Department of Health and Kinesiology, Applied Exercise Science Laboratory, Texas A&M University, College Station, Texas.
Department of Kinesiology, Texas Christian University, Ft. Worth, Texas.
J Strength Cond Res. 2019 Apr;33(4):1028-1034. doi: 10.1519/JSC.0000000000003071.
Crouse, SF, Tolson, H, Lytle, J, Johnson, KA, Martin, SE, Green, JS, Oliver, J, Carbuhn, A, Lambert, B, and Bramhall, JP. Predicting V[Combining Dot Above]O2max from treadmill performance in American-style football athletes. J Strength Cond Res 33(4): 1028-1034, 2019-Prediction equations are often used to estimate V[Combining Dot Above]O2max in the general population but are lacking for American-style football (ASF) athletes. We sought to develop a regression model to estimate V[Combining Dot Above]O2max from treadmill exercise time in ASF athletes and compare our football V[Combining Dot Above]O2max model with 2 published prediction equations (Foster et al., 1984, and Bruce, 1973). American-style football athletes (N = 472, age = 18 ± 1 year, height = 186.1 ± 8.2 cm, and body mass = 101.8 ± 20.4 kg) underwent treadmill exercise to voluntary exhaustion (Bruce protocol). Maximal exercise time was recorded in minutes (Tmin), and V[Combining Dot Above]O2max was simultaneously measured (M-V[Combining Dot Above]O2max, mlO2·kg·min) by an automated gas-analysis system. Athletes were then randomly divided into validation and cross-validation groups (n = 236). Linear regression yielded estimates of V[Combining Dot Above]O2max from Tmin as follows: validation V[Combining Dot Above]O2max = 4.012 × Tmin - 4.628 (r = 0.678, p < 0.001, and SEE = 4.07); cross-validation V[Combining Dot Above]O2max = 4.025 × Tmin - 4.693 (r = 0.661, p < 0.001, and SEE = -4.16). These equations had a cross-validation coefficient of 0.813 and a double cross-validation coefficient of 0.823. Differences between the slopes of the 2 equations were not significant (t-test, p = 0.9603). Because validation and cross-validation groups were not statistically different on any variables measured (multivariate analysis of variance, p > 0.05), all athletes were combined to yield our final prediction equation: football V[Combining Dot Above]O2max = 4.017 × Tmin - 4.644 (r = 0.670, p < 0.001, and SEE = 4.11). Repeated-measures analysis of variance demonstrated significant differences (p < 0.001) in estimates of V[Combining Dot Above]O2max among Foster (44.1 ± 6.1), Bruce (47.1 ± 5.5), and our football (45.1 ± 5.8) equations. Foster and Bruce V[Combining Dot Above]O2max estimates were also significantly different from M-V[Combining Dot Above]O2max ((Equation is included in full-text article.)diff = -0.975 and 1.995, respectively, p < 0.001). V[Combining Dot Above]O2max of ASF athletes can be reasonably estimated by our football prediction equation using maximal treadmill time as the predictor.
克劳斯 SF、托尔森 H、莱特尔 J、约翰逊 KA、马丁 SE、格林 JS、奥利弗 J、卡布恩 A、兰伯特 B 和布拉姆霍尔 JP。用跑步机性能预测美式足球运动员的最大摄氧量。J 力量与调节研究 33(4):1028-1034，2019 年-预测方程常用于估计普通人群中的最大摄氧量，但缺乏美式足球运动员的预测方程。我们试图建立一个回归模型，从美式足球运动员的跑步机运动时间来估计 V[Combining Dot Above]O2max，并将我们的足球 V[Combining Dot Above]O2max 模型与 2 个已发表的预测方程（福斯特等人，1984 年；布鲁斯，1973 年）进行比较。美式足球运动员（N = 472，年龄 = 18 ± 1 岁，身高 = 186.1 ± 8.2 厘米，体重 = 101.8 ± 20.4 千克）进行跑步机至力竭的运动（布鲁斯方案）。最大运动时间以分钟（Tmin）记录，同时通过自动气体分析系统同时测量最大摄氧量（M-V[Combining Dot Above]O2max，mlO2·kg·min）。然后，运动员被随机分为验证组和交叉验证组（n = 236）。线性回归得出了 Tmin 估计的 V[Combining Dot Above]O2max 如下：验证 V[Combining Dot Above]O2max = 4.012 × Tmin - 4.628（r = 0.678，p < 0.001，SEE = 4.07）；交叉验证 V[Combining Dot Above]O2max = 4.025 × Tmin - 4.693（r = 0.661，p < 0.001，SEE = -4.16）。这些方程的交叉验证系数为 0.813，双交叉验证系数为 0.823。两个方程的斜率差异不显著（t 检验，p = 0.9603）。由于验证组和交叉验证组在任何测量变量上都没有统计学差异（多变量方差分析，p > 0.05），因此所有运动员都被合并，得出我们的最终预测方程：足球 V[Combining Dot Above]O2max = 4.017 × Tmin - 4.644（r = 0.670，p < 0.001，SEE = 4.11）。重复测量方差分析表明，福斯特（44.1 ± 6.1）、布鲁斯（47.1 ± 5.5）和我们的足球（45.1 ± 5.8）方程之间的 V[Combining Dot Above]O2max 估计值存在显著差异（p < 0.001）。福斯特和布鲁斯 V[Combining Dot Above]O2max 估计值也与 M-V[Combining Dot Above]O2max 显著不同（（方程包含在全文中）差异分别为 -0.975 和 1.995，p < 0.001）。我们的足球预测方程可以合理地估计美式足球运动员的 V[Combining Dot Above]O2max，方法是将最大跑步机时间作为预测因子。
