Author and graduation date: Tabitha Antoinette WASHINGTON, March, 1998

Committee members: Michael J. Buono (Chair), Patricia Patterson, Melbourne F. Hovell

Thesis title: Validation of the Ebbeling Submaximal Equation in Sedentary Latino Women 18-50 Years : Development of a Submaximal Treadmill Walking Test

The rising population of Latino women in the United States is at high risk for CVD, in part due to a sedentary life style, obesity, and a high fat diet. Few studies, to date, have focused on the derivation of submaximal prediction equations for minorities. The purpose of this study was to cross validate the generalized treadmill equation developed by Ebbeling and colleagues for estimation of maximal oxygen uptake in Latino women ages 18-50 ( many of whom are sedentary, overweight, and pre-diabetic) and to develop a prediction equation for this population if the Ebbeling equation proved invalid. A graded exercise treadmill test to measure maximal oxygen uptake was administered to healthy, sedentary (mean VO2max = 27.95 + 4.32) Latino women at risk for CVD participating in a community intervention (N = 88). This test included an initial submaximallevel within the parameters of the prediction equation (0% grade at a constant speed of 3 mph). A metabolic cart measured heart rate (bpm), respiratory exchange ratio, and VO2max values (ml/kg/min). Results indicated a validity coefficient of .22 (p <.05). Predicted values were determined from treadmill speed (mph), heart rate (bpm), age (years), and gender. To test for significant differences, measured and predicted VO2 maximal scores were compared via a dependent t-test (t1,85 = 14.69, p <.05) and found different. Results suggest that the Ebbeling et al. submaximal prediction equation overpredicted maximal oxygen consumption for these Latino women (predicted VO2max = 34.55 + 1.92, measured VO2max = 27.95 + 4.32).

A multiple regression analysis to determine a submaximal VO2 prediction equation specifically tailored for this population resulted in two equations. The independent variables were age (years), height (cm), weight (kg), heart rate at 5 and 7 minutes and at maximum (bpm), hip and waist circumference (cm), and body fat (%). Multiple regression analysis to estimate absolute (R2 = .391, R = .625, SEE = + 3.367 ml/kg/min) VO2max from the submaximal data yielded equations which were not highly valid and therefore the accuracy of the prediction will be low. Findings are significant as they lead the way for the emphasis on research which focuses on the development of more accurate prediction methods for VO2max based on submaximal data specifically tailored for this population of minorities. Submaximal prediction equations allow for more cost efficient, feasible, and safer methods to obtain maximal oxygen consumption, especially in community settings.

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