Research Study Abstract

Accelerometric estimates of physical activity vary unstably with data handling.

  • Published on Nov 6, 2017

Background: Because of unreliable self-report, accelerometry is increasingly used to objectively monitor physical activity (PA). However, results of accelerometric studies vary depending on the chosen cutpoints between activity intensities. Population-specific activity patterns likely affect the size of these differences. To establish their size and stability we apply three sets of cutpoints, including two calibrated to a single reference, to our accelerometric data and compare PA estimates.

Methods: 1402 German adolescents from the GINIplus and LISAplus cohorts wore triaxial accelerometers (Actigraph GT3x) for one week (mean 6.23 days, 14.7 hours per day) at the hip. After validation of wear, we applied three sets of cutpoints for youth, including the most common standard (Freedson, 2005) and two calibrated to a single reference, (Romanzini uni- and triaxial, from Romanzini, 2014) to these data, estimating daily sedentary, light, moderate, vigorous and moderate-to-vigorous PA (MPA, VPA, MVPA). Stability of differences was assessed by comparing Romanzini’s two sets of cutpoints.

Results: Relative agreement between cutpoints was closer for activity of lower intensities (largest difference for sedentary behavior 9%) but increased for higher intensities (largest difference for light activity 40%, MPA 102%, VPA 88%; all p<0.01). Romanzini’s uniaxial and triaxial cutpoints agreed no more closely with each other than with Freedson’s.

Conclusions: Estimated PA differed significantly between different sets of cutpoints, even when those cutpoints agreed perfectly on another dataset (i.e. Romanzini’s.) This suggests that the detected differences in estimated PA depend on population-specific activity patterns, which cannot be easily corrected for: converting activity estimates from one set of cutpoints to another may require access to raw data. This limits the utility of accelerometry for comparing populations in place and time. We suggest that accelerometric research adopt a standard for data processing, and apply and present the results of this standard in addition to those from any other method.


  • Smith MP 1,2
  • Standl M 1
  • Heinrich J 1,3
  • Schulz H 1,4


  • 1

    Institute of Epidemiology 1, Helmholtz Zentrum M√ľnchen-German Research Center for Environmental Health, Neuherberg, Germany.

  • 2

    Department of Public Health, School of Medicine, St George's University, Grenada, West Indies.

  • 3

    Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Inner City Clinic, University Hospital of Munich (LMU), Munich, Germany.

  • 4

    CPC-Munich, Member of German Center for Lung Research, Munich, Germany.


Plos One


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