Consequences of choosing different settings when processing hip-based accelerometry data from older adults: a practical approach using baseline data from the SITLESS study

Accurately measuring older adults’ physical activity (PA) and sedentary behavior (SB) using accelerometers is essential, as both are important markers of health. This study aimed to highlight how steps taken during data processing may affect key hip-based accelerometry outcomes in older adults, using a selection of baseline accelerometry data (n = 658) from the SITLESS study. Different analytical parameters tested included wear-time algorithms, use of low-frequency extension (LFE) filter, epoch length, and minimum and maximum daily wear-time thresholds. These were compared against vertical axis counts per minute (CPM), vector magnitude (VM) CPM, SB, light PA, moderate-to-vigorous PA, step counts, and wear-time percentage. Differences in settings across the analytical parameters were assessed using paired sample t-tests and repeated measures ANOVAs using Bonferroni correction. Using the “Choi” versus “Troiano” wear-time algorithm resulted in a higher percentage wear-time. Most SB and PA outcomes were significantly different across wear-time algorithms (p < .001). This was similar when using the LFE filter versus normal filter (p < .001). Using 10-second epoch length increased daily SB time (between +75.7 and +79.2 minutes) compared to 60-second. Most SB and PA outcomes significantly changed comparing minimum-wear-time thresholds of 360, 480, 600, and 720 minutes per day (p < .001). Applying a log-diary with a ≥1140-minute threshold had a significant impact on vertical axis CPM, VM CPM, SB, and light PA outcomes (p < .001). This study demonstrates the potential variability in the number of participants being included in studies and reported SB and PA levels when processing older adults’ accelerometry data dependent on the analytical procedures utilized