We will assess program effects at the station and individual level. We will analyze the hierarchical data (fire fighters nested at fire stations) using linear modeling and use latent growth modeling to examine change over time. In addition, we will use covariance structure models to identify constructs and latent paths among constructs that affect outcomes. Our large data set, nested study design, and prospective longitudinal assessment make these newer modeling techniques well suited for our data analysis. Results from PHLAME will provide information on health behavior change and health promotion for adults.