Compositional functional regression and isotemporal substitution analysis: Methods and application in time-use epidemiology
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15510%2F23%3A73620077" target="_blank" >RIV/61989592:15510/23:73620077 - isvavai.cz</a>
Alternative codes found
RIV/61989592:15310/23:73620077
Result on the web
<a href="https://journals.sagepub.com/doi/epub/10.1177/09622802231192949" target="_blank" >https://journals.sagepub.com/doi/epub/10.1177/09622802231192949</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1177/09622802231192949" target="_blank" >10.1177/09622802231192949</a>
Alternative languages
Result language
angličtina
Original language name
Compositional functional regression and isotemporal substitution analysis: Methods and application in time-use epidemiology
Original language description
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 ????2 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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
STATISTICAL METHODS IN MEDICAL RESEARCH
ISSN
0962-2802
e-ISSN
1477-0334
Volume of the periodical
32
Issue of the periodical within the volume
10
Country of publishing house
GB - UNITED KINGDOM
Number of pages
17
Pages from-to
2064-2080
UT code for WoS article
001062095800001
EID of the result in the Scopus database
2-s2.0-85171292030