Conjoint Developmental Trajectories of Young Adult Alcohol and Tobacco Use.

Abstract

Developmental and etiological advances have set the stage for considering trajectories of problem behavior across the life course, but little work thus far addresses co-occurring problem behavior trajectories. Although recent work characterizes drinking and smoking trajectories, none has explored the course of concurrent drinking and smoking. Using panel data from the Monitoring the Future Project (N = 32,087), the authors applied growth mixture modeling to 4 waves of heavy drinking and smoking in a young-adult sample. The authors extracted a single latent group membership factor from heavy drinking and smoking. Associations between trajectory classes and risk factors were relatively unique to the substance being predicted. The association of smoking with alcohol expectancies and delinquency appeared to exist by virtue of smoking's comorbidity with drinking. Keywordsalcohol; tobacco; comorbidity; trajectory; developmental In the past decade, much research has been focused on modeling age trends in substance use and on examining both predictors and outcomes of such trends. Such research on the natural history of substance use has demonstrated that, on average, substance use tends to increase throughout adolescence, decline over young adulthood, and level off by the fourth decade of life (Bachman, Wadsworth, O'Malley, Johnston, & Schulenberg, 1997;Chen & Kandel, 1995). Despite the importance of identifying these normative age trends, however, the emphasis on average change belies the growing evidence that the developmental course of substance use is systematically heterogeneous across the life course with distinct variation in the timing and degree of escalation and duration. Identifying and modeling distinct courses of substance use can reveal the extent to which different risk and protective factors contribute to divergent developmental courses, and may have implications for intervention and treatment utilization, content, timing, and outcome (Schulenberg, Maggs, Steinman, & Zucker, 2001). This "person-centered" or "pattern-centered" emphasis (as opposed to a more "variablecentered" emphasis) has recently gained popularity and is based on understanding individual trajectories over time, rather than understanding average growth over time (Bates, 2000). More broadly, this reflects the growing understanding about the heterogeneity in the course of (Cicchetti & Rogosch, 2002). A key assumption of these "developmental typology" groupings is that the experience of those within a given group is distinctive; for example, those in the heavy chronic use groups use substances (and engage in related behaviors) in distinctive ways compared to those in low substance use groups. Developmental Course of Alcohol Use and Tobacco UseDuring recent years, theoretical and empirical research has begun to chart the longitudinal course of alcohol involvement during adolescence and young adulthood. Theoretical (Zucker, 1987(Zucker, , 1994Zucker, Fitzgerald, &Moses, 1995) and empirical (e.g., Bennett, McCrady, Johnson, &Pandina,...

A Developmental Perspective on Alcohol and Youths 16 to 20 Years of Age

“…The advantages of this approach include the abilities to draw meaningful distinctions among the groups in terms of antecedents and consequences and to consider the occurrence of similar trajectory groups across different outcomes. 77 Maggs and Schulenberg 74 summarized several studies that used this approach to examine alcohol use and problem drinking during late adolescence and early adulthood. Although the studies varied considerably in terms of ages, waves, measures, and analytic strategies, several common trajectory groups were found across the studies (Table 3).…”

Three-Year Changes in Adult Risk Drinking Behavior in Relation to the Course of Alcohol-Use Disorders

“…Virtually all studies have found male gender to be associated with higher baseline levels of heavy drinking and trajectories more indicative of increasing or continued heavy drinking. Other factors associated with change in drinking behavior over time have included baseline levels of alcohol and other substance use (Auerbach and Collins, 2006;Chassin et al, 2002;Hill et al, 2000;Sher and Rutledge, 2007;Windle et al, 2005); family history of alcoholism (Chassin et al, 2002(Chassin et al, , 2004Jackson et al, 2001;Timberlake et al, 2007); borderline personality disorder (PD) and/or behavioral undercontrol and impulsivity (Rohde et al, 2001;Rutledge and Sher, 2001); externalizing behavior, delinquency, conduct disorder, and antisocial PD (Bucholz et al, 2000;Chassin et al, 2002;Hill et al, 2000;Jackson and Sher, 2005;Tucker et al, 2003); and early initiation of drinking (Casswell et al, 2002;Goudriaan et al, 2007;Windle et al, 2005).…”

Nonnormality and divergence in posttreatment alcohol use: Reexamining the Project MATCH data "another way."

“…Covariates were mean centered to enhance interpretability of coefficients (Aiken & West, 1991). For the current study, one to four class models were compared by using the BIC, classification accuracy, class prevalence greater than 5% of sample (Jackson, Sher, & Schulenberg, 2005), the Lo-Mendell-Rubin likelihood ratio test (LRT) for k versus k -1 classes (Lo, Mendell, & Rubin, 2001), class interpretability and inspection of pseudoclass plots for all classes to check the scatter of observations. Classification accuracy was measured by using the entropy statistic measure given by Ramasway, DeSarbo, Reibstein, and Robinson (1993), with entropy values close to 1 (range = 0 to 1), indicating higher classification precision.…”