Cross-validation of ventilatory threshold prediction equations on aerobically trained men and women

被引:5
|
作者
Malek, Moh H. [1 ]
Housh, Terry J.
Coburn, Jared W.
Schmidt, Richard J.
Beck, Travis W.
机构
[1] Univ Nebraska, Dept Nutr & Hlth Sci, Human Performance Lab, Lincoln, NE 68583 USA
[2] Calif State Univ Fullerton, Dept Kinesiol, Fullerton, CA 92834 USA
关键词
endurance-trained; regression analysis; statistics; V-slope method;
D O I
10.1519/00124278-200702000-00006
中图分类号
G8 [体育];
学科分类号
04 ; 0403 ;
摘要
The purpose of this investigation was to determine the validity of the non-exercise-based equations of Davis et al. (13), Jones et al. (20), and Neder et al. (30) for estimating the ventilatory threshold (VT) in samples of aerobically trained men and women. One hundred and forty-four aerobically trained men (mean +/- SD age, 41.0 +/- 11.6 years; N = 83) and women (37.1 +/- 9.0 years, N = 61) performed a maximal incremental test to determine Vo(2)max and observed VT on a cycle ergometer. The observed VT was determined by gas exchange measurements using the V-slope method (Vco(2)/ Vo(2)) in conjunction with analyses of the ventilatory equivalents (i.e., minute ventilation V-E/Vo(2) and V-E/Vco(2)) and end-tidal gas tensions (i.e., PETO2 and PETCO2) for oxygen and carbon dioxide. The predicted VT values from 14 equations were compared to the observed VT values by examining the constant error (CE), standard error of estimate (SEE), Pearson correlation coefficient (r), and total error (TE). The results of this investigation indicated that all 14 equations resulted in significant (p < 0.008) CE values ranging from 1.13 to 1.72 L center dot min(-1) for the men and from 0.58 to 1.12 L center dot min(-1) for the women. Furthermore, the SEE, r, and TE values ranged from 0.37 to 0.54, from 0.36 to 0.53, and from 0.68 to 1.81 L center dot min(-1), respectively. The lowest TE values for the men and women represented 45 and 36% of the mean of the observed VT values, respectively. The results of this study indicated that the errors associated with all 14 equations were too large to be of practical value for estimating VT in aerobically trained men and women.
引用
收藏
页码:29 / 33
页数:5
相关论文
共 50 条
  • [1] A new ventilatory threshold equation for aerobically trained men and women
    Malek, Moh H.
    Coburn, Jared W.
    CLINICAL PHYSIOLOGY AND FUNCTIONAL IMAGING, 2009, 29 (02) : 143 - 150
  • [2] Cross-Validation of Resting Metabolic Rate Prediction Equations
    Flack, Kyle D.
    Siders, William A.
    Johnson, LuAnn
    Roemmich, James N.
    JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS, 2016, 116 (09) : 1413 - 1422
  • [3] CROSS-VALIDATION FOR PREDICTION
    COOIL, B
    WINER, RS
    RADOS, DL
    JOURNAL OF MARKETING RESEARCH, 1987, 24 (03) : 271 - 279
  • [4] Ventilatory Threshold Correlates with Autonomic Function in Endurance-Trained Young Men and Women
    Gonzalez-Mejia, Jose
    Webb, Shannon
    Sherwood, Jennifer
    Brizendine, Evan
    Yingling, Vanessa
    Lansangan, Steven
    Tran, Trina
    Inouye, Cathy
    MEDICINE AND SCIENCE IN SPORTS AND EXERCISE, 2015, 47 (05): : 534 - 534
  • [5] Cross-validation Of Whole Body Sweat Sodium Prediction Equations
    Baker, Lindsay B.
    Nuccio, Ryan P.
    Reimel, Adam J.
    Brown, Shyretha
    Ungaro, Corey T.
    De Chavez, Peter J. D.
    Barnes, Kelly A.
    MEDICINE & SCIENCE IN SPORTS & EXERCISE, 2020, 52 (07) : 969 - 969
  • [6] CROSS-VALIDATION AND MULTINOMIAL PREDICTION
    STONE, M
    BIOMETRIKA, 1974, 61 (03) : 509 - 515
  • [7] Cross-validation of prediction equations for estimating body composition in ballet dancers
    Araujo Leal, Leilane Lilian
    Lopes Barbosa, Giovanna Stefanne
    Urbano Ferreira, Rannapaula Lawrynhuk
    Avelino, Erikarla Baracho
    Bezerra, Adriana Nunes
    de Lima Vale, Sancha Helena
    Lima Maciel, Bruna Leal
    PLOS ONE, 2019, 14 (07):
  • [8] Cross-Validation of Recent and Longstanding Resting Metabolic Rate Prediction Equations
    Flack, Kyle D.
    Siders, William A.
    Johnson, Luann
    Roemmich, James N.
    FASEB JOURNAL, 2016, 30
  • [9] Cross-Validation Without Doing Cross-Validation in Genome-Enabled Prediction
    Gianola, Daniel
    Schoen, Chris-Carolin
    G3-GENES GENOMES GENETICS, 2016, 6 (10): : 3107 - 3128
  • [10] Constructive cross-validation in linear prediction
    Spitzner, Dan J.
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2007, 36 (05) : 939 - 953