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

Citation
Sj. Strath et al., Evaluation of heart rate as a method for assessing moderate intensity physical activity, MED SCI SPT, 32(9), 2000, pp. S465-S470
Citations number
27
Categorie Soggetti
Medical Research General Topics
Journal title
MEDICINE AND SCIENCE IN SPORTS AND EXERCISE
ISSN journal
01959131 → ACNP
Volume
32
Issue
9
Year of publication
2000
Supplement
S
Pages
S465 - S470
Database
ISI
SICI code
0195-9131(200009)32:9<S465:EOHRAA>2.0.ZU;2-X
Abstract
To further develop our understanding of the relationship between habitual p hysical activity and health, research studies require a method of assessmen t that is objective, accurate, and noninvasive. Heart rate (HR) monitoring represents a promising tool for measurement because it is a physiological p arameter 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-(V)over dotO(2) relationship. Purpose: Th e primary purpose of this study was to examine the relationship between HR (beats.min(-1)) and (V)over dotO(2) (mL.kg(-1.-1)min(-1)) during field- and laboratory-based moderate-intensity activities. In addition, we examined t he validity of estimating EE from HR after adjusting for age and fitness. T his was done by expressing the data as a percent of heart rate reserve (%HR R) and percent of (V)over dotO(2) reserve (%(V)over dotO(2R)). Methods: Six ty-one adults (18-74 yr) performed physical tasks in both a laboratory and field setting. HR and (V)over dotO(2) were measured continuously during the 15-min tasks. Mean values over min 5-15 were used to perform linear regres sion analysis on HR versus (V)over dotO(2). HR data were then used to predi ct EE (METs), using age-predicted HRmax and estimated (V)overdotO(2max). Re sults: The correlation between HR and (V)over dotO(2) was r = 0.68, with HR accounting for 47% of the variability in(V)over dotO(2). After adjusting f or 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 res earchers to more accurately quantify physical activity in free-living indiv iduals.