one year increase. An unconditional latent growth curve model without any covariate or predictor was first fitted using all participants to establish the most parsimonious growth model. Preliminary analyses revealed a small and significant quadratic slope, as well as a non-significant variance for the quadratic slope. Therefore, the variance for the quadratic slope was fixed at zero in all subsequent analyses. Next, ethnicity (1 = “AAs”, 0 = “EAs”), intervention status (1 = “intervention”, 0 = “control”), and covariates (gender, severity-of-risk screen score, age, cohort, and site) were included in the latent growth curve model to predict the intercept and linear slope.
