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Purpose: To compare the effects of increased load of low- versus high-intensity endurance training on performance and physiological adaptations in well-trained endurance athletes. Methods: Following an 8-week preintervention period, 51 (36 men and 15 women) junior cross-country skiers and biathletes were randomly allocated into a low-intensity (LIG, n = 26) or high-intensity training group (HIG, n = 25) for an 8-week intervention period, load balanced using the overall training impulse score. Both groups performed an uphill running time trial and were assessed for laboratory performance and physiological profiling in treadmill running and roller-ski skating preintervention and postintervention. Results: Preintervention to postintervention changes in running time trial did not differ between groups (P = .44), with significant improvements in HIG (-2.3% [3.2%], P = .01) but not in LIG (-1.5% [2.9%], P = .20). There were no differences between groups in peak speed changes when incremental running and roller-ski skating to exhaustion (P = .30 and P = .20, respectively), with both modes being significantly improved in HIG (2.2% [3.1%] and 2.5% [3.4%], both P < .01) and in roller-ski skating for LIG (1.5% [2.4%], P < .01). There was a between-group difference in running maximal oxygen uptake changes (P = .04), tending to improve in HIG (3.0% [6.4%], P = .09) but not in LIG (-0.7% [4.6%], P = .25). Changes in roller-ski skating peak oxygen uptake differed between groups (P = .02), with significant improvements in HIG (3.6% [5.4%], P = .01) but not in LIG (-0.1% [0.17%], P = .62). Conclusion: There was no significant difference in performance adaptations between increased load of low- versus high-intensity training in well-trained endurance athletes, although both methods improved performance. However, increased load of high-intensity training elicited better maximal oxygen uptake adaptations compared to increased load of low-intensity training.
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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 (SeptemberNovember).
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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, 23 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 athletes 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 (6072% 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 (6072% 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 620-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 ShapiroWilk 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: 0.00.24 trivial, 0.250.49 small,
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0.51.0 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=0.050.1 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 34% 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 34% 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
432
athletes, although both methods improved performance. However, increased load of HIT
433
elicited better VO2max adaptations compared to increased load of LIT.
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435
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Acknowledgements
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The authors would like to thank the athletes and their coaches for their enthusiastic cooperation
438
and participation in the study. Particular gratitude is directed to Lars Jonatan Engdahl, Johan
439
Persson, and Henek Tomson for their help with collecting laboratory data. Moreover, the
440
authors would like to thank Knut Skovereng and Guro Strøm Solli for valuable comments on
441
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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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), 05% 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), 05%
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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)
Age (y)
17 ± 1
17 ± 0
Body height (cm)
181.3 ± 0.7
167.2 ± 3.6
Body mass (kg)
72.7 ± 7.1
62.0 ± 5.4
Body mass index (kg·m-2)
22.1 ± 1.6
22.2 ± 2.2
RUN-VO2max (L·min-1)
5.08 ± 0.56
3.48 ± 0.35
RUN-VO2max (mL·min-1·kg-1)
70.3 ± 4.5
56.0 ± 3.4
SKATE-VO2peak (L·min-1)
4.86 ± 0.55
3.32 ± 0.36
SKATE-VO2peak (mL·min-1·kg-1)
66.8 ± 4.9
53.7 ± 3.9
Annual training volume (h y-1)
529 ± 95
493 ± 103
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
ES
Anthropometrics
Body mass (kg)
70.8 ± 7.5
71.2 ± 8.0
67.5 ± 7.9
0.10
Body mass index (kg·m-2)
22.5 ± 1.6
22.6 ± 1.6
21.4 ± 1.6
0.19
TT performance (4.5/6.4-km)
Mean finishing time (s)
27:14
26:49
28:06
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
0.22
VO2 in % VO2max
70.9 ± 6.2
69.9 ± 6.2
69.7 ± 5.5
0.07
RER
0.91 ± 0.04
0.91 ± 0.03
0.92 ± 0.05
0.75
HR (beats·min-1)
167 ± 12
165 ± 11
164 ± 10
0.27
HR in %HRmax
83.2 ± 4.8
82.2 ± 4.7
82.9 ± 4.2
0.29
Borg (6-20)
12.7 ± 1.3
12.4 ± 1.6
12.8 ± 1.4
0.21
[La-] (mmol·L-1)
2.12 ± 0.84
1.90 ± 0.58
2.27 ± 0.90
0.03
RUN TTE
VO2max (L·min-1)
4.68 ± 0.92
4.63 ± 0.83
4.54 ± 0.80
0.18
VO2max (mL·min-1·kg-1)
65.7 ± 7.6
64.7 ± 6.3
66.7 ± 7.1
0.22
RER
1.13 ± 0.04
1.15 ± 0.04
1.14 ± 0.05
0.30
HRmax (beats·min-1)
199 ± 6
199 ± 7
197 ± 9
0.02
[La-] (mmol·L-1)
11.02 ± 1.49
11.57 ± 1.91
11.48 ± 1.78
0.06
TTE (s)
350 ± 63
360 ± 57
359 ± 55
0.36
Vpeak (km·h-1)
14.5 ± 1.4
14.7 ± 1.3
14.8 ± 1.2
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
ES
SKATE submaximal (10/12-km·h-1)
VO2 (L·min-1)
3.19 ± 0.51
3.12 ± 0.49*
3.05 ± 0.42
0.10
VO2 in % VO2peak
71.8 ± 5.3
70.3 ± 4.4*
71.6 ± 5.9
0.29
RER
0.93 ± 0.03
0.91 ± 0.03
0.95 ± 0.05
0.13
HR (beats·min-1)
173 ± 10
173 ± 9
170 ± 10
0.32
HR in %HRmax
86.4 ± 4.2
86.5 ± 3.3
86.2 ± 3.8
0.40
Borg (6-20)
11.2 ± 1.9
11.6 ± 1.8
11.9 ± 1.2
0.44
[La-] (mmol·L-1)
2.72 ± 0.91
2.79 ± 0.77
3.06 ± 1.21
0.27
GE (%)
13.8 ± 0.6
14.2 ± 0.6*
13.9 ± 0.8
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
0.08
VO2 in % VO2peak
80.6 ± 5.6
79.5 ± 4.5
80.7 ± 4.8
0.41
RER
0.96 ± 0.04
0.95 ± 0.03
0.97 ± 0.03
0.15
HR (beats·min-1)
184 ± 9
183 ± 7
180 ± 11
0.12
HR in %HRmax
92.0 ± 3.2
91.5 ± 2.2
91.4 ± 3.7
0.17
Borg (6-20)
14.4 ± 1.3
14.1 ± 1.4
14.6 ± 1.2
0.31
[La-] (mmol·L-1)
4.11 ± 1.37
4.09 ± 1.11
4.28 ± 2.01
0.05
GE (%)
14.3 ± 0.6
14.6 ± 0.3*
14.4 ± 0.7
0.01
SKATE TTE
VO2peak (L·min-1)
4.48 ± 0.89
4.46 ± 0.84
4.30 ± 0.72
0.18
VO2peak (mL·min-1·kg-1)
62.8 ± 7.0
62.5 ± 6.5
63.4 ± 6.7
0.18
RER
1.11 ± 0.05
1.11 ± 0.04
1.11 ± 0.05
0.01
HRpeak (beats·min-1)
198 ± 7
199 ± 7
196 ± 8
0.10
[La-] (mmol·L-1)
10.84 ± 1.66
11.16 ± 2.17
10.78 ± 1.60
0.12
TTE (s)
281 ± 56
299 ± 56*
292 ± 71
0.18
Vpeak (km·h-1)
21.0 ± 1.6
21.3 ± 1.6*
21.4 ± 1.8
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).
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... At the same time, athletes need to monitor changes in the anaerobic threshold closely. 8 Coaches consider the relationship between individual lactate threshold and exercise intensity, duration, training level, glycogen content, and hypoxia as the basis for formulating and revising training plans. Athletes increase the lactate threshold by adding anaerobic threshold intensity training to their daily training. ...
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Cross-country (XC) skiing is an Olympic Winter sport combining upper-and lower-body work to cross varied terrain in endurance competitions lasting from multiple ∼3 min (∼1.3–1.8 km) efforts in the sprint discipline to more than 2 hours (≤50 km) in the longest distance competitions. Over the last decades, retrospective training analyses of world-class XC skiers combined with more experimental designs have led to a well-developed theoretical framework of endurance training in XC skiing, although there is an ongoing discussion on how training volume and intensity should be progressed throughout the preparation period to optimize performance development. These training methods have elicited some of the highest maximal oxygen uptake (VO2max) values reported in the literature, with concurrent high peak oxygen uptakes (VO2peak) within the main sub-techniques of the skating and classical technique. In this context, it would be interesting to understand how athletes originating from other endurance sports would progress their VO2max/VO2peak values, in addition to improving their technique and efficiency, while transferring to XC skiing and adopting these training methods. Accordingly, the overall objectives of the present dissertation were to: (1) investigate both the short-term and more subsequent effects of increased low (LIT)- vs. high-intensity endurance training (HIT) on performance and physiological adaptations in the preparation period of junior XC skiers (study I-II), and (2) investigate the influence of adopting state-of-the-art training methods in XC skiing to endurance athletes originating from other sports in a talent transfer program (study III-IV). Studies I-II are based on a randomized, experimental design which investigated the effects of increased load of LIT vs. HIT during an 8-week intervention (simulating general preparation period) followed by 5 weeks of standardized training with similar intensity distribution (simulating specific preparation period), and thereafter 14 weeks of self-chosen training and competitions (competition period) in junior XC skiers. Study I demonstrated that performance adaptations, including uphill running time-trial performance and peak speed when incremental running and roller-ski skating to exhaustion in the laboratory, did not differ significantly between the two groups. However, increased HIT elicited ~3-4% greater changes in VO2max running and VO2peak roller-ski skating compared to increased LIT. Study II was a follow-up study, demonstrating that the observed differences in physiological adaptations between the two groups during the 8-week intervention were outbalanced following 5 weeks of standardized training with similar intensity distribution across groups. Lastly, no further changes in any performance or physiological indices neither within nor between groups were found 14 weeks into the subsequent competition period. Studies III-IV are based on a prospective, observational design investigating the development of performance, physiological, and technical indices of endurance athletes (i.e. runners, kayakers, and rowers) transferring to XC skiing during a talent transfer program. Study III demonstrated that the 6-month training period elicited large improvements in sport-specific performance indices (i.e. roller-ski skating and double-poling ergometry), whereas performance indices in a general mode (i.e. running) were unchanged. Improvements in sport-specific performance indices were coincided by better skiing efficiency/work economy and longer cycle lengths while roller-ski skating, as well as increased upper-body one-repetition maximum-strength (1RM) in ski-specific exercises. However, no changes in VO2max running and VO2peak roller-ski skating and double-poling ergometry were found at a group level. Moreover, larger development in sport-specific performance indices were found in runners compared to kayakers/rowers, which coincided with improved VO2peak and overall better physiological adaptations in roller-ski skating. Study IV was a follow-up study, comparing high- and low-performance responders to the 6-month training period using a multidisciplinary approach. Here, high-responders demonstrated superior physiological adaptations both at submaximal and maximal workloads (e.g. power at 4 mmol·L-1 and VO2max running and VO2peak roller-ski skating) than low-responders. These findings were coincided with higher training loads, greater perceived effort during sessions, and lower incidents of injury and illness during the 6-month period in comparison to their lower-responding counterparts. Lastly, qualitative interviews with the athletes coaches highlighted that greater motivation and passion for XC skiing together with the ability to build a strong coach-athlete relationship separated high- from low-responders. Conclusively, the present dissertation demonstrates that performance development can successfully be achieved both by increased low- and high-intensity endurance training during the preparation period in XC skiers, although increased high-intensity training may provide short-term benefits for maximal aerobic energy turnover. However, these different ways of progressing training load had little or no effects on the subsequent performance and physiological development following a period of similar training regimes. Moreover, adopting the theoretical framework of training (i.e. state-of-the-art) in XC skiing on endurance athletes (i.e. runners, kayakers, and rowers) transferring to XC skiing elicits large sport-specific performance improvements, while improvements in aerobic energy turnover were limited. Here, the athletes with largest development had a background from running and the ability to concurrently develop high aerobic energy turnover rates together with skiing efficiency, cycle length, and upper-body specific strength. However, a more long-term approach than employed in the present studies is clearly needed to reach a high international level in XC skiing following talent transfer. Overall, the present data provides novel understanding of both the short-term and more subsequent effects of progressing endurance training volume and intensity in XC skiing, as well as the effects of applying state-of the-art XC skiing training to endurance athletes originating from other sports.
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Purpose: To investigate how the effects of increased low- versus high-intensity endurance training in an 8-week intervention influenced the subsequent development of performance and physiological indices in cross-country skiers. Methods: Forty-four (32 men and 12 women) junior cross-country skiers were randomly assigned into a low-intensity training group (LITG, n = 20) or high-intensity training group (HITG, n = 24) for an 8-week intervention followed by 5 weeks of standardized training with similar intensity distribution, and thereafter 14 weeks of self-chosen training. Performance and physiological indices in running and in roller-ski skating were determined preintervention, after the intervention, and after the standardized training period. Roller-ski skating was also tested after the period of self-chosen training. Results: No between-groups changes from preintervention to after the standardized training period were found in peak speed when incremental running and roller-ski skating (P = .83 and .51), although performance in both modes was improved in the LITG (2.4% [4.6%] and 3.3% [3.3%], P < .05) and in roller-ski skating for HITG (2.6% [3.1%], P < .01). While improvements in maximal oxygen consumption running and peak oxygen uptake roller-ski skating were greater in HITG than in LITG from preintervention to after the intervention, no between-groups differences were found from preintervention to after the standardized training period (P = .50 and .46), although peak oxygen uptake in roller-ski skating significantly improved in HITG (5.7% [7.0%], P < .01). No changes either within or between groups were found after the period of self-chosen training. Conclusions: Differences in adaptations elicited by a short-term intervention focusing on low- versus high-intensity endurance training had little or no effect on the subsequent development of performance or physiological indices following a period of standardized training in cross-country skiers.
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Researchers have retrospectively analyzed the training intensity distribution (TID) of nationally and internationally competitive athletes in different endurance disciplines to determine the optimal volume and intensity for maximal adaptation. The majority of studies present a “pyramidal” TID with a high proportion of high volume, low intensity training (HVLIT). Some world-class athletes appear to adopt a so-called “polarized” TID (i.e., significant % of HVLIT and high-intensity training) during certain phases of the season. However, emerging prospective randomized controlled studies have demonstrated superior responses of variables related to endurance when applying a polarized TID in well-trained and recreational individuals when compared with a TID that emphasizes HVLIT or threshold training. The aims of the present review are to: (1) summarize the main responses of retrospective and prospective studies exploring TID; (2) provide a systematic overview on TIDs during preparation, pre-competition, and competition phases in different endurance disciplines and performance levels; (3) address whether one TID has demonstrated greater efficacy than another; and (4) highlight research gaps in an effort to direct future scientific studies.
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Researchers have retrospectively analyzed the training intensity distribution (TID) of nationally and internationally competitive athletes in different endurance disciplines to determine the optimal volume and intensity for maximal adaptation. The majority of studies present a “pyramidal” TID with a high proportion of high volume, low intensity training (HVLIT). Some world-class athletes appear to adopt a so-called “polarized” TID (i.e., significant % of HVLIT and high-intensity training) during certain phases of the season. However, emerging prospective randomized controlled studies have demonstrated superior responses of variables related to endurance when applying a polarized TID in well-trained and recreational individuals when compared with a TID that emphasizes HVLIT or threshold training. The aims of the present review are to: (1) summarize the main responses of retrospective and prospective studies exploring TID; (2) provide a systematic overview on TIDs during preparation, pre-competition, and competition phases in different endurance disciplines and performance levels; (3) address whether one TID has demonstrated greater efficacy than another; and (4) highlight research gaps in an effort to direct future scientific studies.
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The aim of this study was to investigate factors that can predict individual adaptation to high-volume or high-intensity endurance training. After the first 8-week preparation period, 37 recreational endurance runners were matched into the high-volume training group (HVT) and high-intensity training group (HIT). During the next 8-week training period, HVT increased their running training volume and HIT increased training intensity. Endurance performance characteristics, heart rate variability (HRV), and serum hormone concentrations were measured before and after the training periods. While HIT improved peak treadmill running speed (RSpeak ) 3.1 ± 2.8% (P < 0.001), no significant changes occurred in HVT (RSpeak : 0.5 ± 1.9%). However, large individual variation was found in the changes of RSpeak in both groups (HVT: -2.8 to 4.1%; HIT: 0-10.2%). A negative relationship was observed between baseline high-frequency power of HRV (HFPnight ) and the individual changes of RSpeak (r = -0.74, P = 0.006) in HVT and a positive relationship (r = 0.63, P = 0.039) in HIT. Individuals with lower HFP showed greater change of RSpeak in HVT, while individuals with higher HFP responded well in HIT. It is concluded that nocturnal HRV can be used to individualize endurance training in recreational runners. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.