Childhood Predictors and Mid-Adolescent Correlates of Developmental Trajectories of Alcohol Use among Male and Female Youth

Participant loss primarily occurred for two reasons (both a consequence of German unification). First, families moved away from the city of Leipzig from 1990 onward, usually to West Germany (see also Sahner 1996; Statistisches Landesamt des Freistaates Sachsen 2002). Second, the East German school system was restructured in 1990–1991 (Kuhnke 1997).

As of July 1991, the equivalent amounts in USD currency were: the median per capita household income was $344.92 per month (ranging from $57.40 to $1069.54).

According to Pulkkinen (1996), impulsivity is characterized by acting without appropriate reflection, distorted information processing, or inability to maintain attention. In the present study, both cognitive (i.e., cognitive test results) and behavioral (i.e., parent and teacher reports) aspects of impulsivity were assessed (White et al. 1994). All indicators sought to capture features of temperament that are related to problematic use of alcohol among adolescents (see Tarter 2002). Our measure of impulsivity was validated by concurrent parent reports which revealed meaningful associations between high impulsivity on the one hand and perinatal complications and problematic, harsh parenting practices on the other hand (see Weichold 2002, for more information).

As shown in several studies (e.g., Lane et al. 2013; Stoolmiller et al. 2005), predictors may be related to trajectory class membership and/or developmental course over time within a given trajectory group. Both components of prediction have important implications for prevention and intervention efforts. Because the main focus of the current study was on the prediction of trajectory class membership, we applied the described stepwise testing strategy in order to empirically identify the most salient predictors of within-class developmental course and thus minimize model complexity.

We also predicted trajectory group membership using groups with “normative” consumption trajectories (i.e., “late escalators” for males and “increases” for females) as baseline groups. Result tables for these analyses can be obtained from the first author upon request. Briefly summarizing, the key findings for these prediction models were as follows: for males, just one variable was significantly linked to membership in the early peaker group. Older males were more likely to belong to the early peaker group than to the baseline group of late escalators (p < .05). Three variables were significant predictors of membership in the regular user group. Males from larger communities (p < .05) and with highly educated parents (p < .05) were less likely to belong to the regular user group, and males with higher levels of parents’ alcohol use were more likely to belong to the regular user group (p < .01) relative to the baseline group of late escalators. Finally, two variables were significantly associated with membership in the rare user group. Older males were more likely to be in the rare user group (p < .05), and males with more highly educated parents were less likely to belong to the rare user group (p < .05) compared to the baseline group of late escalators. For females, two variables significantly predicted membership in the rare user group. Females with higher impulsivity (p < .05) and from larger communities (p < .05) were more likely to be in the rare user group than in the baseline group of increasers. Two variables were significantly linked to membership in the decreaser group. Females with higher body mass index (p < .05) and with a more risky peer context (p < .01) were more likely to belong to the decreasers compared to the baseline group of increasers. Finally, five variables were significant predictors of regular user group membership. Females with higher levels of impulsivity (p < .05) and higher paternal education (p < .05) were less likely to belong to the regular users than to the baseline group of increasers. Females with higher levels of parents’ alcohol use (p < .01), higher body mass index (p < .01), and a more risky peer context (p < .01) were more likely to be in the regular user group compared to the baseline group of increasers.