Validity of two wearable monitors to estimate breaks from sedentary time

Abstract

Investigations using wearable monitors have begun to examine how sedentary time behaviors influence health.

Purpose: 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.

Methods: 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)).

Results: 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.

Conclusion: 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.

Conflict of interest statement

Kate Lyden: No Conflict of Interest

Sarah Kozey-Keadle: No Conflict of Interest

John Staudenmayer: No Conflict of Interest

Patty Freedson is on the Scientific Advisory Board for ActiGraph, which manufactures one of the monitors used in this study.

Figures

Figure 1

Bias for activPAL and ActiGraph estimates of absolute number of breaks (top panel) and break-rate (bottom panel). Error bars = 95% CI of the bias. * Not significantly different from direct observation. activPAL: n=13, AG-LFE: n=12, AG-Norm: n=11.

Figure 1

Bias for activPAL and ActiGraph estimates of absolute number of breaks (top panel) and break-rate (bottom panel). Error bars = 95% CI of the bias. * Not significantly different from direct observation. activPAL: n=13, AG-LFE: n=12, AG-Norm: n=11.

Figure 2

Mean estimates of break-rate per condition. Error bars = 95% CI and p-value is from the likelihood ratio testing. The lower the p-value, the more sensitive the measurement method was to the intervention. * Measurement method detected the intervention. activPAL: n=11, AG-LFE: n=11, AG-Norm: n=11.