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Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach

BACKGROUND: The social and behavioural factors related to physical activity among adults are well known. Despite the overlapping nature of these factors, few studies have examined how multiple predictors of physical activity interact. This study aimed to identify the relative importance of multiple...

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Autores principales: Biswas, Aviroop, Chen, Cynthia, Dobson, Kathleen G., Prince, Stephanie A., Shahidi, Faraz Vahid, Smith, Peter M., Fuller, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517528/
https://www.ncbi.nlm.nih.gov/pubmed/37741965
http://dx.doi.org/10.1186/s12889-023-16747-9
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author Biswas, Aviroop
Chen, Cynthia
Dobson, Kathleen G.
Prince, Stephanie A.
Shahidi, Faraz Vahid
Smith, Peter M.
Fuller, Daniel
author_facet Biswas, Aviroop
Chen, Cynthia
Dobson, Kathleen G.
Prince, Stephanie A.
Shahidi, Faraz Vahid
Smith, Peter M.
Fuller, Daniel
author_sort Biswas, Aviroop
collection PubMed
description BACKGROUND: The social and behavioural factors related to physical activity among adults are well known. Despite the overlapping nature of these factors, few studies have examined how multiple predictors of physical activity interact. This study aimed to identify the relative importance of multiple interacting sociodemographic and work-related factors associated with the daily physical activity patterns of a population-based sample of workers. METHODS: Sociodemographic, work, screen time, and health variables were obtained from five, repeated cross-sectional cohorts of workers from the Canadian Health Measures Survey (2007 to 2017). Classification and Regression Tree (CART) modelling was used to identify the discriminators associated with six daily physical activity patterns. The performance of the CART approach was compared to a stepwise multinomial logistic regression model. RESULTS: Among the 8,909 workers analysed, the most important CART discriminators of daily physical activity patterns were age, job skill, and physical strength requirements of the job. Other important factors included participants’ sex, educational attainment, fruit/vegetable intake, industry, work hours, marital status, having a child living at home, computer time, and household income. The CART tree had moderate classification accuracy and performed marginally better than the stepwise multinomial logistic regression model. CONCLUSION: Age and work-related factors–particularly job skill, and physical strength requirements at work–appeared as the most important factors related to physical activity attainment, and differed based on sex, work hours, and industry. Delineating the hierarchy of factors associated with daily physical activity may assist in targeting preventive strategies aimed at promoting physical activity in workers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16747-9.
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spelling pubmed-105175282023-09-24 Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach Biswas, Aviroop Chen, Cynthia Dobson, Kathleen G. Prince, Stephanie A. Shahidi, Faraz Vahid Smith, Peter M. Fuller, Daniel BMC Public Health Research BACKGROUND: The social and behavioural factors related to physical activity among adults are well known. Despite the overlapping nature of these factors, few studies have examined how multiple predictors of physical activity interact. This study aimed to identify the relative importance of multiple interacting sociodemographic and work-related factors associated with the daily physical activity patterns of a population-based sample of workers. METHODS: Sociodemographic, work, screen time, and health variables were obtained from five, repeated cross-sectional cohorts of workers from the Canadian Health Measures Survey (2007 to 2017). Classification and Regression Tree (CART) modelling was used to identify the discriminators associated with six daily physical activity patterns. The performance of the CART approach was compared to a stepwise multinomial logistic regression model. RESULTS: Among the 8,909 workers analysed, the most important CART discriminators of daily physical activity patterns were age, job skill, and physical strength requirements of the job. Other important factors included participants’ sex, educational attainment, fruit/vegetable intake, industry, work hours, marital status, having a child living at home, computer time, and household income. The CART tree had moderate classification accuracy and performed marginally better than the stepwise multinomial logistic regression model. CONCLUSION: Age and work-related factors–particularly job skill, and physical strength requirements at work–appeared as the most important factors related to physical activity attainment, and differed based on sex, work hours, and industry. Delineating the hierarchy of factors associated with daily physical activity may assist in targeting preventive strategies aimed at promoting physical activity in workers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16747-9. BioMed Central 2023-09-23 /pmc/articles/PMC10517528/ /pubmed/37741965 http://dx.doi.org/10.1186/s12889-023-16747-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Biswas, Aviroop
Chen, Cynthia
Dobson, Kathleen G.
Prince, Stephanie A.
Shahidi, Faraz Vahid
Smith, Peter M.
Fuller, Daniel
Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach
title Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach
title_full Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach
title_fullStr Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach
title_full_unstemmed Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach
title_short Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach
title_sort identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517528/
https://www.ncbi.nlm.nih.gov/pubmed/37741965
http://dx.doi.org/10.1186/s12889-023-16747-9
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