Abstract
Large epidemiological studies that use accelerometers for physical behavior and sleep assessment differ in the location of the accelerometer attachment and the signal aggregation metric chosen. This study aimed to assess the comparability of acceleration metrics between commonly-used body-attachment locations for 24 hours, waking and sleeping hours, and to test comparability of PA cut points between dominant and non-dominant wrist. Forty-five young adults (23 women, 18–41 years) were included and GT3X + accelerometers (ActiGraph, Pensacola, FL, USA) were placed on their right hip, dominant, and non-dominant wrist for 7 days. We derived Euclidean Norm Minus One g (ENMO), Low-pass filtered ENMO (LFENMO), Mean Amplitude Deviation (MAD) and ActiGraph activity counts over 5-second epochs from the raw accelerations. Metric values were compared using a correlation analysis, and by plotting the differences by time of the day. Cut points for the dominant wrist were derived using Lin’s concordance correlation coefficient optimization in a grid of possible thresholds, using the non-dominant wrist estimates as reference. They were cross-validated in a separate sample (N = 36, 10 women, 22–30 years). Shared variances between pairs of acceleration metrics varied across sites and metric pairs (range in r2: 0.19–0.97, all p < 0.01), suggesting that some sites and metrics are associated, and others are not. We observed higher metric values in dominant vs. non-dominant wrist, thus, we developed cut points for dominant wrist based on ENMO to classify sedentary time (<50 mg), light PA (50–110 mg), moderate PA (110–440 mg) and vigorous PA (≥440 mg). Our findings suggest differences between dominant and non-dominant wrist, and we proposed new cut points to attenuate these differences. ENMO and LFENMO were the most similar metrics, and they showed good comparability with MAD. However, counts were not comparable with ENMO, LFENMO and MAD.
Highlights
Large epidemiological studies that use accelerometers for physical behavior and sleep assessment differ in the location of the accelerometer attachment and the signal aggregation metric chosen
In concordance with van Hees et al.’s study[24] in adults, our findings show stronger associations between pairs of metrics with none or minimal filtering (ENMO, Low-pass filtered ENMO (LFENMO) and Mean Amplitude Deviation (MAD)) than the comparisons of any of these metrics with counts, which may be explained by the application of a frequency filter to the raw signal
We found that the movement pattern identified throughout the day was visually similar for Euclidean Norm Minus One g (ENMO), LFENMO and MAD, while counts did not identify some peaks of movement detected by the rest of the metrics
Summary
Large epidemiological studies that use accelerometers for physical behavior and sleep assessment differ in the location of the accelerometer attachment and the signal aggregation metric chosen. Hip and wrist are the most frequently selected locations[17], and both have been demonstrated to be valid locations for classifying PA intensities and sedentary time[8,9,10,17], as well as to assess sleep[14,15,16] It is unclear how much the accelerometer outcome measures vary between body sites. Moderate-to-high correlations between acceleration values from either wrist and the hip have been reported (i.e., r coefficients between 0.7 and 0.9)[20,21] These studies had a focus on PA and sedentary time (i.e., waking hours) and did not report associations during sleeping hours. Studies where accelerometers were placed on the dominant wrist do not have specific cut points proposed for their data, for instance the UK Biobank trial[23]
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