James D. George

Non-exercise VO2max estimation for physically active college students.

This study sought to develop a maximal oxygen consumption (VO2max) regression model derived strictly from self-reported non-exercise (N-EX) predictor variables. The VO2max (mean +/- SD; 44.05 +/- 6.6 ml.kg-1.min-1) of 100 physically active college students (50 females, 50 males), aged 18 to 29 yr, was measured using a treadmill protocol and open circuit calorimetry. Questionnaire-based predictor variables used in the N-EX regression model included (a) the subjects perceived functional ability (PFA) to walk, jog, or run given distances, (b) habitual physical activity (PA-R) data, (c) body mass index (BMI), and (d) gender. BMI (kg.m-2) was computed from self-reported body weight in pounds and self-reported body height in feet and inches. The questionnaire-based N-EX regression model (R = 0.85, SEE = 3.44 ml.kg-1.min-1) developed in this study exceeded the accuracy of previously developed N-EX regression models and is comparable to many exercise-based regression models in the literature. Cross-validation using PRESS (predicted residual sum of squares) statistics demonstrated minimal shrinkage (R = 0.84, SEE = 3.60 ml.kg-1.min-1) of the present regression model. The PFA data were useful in explaining observed VO2max variance (squared partial r2 = 0.155, P < 0.0001) and enhanced the ability of the N-EX regression model to accurately predict criterion VO2max. These results suggest that a questionnaire-based N-EX regression model provides a valid and convenient method for predicting VO2max in physically active college students.

VO2max estimation from a submaximal 1-mile track jog for fit college-age individuals.

The primary purpose of this study was to develop a submaximal field test for the estimation of maximal oxygen uptake (VO2max) using a 1-mile track jog. A second purpose was to determine the accuracy of the 1.5-mile run in estimating VO2max for both male and female subjects. VO2max was measured in 149 relatively fit college students (males = 88, females = 61) 18-29 yr using a treadmill protocol (mean +/- SD; VO2max = 47.7 +/- 6.3 ml.kg-1 x min-1). Multiple regression analysis (N = 54) to estimate VO2max from the submaximal, steady-state 1-mile track jog yielded the following validation (V) model (r(adi) = 0.87, SEE = 3.0 ml.kg-1 x min-1): VO2max = 100.5 + 8.344* GENDER (0 = female; 1 = male) - 0.1636* BODY MASS (kg) - 1.438* JOG TIME (min.mile-1) - 0.1928* HEART RATE (bpm). To help ensure that a submaximal level of exertion was realized for the 1-mile track jog, elapsed jog time was restricted to > or = 8.0 min for males and > or = 9.0 min for females and exercise HR to < or = 180 bpm. Cross-validation (CV) of the 1-mile track jog comparing observed and estimated VO2max (N = 52) resulted in radj = 0.84, SEE = 3.1 ml.kg-1 x min-1. Multiple regression analysis (N = 50) to estimate VO2max from the 1.5-mile run (V:N = 49, radj = 0.90, SEE = 2.8 ml.kg-1 x min-1; CV: N = 47, radj = 0.82, SEE = 3.9 ml.kg-1 x min-1), used elapsed run time, body mass, and gender as independent variables.(ABSTRACT TRUNCATED AT 250 WORDS)

An Accurate VO2max Nonexercise Regression Model for 18–65-Year-Old Adults

Abstract The purpose of this study was to develop a regression equation to predict maximal oxygen uptake (VO2max) based on nonexercise (N-EX) data. All participants (N= 100), ages 18–65 years, successfully completed a maximal graded exercise test (GXT) to assess VO2max (M= 39.96 mL·kg -1· min -1 , SD = 9.54). The N-EX data collected just before the maximal GXT included the participants age; gender; body mass index (BMI); perceived functional ability (PFA) to walk, jog, or run given distances; and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL·kg -1· min -1 , %SEE= 8.62): VO2max (mL·kg -1· min -1 ) = 48.0730 + (6.1779 x gender; women = 0, men = 1) – (0.2463 x age) – (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (R p = .91 and SEE p = 3.63 mL·kg -1· min -1 ); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (ages 18–-65 years) with a similar cardiorespiratory fitness level. Based on standardized β-weights, the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.

Prediction of Maximum Oxygen Consumption from Walking, Jogging, or Running.

Abstract The purpose of this study was to develop a submaximal, 1.5-mile endurance test for college-aged students using walking, jogging, or running exercise. College students (N = 101: 52 men, 47 women), ages 18–26 years, successfully completed the 1.5-mile test twice, and a maximal graded exercise test. Participants were instructed to achieve a “somewhat hard” exercise intensity (rating of perceived exertion = 13) and maintain a steady pace throughout each 1.5-mile test. Multiple linear regression generated the following prediction equation: VO2max = 65.404 + 7.707 × gender (1 = male; 0 = female) − 0.159 × body mass (kg) − 0.843 × elapsed exercise time (min; walking, jogging, or running). This equation shows acceptable validity (R = .86, SEE = 3.37 ml•kg1 •min−1) similar to the accuracy of comparable field tests, and reliability (ICC = .93) is also comparable to similar models. The statistical shrinkage is minimal (Rpress = 0.85, SEEpress = 3.51 ml•kg1 •min−1); hence, it should provide comparable results when applied to other similar samples. A regression model (R = .90, and SEE = 2.87 ml•kg1 •min−1) including exercise heart rate was also developed: VO2max = 100.162 + 7.301 × gender (1 = male; 0 = female) − 0.164 × body mass (kg) − 1.273 × elapsed exercise time − 0.156 × exercise heart rate, for those who have access to electronic heart rate monitors. This submaximal 1.5-mile test accurately predicts maximal oxygen uptake (VO2max) without measuring heart rate and is similar to the 1.5-mile run in that it allows for mass testing and requires only a flat, measured distance and a stopwatch. Further, it can accommodate a wide range of fitness levels (from walkers to runners).

Effect of water running and cycling on maximum oxygen consumption and 2-mile run performance

This study compared water running, cycling, and run ning for maintaining VO2max and 2-mile run perform ance over a 6-week training period. Thirty-two trained subjects between the ages of 18 and 26 were evaluated for maximum oxygen uptake (VO2max) and 2-mile run performance. Subjects were stratified by a 2-mile run pretest into high, medium, and low performance levels and then randomly assigned to water running, cycling, or running training. The three groups trained with similar frequency, duration, and intensity over a 6-week period. After 6 weeks of training, all of the groups made a small but statistically significant decrease in fitness (VO2max), but no change in 2-mile run time. However, there were no differences with respect to either training modality or pretraining performance level. It was concluded that over a 6-week period, runners who cannot run because of soft tissue injury can maintain VO2max and 2-mile run performance similar to running training with either cycling or water running.

Development of a submaximal treadmill jogging test for fit college-aged individuals.

The purpose of this study was to develop a single-stage submaximal treadmill jogging test for the estimation of maximal oxygen uptake (VO2max). VO2max was measured in 129 relatively fit individuals (males = 84, females = 45), 18-29 yr, using a maximal treadmill protocol (mean +/- SD; VO2max = 48.3 +/- 6.2 ml.kg-1 x min-1, range = 35.6 to 62.3 ml.kg-1 x min-1). The treadmill test required subjects to sustain a comfortable, submaximal jogging pace (4.3-7.5 mph; level grade) until a steady-state heart rate was achieved (approximately 3 min). To help ensure that a submaximal level of exertion was realized for the treadmill jogging test, treadmill speed and exercise HR criteria were established that restricted treadmill speed to < or = 7.5 mph for males and < or = 6.5 mph for females and steady-state exercise HR < or = 180 bpm. Multiple regression analysis (N = 66) to estimate VO2max from the treadmill jogging test yielded the following validation (V) model (r(adj) = 0.84, SEE = 3.2 ml.kg-1 x min-1): VO2max = 54.07 + 7.062 * GENDER (0 = female; 1 = male) - 0.1938 * WEIGHT (kg) + 4.47* SPEED (miles.h-1) - 0.1453 * HEART RATE (bpm). Cross-validation (CV) of the treadmill jogging test comparing observed and estimated VO2max (N = 63) resulted in r(adj) = 0.88, SEE = 3.1 ml.kg-1 x min-1. The results indicate that this submaximal single-stage treadmill jogging test based on multiple linear regression provides a valid and convenient method for estimating VO2max.

Evaluation of an Internet, Stage-Based Physical Activity Intervention

Abstract This study evaluated the effectiveness of online, stage-based materials on exercise behavior and stage of readiness to change. Participants (n=525) were assigned to a stage-based group, an action-message group, or a control group. Seven-day physical activity, occupational and leisure activity, exercise self-efficacy, and stage of readiness to change were assessed at baseline and 6 weeks. The action-message group demonstrated significant increases in leisure time activity, occupational activity, and daily energy expenditure estimated from a 7-day recall. The stage-based message group demonstrated significant increases in leisure time activity only. All three groups demonstrated small improvements in stage of readiness to change. In a 6-week, online intervention, stage-based messages were less effective than action messages.

Submaximal Treadmill Exercise Test to Predict VO2max in Fit Adults

This study was designed to develop a single-stage submaximal treadmill jogging (TMJ) test to predict VO2max in fit adults. Participants (N = 400; men = 250 and women = 150), ages 18 to 40 years, successfully completed a maximal graded exercise test (GXT) at 1 of 3 laboratories to determine VO2max. The TMJ test was completed during the first 2 stages of the GXT. Following 3 min of walking (Stage 1), participants achieved a steady-state heart rate (HR) while exercising at a comfortable self-selected submaximal jogging speed at level grade (Stage 2). Gender, age, body mass, steady-state HR, and jogging speed (mph) were included as independent variables in the following multiple linear regression model to predict VO2max (R = 0.91, standard error of estimate [SEE] = 2.52 mL · kg−1 · min−1): VO2max (mL · kg−1 · min−1) = 58.687 + (7.520 × Gender; 0 = woman and 1 = man) + (4.334 × mph) − (0.211 × kg) − (0.148 × HR) − (0.107 × Age). Based on the predicted residual sum of squares (PRESS) statistics (RPRESS = 0.91, SEE PRESS = 2.54 mL · kg−1 · min−1) and small total error (TE; 2.50 mL · kg−1 · min−1; 5.3% of VO2max) and constant error (CE; −0.008 mL · kg−1 · min−1) terms, this new prediction equation displays minimal shrinkage. It should also demonstrate similar accuracy when it is applied to other samples that include participants of comparable age, body mass, and aerobic fitness level. This simple TMJ test and its corresponding regression model provides a relatively safe, convenient, and accurate way to predict VO2max in fit adults, ages 18 to 40 years.

A Modified Submaximal Cycle Ergometer Test Designed to Predict Treadmill VO2max

This study sought to develop a modified submaximal cycle ergometer test designed to predict maximal oxygen consumption (VO2max) obtained on a treadmill. Volunteers (N = 156; women = 80, men = 76) with ages from 18 to 39 years old successfully performed a submaximal cycle protocol on a stationary cycle ergometer and a maximal graded exercise test (GXT) on a treadmill. Open circuit calorimetry was used during the GXT to measure VO2max. Multiple linear regression resulted in the following prediction equation: VO2max = 85.447 + 9.104 χSex (0 = women; 1 = men) - 0.2676 χAge (year) - 0.4150 χBody Mass (kg) + 0.1317 χPower Output (W) - 0.1615 χHeart Rate (bpm), which had acceptable validity (r = .88, standard error of estimate [SEE] = 3.12 ml· kg-1 · min-1). Selected participants (n = 34) performed the submaximal cycle ergometer test twice (within a 5-day period), yielding a test-retest intraclass reliability coefficient of r = .95 for VO2max estimations across days. The reliability of VO2max estimates for women (r = .93) was greater than that for men (r = .74). Cross-validation results were also acceptable using predicted residual sum of squares (PRESS; rPRESS = .87, SEEPRESS = 3.24 ml · kg-1 min-1), which suggests that the new equation should yield acceptable accuracy when it is applied to a similar, but independent sample of adults. In summary, the modified cycle ergometer test developed in this study yields relatively accurate estimates of treadmill VO2max in young adults, requires only a moderate level of exertion, and appears to be a convenient and time-efficient means of estimating cardiorespiratory fitness.

Support vector regression and multilayer feed forward neural networks for non-exercise prediction of VO2max

The purpose of this study is to develop non-exercise (N-Ex) VO2max prediction models by using support vector regression (SVR) and multilayer feed forward neural networks (MFFNN). VO2max values of 100 subjects (50 males and 50 females) are measured using a maximal graded exercise test. The variables; gender, age, body mass index (BMI), perceived functional ability (PFA) to walk, jog or run given distances and current physical activity rating (PA-R) are used to build two N-Ex prediction models. Using 10-fold cross validation on the dataset, standard error of estimates (SEE) and multiple correlation coefficients (R) of both models are calculated. The MFFNN-based model yields lower SEE (3.23mlkg-1min-1) whereas the SVR-based model yields higher R (0.93). Compared with the results of the other N-Ex prediction models in literature that are developed using multiple linear regression analysis, the reported values of SEE and R in this study are considerably more accurate. Therefore, the results suggest that SVR-based and MFFNN-based N-Ex prediction models can be valid predictors of VO2max for heterogeneous samples.