Identification Of Static vs. Active Standing From A Triaxial Accelerometer

Standing has emerged as a possible strategy to interrupt prolonged sedentary behavior including being published in national activity guidelines as a health enhancing tool. However, some self-reported data suggest that only some types of standing are associated with health benefits. To rigorously study associations between standing and health outcomes, it is first necessary to develop objective methods to measure different types of standing, namely static vs. active. PURPOSE: To determine if a thigh-mounted, triaxial accelerometer can distinguish between static standing and more active forms of standing (i.e., frequent weight shifting). METHODS: Participants (n = 10) performed a supervised, 15-minute standing session broken into three segments: 1) 5-minute static standing (STATIC); 2) 5-minute active standing (pre-determined and structured 1-minute weight shifting patterns: slight step side to side, alternating one foot forward and back, heel raises, alternating rocking knee forward and back, and foot crossing in front of the other) (ACTIVE); and 3) 5-minute standing with self-selected weight shifting and static patterns (FREE). Resultant acceleration data from an ActivPAL4 (PAL Technologies Ltd) were high-pass filtered (0.1 Hz cutoff - to remove the effect of gravity) and the means of absolute acceleration values were calculated over 15-second epochs. Means were compared using repeated measures ANOVA and post hoc comparisons when appropriate. RESULTS: The analysis indicated a significant difference in mean acceleration between the standing types (F (2, 19) 116, p < 0.001, ŋ2 = 0.86). Post hoc testing demonstrated a significant difference between each pair of conditions: STATIC vs. ACTIVE (p < 0.001, 95% C.I. = 0.16-0.22, d = 2.2), STATIC vs. FREE (p < 0.001, 95% C.I. = 0.07-0.13, d = 1.1), and FREE vs. ACTIVE (p < 0.001, 95% C.I. = 0.06-0.12, d = 1.1). CONCLUSION: Objective triaxial accelerometers can delineate static vs. active forms of standing, including self-selected and standardized weight shifting. Future research should develop useful algorithms to process all-day objective standing data to study accumulation patterns of active vs. static standing. This will allow researchers to associate types of standing with health outcomes or study effective replacement behaviors to limit sedentary behavior.