Pre- or early adolescent alcohol use is related to significant problems later in life. Gruber, DiClemente, Anderson, and Lodico (1996) found that onset of alcohol use by age 12 was associated with subsequent use of alcohol and problem behaviors in later adolescence, including alcohol-related violence, alcohol-related injuries, drinking and driving, and absenteeism from school or work, and with being at increased risk for using other drugs. Hawkins et al. (1997) found that early initiation of alcohol use mediated nearly all of the identified risk factors for subsequent alcohol use, including parental drinking, proactive parenting, school bonding, peer alcohol initiation, and ethnicity. Youth who drink before age 15 are estimated to be 4 times more likely to develop alcohol dependence than are those who begin drinking after age 18 (Grant & Dawson, 1997). These data, from the National Longitudinal Alcohol Epidemiologic Survey, indicate that the odds of alcohol dependence decreased by 14% with each increasing year of age at onset of use, and the odds of abuse decreased by 8% (Grant & Dawson, 1997). Notably, of those who began to drink before age 12, 16% reported being dependent on alcohol in the past year as adults (Substance Abuse and Mental Health Services Administration, 2004).

Early alcohol use is found among all races/ethnicities, all socioeconomic strata, both genders, and urban to rural populations. The prevalence of adolescent alcohol use is substantial, even though the rate of use has declined somewhat since 1999 (Johnston, O’Malley, Bachman, & Schulenberg, 2005). Overall, according to 2005 data from the Monitoring the Future national survey, 33.9% of eighth graders used alcohol and 14.1% reported having been drunk in the past year. In addition, 17.1% had used alcohol and 6.0% had been drunk in the past month (Johnston, O’Malley, Bachman, & Schulenberg, 2006).

Early alcohol use has been conceptualized as an interaction of social, environmental, intrapersonal, and behavioral factors. Prior research on social factors has shown an association between early conduct problems at ages 7 to 9 and alcoholism 25 years later (Fergusson, Horwood, & Ridder, 2005). Early use of other substances, feelings of depression, and deviant or violent behaviors also increase the likelihood of early alcohol initiation among youth (Donovan, 2004). Interestingly, youth who own alcohol-promotion items have been found to be more likely to initiate alcohol use than those youth who do not own alcohol-promotion items (McClure, Dal Cin, Gibson, & Sargent, 2006). Time spent with family members (Sweeting, West, & Richards, 1998), participation in extracurricular activities and sports (Harrison & Narayan, 2003), and participation in religious activities (Sinha, Cnaan, & Gelles, 2007) have all been found to reduce the likelihood of alcohol use among adolescents, whereas less is known about these and preadolescent alcohol use.

The most consistent socioenvironmental risk factors for early alcohol use are peer and parental factors (Donovan et al., 2004). Open and frequent parent-child communication has been found to be a protective factor of alcohol use (Kelly, Comello, & Hunn, 2002). Regular and consistent parental monitoring predicts less subsequent onset of alcohol and other drug use (Donovan, 2004), whereas less parental monitoring predicts increases in early alcohol use among youth (Pettit, Laird, Dodge, Bates, & Criss, 2001). Alcohol use by peers, perceptions of peer use, and perceptions of peer influence to use all significantly increase the likelihood of early alcohol use initiation (Donovan, 2004). Hawkins and colleagues (1997) found that those children who had alcohol-using peers at ages 10 to 11 were more likely to initiate early alcohol use and to misuse alcohol when they were older than were children who did not have alcohol-using peers.

In addition to peer and parent factors, access to alcohol, offers of alcohol, and normative expectations help to create an environment that is either conducive to or prohibitive of alcohol use. Among adolescents, intrapersonal factors such as normative beliefs and normative estimates (Komro et al., 2001) are important predictors of intentions touse alcohol and alcohol use. Self-efficacy has also been associated with drinking behavior, and positive expectations or expectancies about drinking may also predispose a child to early use (Donovan, 2004; Hipwell et al., 2005). Adolescents are more likely to use alcohol at earlier ages when they have fewer negative expectations concerning alcohol use (Hipwell et al., 2005).

Although much is known about the risk factors for early adolescent alcohol use, more research is needed to determine which factors are the most salient and modifiable before adolescents begin using alcohol and which factors are amenable to change after use has been initiated. In addition, few studies have used multiethnic, urban, large samples to examine differences in these risk and protective factors at the beginning of early adolescence (sixth grade). As such, comprehensive and robust models, which are multifactorial and include potential targets for prevention interventions, are needed to determine the most potent and predictive factors associated with early onset to guide the development of early preventive interventions. This study seeks to determine how early users of alcohol differ from those adolescents who have not yet initiated alcohol use. In addition, this study provides information about the strongest risk factors for alcohol use to target for each of these two groups.

Project Northland Chicago (PNC) is an alcohol use prevention program involving more than 4,000 sixth through eighth grade students in inner-city Chicago. PNC is an adaptation of Project Northland, which was developed and evaluated in rural northern Minnesota (Komro, Perry, Veblen-Mortenson, et al., 2004). Significant outcomes in terms of reduced alcohol use onset and prevalence were noted among young adolescents in the original Project Northland trial (Perry et al., 1996). However, among the 37% of students who reported having ever had a drink of alcohol at baseline in this study, when they were sixth grade students in 1991, the project was less effective (Perry et al., 1996). In addition, those baseline users of alcohol had a higher prevalence of alcohol use than did baseline nonusers throughout the project’s duration (Perry et al., 1996). Thus, it seemed as if Project Northland may have been too late for those students who were already using alcohol at the beginning of sixth grade.

These findings suggest that primary prevention of alcohol use might need to occur prior to sixth grade, while students are in their “tween-age” years, between childhood and early adolescence, about third through fifth grades. It seems particularly important to examine how sixth grade alcohol users (early users) are different from sixth grade nonusers but to do so with a more contemporary, more urban, and larger sample of students. The current study examines the risk and protective factors associated with alcohol use behavior and intentions among baseline users and nonusers of alcohol from PNC and differences in these risk and protective factors that distinguish the two groups. This examination takes advantage of the more recent, larger, and more urban sample available with PNC to create more robust models that explain alcohol use behavior and intentions in this age group to provide guidance for early alcohol use prevention efforts. This study addresses the following primary question:

Which demographic, socioenvironmental, intrapersonal, and behavioral factors most distinguish users from nonusers?

Based on previous research, social cognitive theory, and the theory of triadic influence, it is hypothesized that sixth grade (early) alcohol users will be at significantly greater socioenvironmental, intrapersonal, and behavioral risk than nonusers, as evidenced by differences in the “risk profiles” of these two groups. In addition, this study explores which demographic, socioenvironmental, intrapersonal, and behavioral factors are associated with alcohol use behavior and intentions for sixth grade alcohol users and nonusers. It also identifies which factors are most potent or most strongly associated with alcohol use behavior and intentions in these two groups of young adolescents (i.e., How much of the variance in early alcohol use behavior and intentions is accounted for by these factors?). Although it is expected that a different set of risk factors will be correlated with alcohol behavior and intentions in each of these two groups (early users and nonusers) and that the importance of these risk factors will also vary by group, formal hypotheses have not been generated a priori. It is imperative that we understand which risk factors are the most influential in developing alcohol use behaviors and intentions, especially among early users of alcohol, to intervene to prevent early alcohol use among tweens. The knowledge gained in this study will provide information about useful intervention points that can be incorporated into universal intervention programs, particularly early intervention programs in elementary school, that will help to more effectively reduce the prevalence of preadolescent alcohol use (Donovan et al., 2004).

Because the scales in Table 1 were standardized prior to analysis, the magnitudes of the differences between users and nonusers on each of the scales can be compared to identify the relatively most potent risk factors. Thus, among the behavioral, socioenvironmental, and intrapersonal risk factors, users were much more likely than nonusers to engage in delinquent and violent behaviors and to have lower self-efficacy, to have positive outcome expectations and expectancies concerning alcohol use, to have greater access to alcohol, to have higher normative estimates of alcohol use, and to have a greater number of friends using alcohol, as indicated by large differences in the standardized scale scores. These risk factors strongly differentiate users from nonusers in this sample.

Nearly all of the behavioral, intrapersonal, and socioenvironmental risk factors were significantly related to alcohol use behavior and intentions for students who were users and nonusers of alcohol at baseline. Table 2 presents the results of the analyses for baseline nonusers, whereas Table 3 presents the results for baseline users.

Among the baseline nonusers (Table 2, single regression models), being White increased the risk and being Asian decreased the risk of alcohol use behavior and intentions. Being male, living in a non-two-parent family, speaking only English at home, and being older were significantly associated with alcohol use behavior and intentions. All of the behavioral, intrapersonal, and socioenvironmental factors (except time spent after school with adult supervision) were significantly associated with increased alcohol use behavior and intentions. The only association that was not in the expected direction was that greater time spent outside of school in sports and being physically active was associated with greater alcohol use behavior and intentions. Among baseline users (Table 3, single regression models), a mostly similar pattern emerged. Being White, however, decreased the risk and being Native American increased the risk of alcohol use behavior and intentions. Being male and being older were also associated with greater alcohol use behavior and intentions. Again, all behavioral, intrapersonal, and socioenvironmental factors were associated with alcohol use behavior and intentions in the expected direction. Among time variables, less time spent doing homework and more time spent without adults were associated with alcohol use intentions and behavior. Thus, the factors selected in our model are important potential mediators of the intervention because nearly all are associated with increased risk of alcohol use behavior and intentions for young adolescents, including both users and nonusers. However, the estimates in the single regression models for the user group were larger than those of nonusers, suggesting stronger associations among users between these factors and alcohol use behavior and intentions.

Among baseline nonusers (Table 2, multiple regression model), 15 factors were most strongly associated with alcohol use intentions and behavior (p < .15), with 12 significant factors (p < .05). There were no significant demographic factors in this adjusted model. The significant risk factors included having ever smoked, past-month marijuana use, owning alcohol items, wearing alcohol items, engaging in violent behavior, low self-efficacy, outcome expectancies more favorable to alcohol, outcome expectations more favorable to alcohol, alcohol offers, lower parent-child communication, and higher normative estimates. Attending religious activities was a significant protective factor. All factors were in the hypothesized direction. The 15 factors accounted for 35.1% of the variance in alcohol use behavior and intentions between students.

The risk factors that were explored in this study were nearly all significantly associated with sixth grade alcohol use behavior and intentions for both users and nonusers when examining each separate relationship. Thus, at first glimpse, all of these risk factors would be important to consider as the focus for creating intervention objectives for the primary prevention of alcohol use with young teens, regardless of their drinking status as a tween. This is especially important because many of these risk factors, particularly the socioenvironmental and intrapersonal factors, have been amenable to intervention (Perry, 1999). The relationships between the risk factors and alcohol use behavior and intentions were stronger for users than for nonusers, with higher estimates in the models. This is likely because of greater variability and range in the outcome measure because users exhibited alcohol use intentions and behavior, whereas nonusers (by definition) had only intentions to use alcohol. Higher scores on intentions to use alcohol are strong predictors of subsequent alcohol use, so those nonusers with high intentions scores are at greater risk to begin to drink (Marcoux & Shope, 1997). Still, the single regression models provide only limited guidance for intervention design because it is important to select the most potent and modifiable risk factors to create powerful yet efficient prevention programs (Perry, 1999).

The multiple regression models narrowed the list of most potent risk factors considerably, yet each model still accounted for a substantial percentage of the individual variance in alcohol use behavior and intentions—35% for nonusers and 56% for users—suggesting that these models were robust, notably so for the users. For the baseline nonusers, among the behavioral variables the powerful associations with other drug use, violence, and less attendance at religious activities have been noted elsewhere (Grant & Dawson, 1997). It is noteworthy that owning or collecting and being willing to wear or use items that have the name of an alcohol beverage on them were significantly associated with alcohol use behavior and intentions. This is similar to what Pierce and colleagues (1998) have noted with tobacco use and suggests that owning or even being willing to wear one of these items could increase susceptibility to future alcohol use among nonusers. It appears that efforts to restrict alcohol beverage promotional items may be needed, in the same way that the Master Settlement Agreement banned such items for cigarette manufacturers because they were seen as being too youth oriented (Capehart, 2001). Among the intrapersonal factors, nonusers with higher alcohol use behavior and intentions scores were more likely to have low self-efficacy and more positive alcohol outcome expectations and expectancies. Thus, not having the confidence to be able to refuse alcohol, not perceiving negative consequences of alcohol use, and not valuing the potential consequences of alcohol use all appear to be critical. These are important to note because these risk factors are amenable to intervention, as was found in Project Northland, in which self-efficacy and outcome expectancies (i.e., functional meanings) were both modified as a result of the intervention (Perry et al., 1996). Finally, for nonusers, among the socioenvironmental factors, reporting having had offers to drink, having less frequent parent-child communication, and perceiving that more young people drink are all potent risk factors for alcohol use behavior and intentions, suggesting greater peer influence to use and less positive parental influence. Appropriate and amenable targets for intervention might then be to correct normative estimates of drinking if they are too high (Agostinelli & Grube, 2005), to structure opportunities for greater parent-child communication (Kosterman, Hawkins, Haggerty, Spoth, & Redmond, 2001), to increase monitoring of those who might offer alcohol to youth, and to provide skills concerning alcohol refusal (Perry et al., 1996). To a large extent, many of these risk factors have formed the basis for successful prevention programs with young teens (Botvin, Baker, Dusenbury, Botvin, & Diaz, 1995), but these analyses among the nonusers point to those factors that can be used to strengthen the focus of our programs because they highlight the particular factors associated with the greatest risk for subsequent early onset of alcohol use.

Among baseline users, other related behaviors, including tobacco use, marijuana use, violence, and delinquency, predominate in the multiple regression model. This strongly points to the early covariation of these behaviors and the need to intervene with these youth well before sixth grade. There is ample evidence that children who have conduct disorders or engage in deviant behaviors during early and middle childhood are more likely to continue those behaviors into adolescence, including alcohol use (Caspi, Moffitt, Newman, & Silva, 1996; Fergusson et al., 2005; Hawkins et al., 1997). Thus, early intervention, either through selected or universal programs, is needed to alter the developmental trajectories of these related behaviors during childhood, particularly before these trajectories become less mutable to change in adolescence. Among baseline users, the most potent intrapersonal and socioenvironmental factors included low self-efficacy and more positive expectations of the consequences of drinking, perceptions that more peers drink alcohol, and perceptions that those who drink experience more positive outcomes. These are consistent with others’ research that suggests that children as young as fourth grade who have positive expectancies around alcohol use are more likely to be early users (Hipwell et al., 2005) and that associating with deviant peers and having poor self-regulatory skills during the tween-age years increase the risk of early alcohol use (National Institute on Alcohol Abuse and Alcoholism, Public Health Service, & National Institutes of Health, 2005). Thus, it seems critical to intervene earlier than sixth grade for the primary prevention of alcohol use, particularly for higher risk students. However, in PNC, 17% of the students were already users at the beginning of sixth grade, about 1 in 6 youth. In PN, 37% of the sample, about 3 in 8 youth, had “ever” used alcohol and were less responsive to the intervention (Perry et al., 1996). Thus, the “users” are a substantial proportion of the sixth grade population. It may be important, then, to design a primary prevention program for tweens, prior to sixth grade, that focuses on specific alcohol-related risk factors, such as alcohol use expectancies, expectations, normative estimates, and normative expectations, found to be important in these analyses but that also focuses on the important developmental tasks of that age group—academic achievement, appropriate conduct, and prosocial peer relationships. This approach, intervening at earlier ages, would allow for universal messages about alcohol use and yet also provide support for high-risk students who may be developmentally lagging.

There were some unusual findings that should be noted. Among users, feeling depressed was inversely related to alcohol use. This has not been noted before, and others have found a positive relationship between depression and alcohol use (Donovan et al., 2004) or no relationship (Greenblatt, 2000). Thus, this finding is likely because of the question itself, which was a single item asking the students if they felt depressed or sad in the past month and not specifically addressing depressive symptoms. A second unexpected finding was that alcohol users were more likely than nonusers to spend time outside of school being physically active. This included time spent in team sports, with the drill team, biking, walking, or skateboarding. Thus, it may be that the time is not spent under adult supervision but is spent with peers (e.g., skateboarding) who could encourage alcohol use or other related activities in which users may frequently engage. Because peer alcohol use is also much higher among users, it may be that users associate with other users and the potential for access to alcohol increases. Finally, the lack of significant demographic factors in the multiple regression models suggests that with this urban, inner-city population, these factors are less important than the behavioral, intrapersonal, and socioenvironmental factors and that alcohol use is problematic across genders, races/ethnicities, and socioeconomic levels.

This study of users and nonusers of alcohol was strengthened by its large sample size and multiethnic population and by the recentness of the data. The study is limited by being cross-sectional, so that causal inferences cannot be made in the associations presented. Clearly, there is need to follow-up on these analyses as the students mature. Another limitation of this study is the dependent variable: alcohol behaviors and intentions. For sixth grade users of alcohol, the dependent measure included both alcohol behaviors and intentions, whereas for nonusers the dependent measure included only alcohol intentions because, by definition, they did not participate in any current or past alcohol use behaviors. Although there is a difference in the range of the dependent variable for each group, it is one way to explore associations among the behavioral, intrapersonal, and socioenvironmental factors and overall alcohol behaviors and intentions within each of these groups. This is especially true because the alpha coefficient for the entire scale is .82. As noted, intentions to drink are strongly related to future behaviors.

Future research is needed to explore the cross-sectional associations among the behavioral, intrapersonal, and socioenvironmental factors with alcohol intentions alone. In addition, longitudinal research that explores the associations of earlier behavioral, intrapersonal, and socioenvironmental factors with later behaviors is needed. This longitudinal research will allow for the creation of the groups of users and nonusers at earlier ages and for the exploration of how the behavioral, intrapersonal, and socioenvironm ental factors influence alcohol behavior in each group.