We found evidence for two types of underage problem drinkers: risky problem drinkers and regular problem drinkers. Both types of problem drinkers are at an increased risk of experiencing problems from drinking such as having a headache or hangover, passing out, and being unable to remember what happened as well as less common problems like driving after drinking, being cited or arrested for drinking, missing school, breaking or damaging something, being punished by parents or being warned by friends about drinking. Based on these response patterns detected by latent class analysis (LCA), an estimated 57% of underage drinkers are classified as problem drinkers. If a priori we required regular drinking to be present to indicate problem drinking as in adult populations, only an estimated 27% of adolescents (Class 3) would have been classified as problem drinkers; failing to identify approximately half of underage problem drinkers in our sample. The three class model of underage problem drinking suggests that problem drinking among youth is most strongly characterized by heavy drinking behaviors (i.e. binge drinking and getting drunk) regardless of regularity, lending support to the idea that the majority of alcohol-related harm can be attributed to quantity of drinking among adolescents. This is consistent with the findings of Fergusson et al. (1995)
in which the class that conformed most closely to the general conceptual definition of alcohol abuse was characterized by heavy drinking (71% reported drinking at least 90 ml of pure alcohol on a typical occasion and 85% reported drinking at least 180 ml of pure alcohol on one occasion in the last 3 months). Approximately half of the members in this class reported drinking at least once per week, also consistent with our estimated prevalence of 61% in Class 3 reporting drinking at least 6 days in the past month.
It is also worth pointing out that for a class of underage drinkers in which only approximately 35% have binged in the past 2 weeks and half have gotten drunk at least 2−3 days a month during the past year (Class 2), alcohol-related problems are relatively common. In fact, despite that fact that underage drinkers in Class 3 are almost three times more likely to binge and twice as likely to get drunk at least 2−3 days a month then underage drinkers in Class 2, the mean number of alcohol-related problems between these two groups is practically the same (mean = 1.8 for Class 2 and 2.3 for Class 3). This suggests that even among a group with a moderate prevalence of heavy drinking, the risk of alcohol-related problems should not be ignored. It is interesting that despite the same average number of alcohol-related problems between the two classes, underage drinkers in Class 3 are almost five times more likely to drive after drinking (6.4% versus 34.2%); a consequence perhaps of more regular drinking.
The estimated prevalence of problem drinking in the New Zealand sample (Fergusson et al., 1995
) was approximately 10%; a rate much lower than even our most problematic drinking class (Class 3). However, the New Zealand rate was not restricted to current drinkers. Given that 75% of the New Zealand sample reported consuming alcohol during the past 3 months, we can roughly estimate that the rate of problem drinking among current drinkers in the New Zealand sample is approximately 13% (=0.10/0.75); a rate still much lower than the rate in our sample. However, whereas the New Zealand sample surveyed 16 year olds in 1993, the EUDL sample spans ages 16−20 with data collected between 1999 and 2004. We know based on results from the 2003 National Household Survey on Drug Use and Health that the highest prevalence of heavy drinking is among those aged 18−25, with the peak rate of both measures occurring at age 21 (SAMHSA, 2004
). There is also evidence that the number of college students reporting heavy drinking and drunkenness has increased from 1993 to 1999 (Wechsler et al., 2000
). Both of these factors offer possible explanations for the much higher rates of problem drinking in our sample.
In 2000, the U.S. Surgeon General and the U.S. Department of Health and Human Services recognized binge drinking among college students as a major public health problem (USDHHS, 2000
). Alarmingly, only a mere one-third of our sample had a low probability (<11%) of reporting heavy drinking behaviors (Class 1). In our sample, there was no difference in risk for being a risky problem drinker for late adolescents (ages 16−17) and young adults (ages 18−20) suggesting that at least some of our late adolescent drinkers are manifesting risky drinking behavior profiles at the same rate as young adults. We did find evidence that young adulthood confers an increased risk of being a more regular drinker (Class 3) underscoring the need to recognize that patterns of risky drinking can develop in late adolescence and the window of opportunity for preventing more problematic drinking, i.e. regular drinking, might occur earlier than previously thought.
Similar to others, we found that physical problems from drinking were more prominent than social consequences among underage problem drinkers (Ellickson et al., 1996
). The physical problems surveyed in this study were acute consequences, e.g. passing out, being unable to remember what happened and having a headache or hangover, whereas social consequences may be long-term manifestations of ongoing drinking that causes concerns by friends, parents or law enforcement. In addition, risky drinking is more likely to occur on weekends among this age group and so consequences such as missing school are less probable. Further, if heavy drinking is occurring in the context of college campuses, then social acceptability of drinking as well as less monitoring by parents and law enforcement may make social consequences less likely. The social consequences assessed in this study also fail to include some of the more common social problems among this age group such as fighting with friends, losing a boyfriend/girlfriend or risky sexual behavior which may be reflected in the lower rates.
The study findings also include an assessment of variation in the risk of being a problem drinker based on peer and parental influences. One of the strongest influences on the risk of being a problem drinker was the belief that most friends drink weekly, even after adjustment for other important influences like demographics, current cigarette use and parental consequences for drinking. This result is also consistent with Fergusson et al. (1995)
who found that affiliation with substance using peers was one of only three factors predictive of problem drinking after adjustment for social, family and individual factors. Our findings also provide support for the hypothesis that perceptions of friends drinking behavior is associated with underage drinking behavior and is consistent with prior findings that perceptions of friend's use is a better predictor than actual use (Wilks et al., 1989
; Iannotti and Bush, 1992
). It also fits well within the framework of cognitive development theory (Inhelder and Piaget, 1958
), which suggests that the actual environment is not as important as one's perception or understanding of the environment in shaping behavior. Additionally, others have found that youth tend to overestimate drug use by peers, thereby providing support for a greater impact of perceived use over actual use. We also found that beliefs that most peers in the community drink had little influence once beliefs about friends drinking was included in the models suggesting a greater influence of the immediate social network of friends over normative expectations in the community, as previously reported by others (Baer et al., 1991
; Barnes et al., 1994
). Individual factors such as gender, age, early onset drinking and other drug use signaled an increased risk of problem drinking but the magnitudes of the effects were not as great as they were for peer factors with the exception of current marijuana use. Current marijuana users were ten times more likely to be regular drinkers and four times more likely to be risky drinkers relative to non-problem drinkers. Marijuana use was also a strong discriminator of risky and regular problem drinking. This finding is consistent with other studies supporting the stepping stone hypothesis that alcohol use signals an increased risk of marijuana initiation (Wagner and Anthony, 2002
We were also interested in the relative influence of perceived parental consequences once perceptions of friend's and peer's drinking was controlled in the models. We found that the belief that parents would yell or punish you if they caught you drinking had a significant protective effect on regular drinking, but was no longer influential once individual and peer factors were controlled in analyses. The protective effect for regular drinking but not risky drinking in unadjusted models is consistent with some studies that have found that parents have greater influence over more serious drug use (Kandel, 1985
; Kandel and Andrews, 1987
). The failure of this result to be maintained in the presence of individual factors and peer influences support prior findings that, while family bonding is important early, peers have greatest influence later (Coleman, 1980
; Guo et al., 2002
Several limitations should be noted. There are, of course, limitations inherent in the study methodology. We acknowledge that our inferences are only valid for the population from which we sampled. Although block grants were awarded in all 50 states, discretionary grants were awarded on a competitive basis to a subset of states. In addition, as is typical of telephone surveys, nonwhites and lower SES individuals were underrep-resented in the sample. Older adolescents (i.e. 19 and 20 year olds) are harder to reach in telephone surveys using random digit dialing (RDD) and were also underrepresented in our sample. Nonetheless, despite the lack of a nationally representative sample, a strength of our sample is its size and geographic diversity (~11,000 respondents from 212 communities in 20 states).
We also acknowledge the limitations inherent in the non-randomized design. As mentioned previously, states established the criteria for deciding which communities would receive funding in the state under the discretionary grant program which could bias our results. We attempted to minimize this bias by choosing comparison communities that, as a group, were as similar as possible to the group of intervention communities. As demonstrated by Preisser et al. (2003)
, in the absence of randomization, the use of propensity scores to match EUDL communities resulted in intervention and comparison communities being well-balanced on measured community-level characteristics, including population size, median income, number of liquor law arrests per 100,000 population, and size of the college population.
A different method of classifying drinking behaviors and alcohol-related problems could have resulted in a somewhat different latent class structure. For example, none of the drinking behavior questions were designed to assess usual patterns of behavior and could result in an over-estimation of problem drinkers. The reference period for drinking behaviors and alcohol-related problems also lacks consistency with some questions asking about behaviors and experiences occurring over the past 2 weeks, past month and past year. The lack of specificity regarding the duration of an “occasion” could result in its meaning different things for different respondents which could also compromise the results. In addition, the alcohol-related problems assessed in this survey ranged from fairly common problems such as experiencing headaches or hangovers after drinking to low prevalence problems such as driving after drinking and getting arrested for drinking. The inclusion of different types of problems more or less severe may have resulted in different findings and may limit the generalizability of our results.
Based on data from the YRBSS, an estimated 12.1% of students nationwide reported driving after drinking during the past 30 days. The rate in our total sample including non-current drinkers was 5% and the rate among current drinkers was 12.1%. Only 12% of our sample has never ridden a motor vehicle. The difference in our results is likely due to a difference in question wording. The YRBSS asks “During the past 30 days, how many times did you drive a car or other vehicle when you had been drinking alcohol?” while we say “During the last 30 days, how many times (if any) have you driven after drinking two or more drinks in an hour or less?” Our more narrow definition may have resulted in lower rates of driving after drinking.
Finally, we recognize that the cross-sectional nature of the EUDL study precludes us from determining whether the resultant classes represent distinct subtypes of underage problem drinkers or possibly youths in different stages of problem drinking on the road to alcohol dependence. The cross-sectional design also does not allow us to answer important questions about whether youth who like to drink seek out friends who drink (social selection) or whether perceptions of friend's drinking is having a direct impact on behavior via social pressure (social conformity). To answer this question, future studies would require a longitudinal study of youth prior to onset of alcohol use and would need to collect data from their social network of friends and peers.
In conclusion, within the collection of prior studies on underage problem drinking, most have not had the benefit of a large, geographically diverse community sample of underage drinkers. The present study has attempted to shed light on the nature of underage problem drinking by modeling drinking patterns rather than relying on unidimensional measures or clinical criteria. As such, it provides a better understanding of the heterogeneous nature of underage problem drinking that result in negative consequences, namely risky problem drinking and regular problem drinking. Our study indicates that even for a group of underage drinkers with a moderate prevalence of heavy drinking behavior alcohol-related problems is a significant concern. The results of this study suggest that patterns of risky drinking can develop in late adolescence and the window of opportunity for preventing regular drinking may be narrower than previously thought. In addition, this study underscores the strong association between underage problem drinking and perceptions regarding friends drinking behaviors as well as illicit drug use. As such, these findings may set the stage for longitudinal studies which can probe even further the nature and emergence of problem drinking as well as which underage drinkers are at higher risk of becoming problem drinkers, in order to provide insight into prevention and early intervention.