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

Rochelle M Eime, Jack T Harvey, Melanie J Charity, Rayoni Nelson
Author Information
  1. Rochelle M Eime: School of Health Sciences and Psychology, Federation University, Ballarat, Australia. r.eime@federation.edu.au.
  2. Jack T Harvey: School of Health Sciences and Psychology, Federation University, Ballarat, Australia.
  3. Melanie J Charity: School of Health Sciences and Psychology, Federation University, Ballarat, Australia.
  4. Rayoni Nelson: Victorian Health Promotion Foundation (VicHealth), Melbourne, Australia.

Abstract

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.

Keywords

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MeSH Term

Adolescent
Adult
Australia
Cross-Sectional Studies
Exercise
Female
Humans
Leisure Activities
Male
Middle Aged
Sedentary Behavior
Socioeconomic Factors
Sports
Surveys and Questionnaires
Young Adult

Word Cloud

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