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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.

  1. Contents
  2. Discussion

Discussion

This report presents secondary analysis of 2025 Gambling Survey for Great Britain (GSGB) data to examine whether some people may be particularly susceptible to gambling-related harm at lower levels of gambling risk (as measured using the Problem Gambling Severity Index (PGSI)). After controlling for other demographic characteristics and PGSI scores, we found that participants from ethnic minority backgrounds, those living in lower-income households, and younger participants were more likely to report both potential and severe adverse consequences than their respective comparison groups. For potential adverse consequences, differences by ethnicity and age were most pronounced at lower PGSI scores and reduced as scores increased. For severe consequences, between-group differences were broadly similar across the PGSI scale.

These findings reflect an important distinction between at-risk gambling behaviour, which is captured by the PGSI, and the consequences that people experience. Although higher PGSI scores are generally associated with increased risk of harm, the strength of this association depends on people's wider social and financial circumstances. Relying on PGSI scores alone is likely to mask important differences in vulnerability across the population, and so using a range of markers of harm may help gambling operators identify and support people who are most at risk.

Our findings align with previous research showing that people on lower incomes and those from ethnic minority backgrounds experience harm at comparatively lower levels of gambling frequency and spend (Raybould, Larkin and Tunney, 2021 (opens in new tab); Wheaton, Collard and Nairn, 2024 (opens in new tab)). The increased risk of harm in these groups can be partly explained by differences in financial resilience, stigma, and barriers to accessing support. For example, people on lower incomes may have reduced capacity to absorb financial losses. There is also evidence that gambling is more stigmatised within some ethnic minority communities, which could contribute to harm and discourage people from seeking support (Wheaton, Collard and Nairn, 2024 (opens in new tab)).

Finally, results from this secondary analysis are consistent with the 'prevention paradox' of gambling-related harm, which states that, at a population level, a substantial proportion of harm arises among people who are not classified as high risk (Browne and Rockloff, 2018 (opens in new tab)). Our findings show that only a small proportion of people who scored 0 on the PGSI (categorised as 'non-problem' gambling) reported adverse consequences from gambling. However, because most people who gambled in the past 12 months scored 0 on the PGSI, this group may still account for a meaningful share of gambling-related harm overall. This highlights the need to ensure that harm prevention strategies reach the wider population of people who gamble, rather than focusing solely on those identified as higher risk.

Limitations

Several limitations should be considered when interpreting these findings. Firstly, the analysis draws on cross-sectional data and so we are unable to establish causal relationships between demographic characteristics, PGSI scores, and adverse consequences. Longitudinal research is needed to clarify the direction of these associations and the pathways through which harm develops over time. Secondly, due to low base sizes, participants from ethnic minority backgrounds were grouped within a single category, which is likely to have masked meaningful group differences in gambling behaviour and experiences of harm. We plan to address this in future work by pooling GSGB data across Years 1 to 3 to examine gambling behaviour and adverse consequences among individual ethnic groups.

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Results - Exploring demographic differences in adverse consequences from gambling
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Conclusion - Exploring demographic differences in adverse consequences from gambling
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