Low Frequency Extension Filter Research Articles

Effects of Filter Choice in GT3X Accelerometer Assessments of Free-Living Activity

ActiGraph accelerometers are widely used devices to objectively assess physical activity. The GT3X version has two filter options to be selected before data assessment (normal and low-frequency extension filter option). It is not clear whether the resulting physical activity levels differ depending on the choice of the filter. The aims were to compare GT3X data collected using the different filter options during free-living activities and to establish correction factors if the results were not comparable. Sixty-five participants of the population-based SAPALDIA-cohort (50.8% women, age range = 40-80 yr) wore two GT3X accelerometers with different filter selections simultaneously during 8 d. Spearman correlations, Wilcoxon rank sum tests, McNemar tests, scatter plots, and Bland-Altman plots were used to compare the data. Correction factors were established using linear regression models. Although Spearman correlations were high (r ≥ 0.93), there were significant differences in minutes per day between filter options for nonwearing time and time spent in sedentary, light, and moderate-to-vigorous physical activity (all P < 0.001), with more remarkable differences in the lower range of activity (sedentary and light activities). Mean counts per minute and steps per day were significantly higher using the low-frequency extension filter (P < 0.001). Most differences could be resolved using the correction factors. The observed differences are especially important when research is focusing on sedentary and light activities. In future studies, it is important to carefully evaluate the suitable filter option and to specify the filter choice in publications. The correction factors can be used to make data assessed using the low-frequency extension filter comparable to data assessed using the normal filter option.

Validity of Two Wearable Monitors to Estimate Breaks from Sedentary Time

Investigations using wearable monitors have begun to examine how sedentary time behaviors influence health. The objective of this study is to demonstrate the use of a measure of sedentary behavior and to validate the activPAL (PAL Technologies Ltd., Glasgow, Scotland) and ActiGraph GT3X (Actigraph, Pensacola, FL) for estimating measures of sedentary behavior: absolute number of breaks and break rate. Thirteen participants completed two 10-h conditions. During the baseline condition, participants performed normal daily activity, and during the treatment condition, participants were asked to reduce and break up their sedentary time. In each condition, participants wore two ActiGraph GT3X monitors and one activPAL. The ActiGraph was tested using the low-frequency extension filter (AG-LFE) and the normal filter (AG-Norm). For both ActiGraph monitors, two count cut points to estimate sedentary time were examined: 100 and 150 counts per minute. Direct observation served as the criterion measure of total sedentary time, absolute number of breaks from sedentary time, and break rate (number of breaks per sedentary hour (brk·sed-h)). Break rate was the only metric sensitive to changes in behavior between baseline (5.1 [3.3-6.8] brk·sed-h) and treatment conditions (7.3 [4.7-9.8] brk·sed-h) (mean (95% confidence interval)). The activPAL produced valid estimates of all sedentary behavior measures and was sensitive to changes in break rate between conditions (baseline, 5.1 [2.8-7.1] brk·sed-h; treatment, 8.0 [5.8-10.2] brk·sed-h). In general, the AG-LFE and AG-Norm were not accurate in estimating break rate or the absolute number of breaks and were not sensitive to changes between conditions. This study demonstrates the use of expressing breaks from sedentary time as a rate per sedentary hour, a metric specifically relevant to free-living behavior, and provides further evidence that the activPAL is a valid tool to measure components of sedentary behavior in free-living environments.