Andersson Erik P, Noordhof Dionne A, Lögdal Nestor
Department of Health Sciences, Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden.
Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, Centre for Elite Sports Research, Norwegian University of Science and Technology, Trondheim, Norway.
Front Sports Act Living. 2020 Apr 15;2:37. doi: 10.3389/fspor.2020.00037. eCollection 2020.
Anaerobic capacity is an important performance-determining variable of sprint cross-country skiing. Nevertheless, to date, no study has directly compared the anaerobic capacity, determined using the maximal accumulated oxygen deficit (MAOD) method and gross efficiency (GE) method, while using different skiing sub-techniques. To compare the anaerobic capacity assessed using two different MAOD approaches (including and excluding a measured y-intercept) and the GE method during double poling (DP) and diagonal stride (DS) cross-country skiing. After an initial familiarization trial, 16 well-trained male cross-country skiers performed, in each sub-technique on separate occasions, a submaximal protocol consisting of eight 4-min bouts at intensities between ~47-78% of O followed by a 4-min roller-skiing time trial, with the order of sub-technique being randomized. Linear and polynomial speed-metabolic rate relationships were constructed for both sub-techniques, while using a measured y-intercept (8+ and 8+Y) or not (8-Y and 8-Y), to determine the anaerobic capacity using the MAOD method. The average GE (GE) of all eight submaximal exercise bouts or the GE of the last submaximal exercise bout (GE) were used to calculate the anaerobic capacity using the GE method. Repeated measures ANOVA were used to test differences in anaerobic capacity between methods/approaches. A significant interaction was found between computational method and skiing sub-technique ( < 0.001, η = 0.51) for the anaerobic capacity estimates. The different methodologies resulted in significantly different anaerobic capacity values in DP ( < 0.001, η = 0.74) and in DS ( = 0.016, η = 0.27). The 8-Y model resulted in the smallest standard error of the estimate (SEE, 0.24 W·kg) of the MAOD methods in DP, while the 8-Y resulted in a smaller SEE value than the 8+ model (0.17 vs. 0.33 W·kg) in DS. The 8-Y and GE resulted in the closest agreement in anaerobic capacity values in DS (typical error 2.1 mL Oeq·kg). It is discouraged to use the same method to estimate the anaerobic capacity in DP and DS sub-techniques. In DP, a polynomial MAOD method (8-Y) seems to be the preferred method, whereas the 8-Y, GE, and GE can all be used for DS, but not interchangeable, with GE being the least time-consuming method.
无氧能力是越野滑雪冲刺表现的一个重要决定变量。然而，迄今为止，尚无研究在使用不同滑雪子技术的情况下，直接比较采用最大累积氧亏（MAOD）法和总效率（GE）法测定的无氧能力。比较在双杖滑雪（DP）和斜向滑行（DS）越野滑雪过程中，使用两种不同的MAOD方法（包括和不包括测量的y轴截距）和GE法评估的无氧能力。在进行一次初始熟悉试验后，16名训练有素的男性越野滑雪运动员在不同场合，针对每种子技术进行了一个次最大强度方案，该方案由8次4分钟的运动组成，强度在约47 - 78%的最大摄氧量之间，随后进行4分钟的轮滑计时赛，子技术的顺序是随机的。针对两种子技术构建了线性和多项式速度 - 代谢率关系，使用测量的y轴截距（8 + 和8 + Y）或不使用（8 - Y和8 - Y），以使用MAOD法确定无氧能力。使用所有八次次最大强度运动的平均总效率（GE）或最后一次次最大强度运动的总效率（GE）来使用GE法计算无氧能力。采用重复测量方差分析来测试不同方法/途径之间无氧能力的差异。对于无氧能力估计，发现计算方法和滑雪子技术之间存在显著交互作用（< 0.001，η = 0.51）。不同方法在DP（< 0.001，η = 0.74）和DS（ = 0.016，η = 0.27）中产生了显著不同的无氧能力值。8 - Y模型在DP的MAOD方法中产生了最小的估计标准误差（SEE，0.24 W·kg），而在DS中，8 - Y产生的SEE值比8 + 模型小（0.17对0.33 W·kg）。在DS中，8 - Y和GE在无氧能力值上的一致性最接近（典型误差2.1 mL Oeq·kg）。不建议在DP和DS子技术中使用相同方法估计无氧能力。在DP中，多项式MAOD方法（8 - Y）似乎是首选方法，而8 - Y、GE和GE均可用于DS，但不可互换，其中GE是最省时的方法。
