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Adiposity and the isotemporal substitution of physical activity, sedentary time and sleep among school-aged children: a compositional data analysis approach

Overview of attention for article published in BMC Public Health, March 2018
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3 tweeters

Citations

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52 Dimensions

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140 Mendeley
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Title
Adiposity and the isotemporal substitution of physical activity, sedentary time and sleep among school-aged children: a compositional data analysis approach
Published in
BMC Public Health, March 2018
DOI 10.1186/s12889-018-5207-1
Pubmed ID
Authors

Dorothea Dumuid, Tyman E. Stanford, Željko Pedišić, Carol Maher, Lucy K. Lewis, Josep-Antoni Martín-Fernández, Peter T. Katzmarzyk, Jean-Philippe Chaput, Mikael Fogelholm, Martyn Standage, Mark S. Tremblay, Timothy Olds

Abstract

Daily activity data are by nature compositional data. Accordingly, they occupy a specific geometry with unique properties that is different to standard Euclidean geometry. This study aimed to estimate the difference in adiposity associated with isotemporal reallocation between daily activity behaviours, and to compare the findings from compositional isotemporal subsitution to those obtained from traditional isotemporal substitution. We estimated the differences in adiposity (body fat%) associated with reallocating fixed durations of time (isotemporal substitution) between accelerometer-measured daily activity behaviours (sleep, sedentary time and light and moderate-to-vigorous physical activity (MVPA)) among 1728 children aged 9-11 years from Australia, Canada, Finland and the UK (International Study of Childhood Obesity, Lifestyle and the Environment, 2011-2013). We generated estimates from compositional isotemporal substitution models and traditional non-compositional isotemporal substitution models. Both compositional and traditional models estimated a positive (unfavourable) difference in body fat% when time was reallocated from MVPA to any other behaviour. Unlike traditional models, compositional models found the differences in estimated adiposity (1) were not necessarily symmetrical when an activity was being displaced, or displacing another (2) were not linearly related to the durations of time reallocated, and (3) varied depending on the starting composition. The compositional isotemporal model caters for the constrained and therefore relative nature of activity behaviour data and enables all daily behaviours to be included in a single statistical model. The traditional model treats data as real variables, thus the constrained nature of time is not accounted for, nor reflected in the findings. Findings from compositional isotemporal substitution support the importance of MVPA to children's health, and suggest that while interventions to increase MVPA may be of benefit, attention should be directed towards strategies to avoid decline in MVPA levels, particularly among already inactive children. Future applications of the compositional model can extend from pair-wise reallocations to other configurations of time-reallocation, for example, increasing MVPA at the expense of multiple other behaviours.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 140 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 15%
Student > Ph. D. Student 19 14%
Student > Bachelor 14 10%
Student > Master 12 9%
Student > Doctoral Student 6 4%
Other 21 15%
Unknown 47 34%
Readers by discipline Count As %
Sports and Recreations 27 19%
Nursing and Health Professions 16 11%
Medicine and Dentistry 14 10%
Social Sciences 9 6%
Agricultural and Biological Sciences 6 4%
Other 12 9%
Unknown 56 40%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 December 2021.
All research outputs
#11,907,508
of 19,998,134 outputs
Outputs from BMC Public Health
#8,719
of 13,018 outputs
Outputs of similar age
#149,540
of 292,240 outputs
Outputs of similar age from BMC Public Health
#1
of 1 outputs
Altmetric has tracked 19,998,134 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,018 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 292,240 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them