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Demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 Australian people

BACKGROUND: Regular physical activity (PA) is imperative for good health and there are many different ways that people can be active. There are a range of health, PA and sport policies aiming to get more people active more often. Much research has been directed towards understanding the determinants...

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Autores principales: Eime, Rochelle M., Harvey, Jack T., Charity, Melanie J., Nelson, Rayoni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5989390/
https://www.ncbi.nlm.nih.gov/pubmed/29871601
http://dx.doi.org/10.1186/s12889-018-5608-1
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author Eime, Rochelle M.
Harvey, Jack T.
Charity, Melanie J.
Nelson, Rayoni
author_facet Eime, Rochelle M.
Harvey, Jack T.
Charity, Melanie J.
Nelson, Rayoni
author_sort Eime, Rochelle M.
collection PubMed
description BACKGROUND: Regular physical activity (PA) is imperative for good health and there are many different ways that people can be active. There are a range of health, PA and sport policies aiming to get more people active more often. Much research has been directed towards understanding the determinants of inactivity and PA. However, it is important to understand the differences not only between inactive and active people, but also between activity contexts (for example participation in sport compared to non-sport activities), in order to align policies and strategies to engage market segments who have different participation preferences and accessibility. The aim of this study was to investigate demographic correlates of the propensity to be physically inactive or active within different contexts, and at different levels of frequency of participation. METHODS: Data from the Australian Exercise, Recreation and Sport Survey was used for this analysis. This included information on the type, frequency and duration of leisure-time PA for Australians aged 15 years and over. Reported PA participation in the two-week period prior to the survey was used to allocate respondents into three categories: no PA, non-sport PA only, and sport. Subsequently, sport participants were further categorised according to frequency of participation. Potential demographic correlates included sex, age, education, employment, marital status, language spoken, having a condition that restricts life, children, and socio-economic status. RESULTS: The survey included 21,603 people. Bivariate chi-squared analysis showed that there were significant differences between the profiles of leisure-time PA participation across all demographic variables, except the variable languages spoken at home. Ordinal regression analysis showed that the same demographic variables were also correlated with the propensity to engage in more organised and competitive PA contexts, and to participate more frequently. CONCLUSIONS: People who were female, older, married or had a disability were less likely to participate in sport. Therefore when designing PA opportunities to engage those who are inactive, particularly those that are organised by a club or group, we need to ensure that appropriate strategies are developed, and tailored sport products offered, to ensure greater opportunities for increased diversity of participation in sport.
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spelling pubmed-59893902018-06-20 Demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 Australian people Eime, Rochelle M. Harvey, Jack T. Charity, Melanie J. Nelson, Rayoni BMC Public Health Research Article BACKGROUND: Regular physical activity (PA) is imperative for good health and there are many different ways that people can be active. There are a range of health, PA and sport policies aiming to get more people active more often. Much research has been directed towards understanding the determinants of inactivity and PA. However, it is important to understand the differences not only between inactive and active people, but also between activity contexts (for example participation in sport compared to non-sport activities), in order to align policies and strategies to engage market segments who have different participation preferences and accessibility. The aim of this study was to investigate demographic correlates of the propensity to be physically inactive or active within different contexts, and at different levels of frequency of participation. METHODS: Data from the Australian Exercise, Recreation and Sport Survey was used for this analysis. This included information on the type, frequency and duration of leisure-time PA for Australians aged 15 years and over. Reported PA participation in the two-week period prior to the survey was used to allocate respondents into three categories: no PA, non-sport PA only, and sport. Subsequently, sport participants were further categorised according to frequency of participation. Potential demographic correlates included sex, age, education, employment, marital status, language spoken, having a condition that restricts life, children, and socio-economic status. RESULTS: The survey included 21,603 people. Bivariate chi-squared analysis showed that there were significant differences between the profiles of leisure-time PA participation across all demographic variables, except the variable languages spoken at home. Ordinal regression analysis showed that the same demographic variables were also correlated with the propensity to engage in more organised and competitive PA contexts, and to participate more frequently. CONCLUSIONS: People who were female, older, married or had a disability were less likely to participate in sport. Therefore when designing PA opportunities to engage those who are inactive, particularly those that are organised by a club or group, we need to ensure that appropriate strategies are developed, and tailored sport products offered, to ensure greater opportunities for increased diversity of participation in sport. BioMed Central 2018-06-05 /pmc/articles/PMC5989390/ /pubmed/29871601 http://dx.doi.org/10.1186/s12889-018-5608-1 Text en © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Eime, Rochelle M.
Harvey, Jack T.
Charity, Melanie J.
Nelson, Rayoni
Demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 Australian people
title Demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 Australian people
title_full Demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 Australian people
title_fullStr Demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 Australian people
title_full_unstemmed Demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 Australian people
title_short Demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 Australian people
title_sort demographic characteristics and type/frequency of physical activity participation in a large sample of 21,603 australian people
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5989390/
https://www.ncbi.nlm.nih.gov/pubmed/29871601
http://dx.doi.org/10.1186/s12889-018-5608-1
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