Abstract

ObjectiveTo examine the effects of accelerometer epoch lengths, wear time (WT) algorithms, and activity cut-points on estimates of WT, sedentary behavior (SB), and physical activity (PA).Methods268 7–11 year-olds with BMI ≥ 85th percentile for age and sex wore accelerometers on their right hips for 4–7 days. Data were processed and analyzed at epoch lengths of 1-, 5-, 10-, 15-, 30-, and 60-seconds. For each epoch length, WT minutes/day was determined using three common WT algorithms, and minutes/day and percent time spent in SB, light (LPA), moderate (MPA), and vigorous (VPA) PA were determined using five common activity cut-points. ANOVA tested differences in WT, SB, LPA, MPA, VPA, and MVPA when using the different epoch lengths, WT algorithms, and activity cut-points.ResultsWT minutes/day varied significantly by epoch length when using the NHANES WT algorithm (p < .0001), but did not vary significantly by epoch length when using the ≥ 20 minute consecutive zero or Choi WT algorithms. Minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA varied significantly by epoch length for all sets of activity cut-points tested with all three WT algorithms (all p < .0001). Across all epoch lengths, minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA also varied significantly across all sets of activity cut-points with all three WT algorithms (all p < .0001).ConclusionsThe common practice of converting WT algorithms and activity cut-point definitions to match different epoch lengths may introduce significant errors. Estimates of SB and PA from studies that process and analyze data using different epoch lengths, WT algorithms, and/or activity cut-points are not comparable, potentially leading to very different results, interpretations, and conclusions, misleading research and public policy.

Highlights

  • Accelerometers are commonly used to objectively measure sedentary behavior (SB) and physical activity (PA), including assessing activity levels for population level surveillance, examining associations between activity levels and measures of health and disease, and examining the efficacy of PA promotion and obesity prevention and treatment efforts

  • Minutes/day and percent time spent in SB, light PA (LPA), moderate PA (MPA), vigorous PA (VPA), and moderate and vigorous PA (MVPA) varied significantly by epoch length for all sets of activity cut-points tested with all three wear time (WT) algorithms

  • Minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA varied significantly across all sets of activity cut-points with all three WT algorithms

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Summary

Introduction

Accelerometers are commonly used to objectively measure sedentary behavior (SB) and physical activity (PA), including assessing activity levels for population level surveillance, examining associations between activity levels and measures of health and disease, and examining the efficacy of PA promotion and obesity prevention and treatment efforts. One key decision is the choice of epoch length, which refers to the interval of time over which the units of accelerometer measures ( known as “counts”) are summed. Another important decision is the selection of an algorithm to differentiate accelerometer wear time (WT) from non-wear time. Of particular interest is whether it is acceptable to use an epoch length for data analysis that differs from the epoch length originally used to validate algorithms and activity cut-point definitions for WT, SB, and PA intensity levels, and whether results vary when using different validated WT algorithms and activity cut-points

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