Position of Gateway Drugs in the Spectrum of Adolescent
Drug-Use Initiation in Indiana: Relevance of Market
Basket Analysis of Data Mining in Detection of Common
Substance-Use Initiation Sequences
Ahmed H. YoussefAgha*(PhD), Wasantha P. Jayawardene*†(MD)
* Department of Applied Health Science, School of Health, Physical Education, and Recreation, Indiana
University Bloomington, Indiana, United States; † Corresponding Author
Abstract
Background: Empirical evidence confirms that the
majority of individuals’ legal or illicit drug use begins after
use of cigarettes, alcohol, or cannabis (marijuana) hence
they are known as the gateway drugs.
Objectives: To study the sequences of initiating use of
gateway drugs and other drugs among adolescents,
especially among 12th-grade students, in Indiana.
Methods: Data from the 1993-2009 Annual Surveys of
Alcohol, Tobacco, and Other Drug Use by Indiana Children
and Adolescents was used for the current study. Market
Basket Analysis was used to identify sequences and
association among drug- use.
Results: The majority of adolescents initiated drug use
with gateway drugs followed by combining them with
prescription drugs.
Conclusion: Market Basket Analysis reveals that the
gateway theory is applicable to Indiana adolescents
because many of them initiate drug use with alcohol,
tobacco, or marijuana or with a combination of them
followed by use of prescription drugs.
Keywords: Gateway drugs, Prescription drugs, Market
basket analysis; Drug-use initiation
1 Introduction
Empirical evidence confirms that the majority of
individuals’ illicit drug use starts only after they use
cigarettes, alcohol, or cannabis (marijuana). Because using
these less deleterious drugs may lead to more dangerous
hard drugs, these three substances are known as the gateway
drugs [1]. The gateway pattern of drug initiation describes a
normative sequence that begins with alcohol and tobacco
use followed by cannabis use and then other illicit drugs [2].
In the United States also, this progression proceeds from the
use of tobacco or alcohol to the use of marijuana and other
illicit drugs. Kandel presented the first systematic discussion
of the gateway hypothesis [3]. He explored the hypothesis
from various perspectives ranging from developmental
social psychology to prevention and intervention science,
animal models, neurobiology and analytical methodology.
Although this pattern is recognized, some evidence suggests
that prevention strategies focusing on breaking this chain to
chronic and severe drug abuse may be of limited value [4].
Considering the prevalence of these three substances among
the U.S. adolescent population, the gateway drugs should
still be given maximum attention when compared to all
other substances that can cause abuse and/or dependence
[5].
Some studies revealed that weekly alcohol
consumption came after marijuana use and preceded all
other illicit drug use for Hispanic, White, and Black youth,
but followed use of hard drugs for Asians [6]. There was
evidence supporting that both Hispanic ethnicity and gender
was significant in determining adolescent polydrug use. In
the first year of middle school, gender moderated the effect
of Hispanic ethnicity on lifetime polydrug use, and more
serious levels of polydrug use were observed in the second
year of middle school [7].
According to data from a recent national survey,
nonsmokers who were also nondrinkers were most likely to
indicate they would never use drugs in the future; users of
both substances were most likely to indicate they would use
drugs. And while smokers and drinkers were most likely to
indicate expected illegal substance use in the future, those
who only smoke were more likely than those who only
drink to indicate probable use of such substances [8].
Adolescents were not likely to use marijuana without first
using alcohol and tobacco, and they will not use more
serious drugs, such as cocaine and heroin, without first
using marijuana [9, 10]. Some research revealed that
Whites, both male and female, had a significantly stronger
positive association between predictors and drug use when
compared to Blacks, while White females were most likely
to use gateway substances, followed by White males [11].
Positive alcohol and cannabis outcome
expectancies were meaningfully related to expectancies of
future substance use, and positive cannabis outcome
expectancies increased, while negative cannabis outcome
expectancies decreased, with increasing frequency of
alcohol use [12]. In another research, it was revealed that
alcohol intake has a positive correlation with drug abuse
among smokers [13]. A South African study showed that the
pattern of onset of drug-use was similar across genders.
Black South African adolescents first used either alcohol or
tobacco, followed by both, and then dagga (cannabis) [14].
A prospective study among male Japanese students found
that those who had smoking experiences by 16 years of age
were more likely to abuse alcohol by 22 years of age than
those without smoking experiences, but females did not
show such a correlation [15]. In another study in Japan,
cigarette smoking in high school students showed a strong
relationship with solvent inhalation, while drinking alcohol
depended on the presence of adults [16].
Particularly strong associations were found
between smoking and having many friends who smoke.
Using marijuana was strongly correlated with having friends
or older siblings who use marijuana. The self-esteem scale
score was not correlated with substance use. Anomie and
antisocial behavior were more strongly associated with
substance use than depression was. These associations were
stronger for females than for males. Therefore, when
designing and implementing preventive interventions in
schools, it is essential to simultaneously address the use of
gateway drugs and deviant behavior with environmental risk
factors [17]. Current prevention programs are often
ineffective when substance use is normalized by schools,
community, and family. In such situations, positive adult
role models can deter use, and focus group discussions can
strengthen the development of tailored prevention programs
[18].
Between U.S. and European students, there were
the similar trends in drug use of gateway drugs already in
use by early adolescence and higher rates of drug use among
males than among females. However, cross-national
differences in cannabis use revealed that U.S. preadolescents were 25 times more likely to use it than those in
Europe. In the same study, Arizona Latinos reported higher
cannabis use than Arizona non-Latinos, which was probably
influenced by their acculturation level [19]. Low physical
activity is associated with cigarette smoking and marijuana
use. For alcohol consumption, significant links were found
to race/ethnicity or sex, suggesting that socio-cultural
factors may affect the relationships between physical
activity and substance use [20]. Data from the Youth Risk
Behavior Survey revealed that those using cigarettes before
age 13 were 3.3 times more likely to have used marijuana
than those who had never smoked. And users of alcohol
were 4.5 times more likely to have used marijuana than
those who had never used alcohol. The same survey showed
that youth using marijuana before the age of 14 were 7.4
times more likely to have used other drugs even after
controlling for selected other risk and protective behaviors
[21].
The use of both tobacco and illicit drugs appears to
be strongly associated with alcohol use, which is more
prevalent, and the risk of smoking and illicit drug use is
particularly high in adolescents who report high levels of
drunkenness [22]. Factors which tend to increase the
probability of alcohol use by adolescents include the fact
that their friends drink, their awareness of the risks
associated with alcohol use, and ease in obtaining alcohol.
Hence, the typical adolescent who uses alcohol seems to be
a risk-taker who may enjoy the dangers surrounding alcohol
use and have alcohol-using friends. Religion, gender, race,
academic performance, and extracurricular school activities
are not directly related to the use of alcohol [23].
In 2006, marijuana (cannabis) was the most
commonly used illicit drug (14.8 million past-month users)
among persons in the United States aged 12 or older
Marijuana users were twice as likely to use illicit drugs as
young adults than non-users. Shared environmental factors
mediated much of the relationship between adolescent
marijuana use and young adult drug use [24]. Individuals
who used cannabis by age 17 had higher rates of other drug
use, alcohol dependence, and drug abuse or dependence.
The association may arise from the effects of the peer and
social context within which cannabis is obtained and used.
In particular, early access and use of cannabis may reduce
perceived barriers against the use of other illegal drugs and
provide more access to these drugs [25].
Although the gateway effects of marijuana exist,
they are not required to explain the common-factor model of
initiating illicit drug use [26]. Extensive research does
suggest that marijuana use tends to precede the use of other
illicit substances among adolescents; however, there is a
simultaneous argument that the correlation between
marijuana use and other drug use may be spurious, which
reflects the influence of one or more confounding variables
that can concurrently cause both behaviors. Even after
adjusting for the influence of variables, National Youth
Survey results confirm the hypothesis that marijuana use
exerts a causal influence on one’s probability of using other
illicit substances [27].
2 Purpose of the Study
This study aims to study the sequences of initiating
use of gateway and other drugs among adolescents,
especially among 12th-grade students, in Indiana. The study
also explores the applicability of method “Market Basket
Analysis” of data mining in detection of common drug-use
initiation patterns in the community.
3 Methods
3.1 Study Design
Data from the 1993 to 2009 Annual Surveys of
Alcohol, Tobacco, and Other Drug Use by Indiana Children
and Adolescents—a survey conducted by the Indiana
Prevention Resource Center—was used for the current study
[1]. The original survey’s purpose was to provide data for
state and local planning in respect to alcohol, tobacco, and
other drug use, gambling behaviors, and risk and protective
factors.
3.2 Study Population
Surveys were administered through local school
officials to students in grades 6 through 12 in 557 schools
throughout Indiana. Participation in the survey was
voluntary. In 2009, a total of 202,091 youth (182,496 usable
surveys) from both public and private schools completed it
[1]. The current research sample was composed of 12thgraders. They are of particular interest because they are on
the verge of entering college or the workforce. Their
substance abuse habits can negatively impact their academic
and career functioning, which has detrimental effects on
society.
3.3 Instrument
A closed-ended, self-administered written
questionnaire that was anonymous and voluntary asked
adolescents about their use of twenty different types of
drugs or drug categories, including prescription
medications. When necessary, examples and descriptions
were provided next to the drug’s name or its classification.
3.4 Analysis
In 1980s, Yamaguchi and Kandel [28] utilized the
log linear model to study associations and sequences of drug
use. Their model was applied to study sequences up to five
drugs; alcohol, cigarette, marijuana, cocaine, and heroin.
This model is selected for our research to study the
preferences of using drugs.
Annual prevalence, the percentage who report
using a particular drug at least once in the past year, was
used for the current study. Annual prevalence in abuse of
prescription drugs, alcohol, tobacco, marijuana, cocaine, and
heroin, including the self-reported age at first-time use of
each drug, was obtained from the survey [1]. Prescription
drug use among 12th-graders was identified using a sample
of 260,183 students during the 3-year period of 2007-2009.
For alcohol, cigarettes, and marijuana use among 12 thgraders during the same time period, a sample of 246,793
students was utilized.
Adolescents were asked, in which grade he or she
started using each drug. Based on this information, the
chronological order of drugs use initiation was established.
This study focuses on data derived from a single item of the
survey. Both items were used to collect information about
11 different drugs or drug categories: alcohol, cigarettes,
marijuana, OTC substances, tranquilizers, narcotics, Ritalin,
cocaine, crack, steroids, and heroin. The question asks “At
what age did you first use drug A” with the response
options: 10 or younger, 11, 12, 13, 14, 15, 16, 17, and 18 or
older.
Data obtained from the second question was
analyzed using a derivative of Market Basket Analysis
(MBA), a model utilized in studying patterns of goods sales
(here they are drugs) focusing associations and sequences.
In general, Market Basket Analysis is utilized in business
management and marketing to understand how particular
items were bought in conjunction with other items. MBA is
one of the data mining models under SAS Enterprise Minor.
The term “market basket” means a basket of items
purchased in a transaction. The purpose of such analyses
typically is to find subsets of items that are purchased
together in many transactions [29].
We used a modified version of MBA to determine
sequences of drug-use initiation by suggesting that
individuals initiate use (equivalent to purchase) of specific
drugs from among a larger set of available drugs (equivalent
to market). Specifically, we drew from the overall sample
those adolescents who report ever having used a gateway
substance. We used SAS 9.3 to identify the most frequent
sequences of drug use initiation among those individuals by
ordering the respondents’ age of first use for each substance.
Analyses focused on the “confidence %” statistic,
which represents the probability, that event “Y” occurred
after event “X.” If 500 people abuse drug “X,” and then, in
a subsequent year, 125 of those people abuse drug “Y,” the
confidence for XY is 25%. For example, the sequence
“Alcohol  Cocaine” is assessed using a rule that identifies
all alcohol users, and then determines, how many initiated
cocaine use in a year subsequent to their initiation of alcohol
use.
4 Results
Of the 492,957 students who provided data on drug
use, 45.3% used at least one category of drugs in the past
year, and 44.8% of the total used non-prescription drugs in
the past year. But, only 34.4% of the total used nonprescription drugs alone and 10.4% used them
simultaneously with prescription drugs. Of the 48,227
twelfth-graders who provided data on drug use, 33,961
(70.4%) used non-prescription drugs and 25,652 (75.5%) of
non-prescription drug-users used only gateway drugs, while
22.1% used gateway drugs with prescription medications
and 2% used gateway drugs with hard drugs (heroin,
cocaine, and crack). Of the 12th-graders, 19.3% used alcohol
only; 8.4% used cigarettes only and 4.8% used marijuana
only (Table 1).
More males compared to females used prescription
and nonprescription drugs simultaneously. In addition, more
males compared to females used at least one category of
drugs, either prescription or non-prescription. Both of these
findings are unexpected differences (p<0.0001). Similarly,
more Whites compared to other races used prescription and
nonprescription drugs simultaneously. In addition, more
Whites compared to other races used at least one category of
drugs, either prescription or non-prescription. Both of these
findings are also unexpected differences (p<0.0001).
Drug
User Category
(In Grade 12)
Use Prescr.
Drugs
Don’t Use
Prescr. Drugs
Total
Use NonPrescription
Drugs
9,174
(19.0%)
26,070
(54.1%)
35,244
(73.1%)
Don’t Use
Non-Prescr
Drugs
104
(0.2%)
12,879
(26.7%)
12,983
(26.9%)
Total
9,278
(19.2%)
38,949
(80.8%)
48,227
(100.0%)
Table 1: Self-Reported Annual Use of Prescription and
Non-Prescription Drugs Among Indiana Adolescents in
Grade 12 During the Period 2007-2009.
Gateway drug use and the use of prescription and
over-the-counter (OTC) medications have strong
relationships (Figure 1). Also evident is that there are
always two groups of drugs representing two chains. The
first group contains alcohol, cigarettes, marijuana, cocaine,
and crack. The second group consists of psychostimulants,
CNS depressants, narcotics, and OTC drugs (Figure 2).
After adjusting for age, gender, and race, similar sequences
of using gateway drugs followed by hard drugs and
prescription drugs were observed (Figure 2). But analysis of
normative beliefs revealed that a majority of peers and
parents of adolescents do not pay attention to prevention of
tobacco, alcohol, prescription drug, and cocaine use,
although considerable attention is paid to marijuana use [1].
Figure 1: Relationships and Strength Between Use of
Alcohol, Cigarettes, and Marijuana as Gateway Drugs
and the Use of Psychostimulants, Narcotics, CNS
Depressants, or OTC Drugs Among Indiana Adolescents
(2007-2009) According to Market Basket Analysis.
Thickness of the Lines is Proportionate to Strength of
Association.
Figure 2: Sequence and Strength Between Use of NonPrescription Drugs (Alcohol, Cigarettes, Marijuana,
Cocaine, & Crack) and the Nonmedical Use of
Medications (Psychostimulants, Narcotics, CNS
Depressants, & OTC Drugs) Among Indiana
Adolescents (2007-2009) According to Market Basket
Analysis. Thickness of the Lines is Proportionate to
Strength of Association.
5 Discussion
Slightly less than half of Indiana adolescents use at
least one category of prescription or non-prescription drugs,
and almost 99% of these drug users report annual use of
non-prescription drugs, including alcohol, cigarettes, and
marijuana. This indicates that almost all prescription drug
users simultaneously use non-prescription drugs as well.
This pattern intensifies when 12th-graders are considered
because almost three quarters of these adolescents use some
kind of drug.
In general, males are more prone to drug use and
non-prescription drug use than females as males tend to
report combined use of gateway drugs with other drugs,
such as prescription drugs and hard drugs. The tendency of
males to experiment may be the reason for this trend.
Market Basket Analysis reveals that the gateway
theory is applicable to Indiana adolescents because many of
them initiate drug use with alcohol, tobacco, or marijuana or
with a combination of them followed by use of prescription
drugs. The majority of adolescents who use gateway drugs
start using psychostimulants non-medically, follow them
with CNS depressants, and then use prescription narcotics
and OTC drugs. This model proves that the gateway theory
is useful in explaining adolescent drug abuse. But many
parents and peers of adolescents do not pay attention to the
prevention of tobacco, alcohol, prescription drug, and
cocaine use, although considerable attention is paid to
marijuana use.
In 2002, Yamaguchi and Kandel [28] applied two
statistical models for analysis of drug use progression:
quasi-independence model for the analysis of events
sequence data [30] and the log linear model for analysis of
parametric events sequences. Our future studies will focus
on how the outputs of Market Basket Analysis can be
integrated with the models of Yamaguchi and Kandel.
6 Limitations
This is a self-administered anonymous survey on drug
use. The responses of younger adolescents may not be very
accurate. The percentage of missing data in some sections of
the questionnaire is somewhat high.
[3]
[4]
[5]
[6]
[7]
7 Conclusion
Of the 48,227 twelfth-graders who provided data
on their drug use, 70.4% use non-prescription drugs and
75.5% of those non-prescription drug-users abuse gateway
drugs only while 22.1% use gateway drugs with prescription
medications and 2% use gateway drugs with hard drugs.
The majority of adolescents start drug use with gateway
drugs followed by combining them with prescription drugs.
Males, Whites, and older adolescents are more likely to
report single-use of gateway drugs and combined use of
gateway drugs with other drugs. Market basket analysis in
data mining is found to be a useful technique in identifying
common substance-use initiation patterns.
8 Conflict of Interests Statement
[8]
[9]
[10]
[11]
This research is not fully or partially supported by
any funding source and authors have no conflict of interests.
[12]
9 Acknowledgement
[13]
The authors would like to thank Prof. Mohammad
Torabi and Dr. Ruth Gasman of Dept. of Applied Health
Science, Indiana University Bloomington for their help.
[14]
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