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BACKGROUND:To develop targeted policy strategies to increase sports participation, more insight is needed into the behavioural patterns and preferences of users of different club-organized (i.e., sports clubs) and non-club organized (i.e., gyms, health centres or swimming pools) or informal sports settings such as public spaces. This study investigates 1) how users of different settings differ regarding self-determined motivations and goals, and sociodemographic and sports-related characteristics, and 2) how the association of motivations and goals with sports participation may differ between users of different sports settings. METHODS:Data were collected through online surveys among Dutch adults aged 18-80 years (N = 910). Ordinal regression analyses were used to investigate the effects of sports settings, the level of self-determined motivations and goals, and interaction effects of motivations and goals with different sports settings, on sports frequency. RESULTS:Users of different sports settings differed in their personal characteristics, motivations and goals. In general, controlled motivations were negatively associated with sports frequency (B = -0.46). However, among club members, extrinsic goals related to image (B = 0.44), as well as intrinsic goals related to skill development (B = 0.40) and social affiliation (B = 0.47) had significant positive associations with sports frequency. Health-related goals significantly increased sports frequency among users of informal settings, such as public spaces. CONCLUSION:The association of motivational variables with sports participation differs between settings. This implies that sports frequency is higher when participants engage in settings that better fit their motivations and goals. Because of the growing importance of informal and flexible settings and health goals, professionals in the sports and health domains should take into account the motivations, goals and needs of different target groups who (want to) use unorganized, informal sports settings including public spaces.

Unhealthy food choices follow a socioeconomic gradient that may partly be explained by one's 'cultural capital', as defined by Bourdieu. We aim 1) to carry out a systematic review to identify existing quantitative measures of cultural capital, 2) to develop a questionnaire to measure cultural capital for food choices, and 3) to empirically test associations of socioeconomic position with cultural capital and food choices, and of cultural capital with food choices.We systematically searched large databases for the key-word 'cultural capital' in title or abstract. Indicators of objectivised cultural capital and family institutionalised cultural capital, as identified by the review, were translated to food choice relevant indicators. For incorporated cultural capital, we used existing questionnaires that measured the concepts underlying the variety of indicators as identified by the review, i.e. participation, skills, knowledge, values. The questionnaire was empirically tested in a postal survey completed by 2,953 adults participating in the GLOBE cohort study, The Netherlands, in 2011.The review yielded 113 studies that fulfilled our inclusion criteria. Several indicators of family institutionalised (e.g. parents' education completed) and objectivised cultural capital (e.g. possession of books, art) were consistently used. Incorporated cultural capital was measured with a large variety of indicators (e.g. cultural participation, skills). Based on this, we developed a questionnaire to measure cultural capital in relation to food choices. An empirical test of the questionnaire showed acceptable overall internal consistency (Cronbach's alpha of .654; 56 items), and positive associations between socioeconomic position and cultural capital, and between cultural capital and healthy food choices.Cultural capital may be a promising determinant for (socioeconomic inequalities in) food choices.