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Lookup NU author(s): Professor Niina KolehmainenORCiD, Dr Christopher ThorntonORCiD, Dr Olivia Craw, Professor Mark PearceORCiD, Laura Kudlek, Professor Kianoush Nazarpour, Dr Laura Cutler, Professor Tim Rapley
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023 The Authors. Background: Evidence about physical activity of young children across developmental and health states is very limited. Using data from an inclusive UK cohort, ActiveCHILD, we investigated relationships between objectively measured physical activity, child development, social context, and health-related quality of life (HRQoL). Methods: Children (12–36 months), purposively sampled across health pathways, developmental abilities, and sociodemographic factors, were recruited through thirteen National Health Service organisations in England. Data were collected from 07/2017 to 08/2019 on: weekly physical activity (3–7 days) using waist-worn accelerometer (ActiGraph 3GTX); sociodemographics, parent actions, child HRQoL, and child development using questionnaires; and child health conditions using clinical records. A data-driven, unsupervised method, called hidden semi-Markov model (HSMM) segmented the accelerometery data and provided estimates of the total time spent active (any intensity) and very active (greater intensity) for each child. Relationships with the explanatory factors were investigated using multiple linear regression. Findings: Physical activity data were obtained for 282 children (56% females, mean age 21 months, 37.5% with a health condition) covering all index of multiple deprivation deciles. The patterns of physical activity consisted of two daily peaks, children spending 6.44 (SD = 1.39) hours active (any intensity), of which 2.78 (SD = 1.38) hours very active, 91% meeting WHO guidelines. The model for total time active (any intensity) explained 24% of variance, with mobility capacity the strongest predictor (β = 0.41). The model for time spent very active explained 59% of variance, with mobility capacity again the strongest predictor (β = 0.76). There was no evidence of physical activity explaining HRQoL. Interpretation: The findings provide new evidence that young children across developmental states regularly achieve mainstream recommended physical activity levels and challenges the belief that children with development problems need lower expectations for daily physical activity compared to peers. Advancing the rights of all children to participate in physical activity requires inclusive, equally ambitious, expectations for all. Funding: Niina Kolehmainen, HEE/NIHR Integrated Clinical Academic Senior Clinical Lecturer, NIHR ICA-SCL-2015-01-00, was funded by the NIHR for this research project. Christopher Thornton, Olivia Craw, Laura Kudlek, and Laura Cutler were also funded from this award. Tim Rapley is a member of the NIHR Applied Research Collaboration North East and North Cumbria, with part of his time funded through the related award ( NIHR200173). The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR, NHS, or the UK Department of Health and Social Care. The work of Kianoush Nazarpour is supported by Engineering and Physical Sciences Research Council (EPSRC), under grant number EP/R004242/2.
Author(s): Kolehmainen N, Thornton C, Craw O, Pearce MS, Kudlek L, Nazarpour K, Cutler L, Van Sluijs E, Rapley T
Publication type: Article
Publication status: Published
Journal: eClinicalMedicine
Year: 2023
Volume: 60
Print publication date: 01/06/2023
Online publication date: 25/05/2023
Acceptance date: 27/04/2023
Date deposited: 07/06/2023
ISSN (electronic): 2589-5370
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.eclinm.2023.102008
DOI: 10.1016/j.eclinm.2023.102008
Data Access Statement: The datasets used during the current study are available from the corresponding author on reasonable request. Anonymised data, a data dictionary, study protocol, and recruitment packs are also accessible for reviewing and research use at the Newcastle University data repository data.ncl and can be located using the following link: https://doi.org/10.25405/data.ncl.21120457
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