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Cross-validation of cut-points in preschool children using different accelerometer placements and data axes.

Teatske M AltenburgLotte de VriesRianne Op den BuijschEmma L J EyreAlexandra DobellMichael Joseph DuncanMai J M Chinapaw
Published in: Journal of sports sciences (2022)
The present study cross-validated various cut-points to assess physical activity and sedentary behaviour in preschoolers, using hip- and wrist-worn accelerometers and both vertical axis and vector magnitude data. Secondly, we examined the influence of epoch length on time estimates of physical activity and sedentary behaviour. Sixty-four preschoolers (34 girls) wore two accelerometers, on their right hip and dominant wrist, during 1 hour of free play. Preschoolers' activities were observed by two trained researchers. Area under the curve (AUC) was calculated for the receiving operating characteristic (ROC) curves as a measure of precision. AUC ranges were 0.603-0.723 for sedentary behaviour, 0.472-0.545 for light physical activity and 0.503-0.661 for moderate-to-vigorous physical activity (MVPA), indicating poor to fair precision. Percentage of time classified as sedentary behaviour, light or MVPA according to observation and accelerometer data varied largely between cut-points, accelerometer placements and axes. The influence of epoch length on time estimates was minimal across cut-points, except for one hip-based vector magnitude cut-point. Across all accelerometer placements and data axes, no set of cut-points demonstrated adequate precision for sedentary behaviour, light physical activity and MVPA. The highly variable and omnidirectional activity pattern of preschoolers may explain the lack of adequate cut-points.
Keyphrases
  • physical activity
  • electronic health record
  • body mass index
  • big data
  • sleep quality
  • blood pressure
  • total hip arthroplasty
  • machine learning
  • body composition
  • resistance training