ArticlePloS one2017
Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 21 citations in OpenAlex.
- Article
- Differences in the activity intensity distribution over the day between boys and girls aged 3 to 17 years.Scientific reports · 2025Article
- Compositional functional regression and isotemporal substitution analysis: Methods and application in time-use epidemiology.Statistical methods in medical research · 2023Article
- Longitudinal Associations Between Timing of Physical Activity Accumulation and Health: Application of Functional Data Methods.Statistics in biosciences · 2023Article
- Current Trends and Strategies for Exercise in Diabetes.Diabetes spectrum : a publication of the American Diabetes Association · 2023Article
- Physical Activity Management for Youth With Type 1 Diabetes: Supporting Active and Inactive Children.Diabetes spectrum : a publication of the American Diabetes Association · 2023Article
- Joint regression modelling of intensity and timing of accelerometer counts.Statistics in medicine · 2023Article
- A function-based approach to model the measurement error in wearable devices.Statistics in medicine · 2022Article
- Associations between socioeconomic position and young people's physical activity and sedentary behaviour in the UK: a scoping review.BMJ open · 2022Article
- Heat-related mortality prediction using low-frequency climate oscillation indices: Case studies of the cities of Montréal and Québec, Canada.Environmental epidemiology (Philadelphia, Pa.) · 2022Article
- Evaluation of Wrist Accelerometer Cut-Points for Classifying Physical Activity Intensity in Youth.Frontiers in digital health · 2022Article
- Moderate-to-Vigorous Physical Activity in Primary School Children: Inactive Lessons Are Dominated by Maths and English.International journal of environmental research and public health · 2021Article
- Additive quantile regression for clustered data with an application to children's physical activity.Journal of the Royal Statistical Society. Series C, Applied statistics · 2019Article
- Exercise Management for Young People With Type 1 Diabetes: A Structured Approach to the Exercise Consultation.Frontiers in endocrinology · 2019Review
- Assessment of exposure to air pollution in children: Determining whether wearing a personal monitor affects physical activity.Environmental research · 2018Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundTemporal 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.
methodsChildren 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.
resultsDiurnal 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.
conclusionDiminished 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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