Are Alcohol Trajectories a Useful Way of Identifying At-Risk Youth? A Multiwave Longitudinal-Epidemiologic Study.
- Authors
- Vachon, David D; Krueger, Robert F; Irons, Daniel E; Iacono, William G; McGue, Matt
- Year
- 2017
- Journal
- Journal of the American Academy of Child and Adolescent Psychiatry
- PMID
- 28545755
- DOI
- 10.1016/j.jaac.2017.03.016
- PMCID
- PMC5477663
OBJECTIVE: Trajectory approaches are a popular way of identifying subgroups of children and adolescents at high risk for developing alcohol use problems. However, mounting evidence challenges the meaning and utility of these putatively discrete alcohol trajectories, which can be analytically derived even in the absence of real subgroups. This study tests the hypothesis that alcohol trajectories may not reflect discrete groups-that the development of alcohol use is continuous rather than categorical. METHOD: A multiwave longitudinal-epidemiologic twin study was conducted using 3,762 twins (1,808 male and 1,954 female) aged 11 to 29 years from the Minnesota Center for Twin and Family Research (MCTFR). The main outcome measures included various assessments of substance use, psychopathology, personality, and cognitive ability. RESULTS: Although multiple trajectories are derived from growth mixture modeling techniques, these trajectories are arrayed in a tiered spectrum of severity, from lower levels of use to higher levels of use. Trajectories show perfect rank-order stability throughout development, monotonic increases in heritability, and perfect rank-order correlations with established correlates of alcohol use, including other substance use behaviors, psychiatric disorders, personality traits, intelligence, and achievement. CONCLUSION: Alcohol trajectories may represent continuous gradations rather than qualitatively distinct subgroups. If so, early detection and interventions for youth based on trajectory subtyping will be less useful than continuous liability assessments. Furthermore, a continuous account of development counters the notion that individuals are predestined to follow one of a few categorically distinct pathways and promotes the opposite idea-that development is mutable, and its continuous terrain can be traversed in many directions.
Alcohol Use Index (AUI) sample means for each cohort, and overall growth curve from combined sample. Note: Cohort 1 = ages 11, 14, 17, 20, 24, 29; Cohort 2 = ages 17, 20, 24, 29; Cohort 3 = ages 11, 14, 17, 20.
Alcohol use trajectory groups
Mean scores for each alcohol trajectory group. Note: “rev.” = reversed; these scales were reversed so that all measures were displayed in the direction of dysfunction (e.g., higher reversed IQ scores indicate lower intelligence). External correlates exhibit perfect rank-order correlation with trajectory group (rs = 1.00). ADHD = attention-deficit/hyperactivity disorder; GAD = generalized anxiety disorder; MDD = major depressive disorder; ODD = oppositional defiant disorder; PD = personality disorder.
Alcohol trajectories as contour lines on a continuous developmental topography.
No entities extracted from this document yet.
No uploaded files.
In this knowledge base
| Title | Year | PMID |
|---|---|---|
| Parsing genetically influenced risk pathways: genetic loci impact problematic alcohol use via externalizing and specific risk. | 2022 | 36180423 |
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Can psychiatric genetics advance without incorporating a lifecourse perspective? | Dennis JK et al. | — | 2026 | → |
| Associations of polygenic scores and developmental trajectories of externalizing behaviors. | Sasia AB et al. | — | 2025 | → |
| Etiology and correlates of alcohol misuse in early midlife. | Lumpe E et al. | — | 2025 | → |
| Informative patterns of health care utilization preceding the recognition of adult-onset multiple sclerosis: A population-based study. | Yusuf FLA et al. | — | 2025 | → |
| Patterns and predictors of alcohol misuse trajectories from adolescence through early midlife. | Stephenson M et al. | — | 2025 | → |
| Unsupervised machine learning identifies opioid taper reversal patterns in a longitudinal cohort (2008-2018). | Ray M et al. | — | 2025 | → |
| A Bootstrap Approach for Evaluating Uncertainty in the Number of Groups Identified by Latent Class Growth Models. | Mésidor M et al. | — | 2023 | → |
| Marginal structural models with latent class growth analysis of treatment trajectories: Statins for primary prevention among older adults. | Diop A et al. | — | 2023 | → |
| Parental Divorce and Trajectories of Alcohol Consumption in Men: A Genetically Informative Perspective. | Salvatore JE et al. | — | 2023 | → |
| The problem of latent class trajectory analysis in child growth and obesity research. | Johnson W | — | 2023 | → |
| Does group-based trajectory modeling estimate spurious trajectories? | Mésidor M et al. | — | 2022 | → |
| Exploring the relationships between adolescent alcohol misuse and later life health outcomes. | Pascale A et al. | — | 2022 | → |
| Heavy alcohol consumption before and after negative life events in late mid-life: longitudinal latent trajectory analyses. | Agahi N et al. | — | 2022 | → |
| Longitudinal associations of emerging adults' drinking trajectories with their behavior, health, education and work outcomes 1, 4, and 9 years later. | Schulte R et al. | — | 2022 | → |
| Parsing genetically influenced risk pathways: genetic loci impact problematic alcohol use via externalizing and specific risk. | Barr PB et al. | — | 2022 | → |
| Mexican-Origin Youths' Trajectories of Internalizing Symptoms from Childhood into Adolescence and Associations with Acculturation Processes. | Cruz RA et al. | — | 2021 | → |
| Parsing Genetically Influenced Risk Pathways: Genetic Loci Impact Problematic Alcohol Use Via Externalizing and Specific Risk | Barr PB et al. | — | 2021 | — |
| Revisiting trajectories of BMI in youth: An in-depth analysis of differences between BMI and other adiposity measures. | Sylvestre MP et al. | — | 2021 | → |
| A systematic review of cigarette smoking trajectories in adolescents. | Ahun MN et al. | — | 2020 | → |
| Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation. | Sylvestre MP et al. | — | 2020 | → |