Estimating resting energy expenditure with a portable armband device in an ambulatory setting

The measurement of resting energy expenditure (REE) in an ambulatory setting raises methodological problems. Therefore, the use of predictive equations for the estimation of REE is common. Alternatively, the measurement of sleeping energy expenditure (SEE) has been proposed. The authors retrospectively analyzed data on SEE assessed with a portable armband (PA) device in an ambulatory setting and evaluated this approach against predictive equations and REE measured by indirect calorimetry (IC).

REE was measured with IC, and SEE was assessed with the PA using standardized conditions in 81 participants (aged 46 ± 13 years) over a wide range of body weight (mean body mass index [BMI] 36.4 ± 9.3 kg/m(2); range, 21.6-55.7).

SEE (1756 ± 393 kcal/d) was 7.6% higher than REE (1632 ± 346 kcal/d) (P < .001). This difference (123 ± 214 kcal/d) was smaller than that using the predictive equation for REE by Harris and Benedict (207 ± 217 kcal/d) and the BMI group-specific equations according to Müller et al (209 ± 190 kcal/d). Linear regression analysis was significant (r (2) = 0.705; P < .001). SEE showed similar 95% confidence intervals compared with both of the predictive equations.

The described standardized assessment of SEE by a PA device appears to be a promising approach to estimate REE in an ambulatory setting. SEE reflects REE at least as precisely as the predictive equations.