Prediction of Maximum Oxygen Uptake Using Both Exercise and Non-Exercise Data

Autor/inn/en	George, James D.; Paul, Samantha L.; Hyde, Annette; Bradshaw, Danielle I.; Vehrs, Pat R.; Hager, Ronald L.; Yanowitz, Frank G.
Titel	Prediction of Maximum Oxygen Uptake Using Both Exercise and Non-Exercise Data
Quelle	In: Measurement in Physical Education and Exercise Science, 13 (2009) 1, S.1-12 (12 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1091-367X
Schlagwörter	Metabolism; Body Composition; Physical Activities; Physical Activity Level; Predictor Variables; Prediction; Data Analysis; Exercise Physiology; Regression (Statistics); Gender Differences; Questionnaires; Tests + Suchen Sie Ihr Suchwort? Stoffwechsel; Prädiktor; Vorhersage; Auswertung; Sportphysiologie; Regression; Regressionsanalyse; Geschlechterkonflikt; Fragebogen; Examination; Prüfung; Examen
Abstract	This study sought to develop a regression model to predict maximal oxygen uptake (VO[subscript 2max]) based on submaximal treadmill exercise (EX) and non-exercise (N-EX) data involving 116 participants, ages 18-65 years. The EX data included the participants' self-selected treadmill speed (at a level grade) when exercise heart rate first reached at least 70% of predicted maximum heart rate (HR[subscript max]; 220 - age) by the end of any one of three 4-min consecutive stages involving walking (3.0-4.0 mph; Stage 1), jogging (4.1-6.0 mph; Stage 2), and running (greater than 6.0 mph; Stage 3). The N-EX data included various demographic (age, gender), biometric (body mass), and questionnaire (participants' perceived functional ability [PFA] to walk, jog, or run given distances, and their self-reported level of physical activity [PA-R]) information. All participants (n = 100) who completed the study requirements and successfully achieved a maximal level of exertion during a graded exercise test (GXT) to assess VO[subscript 2max] (mean [plus or minus] SD; 41.39 [plus or minus] 9.15 ml [middle dot] kg[superscript -1] [middle dot] min[superscript -1]) were included in the data analysis. Stepwise regression was used to generate the following prediction equation (R = 0.94, SEE = 3.09 ml [middle dot] kg[superscript -1] [middle dot] min[superscript -1]): VO[subscript 2max] (ml [middle dot] kg[superscript -1] [middle dot] min[superscript -1]) = 30.04 + (6.37 x gender; females = 0, males = 1) - (0.243 x age) - (0.122 x body mass) + (3.263 x ending self-selected treadmill speed; mph) + (0.391 x PFA) + (0.669 x PA-R). Each of the predictor variables were statistically significant (p less than 0.001) and cross-validation procedures using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (R[subscript p] = 0.92 and SEE[subscript p] = 3.29 ml [middle dot] kg[superscript -1] [middle dot] min[superscript -1]). In summary, this submaximal treadmill test and accompanying regression model yields relatively accurate VO[subscript 2max] estimates in healthy men and women (ages 18-65 years) using both EX and N-EX data. (Contains 1 figure and 4 tables. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10