Modeling physical activity propagation, such as physical exercise level and intensity, is the key to preventing the conduct that can lead to obesity and to spreading wellness and healthy behavior in a social network. The authors introduce a model for Topic-aware Community-level Physical Activity Propagation (TaCPP) to analyze physical activity propagation and social influence at different granularities. Given a social network, the TaCPP model first integrates the correlations between the content of social communication and social influences and then uses a hierarchical approach to detect a set of communities and their reciprocal influence strength. The authors' experimental evaluation shows not only the effectiveness of their approach but also the correlation of the detected communities with various health outcome measures.