Table 1 Summary of cross-sectional studies investigating the relationship between casino proximity and problem gambling

Baraboo, Wisconsin, United States

Study type: Cross-sectional study

Number of participants: 1394 patients

Problem gambling assessment method: South Oaks Gambling Screen (SOGS)

Patients attending the 3 primary care clinics were surveyed before meeting with the physician.

Findings: The prevalence of problem gambling (SOGS score ≥ 3) was identical, i.e., 6.2%, in all clinics, including Baraboo (experimental group) and two other control groups. The prevalence of pathological gambling (SOGS score ≥ 5) was higher in Baraboo, i.e., 4.0%, which was only 10 km from the nearest casino, compared with 1.4% and 2.7% in two control groups, but the differences were not significant after controlling for age and sex.

Comments: No link was established between casino proximity and prevalence of problem and pathological gambling.

Pasternak and Fleming, 1999

All states in United States

Study type: Cross-sectional study

Number of participants: 2631 adults, aged 18 or above.

Problem gambling assessment method: DSM-IV.

Respondents’ data were obtained from national telephone survey, and Census data was used for calculating the distance from respondent’s home to nearest casino establishment

Findings: The presence of a casino within 10 miles of the respondent’s home was positively related to problem gambling. Neighborhood disadvantage was positively related to frequency of gambling and problem gambling.

Comments: A correlation relationship was established between casino proximity and prevalence of problem gambling.

Welte, Barnes et al., 2004

114 counties and the City of St. Louis in Missouri, United States

Study type: Cross-sectional study

Number of participants: 6599 self excluders from Missouri casinos.

Problem gambling assessment method: Self-exclusion rate and self-exclusion addition among the population.

Self excluders’ information was obtained from Missouri Gaming Commission. Their demographic data was matched with the distance between participant’s home and nearest casino, and the number of casinos clustered with the closest casino.

Findings: Kansas City and its surrounding region had most casino locations in Missouri counties. The Western region around Kansas City was an epicenter of problem gambling. The number of self-exclusion enrollment increased during the first few years of Missouri self-exclusion program, followed by leveling-off during the later years. Besides, after two casinos were opened in Northern and Central regions, the two places had highest rate of self-excluders addition over total number of self-excluders, and the increase was with statistical significance.

Comments: The data suggested that number of self-exclusion enrollment and self-excluder addition rates, which were indirect indicators of problem gambling, was geographically clustered in the areas with more casinos.

LaBrie et al., 2007

Four medium-sized campuses, Ontario, Canada

Study type: Cross-sectional study

Number of participants: 1579 university students

Problem gambling assessment method: South Oaks Gambling Screen (SOGS).

The data were collected via a variety of administration methods, including mailed survey, survey in classroom settings, data collection from psychology research pool, and approaching students in public settings at the university

Findings: Compared with other universities far from a casino (control group), there were less no problem gambling group (34.0% vs. 66.0%), less mild gambling problem group (42.7% vs. 57.3%), similar moderate gambling group (48.1% vs. 51.9%), and more pathological gambling group (80.0% vs. 20.0%) among students in universities near to a casino (experimental group). Statistical significance, with p value of 0.00004, was achieved for a chi-square test with 2 (near to versus far from casino) x 4 (four levels of problem gambling) contingency table.

Comments: A positive link was established between casino proximity in respondents’ residing university and problem gambling among university students.

Adams et al., 2007

New Zealand

Study type: Cross-sectional study

Number of participants: 12529 respondents, aged 15 years or above.

Problem gambling assessment method: Two questions with dichotomous outcome variables developed to identify whether each respondent was a gambler or problem gambler (Lie/Bet questions).

The data was obtained from 2002/2003 New Zealand Health Survey. The finding was then correlated with geographical access to the closest gambling venue, i.e., travel distance to the nearest gambling venue along the road network

Findings: Compared with those living in the quartile of neighborhoods with the furthest access to a gambling venue, i.e., casino, residents living in the quartile of neighborhoods with the closest access were more likely to be a gambler (Adjusted Odds Ratio: 1.60, 95% CI: 1.20 to 2.15), and problem gambler (Adjusted Odds Ratio: 2.70, 95% CI: 1.03 to 7.05)

Comments: Casino proximity, in terms of distance between living location and nearest casino, was found to be a statistical significant risk factor for being a problem gambler.

Pearce et al., 2008

Quebec, Canada

Study type: 2 cross-sectional studies

Number of participants: 8842 and 5148 participants.

Problem gambling assessment method: South Oaks Gambling Screen (SOGS) and Canadian Problem Gambling Index (CPGI).

Gambling habits were surveyed, and were correlated with the driving distance between the nearest casino and home.

Findings: Positive links were established between casino proximity and gambling participation (at the provincial and Montreal levels) and expenditure (at the provincial level only). But there was no link between the current prevalence rate of problem gambling and casino proximity.

Comments: No link was established between casino proximity and prevalence of problem gambling.

Sevigny et al., 2008

Victoria, Australia

Study type: Cross-sectional study

Number of participants: 533 gaming venue employees (18-70 years old).

Problem gambling assessment method: Problem Gambling Severity Index (PGSI).

A 13-item questionnaire, including 5 items in physical accessibility, was used to survey the participants.

Findings: Casino table games did not have statistical significant relationship with physical accessibility in PGSI values, and gambling expenditure, but had a statistical significant relationship with physical accessibility in gambling frequency. Casino proximity is one of the criteria in physical accessibility of casino in this study.

Comments: No link was established between physical accessibility of casinos and prevalence of probable problem and pathological gambling.

Hing & Haw, 2009

All Australian states

Study type: Cross-sectional study

Number of participants: 303 participants (18-61 years old).

Problem gambling assessment method: Problem Gambling Severity Index (PGSI).

Scales in Accessible Retreat were used in survey. Accessible Retreat was related to the degree to which venues were enjoyed because they were geographically and temporally available and provided a familiar and anonymous retreat with few interruptions or distractions.

Findings: Accessible Retreat had 7 “convenience” items, covering different aspects of geographic, temporal and within-venue accessibility, and 5 “retreat” items, covering anonymity, lack of distractions, quietness, familiarity and perceived escape from life. Accessible Retreat was associated with stronger urges to gamble and gambling problems, indicating geographical and temporal availability had a role in PGSA.

Comments: A correlation was established between Accessible Retreat of casino and prevalence of problem gambling. However, the study did not provide further break down analysis in Accessible Retreat, in where casino proximity was measured in terms of “convenience”.

Moore et al., 2011