Abstract

BackgroundPublic health research on sedentary behavior (SB) in youth has heavily relied on accelerometers. However, it has been limited by the lack of consensus on the most accurate accelerometer cut-points as well as by unknown effects caused by accelerometer position (wrist vs. hip) and output (single axis vs. multiple axes). The present study systematically evaluates classification accuracy of different Actigraph cut-points for classifying SB using hip and wrist-worn monitors and establishes new cut-points to enable use of the 3-dimensional vector magnitude data (for both hip and wrist placement).MethodsA total of 125 children ages 7–13 yrs performed 12 randomly selected activities (from a set of 24 different activities) for 5 min each while wearing tri-axial Actigraph accelerometers on both the hip and wrist. The accelerometer data were categorized as either sedentary or non-sedentary minutes using six previously studied cut-points: 100counts-per-minute (CPM), 200CPM, 300CPM, 500CPM, 800CPM and 1100CPM. Classification accuracy was evaluated with Cohen's Kappa (κ) and new cut-points were identified from Receiver Operating Characteristic (ROC).ResultsOf the six cut-points, the 100CPM value yielded the highest classification accuracy (κ = 0.81) for hip placement. For wrist placement, all of the cut-points produced low classification accuracy (ranges of κ from 0.44 to 0.67). Optimal sedentary cut-points derived from ROC were 554.3CPM (ROC-AUC of 0.99) for vector magnitude for hip, 1756CPM (ROC-AUC of 0.94) for vertical axis for wrist, and 3958.3CPM (ROC-AUC of 0.93) for vector magnitude for wrist placement.ConclusionsThe 100CPM was supported for use with vertical axis for hip placement, but not for wrist placement. The ROC-derived cut-points can be used to classify youth SB with the wrist and with vector magnitude data.

Highlights

  • Excessive time spent on sedentary behavior (SB) in youth is associated with metabolic riskfactors [1], cardiorespiratory fitness [2], childhood obesity [3], and mental health [4].This is a significant public health concern considering that time spent in SB has been shown to be increasingin all age [5] and ethnicity/ socioeconomic groups [6]

  • Accelerometry-based activity monitors such as the Actigraph (Actigraph LLC, Pensacola, FL, USA) have been widely used to assess time spent in physical activity, but there is no consensus on the most accurate ‘‘cut-point’’ to classify time spent in SB

  • For both the hip and wrist, the means and standard deviations of vertical axis counts and vector magnitudes were larger with higher intensities of physical activity

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Summary

Introduction

Excessive time spent on sedentary behavior (SB) in youth is associated with metabolic riskfactors [1], cardiorespiratory fitness [2], childhood obesity [3], and mental health [4].This is a significant public health concern considering that time spent in SB has been shown to be increasingin all age [5] and ethnicity/ socioeconomic groups [6]. Accelerometry-based activity monitors such as the Actigraph (Actigraph LLC, Pensacola, FL, USA) have been widely used to assess time spent in physical activity, but there is no consensus on the most accurate ‘‘cut-point’’ to classify time spent in SB. The ideal cut-point for SB would accurately distinguish sedentary activities from physical activities but many different values have been proposed and/or derived from previous studies. Public health research on sedentary behavior (SB) in youth has heavily relied on accelerometers. It has been limited by the lack of consensus on the most accurate accelerometer cut-points as well as by unknown effects caused by accelerometer position (wrist vs hip) and output (single axis vs multiple axes). The present study systematically evaluates classification accuracy of different Actigraph cut-points for classifying SB using hip and wrist-worn monitors and establishes new cut-points to enable use of the 3-dimensional vector magnitude data (for both hip and wrist placement)

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Results
Conclusion
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