Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study.
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5678875?pdf=render |
| _version_ | 1818188310301900800 |
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| author | Francesco Sera Lucy J Griffiths Carol Dezateux Marco Geraci Mario Cortina-Borja |
| author_facet | Francesco Sera Lucy J Griffiths Carol Dezateux Marco Geraci Mario Cortina-Borja |
| author_sort | Francesco Sera |
| collection | DOAJ |
| description | 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.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.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.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. |
| first_indexed | 2024-12-11T23:24:53Z |
| format | Article |
| id | doaj.art-9efb3c1eec1e4645b5ea165838273f41 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-11T23:24:53Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-9efb3c1eec1e4645b5ea165838273f412022-12-22T00:46:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-011211e018767710.1371/journal.pone.0187677Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study.Francesco SeraLucy J GriffithsCarol DezateuxMarco GeraciMario Cortina-BorjaTemporal 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.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.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.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.http://europepmc.org/articles/PMC5678875?pdf=render |
| spellingShingle | Francesco Sera Lucy J Griffiths Carol Dezateux Marco Geraci Mario Cortina-Borja Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study. PLoS ONE |
| 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 |
| url | http://europepmc.org/articles/PMC5678875?pdf=render |
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