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Exploring the relationship between gambling activities and Problem Gambling Severity Index (PGSI) scores

This report explores the relationship between participation in individual gambling activities in the past 12 months and Problem Gambling Severity Index Scores (PGSI).

Published
30 January 2025

Last updated
6 February 2025 - Changes

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  1. Contents
  2. Methods

Methods

To explore this, 3 binary logistic regression models were run for each of the 18 commercial gambling activities undertaken in the past 12 months. For each model, the outcome variable was whether someone had a PGSI score of 8 or more.

Model 1:

Unadjusted binary logistic regression model. This shows the odds of having a PGSI score of 8 or more among those taking part in each individual activity (see Table 1 in the Excel file).

Model 2:

Adjusted binary logistic regression model. This shows the odds of having a PGSI score of 8 or more among those taking part in each activity, with the number of other gambling activities undertaken in the past 12 months and the highest frequency of gambling across any activity also entered into the model. If a gambling activity remains significant in this model, it means the association persists even after the broader gambling involvement is taken into account, separating out the impact of the activity from an individual’s overall gambling (Table 2 in the Excel file).

Model 3:

Further adjusted model. This repeats model 2 but also includes the following variables: age, sex, education level, employment status, household income quintile, area deprivation, marital status and ethnicity, all of which have been previously identified as being associated with PGSI scores. As with model 2, if a gambling activity remains significant in the further adjusted model, it means the association persists even after the broader gambling involvement and other factors are taken into account, separating out the impact of the activity from an individual’s overall gambling and their demographic and economic characteristics (Table 3 in the Excel file).

All logistic regression models were based on those who had gambled in the past 12 months to identify differences among those who gamble.

Results from logistic regression models are presented as odds ratios. Results for each activity are interpreted relative to a reference category. Those who did not gamble on a specific activity are given a reference of 1, and the odds ratios for those who did gamble on this activity are interpreted relative to this group. This shows whether odds ratios are higher or lower among those that gambled on this activity than those who did not (but did gamble on other things). An odds ratio of more than 1 indicates higher odds of having PGSI score of 8 or more, an odds ratio of less than 1 indicates lower odds of having a PGSI score of 8 or more. Confidence intervals at the 95 percent level (95 percent CI) for each odds ratio are also shown. If this confidence interval does not include 1, there is a significant association between the gambling activity being considered and having a PGSI score of 8 or more.

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PGSI Report - Results
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