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. Author manuscript; available in PMC: 2009 Jan 1.
Published in final edited form as: Addict Behav. 2007 May 3;33(1):134–142. doi: 10.1016/j.addbeh.2007.04.027

Alcohol in Emerging Adulthood: 7-Year Study of Problem and Dependent Drinkers

Kevin L Delucchi a,*, Helen Matzger a,b, Constance Weisner a,c
PMCID: PMC2100394  NIHMSID: NIHMS34626  PMID: 17537582

Abstract

Objective

This study examined the level, changes and predictors of alcohol consumption and binge drinking over a seven year period among young adults (18-25 years) who met criteria for problem drinking.

Method

Interviews with 270 18- to 25-years old problem and dependent drinkers from representative public and private substance use treatment programs and the general population, were conducted after 1, 3, 5, and 7 years. Measures included demographic characteristics, severity measures, and both formal and informal influences on drinking.

Results

Overall alcohol consumption declined over time but leveled off around 24 years of age. Being male, not attending AA over time, as well as more baseline dependence symptoms and greater ASI alcohol and legal severity were associated with greater consumption and binge drinking. In addition greater levels of binge drinking were associated with less education, earlier age of first use, and a larger social network of heavy drinkers.

In conclusion, more attention should be paid to heavy drinking among young adults and to the factors that influence their drinking patterns.

Keywords: Alcohol, emerging adulthood, problem drinking, longitudinal data

1. Introduction

Alcohol consumption among young people, including binge drinking, is a serious public health concern, and the prevalence of heavy drinking among 18 to 24 year olds has increased over the last decade (Chen et al., 2004). Drinking in young adults is influenced by several contributing factors, including genetic influences, ethnicity, family alcoholism, “role transition” such as marriage, health-related problems, suicide risk, and neurocognitive effects up to eight years later (e.g., (Brown & Tapert, 2004; Chassin et al., 2004; Hopfer et al., 2005; Paschall et al., 2005; Pletcher et al., 2005). Young adults, however, are more likely to have trajectories of improvement (e.g., (Fillmore, 1987).

Less well-studied are those emerging adults who already have a drinking problem. In this work we modeled both volume of alcohol and binge drinking which, while related, may provide a different perspective on behavior (Rehm, 1998). This study has three goals: (1) To describe the amount and time course of alcohol consumption and binge drinking in this sample of heavy drinking emerging adults; (2) To estimate and test a predictive model of consumption over seven years; and, (3) To compare that model of alcohol consumption to a parallel model of the frequency of binge drinking.

2. Methods

We selected all participants 18 to 25 years of age (n=265) from a larger study. The full sample was produced from two sampling procedures; details can be found in Weisner and Matzger (2002) and Weisner, Matzger, Schmidt, & Tam (2002). In-person interviews were conducted with individuals entering a county’s public and private chemical dependency programs (the treatment sample) and with problem and dependent drinkers from the general county population (general population sample) who had not received treatment in the prior year. The treatment sample (n = 926 full sample, n = 88 age 25 or younger) included consecutive admissions in the ten public and private programs in the county. The general population sample of dependent and problem drinkers not entering treatment (n = 672 full sample, n = 177 age 25 or younger) was collected using random digit dialing methods in the same county. The behaviors modeled were the base-10 log total number of drinks taken in the year prior to each assessment—the total volume of alcohol consumed—and the frequency of binge drinking, defined by the number of days in the past year when the respondent consumed three or more drinks if they were a woman and five or more if a man. Variables used are displayed as part of Table 2. Four latent variable mixed-effects growth models were estimated and tested. Two models used log-alcohol volume as the dependent variable; one without interaction terms and one with. The other two models were parallel to the first two but used frequency of binge drinking as the outcome. Rates of follow-up for this sub-sample were 86%, 83%, 81%, and 78% in Years 1, 3, 5 and 7 respectively.

Table 2.

Estimates of effects, standard errors and p-values for log-volume alcohol consumed without interaction terms and p-values for model with interaction terms.

Effect Volume Measure With Interactions
Estimate Standard Error p-value p-value
Intercept 1.660 0.3083 < 0.001 < 0.001
Time – linear −0.111 0.0451 0.014 0.006
Time-quadratic 0.0104 0.0053 0.049 0.079
Demographics
Female −0.228 0.0607 < 0.001 0.051
Ethnicity
 Black v. White −0.189 0.1051 0.073 0.068
 Hispanic v. White −0.160 0.0844 0.060 0.044
 Other v. White −0.13 0.0930 0.149 0.121
Age 0.013 0.0153 0.396 0.449
Marital Status
 Formerly Married v. Never −0.088 0.1081 0.414 0.404
 Married v. Never −0.097 0.0483 0.044 0.054
Years of School −0.028 0.0207 0.176 0.169
Income 0.007 0.0057 0.220 0.234
General Pop. Sample 0.522 0.0756 < 0.001 < 0.001
DSM-IV Dependent 0.243 0.0725 < 0.001 0.001
No Family Alcohol Prob. −0.079 0.0685 0.251 0.313
Age of First Use −0.023 0.0110 0.038 0.011
Severity
N Dependence Symptoms 0.178 0.0125 < 0.001 < 0.001
N Alcohol-Related Events 0.079 0.0303 0.009 0.825
ASI Alcohol Severity 1.572 0.1847 < 0.001 < 0.001
ASI Psychiatric Severity −0.027 0.1431 0.850 0.829
ASI Medical Severity −0.031 0.0911 0.736 0.988
ASI Drug Severity 0.434 0.3946 0.271 0.286
ASI Social Severity −0.056 0.1343 0.675 0.719
ASI Legal Severity 0.4704 0.1501 0.002 0.002
ASI Employment Severity −0.100 0.0658 0.129 0.130
Formal Influences
Treatment prior year −0.193 0.0731 0.009 0.002
Formal Contacts −0.049 0.0292 0.097 0.085
Informal Influences
No AA meetings 0.3526 0.0627 < 0.001 0.117
Size of Drinking/Drug Using Social Network 0.003 0.0028 0.258 0.198
Suggestions to Get Help −0.069 0.0568 0.231 0.199
Time by Gender 0.351
Time by Sample 0.066
Time by Age of First Use 0.141
Time by N Consequences 0.029
Time by AA Attendance 0.009
BIC 2130.4 2144.5
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BIC - Bayesian Information Criterion

P-values < 0.05 in bold font

3. Results

Baseline descriptors of the young adults in the sample are shown in Table 1, broken down by their alcohol dependence status, a potentially confounding variable.

Table 1.

Percentages, means, and standard deviations of baseline demographic and alcohol-related measures of the young adult respondents by dependence status.

Problem Drinkers (N=196) Alcohol Dependent (n=69) p-value
Demographic Characteristics
Ethnicity (%)
 White 70.9 51.5 0.017
 Black 7.6 14.7
 Hispanic 13.3 16.2
 Other 8.2 17.6
Education (%)
 < High School 17.4 30.4 0.126
 High School 57.1 53.6
Graduate
 > High School 25.5 16.0
Income <$25,000(%) 50.5 50.0 0.940
Male (%) 59.7 65.2 0.418
Never Married (%) 81.1 79.7 0.798
Went to AA (%) 29.6 50.7 0.002
No suggestions tx (%) 92.9 78.6 0.001
Problem Drinkers (N=196) Alcohol Dependent (n=69) p-value
Mean Std Dev Mean Std Dev
Age of respondent 21.08 2.26 21.27 2.58 0.563
N drinks, yearly 897.34 1168.83 2180.37 1827.44 < 0.001
Log(10) of N drinks, yearly 2.53 0.72 3.09 0.57 < 0.001
Per year 5-12+ drinks 4.80 2.28 3.06 2.11 <0.001
Per year 5+(men) 3+ women 90.30 131.03 214.94 182.52 <0.001
Age of regular use 18.74 3.10 17.20 3.45 0.001
Problematic drinking measure 2.35 1.72 5.07 2.28 < 0.001
Alcohol Severity 0.12 0.11 0.39 0.23 <0.001
Alcohol Related Events 0.36 0.81 1.23 1.24 < 0.001
Social Severity, etc. 0.17 0.23 0.31 0.27 <0.001
Number of using people 4.40 5.91 6.12 10.51 0.097
ASI-Psychiatric 0.20 0.21 0.38 0.23 < 0.001
ASI-medical 0.15 0.27 0.17 0.27 0.621
ASI-all Drug 0.05 0.09 0.11 0.12 0.001
ASI-legal 0.08 0.16 0.13 0.20 < 0.001
ASI-employment 0.58 0.34 0.64 0.33 0.037
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Consumption

Over the seven years, mean consumption declined significantly (p = .014). While the frequency of binge drinking also declined, the change did not reach statistical significance (p = .109). The log-transformed means of the two measures of drinking are graphed in Figure 1. The median (raw scale) number of drinks per year was 564, 290, 190, 173, and 139 over the five assessments. Similarly, the median number of binge occasions dropped over time; 48, 29, 18, 16, and 11. Given the decline in drinking, it was not unexpected to find the number of participants experiencing alcohol-related problems declining over time from 93 (35%) reporting having had an event in the prior year down to only 24 (11%) experiencing a negative alcohol-related event in Year 7. Not all study participants drank alcohol in all years. Out of the 265 respondents, 121 (45.7%) reported not drinking in at least one of the years prior to an assessment while 73 (27.5%) did not drink alcohol in the year leading up to an assessment which followed one wherein they reported no consumption in the prior year. Table 2 displays the estimates, the standard errors and associated p-values for the statistical model of log-transformed alcohol volume consumed. Several measures were significantly predictive over the seven years. As noted and reflected in Figure 1, drinking declined over time but leveled off around Year 3 when the mean age was 24 (i.e., significant time and quadratic-time effects).

Figure 1.

Figure 1

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Mean yearly volume of alcohol consumed (n drinks) and frequency of drinking 3+ (women) or 5+ (men) drinks on a single occasion—both on the base-10 log scale.

Note: Scales for two measures are not the same; 5+3+ Occasions is in log-day and N Yearly drinks is in log-drinks.

Binge Drinking

When the same model was re-estimated with the measure of binge drinking as the dependent variable, the estimates were all in the same direction, with one exception, and largely similar in value. Table 3 displays the estimates, the standard errors and associated p-values for this model which did not fit the data as well as the model for log-volume (BIC volume = 2130.4 vs. 3315.2). Change in bingeing over time, however, was no longer significant (p = .109). The time-varying index of having had alcohol treatment in the prior year was not significant in this model with a noticeable change in the p-value from p = .009 in modeling volume to p = .944 here. Also, the contrast between married and never married respondents was no longer significant (p = .184). Years of schooling, however, was significant in this model (p = .002) with a negative sign indicating more education was related to less binge drinking. The exception to the direction of effects was found for gender. The estimate (.322, p = .101) indicates that, when statistically controlling for all of the other measures, women binge more than men. The means at each assessment are greater for the men, and attempts to pinpoint a single or small set of covariates responsible for this reversal failed, suggesting a complex relationship. Examination of the distributions of the binge measure did not vary markedly between genders; the distributions of the residuals were reasonable and the proportions indicating they did not binge at all did not differ between genders (not shown).

Table 3.

Estimates of effects, standard errors and p-values for binge drinking without interaction terms and p-values for model with interaction terms.

Effect Binge Measure With Interactions
Estimate Standard Error p-value p-value
Intercept 1.909 0.6348 0.003 0.001
Time – linear −0.160 0.1001 0.109 0.025
Time-quadratic 0.0111 0.0119 0.351 0.319
Demographics
Female 0.322 0.1237 0.010 0.007
Ethnicity
 Black v. White −0.389 0.2258 0.086 0.086
 Hispanic v. White −0.304 0.1700 0.076 0.070
 Other v. White −0.121 0.1921 0.528 0.486
Age 0.053 0.0314 0.093 0.099
Marital Status
 Formerly Married v. Never −0.153 0.2439 0.530 0.507
 Married v. Never −0.142 0.1068 0.184 0.265
Years of School −0.129 0.0415 0.002 0.002
Income 0.0125 0.0122 0.309 0.334
General Pop. Sample 0.769 0.1618 < 0.001 < 0.001
DSM-IV Dependent 0.435 0.1484 0.004 0.005
No Family Alcohol Prob. −0.099 0.1385 0.477 0.558
Age of First Use −0.084 0.0226 < 0.001 < 0.001
Severity
N Dependence Symptoms 0.337 0.0269 < 0.001 < 0.001
N Alcohol-Related Events 0.175 0.0649 0.007 0.867
ASI Alcohol Severity 3.193 0.3985 < 0.001 < 0.001
ASI Psychiatric Severity −0.208 0.3113 0.503 0.553
ASI Medical Severity 0.011 0.2008 0.954 0.722
ASI Drug Severity 1.102 0.8683 0.205 0.238
ASI Social Severity −0.388 0.2953 0.189 0.194
ASI Legal Severity 0.750 0.3249 0.021 0.019
ASI Employment Severity −0.243 0.1500 0.106 0.133
Formal Influences
Treatment prior year 0.011 0.1613 0.944 0.513
Formal Contacts −0.088 0.0642 0.168 0.155
Informal Influences
No AA meetings 0.411 0.1365 0.003 0.231
Size of Drinking/Drug Using Social Network 0.013 0.0060 0.034 0.025
Suggestions to Get Help 0.079 0.12600 0.532 0.681
Time by Gender 0.217
Time by Sample 0.056
Time by Age of First Use 0.045
Time by N Consequences 0.015
Time by AA Attendance 0.331
BIC 3315.2 3329.6
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BIC - Bayesian Information Criterion

P-values < 0.05 in bold font

Change Over Time

To test for differences in the change over time, the models for both alcohol volume and binge drinking were re-estimated with the addition of interaction terms between the year of assessment (i.e., time) and five significant predictors; gender, treatment or general population sample, age of first use, number of alcohol-related consequences, and whether they attended AA. The p-values for these terms are tabled in the last column of Tables 2 and 3. For both dependent variables the estimates and p-values were generally very similar between models with and without the interaction terms. The one notable exception was that the number of negative alcohol-related events was no longer significant (p = .825), but the interaction term including that measure was (p = .029). In the binge model, similar to the model of volume, the addition of the interaction terms produced a loss of significance for the number of alcohol-related events, from p = .007 to p = .867. Change in binge drinking over time was now significant for this model and the positive sign on gender remained. As with volume, the relationship between the number of events and consumption increased over time. The interaction with age of first use was also significant, with the level of the negative correlation (lower age of first use relating to increased binge drinking) declining over time to near zero.

4. Discussion

As they aged, this sample of young adults demonstrated an overall decline in alcohol consumption. This is consistent with the findings of Brown and colleagues (Brown et al., 2001) and the findings summarized by Chung (Chung et al., 2003), and our findings extend those results to binge drinking as well. It should also be noted however that, in general, many continued to consume alcohol and only a small proportion maintained abstinence—a finding also seen by Jackson, et al. (Jackson et al., 2001). While the overall averages for both volume and binge drinking declined, they appeared to level off at an average age of about 24 years, which is about the end of this emergent adulthood period. This is consistent with recent findings (Casswell et al., 2002; Poelen et al., 2005). Being male, being dependent, age of first use, higher severity and no AA attendance were significant predictors of both greater drinking volume and binge drinking. In addition, receiving treatment in the year prior to assessment was related to decreased volume but not bingeing, while, conversely, a larger drug and heavy alcohol using social network was predictive of binge drinking but not of volume.

The most unexpected finding was the unpredicted greater level of binge drinking among women once the other measures were included in the statistical model. This suggests that if one were to find two heavy drinking samples of young adults who were identical on everything except their sex, the women would tend to binge more over time than men. More recent studies from college studies have documented increased binge drinking among young women – as a badge of honor to be able to drink “like a guy” as well as to receive positive attention from male peers (Young et al., 2005). In our case, this finding may also be a function of this particular sample—women in the stage of emerging adulthood who already are problem drinkers. Unlike findings reported by Grella and Abrantes but in concert with the results of Chung, we found no evidence of gender differences in changes in consumption (Chung et al., 2003). Also, in the models with interaction terms the genders did not change differentially over time on either of the behaviors.

Acknowledgments

This research was supported by RO1AA09750, PO50-AA05595, and P50DA09253. Portions of this work were presented at the 28th Annual Scientific Meeting of the Research Society on Alcoholism, June 30, 2005.

The authors wish to thank Lee Kaskutas, Ph.D. for a careful reading of an early draft and several helpful suggestions, Lyndsay Ammon for data management, and Priya Kamat for editorial help.

Footnotes

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