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Calibration and Validation of Accelerometry using cut-points to Assess Physical Activity in Paediatric Clinical Groups: A Systematic Review

Mayara S Bianchim, Melitta McNarry Orcid Logo, Lillebeth Larun, Alan R Barker, Craig A Williams, Kelly Mackintosh Orcid Logo

Preventive Medicine Reports, Volume: 19

Swansea University Authors: Melitta McNarry Orcid Logo, Kelly Mackintosh Orcid Logo

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Abstract

Regular physical activity is associated with physiological and psychosocial benefits in both healthy and clinical populations. However, little is known about tailoring the analysis of physical activity using accelerometers to the specific characteristics of chronic conditions. Whilst accelerometry i...

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Published in: Preventive Medicine Reports
ISSN: 2211-3355
Published: Elsevier BV 2020
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa54402
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Abstract: Regular physical activity is associated with physiological and psychosocial benefits in both healthy and clinical populations. However, little is known about tailoring the analysis of physical activity using accelerometers to the specific characteristics of chronic conditions. Whilst accelerometry is broadly used to assess physical activity, recommendations on calibration in paediatric clinical groups are warranted. The aim of this systematic review was to provide a critical overview of protocols used to calibrate accelerometry in children and adolescents with clinical conditions, as well as to develop recommendations for calibration and validation of accelerometry in such populations. The search was performed between March to July 2017 using text words and subject headings in six databases. Studies had to develop moderate-to-vigorous intensity physical activity (MVPA) cut-points for paediatric clinical populations to be included. Risk of bias was assessed using a specific checklist. A total of 540,630 titles were identified, with 323 full-text articles assessed. Five studies involving 347 participants aged 9 to 15 years were included. Twenty-four MVPA cut-points were reported across seven clinical conditions, 16 of which were developed for different models of ActiGraph, seven for Actical and one for Tritrac-R3D. Statistical approaches included mixed regression, machine learning and receiver operating characteristic analyses. Disease-specific MVPA cut-points ranged from 152 to 735 counts·15 s−1, with lower cut-points found for inherited muscle disease and higher cut-points associated with intellectual disabilities. The lower MVPA cut-points for diseases characterised by both ambulatory and metabolic impairments likely reflect the higher energetic demands associated with those conditions.