Alcohol And Development In Youth—

advertisement
Alcohol and Development in Youth—
A Multidisciplinary Overview
Introduction
Underage drinking is a complex problem that has plagued society for generations. As the
lead Federal agency for supporting and conducting basic and applied research on alcohol
problems, the National Institute on Alcohol Abuse and Alcoholism (NIAAA) has long been
at the forefront of efforts to address the broad spectrum of issues related to drinking by
youth through projects ranging from studies of alcohol consumption among adolescents
to trials of ways to prevent and treat underage drinking.
Over the past decade, NIAAA’s research investment in underage drinking has increased steadily,
especially during the 5-year National Institutes of Health budget-doubling period that began in
1998. Increased funding during this period allowed NIAAA to support additional studies and
undertake its 1998 college drinking initiative, a collaborative enterprise involving researchers and
college presidents.
The college drinking initiative advanced our understanding of drinking by college students,
particularly the heavy episodic alcohol consumption commonly called “binge” drinking, and is
leading to ways to treat and prevent alcohol-related problems among college students. It also
underscored the fact that although some students begin drinking in college, most begin drinking
much earlier—in high school, middle school, and even elementary school.
Previously, data from NIAAA’s National Longitudinal Alcohol Epidemiologic Survey (NLAES) had
shown that alcohol use early in life correlates strongly with the development of alcohol
dependence later in life. In March 2002, NIAAA partnered with the Robert Wood Johnson
Foundation to launch the Leadership to Keep Children Alcohol Free Initiative. Spearheaded by
Governors’ spouses, this initiative focuses on increasing public awareness of alcohol
consumption among children ages 9 to 15 and ensuring that policymakers remain fully informed
of the seriousness of the childhood drinking issue.
The convergence of a number of recent public events and new scientific developments makes
this a particularly opportune and appropriate time to intensify our research, evaluation, and
outreach efforts to confront this critical public health issue. First, new findings from NIAAAsupported research indicate that the kind of serious drinking problems previously associated with
middle adulthood (including what has been called alcoholism) often begin to emerge during
adolescence and young adulthood. These findings, and other results that have enhanced our
understanding of alcohol consumption during adolescence, have led to a reconceptualization of
alcohol dependence.
We now believe that our science will advance optimally by investigating alcohol-related problems
in a developmental context. In fact, alcohol abuse and dependence are probably best
characterized as developmental disorders, with sequelae that play out throughout the life span.
Furthermore, neurobiological research suggests that adolescence may be a period of particular
vulnerability to the effects of alcohol.
In addition, the recent National Research Council and Institute of Medicine report, Reducing
Underage Drinking: A Collective Responsibility, underscores the dangers of underage drinking,
even when the level of drinking falls short of a diagnosable condition. This report also proposes a
strategy to begin to address this issue. Although we clearly must act now, it also is clear that our
currently limited understanding of how alcohol influences adolescent development will limit the
success of prevention and intervention efforts. For example, adolescents comprise a very diverse
population—a 13-year-old and a 17-year-old differ in many ways, both physically and
psychologically. Thus, a single approach for preventing underage drinking will likely be less
effective than multiple, developmentally appropriate approaches, even if the primary means for
reaching all adolescents is via their parents. To truly understand the risk and protective factors
for, and consequences of, alcohol consumption during the first decades of life, we must study
alcohol consumption as a developmental phenomenon that begins in childhood and continues
through adolescence and into young adulthood.
This issue of Alcohol Research & Health is a first step in NIAAA’s efforts to bring the
developmental perspective to bear upon the problem of underage drinking. In this special issue,
we review the many domains that have been shown by research to interface with alcohol
consumption by youth and evaluate the latest research findings in each of these domains.
Because a developmental perspective has yet to be fully integrated with research on alcohol and
youth, any present review of existing research necessarily must remain limited in this regard. For
this reason, since May 2004, NIAAA has been consulting with experts in biological and behavioral
development to attempt a significant advance in understanding the phenomenon of underage
drinking. To this end, scientists from NIAAA’s staff currently are at work with these developmental
scientists to produce a “next generation” report that will explicitly address how developmental
science can inform both (a) understanding of the origins of underage drinking and (b) strategic
planning to reduce the adverse outcomes suffered by our most precious resource, our children.
This new report will, for the first time, explicitly consider the issues involved with underage
drinking as a function of age and developmental stage. We anticipate this followup report to be
available in the spring of 2006.
In closing, we wish to enthusiastically acknowledge the 2004 report from the National Research
Council and the Institute of Medicine (IOM), Reducing Underage Drinking: A Collective
Responsibility. There are many areas of overlap between the articles in this issue of Alcohol
Research & Health and the IOM report, and some areas of divergence. In part because of the
availability of the earlier report and its extensive accompanying background material, the articles
included here could be limited to brief tutorials in many relevant areas of science, and could build
upon the earlier contributions by increasing coverage of biological and other laboratory findings.
We hope that this summary of recent scientific findings will help researchers and policymakers
move forward expeditiously to address the critical problem of underage drinking.
Vivian B. Faden, Ph.D.
Mark Goldman, Ph.D.
Co-Leaders,
NIAAA Interdisciplinary Team on Underage Drinking Research
October 2005
Acknowledgements
Outside Advisors
Adrian Angold, M.R.C. Psych
Duke University
Psychiatry and Behavioral Sciences
Box 3454, Brightleaf Square, Suite 22
Durham, NC 22710–3454
Professor Richard Bonnie
John S. Battle Professor of Law
Director, University of Virginia Institute of Law, Psychiatry and Public Policy
University of Virginia School of Law
P.O. Box 400405
Charlottesville, VA 22904–4405
Jane Brown, Ph.D.
James L. Knight Professor
Journalism/Mass Communications
360 Carroll Hall
University of North Carolina
Chapel Hill, NC 27514
Sandra Brown, Ph.D.
Professor of Psychology and Psychiatry
Department of Psychology, 0109
University of California, San Diego
9500 Gilman Drive
La Jolla, CA 92093–0109
Ronald E. Dahl, M.D.
Staunton Professor of Psychiatry and Pediatrics
Western Psychiatric Institute and Clinic
University of Pittsburgh
3811 O’Hara Street
Pittsburgh, PA 15213
Thomas J. Dishion, Ph.D.
Founder and Director of Research Child and Family Center
University of Oregon
195 North 12th Avenue
Eugene, OR 97401
John E. Donovan, Ph.D.
Department of Psychiatry
Western Psychiatric Institute and Clinic
University of Pittsburgh School of Medicine
3811 O’Hara Street
Pittsburgh, PA 15213
Cindy L. Ehlers, Ph.D.
Department of Neuropharmacology
The Scripps Research Institute
10550 N. Torrey Pines Road CVN–14
La Jolla, CA 92037
Mrs. Kendel Ehrlich
First Lady of Maryland
Office of the First Lady
State House
100 State Circle
Annapolis, MD 21401–1925
Ms. Mimi Fleury
Community of Concern
c/o Georgetown Preparatory School
10900 Rockville Pike
North Bethesda, MD 20852
Mrs. Nancy Freudenthal
First Lady of Wyoming
Office of the First Lady
5001 Central Avenue
Cheyenne, WY 82009–4011
Jay Giedd, M.D.
National Institutes of Health
National Institute of Mental Health
9000 Rockville Pike, MSC 1367
Bethesda, MD 20892–1367
Jennifer Lerner, Ph.D.
Department of Social and Decision Sciences
Carnegie Mellon University
208 Porter Hall
Pittsburgh, PA 15213
Christopher S. Martin, Ph.D.
Department of Psychiatry
Western Psychiatric Institute and Clinic
University of Pittsburgh School of Medicine
3811 O’Hara Street
Pittsburgh, PA 15213
Ann S. Masten, Ph.D.
Director, Institute of Child Development
University of Minnesota
51 East River Road
Minneapolis, MN 55455–0345
Matthew K. McGue, Ph.D.
Psychology Department
N218 Elliott Hall
University of Minnesota
75 East River Road
Minneapolis, MN 55455–0344
Frank A. Middleton, Ph.D.
Assistant Professor
Departments of Psychiatry and Neuroscience and Physiology
Director, Center for Neuropsychiatric Genetics
Director, Microarray Core Facility
State University of New York Upstate Medical University
750 East Adams Street
Syracuse, NY 13210
Stacia A. Murphy
President
National Council on Alcoholism and Drug Dependence, Inc.
20 Exchange Place, Suite 2902
New York, NY 10005
Daniel Pine, M.D.
Chief, Section on Development and Affective Neuroscience and Chief of Child and Adolescent
Research
Mood and Anxiety Disorders Program
National Institute of Mental Health
Building 15K, Room 110
Bethesda, MD 20892
John E. Schulenberg, Ph.D.
University of Michigan Institute for Social Research
P.O. Box 1248
Room 2138
Ann Arbor, MI 48106–1248
Kenneth J. Sher, Ph.D.
Professor
Department of Psychological Studies
University of Missouri
200 South Seventh Street
Columbia, MO 65211–0001
Linda Spear, Ph.D.
Distinguished Professor of Psychology
Chair of Department of Psychology
Binghamton University
State University of New York
P.O. Box 6000
Binghamton, NY 13902–6000
H. Scott Swartzwelder, Ph.D.
Professor of Psychiatry and Behavioral Sciences
Senior VA Research Career Scientist
Building 16, Room 24
VA Medical Center
508 Fulton Street
Durham, NC 27705
Susan F. Tapert, Ph.D.
Department of Psychiatry
University of California, San Diego
VA San Diego Healthcare System
3350 La Jolla Village Drive, 116B
San Diego, CA 92161
Michael Windle, Ph.D.
Professor of Psychology
University of Alabama-Birmingham Center for the Advancement of Youth Health
912 Building, 1530 3rd Avenue, South
Birmingham, AL 35294–1200
Robert A. Zucker, Ph.D.
Professor of Psychiatry and Psychology
Addiction Research Center
University of Michigan
400 East Eisenhower Pkwy., Suite 2A
Ann Arbor, MI 48108–3318
NIAAA Contributors
Charlotte Armstrong
Office of Research Translation and Communications
Judith Arroyo, Ph.D.
Division of Epidemiology and Prevention Research
Gregory Bloss, M.A.
Division of Epidemiology and Prevention Research
John Bowersox
Office of Research Translation and Communications
Gayle Boyd, Ph.D.
(now at Center for Scientific Review, NIH) Division of Epidemiology and Prevention Research
Vivian B. Faden, Ph.D.
Division of Epidemiology and Prevention Research
Thomas Gentry, Ph.D.
Division of Metabolism and Health Effects
David Goldman, M.D.
Division of Intramural Clinical and Biological Research
Mark Goldman, Ph.D.
Office of the Director
Roger Hartman, M.L.S.
Office of Research Translation and Communications
Ralph Hingson, Sc.D., M.P.H.
Division of Epidemiology and Prevention Research
Cherry Lowman, Ph.D.
Division of Treatment and Recovery Research
Howard Moss, M.D.
Office of the Director
Patricia Powell, Ph.D.
Office of Scientific Affairs
Gregory Roa
Office of Research Translation and Communications
Kathy Salaita, Ph.D.
(now at Center for Scientific Review, NIH) Division of Epidemiology and Prevention Research
Roger Sorensen, Ph.D.
Division of Neuroscience and Behavior
Ellen Witt, Ph.D.
Division of Neuroscience and Behavior
The Scope of the Problem
Alcohol is the drug of choice among youth, often with devastating consequences. Alcohol
is a leading contributor to injury death, the main cause of death for people under age 21.
Drinking early in life also is associated with an increased risk of developing an alcohol use
disorder at some time during the life span. Data consistently indicate that rates of drinking
and alcohol-related problems are highest among White and American Indian or Alaska
Native youth, followed by Hispanic youth, African Americans, and Asians. Prevalence
rates of drinking for boys and girls are similar in the younger age groups; among older
adolescents, however, more boys than girls engage in frequent and heavy drinking, and
boys show higher rates of drinking problems. This article summarizes research on the
epidemiology of youth drinking, including the consequences of youthful drinking, risk and
protective factors and drinking trajectories, and information on special populations at
particular risk for drinking-related problems. Key words: underage drinking; adolescent;
survey; AODU (alcohol and other drug use) pattern; binge drinking; AOD (alcohol and other drug)
induced risk; risk and protective factors; alcohol and other drug related (AODR) consequences;
AODR injury; epidemiology; special populations; children of alcoholics; undergraduate student;
military; ethnic group; gender differences
OVERVIEW
National surveys make it clear that alcohol drinking among youth is both widespread and harmful.
Surveys provide data not only on the numbers of middle and high school students who drink but
also on how they drink. The data show that when youth drink, they drink heavily in comparison
with adults, consuming on average four to five drinks per occasion about five times a month,
compared with two to three drinks per occasion about nine times a month for adults. Studies also
find that drinking often begins at very young ages; a recent survey found that more than onefourth of 14-year-olds reported drinking within the last year.
The negative consequences of underage drinking include a range of physical, academic, and
social problems. Perhaps most frightening, alcohol is the leading contributor to injury death, the
main cause of death for people under age 21. However, alcohol also plays a powerful role in risky
sexual behavior, including unwanted, unintended, and unprotected sexual activity, and sex with
multiple partners. Alcohol is associated with academic failure and drug use. Over the longer term,
data have shown that drinking early in life is associated with an increased risk of developing an
alcohol use disorder at some time during the life span.
Although almost all U.S. youth grow up in a culture permeated by alcohol, they are not uniformly
at risk for alcohol consumption or its consequences. Epidemiology provides clues to risk and
protective factors associated with youth drinking, including family history and genetic vulnerability,
comorbid conditions, sociodemographic characteristics, social stressors such as poverty and lack
of social support, family characteristics, alcohol availability, temperament, and other individual
factors. Epidemiology also provides a profile of how specific populations of young people differ in
their drinking patterns. Drinking, including heavy drinking, is common and accepted among
college students, with consequences affecting both those who do the drinking and those who do
not. Rates of heavy drinking among 18- to 25-year-olds in the military are much higher than
among civilians. There is considerable variation between Whites and other ethnic/racial minority
youth with respect to drinking, but also significant variation within these populations. Research is
needed to determine how national origin, tribal affiliation, acculturation, immigration status, and
language all influence drinking patterns among youth.
EPIDEMIOLOGY OF UNDERAGE DRINKING
Alcohol is the drug of choice among youth. Young people drink too much and at too early an age,
thereby creating problems for themselves, for people around them, and for society as a whole.
Hence, underage drinking is a leading public health problem in this country.
Prevalence and Age of Initiation
Nationwide surveys, as well as studies in smaller populations, show that alcohol drinking is
widespread among adolescents. For example, 2004 data from Monitoring the Future (MTF), an
annual survey of U.S. youth, show that more than three-fourths of 12th graders, nearly two-thirds
of 10th graders, and more than two in five 8th graders have consumed alcohol at some point in
their lives (Monitoring the Future Web site). And when youth drink, they tend to drink heavily.
Underage drinkers consume on average four to five drinks per occasion about five times a month
(Substance Abuse and Mental Health Services Administration [SAMHSA] 2003). By comparison,
adult drinkers ages 26 and older consume on average two to three drinks per occasion about
nine times a month. A particularly worrisome aspect of underage drinking is the high prevalence
of heavy episodic drinking, defined as drinking five or more drinks in a row in the past 2 weeks.
MTF data show that 12 percent of 8th graders, 22 percent of 10th graders, and 28 percent of 12th
graders engage in heavy episodic drinking (Johnston et al. 2004). It should come as no surprise,
then, that about three-fifths of 12th graders, two-fifths of 10th graders, and one-fifth of 8th graders
say they have been drunk (Monitoring the Future Web site). In fact, the highest prevalence of
dependence is seen in people ages 18–24.
Figure 1 Nationwide surveys, as well as studies in smaller
populations, show that drinking is widespread among people under
age 21.
Studies also indicate that drinking often begins at very young ages. Data from recent surveys
show that approximately 10 percent of 9- to 10-year-olds have already started drinking (Donovan
et al. 2004), nearly a third of youth begin drinking before age 13 (Grunbaum et al. 2004), and
more than one-fourth of 14-year-olds report drinking within the past year (SAMHSA 2003). Other
researchers have documented that drinking becomes increasingly common through the teenage
years (e.g., O’Malley et al. 1998). In addition, a number of studies have documented that the
early onset of alcohol use (usually set at age 13 and younger) as well as the escalation of
drinking in adolescence are both risk factors for the development of alcohol-related problems in
adulthood (e.g., Gruber et al. 1996; Grant and Dawson 1998; Hawkins et al. 1997; Schulenberg
et al. 1996a).
These findings clearly are cause for concern, as are recent data suggesting that the age of first
use of alcohol is declining (SAMHSA, National Household Survey on Drug Abuse [NHSDA] for
years prior to 2000). These data indicate that the average age of first use among young people of
all ages was about 16 in 1999, compared with about 17 1/2 in 1965 (SAMHSA 2003). Looking at
underage drinkers only, 12- to 18-year-olds who report drinking report that they began doing so
between 2 and 3 years earlier, when they were about 9 to 15, respectively (SAMHSA 2003). This
is important because, as already noted, initiating alcohol consumption earlier in adolescence or in
childhood is a marker for later problems, including heavier use of alcohol and other drugs during
adolescence (e.g., Robins and Przybeck 1985; Hawkins et al. 1997) and meeting criteria for an
alcohol dependence diagnosis in adulthood (Grant and Dawson 1998).
Most of what we know about underage drinking derives from studies of youth ages 12 to 21. To
address alcohol- related problems as developmental phenomena, we will need to understand
more about what happens before age 12 with regard to alcohol consumption, alcohol awareness,
and alcohol expectancies among children who have started to drink and among those who have
not. A recent Medline search found a dearth of studies addressing drinking by younger children,
and the few existing studies that turned up in this search were conducted among non-U.S.
populations. Two national data sets, however, address alcohol use by children in sixth grade or
below (typically age 12 and younger), albeit imperfectly and far from comprehensively. One is the
Partnership Attitude Tracking Study (PATS), carried out for the Partnership for a Drug-Free
America in 1993, and annually from 1995 through 1999. The other is the collection of PRIDE
surveys carried out during the academic years 1997–1998 through 2001–2002. PATS data reveal
a tripling of alcohol experience between fourth and sixth grade: 9.8 percent of fourth graders, 16.1
percent of fifth graders, and 29.4 percent of sixth graders report trying more than a sip of alcohol
(Donovan et al. 2004). PRIDE data show similar rates of use in this population. Despite
methodological problems with these data sets, PATS and PRIDE show that a nontrivial level of
alcohol consumption occurs among a significant proportion of the 12-and-under population.
Consequences
Underage drinking can result in a range of adverse short-term and long-term consequences,
including:










Academic problems
Social problems
Physical problems such as hangovers or medical illnesses
Unwanted, unintended, and unprotected sexual activity
Physical and sexual assault
Memory problems
Increased risk for suicide and homicide
Alcohol-related car crashes and other unintentional injuries such as burns, falls, and
drownings
Death from alcohol poisoning
Alterations in brain development that may have consequences reaching far beyond
adolescence.
Alcohol is a leading contributor to injury death, the main cause of death for people under age 21.
Annually, about 5,000 youth under age 21 die from alcohol-related injuries that involve underage
drinking. This includes injuries sustained in motor vehicle crashes (about 1,900), homicides
(about 1,600), and suicides (about 300), as well as unintentional injuries not related to motor
vehicle crashes (National Highway Traffic Safety Administration [NHTSA] 2003; Centers for
Disease Control and Prevention [CDC] 2004; Smith et al. 1999; Levy et al. 1999; Hingson and
Kenkel 2004). Furthermore, the role of alcohol in both fatalities and injuries may be significantly
underreported, in part because in many States, alcohol involvement in an injury relieves
insurance providers of liability for medical expenses, so health care providers may not ask victims
about, or report, alcohol use.
Numerous cases of alcohol poisoning, the result of the acute toxic effects of alcohol that can
range from gastritis to severe gastrointestinal bleeding to respiratory arrest and death, have been
reported in the news media. Although many of these tragedies occur on college campuses,
especially striking was the recent report of two 11-year-old boys found dead of alcohol poisoning
in a snowy field on the Flathead Indian Reservation in Montana, with blood alcohol concentration
(BAC) levels of 0.20 percent and 0.50 percent. Although alcohol poisoning is by no means a
major cause of death among youth, reports such as this underscore the tragic influence that
hazardous drinking can wield over youth culture.
In the National Longitudinal Alcohol Epidemiologic Survey (NLAES) of people ages 18 and older
in the United States, people who reported starting to drink before the age of 15 were four times
more likely to also report meeting the criteria for dependence at some point in their lives (Grant
and Dawson 1998). This survey also shows that children who drink at age 14 or younger are
much more likely during their lifetimes to sustain unintentional injuries, to get into physical fights,
and to become involved in motor vehicle crashes after drinking (Hingson et al. 2000, 2001, 2002).
TEXT BOX
Consequences of Underage Drinking:
Mortality From Alcohol-Related Injuries
Annually, about 5,000 people under age 21 die
from alcohol-related injuries involving underage
drinking, including:



Motor vehicle crashes – 1,900
Homicides – 1,600
Suicides – 300
SOURCE: National Highway Traffic Safety
Administration 2003; Centers for Disease
Control and Prevention 2004; Smith et al. 1999;
Levy et al. 1999; Hingson and Kenkel 2004. All
statistics are approximate.
END OF TEXT BOX
Similarly, other survey data indicate that the younger children and adolescents are when they
start to drink, the more likely they are to engage in behaviors that can harm themselves and
others (Grunbaum et al. 2004). Those who start to drink before age 13, for example, are nine
times more likely to binge1 drink frequently (five or more drinks on an occasion at least six times
per month) as high school students than those who begin drinking later. ( 1 SAMHSA’s definitions
of binge and heavy drinking: binge drinkers report that they had consumed five or more drinks on
the same occasion at least once in the past 30 days; heavy drinkers report that they had
consumed five or more drinks on the same occasion on at least 5 different days in the past 30
days (SAMHSA 2003). The National Institute on Alcohol Abuse and Alcoholism’s (NIAAA’s)
definition of binge drinking: a “binge” is a pattern of drinking alcohol that brings blood alcohol
concentration (BAC) to 0.08 grams percent or above. For the typical adult, this pattern
corresponds to consuming five or more drinks (men), or four or more drinks (women), in about 2
hours. Binge drinking is clearly dangerous for the drinker and for society. [The NIAAA National
Advisory Council approved this definition of binge drinking on February 5, 2004.]) And compared
with nondrinkers, a greater proportion of frequent binge drinkers (nearly 1 million high school
students nationwide) engaged in other risky behavior in the past 30 days (Grunbaum et al. 2004),
including carrying a gun (22 percent vs. 3 percent), using marijuana (73 percent vs. 7 percent),
using cocaine (26 percent vs. 0 percent), and having sex with six or more partners (31 percent vs.
4 percent). In addition, these youth were more likely than abstainers to earn grades that are
mostly Ds or Fs in school (15 percent vs. 5 percent), be injured in a fight (13 percent vs. 2
percent), or be injured in a suicide attempt (9 percent vs. 1 percent). The extent to which alcohol
use per se makes these other outcomes more likely is yet to be determined. However, the
longitudinal evidence is very strong that the risk factors predicting earlier alcohol use also are
strong predictors of virtually all of these other consequences (Biglan et al. 2004; Caspi et al.
1997).
Risk Trajectories and Drinking Trajectories
Not only do youth begin drinking at different ages but their trajectories of risk also vary
considerably, even before alcohol use has begun. Recent work following high-risk populations of
children from preschool onward has shown major differences in the trajectories of externalizing
and internalizing risk from preschool to early adolescence. These varied as a function of initial
level of risk in early childhood, the child’s age, and the level of familial risk. Particularly for the
externalizing trajectory, children who started out at very high levels of individual and familial risk
became indistinguishable from those at lower levels during the early school years, but as these
youth moved into early adolescence, the differences reemerged and became amplified, with the
highest-risk children increasing the greatest amount (Zucker et al. 2003). Conversely, the
externalizing behavior of children at the lowest level of initial risk who were exposed to the lowest
level of familial risk changed the least, although even they increased in level of externalizing
behavior as they moved into adolescence.
Similarly, the drinking patterns and practices youth adopt as they grow into young adults—their
drinking trajectories—also vary considerably once they start to drink. No single trajectory
describes the course of alcohol use for all or even most young people. Research findings provide
strong evidence for wide developmental variation in drinking patterns in the population. For
example, Steinman and Schulenberg (2003) identified six common trajectories among early and
middle adolescents: abstinence, rare use, high school onset, early but nonescalating use, early
and gradually escalating use, and consistently high use. In another study, Schulenberg and
colleagues (1996b) identified six trajectories of heavy drinking among young people ages 18 to
24: chronic heavy drinkers, decreased, increased, fling (i.e., low, high, low), rare, and never. In
addition, alcohol abuse treatment (Chung et al. 2003) and other experiences may influence
drinking trajectories. Studying the developmental trajectories of drinking behavior and how
various risk and protective factors influence those trajectories is critical to understanding the
complexity of underage drinking.
Figure 2 Alcohol use by youth is an international phenomenon. The 2003 European
School Survey Project on Alcohol and Other Drugs (ESPAD) surveyed 15-year-olds
in 35 European countries where legal drinking ages are lower (typically ages 16–18)
than in the United States. The ESPAD questions were similar to those used with
10th graders in the U.S. Monitoring the Future study. In all European countries
except the predominantly Moslem nation of Turkey, a greater percentage of 15-yearolds drank alcohol than in the United States; and in more than three-quarters of the
countries, a greater percentage reported drinking to intoxication in the previous year
than in the United States.
SOURCE: http://www.espad.org/reports.html
SPECIAL POPULATIONS OF YOUNG PEOPLE
Children of Alcoholics
Children of alcoholics (COAs) are between 4 and 10 times as likely to become alcoholics
themselves as children from families that have no adults with alcoholism (Russell 1990). COAs
are at elevated risk for earlier onset of drinking (Donovan et al. 2004) and earlier progression into
drinking problems (Grant and Dawson 1998). Some of the elevated risk is attributable to
exposure and socialization effects found in alcoholic households, some to genetically transmitted
differences in response to alcohol that make the drinking more pleasurable and/or less aversive,
and some is attributable to elevated transmission of risky temperamental and behavioral traits
that lead COAs, more than other youth, into increased contact with earlier-drinking and heavierdrinking peers.
From a public health standpoint, according to NLAES data (Grant 2000), approximately 9.7
million children age 17 or younger, or 15 percent of the child population in that age range, were
living in households with one or more adults classified as having an alcohol abuse or dependence
diagnosis during the past year. Approximately 70 percent of these children were biological, foster,
adopted, or stepchildren. That is, 6.8 million children meet the formal definition of COA, although
not all are exposed to the same level of risk for use, problem use, and alcohol use disorder
(AUD). Given that these figures concern past-year exposure to at least one alcoholic adult, from
the perspective of socialization risk, they only reflect acute exposure. Other data from NLAES
provide estimates of the number of children living in a household with an adult who had abused or
been dependent on alcohol at some point; the figure is 43 percent of the under-18 population, or
somewhat less than half of all children. Given the size of this group, any approach to risk
identification will be extremely complex.
A second important consideration is that COA status is heavily used as a proxy for “alcoholism
risk” on the one hand and socialization risk on the other, but the COA designation more precisely
is a proxy for multiple causal inputs, not all of which may be present in the individual case. Thus,
being a COA implies elevated genetic risk, although the alcoholic genetic diatheses may not have
been passed on to a particular child. One may be a COA without being undercontrolled, having
an attention deficit hyperactivity disorder diagnosis, or other problems known to be associated
with increased risk of alcohol dependence.
Socialization risk involves exposure, but given the high divorce rates found in this population,
evaluating the level of socialization risk is complex, involving both the quantification of the length
of the exposure and the identification of the developmental period during which the socialization
took place. Vulnerability is greater during some developmental periods than others (Fuller et al.
2003). In addition, a substantial amount of marital assortment occurs in alcoholic families
(Schuckit et al. 2002). When assortment is present, risk exposure is multiplied, and COA effects
become a function of genetic risk(s), individual parent risk, and the synergistic risk created by
marital interaction (Fuller et al. 2003).
SIDEBAR
Risk and Protection
Although almost all U.S. youth grow up in a culture permeated by alcohol, they are not uniformly
at risk for alcohol consumption or its consequences. Much research has addressed the risk and
protective factors associated with youth drinking. These factors include but are not limited to
family history and genetic vulnerability, comorbid conditions and their developmental
antecedents, sociodemographic characteristics, social stressors such as poverty and lack of
social support, family characteristics, alcohol availability, temperament, and other individual
factors. Some of the most consistently documented epidemiologic findings regarding the
association of alcohol consumption and other factors are presented in the following brief
overview.
Data from general population surveys of youth, as well as data from smaller, more localized
studies, consistently indicate that rates of drinking and alcohol-related problems are highest
among White and American Indian or Alaska Native youth, followed by Hispanic youth, African
Americans, and Asians. Likewise, studies uniformly indicate that alcohol consumption generally
increases as a person’s age increases. Prevalence rates of drinking for boys and girls are similar
in the younger age groups; among older adolescents, however, more boys than girls engage in
frequent and heavy drinking, and boys show higher rates of drinking problems. Other common
findings are a strong association between conduct problems and earlier alcohol consumption, and
youth with a family history of alcohol problems are at much greater risk both for problem use and
later alcohol use disorders. Studies also show that underage drinkers generally possess more
than one risk factor and exhibit clusters of problem behaviors.
The scientific literature on risk and protective factors for underage drinking reveals important
conceptual as well as methodological issues. For example, many such risk factors have been
identified solely on the basis of their association with drinking and its consequences. This
association is not sufficient evidence, however, to prove that something actually increases risk
for, or protection from, underage drinking. Some scientists, therefore, advocate a stricter
definition of risk/protective factors (e.g., Donovan 2004). The term “risk factor,” for example,
would apply only to variables for which there is a statistically significant link to the onset of
adolescent alcohol use as well as evidence that any such variable was present prior to the onset
of drinking (Donovan 2004). Furthermore, “alcohol consumption” encompasses not just one but
numerous phenomena. Finally, it is important to be aware that many of the risk factors predicting
early drinking are not drinking variables but instead are more nonspecific characteristics, such as
externalizing and internalizing problems, that are identifiable much earlier than the first drinking
experience but represent high-risk pathways into earlier use (NIAAA 2000; Zucker and Wong
2005). We therefore need to more precisely define those risk/protective factors that apply to the
initiation of drinking, to the escalation of drinking, to risky drinking, and to other aspects of
consumption.
References
Donovan, J.E. Adolescent alcohol initiation: A review of psychosocial risk factors. Journal of
Adolescent Health 35:529.e7–18, 2004.
National Institute on Alcohol Abuse and Alcoholism (NIAAA). Alcohol involvement over the life
course. In: Tenth Special Report to the U.S. Congress on Alcohol and Health: Highlights From
Current Research. Bethesda, MD: Dept. of Health and Human Services, NIAAA, 2000. pp. 28–53.
Available online at: http://pubs.niaaa.nih.gov/publications/10report/intro.pdf.
Zucker, R.A., and Wong, M.M. Prevention for children of alcoholics and other high risk groups. In:
Galanter, M., ed. Recent Developments in Alcoholism, Vol. 17: Alcohol Problems in Adolescents
and Young Adults: Epidemiology, Neurobiology, Prevention, Treatment. New York: Springer,
2005. pp. 299–320. PMID: 15789872
END OF SIDEBAR
Third, the potential for indirect socialization effects also is higher in COAs than in other children.
Parental psychopathology has been documented as a risk factor for poorer parental monitoring
(Chilcoat et al. 1996), which in turn leads to a higher probability of involvement with a deviant
peer group, including earlier exposure to alcohol and other drugs.
Fourth, COA risk is not simply risk for the development of AUD (Zucker and Wong 2005). Given
what is known about the elevated comorbidities found among offspring of alcoholics, this
designator also is a marker of elevated risk for behavioral and cognitive deficits. These include
attention deficit disorder, behavioral undercontrol/conduct disorder, delinquency, lower IQ, poor
school performance, low self-esteem, and other problems (Noll et al. 1992; Nigg et al. 1998; Poon
et al. 2000; Sher 1991; West and Prinz 1987). Furthermore, the evidence strongly implicates
some of these non-alcohol-specific characteristics as causal to both problem alcohol use and
elevated risk for AUD (Caspi et al. 1997; Donovan and Jessor 1985; Nigg et al. 1998).
These factors implicate the COA population as an important component of the underage drinking
population. For the same reasons, however, it is essential to determine which components of that
risk composite are the strongest mediators of the underage drinking outcome.
College Students
College students are a highly visible group of underage drinkers among whom alcohol
consumption is commonplace. Indeed, many college students accept alcohol use as a normal
part of student life. Studies consistently indicate that about four in five college students drink
alcohol; about two in five engage in episodic heavy consumption, often called bingeing (five or
more drinks in a row for men and four or more in a row for women; generally asked with respect
to the past 2 weeks or past 30 days, depending on the survey); and about one in five engages in
frequent episodic heavy consumption (bingeing three or more times in the past 2 weeks) (NIAAA
2002).
The consequences of drinking among college students include academic problems, social
problems, legal problems, involvement in physical and/or sexual assault or risky sex, and even
death. An estimated 1,700 college students between the ages of 18 and 24 die each year from
alcohol-related unintentional injuries including motor vehicle crashes (Hingson et al. 2005).
Another 599,000 students are unintentionally injured while under the influence of alcohol, 696,000
are assaulted by other students who have been drinking, and 97,000 are victims of alcoholrelated sexual assault or date rape (Hingson et al. 2005). A striking number of college students
also report having experienced alcohol-induced memory blackouts. One recent study indicated
that among nonabstaining college students, 40 percent reported experiencing a blackout within
the past year, and 9.4 percent reported having a blackout within the past 2 weeks (White et al.
2002). This could relate to students’ tendency to be unaware of standard drink volumes and to
overpour drinks, thus underestimating their consumption (White et al. 2003). It is not known if
younger drinkers are more susceptible to the memory-impairing effects of alcohol, but one study
in humans showed that a dose of alcohol resulting in a BAC in the range of 80 mg/dl significantly
disrupted learning in people in their early twenties but had little effect on people in their late
twenties (Acheson et al. 1998).
Drinking in college varies from campus to campus and from person to person. Levels and
patterns of consumption are associated with individual, intracampus, and intercampus factors.
For example, athletes and members of fraternities and sororities are among the heaviest drinkers
on most campuses, and students in the Northeast and on campuses where athletics and Greek
organizations are prominent tend to drink more than their counterparts at other institutions
(NIAAA 2002).
Underage and Youthful Drinking Among Military Personnel
The Department of Defense (DOD) conducts periodic surveys to assess alcohol use and other
health-related behaviors among military personnel. Approximately 193,000 of 1.4 million active
duty military personnel are between the ages of 17 and 20. These surveys, therefore, provide
important information about underage drinking in an important subset of young people. According
to the 2002 DOD survey (the most recent one for which results have been released):



33.3 percent of military personnel age 20 and younger are “abstainers” (drink once a year
or less).
15.7 percent are “infrequent/light” drinkers (one to four drinks per typical occasion, one to
three times per month).
10.4 percent are “moderate” drinkers (one drink per typical drinking occasion at least
once a week, or two to four drinks per typical drinking occasion two to three times per
month, or five or more drinks per typical drinking occasion once a month or less).


14.4 percent are “moderate/heavy” drinkers (two to four drinks per typical drinking
occasion at least once a week or five or more drinks per typical drinking occasion two to
three times per month).
26.1 percent are “heavy” drinkers (five or more drinks per typical drinking occasion at
least once a week).
A comparison of data from the 2002 DOD survey with data from the 2001 NHSDA (in which
heavy alcohol use is defined as five or more drinks on one occasion on 5 or more days in the past
30 days) indicates that rates of heavy drinking among 18- to 25-year-olds in the military are
higher than for civilians of the same age (32.2 percent vs. 17.8 percent for men and 8.1 percent
vs. 5.5 percent for women).
The surveys conducted by the DOD also indicate that substantial numbers of youth in the military
experience negative consequences from drinking. The 2002 data show that, during the 12
months prior to the survey, more than one-fifth of the most junior enlisted personnel (who typically
are between the ages of 17 and 20) experienced serious consequences as a result of drinking or
a drinking-related illness, including military punishment, alcohol-related arrest, and the need for
detoxification, and that more than one-fourth experienced a productivity loss because of alcohol
use. DOD investigators classified more than one-fifth of survey participants as alcohol
“dependent” based on the number of days during the previous 12 months that they reported (1)
withdrawal symptoms, (2) inability to recall things that happened while drinking, (3) inability to
stop drinking before becoming drunk, or (4) morning drinking.
Minority Youth
According to national surveys, there is considerable variation between Whites and ethnic/racial
minorities with respect to alcohol consumption. Minority youth generally start drinking at older
ages than their White non-Hispanic counterparts. A greater difference also exists in levels of
drinking between male and female minority youth and a greater percentage of minority youth
abstain or drink very little (Vega et al. 1993). Although a “typical” pattern of underage drinking
could never be attributed to any specific minority group, it is useful to compare minority groups to
identify potential risk and protective factors that may be operating to produce some of the
observed differences in drinking practices. With a burgeoning minority population, it is also
essential to better understand these factors to help design and implement the most effective
prevention and intervention programs.
Data from a recent nationwide survey reveal that about three-fourths of White, American Indian,
and Hispanic high school seniors used alcohol in the past year. More than 6 percent of American
Indian and 5 percent of Mexican and Cuban American seniors report daily drinking, compared
with 1 percent to 3.8 percent for all other groups (Wallace et al. 2002). The limited data on
Hispanic and American Indian adults suggest that, among those who drink, there is a tendency
toward high average intake per drinking day. Youth survey data suggest that some students
establish a pattern of heavy drinking by their senior year of high school. About 60 percent of
African American and about 57 percent of Asian American high school seniors report having used
alcohol in the past 12 months, and about 32.5 percent in both groups report having used it in the
past 30 days. However, there appears to be a “cross-over” effect for African Americans. That is,
even though they use less alcohol as youths than their non-Hispanic White counterparts, rates of
heavy and problem drinking among African American adults, especially males, are higher than for
non-Hispanic Whites.
Studies of race and ethnicity should be conducted with sufficiently large and diverse samples to
allow investigators to assess variations in drinking by national origin or tribal affiliation,
acculturation, immigration status, and language. Significant variation exists among Hispanics and
among American Indians. Recent evidence indicates that members of some American Indian
groups are more likely to abstain than are people in the general U.S. population. Like their
Mexican American counterparts, American Indian drinkers, however, consume more alcohol per
drinking occasion (Beals et al. 2003). In addition, although Asian Americans often are considered
the “model minority,” with low rates of alcohol use, most current literature does not include data
from rapidly growing at-risk Asian groups such as Southeast Asians, Koreans, and Filipinos, or
groups believed to have higher rates of alcohol use, such as Native Hawaiians and other Pacific
Islanders (Zane and Sasao 1992).
Although there is clear evidence of genetic variability in alcohol metabolism, we have yet to fully
understand the interplay of genetic and environmental variables. For example, the inability to
metabolize alcohol efficiently, deemed a protective factor in a subset of the Asian population
because of the unpleasant effects of drinking, often results in facial flushing. Highlighting the
complexity of the interplay between genetic and environmental variables is the observation that
Asian American drinking often increases with level of acculturation in spite of the flushing
response (Sue et al. 1979).
REFERENCES
Acheson, S.K.; Stein, R.M.; and Swartzwelder, H.S. Impairment of semantic and figural memory
by acute ethanol: Age-dependent effects. Alcoholism: Clinical and Experimental Research
22:1437–1442, 1998. PMID: 9802525
Beals, J.; Spicer, P.; Mitchell, C.M.; et al. and the AI-SUPERPFP Team. Racial disparities in
alcohol use: Comparison of 2 American Indian reservation populations with national data.
American Journal of Public Health 93:1683–1685, 2003. PMID: 14534221
Biglan, A.; Brennan, P.A.; Foster, S.L.; et al. Helping Adolescents at Risk: Prevention of Multiple
Problem Behaviors. New York: Guilford, 2004.
Caspi, A.; Begg, D.; Dickson, N.; et al. Personality differences predict health-risk behaviors in
young adulthood: Evidence from a longitudinal study. Journal of Personality and Social
Psychology 73(5):1052–1063, 1997. PMID: 9364760
Centers for Disease Control and Prevention (CDC) National Center for Injury Prevention and
Control (NCIPC). Web-Based Injury Statistics Query and Reporting System (WISQARS), 2004.
Available online at: http://www.cdc.gov/ncipc/wisqars/default.htm.
Chilcoat, H.D.; Breslau, N.; and Anthony, J.C. Potential barriers to parent monitoring: Social
disadvantage, marital status, and maternal psychiatric disorder. Journal of the American Medical
Academy of Child & Adolescent Psychiatry 35:1673–1682, 1996. PMID: 8973075
Chung, T.; Martin, C.S.; Grella, C.E.; et al. Course of alcohol problems in treated adolescents.
Alcoholism: Clinical and Experimental Research 27:253–261, 2003. PMID: 12605074
Donovan, J.E. Adolescent alcohol initiation: A review of psychosocial risk factors. Journal of
Adolescent Health 35:529.e718, 2004. PMID: 15581536
Donovan, J.E., and Jessor, R. Structure of problem behavior in adolescence and young
adulthood. Journal of Consulting and Clinical Psychology 53:890–904, 1985. PMID: 4086689
Donovan, J.E.; Leech, S.L.; Zucker, R.A.; et al. Really underage drinkers: Alcohol use among
elementary students. Alcoholism: Clinical and Experimental Research 28:341–349, 2004. PMID:
15112942
Fuller, B.E.; Chermack, S.T.; Cruise, K.A.; et al. Predictors of aggression across three
generations among sons of alcoholics: Relationships involving grandparental and parental
alcoholism, child aggression, marital aggression and parenting practices. Journal of Studies on
Alcohol 64:472–483, 2003. PMID: 12921189
Grant, B.F. Estimates of U.S. children exposed to alcohol abuse and dependence in the family.
American Journal of Public Health 90:112–115, 2000. PMID: 10630147
Grant, B.F., and Dawson, D.A. Age at onset of drug use and its association with DSM–IV drug
abuse and dependence: Results from the National Longitudinal Alcohol Epidemiologic Survey.
Journal of Substance Abuse 10:163–173, 1998. PMID: 9854701
Gruber, E.; DiClemente, R.J.; Anderson, M.M.; and Lodico, M. Early drinking onset and its
association with alcohol use and problem behavior in late adolescence. Preventive Medicine
25:293–300, 1996. PMID: 8781007
Grunbaum, J.A.; Kann, L.; Kinchen, S.; et al. Youth risk behavior surveillance—United States,
2003. Morbidity and Mortality Weekly Report Surveillance Summary, May 21;53:1–96, 2004.
Erratum in MMWR, 2004 June 25;53:536. Erratum MMWR Morbidity and Mortality Weekly Report
2005 June 24; 54(24):608. PMID: 15152182
Hawkins, J.D.; Graham, J.W.; Maguin, E.; et al. Exploring the effects of age of alcohol use
initiation and psychosocial risk factors on subsequent alcohol misuse. Journal of Studies on
Alcohol 58:280–290, 1997. PMID: 9130220
Hingson, R., and Kenkel, D. Social, health, and economic consequences of underage drinking. In:
National Research Council and Institute of Medicine. Bonnie, R.J., and O’Connell, M.E., eds.
Reducing Underage Drinking: A Collective Responsibility. Washington, DC: National Academies
Press, 2004. pp. 351–382. Available online at: http://www.nap.edu/books/0309089352/html.
Hingson, R.W.; Heeren, T.; Jamanka, A.; and Howland, J. Age of drinking onset and unintentional
injury involvement after drinking. JAMA: Journal of the American Medical Association 284:1527–
1533, 2000. PMID: 11000646
Hingson, R.; Heeren, T.; and Zakocs, R. Age of drinking onset and involvement in physical fights
after drinking. Pediatrics 108:872–877, 2001. PMID: 11581438
Hingson, R.; Heeren, T.; Levenson, S.; et al. Age of drinking onset, driving after drinking, and
involvement in alcohol-related motor vehicle crashes. Accident Analysis and Prevention 34:85–
92, 2002. PMID: 11789578
Hingson, R.W.; Heeren, T.; Winter, M.; and Wechsler, H. Magnitude of alcohol-related mortality
and morbidity among U.S. college students age 18-24: Changes from 1998 to 2001. Annual
Review of Public Health 26:259–279, 2005. PMID: 15760289
Johnston, L.D.; O’Malley, P.M.; and Bachman, J.G. Monitoring the Future, National Survey
Results on Drug Use, 1975–2002. Volume I: Secondary School Students. NIH Pub. No. 03–5375.
Bethesda, MD: National Institute on Drug Abuse, 2003. Available online at:
http://monitoringthefuture.org/pubs/monographs/vol1_2002.pdf .
Johnston, L.D.; O’Malley, P.M.; Bachman, J.G.; and Schulenberg, J.E. Monitoring the Future,
National Survey Results on Drug Use, 1975–2003. Volume I: Secondary School Students. NIH
Pub. No. 04–5507. Bethesda, MD: National Institute on Drug Abuse, 2004. Available online at:
http://monitoringthefuture.org/pubs/monographs/vol1_2003.pdf .
Johnston, L.D.; O’Malley, P.M.; Bachman, J.G.; and Schulenberg, J.E. Monitoring the Future,
National Survey Results on Drug Use, 1975–2004. Volume I: Secondary School Students. NIH
Pub. No. 05–5727. Bethesda, MD: National Institute on Drug Abuse, 2004. Available online at:
http://monitoringthefuture.org/pubs/monographs/vol1_2004.pdf.
Levy, D.T.; Miller, T.R.; and Cox, K.C. Costs of Underage Drinking. Washington, DC: U.S. Dept.
of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention,
1999. Available online at: http://www.udetc.org/documents/costunderagedrinking.pdf.
Monitoring the Future Web site. http://www.monitoringthefuture.org/data/data.html.
National Highway Traffic Safety Administration (NHTSA). Traffic Safety Facts 2002: Alcohol. DOT
Pub. No. HS–809–606. Washington, DC: NHTSA, National Center for Statistics & Analysis, 2003.
Available online at: http://www-nrd.nhtsa.dot.gov/pdf/nrd-30/NCSA/TSF2002/2002alcfacts.pdf.
National Institute on Alcohol Abuse and Alcoholism (NIAAA). Drinking in the United States: Main
Findings from the 1992 National Longitudinal Alcohol Epidemiologic Survey (NLAES). NIH Pub.
No. 99–3519. U.S. Alcohol Epidemiologic Data Reference Manual, Vol. 6. Rockville, MD: NIAAA,
1998. Available online at: http://pubs.niaaa.nih.gov/publications/Nlaesdrm.pdf.
National Institute on Alcohol Abuse and Alcoholism (NIAAA). Alcohol involvement over the life
course. In: Tenth Special Report to the U.S. Congress on Alcohol and Health: Highlights From
Current Research. Bethesda, MD: Dept. of Health and Human Services, NIAAA, 2000. pp. 28–53.
Available online at: http://pubs.niaaa.nih.gov/publications/10report/intro.pdf .
National Institute on Alcohol Abuse and Alcoholism (NIAAA). High-Risk Drinking in College: What
We Know and What We Need To Learn. Final Report of the Panel on Contexts and
Consequences, Task Force of the National Advisory Council on Alcohol Abuse and Alcoholism.
Bethesda, MD: Dept. of Health and Human Services, 2002. Available online at:
http://www.collegedrinkingprevention.gov/Reports/Panel01/Panel01_TOC.aspx.
Nigg, J.T.; Hinshaw, S.P.; Carte, E.T.; and Treuting, J.J. Neuropsychological correlates of
childhood attention-deficit/hyperactivity disorder: Explainable by comorbid disruptive behavior or
reading problems? Journal of Abnormal Psychology 107:468–480, 1998. PMID: 9715582
Noll, R.B.; Zucker, R.A.; Fitzgerald, H.E.; and Curtis, W.J. Cognitive and motoric functioning of
sons of alcoholic fathers and controls: The early childhood years. Developmental Psychology
28:665–675, 1992.
O’Malley, P.M.; Johnston, L.D.; and Bachman, J.G. Alcohol use among adolescents. Alcohol
Health & Research World 22(2):85–93, 1998. PMID: 15706782
Poon, E.; Ellis, D.A.; Fitzgerald, H.E.; and Zucker, R.A. Intellectual, cognitive, and academic
performance among sons of alcoholics, during the early school years: Differences related to
subtypes of familial alcoholism. Alcoholism: Clinical and Experimental Research 24:1020–1027,
2000. PMID: 10924005
Robins, L.N., and Przybeck, T.R. Age of onset of drug use as factor in drug and other disorders.
In: Jones, C.L., and Battjes, R.J., eds. Etiology of Drug Abuse: Implications for Prevention. NIDA
Research Monograph No. 56. Rockville, MD: National Institute on Drug Abuse, 1985. pp. 178–
192. Available online at: http://www.drugabuse.gov/pdf/monographs/56.pdf.
Russell, M. Prevalence of alcoholism among children of alcoholics. In: Windle, M., and Searles,
J.S., eds. Children of Alcoholics: Critical Perspectives. New York: Guilford, 1990. pp. 9–38.
Schuckit, M.A.; Smith, T.L.; Eng, M.Y.; and Kunovac, J. Women who marry men with alcohol-use
disorders. Alcoholism: Clinical and Experimental Research 26:1336–1343, 2002. PMID: 12351927
Schulenberg, J.E.; Wadsworth, K.N.; O’Malley, P.M.; and Bachman, J.G. Adolescent risk factors
for binge drinking during the transition to young adulthood: Variable- and pattern-centered
approaches to change. Developmental Psychology 32:659–674, 1996a.
Schulenberg J.; O’Malley, P.M.; Bachman, J.G.; et al. Getting drunk and growing up: Trajectories
of frequent binge drinking during the transition to young adulthood. Journal of Studies on Alcohol
57:289–304, 1996b. PMID: 8709588
Sher, K.J. Children of Alcoholics: A Critical Appraisal of Theory and Research. Chicago:
University of Chicago Press, 1991.
Smith, G.S.; Branas, C.C.; and Miller, T.R. Fatal nontraffic injuries involving alcohol: A metaanalysis. Annals of Emergency Medicine 33:659–668, 1999. PMID: 10339681
Steinman, K.J., and Schulenberg, J. A pattern-centered approach to evaluating substance use
prevention programs. In: Damon, W.; Peck, S.C.; and Roeser, R.W.; eds. New Directions for
Child and Adolescent Development, Vol. 101: Person-Centered Approaches to Studying
Development in Context. San Francisco: Jossey-Bass, 2003. pp. 87–98.
Substance Abuse and Mental Health Services Administration (SAMHSA). Results from the 2002
National Survey on Drug Use and Health: National Findings. NHSDA Series H–22, DHHS Pub.
No. SMA 03–3836. Rockville, MD: SAMHSA, Office of Applied Studies, 2003. Available online at:
http://www.oas.samhsa.gov/nhsda/2k2nsduh/Results/2k2Results.htm.
Sue, S.; Zane, N.; and Ito, J. Alcohol drinking patterns among Asian and Caucasian Americans.
Journal of Cross-Cultural Psychology 10:41–56, 1979.
Vega, W.A.; Zimmerman, R.S.; Warheit, G.J.; et al. Risk factors for early adolescent drug use in
four ethnic and racial groups. American Journal of Public Health 83:185–189, 1993. PMID:
8427320
Wallace, J.M., Jr.; Bachman, J.G.; O’Malley, P.M.; et al. Tobacco, alcohol, and illicit drug use:
Racial and ethnic differences among U.S. high school seniors. Public Health Reports 117(Suppl.
1):S67–S75, 2002. PMID: 12435829
West, M.O., and Prinz, R.J. Parental alcoholism and childhood psychopathology. Psychological
Bulletin 102:204–218, 1987. PMID: 3310059
White, A.M.; Jamieson-Drake, D.W.; and Swartzwelder, H.S. Prevalence and correlates of
alcohol-induced blackouts among college students: Results of an e-mail survey. Journal of
American College Health 51:117–119; 122–131, 2002. PMID: 12638993
White, A.M.; Kraus, C.L.; McCracken, L.A.; and Swartzwelder, H.S. Do college students drink
more than they think? Use of a free-pour paradigm to determine how college students define
standard drinks. Alcoholism: Clinical and Experimental Research 27:1750–1756, 2003. PMID:
14634490
Zane, N., and Sasao, I. Research on drug abuse among Asian Pacific Americans. Drugs and
Society 6:181–209, 1992.
Zucker, R.A., and Wong, M.M. Prevention for children of alcoholics and other high-risk groups. In:
Galanter, M., ed. Recent Developments in Alcoholism, Vol. 17: Alcohol Problems in Adolescents
and Young Adults: Epidemiology, Neurobiology, Prevention, Treatment. New York: Springer,
2005. pp. 299–320. PMID: 15789872
Zucker, R.A.; Wong, M.M.; Puttler, L.I.; and Fitzgerald, H.E. Resilience and vulnerability among
sons of alcoholics: Relationship to developmental outcomes between early childhood and
adolescence. In: Luthar, S.S., ed. Resilience and Vulnerability: Adaptation in the Context of
Childhood Adversities. New York: Cambridge University Press, 2003. pp. 76–103.
Developmental Issues in Underage Drinking
Research
To better understand underage drinking and how it can be prevented, research is being
conducted in a wide variety of disciplines—focusing on aspects such as risk and
protective factors, biological processes underlying human development, and the impact of
socioenvironmental and pharmacologic influences on these mechanisms. This article
examines underage drinking from a developmental perspective, which seeks to identify
critical developmental periods during which interventions may be especially useful. These
critical periods can provide key opportunities to redirect the course of development and
alter the life course trajectory of the individual. Key words: underage drinking; adolescence;
growth and development; biological maturation; psychological development; brain; cognitive
development; risk factors; protective factors; social adjustment; peer group; gender differences;
intervention; prevention; statistical modeling
OVERVIEW
A mix of many different kinds of factors underlies the development of problem drinking in
adolescents. For this reason, research focusing on any one area is likely to miss the complex
interactions that shape how an adolescent will respond to the availability of alcohol.
Research that takes a developmental perspective seeks to provide an understanding of behavior
in the context of the changes that take place during human maturation. The developmental
perspective assumes interactions that not only are complex but that change over time.
The speed and timing of development are not uniform. The biologically based ability of a person
to regulate mood as well as outwardly directed behavior, for example, changes during
adolescence as the brain matures. The progress of these changes can affect how well an
adolescent handles the tasks of adolescence—achieving autonomy and taking on more adult
roles—or whether problems arise from a mismatch of development and social pressures.
Girls and boys differ not only in the pace of physical maturation but also in how they respond to
the resulting social experiences for which physical changes serve as stimuli. In ways that are
different for boys and girls, the attachments children form with peers or older teens can influence
their risk of involvement in potentially harmful behavior.
One of the challenges of this research is to develop theories that then can be tested using
statistical models to determine how well they predict how the complex array of social, cultural,
environmental, and biological factors interact to increase or reduce the risk of underage drinking.
THE DEVELOPMENTAL PERSPECTIVE
In the effort to understand underage drinking, research in many disciplines has contributed
valuable information on risk and protective factors, biological processes underlying human
development, and the impact of socioenvironmental and pharmacologic influences on these
mechanisms. To date, much of this diverse work has been aligned with specific disciplinary
paradigms. Problematic involvement with alcohol is multicausal, however; studies conducted
within any single research discipline lack the breadth required for a comprehensive approach to
the elucidation of risk and protective factors and to develop improved interventions. Genetic and
socioenvironmental factors act together through biological mechanisms to generate the
complexities of behavior, including early-age problematic involvement with alcohol.
The developmental perspective is a life course approach to understanding behavioral problems
such as underage drinking and its consequences. This perspective has evolved from relatively
recent advances in the fields of developmental psychopathology, human brain development, and
behavior genetics. It is set in the context of the chronology of human maturation and the multiple
social and cultural systems that interact with the developing human. Like systems biology, it
posits complex multidirectional and reciprocal interactions that change over time. Viewed in this
way, development encompasses not only the roots of risk and resilience in maturational pathways
and developmental stages but also the modulation of behavior by present circumstances (Sroufe
and Rutter 1984). The developmental perspective can inform the development of strategies and
opportunities to prevent adverse, health- compromising drinking outcomes. It also can shape the
content and process of therapeutic interventions.
CHARACTERISTICS OF DEVELOPMENTAL RESEARCH
Developmental research is, by nature, longitudinal. There are multiple possible starting points and
developmental pathways to a problematic or positive adolescent outcome. Young people who are
vulnerable as preadolescents can acquire positive, health-promoting low-risk behaviors upon
reaching adolescence. Others who are low risk as preadolescents can have substantial
problematic involvement with alcohol in later adolescence. Cross-sectional strategies may not
reveal the complex interactions of multiple causal factors with biological, cognitive, affective,
psychological, and social maturational milestones in determining relevant positive and negative
outcomes. This is particularly true given the variation within the population in the timing and
achievement of these milestones.
A key assumption underlying developmental research is that, although maturation is progressive,
it is not uniform in speed or timing. There are periods of rapid transition, reorganization, and
spurts of growth (i.e., saltation), alternating with periods of quiescence and consolidation (i.e.,
stasis). Rapid transitions may be critical developmental periods during which the social or cultural
environment most strongly influences the biology and behavior of the developing human, leading
to either an adverse or positive outcome (reviewed in Greenough et al. 1987; Cicchetti and
Tucker 1994). Critical developmental periods may provide key opportunities to redirect the course
of development and alter the life course trajectory of the person (Masten 2004). Timing healthpromoting interventions in terms of critical developmental transitions could enhance efficacy.
SOCIAL CONTEXT
Social context seems to be particularly important in understanding and modifying human
developmental trajectories. During adolescence, parental influences continue to be important, but
there is a progressive increase in the influence of peers. Perhaps reflective of this altered
balance, Brook and colleagues (1990) noted that family-directed alcohol and other drug abuse
prevention efforts are generally more effective for children, whereas interventions involving peers
are more effective for adolescents.
SELF-REGULATION
Self-regulation refers to the organism’s ability to monitor and modulate internal states. In humans,
it includes both the ability to modulate affect and level of arousal and the neurocognitive
executive capacities to engage in goal-directed behavior. These executive cognitive capacities
include the regulation of attention, planning, organization, concept formation, abstract reasoning,
cognitive flexibility, self-monitoring, motor programming, and motor control (Stuss and Benson
1984). Self-regulatory behavioral capacities are refined during early adolescence as
neurobiological maturation progresses and frontal brain regions mature. In parallel, early
adolescence is characterized by the emergence of a social drive to establish an adult role,
behave autonomously, and engage in adult decisionmaking. This social drive for autonomy and
adult status is further stimulated by the mass media’s shaping of perceived social norms for
adolescents.
For some adolescents, however, there may be a mismatch between the drive to assume an adult
social role and the adolescents’ biologically mediated capacity to regulate internal mood states
and outwardly directed behavior. Research indicates that this mismatch between social
aspirations and self- regulatory abilities increases the adolescent’s vulnerability to a variety of
adverse behavioral outcomes, including problematic involvement with alcohol and other drugs
(Dahl 2004). To mitigate problems arising from this mismatch in cognitive-emotional abilities and
social pressures, the balanced support, monitoring, and modeling of social roles by influential
adults (known as social scaffolding) can help guide and protect the adolescent through this
vulnerable period.
PUBERTAL TIMING, SOCIAL FACTORS, AND GENDER HETEROGENEITY
Boys and girls differ significantly in the onset, tempo, and phenomenology of physical sexual
maturation. Puberty’s physical changes serve as stimuli for dynamic changes in the social
experience of maturing children. These social experiences require significant psychosocial
adaptation and are different for boys and girls, particularly when it comes to romantic and peer
affiliations. Early physical maturation can lead to attachments to older boyfriends or girlfriends
and exposure to social pressures and high-risk situations that younger adolescents may not be
able to manage. Having older boyfriends and girlfriends is associated with early sexual activity,
engagement in risky sexual practices, and enhanced risk for sexually transmitted diseases and
unwanted pregnancy (Vanoss et al. 2000; Flick 1986).
For adolescent girls specifically, having an older or adult boyfriend raises the risk for underage
use of alcohol and other drugs and the adoption of delinquent behaviors (Castillo Mezzich 1999).
For boys, same-gender peers tend to provide more of a vector for initiation into alcohol and other
drug use as well as delinquency (Kandel 1978; Dishion et al. 1994; Elliot and Menard 1996;
Sampson and Laub 1993; Fergusson and Horwood 1996, 1999; Hawkins et al. 1992). Thus, boys
and girls may follow different developmental trajectories, may have a different set of maturational
vulnerabilities, and may have a different profile of adverse outcomes. Consequently,
developmental underage drinking research needs to explore the roles of gender differences in
risk and resilience.
MULTICAUSALITY, INTERDISCIPLINARY RESEARCH, AND QUANTITATIVE MODELING
Multiple causal influences, from molecules to the media, interact in complicated ways over time to
influence underage drinking behavior and outcomes. Building empirical models that capture this
complexity can be challenging. Constructing developmental models requires repeated
measurement of social, cultural, environmental, and biological factors influencing each other
across time. Interdisciplinary expertise is typically required to collect and integrate these diverse
types of data. Statistical models also must be developed to validly test a developmental theory—
to see if it accurately reflects what happens in the real world. Although quantitative methods such
as growth curve analysis—an approach to studying change over time—can address some
research questions, methods have yet to be developed to deal with more complex theoretical
models relevant to underage drinking and adolescent alcohol misuse (Curran and Willoughby
2003).
REFERENCES
Brook, J.; Whiteman, M.; Gordon, A.; et al. The psychosocial etiology of adolescent drug use: A
family interaction approach. Genetic, Social and General Psychology Monographs 116:113–267,
1990.
Castillo Mezzich, A.; Giancola, P.R.; Lu, S.Y.K.S.; et al. Adolescent females with a substance use
disorder: Affiliations with adult male sexual partners. American Journal of Addictions 8:190–200,
1999. PMID: 10506900.
Cicchetti, D., and Tucker, D. Development and self-regulatory structures of the mind.
Development and Psychopathology 6:533–549, 1994.
Curran, P.J., and Willoughby, M.T. Implications of latent trajectory models for the study of
developmental psychopathology. Development and Psychopathology 15:581–612, 2003. PMID:
14582933.
Dahl, R.E. Adolescent brain development: A period of vulnerabilities and opportunities. Keynote
address. Annals of the New York Academy of Sciences 1021:1–22, 2004. PMID: 15251869
Dishion, T.J.; Duncan, T.E.; Eddy, J.M.; et al. The world of parents and peers: Coercive
exchanges and children’s social adaptation. Social Development 3:255–268, 1994.
Elliot, D.S., and Menard, S. Delinquent friends and delinquent behaviour: Temporal and
developmental patterns. In: Hawkins, D., ed. Delinquency and Crime: Current Theories.
Cambridge: Cambridge University Press, 1996. pp. 28–67.
Fergusson, D.M., and Horwood, L.J. The role of adolescent peer affiliations in the continuity
between childhood behavioral adjustment and juvenile offending. Journal of Abnormal Child
Psychology 24:205–221, 1996. PMID: 8743245
Fergusson, D.M., and Horwood, L.J. Prospective childhood predictors of deviant peer affiliations
in adolescence. Journal of Child Psychology and Psychiatry, and Allied Disciplines 40:581–592,
1999. PMID: 10357164
Flick, L.H. Paths to adolescent parenthood: Implications for prevention. Public Health Reports
101:132–147, 1986.
Greenough, W.T.; Black, J.E.; and Wallace, C.S. Experience and brain development. Child
Development 58:539–559, 1987. PMID: 3038480
Hawkins, J.D.; Catalano, R.F.; and Miller, J.Y. Risk and protective factors for alcohol and other
drug problems in adolescence and early adulthood: Implications for substance abuse prevention.
Psychological Bulletin 112:64–105, 1992. PMID: 1529040
Kandel, D. Homophily, selection and socialization in adolescent friendships. American Journal of
Sociology 84:427–436, 1978.
Masten, A.S. Regulatory processes, risk, and resilience in adolescent development. Annals of the
New York Academy of Sciences 1021:310–319, 2004. PMID: 15251901
Sampson, R.J., and Laub, J.H. Crime in the Making: Pathways and Turning Points Through Life.
Cambridge, MA: Harvard University Press, 1993.
Sroufe, L.A., and Rutter, M. The domain of developmental psychopathology. Child Development
55:17–29, 1984. PMID: 6705619
Stuss, D.T., and Benson, D.F. Neuropsychological studies of the frontal lobes. Psychological
Bulletin 95:3–28, 1984. PMID: 6544432
Vanoss, M.B.; Coyle, K.K.; Gomez, C.A.; et al. Older boyfriends and girlfriends increase risk of
sexual initiation in young adolescents. Journal of Adolescent Health 27:409–418, 2000. PMID:
11090743
The Effects of Alcohol on Physiological
Processes and Biological Development
Adolescence is a period of rapid growth and physical change; a central question is
whether consuming alcohol during this stage can disrupt development in ways that have
long-term consequences. In general, the existing evidence suggests that adolescents
rarely exhibit the more severe chronic disorders associated with alcohol dependence such
as liver cirrhosis, hepatitis, gastritis, and pancreatitis. Adolescents who drink heavily,
however, may experience some adverse effects on the liver, bone, growth, and endocrine
development. Evidence also is mounting, at least in animal models, that early alcohol use
may have detrimental effects on the developing brain, perhaps leading to problems with
cognition later in life. This article summarizes the physiological effects of alcohol on
adolescents, including a look at the long-term behavioral and physiological consequences
of early drinking. Key words: underage drinking; binge drinking; AODU (alcohol and other drug
use); adolescence; growth and development; puberty; physiological AODE (alcohol and other
drug effects); psychological AODE; chronic AODE; brain; liver; bone; reproductive system; sexual
maturation; long-term AOD (alcohol and other drug) use; animal studies
OVERVIEW
The damage that long-term heavy alcohol consumption can do to the health of adults is well
documented. Some research suggests that, even over the shorter time frame of adolescence,
drinking alcohol can harm the liver, bones, endocrine system, and brain, and interfere with
growth. Adolescence is a period of rapid growth and physical change; a central question is
whether consuming alcohol during this stage can disrupt development in ways that have longterm consequences.
Liver disease is a common consequence of heavy drinking. More severe alcohol-related liver
disease typically reflects years of heavy alcohol use. However, elevated liver enzymes that are
markers of harm have been found in adolescents with alcohol use disorders and in overweight
adolescents who consume more modest amounts of alcohol.
During puberty, accelerating cascades of growth factors and sex hormones set off sexual
maturation, growth in stature and muscle mass, and bone development. Studies in humans have
found that alcohol can lower the levels of growth and sex hormones in both adolescent boys and
girls. In animals, alcohol has been found to disrupt the interaction between the brain, the pituitary
gland (which regulates secretion of sex hormones), and the ovaries, as well as systems within the
ovaries that are involved in regulating sex hormones. In adolescent male animals, both short- and
long-term alcohol administration suppresses testosterone; alcohol use also alters growth
hormone levels, the effects of which differ with age.
Studies on alcohol and adolescent bone development are limited. In studies of male and female
rats, chronic alcohol consumption (an alcohol diet) for the length of adolescence was found to
stunt limb growth. One study found that feeding female rats alcohol in a way that mimics binge
drinking resulted in either increases in bone length and density or in no change with more
frequent bingeing. In human adolescent males but not females, studies have found that alcohol
consumption decreases bone density.
The brain also is changing during adolescence. Adolescents tend to drink larger quantities on
each drinking occasion than adults; this may in part be because adolescents are less sensitive to
some of the unpleasant effects of intoxication. However, research suggests that adolescents may
be more sensitive to some of alcohol’s harmful effects on brain function. Studies in rats found that
alcohol impairs the ability of adolescent animals more than adult animals to learn a task that
requires spatial memory. Research also suggests a mechanism for this effect; in adolescents
more than adults, alcohol inhibits the process in which, with repeated experience, nerve impulses
travel more easily across the gap between nerve cells (i.e., neurons) involved in the task being
learned. The reasons for these differences in sensitivity to alcohol remain unclear.
Research also has found differences in the effects of bingelike drinking in adolescents compared
with adults. Normally, as people age from adolescence to adulthood, they become more sensitive
to alcohol’s effects on motor coordination. In one study, however, adolescent rats exposed to
intermittent alcohol never developed this increased sensitivity. Other studies in both human
subjects and animals suggest that the adolescent brain may be more vulnerable than the adult
brain to chronic alcohol abuse.
Young people who reported beginning to drink at age 14 or younger also were four times more
likely to report meeting the criteria for alcohol dependence at some point in their lives than were
those who began drinking after age 21. Although it is possible that early alcohol use may be a
marker for those who are at risk for alcohol disorders, an important question is whether early
alcohol exposure may alter neurodevelopment in a way that increases risk of later abuse.
Research in rats has found that prenatal or early postnatal exposure to alcohol results in a
greater preference for the odor and consumption of alcohol later in life. Social experiences
associated with youthful drinking also may influence drinking later in life. Additional research is
needed to resolve the question of whether and how early alcohol exposure might contribute to
drinking problems years down the road.
ALCOHOL’S EFFECTS ON THE LIVER, THE NEUROENDOCRINE SYSTEM, AND BONE
The medical consequences of chronic alcohol abuse and dependence have been well
documented in adults. They include liver disease, lung disease, compromised immune function,
endocrine disorders, and brain changes. Investigations of the health problems associated with
adolescent alcohol abuse are sparse and rely mainly on self-report (see Clark et al. 2001; Aarons
et al. 1999; Brown and Tapert 2004). In general, the existing evidence suggests that adolescents
rarely exhibit the more severe chronic disorders associated with alcohol dependence, such as
liver cirrhosis, hepatitis, gastritis, and pancreatitis. However, more research is needed to
determine whether severe alcohol-induced organ damage is strictly a cumulative process that
begins in adolescence and culminates in adulthood as a result of long-term chronic heavy
drinking or whether serious alcohol-related health problems can emerge during the teenage
years. The few studies available indicate that adolescents who drink heavily experience adverse
effects on the liver, bones, growth, and endocrine development, as summarized below. The
effects of chronic alcohol consumption on the adolescent brain are discussed in the section
“Long-Term Behavioral and Physiological Conse quences of Early Drinking.”
Liver Effects
Elevated liver enzymes have been found in some adolescents who drink alcohol. Clark and
colleagues (2001) found that adolescent alcohol use disorders were associated with higher
gamma-glutamyl transpeptidase (GGT) and alanine amino transferase (ALT). Moreover, young
drinkers who also are overweight or obese exhibit elevated levels of serum ALT with even modest
amounts of alcohol intake (Strauss et al. 2000).
Growth and Endocrine Effects
In general, there has been a gradual decline in the onset of female puberty over the last century,
at least when puberty is defined by age at menarche (Tanner 1989). Whether initiation of female
puberty is continuing to decline and at what rate are the subjects of some debate (Lee et al. 2001;
Herman-Giddens et al. 1997). Much less information exists on pubertal development in males
because of the greater difficulty in assessing developmental milestones. However, a recent study
comparing data from two national surveys, one conducted between 1988 and 1994 and the other
between 1963 and 1970, found that American boys from the later generation had earlier onset of
some pubertal stages as measured by standard Tanner staging (Herman-Giddens et al. 2001;
Karpati et al. 2002). Perhaps not surprisingly, early puberty—especially among girls—is
associated with early use of alcohol, tobacco, and other drugs (Wilson et al. 1994; Dick et al.
2000). In addition, alcohol use in early maturing adolescents has implications for normal growth
and neuroendocrine development.
In both males and females, puberty is a period of activation of the hypothalamic-pituitary-gonadal
(HPG) axis. Pulsatile secretion of gonadotrophin-releasing hormone (GnRH) from the
hypothalamus stimulates pituitary secretion of follicle-stimulating hormone (FSH) and luteinizing
hormone (LH) pulses, followed by marked increases in gonadal sex steroid output (estrogen and
testosterone), which in turn increases growth hormone (GH) and insulin-like growth factor-1 (IGF1) production (see Mauras et al. 1996). Data from several studies suggest that both androgens
and estrogens stimulate GH production, but that estrogen controls the feedback mechanism of
GH production during puberty even in males (Mauras et al. 1996; Dees et al. 2001). The increase
in these hormones not only promotes maturation of the gonads but also affects growth, muscle
mass, and mineralization of the skeleton. Thus, alcohol consumed during rapid development (i.e.,
prior to or during puberty) has the potential to disrupt normal growth and endocrine development
through its effects on the hypothalamus, the pituitary gland, and the various target organs such as
the ovaries and testes.
Most human and animal research on alcohol and endocrine development has been conducted in
females, but the limited data on both genders suggest that alcohol can have substantial effects on
neuroendocrine function (see Dees et al. 2001; Emanuele et al. 1998; Emanuele et al. 2002a,b).
Human studies have found that alcohol ingestion can lower estrogen levels in adolescent girls
(Block et al. 1993) and lower both LH and testosterone levels in midpubertal boys (Diamond et al.
1986; Frias et al. 2000a). In both genders, acute alcohol intoxication produces a decrease in GH
levels without significant change in either IGF-1 or insulin-like growth factor binding protein-3
(IGFBP3) (Frias et al. 2000b).
In female rats, alcohol has been shown to suppress the secretion of specific female reproductive
hormones, thereby delaying the onset of puberty (see Dees et al. 2001 and Emanuele et al).
Dees and colleagues (2000) found that immature female rhesus macaques exposed daily to
alcohol (2 g/kg via nasogastric tube) exhibit lower levels of GH, FSH, LH, estradiol (E 2), and IGF1 (but not FSH or Leptin) compared with control subjects. Moreover, even though there was no
effect on age of menarche in these animals, the interval between subsequent menstruations was
lengthened, thereby interfering with the development of regular monthly cycles. Additional studies
in rats have found that alcohol interferes with intraovarian systems, including IGF-1 and IGF-1
receptors; the nitric oxide (NO) system (Dees et al. 2001; Srivastava et al. 2001a), and the
steroidogenic acute regulatory protein (StAR) (Srivastava et al. 2001b), all of which combine to
decrease estradiol secretion. Thus, alcohol not only disrupts the interaction between the brain,
pituitary gland, and ovaries, it also directly impairs the regulatory systems within the ovaries (see
Dees et al. 2001 for review).
In male rats, both acute and chronic alcohol exposure during adolescence results in a reversible
suppression of serum testosterone (Little et al. 1992; Cicero et al. 1990; Tentler et al. 1997;
Emanuele et al. 1998, 1999a,b; Steiner et al. 1997). Evidence exists for involvement at the
hypothalamic, pituitary, and gonadal levels, although the testes appear to be the prime target of
alcohol’s actions (Emanuele et al. 1999a). Furthermore, GH levels are affected by acute and
chronic alcohol exposure in male adolescent rats, whereas IGF-1, growth hormone releasing
factor (GRF), and GRF mRNA content are variable, depending on the type of administration
(Steiner et al. 1997; Tentler et al. 1997).
Thus, the data so far indicate that females who consume alcohol during early adolescence may
be at risk for adverse effects on maturation of the reproductive system. Although in males the
long-term effects of alcohol on reproductive function are unclear, the fact that GH as well as
testosterone and/or estrogen levels are altered by alcohol in both genders may have serious
implications for normal development because these hormones play a critical role in organ
maturation during this stage of development.
Bone Density and Growth Effects
Only a handful of studies have examined the effects of adolescent drinking on bone development,
with the most informative data thus far coming from animal research. Male rats chronically fed an
alcohol liquid diet for 60 days encompassing the adolescent period (postnatal days 35 to 90)
display limb length reduction and reduced metaphyseal and cortical bone growth in the limbs
(Wezeman et al. 1999). These skeletal effects may be mediated through a reduction in osteoblast
formation, which is associated with a decline in testosterone but not IGF-1. In addition, with
abstinence, normal bone metabolism is not completely restored. Similarly, in female rats,
Sampson and colleagues (Sampson et al. 1996; Sampson and Spears 1999) found that chronic
alcohol consumption (4 weeks on an ethanol liquid diet) produces decreased limb length and
reductions in cortical and cancellous bone, which are not fully reversed following cessation of
drinking. Interestingly, female adolescent animals administered a binge model of drinking (i.e., 5
percent alcohol by gavage for either 2 or 5 consecutive days per week) show increased bone
length, weight, and density, or no change, respectively (Sampson et al. 1999). Human studies
indicate an inverse relationship between alcohol consumption and bone mineral density in
adolescent males, but not females (Fehily et al. 1992; Neville et al. 2002; Elgan et al. 2002; Fujita
et al. 1999). However, more studies are needed in humans and animals to get a clearer picture of
alcohol’s effects on bone growth in adolescents, particularly with respect to dose and pattern of
consumption.
A Snapshot of Findings on Alcohol’s Physiological Effects in Adolescent Humans & Animals
Findings
Study
On the Liver
Levels of enzymes that indicate liver damage are
higher in adolescents with alcohol use disorders
Clark et al. 2001
And in obese adolescents who drink more moderate
amounts.
Strauss et al. 2000
In humans
On the Endocrine System
In humans
In rats
Drinking alcohol can lower estrogen levels in
adolescent girls.
Block et al. 1993
Drinking alcohol can lower luteinizing hormone and
testosterone levels in adolescent boys.
Diamond et al. 1986;
Frias et al. 2000a
In both sexes, acute intoxication reduces levels of
growth hormones.
Frias et al. 2000b
In female rats, ingesting alcohol during adolescence
Dees et al. 2001
is associated with adverse effects on maturation of
the reproductive system.
In rhesus
macaques
Alcohol suppresses the secretion of certain female
reproductive hormones, delaying the start of
puberty.
Emanuelle et al. 2001,
2002
Alcohol not only disrupts the interaction between the
brain, pituitary gland, and ovaries, but also impairs
regulatory systems within the ovaries.
Dees et al. 2001
In male rats, alcohol consumption alters growth
hormone and testosterone levels, which may have
serious consequences for normal development.
Little et al. 1992; Cicero et
al. 1990; Tentler et al.
1997; Emanuelle et al.
1998, 1999a, 1999b;
Steiner et al. 1997
In immature female monkeys, daily exposure to
alcohol lowered levels of female hormones and
affected the development of regular monthly cycles.
Dees et al. 2000
On Bone Density
In humans
Increased alcohol consumption is associated with
lowered bone mineral density in adolescent males
but not females.
Fehily et al. 1992; Neville
et al. 2002; Elgan et al.
2002; Fujita et al. 1999
In adolescent female rats, chronic alcohol
consumption produced shorter limb lengths and
reductions in bone growth, neither of which was fully
reversed with abstinence.
Sampson et al. 1996;
Sampson and Spears
1999
In adolescent male rats, chronic alcohol ingestion
was associated with shorter limb length and
reduced bone growth, which are not fully reversed
with abstinence.
Wezeman et al. 1999
In rats
On the Brain
In humans
In rats
A history of alcohol abuse or dependence in
adolescents was associated with reduced
hippocampal volumes
De Bellis et al. 2000
And with subtle white-matter microstructure
abnormalities in the corpus callosum.
Tapert et al. 2003
Chronic intermittent exposure to high alcohol doses
(i.e., bingeing) results in long-lasting changes in
memory in adolescent rats
White et al. 2000
And to more damage to the frontal-anterior cortical
regions of the brain than are produced in adult rats.
Crews et al. 2000
Prolonged alcohol exposure during adolescence
produces:



Neurophysiological changes in the response
to alcohol challenge and in the tolerance to
alcohol’s sedative effects;
Enhanced expression of withdrawal
behaviors; and
Long-lasting neurophysiological effects in
the cortex and hippocampus.
Slawecki et al. 2001;
Slawecki 2002; Slawecki
and Roth 2004
LONG-TERM BEHAVIORAL AND PHYSIOLOGICAL CONSEQUENCES OF EARLY
DRINKING
Although increased tolerance to alcohol’s sedative effects may enable greater intake in
adolescents, repeated exposure to alcohol may produce increased sensitivity to alcohol’s harmful
effects. Studies in rats show that ethanol-induced inhibition of synaptic potentials mediated by Nmethyl-D-aspartate (NMDA) and long-term potentiation (LTP) is greater in adolescents than in
adults (Swartzwelder et al. 1995a,b; see White and Swartzwelder 2005 for review). Initially, the
developmental sensitivity of NMDA currents to alcohol was observed in the hippocampus, but
more recently this effect was found outside the hippocampus in pyramidal cells in the posterior
cingulate cortex (Li et al. 2002). Behaviorally, adolescent rats show greater impairment than
adults in acquisition of a spatial memory task after acute ethanol exposure (Markwiese et al.
1998) in support of greater LTP sensitivity to alcohol in adolescents. Behavioral and
neurobiological mechanisms for the ontogenetic differences in alcohol tolerance and sensitivity
are unclear, as is the relationship between differential sensitivity to ethanol and onset of alcohol
abuse and alcoholism.
Binge alcohol exposure (i.e., chronic intermittent exposure to high alcohol doses) in rats during
adolescence produces long-lasting changes in memory function (White et al. 2000) and interferes
with the normal development of sensitivity to alcohol-induced motor impairments (White et al.
2002). In addition, prolonged alcohol exposure during adolescence, but not adulthood, produces
alterations in neurophysiological response to ethanol challenge, tolerance to the sedative effects
of ethanol, enhanced expression of withdrawal-related behavior, and long-lasting
neurophysiological changes in the cortex and hippocampus in rats (Slawecki et al. 2001;
Slawecki 2002; Slawecki and Roth 2004). Further more, chronic ethanol treatment in rats may
lead to increased NMDA-mediated neurotoxicity, which could be exacerbated by repeated
withdrawals (Hunt 1993). Consistent with this hypothesis is the finding that severity of alcohol and
drug withdrawal symptoms may be a powerful marker of neuropsychological impairments in
detoxified older human adolescents and young adults (Brown et al. 2000; Tapert and Brown
1999; Tapert et al. 2002). Moreover, one recent study found reduced hippocampal volumes in
human adolescents with a history of alcohol abuse/dependence disorder (De Bellis et al. 2000),
and another preliminary investigation of alcohol-abusing teenagers observed subtle white-matter
microstructure abnormalities in the corpus callosum (Tapert et al. 2003), which may be a
precursor of more severe damage produced by long-term chronic drinking (Pfefferbaum and
Sullivan 2002). Juvenile rats exposed to heavy bingelike episodes of ethanol have greater
damage than adults in frontal-anterior cortical regions, including the olfactory frontal cortex,
anterior perirhinal, and piriform cortex (Crews et al. 2000). Thus, the immature brain may be more
susceptible to binge ethanol-induced neurotoxicity, although the mechanisms are unknown.
Because teenagers are likely to engage in binge drinking, it is important to study the effects of
chronic binge patterns of ethanol exposure on brain structure, neurochemistry, and cognitive
functioning. Care must be taken in extrapolating from the described animal studies to the bingedrinking adolescent. Because binge drinking does not usually entail withdrawal, it is important to
distinguish between damage caused by the alcohol itself and that caused by repeated
withdrawals. In addition, primate models may be a better choice for studying the long-term
consequences of alcohol exposure because of primates’ prolonged adolescent period, which
allows extensive manipulation of different types and lengths of exposure. These models, coupled
with new neuroanatomical and neuroimaging techniques, offer a unique opportunity to study the
brain changes associated with adolescent drinking and determine whether adolescent brains are
able to recover more easily because of greater plasticity.
Early Exposure as a Predictor of Later Alcohol Abuse
Early exposure to alcohol—at or before age 14—is strongly associated with later alcohol abuse
and dependence (Grant and Dawson 1998). Two possible explanations for this effect are
obvious. First, early alcohol use may simply be a marker for later alcohol abuse rather than a
causative factor. A good deal of evidence indicates that at least one behavioral factor, behavioral
undercontrol, is measurable very early in life and is a consistently robust predictor of earlier
alcohol use as well as of elevated risk for later alcohol use disorder (NIAAA 2000; Zucker and
Wong 2005; Caspi et al. 1996).
Second, it is possible that alcohol exposure during adolescence actually may alter
neurodevelopmental processes in such a way that the likelihood of later abuse is increased. For
example, alcohol use could promote rewiring or alter normal maturation and pruning within the
nervous system. Ample evidence exists that exposing rats to low or moderate doses of alcohol
during the prenatal or early postnatal period yields a greater preference for ethanol’s odor and its
consumption later in life (Abate et al. 2000; Honey and Galef 2003; see Molina et al. 1999 and
Spear and Molina 2001 for reviews). The young rat’s response to alcohol also is mediated by
social factors such as maternal interactions and/or nursing from an intoxicated dam (e.g., Hunt et
al. 2001; Pepino et al. 2001, 2002; Spear and Molina 2001). Recent evidence shows that prior
nursing experience from an ethanol-intoxicated dam heightens ethanol consumption in infant and
adolescent rats (Ponce et al. 2004; Pepino et al. 2004). In contrast, relatively few reports using
animal models to study the effects of adolescent alcohol exposure on later alcohol consumption
exist, and the results are conflicting (see Spear and Varlinskaya 2005). Yet, as is the case with
younger animals, social experiences associated with adolescent drinking may influence future
drinking behaviors (Hunt et al. 2001; Varlinskaya and Spear 2002). More studies are needed,
however, to explore whether a causal relationship between early chronic exposure to alcohol and
later alcohol problems exists, as well as to discover the underlying mechanisms for this effect.
Nonhuman primates, because of their extended adolescent period, offer a good opportunity to
study the effects of early exposure to alcohol.
REFERENCES
Aarons, G.A.; Brown, S.A.; Coe, M.T.; et al. Adolescent alcohol and drug abuse and health.
Journal of Adolescent Health 24:412–421, 1999. PMID: 10401969
Abate, P.; Pepino, M.Y.; Dominguez, H.D.; et al. Fetal associative learning mediated through
maternal alcohol intoxication. Alcoholism: Clinical and Experimental Research 24:39–47, 2000.
PMID: 10656191
Block, G.D.; Yamamoto, M.E.; Mallick, E.; and Styche, A. Effects on pubertal hormones by
ethanol abuse in adolescents. Alcoholism: Clinical and Experimental Research 17:505, 1993.
Brown, S.A., and Tapert, S.F. Health consequences of adolescent alcohol involvement. In: NRC
and IOM. Bonnie, R.J., and O’Connell, M.E., eds. Reducing Underage Drinking: A Collective
Responsibility. Washington, DC: National Academies Press, 2004. pp. 383–401. Available online
at: http://www.nap.edu/books/0309089352/html.
Brown, S.A.; Tapert, S.F.; Granholm, E.; and Dellis, D.C. Neurocognitive functioning of
adolescents: Effects of protracted alcohol use. Alcoholism: Clinical and Experimental Research
24:164–171, 2000. PMID: 10698367
Caspi, A.; Moffitt, T.E.; Newman, D.L.; and Silva, E.P.A. Behavioral observations at age 3 years
predict adult psychiatric disorders: Longitudinal evidence from a birth cohort. Archives of General
Psychiatry 53:1033–1039, 1996. PMID: 8911226
Cicero, T.J.; Adams, M.L.; O’Connor, L.; et al. Influence of chronic alcohol administration on
representative indices of puberty and sexual maturation in male rats and the development of their
progeny. Journal of Pharmacology and Experimental Therapeutics 255:707–715, 1990. PMID:
2243349
Clark, D.B.; Lynch, K.G.; Donovan, J.E.; and Block, G.D. Health problems in adolescents with
alcohol use disorders: Self-report, liver injury, and physical examination findings and correlates.
Alcoholism: Clinical and Experimental Research 25:1350–1359, 2001. PMID: 11584156
Crews, F.T.; Braun, C.J.; Hoplight, B.; et al. Binge ethanol consumption causes differential brain
damage in young adolescent rats compared with adult rats. Alcoholism: Clinical and Experimental
Research 24:1712–1723, 2000. PMID: 11104119
De Bellis, M.D.; Clark, D.B.; Beers, S.R.; et al. Hippocampal volume in adolescent-onset alcohol
use disorders. American Journal of Psychiatry 157:737–744, 2000. PMID: 10784466
Dees, W.L.; Dissen, G.A.; Hiney, J.K.; et al. Alcohol ingestion inhibits the increased secretion of
puberty-related hormones in the developing female rhesus monkey. Endocrinology 141:1325–
1331, 2000. PMID: 10746635
Dees, W.L.; Srivastava, V.K.; and Hiney, J.K. Alcohol and female puberty: The role of intraovarian
systems. Alcohol Research & Health 25(4):271–275, 2001. PMID: 11910704
Diamond, F., Jr.; Ringenberg, L.; MacDonald, D.; et al. Effects of drug and alcohol abuse upon
pituitary-testicular function in adolescent males. Journal of Adolescent Health Care 7:28–33,
1986. PMID: 2935515
Dick, D.M.; Rose, R.J.; Viken, R.J.; and Kaprio, J. Pubertal timing and substance use:
Associations between and within families across late adolescence. Developmental Psychology
36:180–189, 2000. PMID: 10749075
Elgan, C.; Dykes, A.K.; and Samsioe, G. Bone mineral density and lifestyle among female
students aged 16–24 years. Gynecological Endocrinology 16:91– 98, 2002. PMID: 12012629
Emanuele, M.A.; LaPaglia, N.; Steiner, J.; et al. Reversal of ethanol-induced testosterone
suppression in peripubertal male rats by opiate blockade. Alcoholism: Clinical and Experimental
Research 22:1199–1204, 1998. PMID: 9756033
Emanuele, M.A.; Wezeman, F.; and Emanuele, N.V. Alcohol’s effects on female reproductive
function. Alcohol Research & Health 26(4):274–281, 2002a. PMID: 12875037
Emanuele, N.; Ren, J.; LaPaglia, N.; et al. EtOH disrupts female mammalian puberty: Age and
opiate dependence. Endocrine 18:247–254, 2002b. PMID: 12450316
Emanuele, N.V.; LaPaglia, N.; Vogl, W.; et al. Impact and reversibility of chronic ethanol feeding
on the reproductive axis in the peripubertal male rat. Endocrine 11:277–284, 1999a. PMID:
10786824
Emanuele, N.V.; Lapaglia, N.; Steiner, J.; et al. Reversal of chronic ethanol-induced testosterone
suppression in peripubertal male rats by opiate blockade. Alcoholism: Clinical and Experimental
Research 23:60–66, 1999b. PMID: 10029204
Fehily, A.M.; Coles, R.J.; Evans, W.D.; and Elwood, P.C. Factors affecting bone density in young
adults. American Journal of Clinical Nutrition 56:579–586, 1992. PMID: 1503072
Frias, J.; Rodriguez, R.; Torres, J.M.; et al. Effects of acute alcohol intoxication on pituitarygonadal axis hormones, pituitary-adrenal axis hormones, β-endorphin and prolactin in human
adolescents of both sexes. Life Sciences 67:1081–1086, 2000a. PMID: 10954041
Frias, J.; Torres, J.M.; Rodriguez, R.; et al. Effects of acute alcohol intoxication on growth axis in
human adolescents of both sexes. Life Sciences 67:2691–2697, 2000b. PMID: 11105985
Fujita, Y.; Katsumata, K.; Unno, A.; et al. Factors affecting peak bone density in Japanese
women. Calcified Tissue International 64:107–111, 1999. PMID: 9914316
Grant, B.F., and Dawson, D.A. Age at onset of alcohol use and its association with DSM–IV
alcohol abuse and dependence: Results from the National Longitudinal Alcohol Epidemiologic
Survey. Journal of Substance Abuse 9:103–110, 1998. PMID: 9494942
Herman-Giddens, M.E.; Slora, E.J.; Wasserman, R.C.; et al. Secondary sexual characteristics
and menses in young girls seen in office practice: A study from the Pediatric Research in Office
Settings Network. Pediatrics 99:505–512, 1997. PMID: 9093289
Herman-Giddens, M.E.; Wang, L.; and Koch, G. Secondary sexual characteristics in boys:
Estimates from the National Health and Nutrition Examination Survey III, 1988–1994. Archives of
Pediatric & Adolescent Medicine 155:1022–1028, 2001. PMID: 11529804
Honey, P.L., and Galef, B.G., Jr. Ethanol consumption by rat dams during gestation, lactation and
weaning increases ethanol consumption by their adolescent young. Developmental
Psychobiology 42:252– 260, 2003. PMID: 12621651
Hunt, W.A. Are binge drinkers more at risk of developing brain damage? Alcohol 10:559–561,
1993. PMID: 8123218
Hunt, P.S.; Holloway, J.L.; and Scordalakes, E.M. Social interaction with an intoxicated sibling
can result in increased intake of ethanol by periadolescent rats. Developmental Psychobiology
38:101–109, 2001. PMID: 11223802
Karpati, A.M.; Rubin, C.H.; Kieszak, S.M.; et al. Stature and pubertal stage assessment in
American boys: The 1988–1994 Third National Health and Nutrition Examination Survey. Journal
of Adolescent Health 30:205–212, 2002. PMID: 11869928
Lee, P.A.; Guo, S.S.; and Kulin, H.E. Age of puberty: Data from the United States of America.
APMIS (Acta Pathologica, Microbiologica, et Immunologica Scandinavica) 109:81–88, 2001.
PMID: 11398998
Li, Q.; Wilson, W.A.; and Swartzwelder, H.S. Differential effect of ethanol on NMDA EPSCs in
pyramidal cells in the posterior cingulate cortex of juvenile and adult rats. Journal of
Neurophysiology 87:705–711, 2002. PMID: 11826039
Little, P.J.; Adams, M.L.; and Cicero, T.J. Effects of alcohol on the hypothalamic-pituitary-gonadal
axis in the developing male rat. Journal of Pharmacology and Experimental Therapeutics
263:1056–1061, 1992. PMID: 1469619
Markwiese, B.J.; Acheson, S.K.; Levin, E.D.; et al. Differential effects of ethanol on memory in
adolescent and adult rats. Alcoholism: Clinical and Experimental Research 22:416–421, 1998.
PMID: 9581648
Mauras, N.; Rogol, A.D.; Haymond, M.W.; and Veldhuis, J.D. Sex steroids, growth hormone,
insulin-like growth factor-1: Neuroendocrine and metabolic regulation in puberty. Hormone
Research 45:74–80, 1996. PMID: 8742123
Molina, J.C.; Dominguez, H.D.; Lopez, M.F.; et al. The role of fetal and infantile experience with
alcohol in later recognition and acceptance patterns of the drug. In: Hannigan, J.; Goodlett, C.;
Spear, L.; Spear, N., eds. Alcohol and Alcoholism: Brain and Development. Hillsdale, NJ:
Erlbaum, 1999, pp. 199–227.
National Institute on Alcohol Abuse and Alcoholism (NIAAA). Alcohol involvement over the life
course. In: Tenth Special Report to the U.S. Congress on Alcohol and Health: Highlights from
Current Research. Bethesda, MD: Dept. of Health and Human Services, NIAAA, 2000. pp. 28–53.
Available online at: http://pubs.niaaa.nih.gov/publications/10report/intro.pdf .
Neville, C.E.; Murray, L.J.; Boreham, C.A.G.; et al. Relationship between physical activity and
bone mineral status in young adults: The Northern Ireland Young Hearts Project. Bone 30:792–
798, 2002. PMID: 11996922
Pepino, M.Y.; Spear, N.E.; and Molina, J.C. Nursing experiences with an alcohol-intoxicated rat
dam counteract appetitive conditioned responses toward alcohol. Alcoholism: Clinical and
Experimental Research 25:18–24, 2001. PMID: 11198710
Pepino, M.Y.; Abate, P.; Spear, N.E.; and Molina, J.C. Disruption of maternal behavior by alcohol
intoxication in the lactating rat: A behavioral and metabolic analysis. Alcoholism: Clinical and
Experimental Research 26:1205–1214, 2002. PMID: 12198395
Pepino, M.Y.; Abate, P.; Spear, N.E.; and Molina, J.C. Heightened ethanol intake in infant and
adolescent rats after nursing experiences with an ethanol-intoxicated dam. Alcoholism: Clinical
and Experimental Research 28:895–905, 2004. PMID: 15201632
Pfefferbaum, A., and Sullivan, E.V. Micro structural but not macrostructural disruption of white
matter in women with chronic alcoholism. Neuroimage 15:708–718, 2002. PMID: 11848714
Ponce, L.F.; Pautassi, R.M.; Spear, N.E.; and Molina, J.C. Nursing from an ethanol-intoxicated
dam induces short- and long-term disruptions in motor performance and enhances later selfadministration of the drug. Alcoholism: Clinical and Experimental Research 28:1039–1050, 2004.
PMID: 15252290
Sampson, H.W., and Spears, H. Osteopenia due to chronic alcohol consumption by young
actively growing rats is not completely reversible. Alcoholism: Clinical and Experimental Research
23: 324–327, 1999. PMID: 10069563
Sampson, H.W.; Perks, N.; Champney, T.H.; and Defee, B., 2nd. Alcohol consumption inhibits
bone growth and development in young actively growing rats. Alcoholism: Clinical and
Experimental Research 20:1375–1384, 1996. PMID: 8947313
Sampson, H.W.; Gallager, S.; Lange, J.; et al. Binge drinking and bone metabolism in a young
actively growing rat model. Alcoholism: Clinical and Experimental Research 23:1228–1231, 1999.
PMID: 10443990
Slawecki, C.J. Altered EEG responses to ethanol in adult rats exposed to ethanol during
adolescence. Alcoholism: Clinical and Experimental Research 26:246–254, 2002. PMID: 11964565
Slawecki, C.J., and Roth, J. Comparison of the onset of hypoactivity and anxiety-like behavior
during alcohol withdrawal in adolescent and adult rats. Alcoholism: Clinical and Experimental
Research 28:598–607, 2004. PMID: 15100611
Slawecki, C.J.; Betancourt, M.; Cole, M.; and Ehlers, C.L. Periadolescent alcohol exposure has
lasting effects on adult neurophysiological function in rats. Developmental Brain Research
128:63–72, 2001. PMID: 11356263
Spear, L.P., and Varlinskaya, E.I. Adolescence: Alcohol sensitivity, tolerance, and intake. In:
Galanter, M., ed. Recent Developments in Alcoholism, Vol. 17: Alcohol Problems in Adolescents
and Young Adults: Epidemiology, Neurobiology, Prevention, Treatment. New York: Springer,
2005. pp. 143–159. PMID: 15789864
Spear, N.E., and Molina, J.C. Consequences of early exposure to alcohol: How animal studies
reveal later patterns of use and abuse in humans. In: Carroll, M.E., and Overmier, J.B., eds.
Animal Research and Human Health: Advancing Human Welfare through Behavioral Science.
Washington, DC: American Psychological Association, 2001. pp. 85–99.
Srivastava, V.K.; Hiney, J.K.; Dearth, R.K.; and Dees, W.L. Effects of alcohol on intraovarian
insulin-like growth factor-1 and nitric oxide systems in prepubertal female rats. Recent Research
Developments in Endocrinology 2(part 1):213–221, 2001a.
Srivastava, V.K.; Hiney, J.K.; Dearth, R.K.; and Dees, W.L. Acute effects of ethanol on
steroidogenic acute regulatory protein (StAR) in the prepubertal rat ovary. Alcoholism: Clinical
and Experimental Research 25:1500–1505, 2001b. PMID: 11696671
Steiner, J.C.; LaPaglia, N.; Hansen, M.; et al. Effect of chronic ethanol on reproductive and
growth hormones in the peripubertal male rat. Journal of Endocrinology 154:363–370, 1997.
PMID: 9291847
Strauss, R.S.; Barlow, S.E.; and Dietz, W.H. Prevalence of abnormal serum aminotransferase
values in overweight and obese adolescents. Journal of Pediatrics 136:727–733, 2000. PMID:
10839867
Swartzwelder, H.S.; Wilson, W.A.; and Tayyeb, M.I. Age-dependent inhibition of long-term
potentiation by ethanol in immature versus mature hippocampus. Alcoholism: Clinical and
Experimental Research 19:1480–1485, 1995a. PMID: 8749814
Swartzwelder, H.S.; Wilson, W.A.; and Tayyeb, M.I. Differential sensitivity of NMDA receptormediated synaptic potentials to ethanol in immature versus mature hippocampus. Alcoholism:
Clinical and Experimental Research 19:320–323, 1995b. PMID: 7625564
Tanner, J.M. Foetus into Man: Physical Growth From Conception to Maturity. Ware, Great Britain:
Castlemead Publications, 1989.
Tapert, S.F., and Brown, S.A. Neuropsychological correlates of adolescent substance abuse:
Four-year outcomes. Journal of the International Neuropsychological Society 5:481–493, 1999.
PMID: 10561928
Tapert, S.F.; Granholm, E.; Leedy, N.G.; and Brown, S.A. Substance use and withdrawal:
Neuropsychological functioning over 8 years in youth. Journal of the International
Neuropsychological Society 8:873–883, 2002. PMID: 12405538
Tapert, S.F.; Theilmann, R.J.; Schweinsburg, A.D.; et al. Reduced fractional anisotropy in the
splenium of adolescents with alcohol use disorder. Proceedings of the International Society for
Magnetic Resonance in Medicine 11:8217, 2003.
Tentler, J.J.; LaPaglia, N.; Steiner, J.; et al. Ethanol, growth hormone and testosterone in
peripubertal rats. Journal of Endocrinology 152:477–487, 1997. PMID: 9071969
Varlinskaya, E.I., and Spear, L.P. Acute effects of ethanol on social behavior of adolescent and
adult rats: Role of familiarity of the test situation. Alcoholism: Clinical and Experimental Research
26:1502–1511, 2002. PMID: 12394283
Wezeman, F.H.; Emanuele, M.A.; Emanuele, N.V.; et al. Chronic alcohol consumption during
male rat adolescence impairs skeletal development through effects on osteoblast gene
expression, bone mineral density, and bone strength. Alcoholism: Clinical and Experimental
Research 23:1534–1542, 1999. PMID: 10512321
White, A.M., and Swartzwelder, H.S. Age-related effects of alcohol on memory and memoryrelated brain function in adolescents and adults. In: Galanter, M., ed. Recent Developments in
Alcoholism, Vol. 17: Alcohol Problems in Adolescents and Young Adults: Epidemiology,
Neurobiology, Prevention, Treatment. New York: Springer, 2005. pp. 161–176. PMID: 15789865
White, A.M.; Ghia, A.J.; Levin, E.D.; and Swartzwelder, H.S. Binge pattern ethanol exposure in
adolescent and adult rats: Differential impact on subsequent responsiveness to ethanol.
Alcoholism: Clinical and Experimental Research 24:1251–1256, 2000. PMID: 10968665
White, A.M.; Truesdale, M.C.; Bae, J.G.; et al. Differential effects of ethanol on motor coordination
in adolescent and adult rats. Pharmacology, Biochemistry, and Behavior 73:673–677, 2002.
PMID: 12151043
Wilson, D.M.; Killen, J.D.; Hayward, C.; et al. Timing and rate of sexual maturation and the onset
of cigarette and alcohol use among teenage girls. Archives of Pediatrics and Adolescent Medicine
148:789–795, 1994. PMID: 8044254
Zucker, R.A., and Wong, M.M. Prevention for children of alcoholics and other high risk groups. In:
Galanter, M., ed. Recent Developments in Alcoholism, Vol. 17: Alcohol Problems in Adolescents
and Young Adults: Epidemiology, Neurobiology, Prevention, Treatment. New York: Springer,
2005. pp. 299– 320. PMID: 15789872
Genetics, Pharmacokinetics, and Neurobiology
of Adolescent Alcohol Use
Complex behaviors such as the initiation and use of alcohol result from an intricate
interplay between genes and environment. Genes shape physiological and behavioral
responses to alcohol that can influence the likelihood that a young person will begin using
alcohol and that he or she will progress to problem drinking. Youthful alcohol use also can
have an impact on unfolding developmental patterns, and for some, early use becomes the
entry point for pathways that lead to problems with alcohol. This article first describes
research on genes that may be involved in the development of alcohol problems and how
genetic factors may contribute to adolescent alcohol use. It then examines how the
changes that occur during adolescent development—in alcohol metabolism, in the brain,
and in the endocrine and stress response systems—may affect how a young person
experiences alcohol and the likelihood that he or she will develop alcohol use problems.
Key words: adolescent; AOD (alcohol and other drug) use initiation; alcohol abuse; alcohol
dependence; AOD sensitivity; use initiation; risk factors; protective factors; genetic risk and
protective factors; heredity factors; genetics and heredity; environmental factors; heredity vs.
environmental factors; human study; twin study; animal study; animal model; puberty; biological
development; psychological development; cognitive development; endocrine system; hormones;
stress; ethanol metabolism; alcohol metabolism; pharmacokinetics
OVERVIEW
Many studies have focused on how physiological and neurobiological responses to alcohol—
such as sensitivity to alcohol, change in its rewarding effects, craving, tolerance and withdrawal—
factor into the development of alcohol use and alcohol use disorders. The majority of studies to
identify genes and neurobiological mechanisms that may contribute to alcohol use and alcohol
use disorders in humans have been done with adults. Recent data suggest, however, that the
highest prevalence of alcohol dependence in the general population occurs in people ages 18–
24, and it is not yet clear to what extent genes involved in the onset of alcohol problems in adults
play a similar role in youth. A central goal of research is to understand the genetic and
environmental factors, and the interplay between them, that contribute to the development of
alcohol abuse and dependence in adolescents.
Human genetic research related to alcohol use has involved studies with twins or with families
that have a high prevalence of alcohol-dependent individuals. This work has identified regions of
chromosomes that are associated with an altered risk of developing alcohol dependence, and in
some cases, individual genes or candidate genes. Analysis of the role these genes and gene
regions play in alcohol use is difficult for a number of reasons. As with other complex genetic
diseases, multiple genetic factors may contribute to the risk of developing alcohol dependence,
but no one factor is associated with a large percent of risk. Different risk factors may be active in
different individuals. In the case of alcohol use, studies of both adults and adolescents suggest
that the relative contributions of genes and environment change at different stages of problematic
drinking; for example, genes have a strong influence over the development of problem use,
whereas environment seems to play a greater role in the initiation of alcohol use.
Research using animal models also added to our understanding of the genes that may contribute
to alcohol abuse and/or dependence. Animal studies have helped to identify genes involved in the
effects of alcohol as well as those involved in the pathways affecting sensitivity to acute alcohol
exposure, reward, craving, and withdrawal. Many of the genes that have emerged from this
research have roles in other behaviors as well. For example, serotonin has been implicated in
alcohol consumption in conjunction with its role in anxiety, which, in some individuals, is
particularly manifest during adolescence. Further studies will assess the relative roles of various
signaling pathways and their component genes in the development of alcohol-related behavior,
and determine which are most influential in adolescents.
Superimposed on genetically shaped aspects of physiology are developmental changes that can
measurably affect both the response to alcohol and the chances that someone will drink heavily.
Some research, for example, suggests modest changes during adolescence in the
pharmacokinetics of alcohol—how it is absorbed, distributed, and eliminated. Gender differences
in these processes emerge during puberty and affect blood alcohol levels after drinking.
Animal studies suggest that sensitivity to alcohol is different among adolescents than it is in
adults. For example, adolescent rats are less sensitive to the unpleasant effects of intoxication,
such as sedation, loss of coordination, and hangover effects, and they consume higher levels of
alcohol than do older animals. Possible underlying reasons for the lack of sensitivity include the
developmental immaturity of neurotransmitter receptor systems.
Dramatic hormonal changes take place during puberty, affecting growth and sexual development,
and the body’s stress response systems. These hormonal changes also may affect sensitivity to
alcohol. For example, animal research suggests that hormones involved in the response to stress
may interact with neurotransmitters in the brain that are associated with the sensation of reward
to facilitate drinking.
Clearly, development adds a layer of complexity to understanding the reciprocal interactions
between genes and environment, alcohol metabolism, and the neurobiology of the response to
alcohol.
GENETICS OF ADOLESCENT ALCOHOL USE AND ALCOHOL USE DISORDERS
Accumulating research indicates that complex behaviors result from the interplay between genes
and environment over developmental time. Alcohol use is a prime example of a complex behavior
in which gene expression and environment/ context reciprocally influence one another. For
example, during adolescence, biological and physiological changes may promote risk-taking
behavior, thereby influencing the way people decide to spend their time. The environments that a
person selects may foster the use of alcohol, which in turn may result in acute physiological
reactions that have the potential to trigger long-term biological changes. These changes then may
affect the person’s more immediate behavior as well as move unfolding developmental pathways
toward adverse outcomes, including psychopathology (e.g., anxiety disorders). In this way,
youthful patterns of alcohol initiation and escalation of use can become entry points for pathways
that ultimately lead to abuse and dependence.
However, not all young people experience the same outcome(s) from what may appear to be
similar patterns of adolescent alcohol use. Studying such complexity is difficult, and adding to the
difficulty of understanding these complex pathways at the biological level is the recognition that,
unlike other drugs of abuse, alcohol does not appear to act through a specific receptor. Instead,
alcohol modulates the function of multiple neurotransmitter systems and voltage-gated ion
channels.
At the macro level, pathways that have been associated with the development of alcohol
problems in general, and alcohol dependence more specifically, manifest themselves in the form
of multiple behavioral and physiological characteristics, including disinhibition/ impulsivity,
anxiety, variations in the intensity of response to alcohol, and several independent psychiatric
disorders and alcohol-metabolizing patterns. These characteristics can influence the development
of alcohol dependence through alterations in pathways that determine the rewarding effects of
alcohol, tolerance to some of its intoxicating effects, pathologic effects on the brain, and the
development of withdrawal symptoms (Koob and Le Moal 1997). Genetically conferred
characteristics contribute to the degree and/or rate of development of these changes (Crabbe
2001).
Attempts have been made to categorize people based on the degree and rate that they develop
dependence and to differentiate between the genetic contributions to various categories of
alcohol dependence (Cloninger et al. 1981; Babor et al. 1992). Because the development of
alcohol use, abuse, and alcoholism occurs on a continuum, and because recent data show that
the highest prevalence of alcohol dependence in the population occurs between the ages of 18
and 25, this review focuses on efforts to identify genes contributing to those pathways that appear
in childhood and adolescence (Grant et al. 2004). It must be emphasized, however, that many of
the studies identifying heritable components which may contribute to alcohol abuse or
dependence have been carried out in adults. The extent of their role, if any, in the development of
alcohol problems in youth, therefore, remains to be determined. Additional genetic contributors to
alcohol problems may be identified by future investigations, and some of these may be more
specific to risk in children and adolescents.
Finding genes that contribute to the development of alcohol abuse and dependence in humans
may be simplified by focusing on endophenotypes (i.e., intermediary connections between the
manifestation of dependence and its biological underpinnings). To this end, human genetic
studies have focused on families that have a high prevalence of members with alcohol
dependence, on twin studies, and on studies assessing potential markers and/or contributors to
risk. By performing genetic analyses on such populations, researchers have identified specific
regions on individual chromosomes that correlate with risk for alcohol dependence (e.g., Reich et
al. 1998; Long et al. 1998; Foroud et al. 2000). In some cases, individual candidate genes have
been associated with these regions.
The goal now is to further refine those regions for which a specific gene has not yet been
identified as responsible for the observed phenotype and to determine respective contributions of
candidate genes to alcohol dependence. Research on how the identified genes interact with other
genes and gene products and with the environment to result in alcohol dependence also is
important. To date, functional polymorphisms in the alcohol-metabolizing enzymes alcohol
dehydrogenase and mitochondrial aldehyde dehydrogenase have been the most thoroughly
documented for providing protective effects in specific populations (reviewed in Oroszi and
Goldman 2004). In addition, the Collaborative Study on the Genetics of Alcoholism (COGA) has
identified specific genes within identified regions that affect risk for alcoholism (reviewed in
Edenberg and Kranzler 2005). These include gamma-aminobutyric acid (GABA) receptor
subunits GABRA2 and GABRG3 and the muscarinic cholinergic receptor. GABRA2 has been
independently confirmed (reviewed in Edenberg and Kranzler 2005).
Other promising candidates that have been implicated and are under investigation include the
serotonin transporter 5-HTT (reviewed in Oroszi and Goldman 2004); specific alleles of the
neurotransmitter dopamine (reviewed in Bowirrat and Oscar-Berman 2005); catechol-Omethyltransferase (COMT) (reviewed in Oroszi and Goldman 2004); neuropeptide Y (NPY)
(reviewed in Oroszi and Goldman 2004; Mottagui-Tabar et al. 2005); and the m opioid receptor
(OPRM) (reviewed in Oroszi and Goldman 2004; Edenberg and Kranzler 2005; Bart et al. 2005).
Animal Studies
In addition to studies with humans, studies using animal models, such as worms, flies, and
rodents, permit researchers to model, in less complex systems, individual biological and
behavioral components that may factor into alcohol problems, including dependence. The goal of
this work is the convergence of findings from human and animal model studies to facilitate the
design of pharmacological agents that can reduce, prevent, or ameliorate alcohol problems,
including dependence and associated consequences.
In model organisms, several basic approaches have been used to uncover genetic influences.
One approach is to generate inbred strains of animals (usually rodents) that voluntarily consume
large amounts of alcohol and those which do not, and then perform genetic analyses to determine
the gene(s) underlying this behavior (reviewed in Crabbe et al. 1994).
For example, a well-studied rodent model of alcoholism uses rats selectively bred for increased
alcohol consumption (i.e., alcohol preferring [P] rats and nonpreferring [NP] rats). P rats, in
addition to voluntarily consuming approximately 10 times more alcohol than NP rats, also selfadminister alcohol and are willing to work for alcohol (reviewed in Crabbe et al. 1994). Because
these characteristics are not typical of most rats, they indicate that, compared with NP rats, P rats
possess a genetically determined difference in the neural substrate for determining the rewarding
value of alcohol. These and other high-drinking strains of rodents are being used to identify
chromosomal locations that correlate with the observed drinking behaviors and then to further
refine this correlation to a single gene (e.g., for review in rats, see Bice et al. 1998; Carr et al.
2003; in mice, see Belknap and Atkins 2001). Although perhaps less complex than human
genetic mapping, such research strategies remain complicated. And such searches are made
even more difficult by the pleiotropic nature of genes (i.e., genes have multiple influences and
sites of action) and their complex interactions.
Transgenic mice (i.e., mice that lack a specific gene [knockout mice] or overexpress a gene
product in a specific cell, tissue, or region) also have been used to assess the role of individual
genes. Examples of candidate genes that have been identified or confirmed using transgenic
mice include neuropeptide Y (reviewed in Thiele et al. 2003), protein kinase A (Thiele et al. 1998),
and the cannabinoid receptor1 (CB1; Wang et al. 2003). More recently, gene mapping has been
combined with gene profiling (i.e., analysis and comparison of gene expression patterns to
identify candidate genes within chromosomal regions). Recently, studies combining these lines of
investigation have identified α-synuclein as a potential contributor to alcohol preference in inbred
preferring (or iP) rats (Liang et al. 2003).
Another major approach using model organisms exploits the ability to generate mutations
randomly across the entire genome of an organism (e.g., in worms or fruit flies) and then to
screen these mutations for specific phenotypes or behaviors following alcohol administration.
Because the basic behavioral responses to acute alcohol exposure are similar among humans,
rodents, and flies, identification of mutant animals that are either more or less sensitive to alcohol
exposure has been an area of active research. Studies in animals and humans suggest that
reduced sensitivity to alcohol in an individual predicts development of alcoholism (Crabbe et al.
1994; Schuckit 1999).
Mutated flies that show an increased sensitivity to the acute effects of ethanol have been
generated. Analyses of the gene mutations present in these flies have implicated the cyclic AMP
(cAMP) signal transduction pathway in the regulation of acute ethanol sensitivity (Moore et al.
1998). The requirement for proper cAMP signaling then was mapped to a small group of
neurosecretory cells in the fly brain, which led to the identification of a cluster of cells in this
location that produces insulinlike peptides (DILPs) (Brogiolo et al. 2001; Rulifson et al. 2002).
Within these specific cells, inhibition of protein kinase A (PKA), a downstream component of the
cAMP signal transduction pathway, increased ethanol sensitivity. In addition, flies that have a
mutation which causes a reduction in insulin receptor activity show increased ethanol sensitivity
(Corl et al. 2005). These results suggest a role for the insulin- signaling pathway in regulating
behavioral responses to alcohol. In apparent contradiction, flies with a mutation in pka-RII, one of
the PKA regulatory subunits, showed reduced sensitivity to ethanol (Park et al. 2000). Similar to
the pka-RII-deficient flies, mice lacking the regulatory subunit of PKA showed increased voluntary
alcohol consumption and were less sensitive to alcohol’s sedative effects (Thiele et al. 2000).
However, mice with reduced levels of Ga’s, the adenylyl cyclase–stimulating G-protein, show
increased ethanol sensitivity and reduced voluntary consumption (Wand et al. 2001). As a group,
these results illustrate the complex nature of the regulation of ethanol sensitivity by the cAMP
signal transduction pathway in a variety of cell types.
Similar lines of investigation in flies and mice also have implicated neuropeptide Y (NPY) in
mediating sensitivity to ethanol sedation and in modulating alcohol consumption (reviewed in
Thiele et al. 2003; Wen et al. 2005). As mentioned previously, NPY also has been identified in
human studies. In addition to sensitivity to acute alcohol administration, other factors such as
reward, craving, and withdrawal also contribute to alcohol dependence. Both corticotropinreleasing factor (CRF) (reviewed in Valdez and Koob 2004) and NPY may play a role in
maintenance of heavy drinking despite serious negative consequences. In addition, the dopamine
pathway has been intensively studied to determine its role in the reward pathway (reviewed in
Koob and Le Moal 1997). More recent studies also suggest a role for the endocannabinoids in the
rewarding effect of ethanol (Wang et al. 2003).
Studies analyzing mutagenized worms have uncovered a role for the calcium-activated large
conductance BK potassium channel in ethanol sensitivity (Davies et al. 2003). A primary function
of this channel is to repolarize active neurons, so activation in the presence of ethanol would
inhibit neuronal activity.
Alcohol use is a complex behavior that emerges from the interplay of genes
and environment in the context of development.
Adolescence
The recognition that the prevalence of alcohol dependence is highest in those ages 18 to 24
focuses attention on identifying the genetic contribution to alcohol initiation in childhood and
adolescence; adolescent developmental pathways to alcohol dependence; and adolescent
vulnerabilities to the consequences of alcohol abuse.
Very early starters (those who initiate alcohol use before age 12) often have several co-occurring
problems that may include various externalizing and internalizing behaviors. Ongoing research is
attempting to determine the order of causation and the potential underlying mechanisms that may
be responsible for multiple problems as well as to identify early markers that might indicate some
of those in need of early intervention. For example, what Cloninger (1987) classified as Type II
alcoholism (characterized as male-limited, early onset, and occurring in sensation-seeking people
and people with impaired impulse control) historically has been attributed to serotonergic
dysfunction (Linnoila et al. 1994). Variation in the serotonin transporter gene promoter (5HTTLPR) in humans has been associated with Type II alcoholism as well as with other
neuropsychiatric diseases (Hallikainen et al. 1999; Saunder et al. 1998). Work in nonhuman
primates has confirmed this relationship between excessive alcohol consumption and serotonin
system genes in macaques; and, in addition, it has integrated research on the effects of early
environmental stressors. In particular, this work has shown how environmental factors can
influence gene expression to produce different patterns of behavior (see also Barr et al. 2004 for
review).
The gene that encodes the enzyme monoamine oxidase A (MAOA) also influences synaptic
concentrations of serotonin. Among adolescent and young adult male rhesus macaques, studies
suggest that MAOA gene promoter variation may confer risk for alcohol dependence. Given that
this gene resides on the X chromosome (males only have a single copy and females have two),
males may be particularly susceptible to alterations in its expression. In humans, a polymorphism
in the transcriptional control region of this gene has been associated with antisocial behavior in
alcohol-dependent males (Samochowiec et al. 1999) and with impulsivity, hostility, and a lifetime
history of aggression in a community sample of men (Manuck et al. 2000).
Environmental factors and genetic variations may result in similar phenotypes by affecting levels
of specific gene products. For example, nonhuman primates that are removed from their parents
at birth and reared with age-matched peers exhibit higher levels of anxiety and deficits in impulse
control and are prone to violently aggressive behaviors. These animals also consume significantly
higher volumes of alcohol and are more likely to drink to intoxication than are those reared with
their parents under baseline nonstressful conditions (Higley et al. 1991). When stress is induced
in mother-reared monkeys, however, they increase their alcohol consumption to that of their peerreared counterparts. If peer-reared monkeys are given the serotonin reuptake inhibitor sertraline,
alcohol consumption as well as anxiety and aggression are decreased (Higley and Linnoila
1997a). The level of the serotonin metabolite 5-hydroxyindoleacetic acid (5-HIAA) concentrations
in the cerebrospinal fluid predicts subjects’ response to sertaline, suggesting that a deficit in
serotonin underlies these behaviors (see also Barr et al. 2004 for review).
Consistent with the findings from adult twin studies, problematic use of alcohol in adolescence
has been found to be more heritable than are initiation and more limited use. In a study
specifically addressing adolescents, Rhee and colleagues (2003) applied a logistic regression
model to data collected from sibling/twin/adopted adolescents ages 12–19. Their analysis
resulted in the following conclusions:



Alcohol initiation arises from genetic and from shared (common, family) and nonshared
(uniquely experienced) environmental contributions.
Alcohol use is minimally influenced by genetics but rather arises largely from
environmental influences (shared, nonshared, and twin-shared experiences).
Problem use of alcohol has a high heritability component and is significantly influenced
by nonshared environmental influences (peer experiences, accessibility), but the
contribution of shared environment (family) is small (Rhee et al. 2003).
Whether the specific genes underlying the stages in the progression from initiation to problem
alcohol use are different, and whether the influence of specific genes and their expression vary
with age and/or context remains to be determined.
These findings are consistent with those from other studies of adolescents. Rose and colleagues
(2001) also reported that the strength of genetic influence on adolescent drinking behavior
appears to increase from modest levels in midadolescence to moderate levels by late
adolescence. And these types of findings are not unique to alcohol use; in late adolescence,
genetic influences on problem drinking appear to overlap extensively with genetic influences on
other indicators of disinhibited behavior (Krueger et al. 2002; Young et al. 2000). Although this
latter research suggests that abusive drinking in late adolescence may be driven substantially by
inherited differences in a general disposition to undercontrolled behavior, it does not rule out the
influence of alcohol-specific genetic effects (i.e., genetic influences on alcohol sensitivity), or the
impact of contextual factors. Indeed, mounting evidence exists that genetic influences on complex
behavioral outcomes such as drinking behavior reflect a complex interplay between inherited and
environmental factors (Rutter and Silberg 2002), the implications of which are only beginning to
be explored for models of adolescent drinking (Rose et al. 2001).
ADOLESCENCE AND IN VIVO ALCOHOL PHARMACOKINETICS
Adolescence is associated with profound physiological changes that almost certainly have an
impact on in vivo alcohol pharmacokinetics. There is scant direct evidence in humans of any
differences between the pharmacokinetics of alcohol in adolescents compared with adults, and
for good reason—no one would expose young people to alcohol for research purposes. Although
data relevant to this point in humans is lacking, the ontogeny (i.e., development over the life span
of an individual) of ethanol metabolism has been examined in laboratory animals. (Note, however,
that what may be called “adolescence” in animals may not precisely correspond to the same
developmental period in humans, especially when differences in the timing of adolescence in
human males and females are considered.) These studies suggest general ontogenetic increases
in alcohol dehydrogenase activity (Raiha et al. 1967; Lad et al. 1984), ethanol elimination rates
(see Kelly et al. 1987), and the rate of ethanol metabolism (Silveri and Spear 2000). An exception
to this pattern sometimes has been seen during adolescence, with adolescent animals
occasionally reported to exhibit slightly higher levels of ethanol metabolism than more mature
animals (Hollstedt et al. 1977; Brasser and Spear 2002). Significant elevations in ethanol
metabolism during adolescence are not always evident (e.g., Kelly et al. 1987; Silveri and Spear
2000), however, and are insufficient to account for the attenuated sensitivity to certain ethanol
effects seen in adolescent animals relative to their more mature counterparts (see Little et al.
1996; Silveri and Spear 2000). What can be expected in human adolescents with respect to
specific aspects of pharmacokinetics as they relate to alcohol effects is based on inference from
animal studies and from research on adults, elements of which are described in the following
sections.
Distribution Volume
One feature of puberty is the appearance of gender differentiation in body fat. Girls have
increased fat as a percentage of body weight (BWt). Because ethanol is soluble in water, the
distribution volume for ethanol (VD, water space /BWt) is decreased in girls. Thus, girls
experience higher blood alcohol concentrations (BACs) when they receive an ethanol dose that is
proportionate to BWt (g ethanol /Kg BWt). In contrast, boys typically gain muscle mass and lose
fat, increasing VD and thus reducing the BAC reached after they receive an ethanol dose
proportionate to body weight (NIAAA 1993).
Elimination of Alcohol
Women reportedly metabolize alcohol faster than do men, a difference that probably becomes
evident over the period of pubertal development. Similarly, the reported variation in alcohol
elimination associated with the menstrual period among women presumably develops over the
same age range. Whether the gender difference is an effect of changes in males or females (or
both) should be determinable in animals (NIAAA 1993).
Absorption Rate and Bioavailability
Both the rate of alcohol absorption and bioavailability are largely influenced by prandial state (the
quantity—and perhaps quality—of food recently ingested). Gender differences in this interaction,
particularly as they may affect first-pass metabolism (the metabolism of alcohol in the stomach
and its first passage through the liver), have been suggested by some but not all studies in adults.
Nothing is known about pre- vs. post-pubertal changes (NIAAA 1993).
NEUROBIOLOGICAL MECHANISMS OF ADOLESCENT ALCOHOL ABUSE AND
DEPENDENCE
Over the past 10 years, basic human and animal research has generated important new
knowledge in the following areas: (1) identification of neurobiological and behavioral risk factors
for alcohol abuse and dependence; (2) determination of the consequences of acute and chronic
heavy drinking during adolescence on brain and behavioral maturation; (3) understanding of the
neuropharmacological, neuroanatomical, hormonal, and behavioral mechanisms underlying the
variable response to alcohol across developmental stages; and (4) assessment of the
contribution of early alcohol exposure (during juvenile and adolescent periods) to excessive
drinking and abnormal cognitive and social functioning in adulthood. Below is a summary of the
current research findings on the neurobiological mechanisms involved in adolescent drinking.
Predisposition to Alcoholism
Neurobehavioral research in human adolescents has largely been limited to studies of neural risk
markers in children with a positive family history of alcoholism. These investigations suggest that
there are subtle heritable neurocognitive and neurophysiological abnormalities in children of
recovering alcoholics which could be early indicators of risk for alcoholism (see Tapert and
Schweinsburg 2005 for a review). The most common finding is reduced P3 amplitude of the
event-related potential in children with familial alcoholism (Begleiter et al. 1984; Hill and
Steinhauer 1993). More recently, other neural risk factors that predate the onset of heavy drinking
are being considered in at-risk youth, such as sleep electroencephalographic abnormalities (Dahl
et al. 2003) and changes in brain structure (Hill et al. 2001) and function (Schweinsburg et al.
2004). For example, it was found that youths with dense family histories of alcoholism show
reduced right amygdala volumes, which correlate with P3 amplitudes (Hill et al. 2001). More
importantly, the neurophysiological and neuroanatomical abnormalities may be most pronounced
during the prepubertal and adolescent years. This latter finding underscores the importance of
considering developmental phases when attempting to identify early risk markers for alcoholism.
Taken together, these studies indicate that subtle neural abnormalities may underlie the heritable
aspects of alcohol use disorders (AUDs) (Begleiter and Porjesz 1999; Pihl and Peterson 1996).
However, some studies suggest that family history of AUDs primarily affects brain functioning in
people who also show conduct disorder, antisocial personality disorder, sensation seeking,
behavioral undercontrol, difficult temperament, or poor impulse control (Bauer and Hesselbrock
1999a,b; Schuckit 1998; Schuckit and Smith 1997; Tarter et al. 1985). Understanding these brain
characteristics helps us to appreciate the brain abnormalities that may be produced by personal
alcohol involvement as opposed to features that are attributable to predrinking risk factors.
As discussed in the genetics section, animal models have been used to study heritable factors
that contribute to alcoholism. The selectively bred alcohol-preferring (P) and high alcohol drinking
(HAD) lines of rats are particularly good models for studying the neural mechanisms of early
onset drinking because they readily consume alcohol in the postnatal weaning stage and attain
adult levels of intake by adolescence. Even as early as adolescence, innate differences are
observed in the P and HAD lines in several neurobiological markers that have been associated
with a genetic susceptibility to high alcohol drinking (McKinzie et al. 1998, 2002; Strother et al.
2003; see McBride et al. 2005 for review).
Further, nonhuman primates with low levels of the serotonin metabolite 5-HIAA have been used
to model key aspects of adolescent behavior, such as impulsiveness and aggressiveness,
tolerance to alcohol’s effects on initial exposure to alcohol, and the ability to drink excessive
amounts of alcohol (Higley et al. 1996). Increased availability of serotonin transporters and low
platelet monoamine oxidase activity also are thought to be traitlike markers in nonhuman
primates associated with alcohol sensitivity and increased alcohol consumption (Heinz et al.
2003; Fahlke et al. 2002).
This pattern of behavioral and biochemical markers is similar to that predisposing to early onset
alcoholism in humans and is influenced by genotype–environment interactions. For example,
recent studies in rhesus monkeys found that serotonin transporter genotype influences
cerebrospinal fluid 5-HIAA levels as well as alcohol sensitivity, preference, and consumption, but
only in animals exposed to early life stress (Bennett et al. 2002; Barr et al. 2003). Thus, it is
important to understand the relationships among environmental factors, genetic backgrounds,
and neurobiological markers in predisposing an individual to alcoholism.
Ontogeny of Initial Tolerance and Sensitivity to Alcohol
Adolescent rats consume higher absolute levels of alcohol than do older animals as a result of
multiple factors. One is that adolescents are less sensitive than adult animals to the aversive
effects of acute intoxication (e.g., sedation, ataxia, social impairment, and acute withdrawal/
hangover effects) (Little et al. 1996; Silveri and Spear 1998; White et al. 2002; Doremus et al.
2003; Varlinskaya and Spear 2004; for review, see Spear 2000 and Spear and Varlinskaya
2005). Another is their greater sensitivity to alcohol-induced social facilitation and stimulation of
alcohol intake by social experiences (Hunt et al. 2001; Varlinskaya et al. 2001; Varlinskaya and
Spear 2002; for review, see Spear 2000 and Spear and Varlinskaya 2005). The neural basis for
the developmental differences in initial response to alcohol remains speculative. Recent evidence
suggests, however, that the relative resistance of adolescents to the sedative effects of alcohol is
related in part to both accelerated development of acute tolerance (Silveri and Spear 1998;
Swartzwelder et al. 1998) and developmental immaturity of the GABA (Silveri and Spear 2002; Li
et al. 2003) and/or NMDA (Silveri and Spear 2004) receptor systems. The available data on the
consequences of longer-term adaptations (i.e., rapid and chronic tolerance) to alcohol’s effects in
adolescents are inconsistent, with studies indicating more tolerance in adolescents than adults,
similar levels of tolerance, or the appearance of sensitization rather than tolerance after repeated
adolescent exposures (see Spear and Varlinskaya 2005).
Stress, Hormones, Adolescence, and Alcohol Abuse
Late childhood and adolescence are periods marked by dramatic sexual and psychosocial
development. Between the ages of 5 and 9, adrenarche occurs, resulting in increased secretion
of many adrenal steroids (cortisol, androstenedione, dehydroepiandosterone). Adrenal androgens
in humans are associated with auxiliary and pubic hair growth and a slight increase in bone and
skeletal growth. This is followed by maturation of the reproductive system, also referred to as
“gonadarche,” which is characterized by increased activity of gonadotropins and the sex steroids
(estradiol in females and testosterone in males). The hypothalamic-pituitary- adrenal axis
response to stress also undergoes development during the pubertal period (e.g., Goldman et al.
1973; Sapolsky et al. 1985). Increased life stressors associated with sexual and social
maturation, together with hormonally induced mood and behavior changes, could contribute to
increased consumption of alcohol during the adolescent period (Tschann et al. 1994).
In adult humans and animals, the relationships among stress, drinking, and underlying
neuroendocrine or neurochemical mechanisms are complex. However, basic animal research
suggests that stress-induced changes in glucocorticoids (i.e., corticosterone) may interact with
neurotransmitters in the mesolimbic reward system to facilitate drinking. In adolescents, the
interaction between stress and drinking is even more complicated because the neural systems
involved in modulating alcohol reward and/or stress are undergoing development (see Spear
2000 for review).
In a few studies of adolescent nonhuman primates, it has been shown that under conditions of
social separation stress, subjects double their rates of alcohol consumption (Higley and Linnoila
1997b; Fahlke et al. 2000). In these studies, individual differences in stress-induced drinking are
attributed to anxietylike behaviors mediated by ontogenetic changes in cortisol and corticotropin
levels or to poor impulse control and impaired social competence associated with reduced
serotonin functioning (a traitlike marker present in infancy).
In rats, findings indicate that adolescent animals exhibit an attenuated corticosterone response to
alcohol challenge compared with adults, and that gender differences in this response begin to
emerge at adolescence (Ogilvie and Rivier 1996; Silveri and Spear 2004; for review, see Spear
2000). If elevations in corticosterone contribute to the rewarding effects of alcohol, as indicated in
adult animals, then adolescents may need to increase their levels of alcohol to attain the
reinforcing value reached by more mature animals at lower levels. At this point, however, any
hypothesized interactions between stress-induced changes in hormones and reward-related
neurotransmitters, and their impact on adolescent drinking, remain tentative.
Gonadal hormones influence many aspects of brain development and behavior outside the realm
of reproductive functions via their actions on receptors located throughout the brain (see Wang et
al. 2002; McEwen 2002 for reviews). Alcohol’s disruptive effects on pubertal hormone secretion
may interfere with hormonally mediated developmental processes and result in negative
behavioral outcomes. For example, alcohol-induced increases in testosterone are related to
augmented aggression in male hamsters following chronic alcohol exposure during adolescence
(Ferris et al. 1998). Evidence from adult female nonhuman primates indicates that sensitivity to
the subjective effects of ethanol changes during different phases of the menstrual cycle as a
result of alterations in endogenous levels of ovarian-derived hormones (Grant et al. 1997).
However, virtually nothing is known about adolescent females’ sensitivity to the subjective or
aggressive effects of alcohol or the correlation of these effects with cyclical hormonal changes.
Given that adolescence is a time when hormonal and brain systems are still developing in
humans and animals, research on the relationships among life stressors, affective states, and
hormonal/neurotransmitter interactions may be critical to understanding the onset, maintenance,
and consequences of adolescent drinking.
REFERENCES
Babor, T.F.; Hofmann, M.; DelBoca, F.K.; et al. Types of alcoholics, I. Evidence for an empirically
derived typology based on indicators of vulnerability and severity. Archives of General Psychiatry
49:599–608, 1992. PMID: 1637250
Barr, C.S.; Newman, T.K.; Becker, M.L.; et al. Serotonin transporter gene variation is associated
with alcohol sensitivity in rhesus macaques exposed to early-life stress. Alcoholism: Clinical and
Experimental Research 27:812–817, 2003. PMID: 12766626
Barr, C.S.; Schwandt, M.L; Newman, T.K.; and Higley, J.D. The use of adolescent nonhuman
primates to model human alcohol intake: Neurobiological, genetic, and psychological variables.
Annals of the New York Academy of Sciences 1021:221–233, 2004. PMID: 15251892
Bart, G.; Schluger, J.H.; Borg, L.; et al. Nalmefene induced elevation in serum prolactin in normal
human volunteers: Partial kappa opioid agonist activity? Neuropsychopharmacology 2005. (Epub
ahead of print) PMID: 15988468
Bauer, L.O., and Hesselbrock, V.M. P300 decrements in teenagers with conduct problems:
Implications for substance abuse risk and brain development. Biological Psychiatry 46:263–272,
1999a. PMID: 10418702
Bauer, L.O., and Hesselbrock, V.M. Subtypes of family history and conduct disorder: Effects on
P300 during the Stroop Test. Neuropsychopharmacology 21:51–62, 1999b. PMID: 10379519
Begleiter, H., and Porjesz, B. What is inherited predisposition toward alcoholism? A proposed
model. Alcoholism: Clinical and Experimental Research 23:1125–1135, 1999. PMID: 10443977
Begleiter, H.; Porjesz, B.; Bihari, B.; and Kissin, B. Event-related brain potentials in boys at risk
for alcoholism. Science 255:1493–1496, 1984. PMID: 6474187
Belknap, J.K., and Atkins, A.L. The replicability of QTLs for murine alcohol preference drinking
behavior across eight independent studies. Mammalian Genome 12:893–899, 2001. PMID:
11707775
Bennett, A.J.; Lesch, K.P.; Heils, A.; et al. Early experience and serotonin transporter gene
variation interact to influence primate CNS function. Molecular Psychiatry 7:118–122, 2002. PMID:
11803458
Bice, P.; Fouroud, T.; Bo, R.; et al. Genomic screen for QTLs underlying alcohol consumption in
the P and NP rat lines. Mammalian Genome 9:949–955, 1998. PMID: 9880658
Bowirrat, A., and Oscar-Berman, M. Relationship between dopaminergic neurotransmission,
alcoholism, and Reward Deficiency syndrome. American Journal of Medical Genetics Part B
(Neuropsychiatric Genetics) 132B:29–37, 2005. PMID: 15457501
Brasser, S.M., and Spear, N.E. Physiological and behavioral effects of acute ethanol hangover in
juvenile, adolescent, and adult rats. Behavioral Neuroscience 116:305–320, 2002. PMID:
11996316
Brogiolo, W.; Stocker, H.; Ikeya, T.; et al. An evolutionarily conserved function of the Drosophila
insulin receptor and insulin-like peptide in growth control. Current Biology: CB 11:213–221, 2001.
PMID: 11250149
Carr, L.G.; Habegger, K.; Spence, J.; et al. Analysis of quantitative trait loci contributing to alcohol
preference in HAD1/LAD1 and HAD2/LAD2 rats. Alcoholism: Clinical and Experimental Research
27:1710–1717, 2003. PMID: 14634485
Cloninger, C.R. Neurogenetic adaptive mechanisms in alcoholism. Science 236:410–416, 1987.
PMID: 2882604
Cloninger, C.R.; Bohman, M.; and Sigvardsson, S. Inheritance of alcohol abuse: Cross-fostering
analysis of adopted men. Archives of General Psychiatry 38:861–868, 1981. PMID: 7259422
Corl, A.B.; Rodan, A.R.; and Heberlein, U. Insulin signaling in the nervous system regulates
ethanol intoxication in Drosophila melanogaster. Nature Neuroscience 8:18–19, 2005. PMID:
15592467
Crabbe, J.C. Use of genetic analyses to refine phenotypes related to alcohol tolerance and
dependence. Alcoholism: Clinical and Experimental Research 25:288–292, 2001. PMID: 11236845
Crabbe, J.C.; Belknap, J.K.; and Buck, K.J. Genetic animal models of alcohol and drug abuse.
Science 264:1715–1723, 1994. PMID: 8209252
Dahl, R.E.; Williamson, D.E.; Bertocci, M.A.; et al. Spectral analyses of sleep EEG in depressed
offspring of fathers with or without a positive history of alcohol abuse or dependence: A pilot
study. Alcohol 30:193–200, 2003. PMID: 13679113
Davies, A.G.; Pierce-Shimomura, J.T.; Kim, H.; et al. A central role of the BK potassium channel
in behavioral responses to ethanol in C. elegans. Cell 115:655–666, 2003. PMID: 14675531
Doremus, T.L.; Brunell, S.C.; Varlinskaya, E.I.; and Spear, L.P. Anxiogenic effects during
withdrawal from acute ethanol in adolescent and adult rats. Pharmacology, Biochemistry and
Behavior 75:411–418, 2003. PMID: 12873633
Edenberg, H.J., and Kranzler, H.R. The contribution of genetics to addiction therapy approaches.
Pharmacology & Therapeutics 2005. 108:86–93, 2005. PMID: 16026844
Fahlke, C.; Lorenz, J.G.; Long, J.; et al. Rearing experiences and stress-induced plasma cortisol
as early risk factors for excessive alcohol consumption in nonhuman primates. Alcoholism:
Clinical and Experimental Research 24:644–650, 2000. PMID: 10832905
Fahlke, C.; Garpenstrand, H.; Oreland, L.; et al. Platelet monoamine oxidase activity in a
nonhuman primate model of type 2 excessive alcohol consumption. American Journal of
Psychiatry 159:2107, 2002. PMID: 12450967
Ferris, C.F.; Shtiegman, K.; and King, J.A. Voluntary ethanol consumption in male adolescent
hamsters increases testosterone and aggression. Physiology & Behavior 63:739–744, 1998.
PMID: 9617993
Foroud, T.; Edenberg, H.J.; Goate, A.; et al. Alcoholism susceptibility loci: Confirmation studies in
a replicate sample and further mapping. Alcoholism: Clinical and Experimental Research 24:933–
945, 2000. PMID: 10923994
Goldman, L.; Winget, C.; Hollingshead, G.W.; and Levine, S. Postweaning development of
negative feedback in the pituitary-adrenal system of the rat. Neuroendocrinology 12:199–211,
1973. PMID: 4353346
Grant, K.A.; Azarov, A.; Shively, C.A.; and Purdy, R.H. Discriminative stimulus effects of ethanol
and 3 alpha-hydroxy-5 alpha-pregnan-20-one in relation to menstrual cycle phase in cynomolgus
monkeys (Macaca fascicularis). Psychopharmacology 130:59–68, 1997. PMID: 9089848
Grant, B.F.; Dawson, D.A.; Stinson, F.S.; et al. The 12-month prevalence and trends in DSM–IV
alcohol abuse and dependence: United States, 1991–1992 and 2001–2002. Drug and Alcohol
Dependence 74:223–234, 2004. PMID: 15194200
Hallikainen, T.; Saito, T.; Lachman, H.M.; et al. Association between low activity serotonin
transporter promoter genotype and early onset alcoholism with habitual impulsive violent
behavior. Molecular Psychiatry 4:385–388, 1999. PMID: 10483057
Heinz, A.; Jones, D.W.; Gorey, J.G.; et al. Serotonin transporter availability correlates with alcohol
intake in non-human primates. Molecular Psychiatry 8:231–234, 2003. PMID: 12610654
Higley, J.D., and Linnoila, M. Low central nervous system serotonergic activity is traitlike and
correlates with impulsive behavior. A nonhuman primate model investigating genetic and
environmental influences on neurotransmission. Annals of the New York Academy of Sciences
836:39–56, 1997a. PMID: 9616793
Higley, J.D., and Linnoila, M. A nonhuman primate model of excessive alcohol intake: Personality
and neurobiological parallels of type I- and type II-like alcoholism. In: Galanter, M., ed. Recent
Developments in Alcoholism, Vol. 13: Alcoholism and Violence: Epidemiology, Neurobiology,
Psychology, Family Issues. New York: Plenum, 1997b. pp. 191–219. PMID: 9122496
Higley, J.D.; Hasert, M.F.; Suomi, S.J.; and Linnoila, M. Nonhuman primate model of alcohol
abuse: Effects of early experience, personality, and stress on alcohol consumption. Proceedings
of the National Academy of Sciences of the United States of America 88:7261–7265, 1991. PMID:
1871131
Higley, J.D.; Suomi, S.J.; and Linnoila, M. A nonhuman primate model of type II alcoholism? Part
2. Diminished social competence and excessive aggression correlates with low cerebrospinal
fluid 5-hydroxyindoleacetic acid concentrations. Alcoholism: Clinical and Experimental Research
20:643–650, 1996. PMID: 8800379
Hill, S.Y., and Steinhauer, S.R. Assessment of prepubertal and postpubertal boys and girls at risk
for developing alcoholism with P300 from a visual discrimination task. Journal of Studies on
Alcohol 54:350–358, 1993. PMID: 8487544
Hill, S.Y.; De Bellis, M.D.; Keshavan, M.S.; et al. Right amygdala volume in adolescent and young
adult offspring from families at high risk for developing alcoholism. Biological Psychiatry 49:894–
905, 2001. PMID: 11377407
Hollstedt, C.; Olsson, O.; and Rydberg, U. The effect of alcohol on the developing organism:
Genetical, teratological and physiological aspects. Medical Biology 55:1–14, 1977. PMID: 321891
Hunt, P.S.; Holloway, J.L.; and Scordalakes, E.M. Social interaction with an intoxicated sibling
can result in increased intake of ethanol by periadolescent rats. Developmental Psychobiology
38:101–109, 2001. PMID: 11223802
Kelly, S.J.; Bonthius, D.J.; and West, J.R. Developmental changes in alcohol pharmacokinetics in
rats. Alcoholism: Clinical and Experimental Research 11:281–286, 1987. PMID: 3307494
Koob, G.F., and Le Moal, M. Drug abuse: Hedonic homeostatic dysregulation. Science 278:52–
58, 1997. PMID: 9311926
Krueger, R.F.; Hicks, B.M.; Patrick, C.J.; et al. Etiologic connections among substance
dependence, antisocial behavior, and personality: Modeling the externalizing spectrum. Journal of
Abnormal Psychology 111:411–424, 2002. PMID: 12150417
Lad, P.J.; Schenk, D.B.; and Leffert, H.L. Inhibitory monoclonal antibodies against rat liver alcohol
dehydrogenase. Archives of Biochemistry and Biophysics 235:589–595, 1984. PMID: 6393880
Li, Q.; Wilson, W.A.; and Swartzwelder, H.S. Developmental differences in the sensitivity of
hippocampal GABAA receptor-mediated IPSCS to ethanol. Alcoholism: Clinical and Experimental
Research 27:2017–2022, 2003. PMID: 14691391
Liang, T.; Spence, J.; Liu, L.; et al. Alpha-synuclein maps to a quantitative trait locus for alcohol
preference and is differentially expressed in alcohol-preferring and -nonpreferring rats.
Proceedings of the National Academy of Sciences of the United States of America 100:4690–
4695, 2003. PMID: 12665621
Linnoila, M.; Virkkunen, M.; George, T.; et al. Serotonin, violent behavior and alcohol. Experientia
(Suppl. 71):155–163, 1994. PMID: 7518265
Little, P.J.; Kuhn, C.M.; Wilson, W.A.; and Swartzwelder, H.S. Differential effects of ethanol in
adolescent and adult rats. Alcoholism: Clinical and Experimental Research 20:1346–1351, 1996.
PMID: 8947309
Long, J.C.; Knowler, W.C.; Hanson, R.L.; et al. Evidence for genetic linkage to alcohol
dependence on chromosomes 4 and 11 from an autosome-wide scan in an American Indian
population. American Journal of Medical Genetics. Part B: Neuropsychiatric Genetics 81:216–
221, 1998. PMID: 9603607
Manuck, S.B.; Flory, J.C.; Ferrell, R.E.; et al. A regulatory polymorphism of the monoamine
oxidase-A gene may be associated with variability in aggression, impulsivity, and central nervous
system serotonergic responsivity. Psychiatry Research 95:9–23, 2000. PMID: 10904119
McBride, W.J.; Bell, R.L.; Rodd, Z.A.; et al. Adolescent alcohol drinking and its long-range
consequences: Studies with animal models. In: Galanter, M., ed. Recent Developments in
Alcoholism, Vol. 17: Alcohol Problems in Adolescents and Young Adults: Epidemiology,
Neurobiology, Prevention, Treatment. New York: Springer, 2005. pp. 123–142. PMID: 15789863
McEwen, B. Estrogen actions throughout the brain. Recent Progress in Hormone Research
57:357–584, 2002. PMID: 12017552
McKinzie, D.L.; Nowak, K.L.; Murphy, J.M.; et al. Development of alcohol drinking behavior in rat
lines selectively bred for divergent alcohol preference. Alcoholism: Clinical and Experimental
Research 22:1584–1590, 1998. PMID: 9802545
McKinzie, D.L.; McBride, W.J.; Murphy, J.M.; et al. Effects of amphetamine on locomotor activity
in adult and juvenile alcohol-preferring and -nonpreferring rats. Pharmacology, Biochemistry and
Behavior 71:29–36, 2002. PMID: 11812505
Moore, M.S.; DeZazzo, J.; Luk, A.Y.; et al. Ethanol intoxication in Drosophila: Genetic and
pharmacological evidence for regulation by the cAMP signaling pathway. Cell 93:997–1007,
1998. PMID: 9635429
Mottagui-Tabar, S.; Prince, J.A.; Wahlestedt, C.; et al. A novel single nucleotide polymorphism of
the neuropeptide Y (NPY) gene associated with alcohol dependence. Alcoholism: Clinical and
Experimental Research 29:702–707, 2005. PMID: 15897713
National Institute on Alcohol Abuse and Alcoholism. Biochemical effects of alcohol metabolism.
In: Eighth Special Report to the U.S. Congress on Alcohol and Health. Bethesda, MD: National
Institutes of Health, 1993. pp. 148–164.
Ogilvie, K., and Rivier, C. Gender difference in alcohol-evoked hypothalamic-pituitary-adrenal
activity in the rat: Ontogeny and role of neonatal steroids. Alcoholism: Clinical and Experimental
Research 20:255–261, 1996. PMID:8730215
Oroszi, G., and Goldman, D. Alcoholism: Genes and mechanisms. Pharmacogenomics 5:1037–
1048, 2004. PMID: 15584875
Park, S.K.; Sedore, S.A.; Cronmiller, C.; and Hirsh J. PKA-RII-deficient Drosophila are viable but
show developmental, circadian and drug response phenotypes. Journal of Biological Chemistry
275:20588–20596, 2000. PMID: 10781603
Pihl, R.O., and Peterson, J. Characteristics and putative mechanisms in boys at risk for drug
abuse and aggression. In: Craig, T.G., and Ferris, F., eds. Understanding aggressive behavior in
children. Annals of the New York Academy of Sciences 794:238–252, 1996. PMID: 8853606
Raiha, N.C.; Koskinen, M.; and Pikkarainen, P. Developmental changes in alcoholdehydrogenase activity in rat and guinea-pig liver. Biochemical Journal 103:623–626, 1967. PMID:
6069164
Reich, T.; Edenberg, H.J.; Goate, A.; et al. Genome-wide search for genes affecting the risk for
alcohol dependence. American Journal of Medical Genetics 81:207–215, 1998. PMID: 9603606
Rhee, S.H.; Hewitt, J.K.; Young, S.E.; et al. Genetic and environmental influences on substance
initiation, use, and problem use in adolescents. Archives of General Psychiatry 60:1256–1264,
2003. PMID: 14662558
Rose, R.J.; Dick, D.M.; Viken, R.J.; and Kaprio, J. Gene-environment interaction in patterns of
adolescent drinking: Regional residency moderates longitudinal influences on alcohol use.
Alcoholism: Clinical and Experimental Research 25:637–643, 2001. PMID: 11371711
Rulifson, E.J.; Kim, S.K.; and Nusse, R. Ablation of insulin-producing neurons in flies: Growth and
diabetic phenotypes. Science 296:1118–1120, 2002. PMID: 12004130
Rutter, M., and Silberg, J. Gene-environment interplay in relation to emotional and behavioral
disturbance. Annual Review of Psychology 53:463–490, 2002. PMID: 11752493
Samochowiec, J.; Lesch, K.P.; Rottmann, M.; et al. Association of a regulatory polymorphism in
the promoter region of the monoamine oxidase A gene with antisocial alcoholism. Psychiatry
Research 86:67–72, 1999. PMID: 10359483
Sapolsky, R.M.; Meaney, M.J.; and McEwen, B.S. The development of the glucocorticoid receptor
system in the rat limbic brain. III. Negative-feedback regulation. Developmental Brain Research
18:169–173, 1985. PMID: 3986611
Saunder, T.; Harms, H.; Dufeu, P.; et al. Serotonin transporter gene variants in alcoholdependent subjects with dissocial personality disorder. Biological Psychiatry 43:908–912, 1998.
PMID: 9627746
Schuckit, M.A. Biological, psychological and environmental predictors of the alcoholism risk: A
longitudinal study. Journal of Studies on Alcohol 59:485–494, 1998. PMID: 9718100
Schuckit, M.A. New findings in the genetics of alcoholism. JAMA: Journal of the American
Medical Association 281:1875–1876, 1999. PMID: 10349877
Schuckit, M.A., and Smith, T.L. Assessing the risk for alcoholism among sons of alcoholics.
Journal of Studies on Alcohol 58:141–145, 1997. PMID: 9065891
Schweinsburg, A.D.; Paulus, M.P.; Barlett, V.C.; et al. An fMRI study of response inhibition in
youths with a family history of alcoholism. Annals of the New York Academy of Sciences
1021:391–394, 2004. PMID: 15251915
Silveri, M.M., and Spear, L.P. Decreased sensitivity to the hypnotic effects of ethanol early in
ontogeny. Alcoholism: Clinical and Experimental Research 22:670–676, 1998. PMID: 9622449
Silveri, M.M., and Spear, L.P. Ontogeny of ethanol elimination and ethanol-induced hypothermia.
Alcohol 20:45–53, 2000. PMID: 10680716
Silveri, M.M., and Spear, L.P. The effects of NMDA and GABAA pharmacological manipulations
on ethanol sensitivity in immature and mature animals. Alcoholism: Clinical and Experimental
Research 26:449–456, 2002. PMID: 11981119
Silveri, M.M., and Spear, L.P. Characterizing the ontogeny of ethanol-associated increases in
corticosterone. Alcohol 32:145–155, 2004. PMID: 15163565
Spear, L.P. The adolescent brain and age-related behavioral manifestations. Neuroscience and
Biobehavioral Reviews 24:417–463, 2000. PMID: 10817843
Spear, L.P., and Varlinskaya, E.I. Adolescence: Alcohol sensitivity, tolerance, and intake. In:
Galanter, M., ed. Recent Developments in Alcoholism, Vol. 17: Alcohol Problems in Adolescents
and Young Adults: Epidemiology, Neurobiology, Prevention, Treatment. New York: Springer,
2005. pp. 143–159. PMID: 15789864
Strother, W.N.; Lumeng, L.; Li, T.K.; and McBride, W.J. Regional CNS densities of serotonin 1A
and dopamine D2 receptors in periadolescent alcohol-preferring P and alcohol-nonpreferring NP
rat pups. Pharmacology, Biochemistry, and Behavior 74:335–342, 2003. PMID: 12479952
Swartzwelder, H.S.; Richardson, R.C.; Markwiese-Foerch, B.; et al. Developmental differences in
the acquisition of tolerance to ethanol. Alcohol 15:311–314, 1998. PMID: 9590516
Tapert, S.F., and Schweinsburg, A.D. The human adolescent brain and alcohol use disorders. In:
Galanter, M., ed. Recent Developments in Alcoholism, Vol. 17: Alcohol Problems in Adolescents
and Young Adults: Epidemiology, Neurobiology, Prevention, Treatment. New York: Springer,
2005. pp. 177–197. PMID: 15789866
Tarter, R.E.; Alterman, A.I.; and Edwards, K.L. Vulnerability to alcoholism in men: A behaviorgenetic perspective. Journal of Studies on Alcohol 46:329–356, 1985. PMID: 4033133
Thiele, T.E.; March, D.J.; Ste. Marie, L.; et al. Ethanol consumption and resistance are inversely
related to neuropeptide Y levels. Nature 396:366–369, 1998. PMID: 9845072
Thiele, T.E.; Willis, B.; Stadler, J.; et al. High ethanol consumption and low sensitivity to ethanolinduced sedation in protein kinase A-mutant mice. Journal of Neuroscience 20:RC75, 2000.
PMID: 10783399
Thiele, T.E.; Navarro, M.; Sparta, D.R.; et al. Alcoholism and obesity: Overlapping neuropeptide
pathways? Neuropeptides 37:321–337, 2003. PMID: 14698675
Tschann, J.M.; Adler, N.E.; Irwin, C.E., Jr.; et al. Initiation of substance use early in early
adolescence: The roles of pubertal timing and emotional distress. Health Psychology 13:326–
333, 1994. PMID: 7957011
Valdez, G.R., and Koob, G.F. Allostasis and dysregulation of corticotropin-releasing factor and
neuropeptide Y systems: Implications for the development of alcoholism. Pharmacology,
Biochemistry and Behavior 79:671–689, 2004. PMID: 15582675
Varlinskaya, E.I., and Spear, L.P. Acute effects of ethanol on social behavior of adolescent and
adult rats: Role of familiarity of the test situation. Alcoholism: Clinical and Experimental Research
26:1502–1511, 2002. PMID: 12394283
Varlinskaya, E.I., and Spear, L.P. Acute ethanol withdrawal (hangover) and social behavior in
adolescent and adult male and female Sprague-Dawley rats. Alcoholism: Clinical and
Experimental Research 28:40–50, 2004. PMID: 14745301
Varlinskaya, E.I.; Spear, L.P.; and Spear, N.E. Acute effects of ethanol on behavior of adolescent
rats: Role of social context. Alcoholism: Clinical and Experimental Research 25:377–385, 2001.
PMID: 11290848
Wand, G.; Levine, M.; Zweifel, L.; et al. The cAMP-protein kinase A signal transduction pathway
modulates ethanol consumption and sedative effects of ethanol. Journal of Neuroscience
21:5297–5303, 2001. PMID: 1148605
Wang, L.; Andersson, S.; Warner, M.; and Gustafsson, J.A. Estrogen actions in the brain. Sci
STKE [electronic resource]: Signal Transduction Knowledge Environment 138:PE29, 2002. PMID:
12084905
Wang, L.; Liu, J.; Harvey-White, J.; et al. Endocannabinoid signaling via cannabinoid receptor 1 is
involved in ethanol preference and its age-dependent decline in mice. Proceedings of the
National Academy of Sciences of the United States of America 100:1393–1398, 2003. PMID:
12538878
Wen, T.; Parrish, C.A.; Xu, D.; et al. Drosophila neuropeptide F and its receptor, NPFR1, define a
signaling pathway that acutely modulates alcohol sensitivity. Proceedings of the National
Academy of Sciences of the United States of America 102:2141–2146, 2005. PMID: 15677721
White, A.M.; Truesdale, M.C.; Bae, J.G.; et al. Differential effects of ethanol on motor coordination
in adolescent and adult rats. Pharmacology, Biochemistry and Behavior 73:673–677, 2002. PMID:
12151043
Young, S.E.; Stallings, M.C.; Corley, R.P.; et al. Genetic and environmental influences on
behavioral disinhibition. American Journal of Medical Genetics. Part B: Neuropsychiatric Genetics
96:684–695, 2000. PMID: 11054778
Psychosocial Processes and Mechanisms of
Risk and Protection
Psychosocial research on adolescent drinking includes studies of personality and the
impact of particular personality traits on drinking risk, expectancies (that is, the effects
someone expects after drinking alcohol), and cognitive development. Although studies
involving adolescents have not identified specific sets of personality traits that uniquely
predict alcohol use, some traits have been shown to be associated with heavy alcohol use
and alcohol use disorders. These traits include disinhibition or poor self-regulation,
impulsiveness and aggression, novelty-seeking, and negative affectivity. Externalizing
behaviors in childhood and early adolescence have been found to predict alcohol use
disorders in early adulthood, as have certain internalizing behaviors. This article examines
the theories and psychosocial processes thought to underlie underage drinking. Key
words: underage drinking; adolescent; cause of AODU (alcohol and other drug use); risk factors;
protective factors; AOD expectancies; predictive factor; AOD use behavior; personality theory of
AODU; psychosocial environment; personality trait; negative emotionality; positive emotionality
OVERVIEW
The interactions among alcohol-related genes, biological development, and environment play out
in the psychological processes underlying adolescent decisions to drink or to abstain from
drinking. Psychosocial research on adolescent drinking encompasses studies of personality and
the impact of particular personality traits on drinking risk, expectancies (the effects someone
expects from drinking alcohol), and cognitive development.
As is true for adults, studies involving adolescents have repeatedly failed to find specific sets of
personality traits that uniquely predict alcohol use. In addition, adolescence is a period of change,
and personality is not as stable as it will be in adulthood. Nonetheless, some personality traits
have been shown to be associated with heavy alcohol use and alcohol use disorders in
adolescents. These traits include disinhibition or poor self-regulation, impulsiveness and
aggression, and novelty-seeking. Longitudinal studies have found that externalizing behaviors in
childhood and early adolescence predict alcohol use disorders in early adulthood.
Negative emotionality—depression and anxiety—also have been found to predict alcohol
problems. Adolescents in this case may use drinking as a coping strategy.
Expectancies about the effects of alcohol are measurable in children before they ever begin to
drink. Alcohol-related expectancies influence how early a child will begin to drink and how much
she or he will drink at that point. Research suggests that people who have expectancies of more
positive experiences from drinking tend to drink more than others and are at highest risk for
excessive drinking. Research is looking into the neural processes underlying expectancies and
exactly how they drive behavior.
An almost universal theme whenever adolescent drinking is addressed relates to how
adolescents think and make decisions about the world around them. Despite much literature
suggesting that adolescents have not yet reached full maturity in their cognitive processing, when
called upon to make reasoned decisions using abstract processes, they generally do as well as
adults. Differences in decisionmaking appear between adults and adolescents in situations that
may have social or emotional overtones. Like adults, adolescents may vary their judgments
based on social context, but the contexts that encourage such decisionmaking differ for adults
and adolescents.
With this in mind, adolescent thinking and decisionmaking may be best understood as fully
developed for the purpose for which they evolved: to deal with the tremendous transitions that
humans face at this stage of life. The goal for research is how to integrate this emerging
understanding of adolescence with the need to reduce adverse outcomes.
Many factors play a part in the development of adolescent drinking. Comprehensive theories on
(or models of) the development of adolescent drinking create a framework for understanding and
testing ideas about how multiple factors interact to lead to problems with alcohol. One of the
goals of NIAAA’s underage drinking initiative is to stimulate the synthesis and testing of new and
comprehensive models for adolescent drinking within a developmental framework.
PERSONALITY AND ALCOHOL PROBLEMS IN YOUTH
Although the relationship between personality and alcohol use disorders (AUDs) has been
extensively studied in older adolescents and adults (Sher et al. 1999), far less research has been
conducted with respect to personality and alcohol involvement earlier in adolescence. Indeed,
personality in adolescence in general is much less developed as a research area than it is in
adults. This is probably due in part to the tendency among researchers interested in individual
differences in infancy and childhood to focus on temperamental traits that are thought to
represent very basic tendencies in a person’s response to the environment. These
temperamental traits are highly heritable and are usually assessed by parents or other adults. In
contrast, researchers focusing on adults tend to look at more complex traits obtained through
self-reports. Thus, the period of adolescence (especially early adolescence) sits at the junction of
research traditions on childhood temperament and adult personality, which may be why this age
has not received a greater amount of attention and development.
Numerous personality traits have been described in the literature, but research suggests that
most of these can be subsumed by a handful of higher order traits. Researchers disagree on the
number of these higher order traits, but current influential models are usually defined as either
“Big Three” (Eysenck 1990; Tellegen 1985) or “Big Five” (e.g., Costa and McCrae 1992; Digman
1989, 1990; Goldberg 1990, 1992). Big Three approaches typically describe their factors as
representing: (1) negative emotionality or neuroticism, (2) positive emotionality or sociability or
extraversion, and (3) impulsivity or behavioral undercontrol or (lack of) constraint. Both negative
emotionality/neuroticism and positive emotionality/sociability/extraversion have their counterparts
in Big Five approaches, but impulsivity or behavioral undercontrol or (lack of) constraint appears
primarily to be reflected in the Big Five trait of (or lack of) conscientiousness as well as in the Big
Five traits of (low) agreeableness and neuroticism. In addition, a higher order trait referring to
either “openness to experience” or “intellect” (depending upon the personality system) also
emerges. Research in older adolescents and adults strongly suggests that traits related to
behavioral undercontrol are the most strongly associated with both alcohol use and alcohol use
disorders, whereas traits associated with negative emotionality are somewhat less important
(Sher et al. 1999). Existing research suggests that these basic findings generalize to younger
adolescents, but the evidence base at present is somewhat underdeveloped (Caspi et al. 2005).
SIDEBAR
Cognitive Development and Adolescent Decisionmaking
An almost universal theme whenever adolescent drinking is addressed relates to how
adolescents think and make decisions about the world around them. As perhaps a reflection of
this emphasis, the recent National Research Council and Institute of Medicine report on underage
drinking includes two separate background papers on this topic (Halpern-Felsher and Biehl 2004;
Jacobs 2004), which provide a foundation for this overview. The classic conclusion in this domain
is that adolescents have not yet achieved full maturity of their cognitive processing and that they
are more likely than adults to make risky decisions. A large body of literature exists containing
many variations on the theoretical underpinnings for this conclusion. We will not attempt to review
this material in any depth for this article, but a few ideas that have been central to this conclusion
are worth noting. One is that the transition to the Piagetian concept of “formal operations” in
thinking style has not yet taken place. Another view is that adolescents are very egocentric and
feel invulnerable to harm because of their perceived uniqueness (Elkind 1967, 1978). Still another
view is that adolescents use rational (reason-based) thinking in fewer situations than adults and
depend more on intuitive processing that involves cognitive heuristics and judgment biases
(Agnoli 1991; Barrouillet et al. 2002; Davidson 1995; Jacobs and Potenza 1991).
Social considerations are a potentially important factor; that is, adolescents are understood to be
very interested in their social standing among their peers and therefore are more vulnerable to
decisionmaking that relies heavily on what other adolescents are doing. Related to this notion is
that personal identity is less well established in adolescence, with the result that young people
are more influenced by what they perceive others around them to be doing. A more recent
version of this theme is based on neurological development: the neural substrate for emotional
behavior develops in advance of the more frontal, rational decisionmaking portion of the brain
(Luna and Sweeney 2004). Other versions of this theme are more specific to the alcohol field. For
example, a recurrent view is that young people systematically overestimate the frequency and
quantity of drinking being undertaken by their peers (DeJong 2002; Aas and Klepp 1992; Beck
and Treiman 1996).
Although there may be aspects of the above views that warrant further consideration, our
understanding of the general domain of cognitive development and risk taking also is evolving in
a way that offers an entirely different perspective on these issues. First of all, adolescent
decisionmaking generally has not been found to be inferior to that of adults. When called upon to
make reasoned decisions using abstract processes, adolescents generally do as well as adults.
In many instances, however, both adolescents and adults perform poorly; unless reasoned
thinking is somehow explicitly required in a particular circumstance, both adolescents and adults
will use the more intuitive style of problem solving, leading to a generally equal rate of errors. It is
evident, therefore, that we cannot entirely attribute the apparent riskiness of adolescence to
fundamental differences in problem solving between adolescents and adults. Where differences
do appear, however, is in real-world situations that may have social and/or emotional overtones.
In these situations, adolescents often do not make the same choices as adults. When adolescent
decisionmaking is analyzed closely for underlying processes, the results suggest that adolescents
do not use appropriate base rate information about peers but instead use social heuristics or
“rules of thumb” rather than actual counts of behavioral frequencies to vary their judgments based
on particular contexts (e.g., to use different judgment rules when they are with social peers with
high standing in the peer group, etc.) (Gardner and Steinberg 2005; Steinberg 2004).
It is important to appreciate that adults also make decisions and judgments based on these
biases. It is just that the particular content areas that accentuate biased decisionmaking may be
different (e.g., appearance vs. role performance), as may the contexts in which these biases most
often occur. And in some domains, decisionmaking actually may become more biased (i.e.,
based on social heuristics) as children mature into adolescence. It is clearly not the case,
therefore, that humans become more “rational” with age in a linear fashion.
Hence, although it is clearly appropriate to apply cognitive development and decisionmaking
models to the understanding of adolescent drinking, these models should be informed by the
emerging picture of adolescent development. For example, it might be best to broaden our
conceptualization of adolescent thinking and not assume that adolescent thinking is deficient in
some sense relative to adult decisionmaking, only to arrive at “full” levels of cognition with
adulthood. Instead, adolescent thinking and decisionmaking may be better understood as fully
developed for the purpose for which they evolved; that is, to deal with the tremendous transitions
that humans face at this stage of life. How to integrate this emerging understanding of
adolescence with the need to reduce adverse outcomes from drinking is a critical question.
References
Aas, H., and Klepp, K.I. Adolescents’ alcohol use related to perceived norms. Scandinavian
Journal of Psychology 33:315–325, 1992. PMID: 1287824
Agnoli, F. Development of judgmental heuristics and logical reasoning: Training counteracts the
representativeness heuristic. Cognitive Development 6:195–217, 1991.
Barrouillet, P.; Markovits, H.; and Quinn, S. Developmental and content effects in reasoning with
causal conditionals. Journal of Experimental Child Psychology 81:235–248, 2002. PMID: 11884089
Beck, K.H., and Treiman, K.A. The relationship of social context of drinking, perceived social
norms, and parental influence to various drinking patterns of adolescents. Addictive Behaviors
21:633–644, 1996. PMID: 8876762
Davidson, D. The representativeness heuristic and conjunction fallacy effect in children’s
decision-making. Merrill-Palmer Quarterly 41:328–346, 1995.
DeJong, W. The role of mass media campaigns in reducing high-risk drinking among college
students. Journal of Studies on Alcohol (Suppl. 14):182–192, 2002. PMID: 12022724
Elkind, D. Egocentrism in adolescence. Child Development 38:1025–1034, 1967. PMID: 5583052
Elkind, D. Understanding the young adolescent. Adolescence 13:127–134, 1978.
Gardner, M., and Steinberg, L. Peer influence on risk taking, risk preference, and risky decision
making in adolescence and adulthood: An experimental study. Developmental Psychology
41:625–635, 2005. PMID: 16060809
Halpern-Felsher, B.L., and Biehl, M. Developmental and environmental influences on underage
drinking: A general overview. In: National Research Council and Institute of Medicine. Reducing
Underage Drinking: A Collective Responsibility. Bonnie, R.J., and O’Connell, M.E., eds.
Washington, DC: National Academies Press, 2004. pp. 402–416. Available online at:
http://www.nap.edu/books/0309089352/html.
Jacobs, J.E. Perceptions of risk and social judgments: Biases and motivational factors. In:
National Research Council and Institute of Medicine. Reducing Underage Drinking: A Collective
Responsibility. Bonnie, R.J., and O’Connell, M.E., eds. Washington, DC: National Academies
Press, 2004. pp. 417–436. Available online at: http://www.nap.edu/books/0309089352/html.
Jacobs, J.E., and Potenza, M.T. The use of judgment heuristics to make social and object
decisions: A developmental perspective. Child Development 62:166–178, 1991.
Luna, B., and Sweeney, J.A. The emergence of collaborative brain function: fMRI studies of the
development of response inhibition. Annals of the New York Academy of Sciences 1021:269–
309, 2004. PMID: 15251900
Steinberg, L. Risk taking in adolescence: What changes, and why? Annals of the New York
Academy of Sciences 1021:51–58, 2004. PMID: 15251873
END OF SIDEBAR
Stability of Adolescent Personality
Because adolescence is a period of dramatic physical, social, and interpersonal change, it is
reasonable to believe that the structure and stability of adolescent personality differs in important
ways from the structure and stability of adult personality. Much of the current research on
adolescent personality focuses on the rank order stability of various personality traits from
adolescence through adulthood. Surprisingly, amidst a preponderance of significant life changes,
the rank order stability of adolescent personality remains remarkably high. Specifically,
correlations across time among Big Five personality traits range from .47 to .51 throughout
adolescence (Roberts and DelVecchio 2000; Shiner 2005). Importantly, however, these relatively
high correlations are far from unity. Moreover, personality stability appears to increase throughout
adulthood (with peak correlations after age 50), suggesting that personality during adolescence is
relatively kinetic and unsettled. Other studies of adolescent personality focus on differing levels of
various traits in adult and adolescent populations (Caspi et al. 2005). These studies typically find
that traits related to agreeableness, conscientiousness, dominance, and openness to experience
increase from adolescence to middle adulthood, whereas traits related to neuroticism and
sociability decrease during the same period (Caspi et al. 2005).
It also should be noted that the structure and correlates of alcohol disorders tend to change
across the life span. For example, a growing body of research suggests that different AUD
symptoms have different meanings at different developmental levels (Chung et al. 2005; O’Neil
and Sher 2000). Moreover, there are significant age-related changes in the prevalence and
course of AUDs (Grant et al. 1994; Hasin and Grant 2004). It will be important for future research
to examine adolescent alcohol and other drug use from a developmental perspective with a focus
on how changes in the structures of both personality and AUDs interact across the life span.
The relationship between personality and adolescent alcohol use is complex. As is true for adults,
studies involving adolescents have repeatedly failed to find specific constellations of personality
traits that uniquely predict alcohol use (e.g., an “alcoholic personality”). In addition, a dearth of
research has examined the stability and structure of adolescent personality traits. At the same
time, however, certain personality traits have been consistently associated with adolescent
drinking patterns.
Disinhibition. Traits related to disinhibition or poor self-regulation have been shown to predict
both heavy alcohol use and alcohol use disorders in adolescent samples. For example, Soloff
and colleagues (2000) found higher levels of impulsiveness and aggression among a sample of
young adults with AUDs than among age-matched control subjects. Similarly, Gabel and
colleagues (1999) found that novelty-seeking predicted alcohol and other drug dependence
symptoms both in a sample of treatment-referred male adolescents and in age-matched control
subjects. Other studies have found relationships between alcohol problems and behavioral
undercontrol (King and Chassin 2004), rebelliousness (Brook et al. 1995), low constraint (Chassin
et al. 2004), low harm avoidance (Jones and Heaven 1998), and a host of other disinhibited traits
(Colder and O’Connor 2002; Moss and Kirisci 1995; Colder and Chassin 1997). Moreover,
impulse control disorders such as conduct disorder, oppositional defiant disorder, and borderline
personality disorder are highly comorbid with alcohol and other drug pathology in adolescents,
suggesting the possibility of shared etiological pathways (Clark et al. 1997; Gabel et al. 1999;
Serman et al. 2002; Chassin et al. 2002). Indeed, research by Slutske and colleagues (2002)
indicates that much of the high genetic correlation between conduct disorder and adult alcohol
use disorders is associated with personality traits related to behavioral disinhibition.
Additionally, adolescents at high risk for the development of alcohol use disorders because of a
family history of alcoholism have been shown to be characterized by high levels of disinhibition.
Specifically, several researchers have found high levels of impulsive and externalizing behaviors
among adolescent children of alcoholics (COAs). For example, Clark and colleagues (1999)
found elevated rates of antisocial disorders among early adolescent COAs compared with their
non-COA peers. Similarly, Sher and colleagues (1991) found high levels of behavioral
undercontrol among late adolescent college students with family histories of alcoholism. It is
important to note, however, that a number of studies have failed to find associations between
COA status and externalizing behavior (Alterman et al. 1986; Pihl et al. 1990). Moreover, COA–
disinhibition relationships tend to be small and may be the result of shared third variables such as
parental antisociality or chaotic family environments (Sher 1997). Despite these methodological
concerns, however, the majority of high-risk studies support COA/non-COA behavioral
differences across a variety of methodologies and samples (Pihl et al. 1990).
Perhaps the most informative data on disinhibition and adolescent alcohol use come from
longitudinal studies. These studies often find that externalizing behaviors assessed in
childhood/early adolescence predict AUDs in early adulthood. For example, Cloninger and
colleagues (1988) used teacher ratings of 431 schoolchildren assessed at age 11 to predict
alcohol abuse at age 27. Results showed that high novelty-seeking and low harm avoidance
measured during childhood predicted alcohol abuse during adulthood. Similarly, Caspi and
colleagues (1997) found that aggression, alienation, low harm avoidance, low control, and low
social closeness assessed at age 18 predicted alcohol dependence at age 21. Using a somewhat
different methodology, Iacono and colleagues (2002) found that 17-year-olds with attenuated P3
event-related potential amplitudes (often considered a marker of externalizing disorders) were at
risk for alcohol and other drug use disorders at age 20. Moreover, studies using growth mixture
models suggest that disinhibited traits measured during adolescence are associated with
problematic alcohol and other drug use trajectories (Chassin et al. 2002; Chassin et al. 2004).
Neuroticism/Negative Affectivity. Negative affectivity also has been shown to predict alcohol
problems in adolescent samples. For example, Colder and Chassin (1993) found that negative
affect was associated with both heavy drinking and frequency of alcohol use in a sample of 452
early adolescents. In a later assessment of the same sample, Colder and Chassin (1997) found
that negative affect (1) predicted alcohol use and (2) interacted with impulsivity to predict both
alcohol use and alcohol-related impairment. Other cross-sectional studies have yielded similar
findings (Labouvie et al. 1990; Loukas et al. 2000; Krueger 1999).
High-risk and prospective studies also suggest a relationship between negative affectivity and
AUDs. For example, Elkins and colleagues (2004) found high rates of negative emotionality
among nonalcoholic adolescents with a parental history of alcoholism. Similarly, Zimmerman and
colleagues (2003) found that baseline anxiety disorders predicted the subsequent onset and
course of AUDs in an adolescent community sample. It should be noted, however, that several
researchers have found nonsignificant relationships between negative affectivity and alcohol use
problems (Brook et al. 1986; White et al. 1986). In addition, some research using adult samples
indicates that negative emotionality is a consequence, rather than a cause, of alcohol pathology
(Sutherland 1997). Interestingly, other studies suggest that negative emotionality is only
predictive of alcohol problems among adolescents who use drinking as a coping strategy (Cooper
1994; Newcomb et al. 1988). More research is needed to clarify the mediational role of drinking
motives in the negative affectivity/alcohol problem relationship.
A Snapshot of Research Findings on Adolescent Alcohol Use Disorders and Personality Traits
Findings
Study
Disinhibition/Poor Self-Regulation
Higher rates of impulsiveness and aggression were found
in young adults with alcohol and other drug use disorders
than among an age-matched control group.
Soloff et al. 2000
Higher rates of novelty-seeking predicted substance
dependence symptoms in both a sample of treatmentreferred male adolescents and age-matched control
subjects.
Gabel et al. 1999
Alcohol problems found associated with:





Behavioral undercontrol
Rebelliousness
Low constraint
Low harm avoidance
Other disinhibited traits
Impulse control disorders such as conduct disorder,
oppositional defiant disorder, and borderline personality
disorder are highly comorbid with substance use
disorders in adolescents.





King and Chassin 2004
Brook et al. 1995
Chassin et al. 2004
Jones and Heaven 1998
Colder and O’Connor 2002;
Moss and Kirisci 1995;
Colder and Chassin 1997
Clark et al. 1997; Gabel et al. 1999;
Serman et al. 2003; Chassin et al.
2002
Adolescents at high risk for development of alcohol use
disorders because of family history have been found to
have high rates of disinhibition:


Early adolescent children of adolescents had
higher rates of antisocial disorders than non-COA
peers.
• Clark et al. 1999
College students showed higher levels of
behavioral undercontrol.
• Sher et al. 1991

Some studies have failed to find associations
between COA status and externalizing behavior.
• Alterman et al. 1986;
Pihl et al. 1990

Relationships between COA status and
disinhibition are small and may be caused by
third variables such as parental antisociality or
chaotic home environments.
BUT:
High novelty-seeking and low harm avoidance among 11-
• Sher 1997
Cloninger et al. 1988
year-olds predicted alcohol abuse during adulthood.
Aggression, alienation, low harm avoidance, low control,
and low social closeness at age 18 predicted alcohol
dependence at age 21.
Caspi et al. 1997
Disinhibited traits measured during adolescence are
associated with problematic alcohol and drug use
trajectories.
Chassin et al. 2002, 2004
Negative Affectivity/Neuroticism




Negative affect was associated with both heavy
drinking and frequency of alcohol use in a sample
of early adolescents.

Colder and Chassin 1992
A later assessment of the same sample found
that negative affect predicted alcohol use and
interacted with impulsivity to predict both alcohol
use and alcohol-related impairment.

Colder and Chassin 1997
High rates of negative emotionality were found
among nonalcoholic adolescents with a parental
history of alcoholism.

Elkins et al. 2004
Baseline anxiety disorders predicted the
subsequent onset and course of AUDs in an
adolescent sample.

Zimmerman et al. 2003

Brook et al. 1986; White et
al. 1986

Sutherland 1997

Cooper 1994; Newcomb et
al. 1988
BUT:

Some researchers have found that relationships
between negative affectivity and alcohol use
problems were not significant.

Some research with adults indicates that negative
emotionality is a result rather than a cause of
alcohol pathology.

Recent studies suggest that negative emotionality
is only predictive of alcohol problems among
adolescents who use drinking as a coping
strategy.
SOURCE: www.MonitoringtheFuture.org
Functional Relations Between Personality and Drinking
Within the adult literature, there has clearly been a move away from simply demonstrating
correlations between specific personality traits and alcohol involvement and toward specifying the
ways that personality could affect alcohol involvement through plausible mediating mechanisms.
To date, several mediating models have been proposed, including those which suggest that
certain personality traits are related to specific drinking motivations (e.g., anticipated social
facilitation or self-medicating motives), deviant socialization into heavy-drinking peer groups, and
pharmacological vulnerability to reinforcement from alcohol (Sher et al. 1999). In turn, these
mediators are believed to account, in part, for the association between personality and alcohol
involvement. Available data suggest that these same general mechanisms are applicable to
adolescent drinking, although there is probably some developmental specificity, with deviant
socialization being a more important mechanism during adolescence.
ALCOHOL EXPECTANCIES AND RELATED CONCEPTS
Although the expectancy concept1 has been used across a wide variety of domains within
behavioral science, it has received particular attention within the alcohol field (see Goldman et al.
1987, 1999). (1 Expectancies are stored information [memories] that anticipate future events.)
And within the alcohol field, one point of special focus has been expectancy and the development
of drinking patterns from childhood through adolescence and into young adulthood (Christiansen
et al. 1989; Dunn and Goldman 1996, 2000; Gaines et al. 1988; Lang and Stritzke 1993; Miller et
al. 1990; Smith et al. 1995; Zucker et al. 1995). The original application of the term “expectancy”
within the alcohol field was to experimental conditions in balanced-placebo studies of the
psychopharmacological effects of alcohol. In these conditions, the participants were led to believe
that they were drinking alcohol but actually may have received either alcohol or a placebo
beverage, or were led to believe that they were drinking a nonalcoholic beverage but actually
received a beverage which may have contained alcohol (see Goldman et al. 1987). In general,
according to these studies, the behavior displayed after alcohol consumption often was as much
a function of the expectation (instructional set) that alcohol had been administered as it was
related to what actually was administered (up to particular dosage levels).
In the early 1980s, reports appeared in the literature describing studies in which participants
responded to questionnaires that inquired directly about their expectancies—that is, the effects
they anticipated if they were to consume alcohol (e.g., alcohol makes it easier to talk to people, to
pick a fight, to be sexually responsive; see review by Goldman et al. 1999). Since that time,
hundreds of studies of this type have been completed, with the consistent finding that particular
response patterns on these questionnaires correlate substantially with self-reported alcohol use,
and that these same response patterns can be used to predict later drinking over a time-lagged
(longitudinal) period. Among those expectancies these studies most often identified as being
related to higher levels of drinking are those for enhanced social/sexual functioning and positive
emotional outcomes. Summed across studies, the data suggest that participants who hold more
expectancies for positive/arousing outcomes from drinking, or more strongly endorse such
expectancies on a Likert scale (with which respondents rate the extent to which they agree or
disagree with a given statement), tend to drink more.
Of special relevance to the present review is that these expectancies are measurable in children
before they ever begin to drink (Christiansen et al. 1989; Dunn and Goldman 1996, 1998; Gaines
et al. 1988; Lang and Stritzke 1993; Miller et al. 1990; Noll et al. 1990; Smith et al. 1995; Stacy et
al. 1991; Zucker et al. 1995). And expectancies, even at this early point in development, are
related to how early children will begin to drink and to how much they will drink when they begin
drinking. It is important to note that some assessment devices for obtaining expectancies from
children have been accommodated to their developmental level (in terms of reading level or mode
of presentation; see Dunn and Goldman 1996, 1998; Miller et al. 1990). It is also important to
note that the rudimentary development of expectancies has been established even before the
start of elementary school (Noll et al. 1990). Perhaps most interesting is the finding that children
in general shift from a primary emphasis on the negative or adverse effects of drinking alcohol
before about age 9 to a primary emphasis on the positive and arousing effects of alcohol by about
age 13 (Dunn and Goldman 1996, 1998). Those at highest risk for excessive drinking show the
largest emphasis on positive/arousing effects. Although speculation as to the processes that
might cause this developmental shift has been offered, the actual causes remain to be
determined.
It is, of course, quite possible to simply regard alcohol expectancies as a list or inventory of
expected effects of alcohol. The history of the use of the expectancy concept in several different
venues in behavioral science suggests, however, that expectancies can be an active process
variable, with causal or mediational influence over behavioral output. For example, expectancy
explanations have been applied to a wide variety of clinical phenomena including pain reduction,
placebo effects, psychotherapy, and hypnosis (see Kirsch 1999), and to explanations of other
psychological phenomena including comparative judgment (Ritov 2000), music appreciation
(Krumhansl and Toivaine 2000), and even operant (Dragoi and Staddon 1999) and classical
conditioning (Rescorla and Wagner 1972).
Research also has linked underlying neural phenomena with expectancy. For example, neuronal
signaling involving the neurotransmitter dopamine in the nucleus accumbens (part of the brain’s
reward/reinforcing circuitry) has been noted to encode expectations about external rewards
(Kupfermann et al. 2000). Emotional responses, centering on the operation of the amygdala
(another component of the brain’s reward circuitry), also can be linked to expectancy
(Kupfermann et al. 2000). Within the alcohol and substance abuse fields, expectancy has been
understood to reflect differential dopamine activity in genetically selected animal lines (Katner et
al. 1996) and the manner in which well-established individual differences in the metabolism of
alcohol influence alcohol consumption (McCarthy et al. 2000).
Viewed in this way, alcohol expectancies can have significant implications for how people make
choices to use alcohol and about how much to use. Six increasingly stringent levels of evidence
support a causal role (see Goldman 2002): (1) expectancies correlate with reports of alcohol use,
accounting for up to 50 percent of the variance in drinking outcomes (Earlywine 1994; Leigh and
Stacy 1993); (2) expectancies are found in children before drinking begins and predict drinking
prospectively into adolescence and young adulthood (Dunn and Goldman 1996, 1998; Zucker et
al. 1995); (3) expectancies increase with drinking experience (Smith et al. 1995); (4) at the point
in life at which drinking decreases in many people, expectancies typically decrease (Sher et al.
1996); (5) when tested with statistical methods for demonstrating mediation, expectancies can be
shown to mediate the influence of other known antecedents of drinking risk (Finn et al. 2000); and
(6) expectancies can be manipulated in true experiments, with consequent changes in drinking
levels (Roehrich and Goldman 1995).
Despite the extensive body of research that has related the expectancy concept to alcohol (and
other drug) use and abuse, precise processes have only recently begun to emerge. One
approach has been to treat expectancies as the primary content of memory and then to use
memory models and methods as a basis for examining expectancy operation. This effort has
made use of empirical models of memory networks and associated mathematical techniques
(e.g., multidimensional scaling and clustering) to depict these networks (Rather et al. 1992).
Based on these models, experiments have been performed using well-established cognitive
paradigms (e.g., implicit and explicit stimulus priming, false memory techniques, Stroop task, free
association), resulting in findings consistent with the empirically derived memory models (e.g.,
Kramer and Goldman 2003; Stein et al. 2000). Particularly noteworthy were studies showing that
cognitive priming influences actual alcohol consumption (Roehrich and Goldman 1995; Stein et
al. 2000). Such approaches are only just beginning to be applied to the development of
behavioral approaches to reduce the risk for excessive alcohol use and abuse.
INFLUENTIAL THEORIES OF THE DEVELOPMENT OF ADOLESCENT PROBLEMS WITH
ALCOHOL AND OTHER SUBSTANCES
The theories outlined below are among the historically most influential in research on the origins
and progression of problems in adolescents with alcohol and other drugs. These theories have
tended to be directed toward antisocial and deviant involvement with alcohol and other drugs;
they fail to address the underage drinking behavior of youth thought to be successful and
mainstream. It is the goal of NIAAA’s underage drinking initiative to stimulate the synthesis and
testing of new and comprehensive models that reflect the complex multicausality of all underage
drinking behavior within a developmental framework.
The “Gateway,” or Stage Theory
This theory comes from epidemiological research that has examined patterns of alcohol and other
drug use progression among adolescents. The original findings suggested that adolescents
initially experiment either with alcohol and/or cigarettes (as legal and culturally accepted drugs)
and then progress to marijuana. Once experience with marijuana as an illicit drug is acquired,
adolescents may then try other illicit drugs such as heroin and cocaine. The experimentation with
alcohol and tobacco, as legal drugs, is viewed as a necessary intermediate or “gateway” to illicit
drug use (Kandel and Faust 1975).
Opponents of this theory suggest that there may be a common risk factor (or factors) for illicit
drug use that could account for the relationship between marijuana and other drug use
independent of initial exposures to alcohol and tobacco. Examples of a theorized “third factor”
include a genetic predisposition to problematic involvement with alcohol and other drugs, a
predisposition toward adolescent high-risk behavior in general, or shared opportunities to obtain
both marijuana and other drugs (Morral et al. 2002).
A less controversial offshoot of this theory deals with the age of first experimentation with a broad
class of abused drugs (whether it includes alcohol, tobacco, marijuana, or hard drugs), and the
timing of stages of regular use and problematic involvement. The literature converges around the
association of early alcohol and other drug use, including underage drinking, and subsequent
problematic involvement (Choi et al. 2001; Choi et al. 1997; Kandel and Logan 1984; Schuckit
and Russell 1983; Yamaguchi and Kandel 1984; Hawkins et al. 1997; Grant and Dawson 1998;
Warner and White 2003). For this reason, substantial attention has been focused on prevention
interventions that delay the initiation of alcohol and other drug use.
Problem Behavior Theory
Problem behavior theory is an influential conceptual framework for understanding not only
problematic alcohol and other drug use but also a wide variety of high-risk adolescent behaviors
(Jessor and Jessor 1977). The theory proposes a syndrome of comorbid adolescent problem
behaviors that may manifest themselves within the same person (Jessor 1991). For example,
adolescents with alcohol problems may engage in a spectrum of problem behaviors, such as illicit
drug use, delinquent behaviors (e.g., truancy, petty theft, vandalism, lying, running away), risky
and precocious sexual activity, and other high-risk behaviors (e.g., drag racing, drunk driving).
A single, possibly genetic, factor is hypothesized to underlie a general syndrome of deviance that
may predate adolescence and persist into adult life. Developmental support for this
conceptualization comes from the findings of the Dunedin Multidisciplinary Health and
Development Study. In one group of adolescents in this study, significant conduct problems were
observed in preadolescence, adolescence, and later adulthood (life-course-persistent antisocial
behavior). Another adolescent group was characterized as having behavioral deviancy that began
and ended during adolescence (adolescence-limited antisocial behavior). Adolescents in this
group ultimately had a positive adult outcome (Moffit 1993).
Comorbidity Theory
Epidemiological research has demonstrated significantly elevated rates of alcohol and other drug
use problems among adolescents with defined psychiatric disorders. Most, but not all, clinical and
community studies suggest that psychiatric disorders precede the development of adolescent
alcohol and other drug use problems in these people (e.g., Ellickson and Hays 1991; Boyle et al.
1992; Van Kammen and Loeber 1994; Kellam and Anthony 1998). Some studies have found that
psychiatric symptoms emerge during or after problematic involvement with alcohol and other
drugs (e.g., Brook et al. 1998; Fergusson and Horwood 1996). Developmental research has
suggested that the initial subsyndromal symptoms of most psychiatric disorders (except
depression) precede the onset of adolescent alcohol and other drug use in people with both. Over
time, these people receive full psychiatric diagnoses and subsequently progress to substance use
and a substance use disorder diagnosis (Costello et al. 1999). The childhood psychiatric
disorders known as the disruptive behavior disorders (i.e., attention deficit hyperactivity disorder,
oppositional defiant disorder, and conduct disorder) have the strongest associations with
problematic involvement with alcohol, tobacco, and other drugs during adolescence. It is
noteworthy that among these, adolescent conduct disorder increases the risk for alcohol abuse
and dependence (Deykin et al. 1987; Disney et al. 1999; Lewinsohn et al. 1993; Moss and Lynch
2001).
Depression also is associated with problematic involvement with a wide variety of alcohol and
other drugs during adolescence (Kandel et al. 1997). Some anxiety disorders, such as separation
anxiety, may be protective against alcohol and other drug use behavior during adolescence,
whereas others, such as generalized anxiety disorder, may enhance alcohol drinking and
augment risk (Kaplow et al. 2001). Adolescents with comorbid psychiatric disorders present a
significant challenge for both prevention and treatment of adolescent alcohol problems.
Maladaptive Coping Theory
High-risk behaviors also may be adaptive to the extent that they serve a social or maturational
goal such as separating from parents, achieving adult social status, or gaining peer acceptance
(Spear 2000). Engagement in high-risk behaviors may help an adolescent cope with failure,
boredom, stress, social anxiety or isolation, unhappiness, rejection, and low self-esteem. One
example of maladaptive coping is an adolescent’s reported use of alcohol and other drugs as a
means of gaining social status and acceptance from peers and, at the same time, enhancing
mood and assuaging feelings of low self-worth (DuRant 1995; DuRant et al. 1995). Thus,
problematic involvement with alcohol and other drugs for some adolescents may be a
maladaptive means of coping with the stresses and social pressures that are characteristic of the
adolescent stage of development, particularly in the absence of adult support, guidance, and
monitoring.
Patterson’s Developmental Theory
This theory was originally proposed to explain the development of juvenile delinquency; however,
consistent with the observation that problem behaviors frequently co-occur in adolescents, it also
has been used to understand and address problematic involvement with alcohol and other drugs
of abuse. Patterson and colleagues (Dishion et al. 1991; Patterson et al. 1989) are proponents of
a developmental theory of conduct problems which assumes that adolescent problem behavior is
a consequence of poor parental family management practices interacting with the child’s own
aggressive and oppositional temperament. Here, temperament refers to the early and genetically
determined behavioral characteristics that, over time and life experiences, evolve into personality.
Deficits in parenting skill, such as harsh and inconsistent punishment, increased parent-child
conflict, low parental involvement, and poor parental monitoring, result in school behavior and
performance problems. The poorly performing and poorly behaving child may be socially rejected
by average children; however, he or she forms close friendships with other problematic children.
This process of forming close peer relationships is augmented by the negative interactions with
caregivers in the home. As the child affiliates with more deviant children, he or she adopts deviant
behavior as a norm and becomes less involved in home life. Other deviant children become
powerful social role models; the child learns from them further deviant and socially unacceptable
behavior, including experimentation with alcohol and other drugs. Early experimentation
consistently has been found to be a risk factor for later problematic involvement with a wide
variety of drugs.
These children, therefore, may be viewed as being on a developmental pathway of deviancy and
alcohol and other drug abuse that begins in infancy and is compounded by unskilled parenting
and the formation of social relationships with other problem children (Vuchinich et al. 1992).
Prevention interventions that are based on this theoretical approach offer parenting skills training
to teach parents more effective ways to discipline and monitor their children and to reduce the
negative environment of the home. Tutoring and other forms of educational support may be
provided to reduce academic failure. Social skills training also may be offered to the child to help
him or her cope with rejection by normal peers and to provide a mechanism for graceful
resistance to peer pressure to use alcohol and illicit drugs.
REFERENCES
Alterman, A.I.; Bridges, K.R.; and Tarter, R.E. Drinking behavior of high risk college men:
Contradictory preliminary findings. Alcoholism: Clinical and Experimental Research 10:305–310,
1986. PMID: 3526955
Boyle, M.H.; Offord, D.R.; Racine, Y.A.; et al. Predicting substance use in late adolescence:
Results from the Ontario Child Health Study follow-up. American Journal of Psychiatry 149:761–
767, 1992. PMID: 1590492
Brook, J.S.; Whiteman, M.; Gordon, A.S.; and Cohen, P. Dynamics of childhood and adolescent
personality traits and adolescent drug use. Developmental Psychology 22:403–414, 1986.
Brook, J.S.; Whiteman, M.; Finch, S.; and Cohen, P. Aggression, intrapsychic distress, and drug
use: Antecedent and intervening processes. Journal of the American Academy of Child &
Adolescent Psychiatry 34:1076–1084, 1995. PMID: 7665446
Brook, J.S.; Cohen, P.; and Brook, D.W. Longitudinal study of co-occurring psychiatric disorders
and substance use. Journal of the American Academy of Child & Adolescent Psychiatry 37:322–
330, 1998. PMID: 9519638
Caspi, A.; Begg, D.; Dickson, N.; et al. Personality differences predict health-risk behaviors in
young adulthood: Evidence from a longitudinal study. Journal of Personality and Social
Psychology 73:1052–1063, 1997. PMID: 9364760
Caspi, A.; Roberts, B.W.; and Shiner, R.L. Personality development: Stability and change. Annual
Review of Psychology 56:453–484, 2005. PMID: 15709943
Chassin, L.; Pitts, S.C.; and Prost, J. Binge drinking trajectories from adolescence to emerging
adulthood in a high-risk sample: Predictors and substance abuse outcomes. Journal of
Consulting & Clinical Psychology 70:67–78, 2002. PMID: 11860058
Chassin, L.; Flora, D.B.; and King, K.M. Trajectories of alcohol and drug use and dependence
from adolescence to adulthood: The effects of familial alcoholism and personality. Journal of
Abnormal Psychology 113:483–498, 2004. PMID: 15535782
Choi, W.S.; Pierce, J.P.; Gilpin, E.A.; et al. Which adolescent experimenters progress to
established smoking in the United States. American Journal of Preventive Medicine 13:385–391,
1997. PMID: 9315272
Choi, W.S.; Gilpin, E.A.; Farkas, A.J.; and Pierce, J.P. Determining the probability of future
smoking among adolescents. Addiction 96:313–323, 2001. PMID: 11182877
Christiansen, B.A.; Smith, G.T.; Roehling, P.V.; and Goldman, M.S. Using alcohol expectancies
to predict adolescent drinking behavior at one year. Journal of Consulting and Clinical Psychology
57: 93–99, 1989. PMID: 2925979
Chung, T.; Martin, C.S.; and Winters, K. C. Diagnosis, course, and assessment of alcohol abuse
and dependence in adolescents. In: Galanter, M., ed. Recent Developments in Alcoholism, Vol.
17: Alcohol Problems in Adolescents and Young Adults: Epidemiology, Neurobiology, Prevention,
Treatment. New York: Springer, 2005. pp. 5–27. PMID: 15789857
Clark, D.B.; Pollock, N.; Bukstein, O.G.; et al. Gender and comorbid psychopathology in
adolescents with alcohol dependence. Journal of the American Academy of Child & Adolescent
Psychiatry 36:1195–1203, 1997. PMID: 9291720
Clark, D.B.; Parker, A.M.; and Lynch, K.G. Psychopathology and substance-related problems
during early adolescence: A survival analysis. Journal of Clinical Child Psychology 28:333–341,
1999.PMID: 10446682
Cloninger, C.R.; Sigvardsson, S.; and Bohman, M. Childhood personality predicts alcohol abuse
in young adults. Alcoholism: Clinical and Experimental Research 12:494–505, 1988. PMID:
3056070
Colder, C.R., and Chassin, L. The stress and negative affect model of adolescent alcohol use and
the moderating effects of behavioral undercontrol. Journal of Studies on Alcohol 54:326–333,
1993. PMID: 8487542
Colder, C.R., and Chassin, L. Affectivity and impulsivity: Temperament risk for adolescent alcohol
involvement. Psychology of Addictive Behaviors 11:83–97, 1997.
Colder, C.R., and O’Connor, R. Attention bias and disinhibited behavior as predictors of alcohol
use and enhancement reasons for drinking. Psychology of Addictive Behaviors 16:325–332,
2002. PMID: 12503905
Cooper, M.L. Motivations for alcohol use among adolescents: Development and validation of a
four-factor model. Psychological Assessment 6:117–128, 1994.
Costa, P.T., Jr., and McCrae, R.R. Revised NEO Personality Inventory (NEO-PI-R) Professional
Manual. Odessa, FL: Psychological Assessment Resources, 1992.
Costello, E.J.; Erkanli, A.; Federman, E.; and Angold, A. Development of psychiatric comorbidity
with substance abuse in adolescents: Effects of timing and sex. Journal of Clinical Child
Psychology 28:298–311, 1999. PMID: 10446679
Deykin, E.Y.; Levy, J.C.; and Wells, V. Adolescent depression, alcohol and drug abuse. American
Journal of Public Health 77:178–182, 1987. PMID: 3492151
Digman, J.M. Five robust trait dimensions: Development, stability, and utility. Journal of
Personality 57:195–214, 1989.
Digman, J.M. Personality structure: Emergence of the five-factor model. Annual Review of
Psychology 41:417–440, 1990.
Dishion, T.J.; Patterson, G.R.; Stoolmiller, M.; and Skinner, M.L. Family, school and behavioral
antecedents to early adolescent involvement with antisocial peers. Developmental Psychology
27:172–180, 1991.
Disney, E.R.; Elkins, I.J.; McGue, M.; and Iacono, W.G. Effects of ADHD, conduct disorder, and
gender on substance use and abuse in adolescence. American Journal of Psychiatry 156:1515–
1521, 1999. PMID: 10518160
Dragoi, V., and Staddon, J.E.R. The dynamics of operant conditioning. Psychological Review
106:20–61, 1999. PMID: 10197362
Dunn, M.E., and Goldman, M.S. Empirical modeling of an alcohol expectancy memory network in
elementary school children as a function of grade. Experimental and Clinical
Psychopharmacology 4:209–217, 1996.
Dunn, M.E., and Goldman, M.S. Age and drinking-related differences in the memory organization
of alcohol expectancies in 3rd, 6th, 9th, and 12th grade children. Journal of Consulting & Clinical
Psychology 66:579–585, 1998. PMID: 9642899
Dunn, M.E., and Goldman, M.S. Validation of multidimensional scaling-based modeling of alcohol
expectancies in memory: Age and drinking-related differences in expectancies of children
assessed as first associates. Alcoholism: Clinical and Experimental Research 24:1639–1646,
2000. PMID: 11104111
DuRant, R.H. Adolescent health research as we proceed into the twenty-first century. Journal of
Adolescent Health 17:199–203, 1995. PMID: 8519790
DuRant, R.H.; Getts, A.; Cadenhead, C.; et al. Exposure to violence and victimization and
depression, hopelessness, and purpose in life among adolescents living in and around public
housing. Journal of Developmental and Behavioral Pediatrics 16:233–237, 1995. PMID: 7593657
Earlywine, M. Anticipated biphasic effects of alcohol vary with risk for alcoholism: A preliminary
report. Alcoholism: Clinical and Experimental Research 18:711–714, 1994. PMID: 7943680
Elkins, I.J.; McGue, M.; Malone, S.; and Iacono, W.G. The effect of parental alcohol and drug
disorders on adolescent personality. American Journal of Psychiatry 161:670–676, 2004. PMID:
15056513
Ellickson, P.L., and Hays, R.D. Antecedents of drinking among young adolescents with different
alcohol use histories. Journal of Studies on Alcohol 52:398–408, 1991. PMID: 1943094
Eysenck, H.J. Biological dimensions of personality. In: Pervin, L.A., ed. Handbook of Personality
Theory and Research. New York: Guilford, 1990. pp. 244–276.
Fergusson, D.M., and Horwood, L.J. The role of adolescent peer affiliations in the continuity
between childhood behavioral adjustment and juvenile offending. Journal of Abnormal Child
Psychology 24:205–221, 1996. PMID: 8743245
Finn, P.R.; Sharkansky, E.J.; Brandt, K.M.; and Turcotte, N. The effects of familial risk,
personality, and expectancies on alcohol use and abuse. Journal of Abnormal Psychology
109:122–133, 2000. PMID: 10740943
Gabel, S.; Stallings, M.C.; Schmitz, S.; et al. Personality dimensions and substance misuse:
Relationships in adolescents, mothers and fathers. American Journal on Addictions 8:101–113,
1999. PMID: 10365190
Gaines, L.S.; Brooks, P.H.; Maisto, S.; et al. The development of children’s knowledge of alcohol
and the role of drinking. Journal of Applied Developmental Psychology 9:441–457, 1988.
Goldberg, L.R. An alternative description of personality: The Big Five factor structure. Journal of
Personality and Social Psychology 59:1216–1229, 1990.
Goldberg, L.R. The development of markers for the Big-Five factor structure. Psychological
Assessment 4:26–42, 1992.
Goldman, M.S. Expectancy and risk for alcoholism: The unfortunate exploitation of a fundamental
characteristic of neurobehavioral adaptation. Alcoholism: Clinical and Experimental Research
26:737–746, 2002. PMID: 12045484
Goldman, M.S.; Brown, S.A.; and Christiansen, B.A. Expectancy theory: Thinking about drinking.
In: Blane, H.T., and Leonard, K.E., eds. Psychological Theories of Drinking and Alcoholism. New
York: Guilford, 1987. pp. 181–226.
Goldman, M.S.; Del Boca, F.K.; and Darkes, J. Alcohol expectancy theory: The application of
cognitive neuroscience. In: Leonard, K.E., and Blane, H.T., eds. Psychological Theories of
Drinking and Alcoholism, Second Edition. New York: Guilford, 1999. pp. 203–246.
Grant, B.F., and Dawson, D.A. Age of onset of drug use and its association with DSM–IV drug
abuse and dependence: Results from the National Longitudinal Alcohol Epidemiologic Survey.
Journal of Substance Abuse 10:163–173, 1998. PMID: 9854701
Grant, B.F.; Harford, T.C.; Dawson, D.A.; et al. Prevalence of DSM–IV alcohol abuse and
dependence: United States, 1992. Alcohol Health & Research World 18(4):243–248, 1994.
Halpern-Felsher, B.L., and Biehl, M. Developmental and environmental influences on underage
drinking: A general overview. In: National Research Council and Institute of Medicine. Bonnie,
R.J., and O’Connell, M.E., eds. Reducing Underage Drinking: A Collective Responsibility.
Washington, DC: National Academies Press, 2004. pp. 402–416. Available online at:
http://www.nap.edu/books/0309089352/html.
Hasin, D.S., and Grant, B.F. The co-occurrence of DSM–IV alcohol abuse in DSM–IV alcohol
dependence: Results of the National Epidemiologic Survey on Alcohol and Related Conditions on
heterogeneity that differ by population subgroup. Archives of General Psychiatry 61:891–896,
2004. PMID: 15351767
Hawkins, J.D.; Graham, J.W.; Maguin, E.; et al. Exploring the effects of age of alcohol use
initiation and psychosocial risk factors on subsequent alcohol misuse. Journal of Studies on
Alcohol 58:280–290, 1997. PMID: 9130220
Iacono, W.G.; Carlson, S.R.; Malone, S.M.; and McGue, M. P3 event-related potential amplitude
and the risk for disinhibitory disorders in adolescent boys. Archives of General Psychiatry
59:750–757, 2002. PMID: 12150652
Jacobs, J.E. Perceptions of risk and social judgments: Biases and motivational factors. In:
National Research Council and Institute of Medicine. Bonnie, R.J., and O’Connell, M.E., eds.
Reducing Underage Drinking: A Collective Responsibility. Washington, DC: National Academies
Press, 2004. pp. 417– 436. Available online at: http://www.nap.edu/books/0309089352/html.
Jessor, R. Risk behavior in adolescence: A psychosocial framework for understanding and action.
Journal of Adolescent Health 12:597–605, 1991. PMID: 1799569
Jessor, R., and Jessor, S.L. Problem Behavior and Psychosocial Development: A Longitudinal
Study of Youth. New York: Academic Press, 1977.
Jones, S.P., and Heaven, P.C. Psychosocial correlates of adolescent drug-taking behaviour.
Journal of Adolescence 21:127–134, 1998. PMID: 9585491
Kandel, D., and Faust, R. Sequence and stages in patterns of adolescent drug use. Archives of
General Psychiatry 32:923–932, 1975. PMID: 1156108
Kandel, D.B., and Logan, J.A. Patterns of drug use from adolescence to young adulthood: I.
Periods of risk for initiation, continued use, and discontinuation. American Journal of Public
Health 74:660–666, 1984. PMID: 6611092
Kandel, D.B.; Johnson, J.G.; Bird, H.R.; et al. Psychiatric disorders associated with substance
use among children and adolescents: Findings from the Methods for the Epidemiology of Child
and Adolescent Mental Disorders (MECA) Study. Journal of Abnormal Child Psychology 25:121–
132, 1997. PMID: 9109029
Kaplow, J.B.; Curran, P.J.; Angold, A.; and Costello, E.J. The prospective relation between
dimensions of anxiety and the initiation of adolescent alcohol use. Journal of Clinical Child
Psychology 30:316–326, 2001. PMID: 11501249
Katner, S.N.; Kerr, T.M.; and Weiss, F. Ethanol anticipation enhances dopamine efflux in the
nucleus accumbens of alcohol-preferring (P) but not Wistar rats. Behavioral Pharmacology
7:669– 674, 1996. PMID: 11224464
Kellam, S.G., and Anthony, J.C. Targeting early antecedents to prevent tobacco smoking:
Findings from an epidemiologically based randomized field trial. American Journal of Public
Health 88:1490–1495, 1998. PMID: 9772850
King, K.M., and Chassin, L. Mediating and moderated effects of adolescent behavioral
undercontrol and parenting in the prediction of drug use disorders in emerging adulthood.
Psychology of Addictive Behaviors 18:239–249, 2004. PMID: 15482079
Kirsch, I., ed. How Expectancies Shape Experience. Washington, DC: American Psychological
Association, 1999.
Kramer, D.A., and Goldman, M.S. Using a modified Stroop task to implicitly discern the cognitive
organization of alcohol expectancies. Journal of Abnormal Psychology 112:171–175, 2003. PMID:
12653426
Krueger, R.F. Personality traits in late adolescence predict mental disorders in early adulthood: A
prospective-epidemiological study. Journal of Personality 67:39–65, 1999. PMID: 10030020
Krumhansl, C.L., and Toivaine, P. Melodic expectations: A link between perception and emotion.
Psychological Science Agenda 13:8, 2000.
Kupfermann, I.; Kandel, E.R.; and Iverson, S. Motivational and addictive states. In: Kandel, E.R.;
Schwartz, J.H.; and Jessell, T.M.; eds. Principles of Neural Science, Fourth Edition. New York:
McGraw- Hill, 2000. pp. 998–1018.
Labouvie, E.W.; Pandina, R.J.; White, H.R.; and Johnson, V. Risk factors of adolescent drug use:
An affect-based interpretation. Journal of Substance Abuse 2:265–285, 1990. PMID: 2136115
Lang, A.R., and Strizke, W.G.K. Children and Alcohol. In: Galanter, M., ed. Recent Developments
in Alcoholism, Vol. 11: Ten Years of Progress. New York: Plenum, 1993. pp. 73–85. PMID:
8234939
Leigh, B.C., and Stacy, A.W. Alcohol outcome expectancies: Scale construction and predictive
utility in higher order confirmatory models. Psychological Assessment 5:216–229, 1993.
Lewinsohn, P.M.; Hops, H.; Roberts, R.E.; et al. Adolescent psychopathology: I. Prevalence and
incidence of depression and other DSM–III–R disorders in high school students. Journal of
Abnormal Psychology 102:133–144, 1993. Erratum in: Journal of Abnormal Psychology 102:517,
1993. PMID: 8436689
Loukas, A.; Krull, J.L.; Chassin, L.; and Carle, A.C. The relation of personality to alcohol
abuse/dependence in a high-risk sample. Journal of Personality 68:1153–1175, 2000. PMID:
11130736
McCarthy, D.M.; Wall, T.L.; Brown, S.A.; and Carr, L.G. Integrating biological and behavioral
factors in alcohol use risk: The role of ALDH2 status and alcohol expectancies in a sample of
Asian Americans. Experimental and Clinical Psychopharmacology 8:168–175, 2000. PMID:
10843299
Miller, P.M.; Smith, G.T.; and Goldman, M.S. Emergence of alcohol expectancies in childhood: A
possible critical period. Journal of Studies on Alcohol 51:343–349, 1990. PMID: 2359308
Moffitt, T.E. Adolescence-limited and life-course-persistent antisocial behavior: A developmental
taxonomy. Psychological Review 100:674–701, 1993. PMID: 8255953
Morral, A.R.; McCaffrey, D.F.; and Paddock, S.M. Reassessing the marijuana gateway effect.
Addiction 97:1493–1504, 2002. PMID: 12472629
Moss, H.B., and Kirisci, L. Aggressivity in adolescent alcohol abusers: Relationship with conduct
disorder. Alcoholism: Clinical and Experimental Research 19:642–646, 1995. PMID: 7573787
Moss, H.B., and Lynch, K.G. Comorbid disruptive behavior disorder symptoms and their
relationship to adolescent alcohol use disorders. Drug and Alcohol Dependence 64:75–83, 2001.
PMID: 11470343
Newcomb, M.D.; Chou, C.P.; Bentler, P.M.; and Huba, G.J. Cognitive motivations for drug use
among adolescents: Longitudinal tests of gender differences and predictors of change in drug
use. Journal of Counseling Psychology 35:426–438, 1988.
Noll, R.B.; Zucker, R.A.; and Greenberg, G.S. Identification of alcohol by smell among
preschoolers: Evidence for early socialization about drugs occurring in the home. Child
Development 61:1520–1527, 1990. PMID: 2245743
O’Neill, S.E., and Sher, K.J. Physiological alcohol dependence symptoms in early adulthood: A
longitudinal perspective. Experimental and Clinical Psychopharmacology 8:493–508, 2000. PMID:
11127421
Patterson, G.R.; DeBaryshe, B.D.; and Ramsey, E. A developmental perspective on antisocial
behavior. American Psychologist 44:329–335, 1989. PMID: 2653143
Pihl, R.O.; Peterson, J.; and Finn, P. Inherited predisposition to alcoholism: Characteristics of
sons of male alcoholics. Journal of Abnormal Psychology 99:291–301, 1990. PMID: 2212280
Rather, B.C.; Goldman, M.S.; Roehrich, L.; and Brannick, M. Empirical modeling of an alcohol
expectancy memory network using multidimensional scaling. Journal of Abnormal Psychology
101:174–183, 1992. PMID: 1537963
Rescorla, R.A., and Wagner, A.R. A theory of Pavlovian conditioning: Variations in the
effectiveness of conditioned but not of unconditioned stimuli. Psychological Review 87:532–552,
1972.
Ritov, I. The role of expectations in comparisons. Psychological Review 107:345–357, 2000.
PMID: 10789199
Roberts, B.W., and DelVecchio, W.F. The rank-order consistency of personality traits from
childhood to old age: A quantitative review of longitudinal studies. Psychological Bulletin 126:3–
25, 2000. PMID: 10668348
Roehrich, L., and Goldman, M.S. Implicit priming of alcohol expectancy memory processes and
subsequent drinking behavior. Experimental and Clinical Psychopharmacology 3:402–410, 1995.
Schuckit, M.A., and Russell, J.W. Clinical importance of age at first drink in a group of young
men. American Journal of Psychiatry 140:1221–1223, 1983. PMID: 6614235
Serman, N.; Johnson, J.G.; Geller, P.A.; et al. Personality disorders associated with substance
use among American and Greek adolescents. Adolescence 37:841–854, 2002. PMID: 12564834
Sher, K.J. Psychological characteristics of children of alcoholics. Alcohol Health & Research
World 21(3):247–254, 1997. PMID: 15706777
Sher, K.J.; Walitzer, K.S.; Wood, P.K.; and Brent, E.E. Characteristics of children of alcoholics:
Putative risk factors, substance use and abuse, and psychopathology. Journal of Abnormal
Psychology 100:427–448, 1991. PMID: 1757657
Sher, K.J.; Wood, M.D.; Wood, P.K.; and Raskin, G. Alcohol outcome expectancies and alcohol
use: A latent variable cross-lagged panel study. Journal of Abnormal Psychology 105:561–574,
1996. PMID: 8952189
Sher, K.J.; Trull, T.J.; Bartholow, B.D.; and Vieth, A. Personality and alcoholism: Issues, methods,
and etiological processes. In Leonard, K.E., and Blane, H.T., eds. Psychological Theories of
Drinking and Alcoholism, 2 ed.: The Guilford Substance Abuse Series. New York: Guilford, 1999.
p. 54–105.
Shiner, R.L. A developmental perspective on personality disorders: Lessons from research on
normal personality development in childhood and adolescence. Journal of Personality Disorders
19:202–210, 2005. PMID: 15899716
Slutske, W.S.; Heath, A.C.; Madden, P.A.F.; et al. Personality and the genetic risk for alcohol
dependence. Journal of Abnormal Psychology 111:124–133, 2002. PMID 11871377
Smith, G.T.; Goldman, M.S.; Greenbaum, P.E.; and Christiansen, B.A. Expectancy for social
facilitation from drinking: The divergent paths of high-expectancy and low-expectancy
adolescents. Journal of Abnormal Psychology 104:32–40, 1995. PMID: 7897051
Soloff, P.H.; Lynch, K.G.; and Moss, H.B. Serotonin, impulsivity, and alcohol use disorders in the
older adolescent: A psychobiological study. Alcoholism: Clinical and Experimental Research
24:1609–1619, 2000. PMID: 11104107
Spear, L.P. The adolescent brain and age-related behavioral manifestations. Neuroscience and
Biobehavioral Reviews 24:417–463, 2000. PMID: 10817843
Stacy, A.W.; Newcomb, M.D.; and Bentler, P.M. Cognitive motivation and drug use: A 9-year
longitudinal study. Journal of Abnormal Psychology 100:502–515, 1991. PMID: 1757664
Stein, K.D.; Goldman, M.S.; and Del Boca, F.K. The influence of alcohol expectancy priming and
mood manipulation on subsequent alcohol consumption. Journal of Abnormal Psychology
109:106–115, 2000. PMID: 10740941
Sutherland, I. The development and application of a questionnaire to assess the changing
personalities of substance addicts during the first year of recovery. Journal of Clinical Psychology
53:253–262, 1997. PMID: 9075054
Tellegen, A. Multidimensional Personality Questionnaire. Minneapolis: University of Minnesota
Press, 1985.
Van Kammen, W., and Loeber, R. Delinquency, Drug Use and the Onset of Adolescent Drug
Dealing. Pittsburgh, PA: University of Pittsburgh, 1994.
Vuchinich, S.; Bank, L.; and Patterson, G.R. Parenting, peers, and the stability of antisocial
behavior in preadolescent boys. Developmental Psychology 28:510–521, 1992.
Warner, L.A., and White, H.R. Longitudinal effects of age at onset and first drinking situations on
problem drinking. Substance Use & Misuse 38:1983–2016, 2003. PMID: 14677779
White, H.R.; Johnson, V.; and Horwitz, A. An application of three deviance theories to adolescent
substance use. International Journal of the Addictions 21:347–366, 1986. PMID: 3721640
Yamaguchi, K., and Kandel, D.B. Patterns of drug use from adolescence to young adulthood: III.
Predictors of progression. American Journal of Public Health 74:673–681, 1984. PMID: 6742253
Zimmermann, P.; Wittchen, H.U.; Hofler, M.; et al. Primary anxiety disorders and the development
of subsequent alcohol use disorders: A 4-year community study of adolescents and young adults.
Psychological Medicine 33:1211–1222, 2003. PMID: 14580076
Zucker, R.A.; Kincaid, S.B.; Fitzgerald, H.E.; and Bingham, C.R. Alcohol schema acquisition in
preschoolers: Differences between children of alcoholics and children of nonalcoholics.
Alcoholism: Clinical and Experimental Research 19:1011–1017, 1995. PMID: 7485810
Environmental and Contextual Considerations
A number of environmental factors can influence an adolescent’s risk for drinking,
including parenting styles, an adolescent’s choice of peer groups, and even whether he or
she is active in after-school activities. Alcohol advertising, the price of alcohol, and the
degree to which underage drinking laws are enforced also play a role. It is difficult to
establish the degree to which alcohol use is influenced by environmental factors. This
article describes some of the environmental influences that may increase the risk for
underage drinking. Key words: adolescent; underage drinking; environmental factors; risk
factors; protective factors; drinking and driving; alcoholic beverage; AOD (alcohol and other drug)
product advertising; AOD price; sales and excise tax; minimum drinking age laws; zero tolerance
laws
OVERVIEW
The spectrum of environmental factors that can influence an adolescent’s drinking ranges from
parents and family to the community at large and includes the availability, price, and advertising
of alcohol. For a variety of reasons, measuring the impact of an environmental feature on drinking
in a young person can be a challenge. Research has found, for example, that adolescents with
supportive parents who monitor their children’s activities are less likely to be involved in risky
behaviors than adolescents with less attentive parents. At the same time, genetic influences on
personality can influence parenting styles as well as choice of peer groups and involvement in
activities. Innate traits may help prompt an adolescent to, for example, choose a peer group
inclined to risky behavior; however, that peer group is itself an environmental factor that
encourages risky activity. One goal of research is to be able to provide an understanding of the
interactions of genetics vs. environmental factors and their relative contributions to risky behavior.
On a larger scale, alcohol advertising is pervasive in this culture, and much of it is presented in
ways that appeal to youth. Some research suggests an association between adolescents’
reactions to alcohol advertising and their desire or intention to drink. Results have been mixed,
however, in studies aimed at establishing whether alcohol advertising actually causes youth to
drink.
In contrast, most studies looking at the impact of alcohol price or tax changes on youth have
found that young people’s alcohol consumption drops significantly in response to tax and price
increases. Other research has examined the effects of alcohol prices or taxes on the harmful
consequences of drinking; most studies looking at traffic fatalities have found that higher prices
and taxes are associated with reductions in traffic crash fatalities among younger drivers.
All States now have laws making it illegal to sell alcohol to people younger than age 21.
Numerous studies have established the effectiveness of underage drinking laws in reducing both
drinking and alcohol-related crashes among people under age 21. The National Highway Traffic
Safety Administration (NHTSA) estimates that a legal drinking age of 21 saves 700 to 1,000 lives
annually. All 50 States now also have zero-tolerance laws, which make it illegal for people
younger than age 21 to drive after any drinking. These laws also have contributed to declines in
alcohol-related traffic deaths among those younger than age 21. For a number of reasons, zerotolerance laws have not been vigorously enforced. This lack of vigorous enforcement occurs in
spite of evidence from studies done before universal adoption of zero-tolerance laws indicating
that States instituting these laws saw substantial declines in the proportion of people younger
than age 21 who drove after any drinking.
PARENTS, PEERS, AND COMMUNITY INFLUENCES
Parenting styles, choice of peer group, and the community context in which adolescents are
raised have all been heavily researched as possible risk-promoting or protective influences on
drinking-related outcomes (Halpern-Felsher and Biehl 2004). As might be anticipated, numerous
studies have found that children with loving, supportive, and involved parents had better
developmental outcomes and were less likely to use alcohol than children raised in less
supportive homes. Parental support encompassed monitoring their children’s activities while
supporting their independence and setting limits (Barnes et al. 2000; Bogenschneider et al. 1998;
Reifman et al. 1998; DiClemente et al. 2001; Davies et al. 2001; Steinberg et al. 1994).
However, although parents’ awareness of their children’s activities is certainly important, as is
controlling their whereabouts, the source of parents’ information about what their children are
doing also is critical. Research suggests that facilitating children’s willingness to share information
about their lives may be associated with better outcomes (Stattin and Kerr 2000).
Parents who drank more and who held favorable views about drinking had offspring who drank
more. Similarly, adolescents who spent more time with peers who consumed alcohol were more
likely to drink (Colder and Chassin 1999; Curran et al. 1997; Sieving et al. 2000; Stice et al.
1998).
Although it is tempting to conclude that the variables noted above truly have a causal influence on
drinking, the evidence at this point does not establish a causal or mediational influence. Because
we know that genetic risk for alcohol use patterns can manifest itself through personality
variables, and that these same personality variables can influence parenting styles, choice of
peer groups, and even engagement in after-school programs (and other environmental choices),
it is difficult to establish the degree to which alcohol use is influenced independently by parents,
peers, and environment. These questions must be pursued using genetically informed research
designs and by experiments in which these variables are manipulated independently of genetic
factors.
THE ROLE OF ADVERTISING
Youth are exposed to a significant amount of alcohol advertising. Alcohol ads appear in virtually
all types of media. Such ads are common on television and often are presented in ways that
appeal to youth and are shown at times when many youth are likely to see them. Half of televised
beer ads, for example, air during Saturday or Sunday afternoon sporting events—programs that
are popular among youth (Snyder et al. 2000). Beer is the beverage of choice for many youth,
and between 1998 and 2002, industry spending on televised beer ads increased 45 percent to
$972 million. Over the same period, spending on liquor advertising increased 530 percent to $18
million (Center for Science in the Public Interest [CSPI] 2003). Youth also routinely see ads for
alcoholic beverages in magazines, on billboards, and on the Internet. For example, the Center on
Alcohol Marketing and Youth (CAMY) found that youth saw 49 percent more beer ads and 20
percent more distilled spirits ads than did adults (CAMY 2004). CAMY researchers also reported
that 12- to 17-year-olds hear more alcohol ads on the radio than do adults (CAMY 2003). Radio
alcohol ads were frequently placed on stations with youth formats and were aired when youth
were most likely to be listening (CAMY 2003). A study of Internet use by youth found that alcoholrelated Web sites contained features appealing to youth, such as video games and cartoons, but
had few effective mechanisms to keep underage youth from accessing the Web sites (CAMY
2004).
Scientists are trying to determine how advertising affects youth generally and underage alcohol
consumption more specifically. A simple model of the effects of alcohol advertising would posit
that greater amounts of advertising lead to more exposure to advertising, which leads to more
drinking. Thus, much of the research in this area has been focused on explicating part or all of
this sequence by: quantifying the number of alcohol portrayals in various media (including
advertising); estimating exposure to advertising in various populations; studying whether exposed
populations recall and are aware of alcohol advertising; examining how awareness affects alcohol
expectancies and intention to drink; studying cross-sectionally the association between
advertising and alcohol outcomes; and studying prospectively the causal relationships among
advertising variables and drinking outcomes, such as initiation, escalation, and levels and
frequency of consumption. Among these, the longitudinal studies are of greatest interest because
they have the potential to address the fundamental questions of cause and effect.
Assessing the effect of advertisements on the drinking behavior of individuals or populations is a
complicated endeavor. It often is difficult to ascertain the specific effects of advertising because
they must be measured against a background dense in alcohol messages and images. In
addition, advertisements or alcohol-related messages will influence different individuals and
different populations differently at different developmental stages and times in their lives. And
furthermore, the mechanisms by which advertising may affect actual drinking behavior have not
been extensively studied and are not well understood.
One line of research in this area has directly studied young people’s reactions to alcohol
advertisements and the correlates of those reactions. A study of third, sixth, and ninth graders
showed that the third grade children who found alcohol ads desirable also were more likely to see
positive benefits from drinking and to desire products with alcohol logos. Older children in the
study who found the ads and logo products appealing were more likely to already be engaged in
drinking behaviors (Austin and Knaus 2000). A related survey of 9th and 12th grade students
examined the effect of media exposure on drinking behavior (Austin et al. 2000). Students
reported on their television viewing habits, viewing perceptions, desire for alcohol products, and
alcohol use. Findings supported a positive and indirect effect of media on adolescent drinking.
The media influence beliefs about the appeal and desirability of alcohol, and the beliefs in turn
influence drinking (Austin et al. 2000).
Another study examined brain response to viewing alcoholic beverage pictures and nonalcoholic
beverage pictures in 15- to 17-year-old heavy drinkers and nondrinkers using functional magnetic
resonance imaging. Heavy-drinking teens showed substantially greater brain activation while
viewing the alcohol ads relative to the nonalcohol ads, and this pattern differed significantly from
that of nondrinkers (Tapert et al. 2003). Brain regions showing differential brain response
suggested that heavy-drinking teens attended more closely, recalled pleasure and positive affect,
and generated increased appetitive response while viewing an assortment of alcohol
advertisements. On the other hand, Zogg and colleagues (2004), in an expectancy study of
perceived positive and negative outcomes of alcohol use, found no predictive effects of exposure
to televised alcohol advertisements, televised sports (which is dense in alcohol advertising), or
firsthand observation of others drinking.
SIDEBAR
Social Policy and Law
In a society in which alcohol is widely available and aggressively promoted and where alcohol
use remains normative behavior among youth, what social policies should be adopted toward
adolescent drinking? This question is not just about defining the legal drinking age. Social policy
and law are not the same thing. Law is one tool of social policy, with some advantages (e.g.,
deterrence) and some disadvantages (e.g., individual and social costs of enforcement).
Institutions of social control offer another means of strongly discouraging alcohol use by
youngsters under a certain age, regardless of what age the law defines as the minimum for legal
alcohol consumption. An important goal of research is to determine the ways in which the law can
most efficiently be deployed while encouraging nonlegal institutions to play a more substantial
role than they now do.
Age of Lawful Access
The law can use different ways of drawing the line between legal and illegal conduct. Right now,
the law, by and large, uses an approach to defining the legal age of access to alcohol that is both
binary (legal or not) and categorical (based on a simple age classification). An example of
another type of approach is graduated licensing of young drivers, in which conditions are placed
on driving during a transitional phase before they have unrestricted access to driving a car.
Research is needed to explore the role of alcohol use in the lengthening transition from
adolescence to adulthood, including what some investigators have called the periods of emerging
adulthood and young adulthood. This research should be linked to studies of other developmental
domains, including work and relationships with sexual partners and parents. This body of
research may prove to have important implications for all transitional legal arrangements.
Sanctions for Underage Drinkers
An important objective with regard to drinking laws and youth is identifying the appropriate
sanctions for violators. The policy challenge is to optimize the usefulness of laws against
underage possession and related offenses. This requires attention to the types of sanctions that
are needed as well as the enforcement strategies and judicial procedures that are used. In
general, the goal should be to increase the declarative and deterrent effects of the law without
harming the young person’s future life prospects. These judgments require research on a variety
of issues, including the attitudinal and behavioral effects of different types of sanctions, different
types of adjudicatory procedures, and different types and levels of enforcement. More generally,
a better understanding is needed of the attitudes of young people at different developmental
stages toward obedience to law, and of the ways in which decisions regarding use of alcohol (as
well as tobacco, marijuana, and other drugs) affect and are affected by attitudes toward the law.
These inquiries need to be tied to the developmental perspectives used to understand other
aspects of underage alcohol consumption.
Ways of Raising the “Price” of Underage Drinking
Threatening to punish young people for obtaining alcohol is one way of raising the price of alcohol
use. Another is to curtail the supply by deterring retailers and other adults from selling or giving
alcohol to underage drinkers. Curtailing the supply makes the young person spend more time
looking for alcohol, thereby increasing the “search costs.” Restricting outlets also can do this. A
final way to raise the price is by increasing excise taxes. One political concern raised by tax
increases and outlet restriction is that (unlike the other mechanisms) these tools also raise the
price for adult purchasers. All of these issues require systematic understanding of where and how
underage drinkers get their alcohol and, more generally, of the market for youthful drinking.
END OF SIDEBAR
Image advertising, which focuses on the lifestyle of the product user rather than the product itself,
is preferred by underage youth (seventh grade) and has been associated with intentions to drink
in the future (Kelly and Edwards 1998). A study involving male and female Anglo and Latino
adolescents found that, both for males and females, positive responses to beer advertisements
were associated with greater present and planned alcohol use. No differences were found related
to ethnicity (Slater et al. 1997). Another study conducted focus group discussions with students
ages 9 to 15 to learn what aspects of television alcohol advertisements made them attractive to
young people. The students responded positively to ads with humor, talking animals, and youthful
lifestyle appeal and negatively to the product focus of the ads (Waiters et al. 2001).
Although they are informative and interesting, these studies do not address the question of
causality: Do alcohol advertisements cause youth to drink, or do youth who already drink pay
more attention to alcohol advertising?
Two recent cross-sectional studies found positive associations between advertising and
consumption. Collins and colleagues (2003) measured advertisement awareness, drinking
beliefs, and drinking behavior among eighth grade students. These researchers found that boys
are more likely to be aware of and remember beer marketing and may be more likely to drink as a
result of this awareness.
Another study examined whether recall of and liking of alcohol advertisements leads to greater
intentions to drink in the future and higher consumption of alcohol (Chen and Grube 2001). This
study sampled students in grades 5 to 8 and grades 9 to 11 and measured their response to 16
alcohol ads and 4 soft drink ads. The study found that liking specific elements of alcohol ads
(characters, humor, story line) predicted liking the advertisements, and that liking the advertising
directly predicted current drinking levels and had significant indirect effects on drinking and future
intentions to drink. Results of earlier studies that examined the relationship between liking alcohol
advertising and current and future intentions to drink, however, were mixed (Kelly and Edwards
1998; Wylie et al. 1998).
A few prospective studies also have addressed this issue. A longitudinal study of New Zealand
youth found that liking alcohol advertising at age 18 was related to higher levels of beer
consumption at age 21 (Casswell and Zhang 1998). Two additional recent prospective studies
found a positive relationship between exposure to advertising and consumption. Ellickson and
colleagues (2003) found in a sample of seventh grade drinkers and nondrinkers from North
Dakota that several forms of advertising predicted future adolescent drinking for both groups. And
Stacy and colleagues (2004) found that exposure to advertising increased the risk of subsequent
beer consumption.
Another group of potentially informative investigations are econometric studies of the relationship
between alcohol advertising and consumption. Results of these studies also have been mixed. A
study by Saffer (2002) found that advertising increased consumption, whereas other studies
found that alcohol advertising affects brand choice but not overall consumption (Nelson and
Moran 1995; Gius 1996). Another study by Saffer and Dhaval (2003) suggests that a complete
ban on alcohol advertising might reduce the prevalence of monthly drinking by 12- to 18-year-olds
from about 25 percent to 21 percent and of binge drinking from 12 percent to 7 percent (Saffer
and Dhaval 2003). Despite their potential effectiveness for reducing underage drinking,
comprehensive advertising bans are not likely to receive public support, and partial bans are
likely to prompt the alcohol industry to increase their ads in other media (Saffer 2002).
In general, research on the impact of alcohol advertising on actual drinking behavior has been
mixed, and observed effects have been small. In addition, many of the cited studies are subject to
recall bias. Furthermore, many studies have been cross-sectional, making it difficult to draw
definitive conclusions about the relationship between advertising and alcohol consumption (Grube
2004).
TEXT BOX
By the Numbers: Alcohol Advertising, Price, and Legislation







Industry spending on TV beer ads, 2002: $972 million (up
45 percent from 1998) (CSPI 2003).
Industry spending on TV liquor ads, 2002: $18 million (up
530 percent from 1998) (CSPI 2003).
Young people see 49 percent more beer ads and 27
percent more ads for distilled spirits than adults see
(CAMY 2004).
Studies have found that young people’s alcohol
consumption drops significantly in response to price or tax
changes, in some cases exceeding the reductions
estimated for the general population (Grossman et al.
1987; Coate and Grossman 1988; Kenkel 1993; Sutton
and Godfrey 1995; Ruhm 1996; Grossman et al. 1998).
When States increased the legal drinking age to 21,
alcohol-related crashes among people younger than 21
decreased an average of 16 percent (Shults et al. 2001).
NHTSA estimates that the legal drinking age of 21 saves
700 to 1,000 American lives annually, and has prevented
more than 21,000 traffic deaths since 1976 (NHTSA 2003).
The first 30 States to adopt zero-tolerance laws had a 19percent decline in the proportion of people younger than 21
who drove after drinking, when compared with States
without these laws, and a 23-percent decline in the
proportion who drove after five or more drinks (Wagenaar
et al. 2001).
END OF TEXT BOX
THE EFFECT OF PRICE ON ADOLESCENT ALCOHOL CONSUMPTION
A substantial body of research has shown that higher prices or taxes on alcoholic beverages are
associated with lower levels of alcohol consumption and alcohol-related problems (Leung and
Phelps 1993; Kenkel and Manning 1996; Chaloupka et al. 1998; Cook and Moore 2002).
Estimates vary, however, in the extent to which consumption or problems change in response to
a given price or tax change. Some studies have examined these effects among young people
separately from the general population. Most such studies have found that young people’s
alcohol consumption drops significantly in response to price or tax changes, in some cases
exceeding the reductions estimated for the general population (Grossman et al. 1987; Coate and
Grossman 1988; Kenkel 1993; Sutton and Godfrey 1995; Ruhm 1996; Grossman et al. 1998). An
exception is the study by Dee (1999), which found only small and statistically insignificant effects
of beer taxes on teens’ drinking behavior. In addition, Chaloupka and Wechsler (1996) found that,
although higher beer prices tend to decrease drinking and binge drinking among U.S. college
students, price is a relatively weak tool for influencing these behaviors, especially among males.
In a study of the population age 17 and older, Manning and colleagues (1995) found that alcohol
consumption decreased in response to price increases for all but the top 5 percent of drinkers,
who exhibited no significant price response. Several studies have examined the effects of alcohol
prices or taxes on traffic crash fatalities and other alcohol-related problems. Most such studies
have reported that higher taxes or prices were associated with significant reductions in traffic
crash fatalities or drunk driving, particularly among younger drivers and during nighttime hours
(Saffer and Grossman 1987; Chaloupka et al. 1993; Kenkel 1993; Ruhm 1996). A few later
studies have questioned these findings. Dee (1999) found some evidence that beer taxes tend to
reduce teen traffic fatalities but concluded that those results were not robust and should be
viewed with skepticism. Young and Likens (2000) found no significant effects of beer taxes on
traffic crash fatality rates, either for young drivers or the general population. Mast and colleagues
(1999) found mixed results, with several analyses indicating significant but relatively small effects
of beer taxation on traffic fatalities. Other research has found associations between higher
alcoholic beverage taxes and lower rates of some types of violent crime (Cook and Moore
1993a), reduced incidence of physical child abuse committed by women (Markowitz and
Grossman 2000), and lower rates of sexually transmitted diseases (Chesson et al. 2000), as well
as with increases in college graduation rates (Cook and Moore 1993b).
Further research is needed to clarify the effects that alcoholic beverage prices or taxes have on
different drinking behaviors, health-related outcomes, and population subgroups, and to reconcile
conflicting findings that have appeared in the literature. To date, however, the weight of evidence
suggests that higher prices and taxes can help to reduce alcohol consumption and alcoholrelated problems.
THE EFFECT OF DRINKING LAWS ON ALCOHOL CONSUMPTION BY ADOLESCENTS
Legal Drinking Age of 21
In 1984, when 25 States had a legal drinking age of 21, the U.S. Congress passed legislation that
would withhold highway construction funds from States that did not make it illegal to sell alcohol
to people younger than age 21. By 1988, all States adopted such a law. A review of more than 49
studies of legal drinking age changes revealed that in the 1970s and 1980s, when many States
lowered the drinking age, alcohol-related traffic crashes increased 10 percent. In contrast, when
States increased the legal drinking age to 21, alcohol-related crashes among people younger
than age 21 decreased an average of 16 percent (Shults et al. 2001). Wagenaar and Toomey
(2002) reviewed more than 48 studies of the effects of drinking age changes on drinking and 57
studies of traffic crashes. They concluded that increases in the age of legal alcohol purchase and
consumption have been the most successful intervention to date in reducing drinking and alcoholrelated crashes among people under age 21. One national study of laws raising the drinking age
to 21 indicated that people who grew up in States with a drinking age of 21 relative to those with
lower legal drinking ages drank less not only when they were younger than age 21 but also when
they were ages 21 to 25 (O’Malley and Wagenaar 1991). NHTSA (2003) estimates that a legal
drinking age of 21 saves 700 to 1,000 lives annually and that more than 21,000 traffic deaths
have been prevented by such laws since 1976.
Zero-Tolerance Laws
All States now have zero-tolerance laws that make it illegal for people under age 21 to drive after
any drinking. These laws also have contributed to declines in alcohol-related traffic deaths among
people younger than age 21. A comparison of the first eight States to adopt zero-tolerance laws
with nearby States without such laws revealed a 21-percent greater decline in zero-tolerance law
States in the proportion of fatal crashes among drivers younger than age 21 that were of the type
most likely to involve alcohol (i.e., single-vehicle fatal crashes at night) (Hingson et al. 1994).
Wagenaar and colleagues (2001) found that in the first 30 States to adopt zero-tolerance laws,
relative to the rest of the nation, there was a 19-percent decline in the proportion of people
younger than age 21 who drove after any drinking and a 23-percent decline in the proportion who
drove after five or more drinks.
Unfortunately, despite their demonstrated benefits, legal drinking age and zero-tolerance laws
generally have not been vigorously enforced (Jones and Lacey 2001). Young drivers are
substantially underrepresented in the driving while intoxicated (DWI) arrest population relative to
their contributions to the alcohol-crash problem (Preusser et al. 1992; Voas and Williams 1986).
Younger drivers may be more likely to drink in locations where DWI enforcement resources are
less likely to be deployed. Young drivers with high blood alcohol concentrations also are more
likely to be missed by police at sobriety checkpoints (Wells et al. 1997).
Stepped-up enforcement of alcohol purchase laws aimed at sellers and buyers can be effective
(Preusser et al.1994; Wagenaar et al. 2000) if resources are made available for this purpose.
Enforcement of zero-tolerance laws is hindered in some States because their implied-consent
laws require either an arrest for DWI or probable cause for a DWI arrest before the evidentiary
test can be done to prove a zero-tolerance violation (Ferguson et al. 2000). Thus, in practice,
zero-tolerance laws often are not enforced independently of DWI. In States such as New Mexico,
where this situation exists, the majority of teenagers are unaware that there is a zero-tolerance
law (Ferguson and Williams 2002).
REFERENCES
Austin, E.W., and Knaus, C. Predicting the potential for risky behavior among those “too young”
to drink as the result of appealing advertising. Journal of Health Communications 5:13–27, 2000.
PMID: 10848029
Austin, E.W.; Pinkleton, B.E.; and Fujioka, Y. The role of interpretation processes and parental
discussion in the media’s effects on adolescents’ use of alcohol. Pediatrics 105:343–349, 2000.
PMID: 10654953
Barnes, G.M.; Reifman, A.S.; Farrell, M.P.; and Dintcheff, B.A. The effects of parenting on the
development of adolescent alcohol misuse: A six-wave latent growth model. Journal of Marriage
and Family 62:175–186, 2000.
Bogenschneider, K.; Wu, M.Y.; Raffaelli, M.; and Tsay, J.C. Parent influences on adolescent peer
orientation and substance use: The interface of parenting practices and values. Child
Development 69:1672–1688, 1998. PMID: 9914644
Casswell, S., and Zhang, J.F. Impact of liking for advertising and brand allegiance on drinking
and alcohol-related aggression: A longitudinal study. Addiction 93: 1209–1217, 1998. PMID:
9813902
Center for Science in the Public Interest (CSPI). Alcohol Advertising Expenditures, 1998–2002.
Alcohol Policies Project Fact Sheet. Washington, DC: CSPI, 2003. Available online at:
http://www.cspinet.org/booze/FactSheets/AlcAdExp.pdf.
Center on Alcohol Marketing and Youth (CAMY). Radio Daze: Alcohol Ads Tune in Underage
Youth. Washington, DC: Georgetown University, Center on Alcohol Marketing and Youth, 2003.
Available online at: http://camy.org/research/radio0303/.
Center on Alcohol Marketing and Youth (CAMY). Clicking With Kids: Alcohol Marketing and Youth
on the Internet. Washington, DC: Georgetown University, Center on Alcohol Marketing and
Youth, 2004. Available online at: http://camy.org/research/internet0304/report-high.pdf.
Chaloupka, F.J., and Wechsler, H. Binge drinking in college: The impact of price, availability, and
alcohol control policies. Contemporary Economic Policy 14:112–124, 1996.
Chaloupka, F.J.; Saffer, H.; and Grossman, M. Alcohol-control policies and motor-vehicle
fatalities. Journal of Legal Studies 22:161–186, 1993.
Chaloupka, F.J.; Grossman, M.; and Saffer, H. The effects of price on the consequences of
alcohol use and abuse. In: Galanter, M., ed. Recent Developments in Alcoholism, Vol. 14: The
Consequences of Alcoholism. New York: Plenum Press, 1998. pp. 331–346. PMID: 9751952
Chen, M.J., and Grube, J.W. “TV, Beer, and Soft Drink Advertising: What Young People Like and
What Effects?” Paper presented at the Annual Meeting of the Research Society on Alcoholism,
Montreal, Quebec, Canada, June 2001.
Chesson, H.; Harrison, P.; and Kassler, W.J. Sex under the influence: The effect of alcohol policy
on sexually transmitted disease rates in the United States. Journal of Law and Economics
43:215–238, 2000.
Coate, D., and Grossman, M. Effects of alcoholic beverage prices and legal drinking ages on
youth alcohol use. Journal of Law and Economics 31:145–171, 1988.
Colder, C.R., and Chassin, L. The psychosocial characteristics of alcohol users versus problem
users: Data from a study of adolescents at risk. Development and Psychopathology 11:321–348,
1999.
Collins, R.L.; Schell, T.; Ellickson, P.L.; and McCaffrey, D. Predictors of beer advertising
awareness among eighth graders. Addiction 98:1297–1306, 2003. PMID: 12930217
Cook, P.J., and Moore, M.J. Economic perspectives on reducing alcohol-related violence. In:
Martin, S.E., ed. Alcohol and Interpersonal Violence: Fostering Multidisciplinary Perspectives.
NIAAA Research Monograph No. 24. NIH Pub. No. 93–3496. Rockville, MD: National Institute on
Alcohol Abuse and Alcoholism, 1993a. pp. 193–212.
Cook, P.J., and Moore, M.J. Drinking and schooling. Journal of Health Economics 12:411–429,
1993b.
Cook, P.J., and Moore, M.J. The economics of alcohol abuse and alcohol-control policies. Health
Affairs 21:120–133, 2002. PMID: 11900152
Curran, P.J.; Stice, E.; and Chassin, L. The relation between adolescent alcohol use and peer
alcohol use: A longitudinal random coefficients model. Journal of Consulting and Clinical
Psychology 65:130–140, 1997. PMID: 9103742
Davies, P.T., and Windle, M. Interparental discord and adolescent adjustment trajectories: The
potentiating and protective role of intrapersonal attributes. Child Development 72:1163–1178,
2001. PMID: 11480940
Dee, T.S. State alcohol policies, teen drinking and traffic fatalities. Journal of Public Economics
72:289–315, 1999.
DiClemente, R.J.; Wingood, G.M.; Crosby, R.; et al. Parental monitoring: Association with
adolescents’ risk behaviors. Pediatrics 107:1363–1368, 2001. PMID: 11389258
Ellickson, P.L.; Tucker, J.S.; and Klein, D.J. Ten-year prospective study of public health problems
associated with early drinking. Pediatrics 111(5 Pt 1):949–955, 2003. PMID: 12728070
Ferguson, S.A., and Williams, A.F. Awareness of zero tolerance laws in three states. Journal of
Safety Research 33:293–299, 2002. PMID: 12404994
Ferguson, S.A.; Fields, M.; and Voas, R.B. “Enforcement of Zero Tolerance Laws in the United
States.” Paper presented at the 15th International Conference on Alcohol, Drugs and Traffic
Safety, Stockholm, Sweden, May 2000.
Gius, M.P. Using panel data to determine the effect of advertising on brand-level distilled spirits
sales. Journal of Studies on Alcohol 57:73–76, 1996. PMID: 8747504
Grossman, M.; Coate, D.; and Arluck, G.M. Price sensitivity of alcoholic beverages in the United
States: Youth alcohol consumption. In: Holder, H.D., ed. Control Issues in Alcohol Abuse
Prevention: Strategies for States and Communities. Greenwich, CT: JAI Press, 1987. pp. 169–
198.
Grossman, M.; Chaloupka, F.J.; and Sirtalan, I. An empirical analysis of alcohol addiction:
Results from the Monitoring the Future panels. Economic Inquiry 36:39–48, 1998.
Grube, J.W. Alcohol in the media: Drinking portrayals, alcohol advertising, and alcohol
consumption among youth. In: National Research Council and Institute of Medicine. Bonnie, R.J.,
and O’Connell, M.E., eds. Reducing Underage Drinking: A Collective Responsibility. Washington,
DC: National Academies Press, 2004. pp. 597–624. Available online at:
http://www.nap.edu/books/0309089352/html.
Halpern-Felsher, B.L., and Biehl, M. Developmental and environmental influences on underage
drinking: A general overview. In: National Research Council and Institute of Medicine. Bonnie,
R.J., and O’Connell, M.E., eds. Reducing Underage Drinking: A Collective Responsibility.
Washington, DC: National Academies Press, 2004. pp. 402–416. Available online at:
http://www.nap.edu/books/0309089352/html.
Hingson, R.; Heeren, T.; and Winter, M. Lower legal blood alcohol limits for young drivers. Public
Health Reports 109:738–744, 1994. PMID: 7800781
Jones, R.K., and Lacey, J.H. Alcohol and Highway Safety 2001: A Review of the State of
Knowledge. DOT Pub. No. HS–809–383. Washington, DC: National Highway Traffic Safety
Administration, 2001. Available online at:
http://www.nhtsa.dot.gov/people/injury/research/AlcoholHighway .
Kelly, K.J., and Edwards, R.W. Image advertisements for alcohol products: Is their appeal
associated with adolescents’ intention to consume alcohol? Adolescence 33:47–59, 1998. PMID:
9583659
Kenkel, D.S. Drinking, driving, and deterrence: The effectiveness and social costs of alternative
policies. Journal of Law and Economics 36:877–913, 1993.
Kenkel, D.S., and Manning, W.G. Perspectives on alcohol taxation. Alcohol Health & Research
World 20(4):230–238, 1996.
Leung, S.F., and Phelps, C.E. My kingdom for a drink. . . . ? A review of estimates of the price
sensitivity of demand for alcoholic beverages. In: Hilton, M.E., and Bloss, G., eds. Economics and
the Prevention of Alcohol-Related Problems. NIAAA Research Monograph No. 25. Rockville, MD:
National Institute on Alcohol Abuse and Alcoholism, 1993. pp. 1–31.
Manning, W.G.; Blumberg, L.; and Moulton, L.H. The demand for alcohol: The differential
response to price. Journal of Health Economics 14:123–148, 1995. PMID: 10154654
Markowitz, S., and Grossman, M. The effects of beer taxes on physical child abuse. Journal of
Health Economics 19:271–282, 2000. PMID: 10947580
Martin, S.E.; Snyder, L.B.; Hamilton, M.; et al. Alcohol advertising and youth. Alcoholism: Clinical
and Experimental Research 26:900–906, 2002. PMID: 12068260
Mast, B.D.; Benson, B.L.; and Rasmussen, D.W. Beer taxation and alcohol-related traffic
fatalities. Southern Economic Journal 66:214–249, 1999.
National Highway Traffic Safety Administration (NHTSA). Traffic Safety Facts 2002: Alcohol. DOT
Pub. No. HS–809–606. Washington, DC: NHTSA, 2003. Available online at: http://wwwnrd.nhtsa.dot.gov/pdf/nrd-30/NCSA/TSF2002/2002alcfacts.pdf.
Nelson, J.P., and Moran, J.R. Advertising and U.S. alcoholic beverage demand: System-wide
estimates. Applied Economics 27:1225–1236, 1995.
O’Malley, P.M., and Wagenaar, A.C. Effects of minimum drinking age laws on alcohol use,
related behaviors and traffic crash involvement among American youth: 1976–1987. Journal of
Studies on Alcohol 52:478–491, 1991. PMID: 1943105
Preusser, D.F.; Ulmer, R.G.; and Preusser, C.W. Obstacles to Enforcement of Youthful (Under
21) Impaired Driving. DOT Pub. No. HS–807–878. Washington, DC: National Highway Traffic
Safety Administration, 1992.
Preusser, D.F.; Williams, A.F.; and Weinstein, H.B. Policing underage alcohol sales. Journal of
Safety Research 25:127–133, 1994.
Reifman, A.; Barnes, G.M.; Dintcheff, B.A.; et al. Parental and peer influences on the onset of
heavier drinking among adolescents. Journal of Studies on Alcohol 59:311–317, 1998. PMID:
9598712
Ruhm, C.J. Alcohol policies and highway vehicle fatalities. Journal of Health Economics 15:435–
454, 1996. PMID: 10164038
Saffer, H. Alcohol advertising and youth. Journal of Studies on Alcohol (Suppl. 14):173–181,
2002. PMID: 12022723
Saffer, H., and Dhaval, D. Alcohol Advertising and Alcohol Consumption by Adolescents. NBER
Working Paper No. 9676. New York: National Bureau of Economic Research, 2003. Available
online at: http://www.nber.org/papers/w9676.
Saffer, H., and Grossman, M. Beer taxes, the legal drinking age, and youth motor vehicle
fatalities. Journal of Legal Studies 16:351–374, 1987.
Schults, R.A.; Elder, R.W.; Sleet, D.A.; et al. and the Task Force on Community Preventive
Services. Reviews of evidence regarding interventions to reduce alcohol-impaired driving.
American Journal of Preventive Medicine 21(Suppl.1):66–88. 2001. Erratum in: American Journal
of Preventive Medicine 23:72, 2002. PMID: 11691562
Sieving, R.E.; Perry, C.L.; and Williams, C.L. Do friendships change behaviors, or do behaviors
change friendships? Examining paths of influence in young adolescents’ alcohol use. Journal of
Adolescent Health 26:27–35, 2000. PMID: 10638715
Slater, M.D.; Rouner, D.; Domenech-Rodriquez, M.; et al. Adolescent responses to TV beer ads
and sports content/context: Gender and ethnic differences. Journalism and Mass
Communications Quarterly 74:108–122, 1997.
Snyder, L.B.; Milici, F.F.; Mitchell, E.W.; and Proctor, D.C. Media, product differences and
seasonality in alcohol advertising in 1997. Journal of Studies on Alcohol 61:896–906, 2000. PMID:
11188496
Stacy, A.; Zogg, J.; Unger, J; and Dent, C. Exposure to televised alcohol ads and subsequent
alcohol use. American Journal of Health Behavior 28: 498–509, 2004. PMID: 15569584
Stattin, H., and Kerr M. Parental monitoring: A reinterpretation. Child Development 71:1072–
1085, 2000. PMID: 11016567
Steinberg, L.; Fletcher, A.; and Darling, N. Parental monitoring and peer influences on adolescent
substance use. Pediatrics 93(6 Pt 2):1060–1064, 1994. PMID: 8197008
Stice, E.; Barrera, M.; and Chassin, L. Prospective differential prediction of adolescent alcohol
use and problem use: Examining the mechanisms of effect. Journal of Abnormal Psychology
107:616–628, 1998. PMID: 9830249
Sutton, M., and Godfrey, C. A grouped data regression approach to estimating economic and
social influences on individual drinking behaviour. Health Economics 4:237–247, 1995. PMID:
7550773
Tapert, S.F.; Cheung, E.H.; Brown, G.G.; et al. Neural response to alcohol stimuli in adolescents
with alcohol use disorder. Archives of General Psychiatry 60:727–735, 2003. PMID: 12860777
Voas, R.B., and Williams, A.F. Age differences of arrested and crash-involved drinking drivers.
Journal of Studies on Alcohol 47:244–248, 1986. PMID: 3724162
Wagenaar, A.C., and Toomey, T.L. Effects of minimum drinking age laws: Review and analyses
of the literature from 1960 to 2000. Journal of Studies on Alcohol (Suppl. 14):206–225, 2002.
PMID: 12022726
Wagenaar, A.C.; Murray, D.M.; Gehan, J.P.; et al. Communities Mobilizing for Change on
Alcohol: Outcomes from a randomized community trial. Journal of Studies on Alcohol 61:85–94,
2000. PMID: 10627101
Wagenaar, A.C.; O’Malley, P.M.; and LaFond, C. Lowered legal blood alcohol limits for young
drivers: Effects on drinking, driving and driving-after-drinking behaviors in 30 states. American
Journal of Public Health 91:801–804, 2001. PMID: 11344892
Waiters, E.D.; Treno, A.J.; and Grube, J.W. Alcohol advertising and youth: A focus group analysis
of what young people find appealing in alcohol advertising. Contemporary Drug Problems
28:695–718, 2001.
Wells, J.K.; Greene, M.A.; Foss, R.D.; et al. Drinking drivers missed at sobriety checkpoints.
Journal of Studies on Alcohol 58:513–517, 1997. PMID: 9273917
Wyllie, A.; Zhang, J.F.; and Casswell, S. Responses to televised alcohol advertisements
associated with drinking behaviour of 10-17-year-olds. Addiction 93:361–371, 1998. PMID:
10328044
Young, D.J., and Likens, T.W. Alcohol regulation and auto fatalities. International Review of Law
and Economics 20:107–126, 2000.
Zogg, J.; Ma, H.; Dent, C.; and Stacy, A. Self-generated alcohol outcomes in 8th and 10th
graders: Exposure to vicarious sources of alcohol information. Addictive Behavior 1:3–16, 2004.
PMID: 14667417
Interventions for Alcohol Use and Alcohol Use
Disorders in Youth
Designing effective interventions for adolescents with alcohol use disorders (AUDs)
presents several challenges, not the least of which is the accurate diagnosis of these
disorders. Diagnostic criteria for AUDs have been derived largely from clinical and
research experience with adults. When these criteria were tested among adolescents,
numerous developmental differences were found that may affect the applicability of AUD
criteria to this age group. Despite the absence of clear diagnostic criteria for use with
adolescents, research has identified interventions that show promise for use with youth.
This article examines both environmental- and individual-level approaches to underage
drinking prevention, including school- and family-based programs, and
macroenvironmental and multicomponent comprehensive interventions. Finally, it
describes brief and complex treatment interventions. Key words: adolescent; alcohol abuse;
alcohol dependence; AOD (alcohol and other drug) use pattern; diagnostic criteria; biological
development; psychological development; environmental-level prevention; individual-level
prevention; family intervention; school-based intervention; brief intervention; Project Northland
OVERVIEW
The ultimate goal of research on drinking by youth is to reduce the rates of drinking by
adolescents and successfully treat those who develop problems linked to alcohol use. Prevention
efforts may be aimed at keeping adolescents from starting to drink or at preventing the escalation
of drinking and negative consequences. Research can provide the science on which to base the
design of interventions and the means for determining which interventions are effective.
A valid diagnostic system is essential for assessing the nature and magnitude of adolescent
problem drinking. Existing diagnostic criteria are derived largely from experience with adults, but
developmental differences in alcohol use patterns suggest the need to adapt criteria to make
them relevant and informative for an adolescent’s stage of maturation.
Prevention efforts approach the issue of youth drinking in two ways: Environmental-level
interventions seek to reduce the availability of alcohol to youth and opportunities to drink,
increase penalties for violation of minimum legal drinking age laws, and reduce community
tolerance for alcohol use by youth. Individual-level interventions seek to change knowledge,
attitudes, and skills so that youth are better able to resist influences that support drinking.
In their efforts to reduce adolescent drinking, schools and families can act at both the
environmental and the individual level. School curricula operate at the individual level by trying to
provide students with the knowledge, skills, and motivation to resist pressures to drink. At the
environmental level, schools can make changes to discourage violation of alcohol rules and
engage students’ involvement in their schools, a factor that has been found to predict less alcohol
and other drug involvement.
The ability of parents to influence whether their children drink is well documented and is
consistent across racial/ethnic groups. Family interventions encourage parents to be aware of the
risks from underage drinking, communicate with children, clarify expectations, set rules and
consequences about alcohol use, and monitor children’s activities. In addition to changing the
knowledge and skills of young people, families can create an environment that reduces alcohol
availability and increases the costs associated with drinking.
Research is providing data on the effectiveness of school- and family-based intervention
programs and the elements that successful programs incorporate. One goal of continuing
research is to improve investigators’ ability to measure outcomes and to compare studies and the
methods they use as a means of changing adolescent behavior.
Community-level environmental interventions include strategies such as implementing
restaurant/bar server training, checking alcohol vendors for compliance with underage laws,
deterring adults from purchasing alcohol for minors, strengthening policies to detect and stop
underage drinking parties, and instituting publicity for policies aimed at enforcement of laws
against driving under the influence (DUI) and underage drinking. Community prevention trials
have demonstrated that such efforts can reduce alcohol-impaired driving and fatal crashes
among underage drivers and sales of alcohol to minors.
The most comprehensive interventions encompass coordinated school, family, and community
programs. One such universal prevention program, Project Northland, was tested in 22 school
districts in northern Minnesota in a randomized trial. The intervention included school curricula,
peer leadership, parental involvement programs, and communitywide efforts to address
community norms and alcohol availability. The intervention was delivered to a single cohort from
grades 6 through 12. Comparisons in such measures as “tendency to use alcohol” and drinking
five or more drinks in a row revealed differences between intervention and comparison
communities.
Although the Project Northland intervention was able to reduce rates of drinking among students
who were nondrinkers at the start of the project, the effort had no effect on those who already had
been drinking. These very early starters are likely to have particular risk factors that make them
more likely to drink and less likely to respond to more broadly targeted interventions; the
experience with Project Northland suggests that programs may be needed that are aimed
specifically at this group.
Underscoring the need for effective means of prevention are 2002 prevalence data indicating
that, among youth ages 12 to 17, 1.4 million met the criteria set forth in the Diagnostic and
Statistical Manual of Mental Disorders, Fourth Edition (DSM–IV) for alcohol abuse and
dependence (Substance Abuse and Mental Health Services Administration [SAMHSA] 2003).
The data, moreover, reveal a major unmet need for treatment for alcohol and related behavioral
problems. Only 227,000 of the youth meeting criteria for alcohol problems received any treatment
for these disorders in 2002. Data on alcohol problems among youth also may understate the
prevalence of these disorders; alcoholism treatment researchers believe that DSM–IV criteria
need to be developmentally specific to adequately identify youth with problems.
Adolescents in treatment for alcohol use disorders (AUDs) are likely to have more than one
substance use disorder and may have other psychiatric comorbidities; the success of treatment is
lower with those who have multiple problems than with other subgroups of youth. To date,
treatment for adolescent addiction has involved adapting adult treatments to youth. Ongoing
research is testing some innovative and developmentally tailored interventions aimed at
improving treatment outcomes.
Some of the most promising interventions for adolescents with AUDs have been complex,
multicomponent therapies. The current health care financing system stresses the need for
shorter, more cost-effective treatment, however. An alternative to complex treatments, brief
interventions can be directed at drinking or the consequences of drinking. An example of a brief
intervention is motivational enhancement, which encourages the person to take responsibility for
change and provides a menu of options for change. Early evidence suggests that brief
interventions can be helpful in reducing both drinking and its consequences in adolescents.
Overall, research points to the importance of applying a more nuanced and detailed
understanding of adolescent development to the design of treatments and outcome measures for
alcohol use problems in adolescents.
DIAGNOSIS OF ALCOHOL ABUSE AND DEPENDENCE IN ADOLESCENTS
A valid diagnostic system is essential to advancing treatment and research of adolescent AUDs.
Diagnoses should facilitate communication among clinicians and researchers, identify cases for
different levels of clinical intervention, provide phenotypes for genetics research, and convey
information about prognosis (Robins and Barrett 1989; McGue 1999). DSM–IV (American
Psychiatric Association [APA] 2000) includes two AUDs, alcohol abuse and alcohol dependence,
which are defined by nonoverlapping criterion sets. DSM–IV abuse focuses on negative
psychosocial consequences resulting from drinking, as well as hazardous use, and requires the
presence of at least one of four criteria. DSM–IV dependence is diagnosed when at least three of
seven criteria related to physical dependence, salience of alcohol use, and impaired control over
drinking behavior are met within the same 12-month period. Both DSM–IV AUDs require
evidence of clinically significant impairment or subjective distress resulting from alcohol use for
diagnosis.
Diagnostic criteria for AUDs were derived largely from clinical and research experience with
adults, and only recently has their validity been assessed among adolescents (Chung et al.
2005). Numerous developmental differences between adolescents and adults may affect the
applicability of AUD criteria to youth. For example, adolescents tend to drink less often than
adults but typically consume a greater quantity per occasion (Deas et al. 2000). Developmental
differences in alcohol use patterns indicate the need to adapt criteria to make them relevant to
and properly scaled for an adolescent’s stage of maturation (Brown 1999). Because a construct
may manifest itself differently in adolescents and adults (e.g., role impairment at school vs. work),
a perspective that takes developmental factors and contextual influences into account is essential
for valid assessment of AUD symptoms.
DSM–IV AUDs have shown some validity when used with adolescents in that teens classified as
having alcohol dependence, abuse, and no diagnosis differ on external measures of alcohol
involvement (e.g., Lewinsohn et al. 1996; Winters et al. 1999). Several important limitations have
been identified, however, both at the criterion level of how symptoms are defined and measured
and at the level of the diagnostic algorithms for alcohol abuse and dependence. At the criterion
level, certain symptoms (e.g., withdrawal, use despite medical problems) tend to occur only after
years of heavy drinking and have low prevalence and limited utility when applied to teens. Other
DSM–IV AUD symptoms appear to be more relevant to specific adolescent subgroups. For
example, hazardous use and legal problems have been associated with male gender, increased
age, ethnic background, and presence of conduct disorder symptoms in teens (Langenbucher
and Martin 1996; Wagner et al. 2002). Ethnicity and gender have been found to influence whether
and when certain DSM–IV AUD symptoms tend to occur in teen drinkers (Wagner et al. 2002).
Some symptoms, such as tolerance, appear to have a high prevalence among young drinkers in
part because they are poorly defined or scaled for the developmental period of adolescence
(Martin and Winters 1998). DSM–IV’s definition of tolerance as a “marked increase to obtain the
same effect” is only modestly associated with adolescent alcohol dependence. Many adolescent
drinkers report marked increases to produce the same effect (e.g., from one drink to three) but
are relatively light drinkers, often not having any other symptoms. Some level of tolerance may
occur as a normative developmental phenomenon in youth who drink. Other adolescents are
heavy drinkers who are not assigned the tolerance symptom; they report high quantities of
drinking during early drinking experiences (e.g., six or more drinks) without a subsequent marked
increase to produce the same effect (Chung et al. 2001). Better guidelines need to be developed
regarding the identification of clinically significant levels of tolerance in teens, or alternatives such
as a heavy drinking criterion must be considered (Chung et al. 2001).
Some AUD criteria may be interpreted differently or have different meanings when used with
adolescents compared with adults, such as “drinking more or longer than intended.” This
symptom often is assigned as a result of an adolescent’s poor judgment, inexperience with
alcohol’s effects, or social pressures to drink, rather than as a compulsive pattern of alcohol use
(Chung and Martin 2005). Research has examined the development of more specific interview
probes that query contextual factors, such as adolescents’ motivations for drinking and reasons
for limiting alcohol use, as a way to increase the validity of this symptom among youth.
Differences in how tolerance and drinking more or longer than intended are assessed affect
diagnostic validity and have a large effect on the estimated prevalence of AUDs in adolescent
community samples (Chung et al. 2002).
There are other limitations of the DSM–IV at the level of diagnostic algorithms, that is, abuse as
one out of four criteria and dependence as three out of seven criteria. Some adolescents who
engage in relatively low levels of alcohol use meet criteria for an abuse diagnosis only because of
arguments with their parents about alcohol use and may be considered to be “diagnostic
impostors” (Martin 1999). However, “diagnostic orphans,” who have one to two dependence
symptoms and no abuse symptoms, and thus no DSM–IV AUD, are similar to teens with DSM–IV
alcohol abuse on drinking levels and clinical outcomes (Pollock and Martin 1999). Diagnostic
impostors and orphans limit the ability of the DSM–IV diagnostic system to provide appropriate
categories for research studies and to guide the allocation of scarce health care resources.
The DSM–IV’s separate criterion sets for abuse and dependence are not well distinguished
conceptually or empirically. Data do not support a distinction between the two categories in
severity, age of symptom onset, age of onset of the two diagnoses, or symptom profiles identified
by latent class analysis and factor analysis (e.g., Martin et al. 1996; Wagner et al. 2002). Some
community surveys report higher prevalence of the more severe dependence diagnosis relative to
the milder abuse diagnosis (Chung et al. 2002), a situation that does not conform to most
disorders in psychiatry or medicine. In contrast to the DSM–IV dichotomy of abuse and
dependence, evidence suggests that the latent structure of adolescent alcohol problems
represents a continuum of severity distinguished more by the number than the type of symptoms
(Chung and Martin 2001).
Longitudinal studies indicate that alcohol problems which occur in adolescence and young
adulthood are only modestly associated (e.g., Baer et al. 1995; Rohde et al. 2001). The alcohol
abuse diagnosis appears to be particularly transient, with a high rate of transitions into and out of
this category (Nelson and Wittchen 1998). Many adolescents with AUDs mature out of problem
drinking (Labouvie 1996; Maisto et al. 2002), whereas others show a more chronic course
through adulthood (Abrantes et al. 2002). Multiple developmental trajectories of adolescent-onset
AUDs exist (e.g., Schulenberg et al. 2001) and have been characterized as developmentally
limited or persistent, with diagnoses that may be relatively continuous or intermittent (Zucker et al.
1995). Ongoing longitudinal research will help investigators understand more about the clinical
course and prognosis of adolescent-onset abuse and dependence and will help them test the
predictive validity of diagnostic criteria, course specifiers, and algorithms in the DSM–IV and
beyond.
TEXTBOX
DSM–IV Diagnostic Criteria for Alcohol Abuse and Dependence
Alcohol Abuse
(A) A maladaptive pattern of drinking, leading to clinically significant impairment or distress, as
manifested by at least one of the following occurring within a 12-month period:




Recurrent use of alcohol resulting in a failure to fulfill major role obligations at work,
school, or home (e.g., repeated absences or poor work performance related to alcohol
use; alcohol-related absences, suspensions, or expulsions from school; neglect of
children or household)
Recurrent alcohol use in situations in which it is physically hazardous (e.g., driving an
automobile or operating a machine when impaired by alcohol use)
Recurrent alcohol-related legal problems (e.g., arrests for alcohol- related disorderly
conduct)
Continued alcohol use despite having persistent or recurrent social or interpersonal
problems caused or exacerbated by the effects of alcohol (e.g., arguments with spouse
about consequences of intoxication).
(B) Never met criteria for alcohol dependence.
Alcohol Dependence
(A) A maladaptive pattern of drinking, leading to clinically significant impairment or distress, as
manifested by three or more of the following occurring at any time in the same 12-month period:






Need for markedly increased amounts of alcohol to achieve intoxication or desired effect;
or markedly diminished effect with continued use of the same amount of alcohol
The characteristic withdrawal syndrome for alcohol (or a closely related substance) or
drinking to relieve or avoid withdrawal symptoms
Persistent desire or one or more unsuccessful efforts to cut down or control drinking; or
drinking in larger amounts or over a longer period than intended
Important social, occupational, or recreational activities given up or reduced because of
drinking
A great deal of time spent in activities necessary to obtain, to use, or to recover from the
effects of drinking
Continued drinking despite knowledge of having a persistent or recurrent physical or
psychological problem that is likely to be caused or exacerbated by drinking.
(B) No duration criterion separately specified, but several dependence criteria must occur
repeatedly as specified by duration qualifiers associated with criteria (e.g., “persistent,”
“continued”).
SOURCE: American Psychiatric Association (APA). Diagnostic and Statistical Manual of Mental
Disorders, Fourth Edition. Washington, DC: APA, 1994.
END OF TEXTBOX
PREVENTION OF UNDERAGE DRINKING
Intervention Approaches
Environmental-level interventions seek to reduce opportunities (availability) for underage drinking,
increase penalties for violating minimum legal drinking age (MLDA) and other alcohol use laws,
and reduce community tolerance for alcohol use and misuse by youth. Individual-level
interventions seek to change knowledge, expectancies, attitudes, intentions, motivation, and skills
so that youth are better able to resist the pro-drinking influences and opportunities that surround
them. This section discusses four types of individual- and environmental-level programs: schoolbased programs, family-based programs, macroenvironmental programs, and multicomponent
programs.
School-Based Prevention Programs
School-based curricula to prevent use of alcohol and other drugs by youth have a long history.
However, the use of research-based findings to guide the content and evaluation of such
curricula is a fairly recent development (Bangert-Drowns 1988; Dielman 1995). The first schoolbased programs were primarily informational and often used scare tactics—it was assumed that if
youth understood the dangers inherent in alcohol misuse, they would choose to abstain. These
programs were ineffective. Better programs are now available, but researchers have found that
sometimes they are not used (Silvia and Thorne 1997) or implemented as designed (Dusenbury
et al. 2003).
Efforts to clarify theoretical and methodological issues relevant to improving school-based
prevention curricula have made steady progress. However, methodological issues remain a
critical barrier to interpreting the large number of published studies, as many were conducted with
less than optimal degrees of scientific rigor. Additionally, variations in design and methodology
make comparisons across studies difficult. For example, there is wide variability in alcohol use
outcome measures, and it is common for some measures within a single study to show significant
intervention effects whereas others do not (Foxcroft et al. 2003).
Researchers are increasingly interested in collecting information on alcohol-related problems and
high-risk drinking practices in addition to more straightforward measures of quantity and
frequency of drinking. Outcomes based solely on knowledge and attitudes are no longer
acceptable. Variation in measures makes comparisons across studies difficult. Also, the frequent
use of study-specific composite scales (based on combinations of individual measures) often
makes practical interpretations of findings difficult. This latter problem, coupled with the failure to
report effect sizes, makes it difficult to judge the likely benefit from implementing programs on a
large scale (Gorman 1995). Analysis based on intention-to-treat is the most relevant from a public
health standpoint, but application of this analytic standard often eliminates statistical significance
(Foxcroft et al. 2003). Differences in program intensity (number of sessions), followup periods,
age/grade of students, program goals, population characteristics, and attrition also impede metaanalysis and cross-study comparisons.
However, the following general statements are supported by the literature:


Programs that rely primarily on increasing knowledge about the consequences of drinking
are not effective.
Effective programs often:
– Are based on social influence models
– Include norm setting
– Address social pressures to drink and teach resistance skills
– Include developmentally appropriate information
– Include peer-led components
– Provide teacher training
– Are interactive.
Unfortunately, effect sizes generally are small. Even state-of-the-art programs are not sufficient to
prevent adolescent use and misuse of alcohol in the absence of social and environmental
change. Much of the literature suggests universal prevention curricula are less effective with
higher risk students—those who have initiated drinking prior to grades five or six; additional
research is needed in this area because of inconsistencies in the literature (Gottfredson and
Wilson 2003; Hansen 1992; Komro and Toomey 2002; Tobler 1986; Tobler and Stratton 1997;
National Research Council [NRC] and Institute of Medicine [IOM] 2004; Wagenaar and Perry
1994).
School curricula operate at the individual level by trying to provide students with the knowledge,
skills, and motivation needed to resist pressures to drink. However, schools also may be
considered from an environmental perspective. Policies and practices within the school, such as
consistent enforcement of sanctions for violating alcohol rules, are another arena for intervention.
Students’ bonding or attachment to their schools is found to predict less alcohol and other drug
involvement, so overall school climate and cohesiveness also seem to be important. However,
there are few studies linking specific school policies with alcohol use and even fewer studies of
policy changes (Flay 2000).
Family-Based Prevention Programs
The ability of parents to influence whether their children drink is well documented and is
consistent across racial/ethnic groups (e.g., Barnes et al. 2000; Steinberg et al. 1994). Setting
clear rules about children not drinking, consistently enforcing those rules, and monitoring child
behavior reduce the likelihood of underage drinking. Family conflict and lack of cohesion are
associated with increased risk (Bogenschneider et al. 1998). Family interventions encourage
parents to be aware of the risks from underage drinking, to communicate with children, to clarify
expectations regarding alcohol use, to set rules and consequences for violations, to monitor
children’s activities, and to reduce the availability of alcohol in the home. Additionally, content on
family management practices and communication skills often are included. Parent-directed
programs have been included with school-based interventions, some of which have evidence of
success; but these components have not been evaluated separately (Flay 2000). Stand-alone
family interventions have been successful in reducing alcohol use and other risk behaviors
(Komro and Toomey 2002).
The Iowa Strengthening Families Program (ISFP), delivered when students were in grade six,
has shown long-lasting preventive effects on alcohol use, even when evaluated on the basis of
intent-to-treat (Spoth et al. 2001, 2004). This finding is striking on two counts: First, it suggests
that the intervention succeeded in changing the normative environment of schools in which the
program was offered, because even students whose families did not participate benefited.
Second, the increase in effect size over time and the duration of effects into high school
compares favorably with school-based interventions. A recent Cochrane review identified the
ISFP as one of two potentially effective interventions for the primary prevention of alcohol misuse
by youth (Foxcroft et al. 2003).
Family interventions operate at both the individual and environmental level. Interventions seek to
change behavior of both parents and children by increasing knowledge and skills. However, by
changing parent practices, they affect a primary social environment for the child. This
microenvironment-level change effectively reduces availability and increases “costs” associated
with drinking, which probably accounts for the lasting intervention effects that have been
observed.
Families in distress or youth who are exhibiting behavior problems may need more intensive
interventions (selective and indicated prevention). Tiered or stepped-intervention strategies have
been described to restrict more costly services to the subset of families in most need (Dishion
and Kavanagh 2000; Sanders 2000).
Macroenvironmental Interventions
Environmental approaches may have both direct and indirect influences on drinking by youth.
Enforcement of MLDA laws directly reduces alcohol availability, a critical element in
comprehensive risk models (Wagenaar and Toomey 2002). Penalties for alcohol use and misuse
that apply directly to youth increase the social “cost” of drinking, which is expected to affect
decisions about drinking. Changes in monetary price have been associated with decreases in use
and related problems (Leung and Phelps 1993; Kenkel and Manning 1996; Chaloupka et al.
1998; and Cook and Moore 2002). Public awareness campaigns in support of environmental
change serve to change community norms regarding the acceptability of underage drinking,
which should further reduce opportunities to drink and increase social costs to young drinkers
(NRC and IOM 2004; Toomey and Wagenaar 2002; Wagenaar and Perry 1994).
Environmental interventions are among the recommendations included in the recent NRC and
IOM report, Reducing Underage Drinking: A Collective Responsibility (NRC and IOM 2004), and
by the Panel on Prevention and Treatment of the National Institute on Alcohol Abuse and
Alcoholism (NIAAA) Task Force of the National Advisory Council on Alcohol Abuse and
Alcoholism. Such programs seek to reduce commercial and social availability of alcohol and/or
reduce driving while intoxicated. They may use a variety of strategies, including implementing
server training, instituting compliance checks in outlets, deterring adults from purchasing for
minors (shoulder tap) or providing alcohol to minors (public education and policies), restricting
drinking in public places, enforcing penalties for use of false IDs, strengthening policies to detect
and terminate underage drinking parties, establishing penalties for providing alcohol to a minor,
enforcing DUI and zero-tolerance laws, and creating publicity regarding policies and sanctions.
Three community trials in the United States are noteworthy and are described below. Collectively,
they show the utility of community environmental strategies to reduce underage drinking and
related problems.
The Massachusetts Saving Lives Program. This 5-year comprehensive intervention
implemented in six communities was designed to reduce alcohol-impaired driving and related
traffic deaths. This program decreased fatal crashes, particularly alcohol-related fatal crashes
involving drivers ages 15–25, and reduced the proportion of 16- to 19-year-olds who reported
driving after drinking relative to the rest of Massachusetts. It also increased teen awareness of
penalties for drunk driving and for speeding. Other significant outcomes related to traffic safety
were not age-specific (Hingson et al. 1996; Hingson and Howland 2002).
The Community Prevention Trial Program. This program was implemented in three
intervention communities matched to three comparison sites. The formal goal of the project was
to assist each experimental community to make effective, long-term changes to reduce alcoholinvolved injuries and death but not necessarily to change individual drinking patterns. The
intervention strategies included efforts to reduce alcohol availability to minors. Sales to apparent
minors (people of legal drinking age who appear younger than age 21) were significantly reduced
in the intervention communities compared with the control sites (Grube 1997; Holder 2000).
Communities Mobilizing for Change on Alcohol. This program was a randomized 15community trial to reduce the accessibility of alcoholic beverages to youths under the legal
drinking age. It emphasized environmental factors that affect the supply of alcohol to youth, using
a community organizing approach to achieve policy change among local institutions. Among the
significant findings were that merchants in participating communities were less likely to sell
alcohol to minors and that 18- to 20-year-olds were less likely to try to purchase alcohol or
provide alcohol to younger teens. There also was a decline in DUI arrests among 18- to 20-yearolds. There were no program effects, however, on self-reported drinking by 12th graders, the
youngest age group surveyed. This may be a result of the short duration of the intervention—2.5
years—or it may be that younger adolescents obtain alcohol from adults and are not directly
affected by changes in commercial availability (Wagenaar et al. 2000a,b).
Community-level interventions clearly can reduce commercial sales of alcohol to minors, and this
can affect overall drinking by older adolescents. It remains to be seen whether sustained
interventions can reduce social availability of alcohol to younger adolescents. Additionally, the
fact that community interventions can simultaneously reduce alcohol-related problems among
adults (e.g., injury) and youth (e.g., availability) increases their cost-effectiveness and should
make them attractive to policymakers (Foxcroft et al. 2003).
Multicomponent Comprehensive Interventions
Comprehensive interventions provide coordinated programs at the school, family, and community
levels and target multiple pathways for risk. Ideally, they also should integrate universal,
selective, and indicated prevention programs and treatment for youth who are alcohol dependent.
To date, one such program, Project Northland, has been evaluated.
Project Northland is a comprehensive universal prevention program that was tested in 22 school
districts in northeastern Minnesota in a randomized trial. The intervention included (1) innovative
social behavioral school curricula, (2) peer leadership, (3) parental involvement programs, and (4)
communitywide task force activities to address larger community norms and alcohol availability.
The intervention was delivered to a single cohort in grades 6 through 12. Intervention intensity
and focus varied over the study period. The first phase (grades 6 through 8) had strong school
and family components. By the end of grade 8, fewer students had initiated alcohol use, and the
prevalence of alcohol use (past month and past week) was significantly lower in the intervention
communities compared with control communities (Perry et al. 1996). During the next phase of the
study, grades 9 and 10, there was minimal intervention. In grades 11 and 12, intervention
activities resumed, and the community component to reduce availability was featured more
prominently.
Significant differences were observed between intervention and comparison communities during
each project period for “tendency to use alcohol” (a composite measure that combined items
about intentions to use alcohol and actual use) and “five or more in a row.” The rates of increase
in underage drinking prevalence were lower in the intervention communities during phase 1;
higher during the interim period (suggesting a “catch-up” effect while intervention activities were
minimal); and again lower during phase 2 when intervention activities resumed (Perry et al.
2002).
Based on its success, Project Northland has been designated a model program by SAMHSA, and
its materials have been adapted for a general audience and marketed by Hazelden. It now is
being replicated in ethnically diverse urban neighborhoods.
Very Early Interventions
The Project Northland findings at the same time point to a dilemma that may be a significant
hurdle when working to prevent underage drinking in the highest risk groups. The program began
in sixth grade, when children were approximately 12 years of age, and although it was able to
reduce rates of drinking among those who were nondrinkers at the initiation of the project, the
intervention had no effect on those who had already begun drinking. The study was not able to
parse out the reasons for these differential effects on initial nonusers vs. users, but youth who are
already drinking at sixth grade are very much an early onset group, given that the median age of
onset of first use is age 14. Given also what is known about the impulsivity, heavier drinking by
parents, and conflicted family backgrounds of early onset users (Ellickson et al. 2003; Mayzer et
al. 2003), it is likely that the social micronetworks within which the early onset drinkers moved
would have insulated them to a greater degree from the program’s effects. For this subgroup,
earlier precursive risk intervention programs may be necessary (Nye et al. 1999; Spoth et al.
2001; Zucker and Noll 1987).
TREATMENT FOR ADOLESCENT ALCOHOL USE DISORDERS
Prevalence data on binge and heavy drinking, collected in the 2002 U.S. National Survey on Drug
Use and Health (NSDUH) (SAMHSA 2003), indicate a public health problem of considerable
dimensions in youth ages 12 to 17. Binge drinking is well established by midadolescence, as
reported by 12 percent of 15-year-olds, 18 percent of 16-year-olds, and 25 percent of 17-yearolds. Not only are these youth at high risk for serious accidents and adverse social, health, and
academic consequences related to their alcohol use, but some also may be at risk for developing
multiple behavioral disorders including alcohol abuse and alcoholism. At the same time, as
already discussed, alcoholism treatment researchers who specialize in youth diagnosis and
treatment believe that DSM–IV criteria are inadequate to identify youth who have AUDs. They
conclude that diagnosis of youth substance use disorders needs to be developmentally specific,
to meet fewer criteria than required by DSM–IV, and to add criteria salient to youth drinking
practices (Chung et al. 2003; Clark 2004).
An Unmet Need
Nonetheless, the NSDUH data indicate a major unmet need for effective health services to
prevent and treat alcohol and other associated behavioral problems. Among youth these ages,
1.4 million met DSM–IV criteria for alcohol abuse or dependence, but only 227,000 actually
received any treatment for alcohol use disorders in 2002 (SAMHSA 2003). Further, current
services are not optimally designed for youth access or engagement (Brown 2001). Youth prefer
easy access, low threshold approaches that accentuate strategies adolescents normally use to
stop drinking (Metrik et al. 2003), and treatments that do not remove them from their primary
home or academic settings (Brown 2001). Youth perceive traditional services (e.g., alcoholism
treatment programs, Alcoholics Anonymous) as less helpful than brief interventions tailored to
salient adolescent concerns (D’Amico et al. 2004). Consequently, alternative formats, attention to
developmental transitions, and social marketing are needed to more adequately address alcohol
problems emerging in adolescence (Brown 2001; Kypri et al. 2004; O’Leary et al. 2002).
Alcohol abuse and dependence: The unmet need for treatment in youth ages
12–17, in the past year. In 2002, only 16 percent of the 1.4 million youth
ages 12 to 17 estimated to have alcohol use disorders (AUDs) reported
receiving any type of service for these problems.
SOURCE: SAMHSA, National Survey on Drug Use and Health, calculated
from 2002 raw data tables available on SAMHSA Web site,
http://oas.samhsa.gov/nsduh.htm.
Heterogeneity in Adolescents With Alcohol Use Disorders
According to 2002 NSDUH data, nicotine use and illicit drug use are much higher among drinking
youth ages 12 to 17 who reported they were binge drinkers or heavy drinkers in the past 30 days
than they were among those who reported drinking less. Research on adolescents in treatment
for alcohol use disorders reflects a similar pattern; these youth typically use cigarettes, are likely
to have more than one substance use disorder, and may manifest psychiatric comorbidities as
well (e.g., Abrantes et al. 2004; Myers and Brown 1994; Rowe et al. 2004). Alcohol-dependent
adolescents with psychiatric comorbidities fare more poorly after treatment: These youth have
lower abstention rates, relapse more rapidly, and show deterioration in their mental health
symptoms following relapse to alcohol or other drugs (Tomlinson et al. 2004; McCarthy et al.
2005). Also, adolescents in substance abuse treatment who have combined heavy alcohol use
and drug disorders manifest a more severe problem profile and less successful treatment
outcomes (Grella 2003). Thus, by the time many youth reach treatment, they are already on a
developmental pathway that ultimately, unless deflected, could lead to even more harmful
behavioral lifestyles, medical disorders, and social consequences.
It is important to keep in mind, however, that adolescents in addiction treatment are a
heterogeneous group and follow multiple pathways of change post-treatment, including
successful ones (Abrantes et al. 2004; Brown 2001). Results from several studies of alcoholdependent youth consistently demonstrate that although a portion of adolescents abstain and
others quickly return to problematic use after treatment, the majority of adolescents change their
use patterns over time, both improving and deteriorating as they face new developmental
challenges (e.g., Brown 2004). Among treated youth, alcohol use following treatment also plays a
significant role in relapse to other drugs (e.g., Brown et al. 2000), as well as in functioning in
school, with peers and family, and in physical and mental health (see Brown and D’Amico 2003).
See Chung and colleagues (2003), “Course of Alcohol Problems in Treated Adolescents,” for
analyses of (1) four longitudinal, alcohol-focused treatment outcome studies that cover 1 to 8
years post-treatment and (2) how these treatment outcomes vary by subtypes of patients,
settings, and trajectories.
NIAAA Research on Adolescent Treatment
Out of concern over the emerging evidence on the nature and magnitude of alcohol use and
associated problems in underage youth, in 1997 NIAAA formally initiated a program of research
to develop effective treatment interventions for adolescents with alcohol disorders. Prior to this,
adult addiction treatments were extended to adolescents and rarely had been rigorously
evaluated in youth (e.g., Brown et al. 2005). A total of 20 clinical projects have been funded under
this NIAAA program, 14 of which were cofunded by SAMHSA’s Center for Substance Abuse
Treatment. The majority of these clinical studies are randomized controlled clinical trials. The
objective of this initial wave of studies is to design and test innovative and developmentally
tailored interventions and, in so doing, provide evidence-based knowledge to improve treatment
outcomes for adolescents who have primary alcohol use disorders or manifest at least one or two
symptoms of alcohol dependence (i.e., are “diagnostic orphans” [Pollock and Martin 1999]). The
results of these projects will be forthcoming over the next few years and will provide new
information on the potential efficacy of family-based, cognitive-behavioral, brief motivational, and
guided self-change interventions in a range of settings. They also will provide information on the
efficacy of these treatments in subgroups of adolescents, including homeless and runaway youth,
high school students, juvenile justice–involved youth, and minority youth. This treatment research
also will shed light on distinctive features of adolescent treatment including processes of change
and factors contributing to post-treatment success.
Adolescent Treatment Interventions
Complex interventions have been developed and tested in adolescents referred for treatment of
alcohol and other drug disorders. Many of these patients are likely to have more than one
substance use disorder (e.g., alcohol and marijuana) and to have other psychiatric disorders as
well (e.g., depression, anxiety, or conduct disorder). Brief interventions are, as a rule, delivered to
adolescents in general medical settings (e.g., primary care clinics, emergency rooms) or in
school-based settings. The range in severity of substance use problems encountered in the
nonaddiction specialty settings is greater than in treatment centers, thereby providing the
opportunity to intervene before serious social consequences and alcohol use disorders develop
(Wagner et al. 1999).
Complex Interventions. Some of the most promising interventions for adolescents with alcohol
use disorders have incorporated multiple components and systems. These include (1) family
therapies with both familial and community components (i.e., multidimensional family therapy
[MDFT]) (Faw et al. 2005; Liddle 2004) and multisystemic therapy (MST) (Swensen et al. 2005)
and (2) cognitive-behavioral therapies (CBT) (Waldron and Kaminer 2004). Several studies have
demonstrated significant improvement among teens with alcohol use disorders who were
receiving family-based intervention, group or individual cognitive-behavioral therapy, and
therapeutic community interventions (e.g., Waldron and Kaminer 2004; Swensen et al. 2005). All
forms of these treatments have substantive differences in intervention design and delivery as well
as efficacy evaluation compared with adult alcoholism treatment research (e.g., Brown et al.
2005; Kaminer and Slesnick 2005; Deas et al. 2000). In particular, consideration of youth
motivation appears critical in engagement and retention of youth in single- component and
complex interventions (e.g., Faw et al. 2005) as well as their continued success following
treatment (e.g., Brown and Ramo in press; Kelly et al. 2002). Although limited at this time,
evidence is emerging that pharmacologic treatment of co-occurring psychiatric disorders benefits
adolescents with alcohol use disorders (e.g., Cornelius et al. 2005). Research on adolescents
funded by NIAAA and the National Institute on Drug Abuse has shown that longer adolescent
treatments generally show better outcomes. Yet longer (usually complex) treatments can be
expensive, and the current health financing system stresses the need for shorter, more costeffective treatment. This poses a major challenge to alcohol and other drug treatment research
today—to identify active ingredients and mechanisms of action of specific components in complex
treatments and to determine if such treatments can maintain their effectiveness in reduced forms.
Several models have been proposed to explain adolescent relapse following treatment (e.g.,
cognitive-behavioral, self-medication) and to predict clinical course after treatment (Brown 2004;
Tomlinson et al. 2004). Environmental factors of exposure to substances and use patterns of
peers in the immediate social network most consistently emerge as proximal risk factors for
adolescent alcohol relapse (e.g., Brown et al. 2005). Personal characteristics including coping
skills, self-esteem, and outcome expectancies have been associated with clinical course, as have
personality/temperament features linked to disinhibition and negative reactivity (see Brown et al.
2005 for a review). Because a substantial portion of youth relapses are planned rather than
unexpected, motivation for sustained abstinence appears to play a critical role in the initial
decisions of youth to return to alcohol or other drug involvement after treatment. Although current
evidence suggests that developmental factors such as stage of neurocognitive development,
psychiatric disorders, and emotional self-regulation play a role in the decisionmaking process
regarding relapse, research is needed to explicate the role of each on variability in clinical course.
Brief Interventions. A primary function of brief interventions is to motivate people to initiate
specific health-related behavior changes. The target of the intervention may be the harmful health
behavior itself or consequences of that behavior (e.g., alcohol-related problems). One of the best
known of these time-limited strategies (one to five sessions) is motivational enhancement (Miller
and Sanchez 1994). This intervention is based on a nonauthoritarian empathic approach that
encourages people to take personal responsibility for change, provides objective personalized
assessment results on the relative magnitude of the problem behavior, provides explicit advice on
the direction to change, and delineates a menu of change options. Brief interventions are flexible
in that they can be used to motivate a person to engage in treatment or they can be used as a
stand-alone early intervention.
Early evidence on the effectiveness of brief interventions in reducing or eliminating alcoholrelated problems in adolescents indicates that they may be effective in reducing both drinking and
its consequences (e.g., drunk driving) (Tevyaw and Monti 2004). Recent school-based brief
intervention studies suggest that reductions in alcohol use and consequences are mediated by
purposeful self-change efforts on the part of teens (e.g., Brown et al. in press) and that
expectations of reduction/cessation outcomes may be critical to this change process (e.g., Metrik
et al. 2004). One 4-year followup of college freshmen found, however, that reduction in
consequences had a lasting effect, whereas reductions in quantity and frequency of alcohol use
had washed out by then (e.g., Baer et al. 2001).
FUTURE INTERVENTION RESEARCH
In most adolescent alcoholism treatment studies, developmental criteria have been limited to age
and grade as indicators of position along the developmental continuum. However, there is
growing recognition of the important contribution that developmentally specific theories, models,
and methods can make to the design of innovative and more effective adolescent treatment
strategies, outcome measures, and evaluation (Brown 2004).
REFERENCES
Abrantes, A.; McCarthy, D.M.; Aarons, G.A.; and Brown, S.A. “Trajectories of Alcohol
Involvement Following Addiction Treatment Through 8-Year Follow-Up in Adolescents.” Paper
presented at the Annual Scientific Meeting of the Research Society on Alcoholism, San
Francisco, CA, July 2002.
Abrantes, A.M.; Brown, S.A.; and Tomlinson, K.L. Psychiatric comorbidity among inpatient
substance abusing adolescents. Journal of Child & Adolescent Substance Abuse 13:83–101,
2004.
American Psychiatric Association (APA). Diagnostic and Statistical Manual of Mental Disorders,
Fourth Edition, Text Revision. Washington, DC: American Psychiatric Association, 2000.
Baer, J.S.; Kivlahan, D.R.; and Marlatt, G.A. High-risk drinking across the transition from high
school to college. Alcoholism: Clinical and Experimental Research 19:54–61, 1995. PMID:
7771663
Baer, J.S.; Kivlahan, D.R.; Blume, A.W.; et al. Brief intervention for heavy-drinking college
students: 4-year follow-up and natural history. American Journal of Public Health 91:1310–1316,
2001. PMID: 11499124
Bangert-Drowns, R.L. The effects of school-based substance abuse education: A meta-analysis.
Journal of Drug Education 18:243–264, 1988. PMID: 3058921
Barnes, G.M.; Reifman, A.S.; Farrell, M.P.; and Dintcheff, B.A. The effects of parenting on the
development of adolescent alcohol misuse: A six-wave latent growth model. Journal of Marriage
and Family 62:175–186, 2000.
Bogenschneider, K.; Wu, M.Y.; Raffaelli, M.; and Tsay, J.C. Parent influences on adolescent peer
orientation and substance use: The interface of parenting practices and values. Child
Development 69:1672–1688, 1998. PMID: 9914646
Brown, S.A. “A Double-Developmental Model of Adolescent Substance Abuse.” Paper presented
at the Annual Scientific Meeting of the Research Society on Alcoholism, Santa Barbara, CA,
1999.
Brown, S.A. Facilitating change for adolescent alcohol problems: A multiple options approach. In:
Wagner, E.F., and Waldron, H.B., eds. Innovations in Adolescent Substance Abuse Intervention.
Oxford, England: Elsevier Science, 2001. pp. 169–187.
Brown, S.A. Measuring youth outcomes from alcohol and drug treatment. Addiction 99
(Suppl.2):38–46, 2004. PMID: 15488104
Brown, S.A., and D’Amico, E.J. Outcomes for alcohol treatment for adolescents. In: Galanter, M.,
ed. Recent Developments in Alcoholism, Vol. 16: Research on Alcoholism Treatment. New York:
Plenum, 2003. pp. 289–312. PMID: 12638643
Brown, S.A., and Ramo, D.E. Clinical course of youth following treatment for alcohol and drug
problems. In: Liddle, H., and Rowe, C., eds. Treating Adolescent Substance Abuse: State of the
Science. Cambridge, England: Cambridge University Press, in press.
Brown, S.A., and Tapert, S.F. Health consequences of adolescent alcohol involvement. In:
National Research Council and Institute of Medicine, Bonnie, R.J., and O’Connell, M.E., eds.
Reducing Underage Drinking: A Collective Responsibility. Washington, DC: National Academies
Press, 2004. pp. 383–401. Available online at: http://www.nap.edu/books/0309089352/html.
Brown, S.A.; Tapert, S.F.; Tate, S.R.; and Abrantes, A.M. The role of alcohol in adolescent
relapse and outcome. Journal of Psychoactive Drugs 32:107–115, 2000. PMID: 10801072
Brown, S.A.; Anderson, K.G.; Ramo, D.E.; and Tomlinson, K.L. Treatment of adolescent alcoholrelated problems: A translational perspective. In: Galanter, M., ed. Recent Developments in
Alcoholism, Vol. 17: Alcohol Problems in Adolescents and Young Adults: Epidemiology,
Neurobiology, Prevention, Treatment. New York: Springer, 2005. pp. 327–348. PMID: 15789874
Brown, S.A.; Anderson, KG.; Schulte, M.T.; et al. Facilitating youth self-change through school
based intervention. Psychology of Addictive Behaviors: Special Issue, in press.
Chaloupka, F.J.; Grossman, M.; and Saffer, H. The effects of price on the consequences of
alcohol use and abuse. In: Galanter, M., ed. Recent Developments in Alcoholism, Vol. 14: The
Consequences of Alcoholism. New York: Plenum, 1998. pp. 331–346. PMID: 9751952
Chung, T., and Martin, C.S. Classification and course of alcohol problems among adolescents in
addictions treatment programs. Alcoholism: Clinical and Experimental Research 25:1734–1742,
2001. PMID: 11781506
Chung, T., and Martin, C.S. What were they thinking? Adolescents’ interpretations of DSM–IV
alcohol dependence symptom queries and implications for diagnostic validity. Drug and Alcohol
Dependence 80:191–200, 2005. PMID: 15894432
Chung, T.; Martin, C.S.; Winters, K.C.; and Langenbucher, J.W. Assessment of alcohol tolerance
in adolescents. Journal of Studies on Alcohol 62:687–695, 2001. PMID: 11702808
Chung, T.; Martin, C.S.; Armstrong, T.D.; and Labouvie, E.W. Prevalence of DSM–IV alcohol
diagnoses and symptoms in adolescent community and clinical samples. Journal of the American
Academy of Child & Adolescent Psychiatry 41:546–554, 2002. PMID: 12014787
Chung, T.; Martin, C.S.; Grella, C.E.; et al. Course of alcohol problems in treated adolescents.
Alcoholism: Clinical and Experimental Research 27:253–261, 2003. PMID: 12605074
Chung, T.; Martin, C.S.; and Winters, K.C. Diagnosis, course, and assessment of alcohol abuse
and dependence in adolescents. In: Galanter, M., ed. Recent Developments in Alcoholism, Vol.
17: Alcohol Problems in Adolescents and Young Adults: Epidemiology, Neurobiology, Prevention,
Treatment. New York: Springer, 2005. pp. 5–27. PMID: 15789857
Clark, D. The natural history of adolescent alcohol use disorders. Addiction 99(Suppl. 2):5–22,
2004. PMID: 15488102
Cook, P.J., and Moore, M.J. The economics of alcohol abuse and alcohol-control policies. Health
Affairs 21:120–133, 2002. PMID: 11900152
Cornelius, J.R.; Clark, D.B.; Bukstein, O.G.; et al. Fluoxetine in adolescents with comorbid major
depression and an alcohol use disorder: A 3-year follow-up study. Addictive Behaviors 30:807–
814, 2005. PMID: 15833583
D’Amico, E.J.; McCarthy, D.M.; Metrik, J.; and Brown, S.A. Alcohol-related services: Prevention,
secondary intervention and treatment preferences of adolescents. Journal of Child & Adolescent
Substance Abuse 14:61–80, 2004.
Deas, D.; Riggs, P.; Langenbucher, J.; et al. Adolescents are not adults: Developmental
considerations in alcohol users. Alcoholism: Clinical and Experimental Research 24:232–237,
2000. PMID: 10698377
Dielman, T.E. School-based research on the prevention of adolescent alcohol use and misuse:
Methodological issues and advances. In: Boyd, G.M.; Howard, J.; and Zucker, R.A.; eds. Alcohol
Problems among Adolescents: Current Directions in Prevention Research. Hillsdale, N.J:
Lawrence Erlbaum, 1995. pp.125–146.
Dishion, T.J., and Kavanagh, K. A multilevel approach to family-centered prevention in schools:
Process and outcome. Addictive Behaviors 25:899–911, 2000. PMID: 11125778
Dusenbury, L.; Brannigan, R.; Falco, M.; and Hansen, W.B. A review of research on fidelity of
implementation: Implications for drug abuse prevention in school settings. Health Education
Research 18:237–256, 2003. PMID: 12729182
Ellickson, P.L.; Tucker, J.S.; and Klein, D.J. Ten-year prospective study of public health problems
associated with early drinking. Pediatrics 111:949–955, 2003. PMID: 12728070
Faw, L.; Hogue, A.; and Liddle, H.A. Multi-dimensional implementation evaluation of a residential
treatment program for adolescent substance abuse. American Journal of Evaluation 26:77–94,
2005.
Flay, B.R. Approaches to substance use prevention utilizing school curriculum plus social
environment change. Addictive Behaviors 25:861–885, 2000. PMID: 11125776
Foxcroft, D.R.; Ireland, D.; Lister-Sharp, D.J.; et al. Longer-term primary prevention for alcohol
misuse in young people: A systematic review. Addiction 98:397–411, 2003. PMID: 12653810
Gorman, D.M. On the difference between statistical and practical significance in school-based
drug abuse prevention. Drugs: Education, Prevention and Policy 2:275–283, 1995.
Gottfredson, D.C., and Wilson, D.B. Characteristics of effective school-based substance abuse
prevention. Prevention Science 4:27–38, 2003. PMID: 12611417
Grella, C.E. Alcohol use outcomes at 1 year among adolescents in the drug abuse treatment
outcomes studies (DATOS-A). In: Chung, T.; Martin, C.S.; Grella, C.E.; et al., eds.; Course of
alcohol problems in treated adolescents. Alcoholism: Clinical and Experimental Research
27:254–255, 2003. PMID: 12605074
Grube, J.W. Preventing sales of alcohol to minors: Results from a community trial. Addiction
92(Suppl. 2):S251–S260, 1997. PMID: 9231448
Hansen, W.B. School-based substance abuse prevention: A review of the state of the art in
curriculum, 1980–1990. Health Education Research 7:403–430, 1992. PMID: 10171672
Hingson, R.W., and Howland, J. Comprehensive community interventions to promote health:
Implications for college-age drinking problems. Journal of Studies on Alcohol (Suppl. 14):226–
240, 2002. PMID: 12022727
Hingson, R.; McGovern, T.; Howland, J.; et al. Reducing alcohol-impaired driving in
Massachusetts: The Saving Lives Program. American Journal of Public Health 86:791–797,
1996. PMID: 8659651
Holder, H.D. Community prevention of alcohol problems. Addictive Behaviors 25:843–859, 2000.
PMID: 11125775
Kaminer, Y., and Slesnick, N. Evidence-based cognitive-behavioral and family therapies for
adolescent alcohol and other substance use disorders. In: Galanter, M., ed. Recent
Developments in Alcoholism, Vol. 17: Alcohol Problems in Adolescents and Young Adults:
Epidemiology, Neurobiology, Prevention, Treatment. New York: Plenum, 2005. pp. 383–405.
PMID: 15789877
Kelly, J.F.; Myers, M.G.; and Brown, S.A. Do adolescents affiliate with 12-step groups? A
multivariate process model of effects. Journal of Studies on Alcohol 63:293–304, 2002. PMID:
12086130
Kenkel, D.S., and Manning, W.G. Perspectives on alcohol taxation. Alcohol Health & Research
World 20(4):230–238, 1996.
Komro, K.A., and Toomey, T.L. Strategies to prevent underage drinking. Alcohol Research &
Health 26(1):5–14, 2002. PMID: 12154652
Kypri, K.; McCarthy, D.M.; Coe, M.T.; and Brown, S.A. Transition to independent living and
substance involvement of treated and high-risk youth. Journal of Child & Adolescent Substance
Abuse 13:85–100, 2004.
Labouvie, E. Maturing out of substance use: Selection and self-correction. Journal of Drug Issues
26:457–476, 1996.
Langenbucher, J.W., and Martin, C.S. Alcohol abuse: Adding content to category. Alcoholism:
Clinical and Experimental Research 20 (Suppl. 8):270A–275A, 1996. PMID: 8947279
Leung, S.F., and Phelps, C.E. My kingdom for a drink. . . ? A review of estimates of the price
sensitivity of demand for alcoholic beverages. In: Hilton, M.E., and Bloss, G., eds. Economics and
the Prevention of Alcohol-Related Problems. NIAAA Research Monograph No. 25. Rockville, MD:
National Institute on Alcohol Abuse and Alcoholism, 1993. pp. 1–31.
Lewinsohn, P.M.; Rohde, P.; and Seeley, J.R. Alcohol consumption in high school adolescents:
Frequency of use and dimensional structure of associated problems. Addiction 91:375–390,
1996. PMID: 8867200
Liddle, H.A. Family-based therapies for adolescent alcohol and drug use: Research contributions
and future needs. Addiction 99(Suppl.2):76–92, 2004. PMID: 15488107
Maisto, S.A.; Martin, C.S.; Pollock, N.K.; et al. Nonproblem drinking outcomes in adolescents
treated for alcohol use disorders. Experimental and Clinical Psychopharmacology 10:324–331,
2002. PMID: 12233994
Martin, C.S. “Contrasting Alternative Diagnostic Criteria for Adolescent Alcohol Use Disorders.”
Paper presented at the annual meeting of the Research Society on Alcoholism, Santa Barbara,
CA, June 1999.
Martin, C.S., and Winters, K.C. Diagnosis and assessment of alcohol use disorders among
adolescents. Alcohol Health & Research World 22(2):95–105, 1998. PMID: 15706783
Martin, C.S.; Langenbucher, J.W.; Kaczynski, N.A.; and Chung, T. Staging in the onset of DSM–
IV alcohol symptoms in adolescents: Survival/hazard analyses. Journal of Studies on Alcohol
57:549–558, 1996. PMID: 8858553
Mayzer, R.; Puttler, L.I.; Wong, M.M.; et al. Development constancy of social misbehavior from
early childhood to adolescence as a predictor of early onset of alcohol use. (Abstract).
Alcoholism: Clinical and Experimental Research 27:65A, 2003.
McCarthy, D.M.; Tomlinson, K.L.; Anderson, K.G.; et al. Relapse in alcohol and drug disordered
adolescents with comorbid psychopathology: Changes in psychiatric symptoms. Psychology of
Addictive Behaviors 19:28–34, 2005. PMID: 15783275
McGue, M. The behavioral genetics of alcoholism. Current Directions in Psychological Science
8:109–115, 1999.
Metrik, J.; Frissell, K.C.; McCarthy, D.M.; et al. Strategies for reduction and cessation of alcohol
use: What do adolescents prefer? Alcoholism: Clinical and Experimental Research 27:74–80,
2003. PMID: 12544009
Metrik, J.; McCarthy, D.M.; Frissell, K.C.; et al. Adolescent alcohol reduction and cessation
expectancies. Journal of Studies on Alcohol 65: 217– 226, 2004. PMID: 15151353
Miller, W.R., and Sanchez, V.C. Motivating young adults for treatment and lifestyle change. In:
Howard, G.S., and Nathan, P.E., eds. Alcohol Use and Misuse by Young Adults. Notre Dame, IN:
University of Notre Dame Press, 1994. pp. 55–81.
Myers, M.G., and Brown, S.A. Smoking and health in substance abusing adolescents: A two year
follow-up. Pediatrics 93:561–566, 1994. PMID: 8134209
National Research Council (NRC) and Institute of Medicine (IOM), Committee on Developing a
Strategy to Reduce and Prevent Underage Drinking. Bonnie, R.J., and O’Connell, M.E., eds.
Reducing Underage Drinking: A Collective Responsibility. Washington, DC: National Academies
Press, 2004. Available online at: http://www.nap.edu/books/0309089352/html.
Nelson, C.B., and Wittchen, H.U. DSM–IV alcohol disorders in a general population sample of
adolescents and young adults. Addiction 93:1065–1077, 1998. PMID: 9744137
Nye, C.L.; Zucker, R.A.; and Fitzgerald, H.E. Early family-based intervention in the path to alcohol
problems: Rationale and relationship between treatment process characteristics and child and
parenting outcomes. Journal of Studies on Alcohol (Suppl. 13):10–21, 1999. PMID: 10225484
O’Leary, T.A.; Brown, S.A.; Colby, S.M.; et al. Treating adolescents together or individually?
Issues in adolescent substance abuse interventions. Alcoholism: Clinical and Experimental
Research 26:890–899, 2002. PMID: 12068259
Perry, C.L.; Williams, C.L.; Veblen-Mortenson, S.; et al. Project Northland: Outcomes of a
communitywide alcohol use prevention program during early adolescence. American Journal of
Public Health 86:956–965, 1996. PMID: 8669519
Perry, C.L.; Williams, C.L.; Komro, K.A.; et al. Project Northland: Long-term outcomes of
community action to reduce adolescent alcohol use. Health Education Research 17:117–132,
2002. PMID: 11888042
Pollock, N.K., and Martin, C.S. Diagnostic orphans: Adolescents with alcohol symptoms who do
not qualify for DSM–IV abuse or dependence diagnoses. American Journal of Psychiatry
156:897– 901, 1999. PMID: 10360129
Robins, L.N., and Barrett, J.E., eds. The Validity of Psychiatric Diagnosis. New York: Raven
Press, 1989.
Rohde, P.; Lewinsohn, P.M.; Kahler, C.W.; et al. Natural course of alcohol use disorders from
adolescence to young adulthood. Journal of the American Academy of Child & Adolescent
Psychiatry 40:83–90, 2001. PMID: 11195569
Rowe, C.L.; Liddle, H.A.; Greenbaum, P.E.; et al. Impact of psychiatric comorbidity on treatment
of adolescent drug abusers. Journal of Substance Abuse Treatment 26:129–140. 2004. PMID:
15050090
Sanders, M.R. Community-based parenting and family support interventions and the prevention
of drug abuse. Addictive Behaviors 25:929–942, 2000. PMID: 11125780
Schulenberg, J.; Maggs, J.L.; Steinman, K.J.; and Zucker, R.A. Development matters: Taking the
long view on substance abuse etiology and intervention during adolescence. In: Monti, P.M.;
Colby, S.M.; and O’Leary, T.A.; eds. Adolescents, Alcohol, and Substance Abuse: Reaching
Teens through Brief Interventions. New York: Guilford, 2001. pp. 19–57.
Silvia, E.S., and Thorne, J. School-Based Drug Prevention Programs: A Longitudinal Study in
Selected School Districts. Research Triangle Park, NC: Research Triangle Institute, 1997.
Available online at: http://www.rti.org/pubs/0397drugfree_schools.pdf.
Spoth, R.L.; Redmond, C.; and Shin, C. Randomized trial of brief family interventions for general
populations: Adolescent substance use outcomes 4 years following baseline. Journal of
Consulting and Clinical Psychology 69:627–642, 2001. PMID: 11550729
Spoth, R.; Redmond, C.; Shin, C.; and Azevedo, K. Brief family intervention effects on adolescent
substance initiation: School-level growth curve analyses 6 years following baseline. Journal of
Consulting and Clinical Psychology 72:535–542, 2004. PMID: 15279537
Steinberg, L.; Fletcher, A.; and Darling, N. Parental monitoring and peer influences on adolescent
substance use. Pediatrics 93(6 Pt 2):1060–1064, 1994. PMID:8197008
Substance Abuse and Mental Health Services Administration (SAMHSA), Office of Applied
Studies. Results from the 2002 National Survey on Drug Use and Health: National Findings.
NSDA Series H–22, DHHS Pub. No. SMA 03–3836. Rockville, MD: SAMHSA, 2003. Available
online at: http://www.oas.samhsa.gov/nhsda/2k2nsduh/Results/2k2Results.htm .
Swensen, C.C.; Henggeler, S.W.; Taylor, I.S.; and Addison, O.W. Multisystemic Therapy and
Neighborhood Partnerships: Reducing Adolescent Violence and Substance Abuse. New York:
Guilford, 2005.
Tevyaw, T.O., and Monti, P.M. Motivational enhancement and other brief interventions for
adolescent substance abuse: Foundations, applications, and evaluations. Addiction 99(Suppl.
2):63–75, 2004. PMID: 15488106
Tobler, N.S. Meta-analysis of 143 adolescent drug prevention programs: Quantitative outcome
results of program participants compared to a control or comparison group. Journal of Drug
Issues 16:537–567, 1986.
Tobler, N.S., and Stratton, H.H. Effectiveness of school-based drug prevention programs: A
meta-analysis of the research. Journal of Primary Prevention 18:71–128, 1997.
Tomlinson, K.L.; Brown, S.A.; and Abrantes, A. Psychiatric comorbidity and substance use
treatment outcomes of adolescents. Psychology of Addictive Behaviors 18:160–169, 2004. PMID:
15238058
Toomey, T.L., and Wagenaar, A.C. Environmental policies to reduce college drinking: Options
and research findings. Journal of Studies on Alcohol (Suppl. 14):193–205, 2002. PMID: 12022725
Wagenaar, A.C., and Perry, C.L. Community strategies for the reduction of youth drinking: Theory
and application. Journal of Research on Adolescence 4:319–345, 1994.
Wagenaar, A.C., and Toomey, T.L. Effects of minimum drinking age laws: Review and analyses
of the literature from 1960 to 2000. Journal of Studies on Alcohol (Suppl. 14):206–225, 2002.
PMID: 12022726
Wagenaar, A.C.; Murray, D.M.; Gehan, J.P.; et al. Communities Mobilizing for Change on
Alcohol: Outcomes from a randomized community trial. Journal of Studies on Alcohol 61:85–94,
2000a. PMID: 10627101
Wagenaar, A.C.; Murray, D.M.; and Toomey, T.L. Communities Mobilizing for Change on Alcohol
(CMCA): Effects of a randomized trial on arrests and traffic crashes. Addiction 95:209–217,
2000b. PMID: 10723849
Wagner, E.F.; Brown, S.A.; Monti, P.; et al. Innovations in adolescent substance abuse
intervention. Alcoholism: Clinical and Experimental Research 23:236–249, 1999. PMID: 10069552
Wagner, E.F.; Lloyd, D.A.; and Gil, A.G. Racial/ethnic and gender differences in the incidence
and onset age of DSM–IV alcohol use disorder symptoms among adolescents. Journal of Studies
on Alcohol 63:609–619, 2002. PMID: 12380858
Waldron, H.B., and Kaminer, Y. On the learning curve: The emerging evidence supporting
cognitive-behavioral therapies for adolescent substance abuse. Addiction 99(Suppl. 2):93–105,
2004. PMID: 15488108
Winters, K.C. Treating adolescents with substance use disorders: An overview of practice issues
and treatment outcome. Substance Abuse 20:203–225, 1999. PMID: 12511829
Zucker, R.A., and Noll, R.B. The interaction of child and environment in the early development of
drug involvement: A far-ranging review and a planned very early intervention. Drugs and Society
2:57–97, 1987.
Zucker, R.A.; Fitzgerald, H.E.; and Moses, H.D. Emergence of alcohol problems and the several
alcoholisms: A developmental perspective on etiologic theory and life course trajectory. In:
Cicchetti, D., and Cohen, D.J., eds. Developmental Psychopathology, Volume 2: Risk, Disorder
and Adaptation. New York: John Wiley & Sons, 1995. pp. 677–711.
Glossary
Acetaldehyde: A toxic product that results from the breakdown of alcohol by the enzyme alcohol
dehydrogenase.
Adenosine triphosphate (ATP): A molecule that provides the energy needed for many key
metabolic reactions. ATP is generated largely in the mitochondria.
Alcohol dehydrogenase: An enzyme that breaks down alcohol by oxidation, converting it to
acetaldehyde.
Alcohol poisoning: The result of the acute toxic effects of alcohol consumption, which can range
from gastritis and severe gastrointestinal bleeding to respiratory arrest and death.
Allele: One of two or more variants of a gene or other DNA sequence. Different alleles of a gene
generally serve the same function (e.g., code for a protein that affects eye color) but may produce
different phenotypes (e.g., blue eyes or brown eyes). Some alleles may be defective and produce
a protein that has no function or an abnormal function.
Amino acids: A class of biological molecules, 20 of which serve as the building blocks of
proteins.
Amygdala: A complex grouping of brain cells that, among other things, is thought to be involved
in a person’s emotional reactions and in coordinating the body’s response to stress.
Bases: In genetics, the portion of a nucleotide molecule that contributes to the genetic code.
DNA bases include adenine, thymine, guanine, and cytosine; in RNA, uracil replaces thymine.
Behavioral and cognitive deficits: Difficulties or disorders in social performance or learning,
which include attention deficit disorder, behavioral undercontrol/conduct disorder, delinquency,
lower IQ, poor school performance, and low self-esteem.
Binge drinking: The National Institute on Alcohol Abuse and Alcoholism defines binge drinking
as the amount of alcohol leading to a blood alcohol content (BAC) of 0.08, which, for most adults,
would be reached by consuming five drinks for men or four for women over a 2-hour period.
Cancellous bone: The type of tissue found in the marrow cavity of bone.
Candidate gene: A gene that has been implicated in causing or contributing to a particular
phenotype (e.g., disease).
Catecholamine: One of a group of physiologically active substances with various roles in the
functioning of the nervous system; also helps regulate heart functioning.
Catechol-O-methyltransferase (COMT): An enzyme that catalyzes the transfer of a methyl
group to catcholamines, including the neurotransmitters dopamine, norepinephrine, and
epinephrine.
Central nervous system (CNS): The part of the nervous system consisting of the brain and
spinal cord.
Children of alcoholics: Biological children, foster children, adopted children, or stepchildren
living in households with one or more adults classified as having an alcohol abuse or dependence
diagnosis during the past year.
Chromosomes: Microscopic rod-shaped structures composed of double-stranded DNA and
proteins; can be visualized during a certain phase of the cell cycle. Chromosomes are often
regarded as representing the entire genome of an organism.
Cortical bone: Tissue that forms the shaft of the bone.
DNA (deoxyribonucleic acid): The molecule that carries the genetic code in all organisms
except some viruses. DNA is composed of a linear sequence of nucleotides.
Dopamine: An excitatory neurotransmitter that plays a role in the reward system in the brain and
possibly also in the reinforcing properties of alcohol use.
Endophenotype: A heritable trait or characteristic that is not a direct symptom of the condition
under investigation but has been shown to be associated with the condition; for example, certain
neurobiological characteristics have been noted in people with alcoholism and may be used as
endophenotypes to identify people at risk for alcoholism.
Environmental-level interventions: Efforts to prevent alcohol use problems by focusing on
changing the environment to reduce the availability of alcohol to youth and opportunities to drink,
increase penalties for violation of minimum legal drinking age laws, and lower a community’s
tolerance for alcohol use by youth.
Enzyme: A substance (usually a protein) that speeds up, or catalyzes, a specific biochemical
reaction without being itself permanently altered or consumed.
Event-related potentials (ERPs): Brain waves elicited by a stimulus. One component of the
ERP, measured approximately 300 milliseconds after exposure to the stimulus, is called the P300
signal. It is thought to represent cognitive processing of new information and is commonly
reduced in people at risk for alcoholism.
Externalizing disorders: A constellation of behaviors including acting negatively on the external
environment; and disruptive, hyperactive, and aggressive behavior. In the aggregate, these
behaviors may also be referred to as conduct problems and antisocial or undercontrolled
behavior.
G protein: Intracellular regulatory molecules whose actions are instigated by neurotransmitters.
Several types of G proteins exist, including stimulatory G proteins (G s), which enhance the
activities of enzymes, and inhibitory G proteins (Gi), which inhibit the activities of other enzymes.
Gamma-aminobutyric acid (GABA): An inhibitory neurotransmitter whose actions are
influenced by alcohol; may play a role in alcohol withdrawal.
Gene: A combination of DNA segments that together constitute a unit capable of expressing one
or more functional gene products.
Gene expression: The processes through which the genetic information contained within a gene
on the DNA is converted into a gene product (e.g., a protein).
Genetic code: The way in which information is carried by the DNA molecules determines the
arrangement of amino acids in the proteins synthesized by the cells. Each of the 20 amino acids
found in proteins is represented by 1 or more units of 3 consecutive nucleotide bases in the
mRNA and in the DNA from which the mRNA is derived. All living organisms and viruses use the
same genetic code.
Genetic marker: A segment of DNA with an identifiable physical location on a chromosome. The
inheritance of a genetic marker can be followed.
Genome: The total genetic material of an organism or species.
Genomics: The comprehensive study of the interactions and functional dynamics of whole sets
of genes and their products.
Genotype: The genetic makeup of an individual organism, which is determined by the specific
alleles of each gene carried by the individual. Differences in alleles among individuals interact
with environmental influences to account for the differences in phenotype observed among those
individuals.
Glucocorticoid: Any of a group of steroid hormones, such as cortisol, that are produced by the
adrenal gland and are involved in the metabolism of carbohydrates, proteins, and fats; plays a
key role in the stress response.
Hypothalamic-pituitary-gonadal (HPG) axis: A system consisting of the hypothalamus, the
pituitary, and either the ovaries or testes, which is involved in female or male reproduction,
respectively, and awakens dramatically at puberty.
Indicated prevention: Prevention efforts that identify individuals who are exhibiting early signs of
alcohol abuse and other associated problem behaviors and target them with special programs.
Individual-level interventions: Efforts to prevent alcohol use problems by focusing on the
individual—that is, changing the person’s knowledge, attitudes, and skills, so that he or she is
better able to resist influences that support drinking.
Insulinlike growth factor-1 (IGF-1): A protein produced by the liver in response to growth
hormone (GH). IGF-1 carries out some of the effects of GH at the tissue level.
Internalizing disorders: A tendency in some children to express emotional distress within the
child’s internal environment rather than his or her external world; behavior includes problems
such as being withdrawn, anxious, inhibited, or depressed; also referred to as overcontrolled.
Knockout: The deletion or deactivation of a gene in a mouse or other laboratory animal to create
a line of animals that are incapable of producing the gene product.
Mitochondria: Structures within cells that generate most of the cell’s energy through the
production of adenosine triphosphate (ATP).
Neuron: A nerve cell.
Neuropeptide: A small molecule that can regulate nerve cell function and is made up of amino
acids.
Neurotransmitter: A chemical messenger (i.e., dopamine, GABA) that conveys a signal from
one neuron to another.
Nucleotides: Biological molecules with a variety of physiologic and metabolic functions;
nucleotides also serve as the building blocks of DNA and RNA.
Phenotype: The observable structural or functional characteristics of an individual organism that
result from the interaction of its genotype with environmental factors.
Phosphorylation: A chemical reaction resulting in the addition of phosphate groups to other
molecules (e.g., proteins). Phosphorylation reactions often are critical to regulation of receptor
activity and the functions of other proteins.
Protein: The product of the genetic information encoded in a gene. Proteins are made up of
amino acids; enzymes are one type of protein.
Protein kinases: Enzymes that add phosphate groups to other proteins in a chemical reaction
called phosphorylation; this activates or inactivates the modified proteins.
Receptor: A protein, usually found on the surface of a neuron or other cell, that recognizes and
binds to neurotransmitters or other chemical messengers.
Reinforcement: A process by which a response or behavior (e.g., alcohol consumption) is
strengthened by the anticipation of a reward (e.g., a feeling of euphoria).
Ribonucleic acid (RNA): A class of molecules composed of nucleotides, similar to those that
form DNA. The major types of RNA are mRNA, tRNA, and rRNA, which play important roles in
gene expression.
Selected prevention: Prevention strategies that target subsets of the total population which are
deemed to be at risk for alcohol problems by virtue of their membership in a particular population
segment—for example, children of adult alcoholics, dropouts, or students who are failing
academically.
Self-regulation: The ability to monitor and modulate internal states, including both the ability to
modulate affect and level of arousal and the neurocognitive executive capacities to engage in
goal-directed behavior. These executive cognitive capacities include the regulation of attention,
planning, organization, concept formation, abstract reasoning, cognitive flexibility, self-monitoring,
motor programming, and motor control.
Serotonin: A neurotransmitter that subtly modifies neuron function, exerting its effects by
interacting with receptors on the neuron’s surface.
Synapse: A microscopic gap separating adjacent neurons, where neurotransmitters and
receptors cluster.
Transgenic animals: An animal into whose genome foreign DNA (i.e., a candidate gene) has
been introduced to study the function of DNA.
Prevention strategies that address the entire population (national,
local community, school, neighborhood) with messages and programs aimed at
preventing or delaying the abuse of alcohol.
Universal prevention:
Download