Report
Understanding the adverse consequences of gambling
This report presents secondary analysis of Year 2 (2024) GSGB data
Overlap between potential adverse consequences
Table 5 show the degree of overlap between different types of potential adverse consequences. Overall, 15 percent of participants who had gambled in the past 4 weeks reported at least one potential adverse consequence from their own gambling. Health-related adverse consequences were more frequently experienced in isolation (26.2 percent) compared to those related to resources (12.6 percent) and relationships (10.0 percent). Dual-domain overlaps were observed, with 7.3 percent reporting consequences to both health and resources, 7.3 percent reporting consequences to health and relationships, and 5.8 percent reporting both consequences to resources and relationships. Notably, over a quarter of individuals reported experiencing potential adverse consequences across all 3 domains, indicating a substantial degree of co-occurrence.
Table 5: Participants reporting each combination of potential adverse consequences from their own gambling.
Includes responses from participants who reported at least one potential adverse consequence (Unweighted base size = 1406).
Includes responses from participants who reported at least one adverse consequence (Unweighted base size = 1406).
| Potential adverse consequences | Participants reporting at least one adverse consequence (percentage) |
|---|---|
| Health | 26.2% |
| Resources | 12.6% |
| Relationships | 10.0% |
| Health, Resources | 7.3% |
| Health, Relationships | 7.3% |
| Relationships, Resources | 5.8% |
| Health, Resources, Relationships | 29.5% |
Severe adverse consequences
The following Tables 6a to 6e show the percentages of participants who reported severe consequences, within each socioeconomic category. Base includes participants who had gambled in the past 4 weeks. Percentages are weighted, and base size values are unweighted.
Table 6a: Participants reporting severe consequences, within the PGSI category.
| PGSI 0 (percentage) | PGSI 1 to 2 (percentage) | PGSI 3 to 7 (percentage) | PGSI 8 or more (percentage) | |
|---|---|---|---|---|
| Crime | 0.1% | 0.2% | 0.7% | 18.1% |
| Financial | 0.2% | 0.5% | 1.1% | 20.2% |
| Relationship | 0.2% | 0.4% | 3.0% | 30.4% |
| Violence | 0.1% | 0.6% | 1.0% | 18.0% |
| Base size | 7,065 | 1,322 | 468 | 326 |
Table 6b: Participants reporting severe consequences, within the equivalised household income quintile category.
| Lowest quintile (percentage) | Second quintile (percentage) | Third quintile (percentage) | Fourth quintile (percentage) | Highest quintile (percentage) | |
|---|---|---|---|---|---|
| Crime | 2.6% | 1.0% | 0.5% | 0.3% | 0.3% |
| Financial | 2.9% | 1.7% | 0.5% | 0.4% | 0.6% |
| Relationship | 4.4% | 2.3% | 1.4% | 0.7% | 0.4% |
| Violence | 2.3% | 1.4% | 0.8% | 0.4% | 0.7% |
| Base size | 1,872 | 1,930 | 1,423 | 1,827 | 1,747 |
Table 6c: Participants reporting severe consequences, within the ethnicity category.
| White (percentage) | Mixed (percentage) | Asian (percentage) | Black (percentage) | |
|---|---|---|---|---|
| Crime | 0.6% | 3.2% | 2.5% | 4.5% |
| Financial | 0.7% | 5.5% | 5.7% | 5.8% |
| Relationship | 1.3% | 7.3% | 7.1% | 3.9% |
| Violence | 0.8% | 1.8% | 3.9% | 3.1% |
| Base size | 8,467 | 175 | 336 | 120 |
Table 6d: Participants reporting severe consequences, within the sex category.
| Male (percentage) | Female (percentage) | |
|---|---|---|
| Crime | 1.4% | 0.6% |
| Financial | 1.8% | 0.7% |
| Relationship | 2.6% | 1.2% |
| Violence | 1.4% | 0.8% |
| Base size | 4,770 | 4,417 |
Table 6e: Participants reporting severe consequences, within the age group category.
| 18 to 24 (percentage) | 25 to 34 (percentage) | 35 to 44 (percentage) | 45 to 54 (percentage) | 55 to 64 (percentage) | 65 to 74 (percentage) | 75 and over (percentage) | |
|---|---|---|---|---|---|---|---|
| Crime | 3.7% | 1.8% | 1.5% | 0.5% | 0.1% | 0.4% | 0.0% |
| Financial | 4.1% | 2.7% | 1.4% | 0.8% | 0.6% | 0.0% | 0.2% |
| Relationship | 6.4% | 3.5% | 2.1% | 1.5% | 0.9% | 0.2% | 0.2% |
| Violence | 3.9% | 2.4% | 1.3% | 0.7% | 0.4% | 0.1% | 0.2% |
| Base size | 438 | 1,359 | 1,592 | 1,513 | 1,799 | 1,592 | 906 |
Regression model results, for each type of severe consequence, are described below. Due to the low number of ethnic minority participants reporting each severe consequence, we combined Black, Asian, Mixed race and Other ethnic groups within a single ‘BAME’ category to maximise statistical power and ensure stable model estimates. For brevity, we describe findings from step 2 of each model (that is, after controlling for the number of gambling activities played), however odds ratios and 95 percent confidence intervals from steps 1 and 2 are provided in Tables 7 to 10.
Financial consequences
Females and older participants had significantly lower odds of experiencing severe consequences to finances. The odds of experiencing severe financial consequences were 4.6 times higher amongst BAME participants, relative to White participants, and were significantly higher amongst those in the lowest income quintile (that is, quintile 1), compared with those in quintiles 3 to 5 as shown in Table 7.
Table 7: Odds ratios from logistic regression model predicting severe financial consequences due to gambling.
95 percent confidence intervals are provided in parentheses. Demographic variables were entered into step 1 of the model, and the ‘number of gambling activities played in the past 4 weeks’ was included in step 2. Analysis includes participants who had gambled in the past 4 weeks.
| Odds Ratio (Step 1) | Odds Ratio (Step 2) | Base size | |
|---|---|---|---|
| Age | 0.95* (0.94-0.97) | 0.96* (0.95-0.98) | 9,199 |
| Equivalised income | |||
| Lowest quintile | n/a | n/a | 1,872 |
| Second quintile | 0.79 (0.51-1.24) | 0.94 (0.59-1.49) | 1,930 |
| Third quintile | 0.25* (0.11-0.53) | 0.31* (0.14-0.67) | 1,423 |
| Fourth quintile | 0.21* (0.10-0.45) | 0.29* (0.13-0.62) | 1,827 |
| Highest quintile | 0.23* (0.12-0.47) | 0.33* (0.16-0.67) | 1,747 |
| Ethnicity | |||
| White | n/a | n/a | 8,467 |
| BAME | 5.29* (3.60-7.76) | 4.64* (3.12-6.92) | 175 |
| Sex | |||
| Male | n/a | n/a | 4,770 |
| Female | 0.44* (0.29-0.66) | 0.48 * (0.31-0.74) | 4,417 |
Relationship Breakdown
Females and older participants had reduced odds of experiencing relationship breakdown due to gambling. Compared to White participants, the odds of experiencing relationship breakdown were 2.9 times higher amongst BAME participants. Participants in higher income quintiles (that is, quintiles 2 to 5) had significantly lower odds of experiencing relationship breakdown compared to those in the lowest quintile (quintile 1) as shown in Table 8.
Table 8: Odds ratios from logistic regression model predicting relationship breakdown due to gambling.
95 percent confidence intervals are provided in parentheses. Demographic variables were entered into step 1 of the model, and the ‘number of gambling activities played in the past 4 weeks’ was included in step 2. Analysis includes participants who had gambled in the past 4 weeks.
| Odds Ratio (Step 1) | Odds Ratio (Step 2) | Base size | |
|---|---|---|---|
| Age | 0.96* (0.94-0.97) | 0.97* (0.95-0.98) | 9,199 |
| Equivalised income | |||
| Lowest quintile | n/a | n/a | 1,872 |
| Second quintile | 0.69 (0.47-1.00) | 0.79 (0.53-1.18) | 1,930 |
| Third quintile | 0.39* (0.24-0.64) | 0.50* (0.30-0.84) | 1,423 |
| Fourth quintile | 0.18* (0.10-0.34) | 0.25* (0.13-0.48) | 1,827 |
| Highest quintile | 0.10 * (0.05-0.22) | 0.15* (0.07-0.32) | 1,747 |
| Ethnicity | |||
| White | n/a | n/a | 8,467 |
| BAME | 3.36* (2.42-4.65) | 2.86* (2.02-4.06) | 175 |
| Sex | |||
| Male | n/a | n/a | 4,770 |
| Female | 0.46* (0.33-0.65) | 0.52* (0.37-0.74) | 4,417 |
Violence
Older age was significantly associated with reduced odds of experiencing violence. BAME participants had 2.2 times higher odds of experiencing violence due to their gambling compared with White participants. Participants in the fourth income quintile (60 to 80 percent of the income distribution) had odds of experiencing violence that were almost two-thirds lower than those in the lowest quintile. No significant differences were observed for participants in quintiles 2, 3, and 5. There was no significant association between sex and experiencing violence due to gambling as shown in Table 9.
Table 9: Odds ratios from logistic regression model predicting violence due to gambling.
95 percent confidence intervals are provided in parentheses. Demographic variables were entered into step 1 of the model, and the ‘number of gambling activities played in the past 4 weeks’ was included in step 2. Analysis includes participants who had gambled in the past 4 weeks.
| Odds Ratio (Step 1) | Odds Ratio (Step 2) | Base size | |
|---|---|---|---|
| Age | 0.95* (0.94-0.96) | 0.96* (0.95-0.98) | 9,199 |
| Equivalised income | |||
| Lowest quintile | n/a | n/a | 1,872 |
| Second quintile | 0.83 (0.51-1.34) | 1.05 (0.63-1.76) | 1,930 |
| Third quintile | 0.43* (0.22-0.83) | 0.63 (0.32-1.26) | 1,423 |
| Fourth quintile | 0.23* (0.10-0.50) | 0.38* (0.17-0.84) | 1,827 |
| Highest quintile | 0.33* (0.17-0.64) | 0.57 (0.28-1.15) | 1,747 |
| Ethnicity | |||
| White | n/a | n/a | 8,467 |
| BAME | 2.94* (1.94-4.45) | 2.16* (1.37-3.39) | 175 |
| Sex | |||
| Male | n/a | n/a | 4,770 |
| Female | 0.60* (0.40-0.90) | 0.74 (0.48-1.14) | 4,417 |
Crime
Older age and being female were significantly associated with lower odds of experiencing gambling-related crime. The odds of experiencing crime due to gambling were 2.7 times higher among BAME participants, than among White participants. Participants in higher income quintiles (quintiles 3 to 5) had significantly lower odds of experiencing crime relative to those in the lowest quintile as shown in Table 10.
Table 10: Odds ratios from logistic regression model predicting crime due to gambling.
95 percent confidence intervals are provided in parentheses. Demographic variables were entered into step 1 of the model, and the ‘number of gambling activities played in the past 4 weeks’ was included in step 2. Analysis includes participants who had gambled in the past 4 weeks.
| Odds Ratio (Step 1) | Odds Ratio (Step 2) | Base size | |
|---|---|---|---|
| Age | 0.95* (0.93-0.96) | 0.96* (0.95-0.98) | 9,199 |
| Equivalised income | |||
| Lowest quintile | n/a | n/a | 1,872 |
| Second quintile | 0.49* (0.29-0.85) | 0.58 (0.33-1.02) | 1,930 |
| Third quintile | 0.23* (0.10-0.51) | 0.32* (0.14-0.73) | 1,423 |
| Fourth quintile | 0.16* (0.07-0.38) | 0.25* (0.10-0.60) | 1,827 |
| Highest quintile | 0.12* (0.05-0.31) | 0.19* (0.07-0.51) | 1,747 |
| Ethnicity | |||
| White | n/a | n/a | 8,467 |
| BAME | 3.59* (2.32-5.55) | 2.70* (1.68-4.33) | 175 |
| Sex | |||
| Male | n/a | n/a | 4,770 |
| Female | 0.44* (0.27-0.70) | 0.49* (0.30-0.81) | 4,417 |
Overlap of severe consequences
Table 11 shows the percentage of participants reporting each type of severe consequence, both on its own and in combination with other types. Overall, 2.1 percent of participants who had gambled in the past 4 weeks reported at least one severe consequence from their own gambling. Relationship breakdown was most commonly experienced in the absence of other severe consequences (31 percent), while fewer participants experienced severe financial consequences, violence, and crime in isolation, accounting for 11.4 percent, 6.6 percent, and 6.2 percent of cases, respectively. Over 8 percent of participants who reported severe consequences from gambling had experienced all 4 types.
Table 11: Participants reporting each combination of severe consequences from their own gambling.
Includes responses from participants who reported at least one severe consequence (Unweighted base size = 195).
| Severe consequences | Participants reporting at least one severe consequence (percentage) |
|---|---|
| Relationship | 31.4% |
| Finance | 11.4% |
| Finance, relationship, violence, crime | 8.1% |
| Violence | 6.6% |
| Crime | 6.2% |
| Finance, relationship | 6.1% |
| Relationship, violence, crime | 5.1% |
| Finance, violence, crime | 5.1% |
| Finance, violence | 4.8% |
| Relationship, crime | 3.5% |
| Relationship, violence | 3.5% |
| Finance, crime | 2.9% |
| Finance, violence | 2.8% |
| Violence, crime | 1.7% |
| Finance, relationship, crime | 0.9% |
Understanding the adverse consequences of gambling - Results Next section
Understanding the adverse consequences of gambling - Discussion
Last updated: 2 October 2025
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