidelines. The athletes were instructed to focus on high-volume LIT interspersed with,
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on average, one weekly MIT and one weekly HIT session. In addition, 2–3 weekly strength or
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speed sessions were integrated into LIT sessions or performed as a single session. Based on
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this, individualized training programs were developed together with the athlete’s personal
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coaches to ensure optimal adjustments of load. The athletes were familiarized with the different
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test protocols before performing all pre-tests during the last week of the pre-intervention period.
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Intervention period
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Training plans during the 8-week intervention period were based on a theoretical framework
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developed by the researchers and adopted to each athlete in close collaboration with coaches.
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The groups increased their overall training load in the intervention period by adopting two
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different training regimes. LIG continued with the same focus as during the pre-intervention
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period, but with increased volume of LIT, whereas HIG changed towards increased frequency
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and volume of HIT with reduced volume of LIT. Weekly mesocycle load was designed with
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three different load structures (high, moderate, and low) for both groups, where the coaches,
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individually adjusted and optimized load for each athlete. Based on previous research 13,14 and
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pilot testing of selected athletes, the use of the training impulse (TRIMP) method was
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incorporated as the most valid method for the matching of training load between groups.
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Accordingly, all within-group mesocycle loads were balanced for overall load (TRIMP)
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between-groups. TRIMP was calculated by multiplying the duration in three intensity zones
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with a weighting factor (i.e., LIT, MIT, and HIT are given a score of 1, 2, and 3, respectively).
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Total TRIMP was then obtained by adding the different intensity zone scores. Distribution of
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MIT and HIT sessions per week together with weekly mesocycle loads for both groups are
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displayed in Figure 1. All athletes were instructed to maintain the same diet and training plans
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were designed to maintain similar volume of strength and speed training during the intervention
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period.
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**Figure 1 around here**
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Training monitoring
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All athletes recorded their own training using an online training diary developed by the
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Norwegian Top Sport Centre (Olympiatoppen) by applying the modified session-goal approach
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(SG/TZ).15 Training intensity distribution was recorded using a five-zone intensity scale but
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reported using a three-zone scale (LIT, MIT, and HIT), which better corresponds with relevant
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literature and underlying physiological mechanisms.16 For MIT and HIT sessions performed as
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intervals, time in the intensity zone of the session was registered from the beginning of the first
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interval to the end of the last interval, including recovery periods. Moreover, strength and speed
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training were registered from the start to the finish of that separate part (e.g., strength, speed,
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plyometrics) during the session, including recovery periods. Training mode is reported as
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specific (classical and skating roller-skiing) and non-specific (running and cycling) endurance
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training. In addition, intensity control was achieved by regular use of heart rate (HR) monitoring
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and [La-] measurements throughout the intervention period.
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Test protocols and measurements
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Training plans were designed to include standardized training load in the last two days prior to
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the first day of testing. The athletes were instructed to follow self-selected preparation
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procedures and not to consume any large meals or caffeinated beverages within the last 2 hours
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before the test. There were always >24 hours between all tests for each athlete. The TT in
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combination with laboratory tests were chosen to obtain a comprehensive understanding of
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performance both in practical and laboratory conditions, as well as the underlying physiological
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mechanisms.
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Uphill running TT (test day 1)
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Prior to the TT, athletes performed a 30-min LIT self-selected warm-up procedure.
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Performance times were recorded using two synchronized watches and the Racesplitter
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timekeeping system (Makalu Logistics Inc, Fontana, USA). The TT was performed on asphalt
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with a total distance of 6.4 km (elevation: 270 m) and 4.5 km (elevation: 160 m) for men and
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women, respectively. Weather conditions were stable during each test day, being partly cloudy
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with low and stable wind, but differed in ambient temperature and humidity between pre and
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post (15 vs. 2 ◦C and 70 vs. 90%, respectively). Due to different reasons, six athletes in LIG
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and one athlete in HIG were not able to perform the TT at both pre and post. Hence, 35 athletes
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were included in the final TT analysis (LIG, 10 men and 5 women; HIG, 14 men and 5 women).
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Laboratory treadmill running test (test day 2)
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Following a 10-min individual running warm-up (60–72% of maximal HR [HRmax]), all athletes
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performed one 5-min submaximal stage running at 10.5% incline and at the same absolute speed
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(8 km·h-1 for men and 7 km·h-1 for women). After a 2-min recovery period, the athletes
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performed an incremental test to exhaustion in order to determine VO2max and performance
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measured as peak treadmill speed ([Vpeak] calculated according to Sandbakk et al .,17). The test
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was performed at 10.5% incline with a 1-km·h-1 increase in speed every minute until voluntary
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exhaustion. Starting speed was set to 9 km·h-1and 8 km·h-1 for men and women, respectively.
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Laboratory treadmill roller-ski skating test (test day 3)
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After a 10-min individual running warm-up (60–72% of HRmax) as on test day 2, the athletes
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completed two 5-min submaximal stages at 5% incline while treadmill roller-ski skating. The
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two stages were performed at the same absolute speed for men (12 and 14 km·h-1) and women
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(10 and 12 km·h-1), with 1-min recovery in between. Following a 5-min recovery period, peak
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oxygen uptake (VO2peak) and performance measured as Vpeak were determined.17 The test was
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performed at 5% incline with a starting speed of 14 and 12 km·h-1 for men and women,
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respectively. The incline was kept constant, while the speed was subsequently increased by 2
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km·h-1 every minute up to 20 km·h-1 for men and 18 km·h-1 for women, and thereafter by 1
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km·h-1 until voluntary exhaustion. The athletes were instructed to use the skating G3 sub-
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technique during the entire test.
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Treadmill running was performed on a 2.5 x 0.7-m motor-driven treadmill and treadmill roller-
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ski skating on a 3.5 x 2.5-m treadmill (RL 2500 and RL 3500E, Rodby, Vänge, Sweden). For
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all submaximal testing, respiratory recordings were collected between the third and fourth
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minute of each 5-min stage and HR defined as the average over the last 30 s. Respiratory
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variables were measured using open-circuit indirect calorimetry with mixing chamber (Oxycon
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Pro, Jaeger GmbH, Hoechberg, Germany) and HR by a Garmin Forerunner 935 (Garmin Ltd.,
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Olathe, KS, USA). Rate of perceived exertion (RPE) using the 6–20-point Borg scale and [La]
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were taken from the fingertip directly after completing each stage. [La-] was measured using
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the stationary Biosen C-Line lactate analyzer (Biosen, EKF Industrial Electronics, Magdeburg,
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Germany). In addition, gross efficiency was measured for the submaximal roller-ski stages and
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defined as the ratio of work and metabolic rate.18 For the incremental test to exhaustion,
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respiratory variables and HR were measured continuously, and VO2max/peak defined as the
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highest 1-min average. HRmax was defined as the highest 5-sec HR measurement, whereas RPE
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was determined directly after, and [La-] approximately 1 min after.
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Statistical analysis
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All data are reported as means ± standard deviations (SD). Assumption of normality was tested
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with a Shapiro–Wilk test in combination with visual inspection of histograms. Adopted from
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previous literature,19,20 individual response magnitudes were summarized in three different
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categories: nonresponse defined as <0% change, moderate response as 0% to 5% change, and
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large response as >5% change. An adaptation index for each athlete was also calculated as the
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mean of the percentage change in treadmill running VO2max and Vpeak, treadmill roller-ski
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skating VO2peak and Vpeak from pre- to post.20 To test for differences between groups, a
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univariate general linear model (GLM) analysis of covariance (ANCOVA) was used, with the
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percentage change from pre- to post as the dependent variable, and baseline values as a
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covariate to adjust for possible between-group differences pre-intervention. Pre- to post
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changes within groups were assessed using a paired-samples t-test. Between-group differences
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in baseline and training characteristics were tested using an independent-samples t-test. Effect
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size (ES) was calculated as Cohen’s d by using the mean pre- to post change between groups,
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divided by the pooled pre-test SD (interpreted as follows: 0.0–0.24 trivial, 0.25–0.49 small,
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0.5–1.0 moderate, >1.0 large).21 For all comparisons, statistical significance was set at an alpha
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level of p<0.05, and p=0.05–0.1 indicated trends. All data analyses were conducted using SPSS
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26.0 (SPSS Inc, Chicago, IL, United States).
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Results
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Training characteristics
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Comparisons of training characteristics between groups are shown in Table 2. Weekly TRIMP
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during the pre-intervention and intervention periods did not differ between groups (p=0.60 and
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p=0.93, respectively), whereas the training intensity distribution shifted from having a similar
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pattern across groups during the pre-intervention to clearly differing during the intervention.
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During the intervention period, LIG performed 16% more endurance training hours compared
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to HIG (p<0.01), due to 25% more hours of LIT (p<0.01). HIG performed 118% more hours of
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HIT compared to LIG (p<0.01), whereas hours of MIT did not differ between groups (p=0.35).
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The volume of strength and speed training performed during the intervention period did not
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differ between groups (p=0.67 and 0.23, respectively).
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**Table 2 around here**
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Baseline characteristics and body mass
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There were no differences between groups in age, anthropometrics, or any performance or
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physiological indices before the intervention. There were no between-group differences in body
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mass changes (p=0.12), although an increase was observed in HIG (1.9±2.2%, p<0.01) but not
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in LIG (0.5±2.1%, p=0.19).
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Performance adaptations
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There were no between-group differences in running TT performance changes (p=0.44), but
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HIG improved by -2.3±3.2% (p=0.01), with no change in LIG (-1.5±2.9%, p=0.20). The
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individual response magnitudes for TT performance changes are shown in Figure 2. The
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changes in treadmill running Vpeak did not differ between groups (p=0.30) but were improved
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in HIG (2.2±3.1%, p<0.01), with a corresponding non-change in LIG (1.4±4.2%, p=0.18, Table
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3). Treadmill roller-ski skating Vpeak changes did not differ between groups (p=0.20) but were
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improved within both LIG and HIG (1.5±2.4% and 2.5±3.4%, respectively, both p<0.01).
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**Figure 2 around here**
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**Table 3 around here**
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Physiological adaptations
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There was a between-group difference in treadmill running VO2max changes (p=0.04, Table 3),
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tending to improve in HIG (3.0±6.4%, p=0.09), with a corresponding non-change in LIG (-
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0.7±4.6%, p=0.25). There were no between-group differences in submaximal adaptations
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running at absolute speeds, although trivial to small effects of reduced RER, HR, %HRmax, and
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RPE in HIG vs. LIG were found (see Table 3 for all details).
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The change in treadmill roller-ski skating VO2peak was different between groups (p=0.02), with
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improvements in HIG (3.6±5.4%, p=0.01) and a corresponding non-change in LIG (-0.1±4.0%,
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p=0.62). Overall, positive submaximal adaptations (i.e., %VO2max, RER, %HRmax, and RPE) in
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roller-ski skating at absolute speeds were found in HIG and not in LIG, although gross
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efficiency was improved in both groups (see Table 4 for all details). Individual response
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magnitudes for Vpeak and VO2max/peak in treadmill running and roller-ski skating are presented in
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Figure 3, while Figure 4 shows the adaptation index for each athlete in LIG and HIG.
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**Table 4 around here**
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**Figure 3 around here**
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**Figure 4 around here**
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Discussion
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The present study compared the effects of increased load of LIT vs. HIT on performance and
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physiological adaptations in well-trained endurance athletes. The main findings were that
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performance adaptations, including uphill running TT performance and peak speed when
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incremental running and roller-ski skating to exhaustion in the laboratory, did not differ
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significantly between the two groups progressing their training with different endurance
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training intensities. However, while both groups improved their performance, increased load of
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HIT elicited 3–4% greater changes in running VO2max and roller-ski skating VO2peak compared
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to increased load of LIT.
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In contrast to most previous intervention studies where endurance training load is matched for
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total work or oxygen consumption,7-9 the present approach induced a similar increase in TRIMP
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load when progressing the overall training stimulus for both groups.22,23 Accordingly, a
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significant between-group difference in LIT and HIT load was achieved while obtaining similar
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training loads. Although the intervention per se was regarded as successful because most
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athletes improved their performance, there are potential limitations with this approach caused
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by, e.g., between-athlete variations in adaptive signaling and stress tolerance to LIT and HIT
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training. In addition, this approach does not consider variations in metabolic vs. neuromuscular
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load between different training modalities (e.g., running vs. XC skiing). Although there was a
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change towards more specific training in the intervention period compared to baseline training,
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these changes were non-significant and similar between-groups. Accordingly, the design could
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be regarded valid for the purpose of the study.
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With such matching of training load progression, the present study found little or no effects on
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performance adaptations in running or roller-ski skating when increasing the load of LIT vs.
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HIT in well-trained endurance athletes. Although the individual response magnitudes indicated
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more positive performance adaptations in HIG, the present statistical findings are in contrast to
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those of Stöggl and Sperlich11 and Vesterinen et al.,24 who demonstrated superior performance
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adaptations of a more polarized intensity distribution with greater HIT load compared to high-
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volume LIT regimes. However, Ingham et al.25 and Nuuttila et al.26 found similar performance
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adaptations of high-volume LIT and HIT regimes, which is in line with the present findings and
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implies that similar performance progression can be achieved both by increased load of LIT
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and HIT during the preparation period in endurance athletes.
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In accordance with the hypothesis, increased load of HIT led to 3–4% better VO2max adaptations
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in running and roller-ski skating compared to increased load of LIT. These findings were
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strengthened by the greater individual response magnitudes and adaptation index as well as
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better submaximal adaptations (e.g., reduced HR) at absolute speeds in HIG. Better VO2max
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adaptations in HIG are likely explained by increased O2 delivery capacity,5,6,12 supported by
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other short-term training intensification studies.7-9 This argues that even when matching
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training load with a more ecologically valid method as employed here, a high HIT stimulus
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seems needed to stress the cardiovascular system sufficiently and will thereby increase VO2max
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more than when compensating with increased load of LIT.5,12 Still, only trivial to small effects
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in the differences in physiological adaptations were found, which is likely explained by the
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relatively high training status and the short intervention period.27-29 Altogether, progressing the
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overall training stimulus by intensification seems favorable if the goal is to elicit VO2max
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adaptations over a relatively short training period in well-trained endurance athletes. To what
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extent these adaptations can be transferred also to performance benefits over a longer timescale
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requires further examination.
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The individual response magnitudes revealed that some athletes in LIG also improved their
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VO2max to the same extent as HIG, indicating individual variations in how athletes respond to
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different endurance training in eliciting VO2max.24,30 The present sample of athletes, including
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both sexes and different initial levels, could in part have contributed to the subsequent variations
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in training response. However, the groups were matched for sex and physiological indices pre-
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intervention, and baseline values were adjusted for as a covariate in the statistical analysis. In
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this context, no significant sex-differences in any performance or physiological adaptations
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were found. Accordingly, the present group comparisons are likely valid, although future
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studies should further investigate individual responses to changes in training volume and
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intensity distribution, as well as overall load adjustments in endurance athletes.
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It seems obvious that improved VO2max had a positive effect on performance adaptations in
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HIG. However, the reasons for improved performance in LIG without improving VO2max could
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be explained by increased fractional utilization of VO2max (i.e., anaerobic threshold). In this
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context, an interesting feature is that the number of LIT sessions above 2.5 hours in LIG might
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have provided a different stimulus for adaptive signaling than shorter LIT sessions.
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Accordingly, the hypothesis was that LIT and HIT induce complementary adaptations, which
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is partly induced through different molecular pathways.1,5 However, this remains speculative
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as muscle biopsies or other measures to examine underlying mechanisms were not included in
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the present design.
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Practical applications
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The data presented in this study provide novel information with relevance for optimizing the
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training volume and intensity distribution in periods when the overall training stimulus is
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progressed in endurance athletes. The present data indicate that performance progression can
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be achieved both by increased load of LIT and HIT, although a sufficient HIT stimulus seems
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to be beneficial for eliciting maximal energy delivery capacities in 8 weeks. However, the more
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long-term effects and the effect of different periodization models of LIT and HIT focus prior to
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the competition period require further attention in future studies.
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Conclusions
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The present study found no significant difference in performance adaptations in running or
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roller-ski skating during 8 weeks of increased load of LIT vs. HIT in well-trained endurance
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athletes, although both methods improved performance. However, increased load of HIT
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elicited better VO2max adaptations compared to increased load of LIT.
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Acknowledgements
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The authors would like to thank the athletes and their coaches for their enthusiastic cooperation
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and participation in the study. Particular gratitude is directed to Lars Jonatan Engdahl, Johan
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Persson, and Henek Tomson for their help with collecting laboratory data. Moreover, the
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authors would like to thank Knut Skovereng and Guro Strøm Solli for valuable comments on
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the manuscript. The study is funded by Meråker High School and the Research Council of
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Norway (RCN) (project no. 298645).
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References
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1. Seiler S. What is best practice for training intensity and duration distribution in
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endurance athletes? International journal of sports physiology and performance.
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2010;5(3):276-291.
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Figure legends
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Figure 1 – Training program for 8 weeks of (A) low-intensity training group and (B) high-
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intensity training group, including weekly distribution of moderate- (MIT) and high-intensity
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training (HIT) sessions and overall training load (TRIMP) within three different mesocycle
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loads (low, moderate, and high)
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Figure 2 – Individual response magnitude for pre- to post changes in uphill running time trial
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performance summarized in three different categories: nonresponse (white), <0% change;
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moderate response (grey), 0–5% change; and large response (black) >5% change
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Figure 3 – Individual response magnitude for pre- to post changes summarized in three
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different categories: nonresponse (white), <0% change; moderate response (grey), 0–5%
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change; and large response (black) >5% change. (A) Maximal oxygen uptake in treadmill
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running, (B) peak speed in treadmill running, (C) peak oxygen uptake in treadmill roller-ski
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skating, (D) peak speed in treadmill roller-ski skating
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Figure 4 – Adaptation index for each individual athlete in (A) low-intensity training group and
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(B) high-intensity training group, calculated as the mean of the percentage change in maximal
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oxygen uptake and peak speed in treadmill running and peak oxygen uptake and peak speed in
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treadmill roller-ski skating from pre- to post
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Table 1. Baseline characteristics of the 51 well-trained endurance athletes participating in the
study (mean ± SD)
Variables
Men (n = 36)
Women (n = 15)
Total (n = 51)
Age (y)
17 ± 1
17 ± 0
18 ± 1
Body height (cm)
181.3 ± 0.7
167.2 ± 3.6
177.1 ± 8.2
Body mass (kg)
72.7 ± 7.1
62.0 ± 5.4
69.6 ± 8.2
Body mass index (kg·m-2)
22.1 ± 1.6
22.2 ± 2.2
22.1 ± 1.8
RUN-VO2max (L·min-1)
5.08 ± 0.56
3.48 ± 0.35
4.59 ± 0.90
RUN-VO2max (mL·min-1·kg-1)
70.3 ± 4.5
56.0 ± 3.4
65.9 ± 7.8
SKATE-VO2peak (L·min-1)
4.86 ± 0.55
3.32 ± 0.36
4.41 ± 0.86
SKATE-VO2peak (mL·min-1·kg-1)
66.8 ± 4.9
53.7 ± 3.9
62.9 ± 7.6
Annual training volume (h y-1)
529 ± 95
493 ± 103
511 ± 99
RUN-VO2max, maximal oxygen uptake in running; SKATE-VO2peak, peak oxygen uptake in
roller-ski skating.
14
599
600
601
602
Table 2. Training characteristics during an 8-week baseline and 8-week intervention period among 42 well-
trained endurance athletes, randomized into either LIG or HIG (mean ± SD)
8-week baseline period
8-week intervention period
LIG (n=22)
HIG (n=20)
LIG (n=22)
HIG (n=20)
Training forms
Training volume (h)
97.0 ± 14.2
96.3 ± 18.1
108.7 ± 10.7*
94.8 ± 11.6#
Sessions (n)
60.7 ± 8.1
61.2 ± 9.9
67.0 ± 5.6*
67.0 ± 7.1*
Sickness/injury (d)
1.3 ± 2.6
0.6 ± 1.6
1.8 ± 2.8
1.7 ± 2.7
Training forms
Endurance (h)
87.0 ± 12.9
84.7 ± 19.1
95.6 ± 9.3*
82.5 ± 10.4#
Strength (h)
7.7 ± 3.3
8.4 ± 1.8
9.0 ± 2.2
8.8 ± 2.0
Speed (h)
2.3 ± 1.1
3.2 ± 0.9#
4.1 ± 2.1
3.5 ± 1.0
Training mode
Specific (h)a
40.5 ± 13.4
41.3 ± 9.6
52.6 ± 8.6*
43.7 ± 9.4
Non-specific (h)b
45.1 ± 9.2
43.2 ± 9.5
43.0 ± 7.9
38.8 ± 9.0
Specific/non-specific (%)
47/53
49/51
55/45
53/47
Endurance training volume
Compliance (%TRIMP)
NaN
NaN
98 ± 9
100 ± 7
Load (TRIMP/wk)
729 ± 98
725 ± 157
781 ± 80*
779 ± 87
Load (TRIMP)
5831 ± 781
5804 ± 1257
6249 ± 640*
6230 ± 696
LIT load (TRIMP)
4649 ± 630
4586 ± 1121
5092 ± 587*
4303 ± 665#
MIT load (TRIMP)
489 ± 214
258 ± 237
434 ± 69
403 ± 122
HIT load (TRIMP)
703 ± 269
760 ± 204
723 ± 133
1523 ± 193*#
LIT (h)
78.8 ± 11.7
76.3 ± 18.8
88.0 ± 9.1*
70.4 ± 10.0#
MIT (h)
4.2 ± 1.8
3.8 ± 2.0
3.6 ± 0.6
3.4 ± 1.0
HIT (h)
4.0 ± 1.5
3.8 ± 1.3
4.0 ± 0.7
8.7 ± 1.0*#
LIT/MIT/HIT (%)
90/5/5
90/5/5
92/4/4
85/4/11
Endurance training sessions
LIT (n)
39.9 ± 4.8
37.9 ± 7.0
44.9 ± 4.1*
37.1 ± 5.6#
LIT sessions ≥150 min (n)
7.1 ± 2.2
6.7 ± 2.3
10.3 ± 2.2*
2.3 ± 1.4*#
MIT (n)
5.6 ± 2.2
6.1 ± 2.4
4.9 ± 0.8
4.1 ± 1.1*#
HIT (n)
7.1 ± 2.2
8.6 ± 1.7
6.8 ± 1.0
15.6 ± 1.7*#
LIT/MIT/HIT (%)
76/11/13
72/11/16
80/9/11
65/7/28
LIG, low-intensity training group; HIG, high-intensity training group; LIT, low-intensity training; MIT,
moderate-intensity training; HIT, high-intensity training. Compliance is calculated as percent of total TRIMP
in relation to total TRIMP prescribed. a classical and skating roller skiing; b running and cycling.
*Significantly different from baseline period (*p<0.05) #Significantly different from LIG (#p<0.05).
15
603
604
605
Table 3. Anthropometrics and TT performance as well as performance and physiological indices during treadmill running at pre- and
post-intervention in 42 well-trained endurance athletes, randomized into either LIG or HIG (mean ± SD)
LIG (n=22)
HIG (n=20)
LIG vs. HIG
Pre
Post
Pre
Post
ES
Anthropometrics
Body mass (kg)
70.8 ± 7.5
71.2 ± 8.0
67.5 ± 7.9
68.8 ± 7.7*
0.10
Body mass index (kg·m-2)
22.5 ± 1.6
22.6 ± 1.6
21.4 ± 1.6
21.8 ± 1.6*
0.19
TT performance (4.5/6.4-km)
Mean finishing time (s)
27:14
26:49
28:06
27:31
0.06
RUN submaximal (7/8-km·h-1)
VO2 (L·min-1)
3.28 ± 0.46
3.20 ± 0.45
3.13 ± 0.43
3.16 ± 0.44*#
0.22
VO2 in % VO2max
70.9 ± 6.2
69.9 ± 6.2
69.7 ± 5.5
68.3 ± 4.6
0.07
RER
0.91 ± 0.04
0.91 ± 0.03
0.92 ± 0.05
0.90 ± 0.03*
0.75
HR (beats·min-1)
167 ± 12
165 ± 11
164 ± 10
160 ± 8
0.27
HR in %HRmax
83.2 ± 4.8
82.2 ± 4.7
82.9 ± 4.2
80.5 ± 4.1
0.29
Borg (6-20)
12.7 ± 1.3
12.4 ± 1.6
12.8 ± 1.4
12.2 ± 1.1
0.21
[La-] (mmol·L-1)
2.12 ± 0.84
1.90 ± 0.58
2.27 ± 0.90
2.02 ± 0.74*
0.03
RUN TTE
VO2max (L·min-1)
4.68 ± 0.92
4.63 ± 0.83
4.54 ± 0.80
4.64 ± 0.81#
0.18
VO2max (mL·min-1·kg-1)
65.7 ± 7.6
64.7 ± 6.3
66.7 ± 7.1
67.4 ± 6.2#
0.22
RER
1.13 ± 0.04
1.15 ± 0.04
1.14 ± 0.05
1.14 ± 0.04
0.30
HRmax (beats·min-1)
199 ± 6
199 ± 7
197 ± 9
197 ± 8
0.02
[La-] (mmol·L-1)
11.02 ± 1.49
11.57 ± 1.91
11.48 ± 1.78
11.92 ± 1.88
0.06
TTE (s)
350 ± 63
360 ± 57
359 ± 55
381 ± 45*
0.36
Vpeak (km·h-1)
14.5 ± 1.4
14.7 ± 1.3
14.8 ± 1.2
15.1 ± 1.1*
0.10
TT, time trial; LIG, low-intensity training group; HIG, high-intensity training group; ES, effect size; RUN, laboratory test running; VO2,
oxygen uptake; VO2max, maximal oxygen uptake; HR, heart rate; HRmax, maximal heart rate; [La-], blood lactate; RER, respiratory
exchange ratio; TTE, time to exhaustion; Vpeak, peak velocity. *Significantly different from pre (*p< 0.05). #Significantly different from
pre- to post change in LIG (#p<0.05).
16
Table 4. Performance and physiological indices obtained during treadmill roller-ski skating at pre and post-intervention in 42 well-trained
endurance athletes, randomized into either LIG or HIG (mean ± SD)
LIG (n=22)
HIG (n=20)
LIG vs. HIG
Pre
Post
Pre
Post
ES
SKATE submaximal (10/12-km·h-1)
VO2 (L·min-1)
3.19 ± 0.51
3.12 ± 0.49*
3.05 ± 0.42
3.03 ± 0.39
0.10
VO2 in % VO2peak
71.8 ± 5.3
70.3 ± 4.4*
71.6 ± 5.9
68.8 ± 4.7*
0.29
RER
0.93 ± 0.03
0.91 ± 0.03
0.95 ± 0.05
0.94 ± 0.03*
0.13
HR (beats·min-1)
173 ± 10
173 ± 9
170 ± 10
167 ± 9*#
0.32
HR in %HRmax
86.4 ± 4.2
86.5 ± 3.3
86.2 ± 3.8
84.5 ± 3.4*#
0.40
Borg (6-20)
11.2 ± 1.9
11.6 ± 1.8
11.9 ± 1.2
11.8 ± 1.7
0.44
[La-] (mmol·L-1)
2.72 ± 0.91
2.79 ± 0.77
3.06 ± 1.21
2.82 ± 0.77
0.27
GE (%)
13.8 ± 0.6
14.2 ± 0.6*
13.9 ± 0.8
14.3 ± 0.6*
0.08
SKATE submaximal (12/14-km·h-1)
VO2 (L·min-1)
3.57 ± 0.55
3.52 ± 0.52
3.44 ± 0.47
3.42 ± 0.43
0.08
VO2 in % VO2peak
80.6 ± 5.6
79.5 ± 4.5
80.7 ± 4.8
77.6 ± 4.9*#
0.41
RER
0.96 ± 0.04
0.95 ± 0.03
0.97 ± 0.03
0.96 ± 0.04*
0.15
HR (beats·min-1)
184 ± 9
183 ± 7
180 ± 11
178 ± 9*
0.12
HR in %HRmax
92.0 ± 3.2
91.5 ± 2.2
91.4 ± 3.7
90.3 ± 3.0*
0.17
Borg (6-20)
14.4 ± 1.3
14.1 ± 1.4
14.6 ± 1.2
13.9 ± 1.2*
0.31
[La-] (mmol·L-1)
4.11 ± 1.37
4.09 ± 1.11
4.28 ± 2.01
4.17 ± 1.27
0.05
GE (%)
14.3 ± 0.6
14.6 ± 0.3*
14.4 ± 0.7
14.7 ± 0.6*
0.01
SKATE TTE
VO2peak (L·min-1)
4.48 ± 0.89
4.46 ± 0.84
4.30 ± 0.72
4.43 ± 0.67*#
0.18
VO2peak (mL·min-1·kg-1)
62.8 ± 7.0
62.5 ± 6.5
63.4 ± 6.7
64.4 ± 5.8#
0.18
RER
1.11 ± 0.05
1.11 ± 0.04
1.11 ± 0.05
1.11 ± 0.05
0.01
HRpeak (beats·min-1)
198 ± 7
199 ± 7
196 ± 8
196 ± 7
0.10
[La-] (mmol·L-1)
10.84 ± 1.66
11.16 ± 2.17
10.78 ± 1.60
10.92 ± 1.83
0.12
TTE (s)
281 ± 56
299 ± 56*
292 ± 71
322 ± 58*
0.18
Vpeak (km·h-1)
21.0 ± 1.6
21.3 ± 1.6*
21.4 ± 1.8
21.9 ± 1.6*
0.11
LIG, low-intensity training group; HIG, high-intensity training group; ES, effect size; SKATE, laboratory test roller-ski skating; VO2,
oxygen uptake; VO2peak, peak oxygen uptake; HR, heart rate; HRpeak, peak heart rate; [La-], blood lactate; GE, gross efficiency; RER,
respiratory exchange ratio; TTE, time to exhaustion; Vpeak, peak velocity; *Significantly different from pre (*p< 0.05). #Significantly
different from pre- to post change in LIG (#p<0.05).
17
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Figure 2.
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Figure 1.
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