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Evaluation of heart rate as a method for assessing moderate intensity physical activity

STRATH, SCOTT J.; SWARTZ, ANN M.; BASSETT, DAVID R. JR.; O’BRIEN, WILLIAM L.; KING, GEORGE A.; AINSWORTH, BARBARA E.

Medicine & Science in Sports & Exercise: September 2000 - Volume 32 - Issue 9 - pp S465-S470
Measurement of Moderate Physical Activity: Advances in Assessment Techniques

STRATH, S. J, A. M. SWARTZ, D. R. BASSETT, JR., W. L. O’BRIEN, G. A. KING, and B. E. AINSWORTH. Evaluation of heart rate as a method for assessing moderate intensity physical activity. Med. Sci. Sports Exerc., Vol. 32, No. 9, Suppl., pp. S465–S470, 2000. To further develop our understanding of the relationship between habitual physical activity and health, research studies require a method of assessment that is objective, accurate, and noninvasive. Heart rate (HR) monitoring represents a promising tool for measurement because it is a physiological parameter that correlates well with energy expenditure (EE). However, one of the limitations of HR monitoring is that training state and individual HR characteristics can affect the HR–V̇O2 relationship.

Purpose: The primary purpose of this study was to examine the relationship between HR (beats·min1) and V̇O2 (mL·kg1min1) during field- and laboratory-based moderate-intensity activities. In addition, we examined the validity of estimating EE from HR after adjusting for age and fitness. This was done by expressing the data as a percent of heart rate reserve (%HRR) and percent of V̇O2 reserve (%V̇O2R).

Methods: Sixty-one adults (18–74 yr) performed physical tasks in both a laboratory and field setting. HR and V̇O2 were measured continuously during the 15-min tasks. Mean values over min 5–15 were used to perform linear regression analysis on HR versus V̇O2. HR data were then used to predict EE (METs), using age-predicted HRmax and estimated V̇O2max.

Results: The correlation between HR and V̇O2 was r = 0.68, with HR accounting for 47% of the variability inV̇O2. After adjusting for age and fitness level, HR was an accurate predictor of EE (r = 0.87, SEE = 0.76 METs).

Conclusion: This method of analyzing HR data could allow researchers to more accurately quantify physical activity in free-living individuals.

Department of Exercise Science and Sport Management, University of Tennessee, Knoxville TN 37996, and Department of Epidemiology and Biostatistics and Department of Exercise Science, School of Public Health, University of South Carolina, Columbia SC 29208

Address for correspondence: Scott J. Strath, Department of Exercise Science and Sport Management, The University of Tennessee, Knoxville, 1914 Andy Holt Avenue, Knoxville, TN 37996-2700; E-mail: sstrath@utk.edu.

© 2000 Lippincott Williams & Wilkins, Inc.