This proposal estimates trajectories of substance use and crime through the life course, and builds models to explain those trajectories. It uses three datasets, the Denver Youth Survey, National Youth Survey, and Add Health Survey. It identifies key risk factors from social learning (coercive parenting, deliquent peers, deliquent attitudes, delinquent identity), rational choice (risk of arrest, rewards of drug use), stable trait (impulsivity), and life course theories (high school graduation, employment, marriage). The analysis begins by estimating individual growth curves of marijuana, cigarettes, alcohol, other drugs, and deliquency. It then uses multi-level models tests three hypotheses: (1) A cormobidity hypothesis in which a latent variable underlies one or more trajectories. (2) A stable context and stable trait hypothesis, in which trajectory parameters are predicted by stable traits like impulsivity, and stable contexts, like SES and family functioning. (3) A life course hypothesis, in which life course transitions are treated as time-varying covariates predicting substance use trajectories. (4) A social process hypothesis, in which process variables, like deliquent peers or perceived risk of arrest influence trajectories. We then examine latent classes of trajectories using Nagin's nonparametric mixed model. We test Moffitt's hypothesis that at least two groups-life course persistent and adolescence limited-underly trajectories of illegal behavior, and extend the hypothesis to substance use. We revisit the cormobidity hypothesis by examining whether cormobidity varies within and across latent classes. We then test whether contextual variables and stable traits can explain the group classifications, and using twin data, estimate genetic effects. Finally, we will test our process and life course theories by testing whether their effects are moderated by latent classes (e.g. Are life course persistent drug users immune to the threat of arrest? Do adolescence limited learn from life course persistent? Such results have important health policy implications for prevention and education.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
1R01DA018148-01A1
Application #
6970249
Study Section
Behavioral Genetics and Epidemiology Study Section (BGES)
Program Officer
Rugh, Douglas
Project Start
2005-09-15
Project End
2008-08-31
Budget Start
2005-09-15
Budget End
2006-08-31
Support Year
1
Fiscal Year
2005
Total Cost
$346,209
Indirect Cost
Name
University of Washington
Department
Social Sciences
Type
Schools of Arts and Sciences
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Telesca, Donatello; Erosheva, Elena A; Kreager, Derek A et al. (2012) Modeling Criminal Careers as Departures from a Unimodal Population Age-Crime Curve: The Case of Marijuana Use. J Am Stat Assoc 107:1427-1440