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Keywords:

  • Adolescence;
  • alcohol;
  • childhood;
  • problem behavior

ABSTRACT

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. Conflicts of interest
  9. References

Aims  To identify childhood and adolescent factors differentiating heavy alcohol users in early adulthood from more moderate users or abstainers.

Design  Low-income participants followed from birth to age 28 years.

Participants  A total of 178 adults (95 males) who were first-born children of low-income mothers recruited in Minneapolis, Minnesota, during their third trimester of pregnancy.

Measurements  Maternal hostility (24/42 months), externalizing and internalizing behavior problems (9 years), peer acceptance and academic achievement (12 years), maternal alcohol use and participants' drinking behavior (16 years), quantity of alcohol use per occasion (19, 23 and 26 years), alcohol use disorders (28 years).

Findings  For men: (i) higher amounts of alcohol consumption at age 16 increased the odds of being a heavy drinker compared to an abstainer (age 19) and a moderate drinker (ages 23 and 26); (ii) lower achievement scores at age 12 and having a mother who drank more when the participant was age 16 increased the odds of being a heavy drinker compared to moderate drinker (age 26). Higher levels of externalizing behavior problems at age 9 and drinking more when the participants were age 16 increased the odds that men would have a current alcohol use disorder at age 28. For women: (i) drinking more at age 16 increased the odds of being a heavy drinker compared to being either an abstainer or a moderate drinker (age 26); (ii) having higher levels of achievement at age 12 increased the odds of being a heavy drinker compared to an abstainer at age 23. Adolescent alcohol use mediated the relation between externalizing behavior at age 9 and alcohol use at age 26 for women.

Conclusions  Problem drinking may be the result of a long-term developmental process wherein childhood externalizing behavior problems sets a pathway leading to heavy drinking during and after adolescence.


INTRODUCTION

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. Conflicts of interest
  9. References

Problem drinking behavior carries substantial costs at both individual and societal levels. Numerous health problems are associated with heavy use of alcohol including chronic liver disease, heart disease, sexually transmitted diseases, stroke, depression, unintentional injuries and death [1,2]. Approximately 32.5 million Americans aged 12 or older reported driving under the influence of alcohol in 2004, with the highest rates associated with those aged 21–25 years; in the preceding year 28.2% of individuals in this group reported driving under the influence of alcohol [3]. Forty-one per cent of all traffic-related deaths in 2002 involved alcohol. Moreover, almost one-third of individuals who die each year from non-traffic-related unintentional injuries have blood alcohol levels above the legal limit [2]. Additional societal costs associated with problem drinking include child abuse, domestic violence, unintended pregnancy, crime and lost productivity [1,4]. Obviously, large expenditures of both private and public resources are spent each year on social services, health care and the criminal justice system necessitated by alcohol-related problems.

The prevalence rates of alcohol use disorders and binge drinking reveal relatively extensive heavy drinking in American society. The life-time rate of alcohol abuse and dependence for individuals aged 15–54 was 23.5% in 1992, with rates of 32.6% for males and 14.6% for females [5]. Findings such as these regarding gender differences in alcohol use behaviors and disorders have been reported consistently in the literature (see [6,7] for reviews). More specifically, males tend to drink in larger quantities and have more alcohol-related problems than females and they are also more likely to meet criteria for alcohol abuse and alcohol dependence.

Binge drinking (drinking five or more drinks on one occasion) affects even larger numbers of individuals than alcohol use disorders. In 2004, 55 million Americans (22.8%) 12 years of age or older reported binge drinking in the past 30 days [3]. Other national surveys have found similar results [1,4]. Young people between the ages of 18 to 25 reported the highest prevalence of binge drinking. In 2004, 41.2% of adults aged 18–25 years reported binge drinking in the previous month, with peak prevalence for those 21 years old (48.2%); this percentage dropped to approximately 30% for adults aged 30–39 with continued decreases accompanying increasing age [3]. This overall pattern of an increase in heavy drinking in the early to mid-20s followed by a decline thereafter has been well documented [1,8–13].

Considerable fluctuations in alcohol use across adolescence and into adulthood are also well known. Prevalence of current use of any alcohol ranged from 37% at age 14 years, to 88% at age 24, to 84% at age 30 [11]. Not all individuals who drink alcohol, however, are heavy drinkers, and not all individuals who drink heavily in adolescence and early adulthood continue to drink heavily later in adulthood. From a preventative standpoint it is important to identify factors that influence some individuals to engage in heavy drinking, whereas others drink more moderately or abstain from alcohol use. From a developmental perspective, a key to understanding patterns of substance use in adulthood is identifying childhood and adolescent antecedents of those patterns.

Few researchers have examined prospectively the developmental precursors of varying levels of substance use across early adulthood. Longitudinal studies conducted from a developmental perspective are important for understanding the etiologies and course of substance use disorders as well as the normative patterns of substance use [9,14,15]. However, many of the studies that have examined factors influencing adult alcohol use behavior have been cross-sectional and have considered only concurrent variables [16]. Although some researchers have investigated longitudinal predictors of alcohol use, most of these studies follow individuals from childhood to adolescence [9,17,18] or begin only when the participants have already entered adolescence [e.g. 15,19–21].

Researchers examining developmental predictors of adolescent alcohol use have found a number of risk and protective factors associated with alcohol use in adolescence. These factors include demographic variables (e.g. gender, ethnicity), individual variables (e.g. externalizing behavior problems, delinquent activity, depression, academic achievement), parenting variables (e.g. parents' alcohol use, parenting practices, parent–child relationships) and peer variables (e.g. peer competence, peers' alcohol use, peer deviance) [9,17,18,22–25]. Because alcohol use fluctuates from adolescence to adulthood, however, it may be that childhood risk and protective factors may differ when examining drinking behavior in adulthood rather than adolescence.

Some researchers have examined adolescent and concurrent predictors of various patterns of adult alcohol use. Findings from these studies suggest that personality factors (e.g. undercontrol, depression), drinking behavior in adolescence, drinking behavior of significant others (e.g. parents, peers, romantic partners) and adult roles (e.g. work, marriage) are related to alcohol use behavior in adulthood [15,16,19,26]. In order to identify the roots of varying levels of adult alcohol use, it is essential to examine developmental precursors in childhood, prior to initiation of alcohol use, as well as precursors in adolescence.

Parenting factors have been linked to the onset of drinking in adolescence, levels of alcohol use in adolescence and problems with alcohol use in adolescence and early adulthood. Parental rejection and low levels of parental support have emerged as important predictors of alcohol problems in adolescence [23,27–31]. Parental alcohol use has also been associated with adolescent and early adult alcohol use, such that higher levels of alcohol use by parents foretells higher levels of alcohol use by their offspring [31–36].

In addition to parenting factors, researchers have also found a number of individual variables that are related to adolescent and early adult alcohol use as well as abuse and dependence. One important predictor of adolescent and early adult alcohol use is externalizing behavior problems [e.g. conduct disorder, aggressiveness, attention deficit hyperactivity disorder (ADHD), undercontrol, impulsivity][24,32,37–41]. Researchers have found that externalizing behavior problems in childhood are related to earlier onset of drinking in adolescence [42,43], as well as problem drinking behavior, including alcohol abuse and dependence in early adulthood [24,35,37,39,44,45]. This link between externalizing behavior problems and later problems with alcohol use has been found most extensively in males [33,35,37,46]. Internalizing behavior problems (e.g. depression, anxiety) have also been examined for their relation to alcohol use, but results vary across studies. Some studies have found higher levels of alcohol use associated with higher levels of internalizing problems, others have found lower levels of alcohol use associated with higher levels of internalizing problems, and still others have found no association [19,47–49].

Besides parenting factors and behavior problems, other variables that researchers have found related to alcohol use in early adulthood include drinking behavior in adolescence, academic achievement and peer relationships. A robust finding across studies is that heavy drinking in adolescence predicts heavy drinking and alcohol use disorders in adulthood [26,33,50]. The findings regarding the relation between academic achievement and alcohol use have been somewhat inconsistent. A number of studies have found that lower levels of school achievement predicts higher levels of drinking in adulthood [26,35], whereas other studies have found that college students are more likely to drink heavily compared to non-college students mainly during the time-period that they are attending college [11,51]. One longitudinal study examining a British birth cohort found that higher levels of cognitive ability in childhood increased the risk of alcohol abuse in adulthood for both men and women [52]. Also found to be important for alcohol use, especially during adolescence, are peer factors. One important aspect of peer relationships is competence with peers. Some evidence indicates that adolescents who are competent with their peers are more likely to drink than those who are not as competent with peers [53]. Other studies indicate that substance users have poor social skills in childhood [22,54]. Although some of the findings regarding the impact of these variables are consistent across studies, much of the research is either inconsistent or does not follow participants from childhood through early adulthood.

The purpose of the current study is to examine whether childhood and adolescent risk factors differentiate heavy alcohol users from those individuals who drink at more moderate levels or abstain from alcohol use in early adulthood. Of particular interest were the combined contributions of childhood and adolescent variables to problematic drinking across early adulthood, and whether these predictors vary by gender and age of outcome. Given the considerable fluctuations in drinking behaviors from late adolescence through early adulthood, it may also be important to examine whether there are differential predictions of alcohol use behavior at different ages across this time-period. Additionally, gender predicts adolescent alcohol use [9,17,18,22,24], i.e. men tend to drink more and have higher rates of alcohol use disorders [5–7] than women. Furthermore, findings from previous studies suggest that some predictors may vary by gender [33,35,37,46]. Therefore, analyses were conducted separately by gender in order to shed light on whether the variables of interest differentially predict males versus female heavy drinking in early adulthood.

The Minnesota Longitudinal Study of Parents and Children has followed participants from birth to age 28 from a developmental perspective. Our comprehensive, prospective data set includes measures from multiple sources at various points in time, including direct observational measures of parent–child relationships in early childhood, childhood measures of achievement, peer acceptance and behavior problems, and detailed measures of substance use in adolescence and early adulthood. Our unique prospective, longitudinal data set allows us to examine and identify the developmental precursors of varying levels of alcohol use from late adolescence to early adulthood.

METHODS

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. Conflicts of interest
  9. References

Participants

The original sample consisted of 267 mothers and their first-born children. All the mothers were low-income (below poverty level) at the time of recruitment and were obtained from public health clinics in Minneapolis, Minnesota during their third trimester of pregnancy [55]. The current participants (n = 178, 95 males) were followed from birth to age 28. Participants' race is as follows: 67.6% Caucasian, 10.6% African American, 17.1% mixed race, 1.8% other (e.g. Native American, Hispanic) and 2.9% unknown. At the time of the participants' birth, 57.4% of the mothers were single never married, 39.1% were married and 3.5% were other (e.g. divorced, widowed). Mothers' age at the birth of the participants ranged from 15 to 34 years [mean = 20.70, standard deviation (SD) = 3.57]. The current sample does not differ significantly from the attrition group with respect to mother's socio-economic status (SES), age, marital status or risk status at the time of the child's birth. The attrition group differed significantly from the current sample based on mothers' ethnicity (the attrition group was more likely to be African American) and mothers' education at their children's birth (the attrition group had lower levels of education).

Measures

Alcohol use groups

Alcohol use data were obtained from participants at ages 19, 23 and 26 years through the Adult Health Survey (modified version of the Adolescent Health Survey) [56]. The Adult Health Survey is a self-report questionnaire measuring various risk factors for physical and emotional ill health. Alcohol use groups were determined based on quantity of alcohol use per occasion [‘If you drink alcohol (beer/wine/hard liquor), generally, how much do you drink at one time?’ (don't drink = 0, one drink = 1, two drinks = 2, three drinks = 3, four drinks = 4, five or more drinks = 5)]. Because individuals who are heavy drinkers are distinct from abstainers and moderate drinkers in their alcohol use behaviors, and because researchers have found that abstainers, moderate substance users and abusers are predicted differentially from earlier measures [24], we considered it advantageous to investigate predictors of these alcohol use groups rather than examine predictors based on a continuum of alcohol use.

Three substance use groups at each age period were derived from participants' responses on the Adult Health Survey (abstainers = don't drink; moderate drinkers = one to four drinks for men, one to three drinks for women; heavy drinkers = five or more drinks for men, four or more drinks for women). The lower cut-point of four or more drinks for women was chosen based on both previous definitions in many studies of binge drinking using a lower cut-point for women, the finding that women who drink four drinks are as likely as men who drink five drinks to have similar problems associated with their drinking behaviors, and differences in absorption rates and metabolism of alcohol for women compared to men [2,57] (see Table 1 for a list of constructs and measures used in this study).

Table 1.  List of constructs and measures.
ConstructVariableMeasureAge
Outcomes
 Alcohol useGroups based on quantity of alcohol use per occasion (abstainers, moderate users, heavy users)Self-report19 years 23 years 26 years
 Alcohol use disordersSCID-I (current within past month)Self-report28 years
Predictors
 Alcohol useQuantity of alcohol use per occasionSelf-report16 years
 Family processes/relationshipsMaternal hostilityObserver coded parent– child interactionsCombined 24 & 42 months
 Parental drinkingMaternal drinking behaviorAdolescent report16 years
 Peer relationshipsPeer acceptanceTeacher rating12 years
 Academic achievementPeabody individualized achievement test (PIAT)Total score (standardized)12 years
 Externalizing behavior problemsAchenbach child behavior checklist (standardized by gender)Teacher report (TRF)9 years
 Internalizing behavior problemsAchenbach child behavior checklist (standardized by gender)Teacher report (TRF)9 years

At age 19 (n = 170), 20% of the participants were abstainers (n = 34, 17 males and 17 females), 43.5% were moderate drinkers (n = 74, 33 males and 41 females) and 36.5% were heavy drinkers (n = 62, 38 males and 24 females). At age 23 (n = 158), 8.9% of the participants were abstainers (n = 14, six males and eight females), 58.9% were moderate drinkers (n = 93, 44 males and 49 females) and 32.3% were heavy drinkers (n = 51, 31 males and 20 females). At age 26 (n = 164), 14.4% of the participants were abstainers (n = 23, 10 males and 13 females), 59.1% were moderate drinkers (n = 97, 45 males and 52 females) and 26.8% were heavy drinkers (n = 44, 28 males and 16 females).

Current alcohol use disorders at 28 years

At age 28 years (n = 162) participants were given the abbreviated Clinician's Version of the Structured Clinical Interview for DSM-IV Axis I (SCID-I) [58] to assess current (within past month) and past (since age 18) alcohol abuse and dependence. The SCID-I was administered by interviewers trained extensively on the SCID with ongoing supervision and consultation provided throughout the data collection. The outcome measure used in the current study is any current alcohol use disorder (current alcohol abuse or current alcohol dependence; n = 11, nine males, two females). As the past alcohol use disorders measure may overlap with the heavy drinking groups at age 19, 23 and 26, we chose to examine only the current alcohol use disorder measure.

Developmental predictors

A number of theoretical considerations were taken into account in our determination of predictor variables. First, variables were selected for inclusion in this study based on their identified importance as a childhood predictor of alcohol use in adolescence or early adulthood, or as a predictor of alcohol use in early adulthood based on previous research. Salient variables included parenting factors (maternal rejection/hostility, maternal drinking behaviors), individual factors (externalizing and internalizing behavior problems, academic achievement and drinking behavior in adolescence) and peer factors (peer acceptance). Secondly, a developmental perspective guided our selection of variables based on their salience at different developmental periods. Careful attention was given to determining which variables should be included at what developmental period. Maternal rejection/hostility is especially important in early childhood when parent–child relationships are prominent [59]. Childhood onset behavior problems, particularly externalizing behavior problems, are usually stable through adolescence, occur less frequently than adolescent onset behavior problems and may portent greater levels of adult pathology [60–63]. Academic achievement and peer acceptance are of greater consequence in middle childhood and early adolescence than earlier, with achievement measures becoming fairly stable by middle childhood [64,65] and children spending an increasing amount of time with their peers [66] during early adolescence. Children's perceptions of their parents' drinking may have more of an influence on their children's drinking behavior during adolescence when they are able to think abstractly, consider hypothetical possibilities and use practical reasoning [67,68].

Family relationships (maternal hostility). At ages 24 and 42 months participants were video-taped interacting with their mothers in a series of developmentally appropriate tasks. At 24 months, toddlers and their mothers were observed in a play session, a clean-up session and four tool problem-solving tasks. At 42 months, pre-schoolers and their mothers interacted in four teaching tasks. Trained observers rated the mothers on a number of scales at both ages, including maternal hostility. To assess inter-rater reliability, intraclass correlations were computed for the 24-month and 42-month scales. Intraclass correlations for the hostility scale were 0.75 for 24 months and 0.85 for 42 months.

Maternal hostility in early childhood is a rating of the mother's expression of anger, hostile behavior or rejection of the child at 24 and 42 months based on a seven-point scale. A low score signified no signs of hostile behavior on the part of the mother toward the child, whereas a high score indicated strong expressions of anger toward and rejection of the child. Scores for ages 24 and 42 months were averaged to obtain average scores for maternal hostility in early childhood. Averaged 24 and 42 month scores ranged from 1 to 7 (mean = 1.74, SD = 1.08).

Maternal drinking. Adolescents' perception of the frequency of their mothers' drinking was obtained when the participants were age 16 years using the Adolescent Health Survey [56]. Participants were asked the following: ‘How often does your mother/stepmother/female guardian use beer/wine/alcohol?’. Participants rated their mothers' use of alcohol on the following scale: 1 = never, 2 = once, 3 = less than monthly, 4 = about monthly, 5 = about weekly or 6 = daily. Scores ranged from 1 to 6 (mean = 2.59, SD = 1.44).

Peer acceptance. At 12 years, teachers ranked participants' peer acceptance within their class based on a description of a socially competent child. A socially competent child was considered sociable, popular, accepted by their peers, having friendships and displaying social skills and leadership qualities. Teachers ranked all children in their class from most socially competent to least socially competent. Each participant's percentile rank was calculated by taking the number of children below that child's ranking divided by the number of children in the class multiplied by 100. Peer acceptance rankings at age 12 ranged from 3.23 to 100 (mean = 54.93, SD = 28.73).

Academic achievement. When the participants were 12 years old they were each administered the Peabody Individual Achievement Test (PIAT) [69] by trained graduate students. The PIAT provides a general achievement score that includes assessments of math, reading recognition, reading comprehension, spelling and general information. The total grade standard score was used for data analyses. PIAT scores at 12 years ranged from 65 to 125.75 (mean = 101.57, SD = 9.79).

Externalizing and internalizing behavior problems. Externalizing and internalizing behavior was assessed at 9 years of age based on the Teacher Report Form of the Achenbach Child Behavior Checklist (TRF) [70]. The behavior checklist portion of the TRF is comprised of 118 items rated by the teacher on a three-point scale (0 = not true, 1 = somewhat or sometimes true, 2 = very true or often true) and is designed to obtain teachers' reports of students' problems in a standardized format. Normalized t-scores for the externalizing and internalizing scales were used in this study. At 9 years, the participants' teacher who spent the most time with them during the school day completed the TRF; externalizing scores ranged from 39.00 to 82.00 (mean = 55.70, SD = 10.65) and internalizing scores ranged from 36.00 to 77.00 (mean = 54.06, SD = 9.87).

Alcohol use in adolescence. Alcohol use in adolescence was obtained from the Adolescent Health Survey [56] conducted when the participants were age 16 years. The alcohol use variable is a measure of the quantity of alcohol use per occasion (0 = don't drink, 1 = one drink, 2 = two drinks, 3 = three drinks, 4 = four drinks, 5 = five or more drinks). Scores ranged from 0 to 5 (mean = 1.46, SD = 1.72).

Data analysis plan

In order to identify factors from childhood and adolescence that differentiate levels of alcohol use at ages 19, 23 and 26 we conducted a series of multinomial logistic regressions. These analyses allowed us to examine differences between each of the alcohol use groups (abstainers, moderate drinkers, heavy drinkers) rather than treat individuals as varying only by degree of alcohol use. Because of our specific interests in identifying predictors of heavy alcohol use in early adulthood, the reference group for all the regression analyses was the heavy alcohol use group. In order to identify childhood and adolescent variables that differentiated individuals with current (within past month) alcohol use disorders, we computed binary logistic regressions. Due to sample size, only the main effects for each model are examined. Given the robust findings regarding gender differences in the literature [5–7], we examined the statistical models separately for males and females. As there were only two women who met criteria for current alcohol use disorders at age 28, we did not run these models for women at age 28. Models examining childhood predictors only (maternal hostility, peer acceptance, academic achievement, externalizing behavior and internalizing behavior) were also run separately in order to examine whether the adolescent variables may be mediating relations between childhood predictors and alcohol use in early adulthood.

Missing data

Missing data for the predictor variables (5.78%) were replaced with multiple imputation using the EM (expectation–maximization) algorithm in Prelis 2.80.

RESULTS

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. Conflicts of interest
  9. References

Rate of alcohol use and alcohol use disorders

In Table 2 we present descriptive statistics on the quantity of alcohol use by gender at ages 16, 19, 23 and 26 based on the three alcohol use groups (abstainers, moderate drinkers and heavy drinkers). A larger percentage of females (18.3%) compared to males (7.3%) were heavy drinkers at 16 years of age. By age 19, however, a larger percentage of males (43.1%) compared to females (29.3%) were heavy drinkers; this continued to ages 23 (38.3% of males compared to 26.0% of females) and 26 (33.8% of males compared to 19.8% of females). Within this sample the highest percentage of heavy drinkers occurred when the participants were 19 years of age, with a decline at age 23 and again at age 26. The highest percentage of drinkers (i.e. not abstainers), however, spiked at 23 years of age (92.6% of males and 89.6% of females) and began to decline by age 26 (88.0% of males and 84.0% of females). For the sample, 11.0% of males and 2.5% of females had a current alcohol use disorder at 28 years.

Table 2.  Rate of alcohol use and alcohol disorders.
 AbstainersModerate drinkersHeavy drinkersCurrent alcohol disorder
16 years
 Males (n = 82)43 (52.4%)33 (40.3%)6 (7.3%) 
 Females (n = 75)32 (42.7%)28 (39.0%)15 (18.3%) 
19 years
 Males (n = 88)17 (19.3%)33 (37.5%)38 (43.2%) 
 Females (n = 82)17 (20.7%)41 (50.0%)24 (29.3%) 
23 years
 Males (n = 81)6 (7.4%)44 (54.3%)31 (38.3%) 
 Females (n = 77)8 (10.4%)49 (63.6%)20 (26.0%) 
26 years
 Males (n = 83)10 (12.0%)45 (54.2%)28 (33.8%) 
 Females (n = 81)13 (16.0%)52 (64.2%)16 (19.8%) 
28 years
 Males (n = 82)   9 (11.0%)
 Females (n = 80)   2 (2.5%)

Cross-tabulations were conducted across the alcohol use groups at ages 19, 23, 26 and 28. Although individuals changed their level of alcohol use across early adulthood, the percentage of individuals remaining in the same alcohol use group from one age to another was high (with the exception of abstainers at age 19 changing to moderate drinkers at 23 and 26 years). Of those individuals who were heavy drinkers at age 19, 49.1% were heavy drinkers at age 23 and 46.3% were heavy drinkers at age 26; 60.4% of heavy drinkers at age 23 were heavy drinkers at age 26. Well over half of those individuals identified as having a current alcohol use disorder at age 28 were heavy drinkers at each of the earlier ages (77.8% were heavy drinkers at age 19, 60% were heavy drinkers at age 23 and 90% were heavy drinkers at age 26).

Correlations

Bivariate (Pearson's r) correlations for predictor variables are presented separately by gender in Table 3. Although a number of variables were correlated significantly both for males and females, other variables were correlated significantly for one gender but not the other. Interestingly, although age 16 alcohol use is not related significantly to any of the other predictors for men, adolescent alcohol use is related significantly to externalizing behaviors at age 9, achievement at age 12 and maternal alcohol use when the participants were adolescents for women.

Table 3.  Correlations (Pearson's R) among predictors of early adulthood alcohol use groups by gender (males above diagonal n = 95, females below diagonal n = 83).
 (1)(2)(3)(4)(5)(6)(7)
  • *

    P < 0.05,

  • **

    P < 0.01,

  • ***

    P < 0.001. SD: standard deviation.

1. Hostility (24 & 42 months)−0.14−0.22*−0.020.070.14−0.09
2. Maternal alcohol use (16 years)0.03−0.010.27**−0.32**−0.30**−0.07
3. Peer acceptance (12 years)−0.23*0.040.10−0.25*−0.26**0.04
4. Achievement (12 years)−0.35***0.24*0.40***−0.07−0.180.14
5. Externalizing (9 years)0.37***0.09−0.12−0.080.41***0.13
6. Internalizing (9 years)0.13−0.15−0.150.070.28*−0.01
7. Alcohol use (16 years)0.040.33**0.160.28*0.29**0.02
Means (SD)
 Males1.74 (1.15)2.55 (1.40)49.49 (29.50)101.20 (9.79)56.27 (11.24)54.03 (9.95)1.24 (1.64)
 Females1.74 (1.00)2.64 (1.48)61.15 (26.41)102.00 (9.82)55.04 (9.95)54.08 (9.83)1.70 (1.79)

Logistic regression models

Results from the multinomial logistic regression models examining the combined childhood and adolescent measures predicting early adult alcohol use for males and females are reported in Tables 4 and 5, respectively. Odds ratios are dependent on the unit of measurement; the unit of measurement varies across the variables and therefore the odds ratios are not comparable from one variable to another. The χ2 likelihood ratio test for each predictor variable is identified on the tables and indicates whether the variable significantly predicts outcome groups; the Wald test was used to test significance levels for individual coefficients for each predictor variable.

Table 4.  Multinomial logistic regression predicting alcohol use behavior from childhood and adolescent measures for males (age 19, n = 88; age 23, n = 81; age 26, n = 83; age 28, n = 82).
Measures19 years23 years26 years28 years
χ2ORCIχ2ORCIχ2ORCIχ2ORCI
  1. Pseudo R2[77] 19 years = 0.21, 23 years = 0.23, 26 years = 0.32, 28 years = 0.36; CI = confidence interval; OR = odds ratio. *P < 0.05, **P < 0.01, ***P < 0.001, P < 0.10.

Maternal hostility, 24 & 42 months1.62  1.93  1.25  2.27  
 Abstainers versus heavy users 0.840.46–1.54 1.110.53–2.30 0.750.34–1.65   
 Moderate users versus heavy users 0.700.40–1.24 0.750.45–1.23 1.090.70–1.72   
 No disorder versus current alcohol use disorder          0.600.33–1.11
Maternal alcohol use, 16 years1.89  1.71  6.65*  3.31  
 Abstainers versus heavy users 0.820.50–1.34 0.720.32–1.65 0.640.32–1.27   
 Moderate users versus heavy users 0.760.51–1.14 0.780.52–1.16 0.57*0.37–0.90   
 No disorder versus current alcohol use disorder          0.510.24–1.10
Peer acceptance, 12 years1.58  1.30  6.52*  0.89  
 Abstainers versus heavy users 1.010.99–1.04 0.980.94–1.03 0.970.93–1.00   
 Moderate users versus heavy users 1.010.99–1.03 1.010.99–1.02 1.010.99–1.03   
 No disorder versus current alcohol use disorder          1.010.98–1.05
Academic achievement, 12 years0.23  1.28  6.79*  2.24  
 Abstainers versus heavy users 1.010.95–1.08 1.050.95–1.15 1.020.94–1.12   
 Moderate users versus heavy users 1.010.96–1.07 1.020.97–1.08 1.08*1.01–1.15   
 No disorder versus current alcohol use disorder          1.080.97–1.20
Externalizing behavior, 9 years0.14  0.59  5.10  5.40*  
 Abstainers versus heavy users 0.990.93–1.06 0.980.90–1.08 0.91*0.83–0.99   
 Moderate users versus heavy users 1.000.95–1.06 1.010.97–1.08 0.970.92–1.03   
 No disorder versus current alcohol use disorder          0.90*0.81–0.99
Internalizing behavior, 9 years3.48  1.07  0.10  0.00  
 Abstainers versus heavy users 1.050.98–1.14 1.000.87–1.14 0.990.90–1.10   
 Moderate users versus heavy users 1.050.99–1.12 0.970.91–1.03 1.010.95–1.07   
 No disorder versus current alcohol use disorder          1.000.90–1.12
Alcohol use, 16 years8.94*  9.14*  6.01*  4.62*  
 Abstainers versus heavy users 0.46*0.24–0.89 0.330.07–1.53 0.690.39–1.24   
 Moderate users versus heavy users 0.850.63–1.15 0.69*0.50–0.94 0.67*0.47–0.98   
 No disorder versus current alcohol use disorder          0.61*0.39–0.98
Table 5.  Multinomial logistic regression predicting alcohol use behavior from childhood and adolescent measures for females (age 19, n = 82; age 23, n = 77; age 26, n = 81).
Measures19 years23 years26 years
χ2ORCIχ2ORCIχ2ORCI
  1. Pseudo R2[77] 19 years = 0.36, 23 years = 0.47, 26 years = 0.29; CI = confidence interval; OR = odds ratio. *P < 0.05, **P < 0.01, P < 0.10.

Maternal hostility, 24 & 42 months7.03*  3.32  0.48  
 Abstainers versus heavy users 1.790.70–4.55 8.100.45–144.64 1.410.51–3.94
 Moderate users versus heavy users 0.600.31–1.14 1.560.73–3.33 1.050.54–2.04
Maternal alcohol use, 16 years4.41  10.04**  0.26  
 Abstainers versus heavy users 0.560.27–1.15 0.050.00–1.08 0.900.46–1.75
 Moderate users versus heavy users 1.110.75–1.63 0.790.53–1.16 0.900.60–1.36
Peer acceptance, 12 years1.05  4.14  0.69  
 Abstainers versus heavy users 1.010.98–1.04 1.080.98–1.19 1.000.97–1.04
 Moderate users versus heavy users 0.990.97–1.02 1.000.98–1.03 1.010.98–1.04
Academic achievement, 12 years0.59  9.99**  1.55  
 Abstainers versus heavy users 0.970.88–1.07 0.68*0.47–0.98 0.940.84–1.05
 Moderate users versus heavy users 0.980.91–1.05 1.010.94–1.09 0.990.91–1.07
Externalizing behavior, 9 years2.71  0.09  6.09*  
 Abstainers versus heavy user 0.980.89–1.07 1.010.89–1.16 0.900.80–1.02
 Moderate users versus heavy users 1.040.97–1.11 1.010.95–1.08 1.010.95–1.09
Internalizing behavior, 16 years1.28  5.05  0.02  
 Abstainers versus heavy users 0.950.87–1.04 0.820.67–1.01 0.990.91–1.09
 Moderate users versus heavy users 0.990.93–1.05 0.970.92–1.04 1.000.93–1.07
Alcohol use, 16 years5.16  1.02  6.42*  
 Abstainers versus heavy users 0.55*0.31–0.98 0.870.38–1.98 0.52*0.27–0.99
 Moderate users versus heavy users 0.850.62–1.18 0.830.59–1.19 0.66*0.45–0.96

For men (see Table 4), the only significant predictor of alcohol use group at ages 19 and 23 was alcohol use at age 16; however, additional predictors were identified for alcohol use group at age 26 and current alcohol use disorder at age 28. Alcohol use at age 16 differentiated heavy alcohol users from abstainers at age 19, and from moderate alcohol users at ages 23 and 26, as well as those with current alcohol use disorders from those without at age 28. Higher levels of alcohol use at age 16 increased the odds of being (i) a heavy drinker compared to an abstainer at age 19 and a moderate alcohol user at ages 23 and 26; and (ii) having a current alcohol use disorder at age 28. The odds of being an abstainer compared to a heavy user at age 19 decreased by 0.46 for every 1-unit increase in adolescent alcohol use; this translates to an increase in the odds of being a heavy user by a factor of 2.17 (1/0.46) for every 1-unit increase in alcohol use at age 16. The odds of being a heavy user compared to a moderate user at ages 23 and 26 increased by a factor of 1.45 (1/0.69) and 1.49 (1/0.67), respectively, for every 1-unit increase in adolescent alcohol use. For every 1-unit increase in adolescent alcohol use the odds of having an alcohol use disorder increased by a factor of 1.64 (1/0.61).

In addition to alcohol use at age 16, other childhood and adolescent predictors also differentiated men who were heavy alcohol users from moderate alcohol users at age 26, and men with current alcohol use disorders from those without at age 28. Every 1-unit increase in maternal alcohol use at age 16 increased the odds of being a heavy user at age 26 compared to a moderate alcohol user increased by a factor of 1.75 (1/0.57). Additionally, academic achievement at age 12 and peer acceptance at age 12 predicted alcohol use group significantly at age 26. Every 1-unit increase in academic achievement at age 12 increased the odds of being a moderate alcohol user at age 26 compared to a heavy alcohol user by a factor of 1.08. In addition to higher levels of alcohol use at age 16, every 1-unit of increase in externalizing behavior problems at age 9 increased the odds of men having current alcohol use disorders at age 28 compared to those with no current alcohol use disorder by a factor of 1.10 (1/0.91).

For women (see Table 5), several variables predicted alcohol use groups significantly, although these varied by age. At age 19 maternal hostility at 24/42 months predicted alcohol use group significantly. At age 23 academic achievement at age 12 and maternal alcohol use at age 16 predicted alcohol use group significantly. Every 1-unit increase in academic achievement at age 12 increased the odds of being a heavy user at age 23 compared to an abstainer by a factor of 1.47 (1/0.68). At age 26 externalizing behavior problems at age 9 and alcohol use at age 16 predicted alcohol use groups significantly. Every 1-unit of increase in alcohol use at age 16 increased the odds of being a heavy alcohol user at age 26 compared to an abstainer by a factor of 1.92 (1/0.52) and a moderate user by a factor of 1.52 (1/0.66).

Mediational analyses

Logistic regressions examining only childhood predictors yielded similar findings for both men and women as the full models and did not suggest that the adolescent variables mediated any childhood variables, with one exception. In the childhood-only model higher levels of externalizing behavior at age 9 increased the odds that women would be heavy drinkers at age 26 compared to abstainers; this difference was a trend in the full model. Further testing for mediation using the Sobel procedure [71] indicated that adolescent alcohol use mediated the relation between externalizing behavior in childhood and alcohol use at age 26 for women (z = −23.77; P < 0.001).

DISCUSSION

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. Conflicts of interest
  9. References

In this study we examined developmental predictors of heavy alcohol use and alcohol disorders in early adulthood. Specifically, we were interested in how childhood and adolescent predictors differentiated heavy alcohol users from abstainers and moderate drinkers at ages 19, 23 and 26 and whether those predictors differentiated individuals with and without current alcohol use disorders at age 28.

Descriptive statistics indicate that rates of alcohol use and heavy drinking behavior across early adulthood in our sample are similar to alcohol use rates obtained in other US samples. We found that alcohol use rates among our participants peaked at age 23, with 91.2% of the participants drinking, and declined slightly by age 26, 85.9% of the sample drinking. These rates are similar to those obtained in other studies [11]. Heavy drinking rates across early adulthood in our sample also correspond with rates obtained from other sources [3]. The rates of alcohol abuse were similar for women across our sample compared to the 2001–02 rates in the National Epidemiologic Survey on Alcohol and Related Conditions [72], but current prevalence rates were somewhat higher for men in our sample (11.0%) compared to this national sample (6.9%), a difference due perhaps to sample size.

Alcohol use at age 16 was an especially robust predictor of heavy alcohol use across early adulthood, especially for men, but also for women at age 26. This result supports previous findings indicating that adolescent alcohol use is an important predictor of later alcohol use [19,26,33,50].

One notable finding was that academic achievement predicted differentially heavy alcohol use for women at age 23 and men at age 26. Results from the 23 years model indicating that higher levels of academic achievement in early adolescence increased the odds that women were heavy drinkers compared to women who were abstainers at age 23. Some researchers have found that college students drink more than individuals who do not attend college [73]. It is possible that our more academically inclined women were attending college when they were in their early 20s, and therefore drank more than non-college-attending women participants during this time-period. Post-hoc analyses support this possibility. We found that while 50% of women who were abstainers at age 23 had some college by age 26 (four of eight), 80% of women who were heavy drinkers had at least some college by this age (16 of 20). Academic achievement was a predictor of heavy drinking only in women at age 23, however, a time-period when the participants were probably attending college. In contrast to our findings for women, lower levels of academic achievement at age 12 increased the odds that men were heavy drinkers at age 26 compared to moderate alcohol users. These results for men support findings from other studies indicating that poor school performance predicts heavy drinking in adulthood [26,35].

Mothers' use of alcohol, as reported by the participants at age 16, differentiated significantly men who were heavy drinkers at age 26 from moderate users. Trends regarding maternal alcohol use were also found at age 23 for women, differentiating heavy drinkers from abstainers (higher levels of maternal drinking increased odds of being a heavy drinker) and for men at age 28 (higher levels of maternal drinking increased odds of having a current alcohol use disorder). Psychosocial factors as well as genetic factors may account for these findings. Findings from the field of behavioral genetics support the idea that certain individuals have a genetic predisposition, or vulnerability, to develop addictions (see [41,74] for reviews); however, given that alcoholism is a heterogeneous disorder, it is likely that there are both genetic and environmental factors contributing to its development [75]. These findings may also indicate an environmental influence; participants who perceived that their mothers drank more may have been more likely to consider drinking acceptable in early adulthood.

It is plausible that a genetic link to alcoholism is not direct, but rather is evident only in combination with specific environmental factors. Our findings suggest that externalizing problems in childhood may be a key developmental predictor of alcohol use disorders in early adulthood. Externalizing behavior problems in childhood and higher levels of alcohol use in adolescence differentiated men who had a current alcohol use disorder at age 28 from those who did not. There was also a trend at 26 years for both men and women, indicating that externalizing behavior problems in childhood increased the odds of being a heavy drinker compared to an abstainer. This association for women was found to be mediated by adolescent alcohol use. It is possible that both externalizing behaviors and substance use behaviors are manifestations of underlying behavioral dysregulation and undercontrol, as has been suggested by some researchers (e.g. [37,41,45)]. Poor parenting in early childhood, especially neglect and harsh treatment, has been found to be associated with later conduct problems [76]. Correlations indicate that externalizing behavior problems are associated significantly with maternal hostility in early childhood for the women in our sample. Perhaps a genetic predisposition to alcohol disorders coupled with poor parenting leading to behavioral dysregulation in childhood together with a perception of heavy alcohol use as acceptable behavior may place individuals on a pathway towards heavier drinking in adolescence and into early adulthood.

Several important limitations of this study should be mentioned. First, the number of participants is small, especially when data are examined separately by gender. The models need to be interpreted with caution due to the small number of participants (e.g. nine men had current alcohol use disorders at age 28). Our results from age 28, however, are also reflected, albeit to a lesser degree, at age 26, suggesting that these are not spurious findings. Other longitudinal data sets should be examined in order to validate the findings presented here. The studies included in this special issue are a first step toward validating results across our studies. A second limitation is the use of adolescent report of maternal drinking as a measure of maternal alcohol use. Although adolescents' reports may reflect actual drinking behavior accurately, these reports may also be biased based on the adolescents' own drinking behavior and their perceptions of, as well as their relationship with, their parents. In order to truly assess a possible genetic predisposition to alcoholism, measures of both maternal and paternal alcoholism should be obtained. Our data set is lacking in these measures and, given that a large number of our participants' mothers were single (only 39% were married at the birth of our participants) we do not have information on paternal alcohol use. Additional research should be conducted that assesses parental problem drinking more directly and, especially, gathers information about paternal alcoholism. Another limitation is the use of self-report data for alcohol use. The alcohol use data were not validated with other informants; thus participants may not have provided accurate information about their use of alcohol. We did, however, conduct assessments prospectively. Finally, we caution that despite findings of developmental variation in significant predictors, this does not necessarily imply that the variable predicts differently at different ages; some of our participants changed their alcohol use behaviors over time.

Our findings provide preliminary indications that there may be a developmental pathway leading to heavy drinking and alcohol use disorders in early adulthood through behavioral dysregulation and, in particular, impulse control problems (manifest in externalizing behavioral problems) in childhood; this may be especially true for those individuals who are genetically predisposed to alcoholism. Findings from this study support the theoretical literature [41] suggesting that, especially for those individuals with a genetic predisposition to alcoholism, there may be a developmental pathway from poor parenting to behavioral dysregulation leading to alcohol use disorders in adulthood. Further research should explore this possible pathway to alcohol use disorders more fully. Additionally, researchers should also incorporate the use of dynamic models to examine changes in drinking behaviors in early adulthood and attempt to identify developmental predictors of change in alcohol use behaviors. Further research should also examine concurrent factors that are known to be associated with alcohol use in early adulthood together with developmental predictors. An examination of concurrent variables in conjunction with developmental predictors may yield important insights into how current circumstances interact with developmental history to shape early adult drinking behavior.

Acknowledgements

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. Conflicts of interest
  9. References

Preparation of this work and the research described herein were supported by grants to the Center for the Analysis of Pathways from Childhood to Adulthood from the National Science Foundation (0322356) and to the Longitudinal Study of Parents and Children from the National Institute of Mental Health (MH40864) and the National Institute of Child Health and Human Development (HD054850).

Conflicts of interest

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. Conflicts of interest
  9. References

The authors have declared no conflicts of interest.

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  6. DISCUSSION
  7. Acknowledgements
  8. Conflicts of interest
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