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Mendeley readers
Attention Score in Context
| Title |
Compositional functional regression and isotemporal substitution analysis: Methods and application in time-use epidemiology
|
|---|---|
| Published in |
Statistical Methods in Medical Research, August 2023
|
| DOI | 10.1177/09622802231192949 |
| Pubmed ID | |
| Authors |
Paulína Jašková, Javier Palarea-Albaladejo, Aleš Gába, Dorothea Dumuid, Željko Pedišić, Jana Pelclová, Karel Hron |
| Abstract |
The distribution of time that people spend in physical activity of various intensities has important health implications. Physical activity (commonly categorised by the intensity into light, moderate and vigorous physical activity), sedentary behaviour and sleep, should not be analysed separately, because they are parts of a time-use composition with a natural constraint of 24 h/day. To find out how are relative reallocations of time between physical activity of various intensities associated with health, herewith we describe compositional scalar-on-function regression and a newly developed compositional functional isotemporal substitution analysis. Physical activity intensity data can be considered as probability density functions, which better reflects the continuous character of their measurement using accelerometers. These probability density functions are characterised by specific properties, such as scale invariance and relative scale, and they are geometrically represented using Bayes spaces with the Hilbert space structure. This makes possible to process them using standard methods of functional data analysis in the L2 space, via centred logratio (clr) transformation. The scalar-on-function regression with clr transformation of the explanatory probability density functions and compositional functional isotemporal substitution analysis were applied to a dataset from a cross-sectional study on adiposity conducted among school-aged children in the Czech Republic. Theoretical reallocations of time to physical activity of higher intensities were found to be associated with larger and more progressive expected decreases in adiposity. We obtained a detailed insight into the dose-response relationship between physical activity intensity and adiposity, which was enabled by using the compositional functional approach. |
X Demographics
The data shown below were collected from the profiles of 29 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 14% |
| Czechia | 2 | 7% |
| Canada | 1 | 3% |
| Australia | 1 | 3% |
| United Kingdom | 1 | 3% |
| Brazil | 1 | 3% |
| France | 1 | 3% |
| Unknown | 18 | 62% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 48% |
| Members of the public | 12 | 41% |
| Practitioners (doctors, other healthcare professionals) | 3 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 30% |
| Unspecified | 1 | 10% |
| Researcher | 1 | 10% |
| Student > Master | 1 | 10% |
| Unknown | 4 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 3 | 30% |
| Mathematics | 1 | 10% |
| Medicine and Dentistry | 1 | 10% |
| Design | 1 | 10% |
| Unknown | 4 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 30 November 2023.
All research outputs
#1,970,498
of 25,387,668 outputs
Outputs from Statistical Methods in Medical Research
#35
of 964 outputs
Outputs of similar age
#33,686
of 356,469 outputs
Outputs of similar age from Statistical Methods in Medical Research
#2
of 14 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 964 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 96% of its peers.
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 356,469 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.