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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.

Published
16 July 2026

Last updated
16 July 2026 - Changes

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  1. Contents
  2. Supplementary information

Supplementary information

Percentage of participants reporting potential adverse consequences, and severe consequences, by demographic group and Problem Gambling Severity Index (PGSI) category

Tables S1 and S2 show the percentage of participants who reported ‘one or more’ potential adverse consequences and any severe consequences from gambling6. Percentages are broken down by PGSI risk category (0, 1 to 2, 3 to 7, and 8 or more) and demographic group (ethnicity, household income, educational qualification, age, and sex).

Among those who scored 0 on the PGSI, potential adverse consequences were more prevalent among younger participants, males, people from ethnic minority backgrounds, those living in lower-income households, and among people who did not hold an educational qualification. Among people scoring 1 to 2 on the PGSI, similar differences were observed for ethnicity, income, and educational qualification. However, demographic differences in rates of potential adverse consequences were less pronounced among those scoring 3 to 7 and 8 or more on the PGSI (Table S1).

Across all PGSI categories, rates of severe consequences were higher among participants from ethnic minority backgrounds, compared with white participants. Participants in the highest PGSI risk category (PGSI 8 or more) were more likely to report severe consequences if they were living in lower income households, did not hold an educational qualification, and were male. Rates of severe consequences were similar for those aged under 35 and over 35 across all PGSI categories (Table S2).

References

6 Tables S1 and S2 are descriptive only; no statistical significance testing was conducted for these subgroup comparisons

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Conclusion - Exploring demographic differences in adverse consequences from gambling
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