paperKB
coga / coga-kb
Help
Sign in

Chunk #24 — RESULTS — Trajectory Evidence of Developmental Continuity

Source
Are Alcohol Trajectories a Useful Way of Identifying At-Risk Youth? A Multiwave Longitudinal-Epidemiologic Study.
Embedded
yes

Text

Presented in Figure 1 is the overall growth curve for our sample, the average trajectory of alcohol use between ages 11–29. Presented in Figure 2 are the best-fitting trajectory group models, which yielded 6 trajectory groups (for both LCGA and GMM). In these models, alcohol trajectories are splayed out in a series of quadratic arcs ranked from lower levels of alcohol use to higher levels of use, with more individuals grouped in center trajectories than in fringe trajectories. From low to high, the percent of participants in each of the six trajectories is 4%, 11%, 39%, 29%, 15%, and 1% (LCGA) or 4%, 11%, 40%, 27%, 16%, and 1% (GMM). The rank order of these trajectories is stable throughout development, and none of the trajectories crosses at any age. Repeating our entire analytic approach in samples comprised of only one twin replicated these results, ruling out the possibility that genetic dependency between twins affected the results, and providing a strong replication (same method, same sampling, same demographics, 50–100% shared genetics, common environment, etc.).