Standardised criteria for classifying the International Classification of Activities for Time-use Statistics (ICATUS) activity groups into sleep, sedentary behaviour, and physical activity.


Journal

The international journal of behavioral nutrition and physical activity
ISSN: 1479-5868
Titre abrégé: Int J Behav Nutr Phys Act
Pays: England
ID NLM: 101217089

Informations de publication

Date de publication:
14 11 2019
Historique:
received: 28 06 2019
accepted: 04 11 2019
entrez: 16 11 2019
pubmed: 16 11 2019
medline: 20 2 2020
Statut: epublish

Résumé

Globally, the International Classification of Activities for Time-Use Statistics (ICATUS) is one of the most widely used time-use classifications to identify time spent in various activities. Comprehensive 24-h activities that can be extracted from ICATUS provide possible implications for the use of time-use data in relation to activity-health associations; however, these activities are not classified in a way that makes such analysis feasible. This study, therefore, aimed to develop criteria for classifying ICATUS activities into sleep, sedentary behaviour (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), based on expert assessment. We classified activities from the Trial ICATUS 2005 and final ICATUS 2016. One author assigned METs and codes for wakefulness status and posture, to all subclass activities in the Trial ICATUS 2005. Once coded, one author matched the most detailed level of activities from the ICATUS 2016 with the corresponding activities in the Trial ICATUS 2005, where applicable. The assessment and harmonisation of each ICATUS activity were reviewed independently and anonymously by four experts, as part of a Delphi process. Given a large number of ICATUS activities, four separate Delphi panels were formed for this purpose. A series of Delphi survey rounds were repeated until a consensus among all experts was reached. Consensus about harmonisation and classification of ICATUS activities was reached by the third round of the Delphi survey in all four panels. A total of 542 activities were classified into sleep, SB, LPA, and MVPA categories. Of these, 390 activities were from the Trial ICATUS 2005 and 152 activities were from the final ICATUS 2016. The majority of ICATUS 2016 activities were harmonised into the ICATUS activity groups (n = 143). Based on expert consensus, we developed a classification system that enables ICATUS-based time-use data to be classified into sleep, SB, LPA, and MVPA categories. Adoption and consistent use of this classification system will facilitate standardisation of time-use data processing for the purpose of sleep, SB and physical activity research, and improve between-study comparability. Future studies should test the applicability of the classification system by applying it to empirical data.

Sections du résumé

BACKGROUND
Globally, the International Classification of Activities for Time-Use Statistics (ICATUS) is one of the most widely used time-use classifications to identify time spent in various activities. Comprehensive 24-h activities that can be extracted from ICATUS provide possible implications for the use of time-use data in relation to activity-health associations; however, these activities are not classified in a way that makes such analysis feasible. This study, therefore, aimed to develop criteria for classifying ICATUS activities into sleep, sedentary behaviour (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), based on expert assessment.
METHOD
We classified activities from the Trial ICATUS 2005 and final ICATUS 2016. One author assigned METs and codes for wakefulness status and posture, to all subclass activities in the Trial ICATUS 2005. Once coded, one author matched the most detailed level of activities from the ICATUS 2016 with the corresponding activities in the Trial ICATUS 2005, where applicable. The assessment and harmonisation of each ICATUS activity were reviewed independently and anonymously by four experts, as part of a Delphi process. Given a large number of ICATUS activities, four separate Delphi panels were formed for this purpose. A series of Delphi survey rounds were repeated until a consensus among all experts was reached.
RESULTS
Consensus about harmonisation and classification of ICATUS activities was reached by the third round of the Delphi survey in all four panels. A total of 542 activities were classified into sleep, SB, LPA, and MVPA categories. Of these, 390 activities were from the Trial ICATUS 2005 and 152 activities were from the final ICATUS 2016. The majority of ICATUS 2016 activities were harmonised into the ICATUS activity groups (n = 143).
CONCLUSIONS
Based on expert consensus, we developed a classification system that enables ICATUS-based time-use data to be classified into sleep, SB, LPA, and MVPA categories. Adoption and consistent use of this classification system will facilitate standardisation of time-use data processing for the purpose of sleep, SB and physical activity research, and improve between-study comparability. Future studies should test the applicability of the classification system by applying it to empirical data.

Identifiants

pubmed: 31727080
doi: 10.1186/s12966-019-0875-5
pii: 10.1186/s12966-019-0875-5
pmc: PMC6857154
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

106

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Auteurs

Nucharapon Liangruenrom (N)

Institute for Health and Sport, Victoria University, Melbourne, Australia.
Institute for Population and Social Research, Mahidol University, Nakhon Pathom, Thailand.

Melinda Craike (M)

Institute for Health and Sport, Victoria University, Melbourne, Australia.
Mitchell Institute, Victoria University, Melbourne, Australia.

Dorothea Dumuid (D)

Alliance for Research in Exercise, Nutrition and Activity, School of Health Sciences, University of South Australia, Adelaide, Australia.

Stuart J H Biddle (SJH)

Institute for Resilient Regions, University of Southern Queensland, Springfield, Australia.

Catrine Tudor-Locke (C)

College of Health and Human Services, University of North Carolina at Charlotte, NC, USA.

Barbara Ainsworth (B)

Department of Kinesiology, Shanghai University of Sport, Shanghai, Shanghai, People's Republic of China.
College of Health Solutions, Arizona State University, Phoenix, AZ, USA.

Chutima Jalayondeja (C)

Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, Thailand.

Theun Pieter van Tienoven (TP)

Research Group TOR, Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium.
Social Policy Research Centre, University of New South Wales, Sydney, Australia.

Ugo Lachapelle (U)

Department of Urban Studies and Tourism, Universite du Quebec a Montreal, Montreal, Canada.

Djiwo Weenas (D)

Research Group TOR, Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium.
Research Group Interface Demography, Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium.

David Berrigan (D)

Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA.

Timothy Olds (T)

Alliance for Research in Exercise, Nutrition and Activity, School of Health Sciences, University of South Australia, Adelaide, Australia.

Zeljko Pedisic (Z)

Institute for Health and Sport, Victoria University, Melbourne, Australia. zeljko.pedisic@vu.edu.au.

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