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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.

  1. Contents
  2. Results
  3. How does the experience of severe adverse and other potential adverse consequences from gambling vary among those from different ethnic groups?

How does the experience of severe adverse and other potential adverse consequences from gambling vary among those from different ethnic groups?

This section references information that can be found in the ethnic group topic report findings excel files that accompany this report.

Of those who gambled in the past 4 weeks, experience of any severe adverse consequence, or potential adverse consequences relating to health, relationships or resources varied significantly by ethnic group overall. Participants from ethnic minority backgrounds reported higher rates of both potential and severe adverse consequences compared with those from White backgrounds. Potential health consequences were reported by 10.8% of those from White backgrounds who had gambled in the past 4 weeks, rising to 24.6% for those both from Mixed and/or Multiple ethnic backgrounds and Black backgrounds to 29% for those from Asian backgrounds, and 44.3% of those from Other ethnic backgrounds (as shown in Table 9 in the ethnic group topic report findings). This same pattern was observed for potential relationship and resource consequences with those from ethnic minority backgrounds experiencing consistently higher rates than those from White backgrounds (roughly 3 to 4 times as high) as shown in Figure 5. The prevalence of experiencing at least 1 severe adverse consequence was also substantially higher for those from ethnic minority backgrounds with 1.9% of those from White backgrounds reporting this, compared with 10.3% for those from Mixed and/or Multiple ethnic backgrounds, 11.7% for those from Asian backgrounds, 12.5% for those from Black backgrounds and 21.4% of those from Other ethnic backgrounds.

Figure 5: Reporting of adverse consequences among participants who gambled in the past 4 weeks, by ethnic group (percentage)

Figure 5: Reporting of adverse consequences among participants who gambled in the past four weeks, by ethnic group (percentage)

Figure 5: Reporting of adverse consequences among participants who gambled in the past 4 weeks, by ethnic group (percentage)
Consequence type White groups Mixed and/or Multiple ethnic groups Asian groups Black groups Other ethnic groups
Severe adverse consequence 1.9 10.3 11.7 12.5 21.4
Health consequence 10.8 24.6 29.0 24.6 44.3
Relationship consequence 7.9 24.9 26.5 24.5 36.4
Resource consequence 8.5 26.3 30.0 24.8 33.8

Base: Productive individuals who had gambled in the past 4 weeks. Participants within each ethnic group who gambled in the past 4 weeks (unweighted: White groups = 21,470; Mixed and/or Multiple ethnic groups = 454; Asian groups = 863; Black groups = 308; Other ethnic groups = 98).

This pattern was also observed when looking at those who had gambled on activities other than lottery draws in the past 4 weeks. Here, potential health, relationship and resource consequences affected around 1 in 3 participants from Mixed and/or Multiple ethnic backgrounds, Asian backgrounds, Black backgrounds and Other ethnic backgrounds, compared with around 1 in 6 of those from White backgrounds (as shown in Table 9 in the ethnic group topic report findings).

What explains the differences in adverse consequences?

A negative binomial model was used to further investigate the relationship between ethnicity and adverse consequences using the ‘overall harm’ score described in our methods section as the outcome variable. The unadjusted model (Model A; as shown in the following Table 2 and Table 10 in the ethnic group topic report findings) reflected the descriptive findings with participants from all ethnic minority backgrounds having significantly higher IRRs than those from White backgrounds, the baseline group. When socio-economic and demographic characteristics were included, the IRRs lowered but remained significantly higher than those from White backgrounds (Model B; as shown in the following Table 2 and Table 11 in the ethnic group topic report findings). A further adjusted model (Model C; as shown in the following Table 2 and Table 12 in the ethnic group topic report findings) controlling for participation across 21 distinct gambling activities attenuated (that is, lowered the IRRs further) but remained statistically significantly higher than participants from White backgrounds except for those from Black backgrounds. This indicates the increased rates of harm in those from Black backgrounds could be explained by differences in gambling participation, but this is not the case for those from Mixed and/or Multiple ethnic, Asian, and Other ethnic backgrounds.

Table 2: The unadjusted and adjusted model results for the association between ethnic group and ‘overall harm’ score.

Table 2: The unadjusted and adjusted model results for the association between ethnic group and ‘overall harm’ score
Ethnic group Incidence rate ratio Lower 95 percent confidence interval Upper 95 percent confidence interval
Model A: unadjusted
Mixed and/or Multiple ethnic groups 4.46 3.46 5.75
Asian groups 4.68 3.88 5.65
Black groups 4.22 2.84 6.28
Other ethnic groups 7.64 5.13 11.38
Model B: Adjusted for socio-economic and demographic characteristics
Mixed and/or Multiple ethnic groups 2.54 1.97 3.28
Asian groups 3.37 2.70 4.20
Black groups 2.77 1.76 4.36
Other ethnic groups 6.55 3.51 12.22
Model C: Adjusted for socio-economic, demographic characteristics and participation across 21 distinct gambling activities
Mixed and/or Multiple ethnic groups 1.92 1.43 2.58
Asian groups 2.81 2.32 3.40
Black groups 1.77 0.96 3.29
Other ethnic groups 4.72 1.92 11.61

Adverse consequences by Problem Gambling Severity Index (PGSI) category, by ethnic group

The previous sections have examined PGSI scores and adverse consequences by ethnic group separately, both showing elevated rates among those from ethnic minority groups. In this section we explore whether certain ethnic groups experience disproportionate potential adverse consequences at identical PGSI categories. To do this, we analysed the prevalence of experiencing at least one potential adverse consequence across PGSI categories. Among participants who had gambled in the past four weeks, experiencing an adverse consequence varied significantly by PGSI scores overall. The likelihood of experiencing an adverse consequence rose sharply with PGSI category for all ethnic groups, from around 3% at a PGSI score of 0 to over 90% at a score of 8 or more (as shown in Table 13 in the ethnic group topic report findings).

Within all PGSI categories, those from ethnic minority backgrounds consistently reported higher levels of experiencing at least one adverse consequence than participants from White backgrounds, with the largest differences observed at lower levels of gambling risk.

Looking at those with a PGSI score of 0 is informative here. These are people who have gambled in the past four weeks but not endorsed any of the PGSI items. However, 2.7% of those from White groups reported experiencing at least one adverse consequence whereas 10.6% of those from Asian groups or Other ethnic groups reported the same.

The same pattern occurred for those with PGSI scores of 1 to 2: 16.6% of participants from White backgrounds reported at least 1 adverse consequence, compared with 18.9% of participants from Mixed and/or Multiple ethnic backgrounds, 18.7% of those from Black backgrounds, 25.3% of those from Other ethnic backgrounds and 27.0% of those from Asian backgrounds. This is consistent with the Gambling Commission's earlier report Exploring demographic differences in adverse consequences from gambling, which found similar patterns of elevated harm among participants from ethnic minority groups at low PGSI scores.

Interestingly, at PGSI scores of 8 or more, this gap narrowed considerably, and rates were broadly similar across all ethnic groups (91.8% to 100%), with participants from White backgrounds (94.0%) sitting within this range (as shown in Figure 6).

Figure 6: Reporting of adverse consequences among those who gambled within the past 4-weeks by PGSI risk category and ethnic group (percentage)

Figure 6: Reporting of adverse consequences among those who gambled within the past 4-weeks by PGSI risk category and ethnic group (percentage)

Figure 6: Reporting of adverse consequences among those who gambled within the past 4-weeks by PGSI risk category and ethnic group (percentage))
PGSI category White groups Mixed and/or Multiple ethnic groups Asian groups Black groups Other ethnic groups
PGSI 0 2.7 7.2 10.6 7.0 10.6
PGSI 1 to 2 16.6 18.9 27.0 18.7 25.3
PGSI 3 to 7 51.5 61.4 59.1 60.7 61.2
PGSI score 8 or higher 94.0 100.0 93.5 91.8 100.0

Base: Productive individuals who had gambled in the past 4 weeks. Participants within each ethnic group who gambled in the past 4 weeks (unweighted: White groups = 21,436; Mixed and/or Multiple ethnic groups = 454; Asian groups = 861; Black groups = 305; Other ethnic groups = 99).

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How do Problem Gambling Severity Index (PGSI) scores vary by ethnic group?  
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How does the use of support services vary by ethnic group?  
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