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This study examines the meanings and prerequisites of self-organised physical activity from young people’s perspective. The theoretical framework is social space, which enables young people’s experiences to be interpreted in parallel with their physical, social, and cultural environment. Three research questions are addressed: (1) Where does young people’s self-organised physical activity take place? (2) What are the forms of the activity? (3) What meanings do young people associate with the spaces of the activity? The research data were collected within one municipality. The main data consist of 34 theme interviews with young people aged 12 to 16 years. The interviewees were selected mainly with the help of a questionnaire in three lower secondary schools. Interview data were also collected at the sites of self- organised physical activity. The chosen interviewees were boys and girls with different physical activity orientations in terms of the forms and frequency of physical activity, and with different living environments: a small city centre, the residential areas of the city, a rural town centre, and rural areas. The data also include activity maps and on-site observation. The data were analysed using content analysis. The ideal places of self-organised physical activity were situated close to home, available for spontaneous use, and occasionally modifiable. Open and sufficiently large spaces appeared to be more significant than high-quality sites or facilities. The forms of activity were characterised by the adaptation of sports and movement to suit the place, time frame, and particularly the reference group. Physical activity environments proved to be divergent social spaces for different young people. Spaces of sociality and spaces of playfulness were of major importance for the activity, implicating a distinction from the discourse of rationality. The spatial power held by adults over the spaces for the activity was also relevant for the meanings. In conclusion, the role of physical activity in unstructured leisure time varied from spontaneous supplementary motion to goal-oriented training. Finding space for meaningful activity required variable degrees of agency because it often connected with opportunities to negotiate acceptable uses of functionalised and limited space.

Background Obesity researchers increasingly use geographic information systems to measure exposure and access in neighborhood food and physical activity environments. This paper proposes a network buffering approach, the “sausage” buffer. This method can be consistently and easily replicated across software versions and platforms, avoiding problems with proprietary systems that use different approaches in creating such buffers. Methods In this paper, we describe how the sausage buffering approach was developed to be repeatable across platforms and places. We also examine how the sausage buffer compares with existing alternatives in terms of buffer size and shape, measurements of the food and physical activity environments, and associations between environmental features and health-related behaviors. We test the proposed buffering approach using data from EAT 2010 (Eating and Activity in Teens), a study examining multi-level factors associated with eating, physical activity, and weight status in adolescents (n = 2,724) in the Minneapolis/St. Paul metropolitan area of Minnesota. Results Results show that the sausage buffer is comparable in area to the classic ArcView 3.3 network buffer particularly for larger buffer sizes. It obtains similar results to other buffering techniques when measuring variables associated with the food and physical activity environments and when measuring the correlations between such variables and outcomes such as physical activity and food purchases. Conclusions Findings from various tests in the current study show that researchers can obtain results using sausage buffers that are similar to results they would obtain by using other buffering techniques. However, unlike proprietary buffering techniques, the sausage buffer approach can be replicated across software programs and versions, allowing more independence of research from specific software.