Predicting VO[subscript 2max] in College-Aged Participants Using Cycle Ergometry and Perceived Functional Ability

Autor/inn/en	Nielson, David E.; George, James D.; Vehrs, Pat R.; Hager, Ron L.; Webb, Carrie V.
Titel	Predicting VO[subscript 2max] in College-Aged Participants Using Cycle Ergometry and Perceived Functional Ability
Quelle	In: Measurement in Physical Education and Exercise Science, 14 (2010) 4, S.252-264 (13 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1091-367X
Schlagwörter	Metabolism; Body Composition; Physical Activities; Predictor Variables; Multiple Regression Analysis; Measurement Techniques; Exercise Physiology; College Students; Measurement Equipment; Age Differences + Suchen Sie Ihr Suchwort? Stoffwechsel; Prädiktor; Messtechnik; Sportphysiologie; Collegestudent; Messinstrument; Age; Difference; Age difference; Altersunterschied
Abstract	The purpose of this study was to develop a multiple linear regression model to predict treadmill VO[subscript 2max] scores using both exercise and non-exercise data. One hundred five college-aged participants (53 male, 52 female) successfully completed a submaximal cycle ergometer test and a maximal graded exercise test on a motorized treadmill. The submaximal cycle protocol required participants to achieve a steady-state heart rate equal to at least 70% of age-predicted maximum heart rate (220-age), while the maximal treadmill graded exercise test required participants to exercise to volitional fatigue. Relevant submaximal cycle ergometer test data included a mean ([plus or minus]SD) ending steady-state heart rate and ending workrate equal to 164.2 [plus or minus] 13.0 bpm and 115.3 [plus or minus] 27.0 watts, respectively. Relevant non-exercise data included a mean ([plus or minus]SD) body mass (kg), perceived functional ability score, and physical activity rating score of 74.2 [plus or minus] 15.1, 15.7 [plus or minus] 4.3, and 4.7 [plus or minus] 2.1, respectively. Multiple linear regression was used to generate the following prediction of (R = 0.91, standard error of estimates (SEE) = 3.36 ml[middle dot]kg[superscript -1][middle dot]min[superscript -1]): VO[subscript 2max] = 54.513 + 9.752 (gender, 1 = male, 0 = female) -0.297 (body mass, kg) +0.739 (perceived functional ability, 2-26) +0.077 (work rate, watts) -0.072 (steady-state heart rate). Each predictor variable was statistically significant (p less than 0.05) with beta weights for gender, body mass, perceived functional ability, exercise workrate, and steady-state heart rate equal to 0.594, -0.544, 0.388, 0.305, and -0.116, respectively. The predicted residual sums of squares (PRESS) statistics reflected minimal shrinkage (R[subscript PRESS] = 0.90, SEE[subscript PRESS] = 3.56 ml[middle dot]kg[superscript -1][middle dot]min[superscript -1]) for the multiple linear regression model. In summary, the submaximal cycle ergometer protocol and accompanying prediction model yield relatively accurate VO[subscript 2max] estimates in healthy college-aged participants using both exercise and non-exercise data. (Contains 2 figures and 3 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10