A comprehensive evaluation of commonly used accelerometer energy expenditure and MET prediction equations

Abstract

Numerous accelerometers and prediction methods are used to estimate energy expenditure (EE). Validation studies have been limited to small sample sizes in which participants complete a narrow range of activities and typically validate only one or two prediction models for one particular accelerometer. Purpose To evaluate the validity of nine published and two proprietary EE prediction equations for three different accelerometers. Methods 277 participants completed an average of 6 treadmill (TRD) (1.34, 1.56, 2.23 m·sec−1 each at 0% and 3% grade) and 5 self-paced activities of daily living (ADLs). EE estimates were compared to indirect calorimetry. Accelerometers were worn while EE was measured using a portable metabolic unit. To estimate EE, 4 ActiGraph prediction models were used, 5 Actical models, and 2 RT3 proprietary models. Results Across all activities, each equation underestimated EE (bias −0.1 to −1.4 METs and −0.5 to −1.3 kcals, respectively). For ADLs EE was underestimated by all prediction models (bias −0.2 to −2.0 and −0.2 to −2.8, respectively), while TRD activities were underestimated by seven equations, and overestimated by four equations (bias −0.8 to 0.2 METs and −0.4 to 0.5 kcals, respectively). Misclassification rates ranged from 21.7% (95% CI 20.4%, 24.2%) to 34.3% (95% CI 32.3%, 36.3%), with vigorous intensity activities being most often misclassified. Discussion The prediction equations did not yield accurate point estimates of EE across a broad range of activities, nor were they accurate at classifying activities across a range of intensities (light < 3 METs, moderate 3–5.99 METs, vigorous ≥ 6 METs). Current prediction techniques have many limitations when translating accelerometer counts to EE.

Evaluation of a Questionnaire to Assess Sedentary and Active Behaviors in the Southern Community Cohort Study

“…[19][20][21][22] Participants received the monitor by mail with pictures and detailed instructions how to wear and maintain the accelerometer. They were instructed to wear the RT3 attached to a provided belt on the right hip for 7 consecutive days during waking (not sleeping) hours, except while bathing or during aquatic activities.…”

Validation and reliability of two activity monitors for energy expenditure assessment

“…Validation studies among healthy adults, using published equations, have provided inconsistent results. 6,7 The ACT provided valid resting energy expenditure (REE) estimation compared to indirect calorimetry for normal to overweight adults, 8 but discrepancies were observed for EE during short PA periods. 7,9 In a mechanical set-up, the ACT presented a good intra-instrument reliability (coefficient of variation (CV) = 0.5%).…”

Guide to the Assessment of Physical Activity: Clinical and Research Applications

“…Furthermore, equations derived from selected activities tend to be good at estimating those same activities. A detailed summary and analysis of many reported accelerometer prediction equations was reported by Lyden et al 110 It is paramount to understand that there is substantial variability in the prediction equations that have been developed (for instance, moderate-intensity activity ranges begin at points that range from ≈200 to >2000 counts/min, depending on the reference source). An end user must critically examine how a prediction equation was derived, including the individuals and specific activities involved, and must understand the limitations of its use.…”