Report
Gambling behaviour and harm among people from different ethnic groups
This report examines how gambling participation, gambling risk, adverse consequences and use of support services vary among people from different ethnic groups.
Summary
Key findings
Commensurate with prior research, this analysis showed that participants from White backgrounds were the most likely to gamble overall. However, analysis in this report shows that this difference is driven mainly by participation in lottery draws, with those from White backgrounds being substantially more likely to take part in lottery draws than other ethnic groups. When looking at gambling activities separately, participants from ethnic minority backgrounds had much higher participation in non-lottery draw activities compared to those from White backgrounds, in some cases, their rates of participation were up to 4 to 5 times higher than those from White groups. This pattern was broad rather than limited to 1 or 2 activities: 9 individual gambling activities showed higher participation among participants from all 4 ethnic minority backgrounds compared with those from White backgrounds, while only 2 showed lower participation. Those who gambled from ethnic minority groups also tended to take part in more forms of gambling activity than their counterparts from White backgrounds.
Given the increased propensity of those from ethnic minority groups to engage in a wider range of gambling activities, and in non-lottery draw activities, it was perhaps unsurprising that Problem Gambling Severity Index (PGSI) scores were also higher among these groups. These patterns held, and in some cases strengthened, when lottery draw-only participants were excluded, suggesting the findings were not simply a lottery draw effect. Regression models showed that participants from ethnic minority backgrounds had higher PGSI scores even when taking into account demographic, socio-economic characteristics and gambling participation. Whilst the strength of the relationship attenuated, these results suggest that some other, unmeasured, factor may be contributing to increased PGSI risk among people from different ethnic minority groups.
Commensurate with the patterns observed for PGSI scores, participants from ethnic minority backgrounds reported higher rates of potential adverse and severe adverse consequences, often 3 to 4 times higher than participants from White backgrounds. With the exception of those from Black backgrounds, regression models also showed this difference in gambling participation, demographic or socio-economic factors did not fully account for this. Furthermore, this gap was not consistent across all levels of risk: at low PGSI scores, participants from ethnic minority backgrounds reported substantially higher rates of experiencing at least 1 potential adverse consequence than White participants though this gap narrowed among those with PGSI scores of 8 or more, where experience of adverse consequences was the norm across all groups. Interestingly, around 7% to 10% of participants from ethnic minority groups who had gambled in the past 4 weeks and had a PGSI score of 0 reported experiencing at least 1 adverse consequence from gambling. This compares with 2.7% (about 1 in 37) for those from White backgrounds. This suggests participants from ethnic minority backgrounds may experience more harm at earlier stages of risk rather than uniformly across the whole spectrum. This is consistent with the Gambling Commission's earlier report, which similarly found a higher prevalence of harm among those from ethnic minority backgrounds at lower PGSI scores, with this gap narrowing at higher scores.
As would be expected given the findings in this report, there was higher support-seeking among participants from ethnic minority backgrounds. However, even among participants with a PGSI score of 3 or more roughly 3 in 4 had not sought any support, regardless of ethnic group, suggesting not everyone who needs help is seeking it.
Limitations
This report pooled together 3 years of the GSGB to get a large enough sample to look at the ethnic minority groups separately. Despite this, the sample size is relatively small, for example there was a total of 337 people from Other ethnic backgrounds compared to 43,809 people from White backgrounds. This impacts our confidence in the estimates as the sample could be more sensitive to outliers. The results of the modelling should be considered alongside the 95% confidence intervals which reflect the uncertainty associated with a smaller sample. Going forward, as more years of the GSGB are available, it would be ideal to repeat these analyses to check the results still stand with a larger sample.
When reporting on the adverse consequences we used a derived continuous variable in the models. This was done to get an understanding of the spectrum of harm (compared to using a binary variable) and was created following the scoring methodology used in the DSM-IV. However, we acknowledge that this derived variable assumes the potential adverse consequences are of equal consequence to each other (and the same for severe consequences), when this might not be the case. For example, having to reduce or cut back spending on everyday items such as food, bills, and clothing could be interpreted as less severe compared to having to use savings or increase use of credit, such as credit cards, overdrafts, and loans.
Implication for future research
This report highlights the importance of disaggregating the data on gambling participation by gambling activity. Only looking at headline figures of participation masks wider and varied patterns of gambling among people from different ethnic backgrounds. Whilst people from ethnic minority groups gamble less overall, those that do have an increased propensity to gambling on non-lottery draw based products and to gamble on a wider range of activities.
The models in this report could not fully explain the relationship between ethnic background and adverse consequences or PGSI scores. Since these models considered demographic and socio-economic characteristics, and gambling involvement, other unobserved factors must drive the higher levels of harm and elevated PGSI scores observed among those from ethnic minority backgrounds. Future research should focus on identifying the underlying mechanisms. This could involve qualitative research with those with lived experiences which could inform future data collection and analysis.
Previous sectionResults - Gambling behaviour and harm among people from different ethnic groups Next section
Appendix - Gambling behaviour and harm among people from different ethnic groups
Last updated: 27 October 2026
Show updates to this content
No changes to show.