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Individual calibration of accelerometers in children and their health-related implications

  • Lynne M Boddy
  • , Conor Cunningham
  • , Stuart J Fairclough
  • , Marie H Murphy
  • , Gavin Breslin
  • , Lawrence Foweather
  • , Rebecca M Dagger
  • , Lee E F Graves
  • , Nicola D Hopkins
  • , Gareth Stratton

Research output: Contribution to journalArticlepeer-review

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Abstract

This study compared children's physical activity (PA) levels, the prevalence of children meeting current guidelines of ≥60 minutes of daily moderate to vigorous PA (MVPA), and PA-health associations using individually calibrated (IC) and empirical accelerometer cutpoints. Data from 75 (n = 32 boys) 10-12 year old children were included in this study. Clustered cardiometabolic (CM) risk, directly measured cardiorespiratory fitness (CRF), anthropometric and 7 day accelerometer data were included within analysis. PA data were classified using Froude anchored IC, Evenson et al. (Evenson, K. R., Catellier, D. J., Gill, K., Ondrak, K. S., & McMurray, R. G. (2008). Calibration of two objective measures of physical activity for children. Journal of Sports Sciences, 26(14), 1557-1565. doi:10.1080/02640410802334196) (Ev) and Mackintosh et al. (Mackintosh, K. A., Fairclough, S. J., Stratton, G., & Ridgers, N. D. (2012). A calibration protocol for population-specific accelerometer cutpoints in children. PLoS One, 7(5), e36919. doi:10.1371/journal.pone.0036919) (Mack) cutpoints. The proportion of the cohort meeting ≥60mins MVPA/day ranged from 37%-56% depending on the cutpoints used. Reported PA differed significantly across the cutpoint sets. IC LPA and MPA were predictors of CRF (LPA: standardised β = 0.32, p = 0.002, MPA: standardised β = 0.27 p = 0.013). IC MPA also predicted BMI Z-score (standardised β = -0.35, p = 0.004). Ev VPA was a predictor of BMI Z-score (standardised β = -0.33, p = 0.012). Cutpoint choice has a substantial impact on reported PA levels though no significant associations with CM risk were observed. Froude IC cutpoints represent a promising approach towards classifying children's PA data.

Original languageEnglish
Pages (from-to)1340-1345
Number of pages6
JournalJournal of Sports Sciences
Volume36
Issue number12
Early online date18 Sept 2017
DOIs
Publication statusPublished (in print/issue) - 30 Jun 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Accelerometry/instrumentation
  • Anthropometry
  • Calibration
  • Cardiorespiratory Fitness
  • Child
  • Exercise
  • Female
  • Humans
  • Male
  • Reference Values

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