Are Gender Differences in Upper-Body Power Generated by Elite Cross-Country Skiers Augmented by Increasing the Intensity of Exercise?

Hegge, Ann Magdalen; Myhre, Kenneth; Welde, Boye; Holmberg, Hans‐Christer; Sandbakk, Øyvind

doi:10.1371/journal.pone.0127509

Cited by 42 publications

(42 citation statements)

References 33 publications

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“…Reducing the fat percentage and increasing the lean body ratio is important to achieve high VO2max. The different study results clearly show that %Fat and FFM have not only an aerobic endurance but also a great effect on anaerobic and muscle strength [26,27].…”

Section: Discussionmentioning

confidence: 92%

Evaluation of the relationship between body composition and aerobic fitness in youth soccer players

Nalbant¹,

Özer

2018

PES

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Background and Study Aim: The purpose of the study was to make an evaluation between aerobic fitnes (VO2max) and body composition in youth soccer players. Material and Methods: U19, U17, U16 and U15 age groups participated in the study. Twenty-eight U19 (average age 18,03±0,58), twenty-three U17 (average age 16,72±0,30), twenty-seven U16 (average age 15,79±0,23) and twenty-one U15 (average age 14,67±0,31) totally ninety-nine athletes voluntarily participated in the study. The subjects’ body weight and fat percentage were estimated by bioelectrical impedance. VO2max was determined by YOYO Intermittan Recovery test protocol. Shapiro-wilk test, Independent t test, hierarchical regression and analysis of covariance were used to compare the relationships between aerobic fitness and body composition. Additionally, Pearson correlation coefficients were calculated to examine the relationships between variables. The level of significance for all statistics was set at p<0.05. SPSS 23 software was used to calculate the data. The total value of all estimators is f = 18,001 and p <0.0001. Results : Although all variables were included in the model, the BMI was considered the greatest explanatory factor for fatness. Aerobic endurance was assessed in direct proportion to age, sit and reach test, crunch test, plank, and long jump test. As the distance increased, the% fat ratio decreased (p <0.001), and the fat ratio decreased with the decrease in the T test (p <0.001). Conclusions: In this study, it was determined that body fat ratio determined by BMI, body fat percentage decreased with increasing aerobic endurance, body fat ratio was negatively correlated with aerobic fitness and lean body ratio. It was also determined that aerobic fitness was positively correlated with age, sit and reach, crunch test, plank, standing long jump and T test.

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Section: Discussionmentioning

confidence: 92%

Evaluation of the relationship between body composition and aerobic fitness in youth soccer players

Nalbant¹,

Özer

2018

PES

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“…Power output and cycle rate were continuously measured by the ergometer´s internal software, which has been validated in previous studies [19, 23]. …”

Section: Methodsmentioning

confidence: 99%

Association between laboratory capacities and world-cup performance in Nordic combined

et al. 2017

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BackgroundNordic combined (NC) is an Olympic winter-sport performed as a ski jumping (SJ) event followed by a cross-country (XC) pursuit race employing the skating style.PurposeTo elucidate the associations between sport-specific laboratory capacities and SJ, XC skiing, and overall NC performance in a world-cup NC event.MethodsTwelve international world-cup NC athletes from 8 nations performed laboratory testing one day prior to participating in a world-cup NC event. Squat jumps and SJ imitations (IMIT) were performed on a three-dimensional force plate, whereas XC skiing-specific physiological characteristics were obtained from roller ski skating tests on a treadmill and an all-out double poling (DP) test. Finally, body composition was measured. Laboratory capacities were correlated against performance in SJ, 10-km XC skiing, and overall NC in the world-cup event. Multiple regression analysis was used to determine the best suited laboratory variables for predicting performance.ResultsVertical IMIT velocity together with body-mass provided the best prediction for SJ performance (r2 = 0.70, p<0.01), while body-mass-normalized and DP power provided the best prediction for XC performance (r2 = 0.68, p<0.05). Body-mass-normalized was the only significant correlate with overall NC performance (r2 = 0.43, p<0.05) in this competition.ConclusionOverall, the concurrent development of , upper-body power, and SJ-specific vertical jump capacity while minimizing body-mass within the BMI limit set by FIS should be considered in the seasonal training of NC athletes.

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“…However, because of gender differences related to physiological characteristics, it is not recommended to use this model to evaluate sprint performance capability of elite female skiers. For example, men have both higher

{\dot{normalV} O}_{2 \max}

and LM independent of the absolute or relative expressions used 11,16–18…”

Section: Introductionmentioning

confidence: 99%

Aerobic power and lean mass are indicators of competitive sprint performance among elite female cross-country skiers

Carlsson¹,

Tonkonogi²,

Carlsson³

2016

OAJSM

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The purpose of this study was to establish the optimal allometric models to predict International Ski Federation’s ski-ranking points for sprint competitions (FISsprint) among elite female cross-country skiers based on maximal oxygen uptake ( normalV˙O2max) and lean mass (LM). Ten elite female cross-country skiers (age: 24.5±2.8 years [mean ± SD]) completed a treadmill roller-skiing test to determine normalV˙O2max (ie, aerobic power) using the diagonal stride technique, whereas LM (ie, a surrogate indicator of anaerobic capacity) was determined by dual-emission X-ray anthropometry. The subjects’ FISsprint were used as competitive performance measures. Power function modeling was used to predict the skiers’ FISsprint based on normalV˙O2max, LM, and body mass. The subjects’ test and performance data were as follows: normalV˙O2max, 4.0±0.3 L min−1; LM, 48.9±4.4 kg; body mass, 64.0±5.2 kg; and FISsprint, 116.4±59.6 points. The following power function models were established for the prediction of FISsprint: 3.91×105⋅normalV˙O2max−6.00 and 6.95 × 1010 · LM−5.25; these models explained 66% (P=0.0043) and 52% (P=0.019), respectively, of the variance in the FISsprint. Body mass failed to contribute to both models; hence, the models are based on normalV˙O2max and LM expressed absolutely. The results demonstrate that the physiological variables that reflect aerobic power and anaerobic capacity are important indicators of competitive sprint performance among elite female skiers. To accurately indicate performance capability among elite female skiers, the presented power function models should be used. Skiers whose normalV˙O2max differs by 1% will differ in their FISsprint by 5.8%, whereas the corresponding 1% difference in LM is related to an FISsprint difference of 5.1%, where both differences are in favor of the skier with higher normalV˙O2max or LM. It is recommended that coaches use the absolute expression of these variables to monitor skiers’ performance-related training adaptations linked to changes in aerobic power and anaerobic capacity.

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Are Gender Differences in Upper-Body Power Generated by Elite Cross-Country Skiers Augmented by Increasing the Intensity of Exercise?

Cited by 42 publications

References 33 publications

Evaluation of the relationship between body composition and aerobic fitness in youth soccer players

Evaluation of the relationship between body composition and aerobic fitness in youth soccer players

Association between laboratory capacities and world-cup performance in Nordic combined

Aerobic power and lean mass are indicators of competitive sprint performance among elite female cross-country skiers

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