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Reaching population-level impact for families in poverty requires moving beyond a sole focus on individuals, to a wider focus on interactions between individuals and their broader environmental contexts. Place-based initiatives have emerged as a policy response to promote community-level change around these broader interactions between individuals and their local communities through addressing long-standing disparities in housing, employment, education, and health. Together Growing Strong (TGS) is one such place-based initiative focused on transforming the health, wellbeing, and development of young children and their families in Sunset Park, Brooklyn. The Children, Caregivers, and Community (C3) Study is an outcomes-based study designed to assess the trajectories of children and families in Sunset Park along indicators such as family health and wellbeing and child development in relation to TGS program participation. The aims, scope, and protocol of the C3 Study are the subjects of this paper. [ABSTRACT FROM AUTHOR]

This study compared marginal and conditional modeling approaches for identifying individual, park and neighborhood park use predictors. Data were derived from the ParkIndex study, which occurred in 128 block groups in Brooklyn (New York), Seattle (Washington), Raleigh (North Carolina), and Greenville (South Carolina). Survey respondents (n = 320) indicated parks within one half-mile of their block group used within the past month. Parks (n = 263) were audited using the Community Park Audit Tool. Measures were collected at the individual (park visitation, physical activity, sociodemographic characteristics), park (distance, quality, size), and block group (park count, population density, age structure, racial composition, walkability) levels. Generalized linear mixed models and generalized estimating equations were used. Ten-fold cross validation compared predictive performance of models. Conditional and marginal models identified common park use predictors: participant race, participant education, distance to parks, park quality, and population >65yrs. Additionally, the conditional mode identified park size as a park use predictor. The conditional model exhibited superior predictive value compared to the marginal model, and they exhibited similar generalizability. Future research should consider conditional and marginal approaches for analyzing health behavior data and employ cross-validation techniques to identify instances where marginal models display superior or comparable performance. [ABSTRACT FROM AUTHOR]