Purpose: This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil.
Methods: We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model.
Results: The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14–4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16–2.53), reporting a good health (OR = 1.58, 95% CI = 1.02–2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05–2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26–2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18–2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030).
Conclusions: Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil.
1School of Health and Biosciences, Pontificia Universidade Catolica do Parana, Curitiba, BRAZIL; 2Department of Physical Education, Federal University of Parana, Curitiba, BRAZIL; 3Division of Public Health Sciences, Division of Biostatistics, Washington University School of Medicine, St. Louis, MO; 4Prevention Research Center in St. Louis, Brown School, Washington University in St. Louis, St. Louis, MO; and 5Division of Public Health Sciences and Alvin J. Siteman Cancer Center, School of Medicine, Washington University in St. Louis, St. Louis, MO
Address for correspondence: Rodrigo S. Reis, Ph.D., Rua Petit Carneiro, 571 ap501, Curitiba, Parana 80240050, Brazil; E-mail: email@example.com.
Submitted for publication March 2013.
Accepted for publication July 2013.