Accelerometry analysis options produce large differences in lifestyle physical activity measurement.

Objective measurement of physical activity (PA) using accelerometers has become increasingly popular across recreational and clinical applications. However, the effects of multiple processing algorithms, filters, and corrections on PA measurement variability may be underappreciated.
Objective: To examine how lifestyle PA estimates are impacted by multiple available scoring methods.
Approach: Wrist-worn accelerometers (ActiGraph GT3X+) were worn by 132 adults (87 F) having various activity levels for one week. Lifestyle PA was assessed across four PA domains: daily energy expenditure (EE); active EE; moderate-to-vigorous PA (MVPA); and steps using 1-5 algorithms per domain, with/without wrist correction and low-frequency-extension (LFE). Estimates were compared to self-report (International Physical Activity Questionnaire).
Main Results: PA estimates differed between algorithms with variable but frequently large effect sizes (d = 0.08-1.88). The wrist correction reduced PA estimates across all domains (p < 0.05, d = 0.26-3.04) except step counts and one daily EE algorithm (d = 0.0). Conversely, the LFE increased step counts (d = 1.44, p < 0.05) but minimally affected all other outcomes (d = 0.08-0.20, p < 0.05). Correlations between objective and self-reported PA were small to moderate (ρ = 0.22-0.45) and decreased with the wrist correction.
Significance: Measurement of PA using accelerometry is highly dependent on algorithm and filter selection; previously validated methods are therefore not interchangeable. Users should take caution when interpreting absolute PA estimates, and reporting standards should require detailed methodology disclosure to optimize comparisons across studies.