Report
Exploring demographic differences in adverse consequences from gambling
Examining whether associations between 'at-risk' gambling behaviour (measured using the PGSI) and adverse consequences vary across demographic groups.
Results
The sample consisted of 12,194 participants who had gambled in the past 12 months. Of these, 11.7 percent reported ‘one or more’ potential adverse consequences, 2.7 percent reported severe consequences from gambling, and 2.3 percent reported both potential and severe adverse consequences. The most frequently reported consequences were ‘reducing or cutting back spending on everyday items’ (55.2 percent), ‘lying to family or others’ (50.4 percent), and using savings or increased use of credit (50.0 percent). Among those reporting severe consequences (n=138), 64.2 percent reported ‘relationship breakdown’, 39.8 percent reported ‘losing something of significant financial value’, 42.8 percent reported ‘violence or abuse’, and 33.1 percent said that they had ‘committed a crime’ due to gambling.
Among participants who scored 0 on the Problem Gambling Severity Index (PGSI) (categorised as ‘non-problem gambling’) (n=9,747), 3.6 percent reported ‘one or more’ potential adverse consequences from gambling. Among those scoring 8 or above on the PGSI (categorised as problem gambling) (n=335), 92.7 percent reported ‘one or more’ potential adverse consequences. Tables showing the percentage of participants reporting adverse consequences from gambling, by PGSI score and demographic group, are provided in supplementary material (Table S1 and Table S2).
Potential adverse consequences
After controlling for PGSI scores and other demographic characteristics, the odds of reporting ‘one or more’ potential adverse consequences were significantly higher among participants aged under 35, people from ethnic minority backgrounds, and those living in lower-income households, compared with their respective comparison groups4. The association with age and ethnicity varied by PGSI score: differences between groups were most pronounced among those scoring lower on the PGSI, and reduced as PGSI scores increased.
The odds of reporting potential adverse consequences did not differ between male and female participants, or between those with and without an educational qualification. Results from the regression analysis can be found in supplementary Table S3.
Predicted probability of potential adverse consequences by PGSI score and demographic group
Table 1 shows the predicted probability of reporting potential adverse consequences at PGSI scores of 1, 3 and 8, by ethnicity, household income, and age. These scores were selected as anchor points because they correspond to conventional thresholds used to classify gambling risk (PGSI scores of 1, 3 and 8 represent the lower bound of ‘low-risk’, ‘moderate risk’, and ‘problem gambling’ categories, respectively).
At a PGSI score of 1, participants from ethnic minority backgrounds were more than twice as likely as White participants to report potential adverse consequences from gambling (11.8 percent compared with 5.5 percent). This difference became less pronounced as PGSI scores increased: at a score of 3, participants from ethnic minority backgrounds were 1.3 times more likely than White participants to report potential adverse consequences (32.3 percent compared with 24.0 percent), and at a PGSI score of 8 this pattern was no longer observed (see Table 1 and Figure 1).
Similarly, participants aged under 35 had higher predicted probability of potential adverse consequences at a PGSI score of 1, compared with those aged 35 and over (7.5 percent compared with 5.5 percent). This difference was not observed at PGSI scores of 3 or 8.
For those scoring 1 or 3 on the PGSI, the predicted probabilities of potential adverse consequences were slightly higher among participants in lower-income households, compared with those in higher-income households (6.4 percent compared with 5.5 percent at PGSI = 1; 25.5 percent compared with 24.1 percent at PGSI = 3). These differences were no longer observed at a PGSI score of 8.
Figure 1: Predicted probability of reporting ‘one or more’ potential adverse consequences for White and Ethnic minority participants from PGSI scores 0 to 10
Dashed reference lines show values at PGSI = 1 (low risk), PGSI = 3 (moderate risk), and PGSI = 8 (problem gambling).
The graph presents results for Ethnicity shown in Table 1.
Table 1: Predicted probability of reporting ‘one or more’ potential adverse consequences at PGSI = 1 (low risk), PGSI = 3 (moderate risk) and PGSI = 8 (problem gambling), by demographic group
| Demographic group | Probability at PGSI = 1 (percentage) | Probability at PGSI = 3 (percentage) | Probability at PGSI = 8 (percentage) |
|---|---|---|---|
| Ethnicity | |||
| Ethnic minority | 11.8% | 32.3% | 91.9% |
| White | 5.5% | 24.1% | 95.6% |
| Household income quintile | |||
| Higher income (third quintile or above) | 5.5% | 24.1% | 95.6% |
| Lower income (second quintile or below) | 6.4% | 25.5% | 94.0% |
| Age | |||
| 35 years and over | 5.5% | 24.1% | 95.6% |
| Under 35 years | 7.5% | 24.0% | 90.4% |
Severe consequences
After adjusting for PGSI scores and other demographic characteristics, the odds of reporting severe consequences from gambling were significantly higher among participants from ethnic minority backgrounds, those living in lower-income households, and those aged under 35, compared with their respective comparison groups (such as White ethnicity, participants living in higher-income households, and aged 35 years or older)5. The odds of reporting severe consequences did not differ by sex or educational qualification. There were also no significant interactions between PGSI score and any demographic characteristics, indicating that between-group differences did not increase or decrease across varying levels of gambling risk.
Results from regression analyses can be found in supplementary Table S4.
Predicted probability of severe consequences by PGSI score and demographic group
Table 2 shows the predicted probability of severe consequences from gambling at PGSI scores of 3 and 8, by ethnicity, household income, and age. Results for household income are also shown in Figure 2.
At a PGSI score of 3, participants from ethnic minority backgrounds were 3.5 times more likely to report severe consequences, compared with White participants (2.4 percent, compared with 0.7 percent).
The predicted probability of severe consequences was over 2 times higher for those in lower income households, and 1.7 times higher for younger participants, compared with those in higher income households and older participants, respectively (Lower income: 1.5 percent; Higher income: 0.7 percent; Aged under 35: 1.2 percent; Aged 35 and over: 0.7 percent).
Similar between-group differences were observed at a PGSI score of 8.
Figure 2: Predicted probability of reporting severe consequences for people living in higher and lower income households across PGSI scores of 0 to 10
Dashed reference lines show values at PGSI = 3 (moderate risk) and PGSI = 8 (problem gambling).
The graph presents results for Household income shown in Table 2.
Table 2: Predicted probability of reporting severe adverse consequences at PGSI = 3 (moderate risk) and PGSI = 8 (problem gambling), by demographic group
| Demographic group | Probability at PGSI = 3 (percentage) | Probability at PGSI = 8 (percentage) |
|---|---|---|
| Ethnicity | ||
| Ethnic minority | 2.4% | 9.0% |
| White | 0.7% | 3.0% |
| Household income quintile | ||
| Higher income (third quintile or above) | 0.7% | 3.0% |
| Lower income (second quintile or below) | 1.5% | 6.9% |
| Age | ||
| 35 years and over | 0.7% | 3.0% |
| Under 35 years | 1.2% | 4.0% |
References
4 Reference categories were female, age 35 years or older, higher household income (quintile 3 or above), White ethnicity, and has an educational qualification.
5 Some subgroup analyses, particularly for severe consequences (Table S2) and corresponding regression estimates (Table S4), are based on relatively small cell counts. These estimates should therefore be interpreted with caution, as reflected in wider confidence intervals.
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Discussion - Exploring demographic differences in adverse consequences from gambling
Last updated: 16 July 2026
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