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.