Background. Understanding drinking trajectories from adolescence to old age is crucial for assessing the long-term effects of intervention programs for adolescent drinking. This study estimates transition probabilities between alcohol consumption levels to understand the long-term drinking trajectories of adolescents in the United States. Methods. We used Bayesian simulation and simulated annealing to compute age- and sex-specific transition probabilities from age 12 to 65 y in the United States for 4 drinking risk levels (low, medium, high, very high), abstinence, and alcohol dependence. We simulated a cohort from age 12 to 65 y through these matrices to capture long-term trajectories. Results. Heavier drinking states carried greater risk of forward progression. Crucially, however, the lifetime average probability of remaining in dependence is only 0.49, implying a 0.51 chance of recovery—most frequently to abstinence (27%). Moreover, annual backward transitions occur at substantial rates: on average, 23% of high-risk drinkers transition to medium risk, and 25% of medium-risk drinkers transition to low risk across the life course. Limitations. This study lacks prior data on transitioning from alcohol dependence to other drinking states among adolescents, leading to some potentially inaccurate transition probabilities. In addition, although transition probabilities were estimated by age and sex, other factors such as race, geography, and religion were not considered, limiting generalizability. Conclusion. Transition probabilities for alcohol use states are essential to understanding the progression of alcohol use over a lifetime. These transition probabilities can also be used as inputs to model the long-term effects of intervention programs for adolescent drinking. Implications. These findings provide a framework for the long-term evaluation of intervention programs and guiding health care resource allocation to reduce adolescent alcohol consumption. Highlights This study estimates lifetime drinking trajectories from adolescence to old age in the United States. The model uses national survey datasets to simulate real-world alcohol use patterns over time.
Moid et al. (Thu,) studied this question.