Identifying trajectories of adolescent smoking: An application of latent growth mixture modeling

The goal of the current study was to identify discrete longitudinal patterns of change in adolescent smoking using latent growth mixture modeling. Five distinct longitudinal patterns were identified. A group of early rapid escalators was characterized by early escalation (at age 13) that rapidly increased to heavy smoking. A pattern characterized by occasional puffing up until age 15, at which time smoking escalated to moderate levels was also identified (late moderate escalators). Another group included adolescents who, after age 15, began to escalate slowly in their smoking to light (0.5 cigarettes per month) levels (late slow escalators). Finally, a group of stable light smokers (those who smoked 1-2 cigarettes per month) and a group of stable puffers (those. who smoked only a few puffs per month) were also identified. The stable puffer group was the largest group and represented 25% of smokers.

Identifying and predicting adolescent smokers' developmental trajectories

Very few studies have defined trajectories of smoking. In the present study, we modeled growth in adolescent smoking and empirically identified prototypical trajectories. We conceptualized escalation of smoking as a growth process and modeled rates of change and heterogeneity of these patterns using latent growth mixture modeling. The analysis identified six trajectories with low ambiguity about group membership (early rapid escalators, late rapid escalators, late moderate escalators, late slow escalators-smokers, stable puffers, and late slow escalators-puffers). A trajectory of quitters was not identified. We also examined predictors of the smoking trajectories. The predictors were assessed across the adolescent years and included variables related to smoking and other substance use, as well as a range of variables related to sociodemographic factors and mental health. Observed change in the pattern of predictors across age has implications for the mechanism of effect of these variables in relation to smoking trajectories, including predictors that differentiated among daily smokers, variables that may determine the trajectory (e.g., friends smoking), and variables that may result from the trajectory (e.g., marijuana use, less attachment to friends).