Double-Poling Physiology and Kinematics of Elite Cross-Country Skiers: Specialized Long-Distance Versus All-Round Skiers

in International Journal of Sports Physiology and Performance

Purpose: Long-distance cross-country skiers specialize to compete in races >50 km predominantly using double poling (DP). This emphasizes the need for highly developed upper-body endurance capacities and an efficient DP technique. The aim of this study was to investigate potential effects of specialization by comparing physiological capacities and kinematics in DP between long-distance skiers and skiers competing using both techniques (skating/classic) in several competition formats (“all-round skiers”). Methods: Seven male long-distance (32 [6] y, 183 [6] cm, 76 [5] kg) and 6 all-round (25 [3] y, 181 [5] cm, 75 [6] kg) skiers at high international levels conducted submaximal workloads and an incremental test to exhaustion for determination of peak oxygen uptake (VO2peak) and time to exhaustion (TTE) in DP and running. Results: In DP and running maximal tests, TTE showed no difference between groups. However, long-distance skiers had 5–6% lower VO2peak in running (81 [5] vs 85 [3] mL·kg−1·min−1; P = .07) and DP (73 [3] vs 78 [3] mL·kg−1·min−1; P < .01) than all-round skiers. In DP, long-distance skiers displayed lower submaximal O2 cost than all-round skiers (3.8 ± 3.6%; P < .05) without any major differences in cycle times or cyclic patterns of joint angles and center of mass. Lactate concentration over a wide range of speeds (45–85% of VO2peak) did not differ between groups, even though each workload corresponded to a slightly higher percentage of VO2peak for long-distance skiers (effect size: 0.30–0.68). Conclusions: The long-distance skiers displayed lower VO2peak but compensated with lower O2 cost to perform equally with the all-round skiers on a short TTE test in DP. Furthermore, similar submaximal lactate concentration and reduced O2 cost could be beneficial in sustaining high skiing speeds in long-duration competitions.

Because of the wide range of physiological, biomechanical, and anthropometrical demands in endurance sports, specialization is often considered a prerequisite for reaching an elite performance level. As an example, marathon runners display lower maximal oxygen uptake (VO2max) than 5- to 10-km runners but compensate with a lower O2 cost of running to achieve superior performance in long events.1 Similarly, road cyclists who are uphill, flat, or time-trial specialists generally display anthropometrics and indexed VO2max values that are favorable for performance on either uphill or flat terrain, respectively.2,3

Cross-country (XC) skiing is a complex endurance sport consisting of several competition formats with durations ranging from ∼3 minutes (sprint, ∼1.3–1.8 km) to more than 2 hours (≤50 km) in World Cup (WC) and Olympic events. Consequently, an increasing number of athletes specialize, mainly competing in 1 or a few race formats to optimize physiological performance and rank; elite sprint-specialized skiers are heavier and have a larger anaerobic capacity but display lower body mass normalized VO2max compared with distance XC skiers, most likely due to a combination of genetics and training specificity.4

Recently, long-distance mass-start races such as the Ski Classics (a cup of long races separated from the WC), where athletes compete for ∼40 to 90 km using the classical technique, have become increasingly popular, and several male and a few female athletes have specialized their training to optimize performance in such events. Currently, very little is known about these “long-distance skiers,”5 and knowledge about the top athletes’ physiological capacities could provide useful information for athletes and coaches with regard to this race format’s specific demands. Because of the track layouts, improvements in equipment and track preparation allowing for higher speeds, and current trends, elite long-distance skiers use skis without grip wax and rely exclusively on the double poling (DP) technique in the majority of events. This is intriguing as DP relies solely on propulsion trough the poles, emphasizing the need for a well-developed upper-body capacity.5 Hence, long-distance skiers exercise their upper body frequently and may possess other physiological and technical qualities related to DP compared with “all-round skiers” who compete using both the skating and classical techniques in several race formats. In fact, only specialists have won the longest Ski Classics event over the last decade (Vasaloppet, 90 km), even though several world-class all-round skiers have competed.

During the last decade, the DP technique has been extensively analyzed, with studies focusing on different inclines,6 poling frequencies,7 subgroups of athletes,8 and kinematic changes during a race.9 However, to our knowledge, studies investigating the physiology and the technique of DP specialists are lacking. The only study to date found lower submaximal O2 cost and blood lactate concentrations ([La-]) in DP and equal VO2peak in both DP and diagonal skiing in elite long-distance skiers compared with all-round skiers. However, as the all-round skiers were defined as national class skiers with mean International Ski Federation’s (FIS) points as high as 121, it is questionable if these findings can be extrapolated to the elite performance level. Hence, it is currently unknown whether the long-distance skiers’ specialization with respect to training, to perform in long events using predominantly the DP technique, leads to any favorable technical or physiological adaptations compared with the elite all-round skiers.

The XC skiers are normally found to reach a peak oxygen uptake (VO2peak) of “only” ∼90% of VO2max measured in diagonal skiing or VO2peak running when they do incremental exercise tests to exhaustion in DP.1012 Although recently contradicted,13 this may partly be explained by the upper-body muscles having longer diffusional distances, shorter mean transit times, and lower oxidative capacity than leg muscles, even in well-trained XC skiers.1416 Therefore, arm O2 extraction is found to be ∼10% lower than in leg muscles16 and contributes, together with a lower vascular conductance,17 to the ∼10% lower VO2peak observed in DP. Recently, it was suggested that training designed to enhance O2 extraction in the arms, such as high-volume, low-intensity upper-body training, could improve the DP VO2peak/VO2max ratio.18 Therefore, investigating this ratio in long-distance skiers could give some indication of whether the limiting factors can be improved with increased training specificity.

Hence, the present investigation aimed to (1) provide information regarding physiological capacities of elite male long-distance XC skiers and (2) investigate potential effects of specialization by comparing their physiological capacities and kinematics in DP to those of elite all-round skiers.

Methods

Subjects

Of the elite male long-distance skiers included in the present study, 6 of the 7 had podium placements in the (Marcialonga, Vasaloppet, Birkebeinerrennet, etc) Ski Classics and were ranked among the top 10 in the overall standings during the season they were tested in. All 6 male all-round skiers had competed in the FIS WC, with 5 of them finishing top 5 in 1 or more individual races in the previous season (Table 1). Within 2 seasons from data collection, the group of all-round skiers included 1 Olympic and 1 world champion (only individual races considered). The long-distance skiers were older than the all-round skiers (P = .04). However, this difference was not entirely an effect of our sampling, as it also existed between the top 10 WC and Ski Classics skiers (28.3 [3.9] vs 31.6 [5.9]; P = .07; season 2016–2017). All skiers were familiarized with treadmill testing, both in DP and running. The subjects were fully aware of the nature of the study and signed a written informed consent before participation. The study was approved by the ethical committee of the Norwegian School of Sport Sciences (05-130617) and reported to the Norwegian Center for Research Data (54405).

Table 1

Characteristics of the 6 All-Round Skiers and 7 Long-Distance Skiers Included in the Study

All-round skiersLong-distance skiersES (Cohen d)
Age, y25.4 (2.6)32.0 (6.3)*1.31La
Body height, cm181 (5)183 (6)0.32S
Body mass, kg75.1 (5.5)75.7 (5.2)0.11T
Body mass index, kg·m−223.0 (1.1)22.7 (0.8)0.26S
FIS points (distance) 2016/201716.0 (12.4)38.1 (6.5)*2.29VL
Ranking Ski Classics 2016/20176.9 (6.0)

Note: Data are presented as mean (SD). Abbreviations: ES, effect size; FIS, International Ski Federation. Note: Superscript letters by the ESs denote their magnitude as T, trivial (ES < 0.2); S, small (0.2 ≤ ES < 0.6); M, moderate (0.6 ≤ ES < 1.2); La, large (1.2 ≤ ES < 2.0); and VL, very large (ES ≥ 2.0).23 The races in the Ski Classics Cup were in season 2016/2017 given a penalty of 35 points when FIS points were calculated as compared with 0 in World Cup, World Championship, or Olympic races.

*Significant difference between groups (P < .05).

Methodology

Testing was conducted in the late preparation phase (October) and consisted of submaximal workloads and an incremental test to exhaustion in DP, followed by a similar test in running ∼1.5 hours later (nonrandomized). The subjects were allowed to drink a carbohydrate and electrolyte-containing fluid ad libitum during breaks and to eat a small snack (such as an energy bar) between tests. The rationale for performing both tests on the same day was that the participants were elite skiers and that the testing needed to fit their schedule to recruit this highly trained group. The DP test was conducted first as we analyzed kinematics only in DP and as the DP data were evaluated as being the most important with respect to the purpose of the study. This may have affected submaximal and peak responses in running, but unlikely differently in the 2 groups. The day before testing, the skiers were restricted to perform any strenuous training (>75% of maximum heart rate [HR] or strength training).

Instruments

Oxygen uptake (VO2) was measured using open-circuit indirect calorimetry with a mixing chamber (Oxycon Pro; Jaeger Instrument, Hoechberg, Germany)19 calibrated as previously described.20 HR was measured continuously (Polar RS800; Polar Electro Oy, Kempele, Finland) and [La-] was measured in nonhemolyzed capillary fingertip blood (YSI 1500 Sport; Yellow Springs Instruments, Yellow Springs, OH). The roller-ski testing was conducted on a 3 × 4.5-m treadmill (Rodby, Sodertalje, Sweden). As a precautionary measure, the athletes wore a safety harness connected to an automatic emergency brake. The rolling friction coefficient (μ = 0.021) of the roller skis (Swenor, Sarpsborg, Norway) was tested before, during, and after the experiments21 and was unchanged during the study. Work rate was calculated as the sum of power against gravity (Pg) and friction (Pf):

Work rate=Pg+Pf=mgv(sin(α)+cos(α)×μ)
where m is the sum of body mass and mass of equipment (in kilograms), g is the gravitational constant, v is the speed of the treadmill belt (in meters per second), α is the treadmill incline (in degrees), and μ is the frictional coefficient.

The poles (Triac 1.0; Swix, Lillehammer, Norway) were standardized to the nearest length (2.5 cm intervals) that corresponded to 88% of the athletes’ body height, as pole length has been shown to influence submaximal O2 cost, kinematics, and performance.22 The poles were 3.0 (1.0) cm longer than the maximum length allowed during competition the following winter (measured from pole tip to strap insertion), according to the new FIS regulation (84.7 ± 0.5% of the body height including shoes instead of 83%). Therefore, kinematic data may be affected by this, but unlikely any differently in the 2 groups as all subjects were familiarized to long pole lengths. An inertial measurement system (PLUX Wireless Biosignals S.A., Lisbon, Portugal) sampling at 1000 Hz was mounted on the skier’s right pole, and the cycle time, poling time, and reposition time were calculated on the basis of 10 consecutive cycles for each submaximal workload as previously described.24 Joint angles were derived from 50-Hz video analysis in the sagittal plane (Canon HF100; Canon Inc, Tokyo, Japan) using Tracker (Tracker version 4.95; Douglas Brown, Open Source Physics).22 The vertical center of mass (zCOM) was calculated as the weighted average of the COMs of each body segment and equipment, as previously described.22 The running test was conducted using a custom-made treadmill (Woodway GmbH, Weil am Rhein, Germany).

DP Test

All DP workloads were conducted at 2.5° incline, with the incline and speeds chosen to induce competition-relevant technique based on pilot testing and previous research.22 The subjects warmed up for 15 minutes at 10.8 km·h−1 (∼60%–70% of HRpeak-DP), with the last 5-minute serving as the first submaximal workload. Thereafter, the speed was increased by 1.8 km·h−1 (0.5 m·s−1) in each 5-minute step until the lactate threshold was exceeded. The estimated lactate threshold was defined as the highest speed before the [La-] on the first workload + 1.8 mmol·L−1 was exceeded, which corresponds well with the maximal lactate steady-state workload in DP.26 The athletes completed a total of 6 to 7 submaximal workloads (10.8–21.6 km·h−1; ∼45%–85% of VO2peak-DP), always separated by 1.5-minute breaks during which [La-] was immediately assessed. Cardiorespiratory variables were monitored continuously, and the averages of the last 2 minutes of each workload served as the steady-state values. After a 7-minute break including rest and active recovery (∼40% of VO2peak-DP), the incremental test started at 18 km·h−1 and progressed with increases of 0.9 km·h−1 for every 30 seconds completed. Performance was defined as time to exhaustion (TTE). Thirty seconds and 3 minutes after exhaustion, [La-] was assessed and the highest value was used as [La-peak]. The highest continuous VO2 during a 30-second period and the highest HR during a 5-second period were defined as VO2peak-DP and HRpeak-DP, respectively. The mean speed during the last 30 seconds before exhaustion was defined as the peak speed (speedpeak). Peak aerobic speed (sVO2peak) was calculated as the minimal speed requiring a VO2 equal to VO2peak from each individual’s relationship between submaximal O2 cost and treadmill speed.

Running Test

The running test was performed at a 6° incline and was similar in structure to the DP test. Briefly, the test started at 7.5 km·h−1 (∼60–70% of HRmax-RUN) and progressed with increments of 0.9 km·h−1 for each 5-minute step until the lactate threshold was exceeded (workload range: 7.5–12.9 km·h−1; ∼50–85% of VO2peak-RUN). The estimated lactate threshold was defined as the highest speed before the [La-] on the first workload + 1.5 mmol·L−1 was exceeded, which corresponds well with the maximal lactate steady-state workload in running.25 Cardiorespiratory variables were monitored during the last 2.5 minutes of each workload, and the average over the last 2 minutes was used for further analysis. After a 7-minute break including active recovery (∼35% of VO2peak-RUN), the incremental test started at 10 km·h−1 (∼70% of VO2peak-RUN) and progressed with increases of 0.5 km·h−1 for every 30 seconds completed until exhaustion. The highest continuous VO2 during a 60-second period was defined as VO2peak-RUN instead of VO2max, as it has been previously shown that XC skiers can reach 3%–4% higher values during diagonal skiing compared with running.11,27 The highest HR during a 5-second period was defined as HRpeak-RUN.

Training Data

Annual endurance training (May 1 to April 30) was recorded in training diaries and categorized into training modes (skating, classical, running, or other) and intensity zones based on the session-goal approach.28 In addition, the training times spent engaged in speed training and strength training were recorded. Unfortunately, only 3 of the 7 long-distance skiers recorded their training regularly, and their records were used in the comparison with the 6 all-round skiers. Due to the small sample size, no statistical analysis regarding the group comparison was performed.

Statistical Analysis

Group means and group differences are shown as mean (SD) and mean ± 95% confidence interval. The data were normally distributed as assessed by Shapiro–Wilk test. Group differences were analyzed with unpaired Student t tests and 2-factor mixed analysis of variance (group × speed on submaximal and group × exercise mode on peak values). If a significant group effect was found, a Bonferroni post hoc test for multiple comparisons was conducted. Moreover, analysis of covariance was conducted on the VO2peak values using age as a covariate. Effect sizes (ESs; Cohen d) and correlation coefficients (Pearson product–moment correlation) were classified according to Hopkins.22 The alpha level was set to .05 and P values between .05 and .10 were considered to indicate trends. IBM SPSS Statistics 24.0 (IBM Corp, New York, NY) was used for statistical analysis.

Results

Incremental Test to Exhaustion

There was a significant main effect of group on body-mass normalized VO2peak (F1,11 = 7.2, P = .02), with post hoc tests revealing 5.3 ± 5.8% (P = .07) and 6.4 ± 4.1% (P < .01) higher VO2peak-RUN and VO2peak-DP for all-round compared with long-distance skiers, respectively. When adjusted for age, there was still a significant group-difference of 6.5 ± 5.3% (F1,10 = 7.3, P = .02) in VO2peak-DP but no difference in VO2peak-RUN (difference: 4.8 ± 7.6%; F1,10 = 2.0, P = .19). No group differences were found for the ratio VO2peak-DP/VO2peak-RUN (0.92 [0.03] vs 0.91 [0.03] for all-round [range: 0.88–0.95] and long-distance skiers [range: 0.87–0.94], respectively; P = .48; ES: 0.41), TTE or the remaining cardiorespiratory variables (Table 2). A moderate negative correlation was found between VO2peak-RUN and the ratio VO2peak-DP/VO2peak-RUN (r = −.48; P = .09; n = 13). Age had a moderate negative correlation with VO2peak-RUN (r = −.35; P = .24; n = 13) and VO2peak-DP (r = −.40; P = .18; n = 13).

Table 2

Performance and Physiological Response During Incremental Tests to Exhaustion in Running (6.0° Incline) and Double Poling (2.5° Incline)

RunningDouble poling
All-round skiers (n = 6)Long-distance skiers (n = 7)ES (Cohen d)All-round skiers (n = 6)Long-distance skiers (n = 7)ES (Cohen d)
Time to exhaustion, s446 (24)423 (37)0.73M269 (20)268 (22)0.06T
Speedpeak, km·h−116.7 (0.4)16.3 (0.6)0.73M25.2 (0.6)25.1 (0.6)0.06T
Powerpeak, W353 (25)354 (18)0.05T
VO2peak, mL·kg−1·min−185.0 (3.4)#80.6 (4.5)1.11M78.0 (2.5)*73.0 (2.7)1.90La
VO2peak, L·min−16.38 (0.42)6.09 (0.44)0.67M5.86 (0.40)5.52 (0.32)0.92M
sVO2peak, km·h−114.5 (0.5)14.1 (0.8)0.53S23.9 (1.9)23.8 (1.8)0.09T
VEpeak, L·min−1218 (13)217 (16)0.05T194 (10)198 (15)0.28S
RERpeak1.14 (0.04)1.13 (0.02)0.65M1.06 (0.04)1.05 (0.03)0.09T
HRpeak, beats·min−1193 (4)189 (6)0.66M187 (6)185 (8)0.21S
[Lapeak], mmol·L−18.9 (1.7)8.1 (1.1)0.61M7.3 (1.1)7.1 (1.5)0.16S

Note: Data are presented as mean (SD). Abbreviations: ES, effect size; VO2peak, peak oxygen uptake; sVO2peak, the peak aerobic speed calculated from VO2peak and the submaximal relationship between treadmill speed and O2 cost; VEpeak, peak ventilation; RERpeak, peak respiratory exchange ratio; HRpeak, peak heart rate; [Lapeak], peak blood lactate concentration. Note: Superscript letters by the ESs denote their magnitude as T, trivial (ES < 0.2); S, small (0.2 ≤ ES < 0.6); M, moderate (0.6 ≤ ES < 1.2); and La, large (1.2 ≤ ES < 2.0).23 Speedpeak is the highest treadmill speed during the last 30 and 60 seconds for double poling and running, respectively.

*Significant difference between groups (P ≤ .01). #Tendency to difference between groups (.05 < P ≤ .1).

Submaximal Data

During submaximal DP (Table 3 and Figure 1), the O2 cost was on average 3.8 ± 3.6% (1.8 [1.7] mL·kg−1·min−1; F1,11 = 5.5, P = .04; ES: 1.13) lower for the long-distance skiers than all-round skiers, with post hoc tests revealing significant differences on the 3 highest workloads (16.2–19.8 km·h−1; P < .05) and tendencies on the 2 lowest workloads (10.8–12.6 km·h−1; .06 ≤ P ≤ .09). No differences were found for O2 cost as a percentage of VO2peak-DP (F1,11 = 0.7, P = .42), HR (F1,11 = 1.3, P = .28), [La-] (F1,11 = 0.2, P = .68), respiratory exchange ratio (F1,11 = 2.9, P = .12), breathing frequency (F1,11 = 0.2, P = .67), and ventilation (F1,11 = 0.5, P = .51). When the lactate threshold was estimated as the concentration at “warm-up” + 1.8 mmol·L−1 (2.7 [0.2] mmol·L−1, both groups), no significant difference was found for speed (19.2 [0.7] vs 19.5 [0.05] km·h−1; P = .51; ES: 0.40), VO2 (61.4 [2.4] vs 59.1 [2.0] mL·kg−1·min−1; P = .10; ES: 1.03), VO2 as a percent of VO2peak-DP (79 [3] vs 81 ± 5%; P = .32; ES: 0.56), or HR (163 [7] vs 167 [6] beats min−1; P = .34; ES: 0.56) between all-round and long-distance skiers, respectively.

Table 3

Physiological and Kinematic Responses to Double Poling at the Highest Submaximal Speed Before Exceeding Estimated Lactate Threshold (2.5° Incline and 18 km·h−1) in All-Round and Long-Distance Skiers

All-round skiersLong-distance skiersES (Cohen d)
Power output, W252.3 (17.4)253.7 (16.3)0.08T
VO2, mL·kg−1·min−156.3 (1.3)*54.0 (2.1)1.28La
VO2, % of VO2peak-DP72.3 (3.6)74.2 (5.5)0.41S
VE, L·min−1112 (17)121 (18)0.56S
RER0.90 (0.02)0.92 (0.02)0.74M
HR, beats·min−1156 (8.1)159 (7)0.46S
HR, % of HRpeak-DP83.2 (3.5)85.9 (2.8)0.84M
[La-], mmol·L−11.9 (0.7)1.7 (0.4)0.37S
Cycle time, ms1168 (145)1169 (78)0.01T
Poling time, ms360 (15)373 (22)0.67M
Poling time, % of cycle31 (3)32 (2)0.36S
Reposition time, ms807 (134)796 (68)0.12T
Reposition time, % of cycle69 (3)68 (2)0.36S
Cycle length, m5.8 (0.7)5.8 (0.4)0.01T
ROM ankle, °15.3 (6.0)15.5 (4.1)0.03T
ROM knee, °33.6 (8.0)30.7 (3.0)0.51S
ROM hip, °86.8 (4.8)86.9 (3.6)0.03T
ROM shoulder, °97.6 (7.9)89.7 (8.4)0.96M
ROM elbow, °95.7 (9.2)103.4 (12.2)0.70M
zCOM displacement, cm25.6 (1.4)26.7 (2.6)0.50S

Note: Data are presented as mean (SD). Abbreviations: [La-], blood lactate concentration; ES, effect size; HR, heart rate; HRpeak-DP, peak heart rate in double poling; RER, respiratory exchange ratio; ROM, range of motion; VE, ventilation; VO2, oxygen uptake; VO2peak-DP, VO2 in double poling; zCOM, vertical center of mass. Superscript letters by the ESs denote their magnitude as T, trivial (ES < 0.2); S, small (0.2 ≤ ES < 0.6); M, moderate (0.6 ≤ ES < 1.2); La, large (1.2 ≤ ES < 2.0); and VL, very large (ES ≥ 2.0).23 *Significant difference between groups (P < .05). #Tendency to difference between groups (.05 < P ≤ .1).

Figure 1
Figure 1

—Submaximal oxygen (O2) cost, heart rate, and blood lactate concentration for all-round (n = 6) and long-distance (n = 7) cross-country skiers in double poling (A, C, and E) and running (B, D, and F). Values are means and error bars indicate 95% confidence intervals. *Significant difference between groups (P < .05). #Tendency to difference between groups (.05 < P ≤ .1).

Citation: International Journal of Sports Physiology and Performance 14, 9; 10.1123/ijspp.2018-0471

The correlations between O2 cost (grand mean) in DP and age, performance (TTE) and the training hours spent in classical skiing were moderate (r = −.37; P = .21; n = 13), high (r = −.50; P = .08; n = 13), and very high (r = −.82; P < .01; n = 9), respectively.

During submaximal running (Figure 1), no group differences were found for any of the cardiorespiratory variables (F1,11 = 0.01–1.3, P = .28–.91). The correlations between O2 cost in running and age and performance (TTE) were moderate (r = .32; P = .29; n = 13) and high (r = −.60; P = .03; n = 13), respectively.

DP Technique

Neither cycle time (F1,11 = 0.03, P = .86), poling time (F1,11 = 0.5, P = .52), reposition time (F1,11 = 0.2, P = .71), nor cycle length (F1,11 = 0.02, P = .88) differed between groups on the submaximal workloads (Figure 2). At the submaximal speed of 18 km·h−1 (the highest speed at which all subjects were below the estimated lactate threshold), the joint angles and zCOM were analyzed and are shown in Figure 3. No differences were found for zCOM; range of motion (ROM) of joint angles (Table 3); or the specific angles during the cycle for the ankle, knee, shoulder, and elbow (Figure 3). However, for the long-distance skiers, the hip was more flexed for 27% to 41% of the cycle (P < .05), and zCOM tended to be lower for 28% to 35% of the cycle (P ≤ .10) compared with the all-round skiers.

Figure 2
Figure 2

—Changes in cycle time (A), poling time (B), and reposition time (C) by speed for all-round (n = 6) and long-distance (n = 7) cross-country skiers. Values are means and error bars indicate 95% confidence intervals. No differences between groups were detected.

Citation: International Journal of Sports Physiology and Performance 14, 9; 10.1123/ijspp.2018-0471

Figure 3
Figure 3

—Mean joint angles for the elbow (A), shoulder (C), hip (E), knee (B), and ankle (D) during double poling at 18 km·h−1 for all-round (n = 6) and long-distance (n = 7) cross-country skiers. Figure F shows the displacement of the center of mass with respect to its mean position during the cycle. The cycle starts (0%) and ends (100%) at pole plant, and the vertical dashed line indicates pole push-off. The horizontal line with asterisks (*) indicates significant differences between groups (unpaired t test, P < .05). #Tendency to difference between groups (.05 < P ≤ .1).

Citation: International Journal of Sports Physiology and Performance 14, 9; 10.1123/ijspp.2018-0471

Training Data

The annual endurance, speed, and strength training are reported in Table 4. Due to the low sample size of long-distance skiers, no statistical analysis was conducted to compare groups. Compared with the all-round skiers, the long-distance skiers trained 47 ± 67% (mean ± 95% confidence interval) more classical skiing (255 [25] h vs 376 [74] h) and 64 ± 18% less skating (255 [44] h vs 92 [11] h). However, the groups performed similar amounts of running (196 [41] h vs 187 [48] h) and other endurance training modes (61 [44] h vs 40 [22] h; for percentage distributions, see Figure 4).

Table 4

Annual Training (12 Months) for the All-Round and Long-Distance Cross-Country Skiers

All-round skiers (n = 6)Long-distance skiers (n = 3)
Total training, h% of total trainingTotal training, h% of total training
LIT (<81% of HRmax)684 (72)83.1 (3.3)642 (97)83.0 (1.8)
MIT (82–87% of HRmax)37 (11)4.5 (1.2)24 (8)3.0 (1.7)
HIT (>88% of HRmax)32 (10)3.9 (1.1)43 (17)5.5 (1.7)
Strength58 (29)7.0 (3.1)52 (11)6.7 (0.5)
Speed13 (9)1.5 (1.1)14 (8)1.8 (0.9)
Total training824 (89)775 (130)

Note: Data are presented as mean (SD). Abbreviations: HIT, high-intensity training; HRmax, maximum heart rate; LIT, low-intensity training; MIT, moderate-intensity training. Note: Due to the low number of long-distance skiers reporting their training, no statistical analysis was run. The data are merely meant to indicate trends and should be interpreted with caution.

Figure 4
Figure 4

—Percentage distribution of annual endurance training divided between classic skiing, skating skiing, running, and other endurance training modes for all-round (n = 6) and long-distance (n = 3) cross-country skiers. Values are means and error bars indicate 95% confidence intervals. Statistical analyses were not performed due to the low sample size. The data can only be interpreted as trends and should be interpreted with caution.

Citation: International Journal of Sports Physiology and Performance 14, 9; 10.1123/ijspp.2018-0471

Discussion

The present study provides novel information about the requirements for success in elite long-distance XC skiing: (1) low O2 cost in DP may be the key to why these skiers succeed at the longest competition durations, even though they displayed a lower VO2peak as compared with elite all-round skiers; (2) elite long-distance skiers are characterized by a VO2peak in running of about 80 mL·kg−1·min−1, with ∼90% or more being utilized in DP specifically; and (3) the ratio between VO2peak in DP and running was equal for the 2 groups, even though the long-distance skiers trained more using classical skiing in which the DP technique is heavily used.

Interestingly, the long-distance skiers displayed ∼5% to 6% lower VO2peak-RUN and VO2peak-DP than the elite all-round skiers. This could potentially be explained by several factors, including a higher standard of competitors in the WC compared with the Ski Classics, age-related differences, or different physiological demands due to competition duration. In support of the latter, WC distance and Ski Classics events were on average ∼19 km (excluding Sprint events) and ∼59 km, respectively, in the season in which the athletes were tested. Hence, as exercise economy and fractional utilization of VO2peak are known to be increasingly important with prolonged competition duration,29 it could be argued that the reduced submaximal O2 cost and similar lactate threshold as a function of speed may be of even greater importance for the long-distance skiers than an extremely high VO2peak. Moreover, the long-distance skiers were on average ∼6.5 years older than the all-round skiers, and it has been previously shown that VO2peak can decline by approximately ∼5% to 10% per decade after ∼25 years of age, even in trained subjects.30,31 Also, a moderate negative correlation was found between age and both VO2peak-RUN and VO2peak-DP, and several of the oldest long-distance skiers reported verbally that their VO2peak-RUN had been higher at around 25 years of age. Therefore, we included age as a covariate in the statistical analysis comparing VO2peak between groups. The adjustments for age changed the mean difference only slightly but caused a pronounced widening of the confidence intervals. Hence, this adjustment erased the statistical difference between groups only for VO2peak-RUN and not for VO2peak-DP. Therefore, only some of the difference in aerobic power may reflect an effect of aging (or change in training over the years), and the difference must be explained by additional factors such as differences in physiological demands due to race lengths or the standard of the athletes competing in the different race formats.

Our data contradicts the recent findings of Sagelv et al32 who found equal, if not slightly higher (ns), VO2peak both in DP and diagonal skiing when comparing long-distance skiers to all-round skiers. However, this study only included national-class all-round skiers with mean FIS points of 121 compared with 16 in this study using elite all-round skiers. Hence, we conclude that all-round skiers have slightly higher VO2peak values when both groups are recruited from the highest performance level.

Previously, it has been emphasized that the ability to achieve high VO2peak/VO2max ratios in the various skiing techniques is of great importance for sport-specific performance,5,18 and it has been indicated that these ratios may be improved through increased specificity in training.18 Hence, it was appealing to hypothesize that the long-distance skiers would have a higher ratio of VO2peak-DP/VO2peak-RUN than the all-round skiers. However, even though there was a difference in training-mode distribution between groups, at least based on the few athletes reporting their training, both groups showed a ratio of ∼0.91 to 0.92, comparable to the values found when comparing national class all-round skiers to elite long-distance skiers32 and to other studies investigating XC skiers at various performance levels.1012 Moreover, there was a moderate negative correlation between VO2peak-RUN and the ratio VO2peak-DP/VO2peak-RUN. The reason for this is unclear and needs further elucidation. However, the findings may support the idea that DP includes too small a muscle mass to reach VO2peak-RUN/VO2max irrespective of training status or that the lower vascular conductance17 and O2 extraction16 in the upper body compared with the lower body muscles are at least not smaller in those skiers possessing the highest aerobic power.

The high correlation found between performance (TTE) and O2 cost in DP is in agreement with previous research.33,34 Similar to previous findings,32 a large difference was found in DP O2 cost between groups, even though they showed almost identical cycle times, poling times, and movement patterns, as indicated by the joint angles and zCOM. The only technical difference observed was a lower hip angle, which caused zCOM to be slightly lower in the late poling phase for the long-distance skiers. Speculatively, some of the potential energy of elevated body mass that was released by the vertical downward movement of zCOM may have been transferred to the poles at a later part of the poling phase, characterized by a more optimal pole angle. However, without any measurement of pole-force, this is only a speculation, and we do not know if this has contributed to the observed difference in O2 cost. A limitation of this study is the low sample size, and it is possible that more kinematic differences could have been detected if we had been able to recruit more subjects. Hence, due to low statistical power, we cannot exclude undiscovered kinematic differences as a potential explanation for the observed difference in O2 cost.

Previously, a 4% to 5% lower O2 cost was found in a group of elite senior XC skiers compared with their junior counterparts.35 Plausible explanations could therefore be that greater age, or more likely, a larger accumulated training volume over several years may have contributed to the findings. In support, we observed a very high negative correlation between O2 cost in DP and the annual training hours spent during classical skiing. Also, it has previously been found that XC skiers reduce their O2 cost of skiing toward the competition season in parallel with an increased amount of ski-specific training.36 Hence, more DP-specific training during the past years leading up to this investigation may have improved exercise economy without changing the “outward” movement-pattern, potentially through mechanisms not investigated in the present study (eg, fiber-type distribution, mitochondrial efficiency, and muscle-activation patterns).

Based on the few athletes reporting their training, the long-distance skiers trained more classical skiing and less skating, which is not surprising considering the events they compete in. However, due to the small number of subjects, interpretation should be done with caution and future studies should characterize the long-distance skiers’ training in more detail using a larger sample (examining factors such as distribution, intensity, and length of training sessions).

The [La-] during the submaximal workloads and the estimated lactate threshold were similar, even though each submaximal workload represented a somewhat higher percentage of VO2peak-DP for the long-distance compared with the all-round skiers. This, together with the reduced submaximal O2 cost, resulted in equal sVO2peak (Table 2) and equal DP performances in a short performance test, despite the lower VO2peak. Hence, as exercise economy and the lactate threshold become increasingly important with prolonged competition duration,29 these adaptations may be of major importance for long-distance skiers’ sport-specific outcomes. Moreover, improved exercise economy favors reduced energy utilization, potentially reducing the need for energy intake and use of muscle glycogen. Future studies should investigate whether these characteristics result in superior performance for long-distance skiers with prolonged test or competition durations.

Practical Applications

The present study provides valuable information regarding physiological capacities in elite long-distance skiers; a VO2peak in DP of 70 to 75 mL·kg−1·min−1 combined with an efficient exercise economy seems crucial to reach an elite performance level. In addition, the training data and communication with the best long-distance skiers indicate that a large amount of DP-specific training is crucial to improve the endurance of the upper-body muscles that may be necessary to maintain an efficient technique and high skiing speeds over several hours. In practice, this may be achieved through long training sessions mainly using the DP technique combined with sessions of upper-body core and strength training.

Conclusions

In the present investigation, the long-distance skiers were found to have a reduced O2 cost but lower VO2peak compared with all-round skiers, ultimately leading to a similar DP performance in short performance tests. The present study challenges the idea that the ratio between VO2peak in DP and running can be improved through increased specificity in training.

Acknowledgments

The authors would like to thank the athletes for their participation in the study. Special thanks are also given to Camilla Høivik Carlsen and Øyvind Gløersen for help with data analysis.

References

  • 1.

    Maldonado SMujika IPadilla S. Influence of body mass and height on the energy cost of running in highly trained middle- and long-distance runners. Int J Sports Med. 2002;23:268272. PubMed ID: 12015627 doi:10.1055/s-2002-29083

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Padilla SMujika ICuesta GGoiriena JJ. Level ground and uphill cycling ability in professional road cycling. Med Sci Sports Exerc. 1999;31:878885. PubMed ID: 10378916 doi:10.1097/00005768-199906000-00017

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Impellizzeri FMEbert TSassi AMenaspa PRampinini EMartin DT. Level ground and uphill cycling ability in elite female mountain bikers and road cyclists. Eur J Appl Physiol. 2008;102:335341. PubMed ID: 17943306 doi:10.1007/s00421-007-0590-9

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Losnegard THallén J. Physiological differences between sprint- and distance-specialized cross-country skiers. Int J Sports Physiol Perform. 2014;9:2531. PubMed ID: 24155024 doi:10.1123/ijspp.2013-0066

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Sandbakk ØHolmberg HC. Physiological capacity and training routines of elite cross-country skiers: approaching the upper limits of human endurance. Int J Sports Physiol Perform. 2017;12:10031011. PubMed ID: 28095083 doi:10.1123/ijspp.2016-0749

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Stöggl TLHolmberg HC. Double-poling biomechanics of elite cross-country skiers: flat versus uphill terrain. Med Sci Sports Exerc. 2016;48:15801589. doi:10.1249/MSS.0000000000000943

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Lindinger SJHolmberg HC. How do elite cross-country skiers adapt to different double poling frequencies at low to high speeds? Eur J Appl Physiol. 2011;111:11031119. PubMed ID: 21113613 doi:10.1007/s00421-010-1736-8

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Zoppirolli CPellegrini BBortolan LSchena F. Energetics and biomechanics of double poling in regional and high-level cross-country skiers. Eur J Appl Physiol. 2015;115:969979. PubMed ID: 25515019 doi:10.1007/s00421-014-3078-4

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Zoppirolli CBortolan LStella Fet al. Following a long-distance classical race the whole-body kinematics of double poling by elite cross-country skiers are altered. Front Physiol. 2018;9:978. PubMed ID: 30090070 doi:10.3389/fphys.2018.00978

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Skattebo ØHallen JRønnestad BRLosnegard T. Upper body heavy strength training does not affect performance in junior female cross-country skiers. Scand J Med Sci Sports. 2016;26:10071016. PubMed ID: 26146761 doi:10.1111/sms.12517

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Holmberg HCRosdahl HSvedenhag J. Lung function, arterial saturation and oxygen uptake in elite cross country skiers: influence of exercise mode. Scand J Med Sci Sports. 2007;17:437444. PubMed ID: 17040487

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Björklund GStöggl THolmberg HC. Biomechanically influenced differences in O2 extraction in diagonal skiing: arm versus leg. Med Sci Sports Exerc. 2010;42:18991908. doi:10.1249/MSS.0b013e3181da4339

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Ørtenblad NNielsen JBoushel RSöderlund KSaltin BHolmberg HC. The muscle fiber profiles, mitochondrial content, and enzyme activities of the exceptionally well-trained arm and leg muscles of elite cross-country skiers. Front Physiol. 2018;9:1031. PubMed ID: 30116201 doi:10.3389/fphys.2018.01031

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Van Hall GJensen-Urstad MRosdahl HHolmberg HCSaltin BCalbet JA. Leg and arm lactate and substrate kinetics during exercise. Am J Physiol Endocrinol Metab. 2003;284:E193E205. PubMed ID: 12388120 doi:10.1152/ajpendo.00273.2002

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Mygind E. Fibre characteristics and enzyme levels of arm and leg muscles in elite cross-country skiers. Scand J Med Sci Sports. 1995;5:7680. PubMed ID: 7606514 doi:10.1111/j.1600-0838.1995.tb00016.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Calbet JAHolmberg HCRosdahl Hvan Hall GJensen-Urstad MSaltin B. Why do arms extract less oxygen than legs during exercise? Am J Physiol Regul Integr Comp Physiol. 2005;289:R1448R1458. PubMed ID: 15919729 doi:10.1152/ajpregu.00824.2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Calbet JAJensen-Urstad Mvan Hall GHolmberg HCRosdahl HSaltin B. Maximal muscular vascular conductances during whole body upright exercise in humans. J Physiol. 2004;558:319331. PubMed ID: 15121799 doi:10.1113/jphysiol.2003.059287

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Holmberg HC. The elite cross-country skier provides unique insights into human exercise physiology. Scand J Med Sci Sports. 2015;25(suppl 4):100109. doi:10.1111/sms.12601

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Foss ØHallén J. Validity and stability of a computerized metabolic system with mixing chamber. Int J Sports Med. 2005;26:569575. PubMed ID: 16195991 doi:10.1055/s-2004-821317

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Sandbakk ØHegge AMLosnegard TSkattebo ØTønnessen EHolmberg HC. The physiological capacity of the world’s highest ranked female cross-country skiers. Med Sci Sports Exerc. 2016;48:10911100. PubMed ID: 26741124 doi:10.1249/MSS.0000000000000862

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Hoffman MDClifford PSBota BMandli MJones GM. Influence of body mass on energy cost of roller skiing. Int J Sport Biomech. 1990;6:374385. doi:10.1123/ijsb.6.4.374

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Losnegard TMyklebust HSkattebo ØStadheim HKSandbakk ØHallén J. The influence of pole length on performance, O2 cost, and kinematics in double poling. Int J Sports Physiol Perform. 2016;12:211217. PubMed ID: 27193356 doi:10.1123/ijspp.2015-0754

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Hopkins WGMarshall SWBatterham AMHanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41:313. PubMed ID: 19092709 doi:10.1249/MSS.0b013e31818cb278

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Myklebust HLosnegard THallen J. Differences in V1 and V2 ski skating techniques described by accelerometers. Scand J Med Sci Sports. 2013;24:882893. PubMed ID: 23957331 doi:10.1111/sms.12106

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Wisløff UHelgerud J. Methods for evaluating peak oxygen uptake and anaerobic threshold in upper body of cross-country skiers. Med Sci Sports Exerc. 1998;30:963970. PubMed ID: 9624659

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Helgerud JIngjer FStrømme SB. Sex differences in performance-matched marathon runners. Eur J Appl Physiol Occup Physiol. 1990;61:433439. PubMed ID: 2079063 doi:10.1007/BF00236064

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Strømme SBIngjer FMeen HD. Assessment of maximal aerobic power in specifically trained athletes. J Appl Physiol Respir Environ Exerc Physiol. 1977;42:833837. PubMed ID: 881383 doi:10.1152/jappl.1977.42.6.833

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Seiler KSKjerland GO. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sports. 2006;16:4956. PubMed ID: 16430681 doi:10.1111/j.1600-0838.2004.00418.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Bassett DR JrHowley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med Sci Sports Exerc. 2000;32:7084. PubMed ID: 10647532 doi:10.1097/00005768-200001000-00012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Åstrand IÅstrand POHallback IKilbom A. Reduction in maximal oxygen uptake with age. J Appl Physiol. 1973;35:649654. PubMed ID: 4770349 doi:10.1152/jappl.1973.35.5.649

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Ogawa TSpina RJMartin WH 3rdet al. Effects of aging, sex, and physical training on cardiovascular responses to exercise. Circulation. 1992;86:494503. PubMed ID: 1638717 doi:10.1161/01.CIR.86.2.494

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Sagelv EHEngseth TPPedersen Set al. Physiological comparisons of elite male visma ski classics and national level cross-country skiers during uphill treadmill roller skiing. Front Physiol. 2018;9:1523. PubMed ID: 30505276 doi:10.3389/fphys.2018.01523

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Sandbakk ØHolmberg HCLeirdal SEttema G. Metabolic rate and gross efficiency at high work rates in world class and national level sprint skiers. Eur J Appl Physiol. 2010;109:473481. PubMed ID: 20151149 doi:10.1007/s00421-010-1372-3

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Sandbakk ØHegge AMEttema G. The role of incline, performance level, and gender on the gross mechanical efficiency of roller ski skating. Front Physiol. 2013;4:293. PubMed ID: 24155722 doi:10.3389/fphys.2013.00293

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    Ainegren MCarlsson PTinnsten MLaaksonen MS. Skiing economy and efficiency in recreational and elite cross-country skiers. J Strength Cond Res. 2013;27:12391252. PubMed ID: 22344058 doi:10.1519/JSC.0b013e31824f206c

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36.

    Losnegard TMyklebust HSpencer MHallén J. Seasonal variations in VO2max, O2-cost, O2-deficit, and performance in elite cross-country skiers. J Strength Cond Res. 2013;27:17801790. PubMed ID: 22996025 doi:10.1519/JSC.0b013e31827368f6

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

If the inline PDF is not rendering correctly, you can download the PDF file here.

The authors are with the Dept of Physical Performance, Norwegian School of Sport Sciences, Oslo, Norway.

Skattebo (oyvind.skattebo@nih.no) is corresponding author.
International Journal of Sports Physiology and Performance
Article Sections
Figures
  • View in gallery

    —Submaximal oxygen (O2) cost, heart rate, and blood lactate concentration for all-round (n = 6) and long-distance (n = 7) cross-country skiers in double poling (A, C, and E) and running (B, D, and F). Values are means and error bars indicate 95% confidence intervals. *Significant difference between groups (P < .05). #Tendency to difference between groups (.05 < P ≤ .1).

  • View in gallery

    —Changes in cycle time (A), poling time (B), and reposition time (C) by speed for all-round (n = 6) and long-distance (n = 7) cross-country skiers. Values are means and error bars indicate 95% confidence intervals. No differences between groups were detected.

  • View in gallery

    —Mean joint angles for the elbow (A), shoulder (C), hip (E), knee (B), and ankle (D) during double poling at 18 km·h−1 for all-round (n = 6) and long-distance (n = 7) cross-country skiers. Figure F shows the displacement of the center of mass with respect to its mean position during the cycle. The cycle starts (0%) and ends (100%) at pole plant, and the vertical dashed line indicates pole push-off. The horizontal line with asterisks (*) indicates significant differences between groups (unpaired t test, P < .05). #Tendency to difference between groups (.05 < P ≤ .1).

  • View in gallery

    —Percentage distribution of annual endurance training divided between classic skiing, skating skiing, running, and other endurance training modes for all-round (n = 6) and long-distance (n = 3) cross-country skiers. Values are means and error bars indicate 95% confidence intervals. Statistical analyses were not performed due to the low sample size. The data can only be interpreted as trends and should be interpreted with caution.

References
  • 1.

    Maldonado SMujika IPadilla S. Influence of body mass and height on the energy cost of running in highly trained middle- and long-distance runners. Int J Sports Med. 2002;23:268272. PubMed ID: 12015627 doi:10.1055/s-2002-29083

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Padilla SMujika ICuesta GGoiriena JJ. Level ground and uphill cycling ability in professional road cycling. Med Sci Sports Exerc. 1999;31:878885. PubMed ID: 10378916 doi:10.1097/00005768-199906000-00017

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Impellizzeri FMEbert TSassi AMenaspa PRampinini EMartin DT. Level ground and uphill cycling ability in elite female mountain bikers and road cyclists. Eur J Appl Physiol. 2008;102:335341. PubMed ID: 17943306 doi:10.1007/s00421-007-0590-9

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Losnegard THallén J. Physiological differences between sprint- and distance-specialized cross-country skiers. Int J Sports Physiol Perform. 2014;9:2531. PubMed ID: 24155024 doi:10.1123/ijspp.2013-0066

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Sandbakk ØHolmberg HC. Physiological capacity and training routines of elite cross-country skiers: approaching the upper limits of human endurance. Int J Sports Physiol Perform. 2017;12:10031011. PubMed ID: 28095083 doi:10.1123/ijspp.2016-0749

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Stöggl TLHolmberg HC. Double-poling biomechanics of elite cross-country skiers: flat versus uphill terrain. Med Sci Sports Exerc. 2016;48:15801589. doi:10.1249/MSS.0000000000000943

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Lindinger SJHolmberg HC. How do elite cross-country skiers adapt to different double poling frequencies at low to high speeds? Eur J Appl Physiol. 2011;111:11031119. PubMed ID: 21113613 doi:10.1007/s00421-010-1736-8

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Zoppirolli CPellegrini BBortolan LSchena F. Energetics and biomechanics of double poling in regional and high-level cross-country skiers. Eur J Appl Physiol. 2015;115:969979. PubMed ID: 25515019 doi:10.1007/s00421-014-3078-4

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Zoppirolli CBortolan LStella Fet al. Following a long-distance classical race the whole-body kinematics of double poling by elite cross-country skiers are altered. Front Physiol. 2018;9:978. PubMed ID: 30090070 doi:10.3389/fphys.2018.00978

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Skattebo ØHallen JRønnestad BRLosnegard T. Upper body heavy strength training does not affect performance in junior female cross-country skiers. Scand J Med Sci Sports. 2016;26:10071016. PubMed ID: 26146761 doi:10.1111/sms.12517

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Holmberg HCRosdahl HSvedenhag J. Lung function, arterial saturation and oxygen uptake in elite cross country skiers: influence of exercise mode. Scand J Med Sci Sports. 2007;17:437444. PubMed ID: 17040487

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Björklund GStöggl THolmberg HC. Biomechanically influenced differences in O2 extraction in diagonal skiing: arm versus leg. Med Sci Sports Exerc. 2010;42:18991908. doi:10.1249/MSS.0b013e3181da4339

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Ørtenblad NNielsen JBoushel RSöderlund KSaltin BHolmberg HC. The muscle fiber profiles, mitochondrial content, and enzyme activities of the exceptionally well-trained arm and leg muscles of elite cross-country skiers. Front Physiol. 2018;9:1031. PubMed ID: 30116201 doi:10.3389/fphys.2018.01031

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Van Hall GJensen-Urstad MRosdahl HHolmberg HCSaltin BCalbet JA. Leg and arm lactate and substrate kinetics during exercise. Am J Physiol Endocrinol Metab. 2003;284:E193E205. PubMed ID: 12388120 doi:10.1152/ajpendo.00273.2002

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Mygind E. Fibre characteristics and enzyme levels of arm and leg muscles in elite cross-country skiers. Scand J Med Sci Sports. 1995;5:7680. PubMed ID: 7606514 doi:10.1111/j.1600-0838.1995.tb00016.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Calbet JAHolmberg HCRosdahl Hvan Hall GJensen-Urstad MSaltin B. Why do arms extract less oxygen than legs during exercise? Am J Physiol Regul Integr Comp Physiol. 2005;289:R1448R1458. PubMed ID: 15919729 doi:10.1152/ajpregu.00824.2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Calbet JAJensen-Urstad Mvan Hall GHolmberg HCRosdahl HSaltin B. Maximal muscular vascular conductances during whole body upright exercise in humans. J Physiol. 2004;558:319331. PubMed ID: 15121799 doi:10.1113/jphysiol.2003.059287

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Holmberg HC. The elite cross-country skier provides unique insights into human exercise physiology. Scand J Med Sci Sports. 2015;25(suppl 4):100109. doi:10.1111/sms.12601

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Foss ØHallén J. Validity and stability of a computerized metabolic system with mixing chamber. Int J Sports Med. 2005;26:569575. PubMed ID: 16195991 doi:10.1055/s-2004-821317

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Sandbakk ØHegge AMLosnegard TSkattebo ØTønnessen EHolmberg HC. The physiological capacity of the world’s highest ranked female cross-country skiers. Med Sci Sports Exerc. 2016;48:10911100. PubMed ID: 26741124 doi:10.1249/MSS.0000000000000862

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Hoffman MDClifford PSBota BMandli MJones GM. Influence of body mass on energy cost of roller skiing. Int J Sport Biomech. 1990;6:374385. doi:10.1123/ijsb.6.4.374

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Losnegard TMyklebust HSkattebo ØStadheim HKSandbakk ØHallén J. The influence of pole length on performance, O2 cost, and kinematics in double poling. Int J Sports Physiol Perform. 2016;12:211217. PubMed ID: 27193356 doi:10.1123/ijspp.2015-0754

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Hopkins WGMarshall SWBatterham AMHanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41:313. PubMed ID: 19092709 doi:10.1249/MSS.0b013e31818cb278

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Myklebust HLosnegard THallen J. Differences in V1 and V2 ski skating techniques described by accelerometers. Scand J Med Sci Sports. 2013;24:882893. PubMed ID: 23957331 doi:10.1111/sms.12106

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Wisløff UHelgerud J. Methods for evaluating peak oxygen uptake and anaerobic threshold in upper body of cross-country skiers. Med Sci Sports Exerc. 1998;30:963970. PubMed ID: 9624659

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Helgerud JIngjer FStrømme SB. Sex differences in performance-matched marathon runners. Eur J Appl Physiol Occup Physiol. 1990;61:433439. PubMed ID: 2079063 doi:10.1007/BF00236064

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Strømme SBIngjer FMeen HD. Assessment of maximal aerobic power in specifically trained athletes. J Appl Physiol Respir Environ Exerc Physiol. 1977;42:833837. PubMed ID: 881383 doi:10.1152/jappl.1977.42.6.833

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Seiler KSKjerland GO. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sports. 2006;16:4956. PubMed ID: 16430681 doi:10.1111/j.1600-0838.2004.00418.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Bassett DR JrHowley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med Sci Sports Exerc. 2000;32:7084. PubMed ID: 10647532 doi:10.1097/00005768-200001000-00012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Åstrand IÅstrand POHallback IKilbom A. Reduction in maximal oxygen uptake with age. J Appl Physiol. 1973;35:649654. PubMed ID: 4770349 doi:10.1152/jappl.1973.35.5.649

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Ogawa TSpina RJMartin WH 3rdet al. Effects of aging, sex, and physical training on cardiovascular responses to exercise. Circulation. 1992;86:494503. PubMed ID: 1638717 doi:10.1161/01.CIR.86.2.494

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Sagelv EHEngseth TPPedersen Set al. Physiological comparisons of elite male visma ski classics and national level cross-country skiers during uphill treadmill roller skiing. Front Physiol. 2018;9:1523. PubMed ID: 30505276 doi:10.3389/fphys.2018.01523

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Sandbakk ØHolmberg HCLeirdal SEttema G. Metabolic rate and gross efficiency at high work rates in world class and national level sprint skiers. Eur J Appl Physiol. 2010;109:473481. PubMed ID: 20151149 doi:10.1007/s00421-010-1372-3

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Sandbakk ØHegge AMEttema G. The role of incline, performance level, and gender on the gross mechanical efficiency of roller ski skating. Front Physiol. 2013;4:293. PubMed ID: 24155722 doi:10.3389/fphys.2013.00293

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    Ainegren MCarlsson PTinnsten MLaaksonen MS. Skiing economy and efficiency in recreational and elite cross-country skiers. J Strength Cond Res. 2013;27:12391252. PubMed ID: 22344058 doi:10.1519/JSC.0b013e31824f206c

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36.

    Losnegard TMyklebust HSpencer MHallén J. Seasonal variations in VO2max, O2-cost, O2-deficit, and performance in elite cross-country skiers. J Strength Cond Res. 2013;27:17801790. PubMed ID: 22996025 doi:10.1519/JSC.0b013e31827368f6

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
Article Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 117 117 117
PDF Downloads 42 42 42
Altmetric Badge
PubMed
Google Scholar