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Gambling Survey for Great Britain Year 2 topic report: Investigating the profiles of those who gamble more frequently
This topic report uses data from Year 2 of the GSGB to explore the association between engagement in gambling activities, frequency of gambling, and risk.
Published: 2 October 2025
Last updated: 2 October 2025
This version was printed or saved on: 23 October 2025
Online version: https://www.gamblingcommission.gov.uk/report/gambling-survey-for-great-britain-year-2-topic-report-investigating-the
Executive Summary
This Topic Report uses data from Year 2 of the Gambling Survey for Great Britain (GSGB) to explore the association between engagement in gambling activities, frequency of gambling, and risk. It is an extension of the GSGB Year 1 analysis, published in February 2025, that showed, irrespective of someone’s wider engagement in gambling or their demographic profile, there is a significant association between past year engagement in some activities and scoring eight or more on the Problem Gambling Severity Index (PGSI). The Year 2 data allows this relationship to be investigated further; the extended list of activities permit a degree of granularity not possible with any previous gambling survey, for example, through the inclusion of in-play betting as a separate activity, and the larger base sizes allow more detailed analyses than possible in Year 1.
Key findings
There are notable differences in the profiles of people by frequency of gambling and gambling activity. People who gamble weekly but only on lottery draws tend to be older, married, owner-occupiers. People who gamble weekly on any activity, including lottery draws, are more likely to live in more deprived areas, have fewer qualifications and live in housing association accommodation.
There is a strong association between the frequency of specific activities, the type of activity, and Problem Gambling Severity Index (PGSI) scores. PGSI scores measure behavioural symptoms of gambling disorder and certain adverse consequences from gambling. People who gamble weekly on any activity have higher PGSI scores than those who gamble weekly but on lottery draws only. However, people who gamble more frequently, weekly or more often, have higher PGSI scores than those who gamble less frequently.
When looking at weekly participation in gambling activities in turn, there is evidence that weekly participation in fruits and slots in person, in-play betting, but also betting on non-sports events online and other non-National Lottery scratch cards are all associated with higher PGSI scores.
Sports betting on a weekly basis, once in-play betting was excluded, was not significantly related to PGSI scores. However, there was a strong association between weekly in-play betting (either online or in-person) and higher PGSI scores, suggesting the rapid rewards and continuous play connected with this activity is associated to higher PGSI scores.
Definitions
Past 4 weeks gambling
Participants who had participated in any gambling activity in the past 12 months were then asked if they had taken part in the same gambling activity or activities within the past 4 weeks. Participants who answered yes to one or more gambling activity are described in this report as participating in gambling in the past 4 weeks.
Past 12 months gambling
Participants were provided with a list of 18 types of gambling legally available in Great Britain and asked which of these activities they had participated in, in the past 12 months. They were also asked about any private betting or gambling they may have done in the same period. Participants who answered yes to participating in one or more gambling activity are described in this report as participating in gambling in the past 12 months.
Frequency of gambling
Everyone who had gambled on a particular activity in the past 12 months was then asked to report how often, if at all, they had gambled on this activity in the past 4 weeks. Using this information, frequency of gambling was computed for each participant based on their reported highest frequency of gambling to any activity in the past 4 weeks. For example, if a participant reported purchasing National Lottery tickets once a week but bet on sports events a few times a week, they were categorised as gambling a few times a week. Response categories were: everyday, a few times a week, about once a week, about once a fortnight, about once in the past 4 weeks, and less often than this (that is those who had gambled in the past 12 months, but not in the past four weeks).
Full list of gambling activities
The list of gambling activities presented to participants was refined and tested during the development stages of the Gambling Survey for Great Britain (GSGB). The aim was to update the list used in previous surveys to better represent forms of commercial gambling currently available in Great Britain, and to better capture engagement in different online gambling formats. The Appendix shows the full list of gambling activities asked about for the past 12 months. Whether a participant had bet in-play was only asked about within the past 4 weeks.
Problem Gambling Severity Index
The PGSI consists of nine questions and is asked of everyone who had gambled in the past 12 months, capturing the current experience of each of these items. Answer options were ‘almost always’, ‘most of the time’, ‘sometimes’, and ‘never’. Responses to the nine questions are summed and a score ranging between 0 and 27 is computed. Scores are grouped into the following categories:
PGSI score 0
Representing a person who gambles (including heavily) but who does not report experiencing any of the nine symptoms or adverse consequences asked about. In population prevalence analysis, participants who had not gambled in the past 12 months are also given a PGSI score of 0.
PGSI score 1 to 2
Representing low risk gambling by which a person is unlikely to have experienced any adverse consequences from gambling but may be at risk if they are heavily involved in gambling.
PGSI score 3 to 7
Representing moderate risk gambling by which a person may or may not have experienced adverse consequences from gambling but may be at risk if they are heavily involved in gambling.
PGSI score 8 or higher
Representing ‘problem gambling’ by which a person will have experienced adverse consequences from their gambling and may have lost control of their behaviour. Involvement in gambling can be at any level, but is likely to be heavy.
Introduction
This topic report is published alongside the second annual report from the Gambling Survey for Great Britain (GSGB). Further details about the survey methodology including its strengths and limitations are provided in the GSGB Technical report.
This topic report is based on Year 2 data from the GSGB, collected in 2024. It is an extension of the analysis published in February 2025 that used Year 1 (2023) data to explore the association between gambling activities, frequency, and risk. The Year 1 (2023) report showed that, irrespective of someone’s wider engagement in gambling or their demographic profile, a significant association between past year engagement in some activities and scoring eight or more on the PGSI remained, Specifically, non-National Lottery (NL) scratch cards and instant win games, betting on sports and/or racing in person, betting on the outcome of events, all types of casino games, and fruit and slot machines. The report also showed how gambling involvement, measured by the number of activities and frequency of gambling, remained important predictors of scoring eight or more on the PGSI alongside engagement in each of these specific activities. Because of sample sizes, analysis within the Year 1 (2023) topic report looked at those who had gambled on any activity in the past 12 months, meaning that those who gambled very occasionally and those who gambled very frequently were included in the same groups. For those reasons, the Year 1 (2023) report recommended examining further the relationship between engagement in specific activities and Problem Gambling Severity Index1 (PGSI) scores among those who gamble more frequently. The larger base sizes available in Year 2 (2024) coupled with the extended list of activities available in the GSGB allow this relationship to be investigated further, permitting a degree of granularity that was not possible at Year 1 (2023). For example, through the inclusion of in-play betting as a separate activity.
Gambling involvement
Gambling involvement can be measured by expenditure (measured by losses or net spend as a proportion of income), frequency (how often an individual takes part in gambling activities), duration (how long an individual spends in a typical session when gambling), and range (the number of different gambling activities an individual takes part in). There is a known relationship between higher levels of gambling involvement and higher levels of gambling harms 23. In 2010, the Australian Productivity Commission noted that population focus on the determinants of gambling harms can be misleading for policy purposes, as this includes those who gamble very infrequently, and recommended that policy evidence focus on those who gamble frequently instead.
This report takes a deeper dive look at those who gamble frequently, defined here as people who reported gambling at least weekly in the past four weeks. This definition of frequency ties in with the recommended frequency thresholds identified by the Lower-Risk Gambling Guidelines4. This is a set of guidelines, developed by the Canadian Centre on Substance Use and Addiction using data from a range of countries5, that sets out suggested limits on gambling frequency, expenditure, and number of activities with the intention of reducing an individual’s risk from gambling harms. Whilst the UK was excluded in the development, there is evidence suggesting they could also act as a suitable guide to gambling in England6 and potentially the UK. The Lower-Risk Gambling guidelines suggest an individual should gamble no more than four times in a month, roughly equating to once a week. By focusing on weekly activity this report therefore provides insight into a group of people deemed by the guidelines to have a higher probability of harms.
In this report we compare the profiles of people who have different levels of gambling frequency. We then look at the association between weekly gambling on certain product types and Problem Gambling Severity Index (PGSI) scores.
1 The Problem Gambling Severity Index (PGSI) consists of 9 items which measure both behavioural symptoms of gambling disorder and certain adverse consequences from gambling.
2 Rossow, I., 2019. The total consumption model applied to gambling: Empirical validity and implications for gambling policy. Nordic Studies on Alcohol and Drugs, 36(2), pp.66-76.
3 Kesaite V., Wardle H. and Rossow I. (2023) Gambling consumption and harm: a systematic review of the evidence; Addiction Research & Theory (opens in new tab).
4 The Lower-Risk Gambling Guidelines (opens in new tab)
5 Currie, S.R. and Low Risk Gambling Guidelines Scientific Working Group: Currie Shawn Flores-Pajot Marie-Claire Hodgins David (co-chair) Nadeau Louise Paradis Catherine Robillard Chantal Young Matthew (co-chair), 2019. A research plan to define Canada’s first low-risk gambling guidelines. Health promotion international, 34(6), pp.1207-1217.
6 Rochester, E., Cunningham, J.A. Applying the Canadian Low-Risk Gambling Guidelines to Gambling Harm Reduction in England. J Gambl Stud 40, 21–28 (2024) (opens in new tab).
Gambling frequency groups
The GSGB contains detailed questions identifying the frequency by which people gambled on different product types over the past 4 weeks. The response options include ‘every day’, ‘a few times a week’, ‘about once a week’, ‘about once a fortnight’, ‘about once’, and ‘not in the past 4 weeks’.
These questions were used to group survey participants into 4 categories:
Those who had gambled at least weekly in the past 4 weeks on any activity in addition to National Lottery or charity lottery draws, either online or in-person.
Those who had gambled at least weekly in the past 4 weeks but only on National Lottery or charity lottery draws, either online or in-person.
3, Those who had gambled on any activity, either online or in person, less frequently than weekly but within the past 4 weeks.
- Those who had gambled on any activity, either online or in person, less frequently than the past 4 weeks but within the past 12 months.
The first of these groups includes people who took part in a lottery draw at least weekly but only if they did so in addition to another activity. This group will be referred to throughout this report as ‘weekly gambling on any activity or activities in addition to lotteries ’ to highlight the fact that these are people gambling weekly on activities other than lotteries alone. Similarly, the second group will be referred to as ‘weekly lottery-only’, the third group are the ‘4-week group’, and the fourth the ’12-month group’.
Any individuals who had not gambled in the past 12 months were excluded from the analysis. Figure 1 shows the 4 groups with unweighted base (n) and proportion of the weighted sample. The weekly gambling on any activity or activities in addition to lotteries group contains 17 percent of the people who gambled in the past 12 months and is the smallest of the 4 groups. The weekly lottery-only group contains 22 percent of those who gambled in the past 12 months, the past 4-week group contains 40 percent, and the past 12-month group contains 21 percent. It should be noted that National Lottery draws are the most common activity, meaning National Lottery draws will dominate the activities partaken in both the past 4-week and past 12-month groups.
Figure 1: Sample groups
| Frequency | Number | Percentage |
|---|---|---|
| Those who gambled in the past 12 months | 11,555 | n/a |
| Gamble weekly or more often | 4,487 | n/a |
| Gambled in the past 4 weeks but not in the past week | 4,661 | n/a |
| Gambled in the past 12 months but not the past 4 weeks | 2,407 | n/a |
| Weekly gambling on any activity or activities in addition to lotteries group | 1,780 | 17% |
| Weekly lottery only group | 2,707 | 22% |
| 4-week group | 4,661 | 40% |
| 12-month group | 2,407 | 21% |
Composition of the gambling frequency groups
A comparison was made of the socio-demographic profiles of each gambling frequency group. The full set of socio-demographic characteristics included in the analysis were: age, sex, ethnicity, tenure, qualifications, economic activity, household income, marital status, whether there were children present in the household, deprivation indicators, and region.
Methods
The first step was to run a series of tables showing the weighted profile of each socio-demographic characteristic for each of the four categories of gambling frequency group. These are shown in Tables 1 to 9.
A multinomial regression model was then used to investigate whether there were differences in the socio-demographic profiles of frequency groups. Like all regression models, these models regress a number of explanatory variables (in this case, the socio-demographic variables) onto an outcome variable (the four categories of frequency group). The resulting model provides insight into how each of the explanatory variables relates to the outcome, when all other explanatory variables are held constant. This means the model can be used to isolate the impact of specific explanatory variables. This is useful; quite often the relationship between two measures (for example, employment status and frequency of gambling) may in part be explained by underlying differences in a third variable (such as age). Such a model allows us to tease apart the relationships between frequency of gambling, age, and employment.
The multinomial model was run on weighted data. Any demographic characteristics not significantly associated with the frequency group was removed from the model, meaning the model only retained the characteristics that had the most significant relationship with frequency group. These were: age, sex, ethnicity, tenure, qualifications, marital status, whether there were children present in the household, deprivation indicators, and region. Household income and economic activity were not significantly related to frequency group once the other demographic factors had been considered and were removed from the model.
Multinomial models are used when the outcome variable has distinct categories. These models make no assumptions about the underlying order of the categories, hence are suitable in instances such as this where the outcome variable is not only split by frequency, but also by activity (the weekly gambling group is split into those who only buy tickets for lottery draws and those who also participate in all forms of gambling).
The output from a multinomial model is interpreted by comparing each of the outcome variable categories to a baseline group. The baseline group for the gambling frequency variable was the 12-month group (that is, those who had gambled on any activity, either online or in person, less frequently than the past 4 weeks but in the past 12 months). For each demographic characteristic, the profiles of the weekly gambling on any activity or activities in addition to lotteries, weekly lottery-only, and four-month groups are therefore compared to the 12-month group and tested to identify where there are significant differences in profile.
Results
The output from the multinomial model in the following section cross refers to information that can be found in the accompanying set of data tables, specifically table B.1. We summarise the weighted profile of each socio-demographic characteristic included in the model, before describing the direction of the relationships as confirmed by the model output.
Age
Table 1 shows how the weekly lottery-only group has an older age profile: 35 percent of this group were aged over 65 years whereas between 18 to 22 percent of the other groups were 65 and over. Similarly, the weekly lottery-only group has the lowest proportion of people in the younger age bracket. 8 percent of this group were aged 18 to 34 years, whereas between 29 to 34 percent of other age groups were aged between 18 to 34.
Table 1: Age profile by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| 18 to 34 | 30% | 8% | 31% | 34% | 26% |
| 35 to 64 | 52% | 58% | 51% | 46% | 52% |
| 65 and over | 18% | 35% | 18% | 20% | 22% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
After controlling for other demographic characteristics, the weekly lottery-only group still has a notably older age profile than the other groups. Individuals within this group were significantly more likely to belong in an older age bracket; they were nearly six times more likely to be aged 65 and over than aged 18 to 34, and nearly three times more likely to be aged 35 to 64 years than aged 18 to 34, when compared with the baseline 12 month group. The other groups also had a higher likelihood of being aged 35 to 64 than the baseline group, however, the differences were smaller.
Gender
The group with the highest proportion of women was the 12 month group, 57 percent of this group were women, followed by the four-week group (54 percent), then the weekly lottery group (48 percent). The weekly gambling on any activity or activities in addition to lotteries group contains the lowest proportion of women (36 percent). Essentially, as gambling frequency increased, the proportion of women gambling decreased. That said, a third of participants who gambled weekly on activities in addition to lotteries were women. This is shown in Table 2.
Table 2: Gender profile by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| Male (percentage) | 64% | 52% | 46% | 43% | 50% |
| Female and/or non-binary (percentage) | 36% | 48% | 54% | 57% | 50% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
This gender split across groups was also seen in the model output. In all groups, participants were significantly more likely to be male, compared with the baseline group, reflecting the bivariate profile (whereby the 12 month group contained the highest proportion of women).
Ethnicity
The weekly lottery-only group contained the lowest proportion of people belonging to a non-white background at eight percent. The proportion for other groups ranged between 12 to 15 percent.
Table 3: Ethnic background by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| Black, Asian, Mixed, Other, and missing | 14% | 8% | 12% | 15% | 12% |
| White | 86% | 92% | 88% | 85% | 88% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
The model indicates that, after controlling for the other demographic characteristics, participants within the weekly lottery-only and the 4 week groups were significantly more likely to be from a white ethnic background, compared with the baseline group. There were no significant differences between the baseline group and the weekly gambling on any activity or activities in addition to lotteries group.
Tenure
The weekly lottery-only group contained the highest proportion of people who own their homes outright at 39 percent versus 22 to 29 percent for other groups. People in the weekly gambling on any activity or activities in addition to lotteries group were more likely than those in other groups to be renting from a housing association (24 versus 12 percent in all other groups).
Table 4: Tenure by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| Own it outright | 22% | 39% | 27% | 29% | 29% |
| Buying it with the help of a mortgage or loan | 30% | 36% | 39% | 35% | 36% |
| Rent it from a housing association or local council | 24% | 12% | 12% | 12% | 14% |
| Rent it from another type of landlord | 18% | 10% | 18% | 20% | 17% |
| Live here rent-free | 5% | 2% | 3% | 4% | 4% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
After controlling for the other demographic characteristics, significant differences in the tenure profile of the groups remained in the model. The weekly gambling on any activity or activities in addition to lotteries group was significantly more likely to rent from a housing association or be living rent-free (individuals in this group were twice as likely to rent from a housing association or live rent free than they were to be an owner occupier, when compared to the tenure profile of the baseline 12-month group). Both the weekly lottery-only group and the four-week group members were more likely to be buying with a mortgage, compared with the baseline 12-month group.
Marital status
Individuals in the weekly lottery-only group were less likely to be single, (20 percent versus between 36 to 39 percent for other groups), and were more likely to be married (62 percent versus 44 to 49 percent for other groups).
Table 5: Marital status by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| Single | 39% | 20% | 36% | 38% | 33% |
| Married or Civil Partnership | 44% | 62% | 49% | 49% | 51% |
| Separated or Separated Civil Partnership | 3% | 2% | 2% | 2% | 2% |
| Divorced or Dissolved Civil Partnership | 9% | 10% | 8% | 7% | 8% |
| Widowed | 4% | 5% | 4% | 4% | 4% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
The model shows there were significant differences in marital status, and that these were present despite controlling for other socio-demographic characteristics. Those in the weekly gambling on any activity or activities in addition to lotteries group were significantly less likely to be married than the baseline group, whilst those in the weekly lottery-only group were significantly more likely to be married than the baseline. There were no significant differences in marriage rates between the four-week and 12-month group.
Household type
The weekly lottery-only group was less likely to contain people living in households with children (25 percent versus 31 to 32 percent for other groups). The weekly gambling on any activity/activities in addition to lotteries group contained more people living in multi-adult households (55 percent versus 40 to 50 percent for other groups).
Table 6: Household composition by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| All households with children | 32% | 25% | 32% | 31% | 30% |
| All single adult households | 15% | 15% | 14% | 14% | 14% |
| All 2 adult households | 28% | 43% | 35% | 35% | 36% |
| All households with multiple (2 or more) adults | 55% | 40% | 50% | 49% | 49% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
Within the multi-variate model, presence of children in the household was significantly related to gambling frequency group. Both the weekly gambling on any activity or activities in addition to lotteries and weekly lottery-only groups were less likely to have children present in the household when compared with the 12-month group.
Qualifications
There appears to be a strong relationship between gambling frequency and qualifications. People in the weekly gambling on any activity or activities in addition to lotteries group were less likely to have any qualifications, with 29 percent of this group saying they had no qualifications, compared with 20 percent in the weekly lottery-only group and 16 to 17 percent in the four-week and 12-month groups. This pattern is also present when looking at the proportion of participants with a degree and/or higher degree whereby those who gambled weekly, and gambled on things other than lottery draws alone, were less likely to have a degree than those in other groups.
Table 7: Highest qualification by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| None or Missing | 29% | 21% | 16% | 17% | 19% |
| Below degree level | 39% | 42% | 39% | 34% | 39% |
| Degree level or above | 32% | 37% | 45% | 49% | 42% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
These differences were also apparent in the model output. Individuals in the 12-month group were most likely to hold a degree-level qualification, they were twice as likely to have a degree than those in the weekly gambling on any activity or activities in addition to lotteries group. Those in the weekly gambling on any activity or activities in addition to lotteries group were significantly less likely to have any qualifications (either a degree or other qualifications below degree level) than those within the 12-month group. Individuals in the weekly lottery-only group were also significantly less likely to hold a degree-level qualification than those in the 12-month group, although there were no differences in the likelihood of holding other non-degree qualifications between the weekly lottery-only group and the 12-month group. The four-week group were significantly more likely to hold non-degree qualification than the 12-month group.
Index of Multiple Deprivation2
The weekly gambling on any activity or activities in addition to lotteries group contained the highest proportion of people living in deprived local areas, with 27 percent of this group living in the most deprived 20 percent of local areas, compared with 16 to 18 percent in the other groups.
Table 8: Deprivation quintile by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| 20% most deprived | 27% | 16% | 18% | 17% | 19% |
| 2nd | 23% | 20% | 21% | 21% | 21% |
| 3rd | 20% | 22% | 21% | 22% | 21% |
| 4th | 16% | 22% | 21% | 20% | 20% |
| 20% least deprived | 14% | 21% | 19% | 21% | 19% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
The same pattern was apparent in the model output. The weekly gambling on any activity or activities in addition to lotteries group contained a significantly higher proportion of people living in the most deprived areas (top 20 percent), even after controlling for regional differences in the profiles of the groups. Individuals in the weekly gambling on any activity or activities in addition to lotteries group were twice as likely to be in the most deprived quintile than they were in the least deprived quintile, compared with the individuals in the 12-month group. The deprivation profiles of the weekly lottery-only, four-week and 12-month groups were not significantly different.
Region and/or Nation
Those in the weekly gambling on any activity or activities in addition to lotteries group were more likely to be from Scotland (11 percent versus eight percent in all other groups) or the North West (14 percent versus 10 to12 percent across the other groups), and less likely to be from the South East (11 percent versus 14 to 16 percent for other groups).
Table 9: Region by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| East Midlands | 8% | 9% | 8% | 7% | 8% |
| East of England | 9% | 10% | 10% | 10% | 10% |
| London | 10% | 9% | 12% | 14% | 11% |
| North East | 5% | 5% | 5% | 4% | 5% |
| North West | 14% | 12% | 12% | 10% | 12% |
| Scotland | 11% | 8% | 8% | 8% | 9% |
| South East | 11% | 14% | 15% | 16% | 14% |
| South West | 8% | 10% | 9% | 9% | 9% |
| Wales | 5% | 6% | 5% | 4% | 5% |
| West Midlands | 10% | 9% | 8% | 10% | 9% |
| Yorkshire and The Humber | 10% | 10% | 9% | 8% | 9% |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
The model also identified regional differences across groups. The weekly gambling on any activity or activities in addition to lotteries group, weekly lottery-only group and the four-week group were all significantly less likely to contain people from London compared with the baseline 12-month group. The weekly gambling on any activity or activities in addition to lotteries group and weekly lottery-only group were additionally less likely than the 12-month group to contain people living in the South East, and both the weekly lottery-only group and four-week group were additionally less likely than the 12-month group to contain people living in the West Midlands.
Summary of differences between frequency groups
Examining the demographic and socio-economic profile of people who gamble according to gambling frequency highlights some marked differences between these groups. First, those who gamble weekly on any activity in addition to lotteries have a distinct profile. This group is significantly different to all other groups in terms of area deprivation (people in this group are more likely to live in more deprived areas), having a greater proportion of people with a lack of educational qualifications, and higher likelihood of living in accommodation rented from a housing association. Each of these factors is significantly related to group membership, even when the other factors are taken into account (for example, even if we were to remove any differences that exist between groups in terms of educational qualifications or tenure, people who gamble weekly on any activity will still be more likely to live in areas of higher deprivation). This suggests these factors have an additive impact. In short, this group appears to have greater socio-economic disadvantage than those in the baseline 12-month group.
Second, when looking at those who gambled weekly but only on lotteries, differences between this group and others were driven by age, the number of children in the household, and ethnicity. People in this group tended to be older, from White backgrounds and to have fewer children living in the household. This group were also more likely to be married. Notably, this group did not vary from the baseline group according to most socio-economic features. The main difference between these two groups of people who gamble weekly is whether they do something other than lotteries alone. Those who gamble weekly on any activities have a profile consistent with being more socially and economically disadvantaged than people who gamble less frequently on any activities, or those who gamble at the same frequency but only on lotteries.
Variables removed from the model
The following section cross refers to information that can be found in the accompanying set of data tables, specifically table C.1.
Economic occupation and household income had no significant relationship with frequency group once the other socio-economic measures had been controlled for and were removed from the model. Whilst there are some occupational differences seen across frequency groups, these are likely being driven by the differences in age profile across groups – as the key difference was the noticeably higher proportion of retired people in the weekly lottery-only group. Occupation therefore dropped out of the model once the differences in age profile were controlled for. Household income is correlated with both area level deprivation and qualifications, these two measures had stronger relationships with group membership than income, meaning income dropped out of the model also.
Problem Gambling Severity Index
Table 10 shows the difference in PGSI scores by frequency group, both grouped score and mean score. These, as expected, indicate that the weekly gambling on any activity or activities in addition to lotteries group is far more likely to have a PGSI score of eight or more. This is followed by the four-week group (but there is quite a gap between the two). The weekly lottery-only and 12-month groups are very similar in terms of PGSI profile.
Table 10: PGSI score by gambling frequency group
| Frequency of activity and type (either online or in person) | At least weekly on any activity in addition to lottery draws* (percentage) | At least weekly but only on lottery draws* (percentage) | Past 4 weeks but not in the past week (percentage) | Past 12 months but not in the past 4 weeks (percentage) | Total of everyone who gambled in past 12 months (percentage) |
|---|---|---|---|---|---|
| PGSI score 0 | 46% | 84% | 79% | 85% | 75% |
| PGSI score 1 to 2 | 23% | 11% | 15% | 11% | 15% |
| PGSI score 3 to 7 | 14% | 3% | 4% | 2% | 5% |
| PGSI score 8 or more | 17% | 1% | 2% | 2% | 4% |
| Mean score | 3.26 | 0.42 | 0.61 | 0.49 | 1.01 |
| Standard deviation | 5.34 | 1.58 | 2.04 | 2.11 | 3.04 |
| Number of total participants | 1,780 | 2,707 | 4,661 | 2,407 | 11,555 |
The differences in PGSI scores of people who gamble on a weekly basis is explored further in the next section by looking in turn at the associations between weekly participation in each activity and PGSI score.
2 The Index of Multiple Deprivation (IMD) is a measure of relative deprivation applied to small geographic areas, that ranks them according to levels of local deprivation. Each of the four constituent nations of the United Kingdom creates its own index. Whilst there are small differences in the approach used to measure deprivation in each nation, broad themes include income, employment, health, education, crime, barriers to housing and services, and the lived environment.
Analysis of weekly activities and PGSI scores
The association between gambling at least weekly on certain product types and Problem Gambling Severity Index (PGSI) scores was explored further to identify which product types had a stronger relationship with PGSI scores of 8 or more.
Multivariate analysis
A series of regression models were run to examine whether there were associations between weekly engagement in specific gambling activities and PGSI scores, whilst taking into account broader gambling behaviours and socio-demographic characteristics.
For each activity two models were run:
- negative binomial model where the outcome variable was PGSI score
- a binary logistic regression models, where the outcome variable was whether someone had a PGSI score of 8 or more.
In both instances the models included the same set of demographic characteristics used in the profile comparisons of gambling frequency groups, namely: age, sex, ethnicity, tenure, qualifications, economic activity, household income, marital status, whether there were children present in the household, deprivation indicators, and region.
In addition, the models included the number of additional activities that the individual had participated in weekly (that is, the total number of activities, excluding the specific activity being tested in the model).
The two models measure different aspects of the relationship between activity and PGSI scores:
negative binomial regression models3 the relationship across the whole range of PGSI, from 0 to 27. A significant relationship here implies the activity, when done weekly, is significantly associated with incremental increases across the whole range of PGSI score
the logit model4 is focused on the relationship between activity and a PGSI score of 8 or more. A significant relationship here implies the weekly activity is associated with an increased risk of having a score of 8 or more.
Models were run on weighted data. For each model, the base is the people who had participated in that activity (or sets of activities5) in the past 12 months.
Results
In an accompanying set of data tables, table 11 shows the frequency of gambling for each activity and the mean PGSI score of people taking part in each activity, by frequency. The regression output is summarised in tables 12 and 13, with full output presented specifically in tables D1 and D2. These tables show Incidence Risk Ratios (IRR) from the negative binomial regression models and the Odds Ratios (OR) from the logistic regression models. IRR are interpreted in a similar manner to OR. An IRR of 1.25 means that activity is associated with a 25 percent increase in PGSI score, whereas an OR of 1.25 would mean the activity is associated with a 25 percent higher likelihood of having a PGSI of eight or more.
The models show weekly gambling on non-National Lottery instant wins, weekly online and in person fruits or slots, and in-play betting are significantly associated with higher PGSI scores. Additionally, it shows these weekly activities are associated both with increases across the full range of PGSI scores, and with having a PGSI score of 8 or more. The relationship between having a PGSI of 8 or more and both weekly in play betting and gambling weekly on fruits and/or slots in person, are particularly strong; for both activities the likelihood of having a PGSI of 8 or more is over 3 times higher than it is for individuals who gamble less frequently on these activities.
There is also a significant, but negative, relationship in both models for weekly National Lottery online draws, which suggests lower PGSI scores amongst those who participate in weekly lotteries online, regardless of how many other gambling activities the individual takes part in. Similarly, there are two activities, National Lottery draws in person and bingo in person, that are also associated with lower PGSI scores, but only in the negative binomial models. Whilst both activities are associated with lower PSGI scores, there is no evidence of a relationship with PGSI scores of 8 or more. These results suggest participation in these activities is not associated with higher levels of harms.
Finally, there were 3 activities where there was a significant association in the logit but not the negative binomial, meaning weekly participation in each activity was associated with a PGSI score or 8 or more, but not associated with PGSI scores overall. One of these (other charity lotteries in person) had a negative relationship. This means weekly purchase of charity lotteries in person is significantly associated with having a PGSI lower than 8, and unrelated to PGSI more widely when PGSI is treated as a continuous score.
The remaining two (betting on outcomes of a non-sporting event online and other non-National Lottery scratch cards) have a positive relationship with PGSI, meaning weekly gambling on these activities is associated with a higher chance of having a PGSI score of 8 or more. Betting on outcomes of non-sporting events online have odds that are nearly three times as high, and other non-National Lottery scratch cards nearly twice as high.
The distribution of PGSI scores in accompanying data table 11 is useful in interpreting this finding; for both these activities the mean PGSI score of those participating fortnightly is similar or marginally higher than the PGSI score for those participating weekly, which means there is no clear association between activity frequency and increasing PGSI score that would be picked up by the negative binomial modelling. However, in the logit model, the PGSI scores are collapsed into two groups; the model indicates that both betting on outcomes online and other non-National Lottery scratch cards, when carried out weekly, are associated with a higher likelihood of a PGSI score higher than 8, and are therefore associated with greater harms.
The remaining activities were not significantly related to PGSI score in either model. These were: Other charity lotteries online, National Lottery scratch cards, National Lottery Instant Win, Betting on outcomes of non-sporting events in person, Bingo online, Casino games online, Casino games at a casino, Casino games at a machine, and any sports betting not in-play (online or in-person).
Summary
Previous research has identified those who gamble on a weekly basis as having increased risk for the experience of gambling harms6. Analysis presented here examined whether engagement in certain kinds of gambling activities on a weekly basis was associated with increased PGSI scores.
Findings show that weekly gambling on fruit or slot machines, both in person or online, are significantly associated with elevated PGSI scores and having a PGSI score of 8 or more. Equally, betting in play on a weekly basis was also significantly associated with elevated PGSI scores and having a PGSI score of 8 or more, whereas betting on sports excluding in play betting was not associated with either.
These findings are both commensurate with existing knowledge of the types of products more likely to be associated with harms, being continuous, rapid reward products7 8 that bridge the gap between online casinos and/or slots and online betting9.
It is notable, however, that in this analysis other continuous gambling forms, like weekly engagement in online casino products, were not associated with PGSI scores. This may be because engagement in other activities or the characteristics of those who engage better explains this expected association. It may also be because less frequent engagement (that is, less often than weekly) is also strongly associated with PGSI scores, meaning the differences between weekly and less frequent engagement are obscured. In short, there is a need to look at risk curves for frequency of engagement in specific activities to better understand the frequency levels at which risk increases for people who take part in each specific activity.
These data are cross-sectional with attendant issues for causality. The models control for wider gambling involvement (measured by engagement in a number of other gambling activities on a weekly basis) but also the demographic and socio-economic profile of participants. There may, however, be some other unmeasured factor influencing results. Irrespective of the causal direction, there is a strong association between weekly in-play betting and weekly gambling on fruit and slots machines and their online equivalents. Operators providing these products should be aware of the enhanced risk among those gambling on these products most frequently.
3 Negative binomial regression models are well-suited to modelling outcomes, such as PGSI, that are non-negative (0 or greater), skewed, and contain a lot of 0 values.
4 Logit models are suited to outcomes that are binary (have two possible values), in this instance whether the individual has a PGSI score of eight or more, or not.
5 Because of specific filtering used in the online questionnaire, the bases for each activity varies. For example, the base for the model exploring PGSI and weekly participation in online casino games is anyone who played any casino games (online, at a machine, or in person) in the past 12 months. This reflects how the questionnaire was filtered on grouped activities.
6Currie SR, Hodgins DC, Wang J, El-Guebaly N, Wynne H. In pursuit of empirically based responsible gambling limits. International Gambling Studies. 2008;8(2):207–227. doi: 10.1080/14459790802172265
7Allami, Y., Hodgins, D. C., Young, M., Brunelle, N., Currie, S., Dufour, M., Flores-Pajot, M., & Nadeau, L. (2021). A meta-analysis of problem gambling risk factors in the general adult population. Addiction. https://doi.org/10.1111/add.15449
8Wardle H., et al (2024) The Lancet Public Health Commission on gambling, The Lancet Public Health, Volume 9, Issue 11,2024, Pages e950-e994,ISSN 2468-2667,https://doi.org/10.1016/S2468-2667(24)00167-1.
9Killick, E. A., & Griffiths, M. D. (2018). In-play sports betting: A scoping study. International Journal of Mental Health and Addiction 17(2) DOI:10.1007/s11469-018-9896-6
Full list of gambling activities
The following table shows the full list of gambling activities and indicates whether they were asked about for the past 12 months and the past 4 weeks.
| Activity | Asked if participated in past 12 months | Asked if participated in past 4 weeks |
|---|---|---|
| Tickets for National Lottery draws | Yes | No |
| Tickets for National Lottery draws bought online | No | Yes |
| Tickets for National Lottery draws bought in person | No | Yes |
| Tickets for other charity lottery draws | Yes | No |
| Tickets for other charity lottery draws bought online | No | Yes |
| Tickets for other charity lottery draws bought in person | No | Yes |
| National Lottery scratchcards | Yes | Yes |
| Other scratchcards | Yes | Yes |
| National Lottery online instant win games | Yes | Yes |
| Other online instant win games | Yes | Yes |
| Betting on sports and racing online or via an app | Yes | Yes |
| Betting on sports and racing in person | Yes | Yes |
| Betting on the outcome of events online or via an app | Yes | Yes |
| Betting on the outcome of events in person | Yes | Yes |
| Bingo online or via an app | Yes | Yes |
| Bingo played at a venue, for example bingo hall or social club | Yes | Yes |
| Casino games played online or via an app | Yes | Yes |
| Casino games played at a casino | Yes | Yes |
| Casino games played on a machine or terminal in a venue, such as a casino, bookmakers, club, or pub | Yes | Yes |
| Fruit and slots games played online or via an app | Yes | Yes |
| Fruit and slots games played in person (on a machine) | Yes | Yes |
| Football pools | Yes | Yes |
| Private betting | Yes | Yes |