Carlos Blanco, M.D., Ph.D.
Jon Grant, M.D., J.D.
Nancy M. Petry, Ph.D.
H. Blair Simpson, M.D., Ph.D.
Analucia Alegria, B.S.
Shang-Min Liu, M.S.
Deborah Hasin, Ph.D.
Objective: This study presented nation-
ally representative data on the lifetime
prevalence, correlates, and comorbidity
of shoplifting among adults in the United
States.
Method: Data were derived from a large
national sample of the United States pop-
ulation. Face-to-face surveys of more than
43,000 adults ages 18 years and older re-
siding in households were conducted dur-
ing the 2001–2002 period. Diagnoses of
mood, anxiety, and drug disorders as well
as personality disorders were based on
the Alcohol Use Disorder and Associated
Disabilities Interview Schedule—DSM-IV
Version.
Results: The prevalence of lifetime shop-
lifting in the U.S. population was 11.3%.
Associations between shoplifting and all
antisocial behaviors were positive and sig-
nificant. Besides stealing, the behaviors
more strongly associated with shoplifting
were making money illegally and scam-
ming someone for money. Strong associa-
tions between shoplifting and all 12-
month and lifetime comorbid psychiatric
disorders were also found. The strongest
associations with shoplifting were with
disorders often associated with deficits in
impulse control, such as antisocial per-
sonality disorder, substance use disorders,
pathological gambling, and bipolar disor-
der. High rates of mental health service
use were also identified in this popula-
tion.
Conclusions: Shoplifting is a relatively
common behavior. A history of shoplifting
is associated with substantial rates of
comorbid disorders, psychosocial impair-
ment, and mental health service use.
Future research should identify the bio-
logical and environmental underpinnings
of shoplifting and develop effective
screening tools and interventions for indi-
viduals with shoplifting problems.
(Am J Psychiatry 2008; 165:905–913)
The National Association of Shoplifting Prevention
estimates that one in 11 people has shoplifted during his
or her lifetime and that men are as likely to shoplift as
women (1). In fact, more than $13 billion worth of goods
are stolen from retailers in the United States each year (2).
Shoplifting results in significant costs to the legal system
and commerce. Despite these costs, shoplifting has histor-
ically received relatively little attention from clinicians
and researchers. As such, our understanding of the basic
aspects of this behavior is incomplete.
Shoplifting and kleptomania are sometimes used syn-
onymously, yet there are important differences between
them. Shoplifting is a behavior defined by the theft of an
item from a store, regardless of motivation or desire for the
items (3). By contrast, kleptomania refers to a psychiatric
diagnosis characterized by recurrent failure to resist im-
pulses to steal objects that are not needed for personal use
or for their monetary value. Individuals with kleptomania
experience an increasing sense of tension immediately
before committing the theft and gratification or release at
the time of committing the theft. Furthermore, the steal-
ing is not committed to express anger or vengeance. Thus,
although shoplifting can be due to kleptomania, it can
also be simply criminal behavior or a manifestation of
conduct disorder, antisocial personality disorder, or bipo-
lar disorder, among others. More generally, the relation-
ship of shoplifting to other behaviors is poorly under-
stood, and the prevalence of psychiatric disorders among
people who shoplift is unknown.
Research on kleptomania suggests that this disorder is
associated with several domains of psychopathology,
including impulsivity, psychopathy, mood disorders (4–6),
and obsessive-compulsive spectrum disorders (7, 8),
although empirical data examining these associations is
sparse. Similarly, individuals with kleptomania are thought
to seek treatment only rarely because of social stigma (5, 9),
although they may seek treatment for other reasons (10).
However, given the differences between shoplifting and
kleptomania, the applicability of even the limited literature
on kleptomania to shoplifting is unknown. To date, to our
knowledge, no study has reported the rates of psychiatric
disorders or mental health service use among individuals
with a lifetime history of shoplifting.
906 Am J Psychiatry 165:7, July 2008
SHOPLIFTING IN THE UNITED STATES
906 Am J Psychiatry 165:7, July 2008
SHOPLIFTING IN THE UNITED STATES
TABLE 1. Sociodemographic Characteristics of Individuals With and Without a Lifetime History of Shoplifting in the
National Epidemiologic Survey on Alcohol and Related Conditions
Characteristic
Shoplifters (N=4,422) Nonshoplifters (N=37,516)
Odds Ratio 95% CI
% 95% CI % 95% CI
Sex
Men 59.30 57.55 to 61.03 46.35 45.68 to 47.03 1.69 1.56 to 1.82
Women 40.70 38.97 to 42.45 53.65 52.97 to 54.32 1.00 1.00 to 1.00
Race/ethnicity
White 77.52 74.89 to 79.94 70.14 66.73 to 73.34 1.00 1.00 to 1.00
Black 8.72 7.51 to 10.11 11.29 10.02 to 12.69 0.70 0.62 to 0.79
Asian 2.17 1.60 to 2.94 4.68 3.63 to 6.08 0.42 0.30 to 0.59
Native American 3.67 2.95 to 4.56 1.89 1.61 to 2.22 1.76 1.39 to 2.22
Hispanic 7.92 6.38 to 9.79 12.00 9.63 to 14.86 0.60 0.51 to 0.71
Nativity
Born in the United States 94.93 93.77 to 95.89 84.21 80.71 to 87.18 3.51 2.87 to 4.30
Born in a foreign country 5.07 4.11 to 6.23 15.79 12.82 to 19.29 1.00 1.00 to 1.00
Age (years)
18–29 30.27 28.53 to 32.07 20.85 20.06 to 21.67 1.00 1.00 to 1.00
30–44 37.51 35.7 to 39.35 29.95 29.24 to 30.67 0.86 0.78 to 0.96
45–64 27.89 26.32 to 29.71 31.40 30.73 to 32.08 0.61 0.55 to 0.69
65+ 4.24 3.63 to 4.95 17.79 17.05 to 18.56 0.16 0.14 to 0.20
Education
Less than high school 12.83 11.54 to 14.25 15.86 14.86 to 16.92 0.73 0.64 to 0.84
High school graduate 27.02 25.45 to 28.66 29.61 28.47 to 30.79 0.83 0.76 to 0.90
Some college or higher 60.15 58.12 to 62.14 54.53 53.25 to 55.79 1.00 1.00 to 1.00
Personal income ($)
0–19,999 43.95 41.90 to 46.03 47.66 46.47 to 48.86 1.00 1.00 to 1.00
20,000–34,999 22.57 21.01 to 24.20 22.63 21.87 to 23.40 1.08 0.98 to 1.20
35,000–69,999 24.09 22.54 to 25.71 21.72 20.93 to 22.54 1.20 1.09 to 1.33
70,000+ 9.39 8.17 to 10.78 7.99 7.26 to 8.78 1.28 1.11 to 1.47
Family income ($)
0–19,999 22.37 20.63 to 24.21 23.49 22.57 to 24.45 1.00 1.00 to 1.00
20,000–34,999 19.89 18.45 to 21.42 20.22 19.54 to 20.93 1.03 0.92 to 1.16
35,000–69,999 31.90 30.07 to 33.79 32.24 31.56 to 32.96 1.04 0.94 to 1.16
70,000+ 25.84 23.87 to 27.90 24.04 22.66 to 25.48 1.13 1.01 to 1.26
Marital status
Married/cohabiting 56.52 54.67 to 58.35 62.65 61.67 to 63.62 1.00 1.00 to 1.00
Widowed/separated/divorced 15.86 14.66 to 17.14 17.54 17.06 to 18.03 1.00 0.91 to 1.11
Never married 27.62 25.97 to 29.32 19.81 18.85 to 20.81 1.54 1.41 to 1.69
Urbanicity
Urban 81.87 78.19 to 85.06 79.95 76.46 to 83.04 1.00 1.00 to 1.00
Rural 18.13 14.94 to 21.81 20.05 16.96 to 23.54 0.88 0.76 to 1.02
Region
Northeast 18.50 13.31 to 25.12 19.86 13.82 to 27.69 0.64 0.50 to 0.81
Midwest 25.46 19.46 to 32.55 22.88 17.13 to 29.87 0.76 0.61 to 0.95
South 25.45 20.51 to 31.12 36.35 29.97 to 43.26 0.48 0.39 to 0.59
West 30.59 23.50 to 38.74 20.91 14.75 to 28.77 1.00 1.00 to 1.00
Insurance
Private 61.18 59.14 to 63.19 55.75 54.46 to 57.03 1.00 1.00 to 1.00
Public 16.95 15.60 to 18.40 25.83 24.87 to 26.82 0.60 0.54 to 0.66
No insurance 21.86 20.25 to 23.56 18.42 17.14 to 19.78 1.08 0.96 to 1.22
Persisted shoplifting after age 15
Yes 35.80 33.95 to 37.70
No 64.20 62.30 to 66.05
Family history of antisocial behavior 40.95 39.09 to 42.84 15.04 14.22 to 15.90 3.92 3.55 to 4.32
The purpose of this study was to fill these gaps in knowl-
edge. Specifically, with the National Epidemiologic Survey
on Alcohol and Related Conditions (NESARC), a nationally
representative sample of the adult population of the
United States, we sought to 1) examine the prevalence and
sociodemographic correlates of shoplifting in the general
population, 2) document the prevalence of other impul-
sive and antisocial behaviors in people who have shop-
lifted, 3) investigate the lifetime and 12-month prevalence
of psychiatric disorders associated with shoplifting and
the current levels of psychosocial functioning in several
domains, and 4) estimate lifetime and 12-month rates of
mental health treatment-seeking among individuals with
a lifetime history of shoplifting.
Method
Sample
The 2001–2002 NESARC is a nationally representative sample
of the adult population of the United States conducted by the
U.S. Census Bureau under the direction of the National Insti-
tute on Alcoholism and Alcohol Abuse, as described in detail
elsewhere (11, 12). The NESARC target population was the civil-
ian noninstitutionalized population, 18 years and older, resid-
ing in households and group quarters in the 50 states and the
District of Columbia. The final sample included 43,093 respon-
dents drawn from individual households and group quarters.
African Americans, Latinos, and young adults (ages 18 to 24
years) were oversampled. Data were adjusted to account for
oversampling and respondent and household nonresponse.
The overall survey response rate was 81%. The weighted data
were then adjusted with the 2000 decennial census to be repre-
sentative of the U.S. civilian population for a variety of sociode-
mographic variables.
All potential NESARC respondents were informed in writing
about the nature of the survey, the statistical uses of the survey
data, the voluntary aspect of their participation, and the federal
laws that rigorously provided for the strict confidentiality of the
identifiable survey information. The respondents consenting to
participate after receiving this information were interviewed. The
research protocol, including informed consent procedures, re-
ceived full ethical review and approval from the U.S. Census Bu-
reau and the U.S. Office of Management and Budget.
Interviewer Training
Interviews were conducted by approximately 1,800 professional
interviewers from the U.S. Census Bureau. Training was standard-
ized under the direction of the National Institute of Alcoholism and
Alcohol Abuse. For quality control purposes and to verify the accu-
racy of the interviewers’ performance, 2,657 respondents were re-
administered one to three sections of the NESARC interview to ver-
ify answers. These interviews also formed the basis of a test-retest
reliability study of NESARC measures (11).
Diagnostic Assessment
Sociodemographic measures included age, sex, race/ethnicity,
nativity, marital status, place of residence, and region of the coun-
try. Socioeconomic measures included education, insurance
type, and individual and family income.
All psychiatric diagnoses were made according to the DSM-IV
criteria with the National Institute of Alcoholism and Alcohol
Abuse Alcohol Use Disorder and Associated Disabilities Interview
Schedule—DSM-IV Version (AUDADIS-IV), a valid and reliable
fully structured diagnostic interview designed for use by profes-
sional interviewers who are not clinicians. AUDADIS-IV diag-
noses can be separated into five groups: 1) substance use disor-
ders (alcohol abuse/dependence, drug abuse/dependence, and
nicotine dependence), 2) mood disorders (major depressive dis-
order, dysthymia, and bipolar disorder), 3) anxiety disorders
(panic disorder, social anxiety disorder, specific phobia, and gen-
eralized anxiety disorder), 4) personality disorders (avoidant, de-
pendent, obsessive-compulsive, paranoid, schizoid, histrionic,
and antisocial personality disorders), and 5) other (conduct dis-
order and pathological gambling). Diagnoses of personality dis-
orders required long-term patterns of social and occupational
impairment and exclusion of substance-induced cases, as de-
tailed elsewhere (13). The test-retest reliability and validity of AU-
DADIS-IV measures of DSM-IV disorders is good to excellent (14–
17). Owing to concerns about the validity of psychotic diagnoses
in general population surveys as well as the length of the inter-
view, possible psychotic disorders were assessed by asking the re-
spondent if the respondent was ever told by a doctor or other
health professional that he or she had schizophrenia or a psy-
chotic disorder.
Embedded in the antisocial personality disorder section was
the following question: “In your entire life, did you ever shoplift?”
All NESARC participants were asked this question. Individuals
who answered affirmatively were defined in this article as having
a history of shoplifting. They were further asked, “Has this hap-
pened since you were 15?” Test-retest reliability of the entire anti-
social personality disorder section in the NESARC is 0.69 (18). Al-
though test-retest reliability of individual items is unavailable, we
computed Cronbach’s alpha for the antisocial personality disor-
der symptoms, which was 0.86, indicating excellent internal con-
sistency of the antisocial personality disorder section. This value
was unchanged when the shoplifting item was excluded, suggest-
ing high reliability for the item. Functioning was assessed with
the physical component summary and the social, emotional, and
mental health scores of the Short-Form-12v2, a reliable and valid
impairment measure in population surveys (19). Each Short-
Form-12v2 norm-based disability score is a continuous variable
with a mean of 50 in the general population, an SD of ±10, and a
range of 0–100. Lower scores indicate more disability. To assess
family history of antisocial behavior, individuals were also asked
whether any first- or second-degree relatives had engaged in an-
tisocial personality disorder symptoms, such as being cruel to
people or animals, destroying property, lying or conning people,
or being arrested.
To estimate the rates of mental health service use, separate
questions were asked for each major substance use, mood, and
anxiety disorder assessed in the NESARC. Respondents were clas-
sified as receiving treatment if they sought mental health treat-
ment from a counselor, therapist, doctor, psychologist, or an
emergency room; if they were hospitalized at least one night for
psychiatric reasons; or if they were prescribed medications to
treat psychiatric symptoms.
Statistical Analyses
Weighted percentages and means were computed to derive so-
ciodemographic and clinical characteristics of respondents with
and without a lifetime history of shoplifting. Standard errors and
95% confidence intervals (CIs) for all analyses were estimated by
using SUDAAN (20), a software package that uses Taylor series
linearization to adjust for the design effects of complex sample
surveys such as the NESARC. Because the combined SE of two
means (or percents) is always equal to or less than the sum of the
standard errors of those two means, we conservatively consider
that two CIs that do not overlap are significantly different from
one another (21). We consider significant odds ratios those whose
CI does not include 1. Two sets of logistic regressions examined
associations between shoplifting and lifetime and 12-month co-
morbid psychiatric disorders. The first set adjusted only for socio-
demographic characteristics that differed between individuals
with and without a lifetime history of shoplifting. The second set
further adjusted for the presence of other comorbid psychiatric
disorders to identify common and unique factors underlying the
associations of comorbid disorders with shoplifting.
To examine whether the correlates of shoplifting were different
among the individuals who shoplifted past childhood, all analy-
ses were repeated, restricting the group of shoplifters to those
who shoplifted after the age of 15. Similar analyses were con-
ducted excluding individuals with a diagnosis of antisocial per-
sonality disorder. Because these two sets of analyses resulted in a
nearly identical pattern of significant odds ratios to those re-
ported with the lifetime history of shoplifting and the inclusion of
individuals with antisocial personality disorder, only the results
associated with the lifetime history grouping and antisocial per-
sonality disorder are presented.
Results
Sociodemographic and Socioeconomic
Characteristics (Table 1)
The overall lifetime prevalence of shoplifting in the gen-
eral population was 11.3% (95% CI=10.6%–12.1%). The
odds of shoplifting were significantly higher in men than
in women. Native Americans had higher odds than whites,
although blacks, Hispanics, and Asian Americans had
lower odds of shoplifting than non-Hispanic whites. Being
U.S.-born, never married, or in the youngest cohort (ages
18–29) also increased the risk for shoplifting. Shoplifting
was significantly more common in individuals with at
least some college education, among those with individ-
ual incomes over $35,000 and family incomes over
$70,000, and among those living in the West, but less com-
mon among those with public insurance. Individuals with
a history of shoplifting were more likely than those with-
out a history of shoplifting to have a family history of anti-
social behaviors. In over one-third of the cases, shoplifting
persisted after age 15.
TABLE 2. Associated Antisocial Behaviors of Individuals With and Without a Lifetime History of Shoplifting in the National
Epidemiologic Survey on Alcohol and Related Conditions
Behavior
Shoplifters (N=4,422) Nonshoplifters (N=37,516)
Odds
Ratio 95% CI
% 95% CI % 95% CI
Cut class and leave without permission 50.43 48.40 to 52.45 18.30 17.63 to 18.98 4.54 4.15 to 4.97
Stay out late at night 54.15 52.44 to 55.85 22.16 21.32 to 23.03 4.15 3.79 to 4.54
Bully/push people 20.39 18.98 to 21.88 4.44 4.12 to 4.78 5.51 4.94 to 6.16
Run away from home overnight 17.92 16.44 to 19.50 3.51 3.26 to 3.78 6.00 5.29 to 6.80
Be absent from work/school a lot 22.93 21.33 to 24.63 4.85 4.55 to 5.17 5.83 5.24 to 6.49
Quit a job without knowing where to find
another 29.78 28.00 to 31.63 9.29 8.77 to 9.84 4.14 3.73 to 4.59
Quit a school program without knowing what to
do next 11.48 10.41 to 12.65 2.83 2.55 to 3.15 4.45 3.83 to 5.18
Travel around more than 1 month without plans 11.64 10.53 to 12.85 2.39 2.18 to 2.63 5.37 4.65 to 6.20
Have no regular place to live at least 1 month 11.18 9.95 to 12.53 1.69 1.51 to 1.89 7.32 6.28 to 8.53
Live with others at least 1 month 29.76 27.95 to 31.63 8.79 8.19 to 9.44 4.39 3.97 to 4.87
Lie a lot 21.96 20.36 to 23.64 3.17 2.94 to 3.42 8.59 7.57 to 9.76
Use a false or made-up name/alias 9.27 8.22 to 10.44 1.24 1.10 to 1.41 8.11 6.76 to 9.73
Scam/con someone for money 8.74 7.67 to 9.95 0.60 0.50 to 0.71 15.96 12.91 to 19.75
Do things that could have easily hurt you/others 42.55 40.58 to 44.55 10.51 9.71 to 11.36 6.31 5.74 to 6.93
Get three or more traffic tickets for reckless driv-
ing/causing accidents 21.10 19.47 to 22.83 7.10 6.54 to 7.70 3.50 3.13 to 3.92
Have driver’s license suspended/revoked 18.94 17.51 to 20.47 6.37 5.89 to 6.88 3.44 3.06 to 3.87
Start a fire on purpose 5.80 4.95 to 6.80 0.53 0.44 to 0.65 11.48 8.82 to 14.96
Destroy others’ property 19.61 18.05 to 21.27 1.71 1.54 to 1.91 13.98 12.10 to 16.15
Fail to pay off your debts 14.49 13.19 to 15.88 2.86 2.60 to 3.14 5.76 5.01 to 6.62
Steal anything from others 48.94 46.97 to 50.91 3.91 3.59 to 4.26 23.56 21.01 to 26.42
Forge someone’s signature 9.34 8.30 to 10.50 1.24 1.09 to 1.40 8.24 6.90 to 9.84
Rob/mug someone or snatch a purse 1.53 1.18 to 1.97 0.14 0.10 to 0.21 10.76 6.94 to 16.68
Make money illegally 15.59 14.22 to 17.07 1.14 0.99 to 1.31 16.03 13.34 to 19.26
Force someone to have sex 0.41 0.26 to 0.66 0.10 0.07 to 0.16 3.96 2.06 to 7.59
Get into lots of fights that you started 10.31 9.13 to 11.63 1.86 1.68 to 2.06 6.06 5.14 to 7.16
Get into a fight that came to swapping blows
with others 18.77 17.45 to 20.17 5.09 4.70 to 5.51 4.31 3.81 to 4.87
Use a weapon in a fight 9.67 8.57 to 10.89 1.80 1.61 to 2.00 5.86 4.92 to 6.97
Hit someone so hard that you injure them 20.37 18.94 to 21.87 4.20 3.86 to 4.56 5.83 5.17 to 6.58
Harass/threaten/blackmail someone 8.16 7.24 to 9.19 0.91 0.76 to 1.07 9.73 7.90 to 11.98
Physically hurt others on purpose 18.08 16.62 to 19.65 3.41 3.12 to 3.72 6.26 5.46 to 7.16
Hurt an animal on purpose 7.53 6.60 to 8.56 1.10 0.96 to 1.26 7.32 6.01 to 8.90
Associated Antisocial Behaviors (Table 2)
The prevalence of all antisocial behaviors was higher
among individuals with a history of shoplifting than
among those with no self-reported history of shoplifting.
For both groups, the most common behavior was staying
out at night against parental advice, the prevalence of
which was 54.15% (95% CI=52.44%–55.85%) among indi-
viduals with a history of shoplifting versus 22.16% (CI=
21.32%–23.03%) among those with no history of shoplift-
ing. Besides stealing, the behaviors more strongly associ-
ated with shoplifting, as measured by the odds ratio, were
making money illegally (odds ratio=16.03, 95% CI=13.34–
19.26) and scamming somebody for money (odds ratio=
15.96, 95% CI=12.91–19.75).
TABLE 3. Lifetime Psychiatric Comorbidity of Individuals With and Without a Lifetime History of Shoplifting
Comorbid Psychiatric Disorder
Shoplifters (N=4,422) Nonshoplifters
(N=37,516) Sociodemographic
Characteristics
Sociodemographic
Characteristics and Other
Psychiatric Disorders
% SE % SE
Adjusted
Odds
Ratioa 95% CI
Adjusted
Odds
Ratiob 95% CI
Any psychiatric diagnosis 89.30 0.57 49.50 0.88 5.61 4.92 to 6.39 — —
Any axis I diagnosis 87.14 0.59 47.09 0.91 5.02 4.49 to 5.61 4.12 3.68 to 4.60
Any substance use disorder 76.71 0.79 33.76 0.80 4.33 3.93 to 4.77 3.67 3.32 to 4.06
Nicotine dependence 39.48 1.00 15.16 0.45 2.57 2.34 to 2.84 1.35 1.21 to 1.52
Any alcohol use disorder 65.18 0.93 25.94 0.71 3.67 3.35 to 4.02 2.18 1.97 to 2.41
Alcohol abuse 29.76 0.93 16.34 0.51 1.69 1.52 to 1.88 1.45 1.29 to 1.63
Alcohol dependence 35.42 0.93 9.60 0.29 3.08 2.79 to 3.41 1.60 1.42 to 1.80
Any drug use disorder 38.44 0.98 6.83 0.23 5.02 4.54 to 5.55 2.92 2.62 to 3.27
Drug abuse 25.44 0.78 5.54 0.20 3.52 3.16 to 3.92 2.19 1.95 to 2.46
Drug dependence 13.00 0.61 1.28 0.08 6.00 4.99 to 7.21 2.75 2.28 to 3.32
Any mood disorder 34.92 0.85 16.28 0.34 2.06 1.89 to 2.25 1.17 1.05 to 1.29
Major depressive disorder 21.94 0.73 12.41 0.29 1.59 1.45 to 1.75 1.09 0.97 to 1.23
Bipolar disorder 11.85 0.59 3.24 0.13 2.37 2.04 to 2.75 1.12 0.94 to 1.34
Dysthymia 6.42 0.42 2.84 0.11 1.80 1.52 to 2.12 1.14 0.95 to 1.38
Any anxiety disorder 30.32 0.87 15.96 0.44 1.80 1.64 to 1.99 0.99 0.89 to 1.10
Panic disorder 11.14 0.55 4.63 0.16 1.98 1.72 to 2.28 1.07 0.90 to 1.28
Social phobia 11.11 0.60 4.33 0.19 1.91 1.65 to 2.22 1.06 0.89 to 1.26
Specific phobia 16.16 0.76 8.77 0.30 1.63 1.43 to 1.85 0.97 0.85 to 1.12
Generalized anxiety disorder 8.63 0.56 3.68 0.17 1.80 1.50 to 2.16 0.97 0.79 to 1.19
Conduct disorder 4.55 0.37 0.63 0.06 5.37 4.00 to 7.16 6.28 4.64 to 8.49
Pathological gambling 1.42 0.22 0.31 0.04 2.97 1.94 to 4.54 1.25 0.78 to 2.01
Psychotic disorder 0.83 0.17 0.23 0.03 2.93 1.76 to 4.89 1.22 0.70 to 2.14
Any personality disorder 41.00 0.93 11.85 0.30 3.56 3.25 to 3.90 2.57 2.32 to 2.85
Avoidant 6.08 0.48 1.94 0.09 1.98 1.63 to 2.41 1.19 0.92 to 1.55
Dependent 1.72 0.28 0.34 0.04 3.66 2.34 to 5.72 1.67 0.96 to 2.90
Obsessive-compulsive 17.43 0.74 6.89 0.21 1.97 1.74 to 2.22 1.26 1.08 to 1.47
Paranoid 11.09 0.61 3.67 0.14 2.07 1.77 to 2.43 1.00 0.79 to 1.27
Schizoid 7.43 0.47 2.66 0.12 1.97 1.66 to 2.34 1.06 0.85 to 1.31
Antisocial 21.97 0.73 1.39 0.09 11.98 10.07 to 14.25 7.56 6.27 to 9.12
Histrionic 6.38 0.51 1.30 0.07 2.97 2.40 to 3.69 1.56 1.19 to 2.04
TABLE 4. Twelve-Month Psychiatric Comorbidity of Individuals With and Without a Lifetime History of Shoplifting
Comorbid Psychiatric Disorder Shoplifters
(N=4,422) Nonshoplifters
(N=37,516) Sociodemographic
Characteristics
Sociodemographic
Characteristics and Other
Psychiatric Disorders
% SE % SE
Adjusted
Odds
Ratioa 95% CI
Adjusted
Odds
Ratiob 95% CI
Any axis I diagnosis 55.59 0.92 26.34 0.58 2.40 2.20 to 2.62 1.90 1.73 to 2.09
Any substance use disorder 25.29 0.95 7.32 0.43 2.65 2.42 to 2.91 2.28 2.07 to 2.52
Nicotine dependence 29.16 0.96 10.81 0.35 2.33 2.10 to 2.59 1.69 1.51 to 1.90
Any alcohol use disorder 22.25 0.78 6.70 0.22 2.52 2.24 to 2.84 1.87 1.65 to 2.12
Alcohol abuse 10.34 0.57 3.94 0.17 1.90 1.63 to 2.21 1.74 1.48 to 2.05
Alcohol dependence 11.91 0.64 2.76 0.12 2.79 2.30 to 3.30 1.67 1.38 to 2.01
Any drug use disorder 8.39 0.54 1.20 0.07 4.06 3.37 to 4.91 2.24 1.81 to 2.77
Drug abuse 6.60 0.49 0.92 0.06 4.18 3.40 to 5.13 2.49 1.98 to 3.12
Drug dependence 2.83 0.27 0.35 0.04 4.07 2.92 to 5.66 1.54 1.09 to 2.17
Any mood disorder 13.67 0.62 6.32 0.17 1.75 1.54 to 1.99 1.14 0.98 to 1.32
Major depressive disorder 9.46 0.53 5.07 0.16 1.48 1.28 to 1.72 1.03 0.87 to 1.22
Bipolar disorder 3.47 0.32 0.82 0.06 2.55 1.96 to 3.33 1.40 1.06 to 1.86
Dysthymia 2.59 0.27 1.21 0.07 1.76 1.36 to 2.27 1.09 0.82 to 1.44
Any anxiety disorder 19.50 0.78 10.32 0.33 1.61 1.43 to 1.82 0.98 0.86 to 1.12
Panic disorder 5.10 0.37 1.85 0.09 2.04 1.70 to 2.46 1.19 0.95 to 1.49
Social phobia 5.89 0.43 2.43 0.12 1.77 1.46 to 2.16 0.99 0.80 to 1.23
Specific phobia 12.16 0.69 6.68 0.26 1.52 1.30 to 1.77 1.02 0.86 to 1.20
Generalized anxiety disorder 4.38 0.40 1.81 0.10 1.77 1.40 to 2.26 0.89 0.67 to 1.18
Pathological gambling 0.56 0.13 0.11 0.02 3.50 1.97 to 6.22 1.77 0.92 to 3.41
Psychotic disorder 0.96 0.19 0.26 0.03 2.76 1.70 to 4.48 1.23 0.75 to 2.04
Mean SE Mean SE Wald F
(df=1, 65)c p Wald F
(df=1, 65)c p
Short-Form 12
Physical component summary
scale 51.69 0.18 50.43 0.12 0.25 0.62 4.88 0.04
Mental component summary
scale 50.09 0.18 52.70 0.08 114.91 <0.0001 2.05 0.16
Social functioning scale 50.71 0.20 51.92 0.07 46.75 <0.0001 0.05 0.82
Role emotional scale 50.08 0.18 51.12 0.09 45.85 <0.0001 0.03 0.87
Mental health scale 49.88 0.19 52.45 0.09 90.99 <0.0001 0.08 0.77
Lifetime and Current Comorbidity (Table 3 and
Table 4)
The vast majority of individuals with a lifetime history of
shoplifting (89.30%, CI=87.20%–89.60%) had a lifetime
history of at least one psychiatric diagnosis, compared to
49.50% in nonshoplifters. Shoplifters were significantly
more likely than nonshoplifters to have a lifetime axis I
disorder (87.14%, CI=85.91%–88.28%, versus 47.09%, CI=
45.29%–48.91%) and a personality disorder (41.00%, CI=
39.15%–42.88%, versus 11.85%, CI=11.26%–12.45%). In
both groups, the most prevalent disorders were nicotine
dependence and alcohol use disorders, which carried an
increased risk of 2.57 and 3.67, respectively, among shop-
lifters compared with nonshoplifters, after adjustment for
sociodemographic characteristics. Although all psychiat-
ric conditions were significantly associated with shoplift-
ing, the strongest associations were found for antisocial
personality disorder (odds ratio=11.98, CI=10.07–14.25)
and substance use disorders (odds ratio=4.33, CI=3.93–
4.77). Other disorders often associated with deficits in im-
pulse control, such as pathological gambling (odds ratio=
2.97, CI=1.94–4.54) and bipolar disorder (odds ratio=2.37,
CI=2.04–2.75), were also strongly associated with shoplift-
ing, whereas association with mood and anxiety disorders,
although also significant, was of smaller magnitude (odds
ratio <2.0). A similar pattern was observed when we exam-
ined current, rather than lifetime, diagnoses of axis I disor-
ders. During adjustment for the presence of other psychi-
atric disorders, associations with lifetime conduct
disorder, antisocial personality disorder, obsessive-com-
pulsive personality and histrionic disorders, and lifetime
and 12-month substance use disorders remained positive
and statistically significant. The lifetime prevalence of
shoplifting was also high, with rates often above 25%,
among those with psychiatric disorders (Figure 1).
Individuals with a lifetime history of shoplifting had
higher scores on the physical component summary score
but lower scores on the social, emotional, and mental
health scale of the Short-Form Health Survey—12. When
we adjusted for the presence of other psychiatric disor-
ders, the scores on the Short-Form Health Survey—12 so-
cial, emotional, and mental subscales lost their statistical
significance, whereas the physical component summary
score became significant.
TABLE 5. Treatment Correlates of Individuals With a Lifetime History of Shoplifting in the National Epidemiologic Survey
on Alcohol and Related Conditions
Treatment
Shoplifters (N=4,422) Nonshoplifters (N=37,516)
Odds
Ratio 95% CI
% 95% CI % 95% CI
Any mental health treatment (lifetime) 37.41 35.63 to 39.22 16.81 16.01 to 17.64 2.96 2.70 to 3.24
Any mental health treatment (last 12 months) 3.69 3.14 to 4.32 0.69 0.58 to 0.82 5.52 4.34 to 7.02
Any psychiatric hospitalization (lifetime) 10.42 9.37 to 11.58 3.14 2.91 to 3.39 3.59 3.12 to 4.13
Any psychiatric hospitalization (last 12 months) 1.08 0.77 to 1.51 0.16 0.12 to 0.22 6.88 4.50 to 10.51
Any emergency room visit (lifetime) 12.31 11.17 to 13.54 4.15 3.83 to 4.48 3.24 2.85 to 3.70
Any emergency room visit (last 12 months) 0.96 0.67 to 1.38 0.11 0.08 to 0.17 8.68 5.21 to 14.46
Any prescribed psychotropic medication (lifetime) 21.27 19.61 to 23.02 10.94 10.27 to 11.64 2.20 1.98 to 2.45
Outpatient (lifetime) 32.57 30.74 to 34.45 14.23 13.55 to 14.95 2.91 2.60 to 53.20
Outpatient (last 12 months) 3.01 2.50 to 3.63 0.56 0.47 to 0.68 5.48 4.19 to 7.16
Inpatient (lifetime) 14.09 12.88 to 15.40 3.75 3.48 to 4.05 4.21 3.71 to 4.77
Inpatient (last 12 months) 1.92 1.52 to 2.43 0.36 0.28 to 0.45 5.47 3.97 to 7.54
History of Psychiatric Treatment (Table 5)
Lifetime rates of treatment seeking for psychiatric disor-
ders were significantly higher among shoplifters than
nonshoplifters across all treatment settings and regardless
of whether lifetime or past year timeframe was consid-
ered. Over a third of shoplifters had a lifetime history of
mental health treatment, compared with only 16.81% of
nonshoplifters. Any psychiatric hospitalization, emer-
gency room visit, and even past-12-month outpatient or
inpatient psychiatric treatment rate was five or more
times higher among shoplifters than nonshoplifters.
Additional Analyses
To examine the impact of age at shoplifting on our re-
sults, we examined the subsample of individuals with a
history of shoplifting after age 15. The associations with
other antisocial behaviors and psychiatric disorders re-
mained significant and of similar magnitude when we re-
stricted the analyses to those who shoplifted after age 15.
Similarly, exclusion of individuals with a diagnosis of anti-
social personality disorder did not alter the direction or
strength of the findings (results available upon request
from the first author).
Discussion
To our knowledge, this is the first national study to re-
port on rates of shoplifting in the United States. We found
that a lifetime history of shoplifting was common and as-
sociated with high rates of other antisocial behaviors, life-
time and current psychiatric disorders, significant de-
creases in levels of psychosocial functioning, and elevated
use of mental health services.
Our study found that the lifetime prevalence of shoplift-
ing is approximately 10% in the U.S. population, lower
than estimates in some surveys of adolescents (22, 23) but
similar to other recent national estimates in the adult pop-
ulation (1, 2). Failure to use nationally representative sam-
ples and validated instruments may have resulted in in-
flated estimates in the adolescent surveys (22, 23).
Alternatively, recall bias in the adult surveys may have led
to underestimating of past behaviors. The NESARC esti-
mate may represent a lower boundary of the true preva-
lence of shoplifting.
Shoplifting occurred across all sociodemographic
strata. However, it was more common among those with
higher education and income, suggesting that financial
considerations are unlikely to be the main motivator for
shoplifting in most cases. It was also more common
among Native Americans and non-Hispanic whites, possi-
bly indicating a racial/cultural dimension not previously
documented.
To date, to our knowledge, there are no published re-
ports of the psychopathology associated with shoplifting.
We found that shoplifting was associated with a broad
range of antisocial behaviors (many of which can also be
understood as a manifestation of impulsivity) and, in fact,
about one-quarter of individuals with a lifetime history of
shoplifting met criteria for antisocial personality disorder.
However, removing individuals with antisocial personality
disorder from the sample and reanalyzing the data did not
alter the direction or strength of our findings, indicating
our results were not solely driven by features associated
with antisocial personality disorder. Shoplifting was also
more common among men and among individuals with
other disorders associated with impaired impulse control,
such as substance use disorders, bipolar disorder, and
pathological gambling, although those associations were
weakened after adjustment for the presence of other co-
morbid psychiatric disorders. Overall, and converging
with recent findings in alcohol (24) and drug use disorders
(25), our comorbidity analyses suggest that although a
lifetime history of shoplifting is associated with a general
vulnerability to psychopathology, that vulnerability is in-
creased for certain disorders. In particular, our findings
are most consistent with the understanding of shoplifting
as a behavioral manifestation of impaired impulse control
and possibly as a symptom of a broader impaired control
syndrome with an underlying common factor. Future
studies should attempt to delineate the potential bound-
aries of this syndrome, the phenomenological similarities
and genetic overlap of its manifestations, and the unique
factors that determine the presence of specific behavioral
manifestations in each individual and to identify possible
common treatment approaches to behaviors associated
with impaired impulse control. Previous work by our
group and others has identified the similarities and shared
genetics of pathological gambling and substance use dis-
orders (26–28) and their response to similar treatments
(29, 30). This strategy could easily be extended to capture
the broader range of behaviors that might encompass this
syndrome. Furthermore, shoplifting often occurs at an
earlier age than other impulsive behaviors and may serve
as a marker to identify individuals at risk for impulse con-
trol disorders.
The NESARC did not collect data on obsessive-compul-
sive disorder, but it did collect data on obsessive-compul-
sive personality disorder. Although the odds ratios of ob-
sessive-compulsive personality disorder were elevated
among individuals with a history of shoplifting compared
to nonshoplifters, it was not as strongly associated as anti-
social personality disorder or even histrionic personality
disorder. Similarly, although the association with bipolar
disorder was high, the association of shoplifting with major
depressive disorder and dysthymia was substantially
weaker, suggesting that shoplifting is unlikely to represent
a behavioral manifestation of a broader affective spectrum.
Our study found that although about two-thirds of the
cases of shoplifting occur before age 15, over a third of the
cases persisted after that age, representing 4% of the adult
population. Thus, although in the majority of cases, shop-
lifting has a limited time course, a substantial proportion
of individuals engage in this behavior during their late ad-
olescence or adulthood. A lifetime history of shoplifting
appears to be a more important predictor of psychopa-
thology than the age at which shoplifting took place.
Our study also identified higher rates among those with
a history of shoplifting of lifetime and past-year use of psy-
chiatric treatment across a broad range of service settings.
Participants in the NESARC study were not specifically
asked whether they sought treatment for shoplifting but if
they sought treatment for any DSM-IV axis I disorder. To
the extent that prior reports on kleptomania and other im-
pulse control disorders (5, 10, 31) apply to shoplifting per
se, prior research suggests that very few individuals seek
treatment for shoplifting, and when they seek treatment
for other reasons, they are rarely asked about their history
of shoplifting. In conjunction with their high rates of co-
morbidity, the high rates of treatment use found in our
study by individuals with a lifetime history of shoplifting
are probably best understood as an indicator of the overall
severity of their psychopathology. The high rates of mental
health service use present opportunities for clinicians to
identify individuals with shoplifting problems and provide
specific interventions in this regard.
Our study has the limitations common to most large-
scale surveys. First, the NESARC did not examine the reli-
ability of individual items. However, the antisocial person-
ality disorder module of the AUDADIS, which contained
the shoplifting questions, had a kappa=0.67, which com-
pares favorably with other standardized assessments of
antisocial personality disorder (18). Furthermore, the reli-
ability of the antisocial personality disorder module, as
measured by Cronbach’s alpha, is 0.86 and does not change
whether or not the shoplifting questions are included in
the calculation, supporting the reliability of the shoplifting
questions. Second, because the NESARC sample included
only civilian households and group quarters populations,
information was unavailable on individuals in prison, who
may have had higher rates of shoplifting. Third, the assess-
ment of shoplifting was limited to a few questions and did
not include information about the frequency or motivation
for shoplifting, leaving open the possibility that the behav-
ior occurred only once in the individuals’ lifetime. Even
with this broad definition, the results of the study suggest
that a lifetime history of shoplifting is strongly associated
with high rates of psychopathology and treatment seeking.
Future epidemiological studies may benefit from the inclu-
sion of additional questions that may better delineate the
epidemiology of shoplifting and examine the similarities
and differences of shoplifting and kleptomania in the com-
munity. Fourth, this wave of the NESARC did not include
assessment of eating disorders or borderline personality
disorder, both of which have been associated with a history
of shoplifting (32).
Despite these limitations, the NESARC constitutes the
first nationally representative survey to date to include in-
formation on shoplifting. Our results suggest that shoplift-
ing is a relatively common behavior and it is associated
with substantial rates of psychiatric disorders and psycho-
social impairment. High rates of mental health service use
were identified in this population. Future research should
identify the biological and environmental underpinnings
of shoplifting and develop effective screening tools and in-
terventions for individuals with shoplifting problems.
Received Oct. 24, 2007; revision received Jan. 6, 2008; accepted
Jan. 14, 2008 (doi: 10.1176/appi.ajp.2008.07101660). From the New
York State Psychiatric Institute/Department of Psychiatry, College of
Physicians and Surgeons of Columbia University; the Department of
Psychiatry, University of Minnesota, Minneapolis; and the Depart-
ment of Psychiatry, University of Connecticut Health Center, Farming-
ton, Conn. Address correspondence and reprint requests to Dr.
Blanco, New York State Psychiatric Institute, 1051 Riverside Dr., Box
69, New York, NY 10032; cb255@columbia.edu (e-mail).
Supported by NIH grants DA-019606 and DA-020783 (to Dr. Blanco)
and AA-014223 (to Dr. Hasin) and the New York State Psychiatric In-
stitute (to Drs. Blanco, Hasin, and Simpson). The NESARC was funded
by the National Institute on Alcoholism and Alcohol Abuse, with sup-
plemental support from the National Institute on Drug Abuse.
Dr. Blanco reports support from Pfizer, Somaxon, and GlaxoSmith-
Kline. Dr. Grant reports support from Forest, Somaxon, and Glaxo-
SmithKline. Dr. Simpson is a member of the scientific advisory board
for Jazz Pharmaceuticals and has been donated medication for a
study from Janssen. The remaining authors report no competing in-
terests.
References
1. National Association of Shoplifting Prevention: www.
shopliftingprevention.org
2. Hollinger R, Adams A: 2006 National Retail Survey Final Re-
port. Gainesville, Fla., University of Florida, 2007
3. Merriam-Webster Incorporated: Merriam-Webster Online Dic-
tionary. http://m-w.com
4. McElroy SL, Pope HG Jr, Keck PE Jr, Hudson JI, Phillips KA, Stra-
kowski SM: Are impulse-control disorders related to bipolar
disorder? Compr Psychiatry 1996; 37:229–240
5. Baylé FJ, Caci H, Millet B, Richa S, Olié JP: Psychopathology and
comorbidity of psychiatric disorders in patients with kleptoma-
nia. Am J Psychiatry 2003; 160:1509–1513
6. McElroy SL, Pope HG Jr, Hudson JI, Keck PE Jr, White KL: Klepto-
mania: a report of 20 cases. Am J Psychiatry 1991; 148:652–
657
7. Bienvenu OJ, Samuels JF, Riddle MA, Hoehn-Saric R, Liang KY,
Cullen BA, Grados MA, Nestadt G: The relationship of obsessive-
compulsive disorder to possible spectrum disorders: results
from a family study. Biol Psychiatry 2000; 48:287–293
8. Hollander E: Obsessive-Compulsive-Related Disorders. Wash-
ington, DC, American Psychiatric Press, 1993
9. Grant J: Kleptomania, in Clinical Manual of Impulse Control
Disorders. Edited by Hollander ES. Washington, DC, American
Psychiatric Publishing, 2005, pp 175–201
10. Grant JE, Levine L, Kim D, Potenza MN: Impulse control disor-
ders in adult psychiatric inpatients. Am J Psychiatry 2005; 162:
2184–2188
11. Grant B, Moore TC, Shepard J, Kaplan K: Source and Accuracy
Statement: Wave 1: National Epidemiologic Survey on Alcohol
and Related Conditions (NESARC). Bethesda, Md, National Insti-
tute on Alcohol Abuse and Alcoholism, 2003
12. Grant BF, Stinson FS, Dawson DA, Chou SP, Dufour MC, Comp-
ton W, Pickering RP, Kaplan K: Prevalence and co-occurrence of
substance use disorders and independent mood and anxiety
disorders: results from the National Epidemiologic Survey on
Alcohol and Related Conditions. Arch Gen Psychiatry 2004; 61:
807–816
13. Grant BF, Hasin DS, Stinson FS, Dawson DA, Chou SP, Ruan WJ,
Pickering RP: Prevalence, correlates, and disability of personal-
ity disorders in the United States: results from the National Ep-
idemiologic Survey on Alcohol and Related Conditions. J Clin
Psychiatry 2004; 65:948–958
14. Cottler LB, Grant BF, Blaine J, Mavreas V, Pull C, Hasin D, Comp-
ton WM, Rubio-Stipec M, Mager D: Concordance of DSM-IV al-
cohol and drug use disorder criteria and diagnoses as mea-
sured by AUDADIS-ADR, CIDI and SCAN. Drug Alcohol Depend
1997; 47:195–205
15. Grant BF, Dawson DA, Stinson FS, Chou PS, Kay W, Pickering R:
The Alcohol Use Disorder and Associated Disabilities Interview
Schedule—IV (AUDADIS-IV): reliability of alcohol consumption,
tobacco use, family history of depression and psychiatric diag-
nostic modules in a general population sample. Drug Alcohol
Depend 2003; 71:7–16
16. Canino G, Bravo M, Ramirez R, Febo VE, Rubio-Stipec M,
Fernandez RL, Hasin D: The Spanish Alcohol Use Disorder and
Associated Disabilities Interview Schedule (AUDADIS): reliabil-
ity and concordance with clinical diagnoses in a Hispanic pop-
ulation. J Stud Alcohol 1999; 60:790–799
17. Grant BF, Harford TC, Dawson DA, Chou PS, Pickering RP: The
Alcohol Use Disorder and Associated Disabilities Interview
Schedule (AUDADIS): reliability of alcohol and drug modules in
a general population sample. Drug Alcohol Depend 1995; 39:
37–44
18. Grant BF, Dawson DA, Stinson FS, Chou PS, Kay W, Pickering R:
The Alcohol Use Disorder and Associated Disabilities Interview
Schedule—IV (AUDADIS-IV): reliability of alcohol consumption,
tobacco use, family history of depression and psychiatric diag-
nostic modules in a general population sample. Drug Alcohol
Depend 2003; 71:7–16
19. Ware JE, Kosinski M, Turner-Bowker DM, Gandek B: How to
Score Version 2 of the SF-12 Health Survey. Lincoln, RI, Quality
Metrics, 2002
20. Research Triangle Institute: Software for Survey Data Analysis
(SUDAAN), Version 9.0. Research Triangle Park, NC, Research
Triangle Institute, 2004
21. Agresti A: Categorical Data Analysis, 2nd ed. Hoboken, NJ, John
Wiley & Sons, 2002
22. Kivivuori J: Delinquent phases: the case of temporally intensi-
fied shoplifting behaviour. Br J Criminology 1998; 38:663–680
23. Josephson Institute: The Ethics of American Youth. http://
www.josephsoninstitute.org/reportcard/data-tables.html
24. Hasin DS, Stinson FS, Ogburn E, Grant BF: Prevalence, corre-
lates, disability, and comorbidity of DSM-IV alcohol abuse and
dependence in the United States: results from the National Ep-
idemiologic Survey on Alcohol and Related Conditions. Arch
Gen Psychiatry 2007; 64:830–842
25. Compton WM, Thomas YF, Stinson FS, Grant BF: Prevalence,
correlates, disability, and comorbidity of DSM-IV drug abuse
and dependence in the United States: results from the Na-
tional Epidemiologic Survey on Alcohol and Related Condi-
tions. Arch Gen Psychiatry 2007; 64:566–576
26. Moreyra P, Ibanez A, Liebowitz MR, Saiz-Ruiz J, Blanco C: Patho-
logical gambling: addiction or obsession? Psychiatr Ann 2002;
32:161–166
27. Petry NM: How treatments for pathological gambling can be
informed by treatments for substance use disorders. Exp Clin
Psychopharmacol 2002; 10:184–192
28. Slutske WS, Eisen S, True WR, Lyons MJ, Goldberg J, Tsuang M:
Common genetic vulnerability for pathological gambling and
alcohol dependence in men. Arch Gen Psychiatry 2000; 57:
666–673
29. Grant JE, Potenza MN, Hollander E, Cunningham-Williams R,
Nurminen T, Smits G, Kallio A: Multicenter investigation of the
opioid antagonist nalmefene in the treatment of pathological
gambling. Am J Psychiatry 2006; 163:303–312
30. Petry NM, Ammerman Y, Bohl J, Doersch A, Gay H, Kadden R,
Molina C, Steinberg K: Cognitive-behavioral therapy for patho-
logical gamblers. J Consult Clin Psychol 2006; 74:555–567
31. Grant JE: Outcome study of kleptomania patients treated with
naltrexone: a chart review. Clin Neuropharmacol 2005; 28:11–
14
32. Mitchell JE, Fletcher L, Gibeau L, Pyle RL, Eckert E: Shoplifting in
bulimia nervosa. Compr Psychiatry 1992; 33:342–345