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Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)

Data on the use of time in different exposures, behaviors, and work tasks are common in occupational research. Such data are most often expressed in hours, minutes, or percentage of work time. Thus, they are constrained or ‘compositional’, in that they add up to a finite sum (e.g. 8 h of work or 100...

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Autores principales: Gupta, Nidhi, Rasmussen, Charlotte Lund, Holtermann, Andreas, Mathiassen, Svend Erik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7544002/
https://www.ncbi.nlm.nih.gov/pubmed/32607544
http://dx.doi.org/10.1093/annweh/wxaa056
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author Gupta, Nidhi
Rasmussen, Charlotte Lund
Holtermann, Andreas
Mathiassen, Svend Erik
author_facet Gupta, Nidhi
Rasmussen, Charlotte Lund
Holtermann, Andreas
Mathiassen, Svend Erik
author_sort Gupta, Nidhi
collection PubMed
description Data on the use of time in different exposures, behaviors, and work tasks are common in occupational research. Such data are most often expressed in hours, minutes, or percentage of work time. Thus, they are constrained or ‘compositional’, in that they add up to a finite sum (e.g. 8 h of work or 100% work time). Due to their properties, compositional data need to be processed and analyzed using specifically adapted methods. Compositional data analysis (CoDA) has become a particularly established framework to handle such data in various scientific fields such as nutritional epidemiology, geology, and chemistry, but has only recently gained attention in public and occupational health sciences. In this paper, we introduce the reader to CoDA by explaining why CoDA should be used when dealing with compositional time-use data, showing how to perform CoDA, including a worked example, and pointing at some remaining challenges in CoDA. The paper concludes by emphasizing that CoDA in occupational research is still in its infancy, and stresses the need for further development and experience in the use of CoDA for time-based occupational exposures. We hope that the paper will encourage researchers to adopt and apply CoDA in studies of work exposures and health.
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spelling pubmed-75440022020-10-15 Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA) Gupta, Nidhi Rasmussen, Charlotte Lund Holtermann, Andreas Mathiassen, Svend Erik Ann Work Expo Health Commentaries Data on the use of time in different exposures, behaviors, and work tasks are common in occupational research. Such data are most often expressed in hours, minutes, or percentage of work time. Thus, they are constrained or ‘compositional’, in that they add up to a finite sum (e.g. 8 h of work or 100% work time). Due to their properties, compositional data need to be processed and analyzed using specifically adapted methods. Compositional data analysis (CoDA) has become a particularly established framework to handle such data in various scientific fields such as nutritional epidemiology, geology, and chemistry, but has only recently gained attention in public and occupational health sciences. In this paper, we introduce the reader to CoDA by explaining why CoDA should be used when dealing with compositional time-use data, showing how to perform CoDA, including a worked example, and pointing at some remaining challenges in CoDA. The paper concludes by emphasizing that CoDA in occupational research is still in its infancy, and stresses the need for further development and experience in the use of CoDA for time-based occupational exposures. We hope that the paper will encourage researchers to adopt and apply CoDA in studies of work exposures and health. Oxford University Press 2020-07-01 /pmc/articles/PMC7544002/ /pubmed/32607544 http://dx.doi.org/10.1093/annweh/wxaa056 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the British Occupational Hygiene Society. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Commentaries
Gupta, Nidhi
Rasmussen, Charlotte Lund
Holtermann, Andreas
Mathiassen, Svend Erik
Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)
title Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)
title_full Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)
title_fullStr Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)
title_full_unstemmed Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)
title_short Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)
title_sort time-based data in occupational studies: the whys, the hows, and some remaining challenges in compositional data analysis (coda)
topic Commentaries
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7544002/
https://www.ncbi.nlm.nih.gov/pubmed/32607544
http://dx.doi.org/10.1093/annweh/wxaa056
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