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Participation in recreational physical activity: why do socioeconomic groups differ?
Nicola W Burton1, Gavin Turrell, Brian Oldenburg
1School of Public Health, Queensland University of Technology, Kelvin Grove, Australia. n.burton@qut.edu.au
Summary
Socioeconomic position significantly influences recreational physical activity (RPA) participation. Strategies to boost RPA should be general and socioeconomically targeted.
Area of Science:
- Public Health
- Sociology
- Behavioral Science
Background:
- Recreational physical activity (RPA) is crucial for public health.
- Understanding socioeconomic disparities in RPA is essential for targeted interventions.
- Previous research indicates socioeconomic position (SEP) influences health behaviors.
Purpose of the Study:
- To explore how influences on recreational physical activity (RPA) are patterned by socioeconomic position.
- To identify common and SEP-specific factors affecting RPA engagement.
- To inform the development of equitable strategies for promoting RPA.
Main Methods:
- Qualitative study design.
- Face-to-face interviews conducted with 60 participants (10 males, 10 females) across three distinct socioeconomic groups.
- Thematic analysis of interview data to identify key influences and barriers.
Main Results:
- Common influences across all SEP groups included previous opportunities, physical health, social assistance, safety, environmental aesthetics, urban design, health benefits, self-consciousness, low skill, and weather/time constraints.
- High SEP group: social benefits, balanced lifestyle, unpredictable lifestyle barriers.
- Mid and High SEP groups: efficacy, perceived need, activity demands, affiliation, emotional benefits, competing demands barriers.
- Low SEP group: poor health, inconvenient access, low personal functioning barriers.
Conclusions:
- Socioeconomic position significantly shapes the influences and barriers to recreational physical activity.
- General strategies promoting RPA are beneficial but insufficient.
- Targeted, socioeconomic-specific approaches are necessary to address disparities and increase RPA across diverse populations.