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Problem gambling among ethnic minorities: results from an epidemiological study



A few studies have examined gambling behavior and problem gambling among minorities and reported higher rates of both participation and gambling problems among particular minority groups in comparison to Whites who gamble. The present study utilized a representative, epidemiological sample of adults in New Jersey to explore gambling behavior, gambling problem severity, substance use, problem behavior, and mental health issues among minorities. Univariate analyses were conducted, comparing Whites (n = 1341) to respondents who identified as Hispanic (n = 394), Black (n = 261), or Asian/other (n = 177). Overall, the highest proportion of Hispanics were high-risk problem gamblers. Hispanic participants were also significantly more likely than other groups to use and abuse substances and to report mental health problems in the past month, behavioral addictions, and/or suicidal ideation in the past year. Primary predictors of White high risk problem gamblers were being young and male with friends or family who gambled, fair to poor health status, substance use, gambling once a week or more both online and in land-based venues, and engaging in a number of gambling activities. In contrast, gender was not a predictor of minority high risk problem gamblers, who were characterized primarily by having friends or family who gambled, gambling online only, having a behavioral addiction and playing instant scratch-offs and gaming machines. Implications for research and practice are discussed.
Problem gambling amongethnic
minorities: results froman epidemiological
Kyle R. Caler, Jose Ricardo Vargas Garcia and Lia Nower*
Studies have consistently reported high rates of problem gambling among racial and eth-
nic minorities compared to Whites, though findings differ by geographic location and
socioeconomic status: ([Native American] Volberg and Abbott 1997; Zitzow 1996a, b;
[Asian] (Marshall etal. 2009; Petry etal. 2003; Toyama etal. 2014); [Hispanic or Latino]
Barry et al. 2011a; Welte etal. 2001; [Black or African American] Barnes etal. 2009;
Barry etal. 2011b; Welte etal. 2008).
A majority of studies focused on ethnicity investigated rates of gambling and prob-
lem gambling among Blacks, including African Americans. Results of a large nationally-
representative study found that Blacks had twice the rate (2.2%) of disordered gambling
compared to Whites and lower scores on general health measures; they were also more
likely to be women in the lowest income brackets (Alegria etal. 2009). Similar findings
A few studies have examined gambling behavior and problem gambling among
minorities and reported higher rates of both participation and gambling problems
among particular minority groups in comparison to Whites who gamble. The pre-
sent study utilized a representative, epidemiological sample of adults in New Jersey
to explore gambling behavior, gambling problem severity, substance use, problem
behavior, and mental health issues among minorities. Univariate analyses were
conducted, comparing Whites (n = 1341) to respondents who identified as Hispanic
(n = 394), Black (n = 261), or Asian/other (n = 177). Overall, the highest proportion
of Hispanics were high-risk problem gamblers. Hispanic participants were also signifi-
cantly more likely than other groups to use and abuse substances and to report mental
health problems in the past month, behavioral addictions, and/or suicidal ideation
in the past year. Primary predictors of White high risk problem gamblers were being
young and male with friends or family who gambled, fair to poor health status, sub-
stance use, gambling once a week or more both online and in land-based venues, and
engaging in a number of gambling activities. In contrast, gender was not a predictor
of minority high risk problem gamblers, who were characterized primarily by having
friends or family who gambled, gambling online only, having a behavioral addiction
and playing instant scratch-offs and gaming machines. Implications for research and
practice are discussed.
Open Access
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Caler et al.
Asian J of Gambling Issues and Public Health (2017) 7:7
DOI 10.1186/s40405-017-0027-2
Center for Gambling
Studies, School of Social
Work, Rutgers University,
536 George Street, New
Brunswick, NJ 08901, USA
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
have been reported regarding Black youth, who were significantly more likely than white
youth to engage in heavy gambling (Barnes, et al. 2009). Overall, being young, male,
and non-Hispanic Black was associated with high rates of gambling disorder in the U.S.
National Comorbidity Survey Replication (NCS-R) data (Kessler etal. 2008). ese find-
ings generally mirror sociodemographic characteristics and comorbidity patterns found
in earlier studies (Petry etal. 2005; Welte etal. 2001) as well as in special sub-groups
of Black gamblers ([hotline callers] Barry etal. 2008; [casino self-excluders] Nower and
Blaszczynski 2006; [homeless individuals] Nower etal. 2015; [veterans] Stefanovics etal.
2017). Welte etal. (2017) have noted that adults living in disadvantaged neighborhoods
reported the most problem gambling symptoms, however studies have yet to explore
the predictors of problem gambling versus other adaptive and maladaptive behaviors
in these groups apart from religiosity, which serves as a protective factor (Welte etal.
ere is scant research involving Hispanics/Latinos and gambling. e few studies
that exist are small-scale investigations of specific sub-groups. One general population
survey reported that Hispanics/Latinos with subthreshold gambling problems were
more likely to have comorbid mood, anxiety, substance use, and personality disorders
than White participants. In another study of Latino American veterans, Westermeyer
etal. (2005) found that the lifetime prevalence rate of disordered gambling was 4.3%,
nearly four times higher than in the general population. e study further noted that
gambling disorder was comorbid with high rates of major depressive (14.1%), alcohol
(22.9%), and posttraumatic stress (12.2%) disorders in that sample. More than half of
the undocumented Mexican immigrants surveyed in a small study in New York City
reported having gambled, and a majority of those gamblers played scratch and win tick-
ets or the lottery (Momper etal. 2009). ose who sent money home to their families or
had lived in the United States more than 12years and those who reported 1–5days of
poor mental health in the past 30days were most likely to gamble.
Research among Asian gamblers has been limited, possibly because of the tension
between the permissive attitude toward gambling and the increased stigma ascribed
to those who gamble problematically in Asian groups (Dhillon etal. 2011). In the U.S.,
studies have identified higher rates of gambling and problem gambling among Asian
subgroups, such as Southeast Asian and Cambodian refugees in the U.S., who reported
rates of gambling disorder as high as 59% (Petry etal. 2003) and 13.9% (Marshall etal.
2009), respectively. Similarly, another study found that, among college students, Chi-
nese students reported the highest rates of gambling problems followed by Koreans then
Whites. e most significant predictors of problem gambling in that study were being
Chinese or Korean and male, and having an alcohol or drug problems (Luczak and Wall
e culturally-based motivation to gamble and the risk and protective factors that
fuel or arrest the progression toward problem gambling in ethnic sub-groups are likely
complex and varied. Some researchers have suggested that the stress of acculturation
may play a significant role. A recent study, examining differences in gambling behavior
among first, second, and third generation immigrants from a diverse collection of world
regions (Africa, Asia, Europe, and Latin America), found the lowest rates of gambling
participation among Latin Americans, followed by Africa, Asia, and Europe, which had
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
the highest rates. First-generation immigrants had lower rates of gambling prevalence
and problem gambling when compared to second and third generation immigrants or
native-born Americans. In addition, the study found that immigrants who arrived in the
U.S. as children (12 or younger) gambled more frequently than those arriving as adoles-
cents or adults (Wilson etal. 2015). Issues surrounding acculturative stress may also play
a role in the development of gambling problems among youth. A recent study found that
rates of at-risk or problem gambling among first generation adolescent immigrants were
twice as high as their non-immigrant peers, particularly if they lived apart from their
parents (Canale etal. 2017).
In addition to the influence of acculturation, other theorists have suggested that biol-
ogy, values and beliefs also play a role. Chamberlain etal. (2016) suggested that inflated
rates of problem gambling among some ethnic and racial groups may be due, in part, to
neurocognitive differences among groups, as measured by differing rates of compulsiv-
ity, errors on memory and set-shifting tasks, and delay aversion, which they found were
higher in Black versus White participants in one study. Other researchers underscore the
influence of values and beliefs inherent in specific cultural groups or sub-groups in the
progression and maintenance of problem gambling behavior (Alegria etal. 2009; Raylu
and Oei 2004; Sacco etal. 2011). For example, certain Asian cultures consider gambling
activities to be a part of their lifestyle and tradition (Clark etal. 1990; Raylu and Oei
2004). In other ethnic groups and cultures (e.g. Native Americans), the concepts of fate
and a reliance on magical thinking may encourage gambling behavior in the same way as
cognitive distortions do in pathological gamblers (Hardoon etal. 2001; Zitzow 1996a, b).
Issues of social isolation, language barriers, and access to employment must also be clin-
ically considered as factors which can drive immigrant populations towards pathological
gambling behavior (Ngai and Chu 2001; Tse 2003).
To date, a notable exception has been found in the Hispanic native born and immi-
grant communities where, despite the adversity of poverty, lack of education, and social
discrimination, rates of pathological and problem gambling are below that of the White
majority (Alegria etal. 2009). is phenomenon seems to parallel the “Hispanic para-
dox” (Scribner 1996) documented in health outcome studies, where Hispanics have bet-
ter health outcomes despite the challenges of low socioeconomic status and barriers to
accessing healthcare (Grant etal. 2004; Scribner 1996; Vega etal. 1998).
Given the lack of clarity surrounding differences among minority groups and between
minority and White gamblers, the purpose of this study is to explore differences in the
characteristics and behaviors of non-problem gamblers compared to high-risk problem
gamblers across different ethnic groups.
e study utilized a sub-set of 2173 New Jersey residents over 18 who endorsed at least
one gambling activity in the past year from a larger epidemiologic study of 3634 partici-
pants. e remaining 1461 participants reported no involvement in any gambling activi-
ties in the past year and were excluded from the analyses. Data coding and analyses were
conducted using SPSS version 24.
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
e present study incorporated data collected through an epidemiological survey con-
ducted across the state of New Jersey that stratified its sampling method to accurately
reflect the demographic makeups of each region of the state. Sections of the survey
produced data on the following variables: (a) demographics (gender, age, race/ethnic-
ity, education level, household income, immigration status, and relationship status); (b)
substance use (tobacco use, alcohol use, illegal drug use, problems and treatment seek-
ing with substances, behavioral addictions, and binge drinking); (c) mental health and
physical health (overall stress level, overall level of happiness, overall health, experiences
of mental health problems in the past 30days and 12months, suicidal ideation, and
suicidal attempts in the past year); (d) gambling activities participated in the past year
(lottery, bingo, scratch offs, sports betting, horse race track betting, poker, casino table
games, other games of skill, and gaming machines); (e) non-gambling activities partici-
pated in the past year (high risk stocks and daily fantasy sports); (f) gambling behavior
(frequency of participation, amount of money spent, venue preference for gambling, and
online gambling participation across all previously mentioned forms).
Problem Gambling Severity Index (PGSI) of the Canadian Problem Gambling Index
(CPGI, Ferris and Wynne 2001) is 9-item instrument was used to assess gambling sta-
tus. Respondents indicate the extent to which an item applies to them using a four-point
Likert scale ranging from 0 (never) to 3 (almost always). Scores are totaled in accordance
with Ferris and Wynne’s (2001) guidelines: 0 indicates no risk; 1–2 low risk; 3–7 moder-
ate risks; and 8–27 problem gambling, respectively. Ferris and Wynne (2001) reported
satisfactory scale reliability (α=0.84). For the purpose of the logistic regression analy-
ses, a non-problem gambler was classified as any scoring 0 on the PGSI and “at-risk”
gamblers were classified as any participant scoring 3 or higher on the PGSI.
e data was collected both by telephone (cell and landline phones) and Internet to
address limitations inherent in either methodology alone. Stratified sampling was used
in both sub-samples to ensure demographic characteristics of age, gender, and race/eth-
nicity were reflective of the New Jersey population.
Univariate analyses
Univariate comparisons among problem severity categories were performed for gender,
age, race/ethnicity, education level, marital status, household income, and employment
status. Table1 presents the distribution and statistical significance of explanatory vari-
ables by PGSI category. e association between the PGSI and each explanatory vari-
able was assessed using Chi-squared Test of Independence. No socioeconomic variables
showed a significant association with the PGSI. High risk of problem gambling was sig-
nificantly associated with age (younger), gender (male), race/ethnicity (Hispanic and
Asian/other), marital status (married), self-assessed health in the past year (Excellent),
and past year stress (high). Non-problem gambling was significantly associated with age
(older), gender (female), race/ethnicity (White), marital status (divorced/separated), self-
assessed health in the past year (good/fair) and past year stress (low).
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
Table 1 Demographic breakdown ofnon-problem (n = 1510) and at-risk problem gam-
blers (n=663)
Variable Non-PG Low risk PG Moderate
risk PG High risk PG Total
n%n%n%n%n (% oftotal)
21–24 92 6.1 34 12.3 28 14.8 38 19.4 192 (8.8)
25–34 237 15.7 65 23.5 52 27.5 73 37.2 427 (19.6)
35–44 312 20.6 49 17.7 50 26.5 55 28.1 466 (21.4)
45–54 332 22.0 66 23.8 32 16.9 21 10.7 451 (20.8)
55–64 243 16.1 30 10.8 12 6.3 7 3.6 292 (13.4)
65+295 19.5 33 11.9 15 7.9 2 1.0 345 (15.9)
Male 695 46.0 150 54.2 120 63.2 136 69.4 1101 (50.6)
Female 815 54.0 127 45.8 70 36.8 60 30.6 1072 (49.4)
White 1016 67.3 155 60.0 90 47.4 80 40.8 1341 (61.7)
Hispanic 245 16.2 40 14.4 49 25.8 60 30.6 394 (18.1)
Black 155 10.3 51 18.4 27 14.2 28 14.3 261 (12.0)
Asian/other 94 6.2 31 11.2 24 12.6 28 14.3 177 (8.2)
Marital status*
Married or
living w/
937 62.0 162 58.5 108 56.8 139 70.9 1346 (62.0)
241 16.0 42 15.2 15 7.9 19 9.7 317 (14.6)
Single (never
married) 332 22.0 73 26.3 67 35.3 38 19.4 510 (23.4)
Health status (past year)*
Excellent 271 17.9 35 12.6 38 20.0 59 30.1 403 (18.5)
Good/fair 1051 69.6 197 71.2 118 62.1 111 56.6 1477 (68.0)
Poor 188 12.5 45 16.2 34 17.9 26 13.3 293 (13.5)
Overall stress level (past year)*
Low 355 23.5 56 20.2 37 19.5 30 15.3 478 (22.0)
Moderate 1020 67.6 200 72.2 137 72.1 121 61.7 1478 (68.0)
High 135 8.9 21 7.6 16 8.4 45 23.0 217 (10.0)
Yearly household income
Less than
$15,000 65 4.3 14 5.1 9 4.7 13 6.6 101 (4.7)
29,999 137 9.1 19 6.9 30 15.8 18 9.3 204 (9.4)
49,999 207 13.7 53 19.1 28 14.7 21 10.7 309 (14.2)
69,999 256 17.0 54 19.5 42 22.1 44 22.4 396 (18.2)
99,999 305 20.2 57 20.6 36 18.9 41 20.9 439 (20.2)
124,999 198 13.1 36 13.0 18 9.6 34 17.3 286 (13.2)
149,999 120 7.9 15 5.4 10 5.3 14 7.2 159 (7.3)
$150,000 or
more 222 14.7 29 10.4 17 8.9 11 5.6 279 (12.8)
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
Additionally, Table2 presents associations between race/ethnicity and gambling fre-
quency, preferred gambling venue(s), participation in individual gambling activities, five
measures of substance use, and three measures of mental health. Race/ethnicity was sig-
nificantly associated with both high (Hispanics) and low frequency (Whites) gambling,
land-based only gambling (Whites), and gambling both online and in land-based venues
(Hispanics). Looking at specific gambling activities, race/ethnicity was significantly asso-
ciated with instant scratch-off ticket play, bingo, sports betting, horse race track betting,
live poker, live casino table games and other games of skill. Asians were more likely than
other ethnicities to have participated in bingo within the past year, while Hispanics pre-
ferred sports betting, horse race track betting, live poker games, live casino table games
and other games of skill. Hispanic participants were distinguished by their answers to
Table 1 continued
Variable Non-PG Low risk PG Moderate
risk PG High risk PG Total
n%n%n%n%n (% oftotal)
Education level
Less than high
school or
17 1.1 10 3.6 5 2.6 12 6.1 44 (2.0)
High school
diploma or
294 19.5 60 21.7 34 18.0 33 16.8 421 (19.4)
Some college
(less than
1 year)
114 7.5 30 10.8 23 12.1 18 9.2 185 (8.5)
Some college
(more than
1 year)
187 12.4 35 12.6 19 10.0 15 7.7 256 (11.8)
degree 145 9.6 17 6.1 15 7.9 22 11.2 199 (9.1)
degree 465 30.8 89 32.1 55 28.9 44 22.4 653 (30.1)
degree 219 14.5 27 9.7 25 13.2 33 16.8 304 (14.0)
degree 38 2.5 6 2.2 9 4.7 13 6.6 66 (3.0)
degree 31 2.1 3 1.2 5 2.6 6 3.2 45 (2.1)
Employment status
Employed for
Wages 843 55.8 173 62.5 120 63.2 127 64.7 1263 (58.2)
Self-employed 121 8.0 24 8.7 15 7.9 25 12.7 185 (8.5)
Out of work
(less than
1 year)
34 2.3 5 1.8 2 1.1 7 3.6 48 (2.2)
Out of work
(more than
1 year)
32 2.1 7 2.5 9 4.7 5 2.6 53 (2.4)
Homemaker 90 6.1 14 5.1 6 3.2 12 6.1 122 (5.6)
Student 61 4.0 15 5.3 17 8.9 7 3.6 100 (4.6)
Retired 283 18.7 31 11.2 15 7.8 6 3.1 335 (15.4)
Unable to
work 46 3.0 8 2.9 6 3.2 7 3.6 67 (3.1)
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
questions pertaining to substance use and mental health issues. Hispanic respondents
were more likely than the other ethnicities to endorse tobacco use, binge drinking, illegal
drug use and problems due to drug or alcohol use in the past year. Hispanic participants
were also more likely than other groups to endorse a mental health problem in the past
30days, having a behavioral addiction and/or suicidal ideation in the past year.
Multivariate analyses
A primary aim of this study was to identify the primarily predictors of those at mod-
erate or high risk for gambling problems (i.e. 3+ symptoms) compared to non-prob-
lem gamblers (i.e. zero symptoms). For that reason, medium and high risk participants
were recoded as “problem gamblers” and compared to non-problem gamblers. Low
risk gamblers were omitted from the analyses to ensure comparisons between those
with more serious symptoms to those with an absence of symptoms. Multiple logistic
Table 2 Gambling, substance use, andmental health byethnicity
*p.05; **p.01; ***p.001
Variable White Hispanic Black or
Asian/other Total
n (1341) % n (394) % n (261) % n (177) % n (% oftotal)
Gambling frequency**
Low 478 66.1 114 15.8 75 10.4 56 7.7 723 (100.0)
Medium 367 63.1 92 12.7 81 13.9 42 7.2 582 (100.0)
High 496 57.1 188 21.7 105 12.1 79 9.1 868 (100.0)
Preferred gambling venue(s)***
Land-based only 1067 66.2 244 15.1 198 12.3 104 6.4 1613 (100.0)
Online only 66 57.4 26 22.6 7 6.1 16 13.9 115 (100.0)
Land-based and online 208 46.7 124 27.9 56 12.6 57 12.8 445 (100.0)
Gambling activities
Lottery 1059 60.7 323 18.5 219 12.6 143 8.2 1744 (100.0)
Instant scratch-off tickets** 853 60.6 276 19.6 181 12.9 98 7.0 1408 (100.0)
Bingo*** 212 51.0 92 22.1 55 13.2 57 13.7 416 (100.0)
Sports betting*** 139 43.3 98 30.5 42 13.1 42 13.1 321 (100.0)
Horse race track betting*** 201 61.9 75 23.1 18 5.5 31 9.5 325 (100.0)
Live poker*** 129 51.2 70 27.8 26 10.3 27 10.7 252 (100.0)
Live casino table games*** 264 57.0 104 22.5 42 9.1 53 11.4 463 (100.0)
Gaming machines (slots) 416 60.4 139 20.2 73 10.6 61 8.8 689 (100.0)
Other games of skill*** 158 45.7 99 28.6 47 13.6 42 12.1 346 (100.0)
Substance use
Tobacco use*** 351 53.6 156 23.8 93 14.2 55 8.4 655 (100.0)
Alcohol use*** 1051 62.2 325 19.2 178 10.5 136 8.0 1690 (100.0)
Binge drinking*** 230 51.7 120 27.0 45 10.1 50 11.2 445 (100.0)
Illegal drug use*** 116 44.3 82 31.3 41 15.6 23 8.8 262 (100.0)
Problems with drugs or alco-
hol*** 44 40.4 43 39.4 13 11.9 9 8.9 109 (100.0)
Mental health
Behavioral addictions* 165 55.9 74 25.1 35 11.9 21 7.1 295 (100.0)
Mental health problems* 183 60.4 70 23.1 35 11.6 15 5.0 303 (100.0)
Suicidal ideation*** 33 44.0 26 34.7 11 14.7 5 6.7 75 (100.0)
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
regression analyses were used to evaluate the relative contributions of the predictor
variables, which had proven significant in the univariate analyses, to the likelihood of
membership in the at-risk problem gambling group. Continuous variables included age
and number of gambling activities endorsed for the past year. All other variables were
dummy coded. e minimum criteria for entry of covariates into the model were a p
value of less than .05. Partial odds ratios (OR) and 95% confidence intervals (CIs) were
computed for significant predictors. Model effects were estimated by the improvement
in Chi-square and by a classification matrix indicating the proportion of individuals
correctly identified by the model covariates.
To facilitate the identification of specific demographic, mental health, gambling par-
ticipation, and substance use characteristics that differentiate non-problem gamblers
from problem gamblers in Whites and ethnic minorities, backward selection step-wise
logistic regression analyses were performed, entering in Block 1 demographic variables
that had proven significant in the prior analyses between the two groups. ese included
gender, age, marital status, whether friends or family gamble, overall health in the past
year, and overall stress levels in the past year. Substance use, behavioral addiction, and
mental health variables were entered in Block 2, to determine which of the significant
variables added most to the regression equation overall and which, if any, had a moder-
ating effect on the significant demographic characteristics. Gambling behavior variables
were entered into Block 3 to similarly determine which added the most to the regression
equation overall and had a moderating effect on the remaining Block 1 and Block 2 vari-
ables. Tables3 and 4 show the final regression results.
e results of both logistic regressions indicated a good model fit. e regression
model separating White non-problem gamblers and at-risk problem gamblers presented
with a Hosmer–Lemeshow goodness-of-fit statistic of, χ2 (8, N=1341)=2.91, p=.940.
e second regression model separating ethnic minority non-problem gamblers and at-
risk problem gamblers presented with a Hosmer–Lemeshow goodness-of-fit statistic of,
χ2 (8, N=832)=10.25, p=.248. e largest predictors for membership in the White
at-risk problem gambler group in the final model were high frequency gambling, having
problems with drugs or alcohol, gambling both online and in land-based venues, and
participating in instant scratch-off tickets. e largest predictors for membership in the
minority at-risk problem gamblers group in the final model were high and moderate fre-
quency gambling, having friends or family that gamble, and gambling online only.
Among Whites, the results indicate a significant negative relationship with age: Each
one-year increase in age decreased the odds of being an at-risk problem gambler by .98%.
Men were 1.44 times more likely to be White at-risk problem gamblers in comparison to
women. Having friends or family who gambled increased the odds of being a White at-
risk problem gambler by 2.28 times. Whites were also characterized by fair (2.69 times) or
poor (1.64 times) health status in the past year, using tobacco products (1.73 times), having
problems with drugs or alcohol (2.77 times) and/or a behavioral addiction (1.84 times).
Among Whites, high frequency (2.8 times) or moderate frequency (1.7 times) gam-
bling, gambling online (2.6 times) or both online and in land-based venues (2.7 times),
purchasing scratch-off tickets (2.7 times), betting on sports (2.3 times), playing games of
skill (1.8 times), live casino games (1.7 times) and/or gaming machines (1.6 times) were
most predictive of at-risk problem gamblers.
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
Among ethnic minorities, there was a similar negative relationship with age: Each
one-year increase decreased the odds of being an at-risk problem gambler. Gender was
a non-significant predictor for minorities, although having friends or family that gam-
bled proved the most significant predictor for minority at-risk problem gambling status,
increasing the odds by nearly three times. Among the substance use and mental health
variables, only having a behavioral addiction was significant predictor of at-risk problem
minority membership, increasing the odds by 2.0 times. As with Whites, moderate or
high frequency gambling increased the odds of being an at-risk problem gambler by 3.6
and 4.5 times, respectively. Unlike Whites, however, gambling both online and in land-
based venues was not a significant predictor of being at-risk, although gambling only
online increased the odds of membership by 2.5 times. Amongst the individual gambling
activities, only instant scratch-off tickets and gaming machine participation were predic-
tive of at-risk minority status (2.72 and 1.59 times respectively).
Findings from this study highlight the need to further explore ethnic differences among
gamblers and to better differentiate etiological and other risk factors that may variously
predispose different ethnic groups to develop gambling problems. e study utilized a
Table 3 Variables distinguishing between White non-problem gamblers (n = 1016)
andWhite at-risk gamblers (n=325)
*p.05; **p.01; ***p.001
SE OR 95% CI
Age (continuous)*** 0.01 0.98 0.97–0.99
Gender (female)* 0.17 1.44 1.03–2.02
Friends and family gamble*** 0.17 2.28 1.64–3.18
Health status for the last year
Excellent (ref.)
Fair** 0.31 2.69 1.46–4.94
Poor* 0.25 1.64 1.00–2.69
Tobacco use** 0.18 1.73 1.22–2.44
Alcohol use 0.21 0.20 0.50–1.15
Binge drinking 0.21 1.50 0.99–2.26
Problems with drugs or alcohol* 0.51 2.77 1.03–7.47
Behavioral addictions** 0.23 1.84 1.16–2.91
Gambling frequency
Low (ref.)
Medium* 0.23 1.70 1.08–2.68
High*** 0.22 2.80 1.83–4.29
Gambling venue
Land-based only (ref.)
Online and land-based*** 0.23 2.74 1.76–4.26
Online only** 0.33 2.55 1.35–4.81
Instant scratch-off*** 0.20 2.72 1.83–4.04
Sports betting** 0.28 2.35 1.36–4.05
Horse race track 0.25 .66 0.40–1.08
Live casino table games* 0.21 1.65 1.10–2.47
Other games of skill* 0.24 1.75 1.09–2.81
Gaming machines* 0.18 1.59 1.12–2.27
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
representative sample of participants from New Jersey, however, the relatively small sam-
ple size of each ethnic sub-group compared to Whites precluded a detailed exploration
of differences within each sub-group in the multivariate analyses. e data suggested
that, overall, Whites were more likely than other ethnic groups to be non-problem gam-
blers; they were also more likely than other ethnic groups, irrespective of problem gam-
bling severity, to be younger males from families or peer groups that gambled and to
report comorbid addictive behaviors and fair to poor health status. is profile reflects
the characterization of the “emotionally vulnerable” problem gambler (Blaszczynski and
Nower 2002), who gambles problematically in order to escape aversive mood states and
develops problems due to gambling with increasing frequency on multiple gambling
games. Like Whites, Ethnic minority groups appear to be primarily influenced by family
members or peer groups who gambled, however, unlike Whites, gender did not appear
to play a predictive role. As with Whites, higher gambling frequency among minorities
was correlated with higher levels of problem severity, although gambling only online
and presumably on gaming machines appeared to be a greater risk factor. ese find-
ings could suggest that the influence of cultural, familial and community attitudes about
Table 4 Variables distinguishing between Minority non-problem gamblers (n = 494)
andMinority at-risk problem gamblers (n=338)
*p.05; **p.01; ***p.001
SE OR 95% CI
Age (continuous)* 0.01 0.98 0.97–1.00
Gender (female) 0.20 0.68 0.74–1.60
Friends and family gamble*** 0.19 2.95 2.04–4.26
Overall stress level in the past year
Low (ref.)
Moderate 0.24 1.29 0.81–2.05
High 0.39 1.08 0.50–2.31
Relationship status
Married (ref.)
Divorced, separated, or widowed 0.31 1.02 0.56–1.88
Single 0.22 0.86 0.56–1.32
Tobacco use 0.21 1.42 0.96–2.16
Binge drinking 0.22 1.33 0.87–2.03
Illegal drug use 0.27 1.58 0.90–2.59
Behavioral addictions** 0.28 2.16 1.26–3.86
Suicidal ideation in the past year 0.61 1.61 0.46–5.20
Gambling frequency low (ref.)
Medium*** 0.28 3.60 2.08–6.24
High*** 0.27 4.53 2.67–7.70
Gambling venue
Land-based only (ref.)
Online and land-based 0.24 1.53 0.96–2.44
Online only* 0.38 2.47 1.17–5.21
Instant scratch-off* 0.22 1.63 1.06–2.50
Bingo 0.25 1.54 0.95–2.49
Sports betting 0.28 1.63 0.95–2.81
Live casino table games 0.26 1.56 0.95–2.58
Gaming machines* 0.22 1.55 1.02–2.36
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Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
gambling, combined with accessibility of opportunities and the conditioning effects of
reinforcement could lead to gambling problems in some minority subgroups. is eti-
ology, characteristic of “behaviorally conditioned” problem gamblers (Blaszczynski and
Nower 2002), is most responsive to targeted prevention, interventions, and education
efforts directed at the client system.
In contrast to findings in an earlier study (Alegria etal. 2009), the current results fail
to support the notion of a “Hispanic paradox” for gambling and suggest a far more com-
plex and context-dependent array of risk factors likely play a role. In this study, Hispan-
ics were distinguished by the highest rates of problem gambling, substance abuse, and
mental health problems. ough Asian participants also endorsed high rates of problem
gambling, Hispanic gamblers reported the highest proportionate rates of “action” ori-
ented play, such as sports and race track betting and casino table games, and gambling
primarily online. ey were also more likely than other ethnic groups to endorse sub-
stance abuse, mental health problems and suicidality in the past year.
Very little is known about the onset of gambling and problem gambling in Hispanic
communities, the influence of peers and family modeling, the role of erroneous cogni-
tions generated by cultural superstitions, and/or other bio-psycho-social factors that
lead to the development and maintenance of gambling problems in sub-groups of His-
panics and Latinos. In New Jersey, Hispanics are the largest minority but their median
income is almost half that of Whites and less than half that of Asians (U.S. Census
Bureau 2015), however, there are few programs and services targeting Hispanic gam-
blers and few certified gambling counselors who are Spanish-speakers. Future research
with Hispanics and other ethnic minorities should focus on exploring the cultural and
familial systems that introduce and help to maintain gambling behavior in various ethnic
groups and investigating specific risk and protective factors to use as a basis for preven-
tion, intervention and treatment efforts.
Authors’ contributions
All authors participated on the development of this manuscript. All authors read and approved the final manuscript.
The researchers would like to thank Director David L. Rebuck, Robert Moncrief, and Afshien Lashkari of the DGE, Suzanne
Borys from DMHAS, Dr. Rachel Volberg of Gemini Research, and Simon Jaworski and Lance Henik of Leger for their
assistance with this project.
Competing interests
Funding was provided to the DGE by law by industry corporations with online gaming licenses in New Jersey. Authors
Caler and Vargas Garcia are students, employed through that grant. Dr. Nower has received grants from or consult-
ing contracts from industry, governmental, and/or non-profit organizations on projects unconnected to this work. All
authors certify they have no competing interests regarding this study or its findings.
Availability of data and materials
The data is proprietary and not publically available.
Consent to publication
All authors consent to publication of this manuscript.
Ethics approval
All procedures performed in studies involving human participants were approved by the Rutgers University Internal
Review Board and performed in accordance with their ethical standards and those of the 1964 Helsinki declaration and
its later amendments or comparable ethical standards.
This study was supported by a grant from the New Jersey Divisions of Gaming Enforcement (DGE), in collaboration with
the Division on Addictions, Department of Mental Health and Addictive Services (DMHAS).
Page 12 of 13
Caler et al. Asian J of Gambling Issues and Public Health (2017) 7:7
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Received: 26 May 2017 Accepted: 13 August 2017
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... Gambling disorder is also associated with a multitude of adverse physical outcomes (American Psychiatric Association, 1994;2013), including cardiac problems, liver disease (American Psychiatric Association, 2013; Morasco et al., 2006), obesity (Chamberlain et al., 2017), hypertension (Langham et al., 2016), insomnia (Christensen et al., 2001;Langham et al., 2016), diabetes, and arthritis (Desai et al., 2007). Gambling disorder is associated with increased rates of psychological disorders (American Psychiatric Association, 2013;Chamberlain et al., 2017), including depression (Chamberlain et al., 2017;Kerber et al., 2015), anxiety (Chamberlain et al., 2017), personality disorders (American Psychiatric Association, 2013;Fernández-Montalvo & Echeburúa, 2004), and post-traumatic stress disorder (PTSD) (Caler et al., 2017). Prevalence of substance use disorders is also higher among those with gambling disorder (American Psychiatric Association, 2013;Chiu & Hassan, 2016;Hammond et al., 2020;Langham et al., 2016), including alcohol use disorder (Chamberlain et al., 2017), and nicotine use disorder (Welte et al., 2006). ...
... When compared to the general population, there are specific ethnic groups with higher rates of pathological gambling (Fong, 2005). Multiple studies have found that African Americans are most at risk for developing gambling disorder (Alegría et al., 2009;Welte et al., 2016), though some studies find Hispanics, not African Americans, are at greater risk (Caler et al., 2017). Other risk factors are living in disadvantaged neighborhoods and having lower levels of education (Tabri et al., 2017;Welte et al., 2016). ...
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Gambling disorder is a “hidden disease” due to the lack of visible markers. It often negatively affects multiple domains of a person’s life and predicts adverse physical, mental, social, and financial outcomes. Health service settings are suited for early detection of gambling disorder because of its comorbid medical conditions and due to the trust patients have in their health service providers (HSPs). However, HSPs often lack the knowledge needed to screen for this disorder and to make appropriate referrals. This paper reports a quasi-experimental wait-list control study (experimental group n = 18; wait-list control group n = 14), with cross-over and a twelve-week follow-up which assessed whether a brief virtual gambling disorder training entitled Gambling Know More could improve gambling disorder knowledge among HSPs. Results showed workshop participation caused a significant increase in gambling disorder knowledge immediately after the workshop and twelve weeks later. Participation in Gambling Know More bodes well for increasing early detection of gambling disorder and appropriate treatment referrals among HSPs. Findings have important policy implications for the training of HSPs.
... W. Abbott et al., 2014;Bonnaire et al., 2017), obesity (Algren et al., 2015;Black et al., 2013;Loo et al., 2019), poor mental health (Castrén et al., 2013;Ekholm et al., 2018;Lorains et al., 2011), high alcohol intake and daily smoking (Algren et al., 2015;Castrén et al., 2013;Ford & Håkansson, 2020). Additionally, two studies conducted on data from Denmark suggested that foreign origin and belonging to an ethnic minority group is associated with increased risk of becoming a problem gambler (Hakansson et al., 2019;Lyk-Jensen, 2010) and this association has also been reported in other countries (Alegría et al., 2009;Caler et al., 2017;Canale et al., 2017;James et al., 2016;Kastirke et al., 2015;Welte et al., 2004). However, a review from 2016 (Okuda et al., 2016) suggests that being an ethnic minority in itself is not a risk factor for problem gambling, but instead can be a proxy for other underlying potential risk factors or social determinants related to problem gambling. ...
... However, a review from 2016 (Okuda et al., 2016) suggests that being an ethnic minority in itself is not a risk factor for problem gambling, but instead can be a proxy for other underlying potential risk factors or social determinants related to problem gambling. Caler et al. (2017) found, for instance, that Hispanics had the highest rates of problem gambling, mental health problems and substance use and abuse compared to Whites among others, while Alegría et al. (2009) showed that Blacks had twice the rate of problem gambling and also lower scores on general health measures compared to Whites. ...
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Introduction This study examined the degree to which perceptions of familial and household participation in gambling and other addictive behaviors in youth was associated with frequency and problem severity of gambling, alcohol and/or drug use in participants as adults. Method The study measured perceived frequency of gambling, alcohol use, drug use and other potentially addictive behaviors in family/household members and the frequency and problem severity of gambling, alcohol, and drugs in an epidemiological sample of adults 18 and older (N=3,499; m=48.26%, f=51.74%). Results About 23.45% of participants reported their father gambled when they were a child or adolescent, followed by mother (13.56%), grandfather (9.73%), or grandmother (7.83%). A pathway model demonstrated cross-addiction inter- and intra-generational influences. Gambling by a father, mother or brother; substance use by a sister; and/or engagement in other behaviors by a brother, sister, grandmother or other household member was related to higher frequency of participant gambling (ps<0.05), and, in turn, to higher levels of gambling, alcohol, and drug use problem severity (ps<0.05). Discussion Findings demonstrate the complex contributions of specific family and household members in the transmission of addictive behaviors. Frequency of gambling, alcohol use, and drug use mediated the relationship of perceived family behavior with and across addictions. In addition, perceptions regarding use of alcohol and/or other drugs, or engagement in other behaviors by family or household members was related not only to participants' alcohol and drug use but also to problem gambling frequency and severity.
... Ortiz and Hernández (2019) Gambling harms have been shown to be linked with other health considerations, including both drug dependencies (Ortiz and Hernández, 2019), and severe depression (Currie in Breen and Gainsbury 2013). Furthermore, although there is a lack of research exploring the relationship between cooccurring health conditions and ethnicity amongst people who gamble within Great Britain, international evidence suggests that mental health difficulties experienced by people who gamble vary in terms of prevalence and severity between different minority ethnic communities Caler et al 2017). ...
Technical Report
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... In other instances, Asian gamblers have reported losing more money from gambling than other ethno-cultural groups (Venkataraman Rinker et al., 2016). Above all else, the most consistent finding in the extant literature is that East Asians (e.g., Chinese, Japanese, Korean, and Taiwanese) and South Asians (e.g., East Indian, Pakistani, and Sri Lankan) are at higher risk for gambling problems and harms than non-Asian populations (Barry et al., 2009; J. Barry, 2014;Caler et al., 2017;Forrest & Wardle, 2011;Kim, 2012;Ontario Resource Group on Gambling, 2010;Sobrun-Maharaj et al., 2013). Some research has also shown that immigrant and international student status can predict risk of problem gambling. ...
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Online gambling during COVID-19 has been associated with a variety of risk factors and comorbidities, such as co-occurring substance use, mental health problems, and financial concerns and gambling motives. Far less is known about these impacts on ethno-cultural populations, including East and South Asian gamblers. The present study has attempted to explore the health inequities related to these comorbidities and risk factors among East and South Asian gamblers. A cross-sectional online survey of gamblers in Ontario, Canada, was carried out in August 2020—a time when most land-based gambling venues were not operating at full capacity. Descriptive statistical analyses, odds ratios, and negative binomial regression (NBR) were used to compare East and South Asian gamblers to other online gamblers in Ontario. The total survey sample of 2,012 gamblers included sub-samples of East Asian (n = 206) and South Asian gamblers (n = 107). Compared to other gamblers in Ontario, East and South Asians reported higher likelihood of severe gambling problems, risky financially focused gambling motives, gambling under the influence of alcohol, and elevated levels of mental health problems. An adjusted NBR analysis noted that East Asians were more highly involved in online gambling during the pandemic, compared to non-East Asian gamblers. This study has presented an array of factors representing potential health inequities among East and South Asian gamblers during the pandemic. These findings merit further investigation and replication in order to inform the development of appropriate support resources.
The present study sought to identify psychosocial factors associated with recent gambling (gambling within the past 30 days). The 2016, 2018, and 2020 Parents' Institute for Drug Education (PRIDE) data sets were pooled and analyzed, consisting of 108,690 adolescents in 13 local public schools. A sizeable percentage (13.1%) of adolescents reported gambling in the past 30 days. Multiple logistic regression analyses found differences based on demographic factors, previous substance use, and psychosocial factors. Adolescents at highest risk were male, non-white, in high school, sold drugs, and participated in violent activities in the past 30 days. The study also found worrying rates of substance use. Findings from the present study can inform harm reduction efforts, prevention messaging, and clinical interventions related to adolescent gambling.
Despite the rapid expansion of legalized gambling, few social workers are trained to identify problem gambling symptoms. This study explored gambling knowledge, behavior, and problem symptoms in a sample of 1,777 clinical social workers through an online survey. Findings indicate about 77% of social workers gambled and more than 4% of those who gambled reported at least one problem gambling symptom. Participants answered less than half of the knowledge questions correctly, and a majority were unaware of the current diagnostic classification for gambling disorder or the legal age for gambling. Results of a multivariate regression analysis found that social workers in practice 8 to 15 years, employed in substance treatment facilities or universities, and/or with training in gambling treatment had higher levels of knowledge about gambling and gambling treatment. Findings underscore the need for social work schools and organizations to prioritize education and training for problem gambling identification and treatment.
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This study aimed to examine associations between gambling level and clinically relevant measures, including psychiatric disorders and suicidality, in a nationally representative sample of U.S. veterans. Data on 3157 U.S. veterans were analyzed from the National Health and Resilience in Veterans Study. Chi square tests and analyses of variance were used to assess associations between gambling level, and demographic, military, and personality characteristics. Multinomial logistic regressions using stepwise selection were used to identify independent correlates of recreational gambling and at-risk/problem gambling (ARPG). A significant proportion of U.S. veterans engage in gambling activities, with 35.1% gambling recreationally and 2.2% screening positive for ARPG. ARPG was associated with greater prevalence of substance use, anxiety, and depressive disorders, as well as with a history of physical trauma or sexual trauma, having sought mental health treatment (particularly from the Veterans Administration), and minority group status. A similar pattern was found associated with recreational gambling, although the magnitudes of association were lower relative to ARPG. Younger age, self-identifying as black, being retired, and trauma burden were associated with increased odds of ARPG, whereas older age, being single, non-white Hispanic, being retired or not having a job, screening positive for alcohol- and drug-use disorders, and trauma burden were associated with increased odds of recreational gambling. More than a third of U.S. veterans gamble recreationally, with a significant minority (2.2%) screening positive for ARPG. Both recreational and ARPG were associated with elevated trauma burden and psychiatric comorbidities. These findings underscore the importance of routine screening and monitoring of gambling severity, and interventions for ARPG in this population.
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Aim: The primary aim of the present study was to examine the association between immigrant generation, family sociodemographic characteristics, and problem gambling severity in a large-scale nationally representative sample of Italian youth. Method: Data from the 2013-2014 Health Behaviour in School-aged Children (HBSC) Survey were used for cross-sectional analyses of adolescent problem gambling. Self-administered questionnaires were completed by a representative sample of 20,791 15-year-old students. Respondents' problem gambling severity, immigrant status, family characteristics (family structure, family affluence, perceived family support) and socio-demographic characteristics were individually assessed. Findings: Rates of adolescent at-risk/problem gambling were twice as high among first generation immigrants than non-immigrant students; the odds of being at-risk/problem gamblers were higher among first-generation immigrants than adolescents of other immigrant generations or non-immigrant. Not living with two biological or adoptive parents appears to be a factor that increases the risk of becoming a problem gambler in first generation immigrants. Conclusions: Immigrant status and family characteristics may play a key role in contributing to adolescent problem gambling.
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In this article we examine data from a national U.S. adult survey of gambling to determine correlates of problem gambling and discuss them in light of theories of the etiology of problem gambling. These include theories that focus on personality traits, irrational beliefs, anti-social tendencies, neighborhood influences and availability of gambling. Results show that males, persons in the 31-40 age range, blacks, and the least educated had the highest average problem gambling symptoms. Adults who lived in disadvantaged neighborhoods also had the most problem gambling symptoms. Those who attended religious services most often had the fewest problem gambling symptoms, regardless of religious denomination. Respondents who reported that it was most convenient for them to gamble had the highest average problem gambling symptoms, compared to those for whom gambling was less convenient. Likewise, adults with the personality traits of impulsiveness and depression had more problem gambling symptoms than those less impulsive or depressed. Respondents who had friends who approve of gambling had more problem gambling symptoms than those whose friends did not approve of gambling. The results for the demographic variables as well as for impulsiveness and religious attendance are consistent with an anti-social/impulsivist pathway to problem gambling. The results for depression are consistent with an emotionally vulnerable pathway to problem gambling.
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Recent epidemiological data suggest that the lifetime prevalence of gambling problems differs depending on race-ethnicity. Understanding variations in disease presentation in blacks and whites, and relationships with biological and sociocultural factors, may have implications for selecting appropriate prevention strategies. 62 non-treatment seeking volunteers (18-29 years, n=18 [29.0%] female) with gambling disorder were recruited from the general community. Black (n=36) and White (n=26) participants were compared on demographic, clinical and cognitive measures. Young black adults with gambling disorder reported more symptoms of gambling disorder and greater scores on a measure of compulsivity. In addition they exhibited significantly higher total errors on a set-shifting task, less risk adjustment on a gambling task, greater delay aversion on a gambling task, and more total errors on a working memory task. These findings suggest that the clinical and neurocognitive presentation of gambling disorder different between racial-ethnic groups.
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Introduction. A meta-analysis of 119 studies performed in North America found that the lifetime prevalences of pathological gambling in adults are 1.6 percent. We conducted national surveys on addictive behavior to estimate the prevalence of pathological gambling. Methods. A survey of 7,500 men and women ( >= 20 years) was performed; the sampling was obtained from the total Japanese adult population stratified using a two-stage random sampling in 2008. An South Oaks Gambling Screen score of five points or more was defined as a pathological gambler. The follow-up survey was performed in 2013. Results. The prevalence of pathological gambling was estimated to be 9.04% among men and 1.6% among women in 2008. No significant relationships between the rate of pathological gambling and education, marital status, occupation, or income level were seen. The vast majority of male pathological gamblers (93%) used Pachinko as a gambling tool. Similar results were shown in the 2013 survey. Conclusion. This study revealed that the prevalence of pathological gambling, especially among men, was much higher in Japan than in other countries. Pachinko was very popular and was strongly suggested to have contributed to this heightened prevalence.
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The purpose of this study was to investigate the prevalence of gambling disorder and comorbid psychiatric disorders in a homeless population and identify features related to potential subtypes. At baseline, participants were administered a structured interview including socio-demographic sections of the National Comorbidity Study (NCS) interview; seven diagnostic sections of the Diagnostic Interview Schedule (DIS); the alcohol and drug abuse sections of the Composite International Diagnostic Interview-Substance Abuse Module (CIDI-SAM); and the Homeless Supplement to the DIS. At nine months post-baseline assessment, participants were administered additional NCS family history questions and the South Oaks Gambling Screen (SOGS). Participants were an epidemiologic sample of 275 predominately African-American homeless individuals, grouped as lifetime non-gamblers (n = 60), recreational gamblers (n = 152), and problem gamblers (n = 63), recruited on the street and through homeless shelters. Results indicate that lifetime rates of sub-clinical problem (46.2 %) and disordered (12.0 %) gambling were significantly higher than in the general population. Problem gamblers were more likely than non-problem gamblers to meet diagnostic criteria for antisocial personality disorder, post-traumatic stress disorder, bipolar disorder, and any psychiatric disorder, and more likely than non-gamblers to use illicit drugs or meet criteria for abuse/dependence for nicotine, alcohol, or any substance. This study provides evidence that problem gambling is a significant public health issue among the African-American homeless population. Homeless services should include assessment for problem gambling along with psychiatric disorders and referrals to resources and treatment programs. Future studies should explore the relationship of the onset and course of problem gambling and other psychiatric disorders with homelessness as well as racial differences in gambling patterns and problem severity over time.
Background and objectives: This study examined gambling behaviors and the relationship between gambling problems and alcohol use disorders (AUDs) among Chinese-, Korean-, and White-American college students. Methods: Participants were 678 (179 Chinese, 194 Korean, and 305 White; 50% female) 21-26 year-old (M = 22.0 ± 1.36) students attending one university in California. The South Oaks Gambling Screen was administered to assess gambling behavior and the Semi-Structured Assessment for the Genetics of Alcoholism was administered to diagnose lifetime AUDs. Chi-squares and multinomial logistic regressions were conducted to test our hypotheses. Results: Rates of lifetime ever gambling and weekly gambling were similar across the three ethnic groups, but participation in five types of gambling behavior differed. Chinese had the highest rates of gambling problems followed by Koreans and then Whites. Univariate odds ratios determined being Chinese or Korean, being male, and having an AUD were risk factors for gambling problems. When stratified by gender and ethnicity, having an AUD was not related to gambling problems in women, but was strongly associated with gambling problems in Chinese and White men and modestly associated in Korean men. This was true despite low rates of AUDs in Chinese men. Discussion and conclusions: Gambling problems were strongly comorbid with AUDs in Chinese- and White-American men, and moderately comorbid in Korean-American men. No relationship of AUD with gambling problems was found in women. Scientific significance: The results highlight the importance of assessing disaggregated Asian-American subgroups with respect to addictive behaviors and their comorbidity. (Am J Addict 2016;XX:1-8).