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Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study

BACKGROUND: Temporal characterisation of physical activity in children is required for effective strategies to increase physical activity (PA). Evidence regarding determinants of physical activity in childhood and their time-dependent patterns remain inconclusive. We used functional data analysis (F...

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Autores principales: Sera, Francesco, Griffiths, Lucy J., Dezateux, Carol, Geraci, Marco, Cortina-Borja, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678875/
https://www.ncbi.nlm.nih.gov/pubmed/29117203
http://dx.doi.org/10.1371/journal.pone.0187677
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author Sera, Francesco
Griffiths, Lucy J.
Dezateux, Carol
Geraci, Marco
Cortina-Borja, Mario
author_facet Sera, Francesco
Griffiths, Lucy J.
Dezateux, Carol
Geraci, Marco
Cortina-Borja, Mario
author_sort Sera, Francesco
collection PubMed
description BACKGROUND: Temporal characterisation of physical activity in children is required for effective strategies to increase physical activity (PA). Evidence regarding determinants of physical activity in childhood and their time-dependent patterns remain inconclusive. We used functional data analysis (FDA) to model temporal profiles of daily activity, measured objectively using accelerometers, to identify diurnal and seasonal PA patterns in a nationally representative sample of primary school-aged UK children. We hypothesised that PA levels would be lower in girls than boys at play times and after school, higher in children participating in social forms of exercise (such as sport or play), and lower among those not walking to school. METHODS: Children participating in the UK-wide Millennium Cohort Study wore an Actigraph GT1M accelerometer for seven consecutive days during waking hours. We modelled 6,497 daily PA profiles from singleton children (3,176 boys; mean age: 7.5 years) by means of splines, and used functional analysis of variance to examine the cross-sectional relation of time and place of measurement, demographic and behavioural characteristics to smoothed PA profiles. RESULTS: Diurnal and time-specific patterns of activity showed significant variation by sex, ethnicity, UK country and season of measurement; girls were markedly less active than boys during school break times than boys, and children of Indian ethnicity were significantly less active during school hours (9:30–12:00). Social activities such as sport clubs, playing with friends were associated with higher level of PA in afternoon (15:00–17:30) and early evenings (17:30–19:30). Lower PA levels between 8:30–9:30 and 17:30–19:30 were associated with mode of travel to and from school, and number of cars in regular use in the household. CONCLUSION: Diminished PA in primary school aged children is temporally patterned and related to modifiable behavioural factors. FDA can be used to inform and evaluate public health policies to promote childhood PA.
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spelling pubmed-56788752017-11-18 Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study Sera, Francesco Griffiths, Lucy J. Dezateux, Carol Geraci, Marco Cortina-Borja, Mario PLoS One Research Article BACKGROUND: Temporal characterisation of physical activity in children is required for effective strategies to increase physical activity (PA). Evidence regarding determinants of physical activity in childhood and their time-dependent patterns remain inconclusive. We used functional data analysis (FDA) to model temporal profiles of daily activity, measured objectively using accelerometers, to identify diurnal and seasonal PA patterns in a nationally representative sample of primary school-aged UK children. We hypothesised that PA levels would be lower in girls than boys at play times and after school, higher in children participating in social forms of exercise (such as sport or play), and lower among those not walking to school. METHODS: Children participating in the UK-wide Millennium Cohort Study wore an Actigraph GT1M accelerometer for seven consecutive days during waking hours. We modelled 6,497 daily PA profiles from singleton children (3,176 boys; mean age: 7.5 years) by means of splines, and used functional analysis of variance to examine the cross-sectional relation of time and place of measurement, demographic and behavioural characteristics to smoothed PA profiles. RESULTS: Diurnal and time-specific patterns of activity showed significant variation by sex, ethnicity, UK country and season of measurement; girls were markedly less active than boys during school break times than boys, and children of Indian ethnicity were significantly less active during school hours (9:30–12:00). Social activities such as sport clubs, playing with friends were associated with higher level of PA in afternoon (15:00–17:30) and early evenings (17:30–19:30). Lower PA levels between 8:30–9:30 and 17:30–19:30 were associated with mode of travel to and from school, and number of cars in regular use in the household. CONCLUSION: Diminished PA in primary school aged children is temporally patterned and related to modifiable behavioural factors. FDA can be used to inform and evaluate public health policies to promote childhood PA. Public Library of Science 2017-11-08 /pmc/articles/PMC5678875/ /pubmed/29117203 http://dx.doi.org/10.1371/journal.pone.0187677 Text en © 2017 Sera et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sera, Francesco
Griffiths, Lucy J.
Dezateux, Carol
Geraci, Marco
Cortina-Borja, Mario
Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study
title Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study
title_full Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study
title_fullStr Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study
title_full_unstemmed Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study
title_short Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study
title_sort using functional data analysis to understand daily activity levels and patterns in primary school-aged children: cross-sectional analysis of a uk-wide study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678875/
https://www.ncbi.nlm.nih.gov/pubmed/29117203
http://dx.doi.org/10.1371/journal.pone.0187677
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