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Nicotine & Tobacco Research
1
doi: 10.1093/ntr/ntr294
© The Author 2012. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.
All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Introduction
A sizable body of evidence suggests that tobacco use often cooccurs
with problem gambling ( McGrath & Barrett, 2009 ; Petry,
2007 ) with smoking prevalence rates ranging from 41% ( Smart &
Ferris, 1996 ) to 60% ( Cunningham-Williams, Cottler, Compton, &
Spitznagel, 1998 ; Lorains, Cowlishaw, & Thomas, 2011 ) among
problem gamblers. In particular, epidemiological studies indi-
cate that tobacco dependence is frequently associated with prob-
lem gambling. Indeed, one investigation found that tobacco
dependence (60%) is second only to alcohol dependence (73%)
as the most prevalent substance use disorder that is comorbid
with problem gambling ( Petry, Stinson, & Grant, 2005 ). In
addition, recent epidemiological evidence also indicates that ciga-
rette smokers are three times more likely to be problem gam-
blers than nonsmokers ( Griffi ths, Wardle, Orford, Sproston, &
Erens, 2010 ). Despite the substantial degree of cooccurrence
between smoking and gambling disorders, little research has
focused on disentangling the exact dynamics of the smoking —
gambling relationship.
Beyond prevalence rates, relatively few studies have directly
compared smoking and nonsmoking gamblers. Each study that
has done so focused on problem gamblers seeking treatment for
their gambling. Their fi ndings suggest that problem gamblers
who smoke have higher problem gambling severity scores ( Grant,
Kim, Odlaug, & Potenza, 2008 ; Petry & Oncken, 2002 ), experi-
ence more psychiatric symptoms ( Grant et al., 2008 ; Petry &
Oncken, 2002 ; Potenza et al., 2004 ), are more likely to have other
substance use disorders ( Petry & Oncken, 2002 ; Potenza et al.,
2004 ), report stronger urges/cravings to gamble ( Grant & Potenza,
2005 ; Petry & Oncken, 2002 ), spend more time gambling ( Petry &
Oncken, 2002 ), spend/lose more money gambling ( Grant et al.,
Abstract
Introduction: Numerous epidemiological and clinical studies
have found that tobacco use and gambling frequently cooccur.
Despite high rates of smoking among regular gamblers, the
extent to which tobacco potentially infl uences gambling behavior
and vice versa is poorly understood. The current study aimed to
provide more insight into this relationship by directly compar-
ing nonsmoking and smoking gamblers on gambling behavior,
problem gambling indices, and reasons for gambling.
Methods: The data for this study came from the 2005
Newfoundland and Labrador Gambling Prevalence Study.
Gamblers identifi ed as nonsmokers ( N = 997) were compared
with gamblers who smoke ( N = 622) on numerous gambling-
related variables. Chi-square analyses were used to compare groups
on demographic variables. Associations between smoking status
and gambling criteria were assessed with a series of binary logistic
regressions.
Results: The regression analyses revealed several significant
associations between smoking status and past 12-month
gambling. Higher problem gambling severity scores, use of
alcohol/drugs while gambling, amount of money spent gam-
bling, use of video lottery terminals, and reasons for gambling
which focused on positive reinforcement/reward and negative
reinforcement/relief were all associated with smoking.
Conclusions: The findings suggest an association between
smoking and potentially problematic gambling in a population-
based sample. More research focused on the potential reinforc-
ing properties of tobacco on the development and treatment of
problematic gambling is needed.
Original Investigation
A Comparison of Gambling Behavior,
Problem Gambling Indices, and Reasons
for Gambling Among Smokers and
Nonsmokers Who Gamble: Evidence
from a Provincial Gambling Prevalence
Study
Daniel S. McGrath , Ph.D. , 1 Sean P. Barrett , Ph.D. , 1 , 2 Sherry H. Stewart , Ph.D. , 1 , 2 & Pauwlina R. McGrath , B.Sc. (Pharm) 3
1 Department of Psychology, Life Sciences Centre, Dalhousie University, Halifax, Nova Scotia, Canada
2 Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
3 College of Pharmacy, Dalhousie University, Halifax, Nova Scotia, Canada
Corresponding Author : Sean P. Barrett, Ph.D., Department of Psychology, Dalhousie University, Life Sciences Centre, 1355 Oxford Street,
Halifax, Nova Scotia, Canada B3H 4R2. Telephone: 902-494-2956; Fax: 902-494-6585; E-mail: sean.barrett@dal.ca
Received July 8 , 2011 ; accepted November 10 , 2011
doi:10.1093/ntr/ntr294
Advance Access Published on January 16, 2012
© e Author 2012. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.
All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Nicotine & Tobacco Research, Volume 14, Number 7 (July 2012) 833–839
833
at Dalhousie University on July 25, 2012http://ntr.oxfordjournals.org/Downloaded from
Smoking and gambling
2
Smoking and gambling
2008 ; Petry & Oncken, 2002 ), experience more fi nancial problems
( Grant et al., 2008 ; Potenza et al., 2004 ), and more often choose
nonstrategic/riskier forms of gambling such as electronic gam-
ing ( Grant et al., 2008 ; Potenza et al., 2004 ). The aggregate of
these studies indicates that tobacco use is associated with a host
of psychosocial diffi culties among problem gamblers.
To date, however, no known studies have specifi cally addressed
tobacco use within a general population sample which encom-
passes the entire continuum of gamblers (i.e., from non-problem
to severe problem gamblers). Outside of clinical samples, much
remains unknown regarding how smoking and nonsmoking
gamblers might potentially differ in their gambling behavior or
level of risk for problematic gambling. In addition, an increas-
ing emphasis in the gambling literature has been placed on
identifying underlying reasons or “ motives ” for gambling as
a means for differentiating gambler subtypes ( Milosevic &
Ledgerwood, 2010 ; Neighbors, Lostutter, Cronce, & Larimer,
2002 ). Studies on motives for drinking (e.g., Cooper, 1994 ) and
gambling (e.g., Stewart & Zack, 2008 ) indicate that both posi-
tive and negative reinforcement processes underlie motivation
to drink or gamble. Other research suggests that smokers may
also be driven to smoke by similar underlying motives ( Battista
et al., 2008 ; Pomerleau, Fagerström, Marks, Tate, & Pomerleau,
2003 ). However, no known research has acknowledged potential
differences between smokers and nonsmokers in their reasons
for gambling. Identifying potential patterns in gambling in-
volvement, problem gambling risk, and motivation for gam-
bling among smokers may have implications for the prevention
and treatment of problem gambling in this population.
In the current investigation, we attempted to address impor-
tant gaps in the existing literature on tobacco use and gambling.
Specifi cally we explored differences in gambling behavior, problem
gambling indices, and reasons for gambling among gamblers
who are smokers and nonsmokers in a representative Canadian
population-based sample. In line with previous clinical and
epidemiological evidence (e.g., Grant et al., 2008 ; Petry & Oncken,
2002 ; Potenza et al., 2004 ), we hypothesized that smoking among
gamblers would be associated with ( a ) greater gambling
involvement, ( b ) higher problem gambling severity scores, and
( c ) participation in riskier forms of gambling (e.g., electronic
gaming). Based on previous motives research (e.g., Battista et al.,
2008 ; Stewart & Zack, 2008 ), it was also predicted that tobacco
use would be associated with ( d ) reasons for gambling that
either increase positive affect or decrease negative affect.
Methods
The sample in this report was compiled from the 2005
Newfoundland and Labrador Gambling Prevalence Study ( Market
Quest Research Group, 2005 ). The questionnaire consisted of
65 questions organized into four major sections: demographic
variables, gambling involvement (including reasons for gam-
bling), problem gambling behavior and adverse consequences,
and correlates of gambling. Data were collected province-wide
via telephone between September 7 and October 20, 2005. All
respondents were 19 years or older. The sample included 2,154
respondents who reported gambling during the past 12 months
with smoking status data available for 1,619 gamblers (only these
respondents were included in our analyses). Sampling was strat-
ifi ed by gender and region but was otherwise random. The total
response rate was unavailable. A demographic comparison of
smokers ( N = 622) and nonsmokers ( N = 997) is provided in
Table 1 .
Respondents were asked several questions regarding their
gambling involvement and behavior during the past 12 months.
These included: types of gambling activities they had participated
in, total number of activities participated in, and total dollar
amount spent gambling. In the present investigation, amount
spent gambling underwent a square root transformation as a
result of a non-normal distribution and the presence of outliers.
Table 1. Chi-Square Analyses for Demographic Characteristics of Nonsmokers Versus
Smokers
Demographic characteristic Nonsmokers ( N = 997) Smokers ( N = 622) χ 2 df p value
Gender: n (%) 0.63 1 0.44
Male 496 (49.7) 322 (51.8)
Female 501 (50.3) 300 (48.2)
Age group: n (%) 97.26 3 0.01*
19 – 34 years 188 (18.9) 206 (33.1)
35 – 54 years 459 (46.0) 321 (51.6)
55 – 64 years 168 (16.9) 64 (10.3)
65+ years 182 (18.3) 31 (5.0)
Marital status: n (%) 48.82 2 0.01*
Married/common law 796 (80.0) 418 (67.4)
Widowed/separated/divorced 114 (11.5) 76 (12.3)
Single 85 (8.5) 126 (20.3)
Household income: n (%) 8.65 3 0.03*
$20,000 or less 96 (13.1) 69 (14.3)
$20,001 to $40,000 240 (32.7) 191 (39.5)
$40,001 to $80,000 276 (37.6) 163 (33.7)
$80,000 or more 123 (16.6) 61 (12.5)
Note . * p ≤ .05 .
834
at Dalhousie University on July 25, 2012http://ntr.oxfordjournals.org/Downloaded from
Nicotine & Tobacco Research, Volume 14, Number 7 (July 2012)
2
Smoking and gambling
2008 ; Petry & Oncken, 2002 ), experience more fi nancial problems
( Grant et al., 2008 ; Potenza et al., 2004 ), and more often choose
nonstrategic/riskier forms of gambling such as electronic gam-
ing ( Grant et al., 2008 ; Potenza et al., 2004 ). The aggregate of
these studies indicates that tobacco use is associated with a host
of psychosocial diffi culties among problem gamblers.
To date, however, no known studies have specifi cally addressed
tobacco use within a general population sample which encom-
passes the entire continuum of gamblers (i.e., from non-problem
to severe problem gamblers). Outside of clinical samples, much
remains unknown regarding how smoking and nonsmoking
gamblers might potentially differ in their gambling behavior or
level of risk for problematic gambling. In addition, an increas-
ing emphasis in the gambling literature has been placed on
identifying underlying reasons or “ motives ” for gambling as
a means for differentiating gambler subtypes ( Milosevic &
Ledgerwood, 2010 ; Neighbors, Lostutter, Cronce, & Larimer,
2002 ). Studies on motives for drinking (e.g., Cooper, 1994 ) and
gambling (e.g., Stewart & Zack, 2008 ) indicate that both posi-
tive and negative reinforcement processes underlie motivation
to drink or gamble. Other research suggests that smokers may
also be driven to smoke by similar underlying motives ( Battista
et al., 2008 ; Pomerleau, Fagerström, Marks, Tate, & Pomerleau,
2003 ). However, no known research has acknowledged potential
differences between smokers and nonsmokers in their reasons
for gambling. Identifying potential patterns in gambling in-
volvement, problem gambling risk, and motivation for gam-
bling among smokers may have implications for the prevention
and treatment of problem gambling in this population.
In the current investigation, we attempted to address impor-
tant gaps in the existing literature on tobacco use and gambling.
Specifi cally we explored differences in gambling behavior, problem
gambling indices, and reasons for gambling among gamblers
who are smokers and nonsmokers in a representative Canadian
population-based sample. In line with previous clinical and
epidemiological evidence (e.g., Grant et al., 2008 ; Petry & Oncken,
2002 ; Potenza et al., 2004 ), we hypothesized that smoking among
gamblers would be associated with ( a ) greater gambling
involvement, ( b ) higher problem gambling severity scores, and
( c ) participation in riskier forms of gambling (e.g., electronic
gaming). Based on previous motives research (e.g., Battista et al.,
2008 ; Stewart & Zack, 2008 ), it was also predicted that tobacco
use would be associated with ( d ) reasons for gambling that
either increase positive affect or decrease negative affect.
Methods
The sample in this report was compiled from the 2005
Newfoundland and Labrador Gambling Prevalence Study ( Market
Quest Research Group, 2005 ). The questionnaire consisted of
65 questions organized into four major sections: demographic
variables, gambling involvement (including reasons for gam-
bling), problem gambling behavior and adverse consequences,
and correlates of gambling. Data were collected province-wide
via telephone between September 7 and October 20, 2005. All
respondents were 19 years or older. The sample included 2,154
respondents who reported gambling during the past 12 months
with smoking status data available for 1,619 gamblers (only these
respondents were included in our analyses). Sampling was strat-
ifi ed by gender and region but was otherwise random. The total
response rate was unavailable. A demographic comparison of
smokers ( N = 622) and nonsmokers ( N = 997) is provided in
Table 1 .
Respondents were asked several questions regarding their
gambling involvement and behavior during the past 12 months.
These included: types of gambling activities they had participated
in, total number of activities participated in, and total dollar
amount spent gambling. In the present investigation, amount
spent gambling underwent a square root transformation as a
result of a non-normal distribution and the presence of outliers.
Table 1. Chi-Square Analyses for Demographic Characteristics of Nonsmokers Versus
Smokers
Demographic characteristic Nonsmokers ( N = 997) Smokers ( N = 622) χ 2 df p value
Gender: n (%) 0.63 1 0.44
Male 496 (49.7) 322 (51.8)
Female 501 (50.3) 300 (48.2)
Age group: n (%) 97.26 3 0.01*
19 – 34 years 188 (18.9) 206 (33.1)
35 – 54 years 459 (46.0) 321 (51.6)
55 – 64 years 168 (16.9) 64 (10.3)
65+ years 182 (18.3) 31 (5.0)
Marital status: n (%) 48.82 2 0.01*
Married/common law 796 (80.0) 418 (67.4)
Widowed/separated/divorced 114 (11.5) 76 (12.3)
Single 85 (8.5) 126 (20.3)
Household income: n (%) 8.65 3 0.03*
$20,000 or less 96 (13.1) 69 (14.3)
$20,001 to $40,000 240 (32.7) 191 (39.5)
$40,001 to $80,000 276 (37.6) 163 (33.7)
$80,000 or more 123 (16.6) 61 (12.5)
Note . * p ≤ .05 .
3
Nicotine & Tobacco Research
Three gambling activities (i.e., internet gambling, arcade or
video games, and short - term stock) were excluded due to low
rates of endorsement (<5%).
The questionnaire also included Problem Gambling Severity
Index (PGSI) scores from the Canadian Problem Gambling
Index (CPGI; Ferris & Wynne, 2001 ) to determine past 12-month
problem gambling severity (higher scores denote increased
risk for problem gambling). The CPGI displays strong psycho-
metric properties including good internal consistency ( α =
.84), test – retest reliability ( r = 0.78), and high convergent
validity ( r = 0.83) ( Ferris & Wynne, 2001 ) with the South Oaks
Gambling Screen (SOGS; Lesieur & Blume, 1987 ). In the cur-
rent study, the PGSI displayed a high degree of internal consis-
tency ( α = .93). In addition, questions on known correlates
of problem gambling were included such as age fi rst gambled,
remembering first big win, agreement with the “ gambler ’ s
fallacy, ” use of a “ certain system or strategy while gambling, ”
using alcohol or drugs while gambling, and gambling while
drunk or high.
Lastly, respondents were asked to provide the main reasons
why they gamble. They were free to list as many reasons for
gambling as they wished. Each verbatim response was then
placed by the interviewer into one of the following categories:
“ it ’ s an opportunity to socialize, ” “ it is exciting/fun, ” “ I can win
money, ” “ it ’ s a hobby, ” “ out of curiosity, ” “ because I am good
at it , ” and “ to support worthy causes/charities. ” The answer
choices also included: “ I can forget about my problems, ” “ it de-
creases my boredom, ” and “ to be alone. ” Individual motives
were then combined for the current report into three motives
groups based on their conceptual similarity: (1) positive rein-
forcement/reward [socialize, exciting/fun, win money, hobby,
curiosity, and being good at it] ( N = 1,375), (2) negative re-
inforcement/relief [forget problems, boredom, & to be alone]
( N = 151), and (3) charitable motives [support causes/charities]
( N = 456). All reasons for gambling provided by respondents
were included with some providing more than one motive.
Previous research suggests that conceptually similar items load
onto broader gambling motive constructs and usefully differen-
tiate gambler subtypes (e.g., Stewart & Zack, 2008 ).
Statistical Analysis
Data analyses for this study were performed with SPSS software.
Hypotheses were tested by comparing nonsmokers and smokers
across criterion variables. Categorical demographic measures
were examined with individual chi-square analyses. Three binary
logistic regressions were conducted in an effort to identify which
(1) gambling involvement variables, (2) problem gambling
correlates, and (3) reasons for gambling differentially distinguish
nonsmokers and smokers. No violations of the assumptions of
linearity or multicollinearity were detected.
Results
Nonsmoking and smoking gamblers differed on several demo-
graphic variables (see Table 1 ). While no differences in gender
composition were noted, gamblers who smoke were on average
found to be younger, more likely to be single/not married, and
to have lower incomes than gamblers who don ’ t smoke.
The regression model for gambling involvement was signif-
icant, Cox and Snell Pseudo R 2 = .06, χ 2 (10) = 88.92, p < .001.
Amount of money spent gambling ( odds ratio [ OR ] = 1.01) and
use of VLTs (OR = 1.77) in the past 12 months both predicted
smoking over nonsmoking (see Table 2 ). Only raffl e ticket (OR =
0.66) participation predicted nonsmoking group member-
ship. The remaining gambling involvement variables were not
signifi cant.
For problem gambling correlates, the regression analysis
revealed several signifi cant associations with smoking status,
Cox and Snell Pseudo R 2 = .04, χ 2 (7) = 52.68, p < .001. The OR
for average score on the PGSI ( Ferris & Wynne, 2001 ) (OR = 1.08)
and use of alcohol/drugs while gambling (OR = 1.58) signifi-
cantly predicted smoker group membership (see Table 3 ). The
remaining problem gambling correlates were not signifi cant.
Finally, the reasons for gambling regression model were also
signifi cant, Cox and Snell Pseudo R 2 = .02, χ 2 (3) = 23.50, p <
.001. “ Positive reinforcement/reward motives ” (OR = 1.53)
and “ negative reinforcement/relief motives ” (OR = 2.22), each
Table 2. Binary Logistic Regression for Gambling Involvement Among Nonsmokers and
Smokers
Gambling involvement Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
Number of activities: M ( SE ) a 2.7 (0.05) 3.2 (0.07) 0.66 1.43 0.60 3.40
Amount spent gambling (dollars): M ( SE ) a 336.5 (53.1) 724.7 (133.8) 5.93 1.01* 1.00 1.02
Type of gambling
Lottery tickets: n (%) 881 (88.5) 532 (85.7) 3.17 0.67 0.43 1.04
Scratch tickets: n (%) 489 (49.0) 388 (62.6) 0.36 1.14 0.74 1.78
Raffl e tickets: n (%) 565 (56.7) 320 (51.5) 4.89 0.66* 0.46 0.95
Cards and poker: n (%) 142 (14.2) 146 (23.5) 0.81 1.21 0.80 1.84
Sports, horses, and games of skill: n (%) 79 (7.9) 73 (11.7) 0.01 1.02 0.62 1.69
Bingo: n (%) 112 (11.2) 123 (19.8) 2.52 1.39 0.93 2.09
Video lottery terminals: n (%) 92 (9.2) 142 (22.8) 6.84 1.77* 1.15 2.71
Casino games: n (%) 49 (4.9) 33 (5.3) 2.52 0.63 0.35 1.12
Not e. * p ≤ .05
a Original means and SE s reported .
835
at Dalhousie University on July 25, 2012http://ntr.oxfordjournals.org/Downloaded from
Smoking and gambling
4
Smoking and gambling
predicted smoker group membership (see Table 4 ). “ Charitable ”
motives were not found to be signifi cant.
Discussion
The purpose of this study was to investigate potential differ-
ences between nonsmokers and smokers on several gambling-
related criteria. Consistent with our predictions, smoking
gamblers were differentiated from nonsmoking gamblers across
numerous gambling behaviors, problem gambling indices, and
gambling motives.
Tobacco use in this study was associated with increased odds
of elevated PGSI scores, using alcohol/drugs while gambling
and spending more money gambling in the previous 12 months.
Additionally, VLT participation was the only gambling activity
that signifi cantly predicted smoker group membership with an
increase of 1.77 in the log odds. These fi ndings from a population-
based sample are generally consistent with the profi le of tobacco-
using gamblers derived from clinical studies ( Grant & Potenza,
2005 ; Grant et al., 2008 ; Petry & Oncken, 2002 ; Potenza
et al., 2004 ). Our results also suggest that motivation to gamble
for smokers and nonsmokers may be uniquely different. Motives
centered on positive reinforcement/reward as well as negative
reinforcement/relief were strongly associated with tobacco use.
These two groups of motives closely correspond to previous
reports of “ enhancement ” and “ coping ” motives for alcohol
use ( Cooper, 1994 ) and for problematic gambling ( Stewart &
Zack, 2008 ; Stewart, Zack, Collins, & Klein, 2008 ), respectively.
This trend toward gambling for riskier reasons that decrease
negative affect (i.e., “ escape ” ) and increase positive affect
(i.e., “ excitement ” ) among smokers in our sample appears
to parallel their increased association with problem gambling
severity, substance use while gambling, and choice of riskier
types of gambling.
Overall, these results suggest that tobacco use is associated
with potentially problematic gambling outcomes and motives.
It is conceivable that smoking and gambling share a number of
common underlying mechanisms which may help to explain
their association. For instance, evidence indicates that both
nicotine ( Pontieri, Tanda, Orzi, & Di Chiara, 1996 ) and problem
gambling ( Lader, 2008 ; Linnet, Peterson, Doudet, Gjedde, &
Møller, 2010 ) are reinforced via neurochemical processes
including increased dopamine neurotransmission. Theoretically,
it is conceivable that tobacco use during gambling may augment
reinforcement through dopamine mediation. The relationship
between smoking and gambling may also be behaviorally condi-
tioned. For example, evidence indicates that the presence of
environmental cues can elicit cravings in a number of substance
use disorders ( Carter & Tiffany, 1999 ) as well as problem gam-
bling ( Sodano & Wulfert, 2010 ). In animal models, nicotine has
been found to facilitate the release of dopamine in response to
other reinforcing stimuli (e.g., Chaudhri et al., 2007 ). In humans,
nicotine has been shown to increase sensitivity to cocaine-related
cues ( Reid, Mickalian, Delucchi, Hall, & Berger, 1998 ) as well as
increase other addictive behaviors such as alcohol consumption
( Barrett, Tichauer, Leyton, & Pihl, 2006 ). While as yet to be tested,
it is feasible that cue reactivity or the reinforcement-enhancing
properties of nicotine contribute to the problematic gambling
behavior exhibited by smokers who gamble. It is also possible
that cooccurring tobacco use and gambling is infl uenced through
cognitive factors. For instance, a recent laboratory study found
Table 3. Binary Logistic Regression for Problem Gambling Correlates Among
Nonsmokers and Smokers
Problem gambling correlates Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
PGSI score, M ( SE ) 0.33 (0.06) 1.02 (0.14) 8.54 1.08* 1.03 1.13
Age fi rst gambled (years), M ( SE ) 23.3 (0.36) 22.3 (0.39) 0.32 0.99 0.99 1.01
Remember fi rst big win, n (%) 38 (3.9) 37 (6.0) 1.66 1.22 0.90 1.64
Endorse gambler ’ s fallacy, n (%) 45 (4.7) 40 (6.6) 0.18 1.11 0.68 1.82
Use system or strategy, n (%) 90 (9.7) 76 (12.9) 0.56 1.15 0.80 1.65
Use alcohol/drugs while gambling, n (%) 120 (12.3) 146 (23.7) 6.98 1.58* 1.13 2.22
Gambled while drunk/high, n (%) 37 (3.8) 63 (10.3) 3.04 1.61 0.94 2.74
Not e.
* p ≤ .05
Table 4. Binary Logistic Regression for Reasons for Gambling Among Nonsmokers and
Smokers
Reasons for gambling Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
Positive reinforcement/reward, n (%) 837 (87.9) 538 (90.3) 4.88 1.53* 1.05 2.22
Negative reinforcement/relief, n (%) 70 (7.4) 81 (13.6) 18.88 2.22* 1.55 3.19
Charitable, n (%) 297 (31.2) 159 (26.7) 0.72 0.90 0.71 1.15
Note . Gambling reasons are not mutually exclusive with participants free to endorse more than one reason.
* p ≤ .05.
836
at Dalhousie University on July 25, 2012http://ntr.oxfordjournals.org/Downloaded from
Nicotine & Tobacco Research, Volume 14, Number 7 (July 2012)
4
Smoking and gambling
predicted smoker group membership (see Table 4 ). “ Charitable ”
motives were not found to be signifi cant.
Discussion
The purpose of this study was to investigate potential differ-
ences between nonsmokers and smokers on several gambling-
related criteria. Consistent with our predictions, smoking
gamblers were differentiated from nonsmoking gamblers across
numerous gambling behaviors, problem gambling indices, and
gambling motives.
Tobacco use in this study was associated with increased odds
of elevated PGSI scores, using alcohol/drugs while gambling
and spending more money gambling in the previous 12 months.
Additionally, VLT participation was the only gambling activity
that signifi cantly predicted smoker group membership with an
increase of 1.77 in the log odds. These fi ndings from a population-
based sample are generally consistent with the profi le of tobacco-
using gamblers derived from clinical studies ( Grant & Potenza,
2005 ; Grant et al., 2008 ; Petry & Oncken, 2002 ; Potenza
et al., 2004 ). Our results also suggest that motivation to gamble
for smokers and nonsmokers may be uniquely different. Motives
centered on positive reinforcement/reward as well as negative
reinforcement/relief were strongly associated with tobacco use.
These two groups of motives closely correspond to previous
reports of “ enhancement ” and “ coping ” motives for alcohol
use ( Cooper, 1994 ) and for problematic gambling ( Stewart &
Zack, 2008 ; Stewart, Zack, Collins, & Klein, 2008 ), respectively.
This trend toward gambling for riskier reasons that decrease
negative affect (i.e., “ escape ” ) and increase positive affect
(i.e., “ excitement ” ) among smokers in our sample appears
to parallel their increased association with problem gambling
severity, substance use while gambling, and choice of riskier
types of gambling.
Overall, these results suggest that tobacco use is associated
with potentially problematic gambling outcomes and motives.
It is conceivable that smoking and gambling share a number of
common underlying mechanisms which may help to explain
their association. For instance, evidence indicates that both
nicotine ( Pontieri, Tanda, Orzi, & Di Chiara, 1996 ) and problem
gambling ( Lader, 2008 ; Linnet, Peterson, Doudet, Gjedde, &
Møller, 2010 ) are reinforced via neurochemical processes
including increased dopamine neurotransmission. Theoretically,
it is conceivable that tobacco use during gambling may augment
reinforcement through dopamine mediation. The relationship
between smoking and gambling may also be behaviorally condi-
tioned. For example, evidence indicates that the presence of
environmental cues can elicit cravings in a number of substance
use disorders ( Carter & Tiffany, 1999 ) as well as problem gam-
bling ( Sodano & Wulfert, 2010 ). In animal models, nicotine has
been found to facilitate the release of dopamine in response to
other reinforcing stimuli (e.g., Chaudhri et al., 2007 ). In humans,
nicotine has been shown to increase sensitivity to cocaine-related
cues ( Reid, Mickalian, Delucchi, Hall, & Berger, 1998 ) as well as
increase other addictive behaviors such as alcohol consumption
( Barrett, Tichauer, Leyton, & Pihl, 2006 ). While as yet to be tested,
it is feasible that cue reactivity or the reinforcement-enhancing
properties of nicotine contribute to the problematic gambling
behavior exhibited by smokers who gamble. It is also possible
that cooccurring tobacco use and gambling is infl uenced through
cognitive factors. For instance, a recent laboratory study found
Table 3. Binary Logistic Regression for Problem Gambling Correlates Among
Nonsmokers and Smokers
Problem gambling correlates Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
PGSI score, M ( SE ) 0.33 (0.06) 1.02 (0.14) 8.54 1.08* 1.03 1.13
Age fi rst gambled (years), M ( SE ) 23.3 (0.36) 22.3 (0.39) 0.32 0.99 0.99 1.01
Remember fi rst big win, n (%) 38 (3.9) 37 (6.0) 1.66 1.22 0.90 1.64
Endorse gambler ’ s fallacy, n (%) 45 (4.7) 40 (6.6) 0.18 1.11 0.68 1.82
Use system or strategy, n (%) 90 (9.7) 76 (12.9) 0.56 1.15 0.80 1.65
Use alcohol/drugs while gambling, n (%) 120 (12.3) 146 (23.7) 6.98 1.58* 1.13 2.22
Gambled while drunk/high, n (%) 37 (3.8) 63 (10.3) 3.04 1.61 0.94 2.74
Not e.
* p ≤ .05
Table 4. Binary Logistic Regression for Reasons for Gambling Among Nonsmokers and
Smokers
Reasons for gambling Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
Positive reinforcement/reward, n (%) 837 (87.9) 538 (90.3) 4.88 1.53* 1.05 2.22
Negative reinforcement/relief, n (%) 70 (7.4) 81 (13.6) 18.88 2.22* 1.55 3.19
Charitable, n (%) 297 (31.2) 159 (26.7) 0.72 0.90 0.71 1.15
Note . Gambling reasons are not mutually exclusive with participants free to endorse more than one reason.
* p ≤ .05.
5
Nicotine & Tobacco Research
that pathological gamblers who were heavy smokers made fewer
errors on tests of cognitive flexibility than lighter smokers
( Mooney, Odlaug, Kim, & Grant, 2011 ). The authors suggest
that nicotine may serve as a putative cognitive enhancer for
pathological gamblers. Finally , there is evidence to indicate that
smokers and gamblers share common personality characteristics.
In particular, higher levels of impulsivity have been reported
among smokers (e.g., Mitchell, 2004 ), pathological/problem
gamblers (e.g., Alessi & Petry, 2003 ; Nower, Derevensky, &
Gupta, 2004 ), and pathological gamblers with substance-use
disorders ( Verdejo-García, Lawrence, & Clark, 2008 ). It is con-
ceivable that certain personality characteristics differentially
infl uence the genesis and maintenance of cooccurring tobacco
use and gambling. These possible underlying mechanisms warrant
further experimental exploration.
This study contains a number of limitations. First, as the
questions were not designed for this investigation, additional
information that would have been desirable (e.g., co-use of
tobacco while gambling) was not available. Second, demographic
differences (i.e., age, marital status, income) were found be-
tween smokers and nonsmokers. It would have been preferable
to control for these differences; however, continuous informa-
tion was unavailable. Third, the cross-sectional design of the
survey did not allow for an examination of cause and effect. The
present study highlights a number of associations between
smoking and gambling but the directionally or causality of these
effects cannot be inferred. Fourth, while respondents provided
information on their motives for gambling, the construction of
the survey did not allow for the isolation of the “ primary ” rea-
son they gambled during the past year. It is feasible that these
primary motives for gambling are associated with problematic
gambling behavior to a greater extent than the other more sec-
ondary motives provided. Another potential limitation is that
only one Canadian province was included at one point in time.
Laws surrounding gambling and smoking vary; it is possible
that our results do not extrapolate to other jurisdictions. Finally,
results may have been impacted by the timing of data collection.
On July 1, 2005, Newfoundland and Labrador amended the
Smoke- Free Environment Act (2002), prohibiting smoking in
all public places including establishments which host gaming.
The gambling prevalence survey was administered in September
and October, 2005. As such, the smoking ban had been in effect
for 2 months prior to the start of data collection. It is unclear
how this could affect responses, especially for those questions
surrounding smoking. However, most of the gambling-related
questions focused on “ the past 12 months, ” with the majority of
those months occurring prior to the amendment.
The current study may have important implications for
both researchers and clinicians. First, pathological gambling
may soon be reclassifi ed as an addictive disorder in the upcoming
fi fth edition of the American Psychiatric Association Diagnostic
and Statistical Manual of Mental Disorders ( Grant, Potenza,
Weinstein, & Gorelick, 2010 ; Holden, 2010 ). If the diagnostic
classifi cation of pathological gambling changes to more closely
resemble that of substance-use disorders, including tobacco
dependence, an opportunity exists for researchers to further
investigate common features (e.g., genetics, personality, neuro-
biology) associated with both gambling and other substance
dependence including smoking. A strength of the methodology
employed in the current investigation is that it allows for the
identifi cation of important associations between gambling and
other addictive behaviors. Also, in addition to previous work
that examined clinical samples of gamblers (e.g., Grant et al.,
2008 ; Petry & Oncken, 2002 ), the present study indicates that
smoking is also commonly associated with gambling-related
problems in the general population. For clinicians, these results
provide awareness of potentially problematic gambling motives,
correlates , and activities associated with tobacco use and may
ultimately lead to better prevention efforts for smokers at risk
for problem gambling.
The present study was the first to systematically compare
a population-based sample of nonsmokers and smokers who
smoke on gambling behavior, problem gambling indices, and
motives for gambling. Our results indicate that tobacco use
among gamblers was associated with increased participation in
riskier forms of gambling, increased problem gambling severity,
and endorsement of motives linked to problematic gambling.
Future work should address the potential impact of nicotine on
the development, reinforcement, and treatment of problematic
gambling. Of particular importance, more controlled laboratory
studies are needed to accurately elucidate the role that smoking
plays in gambling behavior, craving, and motivation.
Funding
The data for this study w ere generously provided by the Ontario
Problem Gambling Research Centre. Portions of this study were
completed by Daniel McGrath in partial fulfi llment of a Ph . D .
in experimental psychology at Dalhousie University. Daniel was
supported through doctorate student research awards from the
Nova Scotia Health Research Foundation, Gambling Awareness
Nova Scotia, and a doctorate fellowship from the Ontario Problem
Gambling Research Centre during the completion of this
research.
Declaration of Interests
None declared.
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tobacco smoking and gambling: A review of the literature . Drug
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16500
Nower , L. , Derevensky , J. L. , & Gupta , R. ( 2004 ). The relationship
of impulsivity, sensation seeking, coping, and substance use in
youth gamblers . Psychology of Addictive Behaviors , 18 , 49 – 55 .
doi:10.1037/0893-164X.18.1.49
Petry , N. M. ( 2007 ). Gambling and substance use disorders:
Current status and future directions . The American Journal on
Addictions , 16 , 1 – 9 . doi:10.1080/10550490601077668
Petry , N. M. , & Oncken , C. ( 2002 ). Cigarette smoking is associated
with increased severity of gambling problems in treatment-seeking
gamblers . Addiction , 97 , 745 – 753 . doi:10.1046/j.1360-0443.2002.
00163.x
Petry , N. M. , Stinson , F. S. , & Grant , B. F. ( 2005 ). Comorbidity
of DSM-IV pathological gambling and other psychiatric disorders:
Results from the National Epidemiologic Survey on Alcohol and
Related Conditions . Journal of Clinical Psychiatry , 66 , 564 – 574 .
doi:10.4088/JCP.v66n0504
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Pomerleau , C. S. ( 2003 ). Development and validation of a self-
rating scale for positive- and negative-reinforcement smoking:
The Michigan Nicotine Reinforcement Questionnaire . Nicotine &
Tobacco Research , 5 , 711 – 718 . doi:10.1080/146222003100015
8627
Pontieri , F. E. , Tanda , G. , Orzi , F. , & Di Chiara , G. ( 1996 ).
Effects of nicotine on the nucleus accumbens and similarity to
those of addictive drugs . Nature , 382 , 255 – 257 . doi: 10.1038/
382255a0
Potenza , M. N. , Steinberg , M. A. , Mclaughlin , S. D. , Wu , R. ,
Rounsaville , B. J. , Krishnan-Sarin , S. , et al. ( 2004 ). Characteristics
F
838
at Dalhousie University on July 25, 2012http://ntr.oxfordjournals.org/Downloaded from
Nicotine & Tobacco Research, Volume 14, Number 7 (July 2012)
6
Smoking and gambling
Chaudhri , N. , Caggiula , A. R. , Donny , E. C. , Booth , S. , Gharib , M. ,
Craven , L. , et al. ( 2007 ). Self-administered and noncontingent
nicotine enhance reinforced operant responding in rats: Impact
of nicotine dose and reinforcement schedule . Psychopharmacology ,
190 , 353 – 362 . doi:10.1007/s00213-006-0454-8
Cooper , M. ( 1994 ). Motivations for alcohol use among adoles-
cents: Development and validation of a four-factor model .
Psychological Assessment , 6 , 117 – 128 . doi:10.1037/1040-3590.6.
2.117
Cunningham-Williams , R. M. , Cottler , L. B. , Compton , W. , &
Spitznagel , E. L. ( 1998 ). Taking chances: Problem gamblers and
mental health disorders: Results from the St. Louis Epidemiologic
Catchment Area study . American Journal of Public Health , 88 ,
1093 – 1096 . doi:10.2105/AJPH.88.7.1093
Ferris , J. , & Wynne , H. ( 2001 ). The Canadian Problem Gambling
Index: Final report . Canadian Centre on Substance Abuse , Ottawa,
Ontario: CCSA .
Grant , J. E. , Kim , S. , Odlaug , B. L. , & Potenza , M. N. ( 2008 ).
Daily tobacco smoking in treatment-seeking pathological gam-
blers: Clinical correlates and co-occurring psychiatric disorders .
Journal of Addiction Medicine , 2 , 178 – 184 . doi:10.1097/ADM.
0b013e3181878673
Grant , J. E. , & Potenza , M. N. ( 2005 ). Tobacco use and pathological
gambling . Annals of Clinical Psychiatry , 17 , 237 – 241 . doi:10.1080/
10401230500295370
Grant , J. E. , Potenza , M. N. , Weinstein , A. , & Gorelick , D. A.
( 2010 ). Introduction to behavioral addictions . The American
Journal of Drug and Alcohol Abuse , 36 , 233 – 241 . doi:10.3109/
00952990.2010.491884
Griffi ths , M. , Wardle , H. , Orford , J. , Sproston , K. , & Erens , B.
( 2010 ). Gambling, alcohol, consumption, cigarette smoking and
health: Findings from the 2007 British Gambling Prevalence
Survey . Addiction Research & Theory , 18 , 208 – 223 . doi:10.3109/
16066350902928569
Holden , C. ( 2010 ). Behavioral addictions debut in proposed
DSM-V . Science , 327 , 935 . doi: 10.1126/science.327.5968.935
Lader , M. ( 2008 ). Antiparkinsonian medication and pathological
gambling . CNS Drugs , 22 , 407 – 416 . doi:10.2165/00023210-
200822050-00004
Lesieur , H. R. , & Blume , S. B. ( 1987 ). The South Oaks Gambling
Screen (SOGS): A new instrument for the identification of
pathological gamblers . The American Journal of Psychiatry , 144 ,
1184 – 1188 .
Linnet , J. J. , Peterson , E. E. , Doudet , D. J. , Gjedde , A. A. , &
Møller , A. A. ( 2010 ). Dopamine release in ventral striatum of
pathological gamblers losing money . Acta Psychiatrica Scandinavica ,
122 , 326 – 333 . doi: 10.1111/j.1600-0447.2010.01591.x
Lorains , F. K. , Cowlishaw , S. , & Thomas , S. A. ( 2011 ). Preva-
lence of comorbid disorders in problem and pathological
gambling: Systematic review and meta-analysis of population
surveys . Addiction , 106 , 490 – 498 . doi:10.1111/j.1360-0443.2010.
03300.x
Market Quest Research Group . ( 2005 ). 2005 Newfoundland and
Labrador Gambling Prevalence Study . St. John ’ s, NL : Department of
Health and Community Services, Government of Newfoundland
and Labrador .
McGrath , D. S. , & Barrett , S. P. ( 2009 ). The comorbidity of
tobacco smoking and gambling: A review of the literature . Drug
and Alcohol Review , 28 , 676 – 681 . doi: 10.1111/j.1465-3362.2009.
00097.x
Milosevic , A. , & Ledgerwood , D. M. ( 2010 ). The subtyping
of pathological gambling: A comprehensive review . Clinical
Psychology Review , 30 , 988 – 998 . doi:10.1016/j.cpr.2010.06.013
Mitchell , S. H. ( 2004 ). Measuring impulsivity and modeling its
association with cigarette smoking . Behavioral and Cognitive
Neuroscience Reviews , 3 , 261 – 275 . doi:10.1177/15345823052
76838
Mooney , M. E. , Odlaug , B. L. , Kim , S. , & Grant , J. E. ( 2011 ).
Cigarette smoking status in pathological gamblers: Associa-
tion with impulsivity and cognitive flexibility . Drug and
Alcohol Dependence , 117 , 74 – 77 . doi:10.1016/j.drugalcdep.
2010.12.017
Neighbors , C. , Lostutter , T. W. , Cronce , J. M. , & Larimer , M. E.
( 2002 ). Exploring college student gambling motivation . Journal
of Gambling Studies , 18 , 361 – 370 . doi:10.1023/A:10210651
16500
Nower , L. , Derevensky , J. L. , & Gupta , R. ( 2004 ). The relationship
of impulsivity, sensation seeking, coping, and substance use in
youth gamblers . Psychology of Addictive Behaviors , 18 , 49 – 55 .
doi:10.1037/0893-164X.18.1.49
Petry , N. M. ( 2007 ). Gambling and substance use disorders:
Current status and future directions . The American Journal on
Addictions , 16 , 1 – 9 . doi:10.1080/10550490601077668
Petry , N. M. , & Oncken , C. ( 2002 ). Cigarette smoking is associated
with increased severity of gambling problems in treatment-seeking
gamblers . Addiction , 97 , 745 – 753 . doi:10.1046/j.1360-0443.2002.
00163.x
Petry , N. M. , Stinson , F. S. , & Grant , B. F. ( 2005 ). Comorbidity
of DSM-IV pathological gambling and other psychiatric disorders:
Results from the National Epidemiologic Survey on Alcohol and
Related Conditions . Journal of Clinical Psychiatry , 66 , 564 – 574 .
doi:10.4088/JCP.v66n0504
Pomerleau , O. F. , Fagerström , K. , Marks , J. L. , Tate , J. C. , &
Pomerleau , C. S. ( 2003 ). Development and validation of a self-
rating scale for positive- and negative-reinforcement smoking:
The Michigan Nicotine Reinforcement Questionnaire . Nicotine &
Tobacco Research , 5 , 711 – 718 . doi:10.1080/146222003100015
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Pontieri , F. E. , Tanda , G. , Orzi , F. , & Di Chiara , G. ( 1996 ).
Effects of nicotine on the nucleus accumbens and similarity to
those of addictive drugs . Nature , 382 , 255 – 257 . doi: 10.1038/
382255a0
Potenza , M. N. , Steinberg , M. A. , Mclaughlin , S. D. , Wu , R. ,
Rounsaville , B. J. , Krishnan-Sarin , S. , et al. ( 2004 ). Characteristics
7
Nicotine & Tobacco Research
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