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Gambling sponsorship has predictably risen in women's sports as part of this development as the profile of women's sports rising has come with rapid changes to the promotional culture that surrounds its marketisation. Thus, it is likely that gambling may also be becoming more normalised within women's behaviours, and women's sporting fandom.

Much attention has been given to the intergenerational transfer of risk, exploring associations between parental gambling behaviours and that of young people. Emond and Griffiths found that the risk of gambling harm among adolescents was greater among those with low self-esteem, a history of hyperactivity and impulsivity, those who consumed more alcohol than their peers, had less parental supervision and had parents who gamble.

Thus, they understood parental influence alongside a range of other factors. Whether parental influence is as reliable a predictor of their children's gambling regardless of gender is disputed. For example, Forrest and McHale found in their UK-based longitudinal study that parental problem gambling increased the likelihood of problem gambling among their children.

However, they found that this result was only found across gender. Thus, a father's behaviour influenced their daughters and mothers influenced their sons.

Conversely, Vachon et al. It is not only parental influence on gambling behaviours that have been examined. Freund et al. Van Hoorn et al. Hardoon and Derevensky also found that women were more likely than men to be impacted by gambling in situations where they were playing with other men and women — thus they were found to be more influenced by the group condition than men in the study.

However, this study did not look at these effects by gender. Some studies argue this increased visibility of gambling is responsible for increases in sports betting among younger adults. Whilst this brief and non-exhaustive review sheds some light on the range of determinants that shape individual behaviours, it is also clear that very few studies have examined how this may or may not vary for men and women.

Using EAGS dataset, we present preliminary findings to start to address this gap. The analysis in this chapter presents findings on the relationships between these bettors and the associated harms they face.

There is a growing international recognition of the types and scale of harm caused by gambling see Public Health England, Aligned with this literature we consider gambling to be a public health issue, whereby gambling harms are faced by gamblers and wider society.

Types of harms are commonly grouped in relation to financial, emotional and psychological mental health , relationships, education, work and other harms see Public Health England, Thus, the economic and social costs of gambling are often underestimated Wardle et al.

Different products may come with different levels of risk of harms according to context and some groups such as younger individuals and individuals from ethnic minority groups are more at risk of being harmed by gambling.

When considering the levels of risk faced by gamblers, we must consider the intersectional risks faced alongside other inequalities that may make people more at risk due to wider societal inequalities. For example, gender, race, sexuality and class must be viewed alongside and in relation to factors such as age.

This chapter does not dispute the commonly respected idea that young men are more likely to be sports bettors than women. However, our findings fit with some other studies in suggesting that a significant number of women are sports bettors.

McCarthy et al. As women and young people, they are more at risk of experiencing gambling harms and therefore it is important to learn more about the gendered experiences of sports bettors. Consequently, women-specific gambling harms have been under-researched; a better understanding of these harms would allow for a more tailored approach to reducing gambling harms among women.

These characteristics of their behaviour make emerging adults more vulnerable to problem gambling. Thus, our sample is of a group of young people who are particularly at risk of facing gambling harms. The EAGS is a non-probability longitudinal survey that includes individuals between the ages of 16 and 24 who were residents across Britain at the time of data collection.

Respondents were interviewed on a range of topics including their gambling activity, health, socio-economic status and their parental background Wardle, This means that the sampling is not random and potential bias is not measured or controlled Acharya et al.

For this reason, the findings we discuss throughout this chapter relate our specific sample. One useful feature of the EAGS dataset is that it provides data on online and in-person sports betting as well as a wide range of sociodemographic and socio-economic variables.

This enables us to examine the profile of young women and young men who bet on sports. Data was collected from respondents from across the United Kingdom. As seen in Tables 1 and 2 , our results from the first model considered various sociodemographic and socioeconomic variables.

These included the age range of respondents, ethnicity, educational attainment, whether they were employed or studying and where their area level of deprivation according to the Indices of Multiple Deprivation IMD.

Our sports betting measure was created by combining two categorical measures: frequency of betting on sports in licenced betting offices and frequency of betting online on sports events.

We ran summary statistics that showed that a third of sports bettors online were women in our sample. We also found that a third of sports bettors in betting shops were women. Thus, we opted to combine these to make a sports bettor measure. The two variables combined to make our sports bettor measure asked respondents to answer whether they had bet online or in-person in the past 12 months.

Thus, the sports bettor measure captures all sports bettors in our sample who were active in the 12 months beforehand. Our results section can be divided into three main stages. Firstly, summary statistics present both unweighted and weighted summaries.

Secondly, we examine the profile of sports bettors and factors associated with sports betting, by gender. This includes examining the role of parental and peer gambling as well as education, income and region on the likelihood of being involved in sports betting.

Finally, we examine the extent to which women and men sports bettors are more or less likely to experience a range of gambling harms compared with other types of gamblers, i. those who only gambled on lotteries and any other form of gambling ranging from online casinos, slots, to bingo but who do not bet on sports.

Our financial harm measure was based on whether respondents had less money to buy things including food and drink. Our productivity harm measure asked whether gambling had negatively impacted performance in school or work.

Finally, relationship harm was measured by difficulties with family or friends caused by gambling. Thus, we agree with the common finding that men are more likely to be sports bettors than women. However, this proportion was higher than we expected, suggesting that the number of young women engaged in sports betting in Britain may be greater than previously thought.

As Table 1 shows, there were some key differences in the profile of men and women sports bettors. Firstly, men sports bettors were more likely to report betting once a month or more regularly than women sports bettors This suggests that some young people can still navigate around age verification rules to access gambling online before being of legal age.

Among the emerging adult age cohort, women sports bettors were a similar age as men sports bettors, with Note: Current gamblers include those individuals who engaged in gambling in the last 12 months.

To extend this, using logistic regression models separately for men and women sports bettors , we examine the factors associated with being a sports bettor. These models include socioeconomic and demographic features, and also measures of broader gambling behaviours — such as the influence of parents and peers, the influence of advertising and marketing and sports fandom.

The total number of observations in our sample was women and men. Table 2 shows the results from our logistic regression from which three key findings are clear: the impact of your peer network, the frequency of watching sports whether online or in person and age, are associated with women sports betting.

For women sports bettors, the odds ratio of being a sports bettor was 3. Sports betting was 6. For men, these odds were further increased with men watching more than once a week being Men who had watched live sports on TV or online a few times in the last 12 months were 4.

Watching sports in person also had a significant impact. Women who watched live sports in person more than once a week were 2. For men, there was no evidence of a relationship between watching sports in person and sports betting.

Among men, age was associated with sports betting, with the odds of sports betting being higher as age increased. A similar pattern was observed for women among 22—year-olds, though the age group of those aged 19—21 did not differ from the reference group of 16—year-olds, likely because the sample is somewhat underpowered to detect these differences.

For the adolescent boys and men up to 24 in our sample, we found that the likelihood of being a sports bettor was increased by having a mother who gambles. However, for women, we did not find evidence to confidently suggest that there was any parental influence in predicting the likelihood of sports betting among our sample.

We believe that further research is needed to examine the general parental effects on both sons and daughters. Note: The sample includes current gamblers who engaged in gambling in the last 12 months.

To explore the extent to which sports betting is associated with the experience of gambling harms, we analysed different measures of harm financial, productivity and relationship by gambler type sports bettors, lottery or other gambling. First, we created three mutually exclusive types of gamblers: those who only played lotteries; those who had bet on sports as well as other things in the past year and those who gambled on other activities but not sports betting or lotteries alone.

This latter group included those who may have played slot machines, online casino games, online bingo or engaged in private betting. Overall, Equivalent estimates for men were Financial harms included anyone who stated that they at least sometimes have less money to spend on food or drink because of gambling or that gambling had stopped them from buying other things they wanted.

Finally, relationship harms consist of anyone saying that gambling at least sometimes caused them to argue with friends or family; made them feel less close to friends and family; or made them lie to family members or guardians. Overall, 4. Equivalent estimates for men were 7.

Among women, there appeared to be a pattern by which the experience of each of these harms was greatest among those who were sports bettors, followed by those who were other gamblers and lowest among those who were lottery-only gamblers.

Comparable estimates among other bettors were For relationship harms, this pattern was confirmed in logistic regression models, whereby among women the odds of experiencing gambling-related harm were significantly higher among sports bettors 1. The odds of experiencing relationship harms were lower among those who were lottery-only gamblers compared with other gamblers.

For men, sports betting was statistically insignificant, while lottery results were similar in magnitude to women's findings, and it was also statistically significant.

For financial and productivity harms, there were no differences between sports bettors and those engaged in other forms of gambling, whilst lottery-only gamblers were less likely to experience these things.

This pattern was the same for men and women. Thus, we can suggest that men and women gamblers in our sample had comparable levels of risk from these harms Tables 3 and 4. The results of this study lend further evidence regarding young women's increasing engagement with sports betting McCarthy et al.

While our results indicate that sports betting among young people in the United Kingdom remains an activity dominated by men, we found that a substantial proportion of sports bettors were women among our British sample of emerging adults. As discussed in our results section, we found that there was a significant overlap in the predictors for sports betting among our sample of men and women.

Thus, we suggest that women should not be considered safe from sports betting and its associated harms. We found that watching sports and peer influence are important predictors of young women's sports betting. According to this, women were more likely to bet on sports when they were fans of the sports or when gambling was an activity that their close peer network was involved with.

We also found through our question on harms that women sports bettors in our sample were disproportionally at risk of facing harms compared to women who gamble on other products. Very few studies have considered patterns and associations of women sports betting in depth, and our study lends support to emerging evidence on the relationships between sports fandom and the importance of social networks in shaping women's behaviour.

Our findings highlight, for women as well as men, there is likely a reciprocal relationship between watching sports and sports betting.

Whilst much research literature to date has focused on men's experiences, whereby gambling has become a normalised aspect of sports fandom for young men McGee, , it appears similar processes may be at play for women. They also noted that some participants engaged in sports betting as a way to bond with their partners or friends who were interested in sports McCarthy et al.

Their findings suggested overall that sports betting was often socially motivated and connected to ease of access. Notably, our study found that having a close friend who gambled increased the odds ratio of being a sports bettor by 3.

As a result, our findings suggest that there is a significant power held by peer influences over gambling behaviour. Having peers who gamble can normalise gambling behaviour and experiences of gambling-related harm Russell et al.

The presence of peers may also heighten the likelihood of risk-taking for gamblers Van Hoorn et al. These influences are just as apparent in our sample for women sports bettors as for men. In addition, we sought to examine the extent to which parental influences may shape gambling behaviours.

As noted earlier, the evidence tends to show intergenerational correlations between parental and child gambling behaviours. A wealth of prior research has found that family members are often key facilitators in gambling initiation. Less is known about the role of family networks in the continuation and trajectory of gambling careers across the life course.

McCarthy, Thomas, Pitt, Daube and Cassidy found that family members were the key facilitators of gambling for young women in Australia but were replaced by peers and partners as most instrumental after they reached the legal gambling age.

Our study tentatively supports these findings because we did not find evidence of a relationship between parental gambling behaviour and women's sports betting but did between peer gambling and women's sports betting.

However, there are some limitations to the analysis performed here — we only measured how often each parent gambled which itself may be subject to measurement error and not what forms of gambling each parent participated in.

In future studies, capturing the format of parental gambling is likely to be important to tease out these relationships further. There are multiple interesting findings from our results on the relationship between harms and sports betting. We looked at data on three types of harm: 1 Gambling meant less money to buy things including food and drink; 2 gambling meant poorer performance at work or school; 3 gambling caused difficulties with family and friends.

We found that young women sports bettors experience harms at rates similar to men. This finding is in contrast with an argument tentatively put forward by Russell, Hing and Browne that being a woman might be viewed as a protective factor against harms from sports betting. Women engaged in sports betting experienced much higher levels of harms than women gamblers using other products.

Thus, the risk of harm for sports betting men was the same across products. When we consider our findings on the demographics of women sports bettors together with the risk of harm, we find a potentially paradoxical situation. As discussed, women are more likely to be sports bettors due to peer influence, social bonding and social motivations.

However, we also found that women sports bettors were more at risk of experiencing harms associated with difficulties with family and friends than women gamblers using other products.

Thus, the same relationships that motivate sports betting among women may be at risk of deterioration due to the activity and its associated harms. This chapter tentatively suggests that these processes may be more apparent for women than men, which requires further investigation.

It is further notable that women sports bettors tended to gamble less regularly and were less engaged in risky sports betting practices in-play betting than men. Given these behaviours are highly associated with an increased risk of harm, it is concerning to see this elevated level of relationship harms reported among women sports bettors.

Whilst further investigation is needed into this and understanding of how women integrate sports betting into wider gambling repertoires, at minimum our data suggests that women should be considered equally as vulnerable to gambling harms as men.

Women's vulnerabilities may manifest in particular ways which is important to recognise and further investigate. There are some limits to the findings presented here that must be acknowledged. Primarily, the sample size means that our base sample was relatively small.

As a result, we want this chapter to serve as a call for further research and attention to be done to test our findings and push them forward to more fully understand the demographics of women sports bettors and their gendered experiences of harms. Our findings are also based on a non-probability sample which influences what we can say from our data.

There are some themes which we expected to find and did not which may be because of the peculiarities of this particular sample. For example, we did not find a significant relationship between parental gambling behaviours and the likelihood of their children being sports bettors. However, we approach this with caution as we have already highlighted in our background section that there have been significant studies looking at this, albeit with inconclusive results.

Thus, again, we need further studies to explore the relationships discussed here which would avoid the risk of sample selection bias. Furthermore, we would normally expect to see a relationship between certain demographic or socio-economic characteristics and gambling propensity which was not evident in this study for example, relationships with income, ethnicity, employment, deprivation, etc.

Whilst sampling bias may be at play here, also it may be possible that these patterns are less relevant to this age cohort. According to this idea, socioeconomic factors may be less relevant for younger generations who are exposed to gambling from a wide array of directions particularly through the internet , which both encourages and normalises gambling.

This needs further investigation. In writing this chapter, we were surprised by the number of young women sports bettors we identified in our sample. We should not have been. Prior theories about how the increasing availability of gambling through more gender-neutral channels like online , changing social processes promoting sports and sports fandom as both gender-neutral and family-orientated activities and women-centric gambling promotion would suggest an inevitability of such observations e.

see McCarthy et al. Yet, this has not translated into a women-focused research agenda, and too often women's experiences are explored by continued comparisons to men.

Nadine, We believe our findings and the focus of this chapter have sought to solidify the need for women-focused experiences of gambling harms going forward so as not to push women off the table in future research. The invisibility of women in health research has a long history Langer et al. With this chapter, we call for this history not to be repeated.

This chapter has sought to answer two questions. Firstly, we have given new insights into the demographics of women sports bettors in the United Kingdom. An under-researched sub-group of sports bettors, we have argued that there is a need to understand these characteristics to aid policy that will be sensitive to gendered experiences.

With the increasing profile of women in sport e. through the growing reach and investment in women's football , we believe it is essential that further studies draw out the scale of women sports betting and their profile. Secondly, we sought to understand the relationship between women sports betting and the associated harms faced.

We found that women sports bettors were more at risk of experiencing harms associated with difficulties with family and friends than women gamblers using other products. As a result, we are suggesting that our findings show that women sports bettors are a particularly vulnerable group that requires further attention.

Women's vulnerabilities may manifest in particular ways which are important to recognise and further investigate. It is necessary to place women's experience at the centre of research endeavour to help understand, explain and mitigate experiences of gambling harms among this underserved group.

All studies except the one done by Weidberg et al. As is standard, differences in sampling procedures and study designs suggest that these cross-country differences should be interpreted with caution.

Acharya et al. Sampling: Why and how of it? Indian Journal of Medical Specialities , 4 2 , — doi: Althaus et al. Textbook of addiction treatment. Textbook of Addiction Treatment , — Arnett, Arnett , J. Emerging adulthood: A theory of development from the late teens through the twenties.

American Psychologist , 55 5 , — Bozzato et al. Problematic gambling behaviour in adolescents: Prevalence and its relation to social, self-regulatory, and academic self-efficacy. International Journal of Adolescence and Youth , 25 1 , — Bunn et al. Shirt sponsorship by gambling companies in the English and Scottish Premier Leagues: Global reach and public health concerns.

Soccer and Society , 20 6 , — Chalmers and Willoughby, Chalmers , H. Do predictors of gambling involvement differ across male and female adolescents? Journal of Gambling Studies , 22 4 , — Delfabbro et al. Further evidence concerning the prevalence of adolescent gambling and problem gambling in Australia: A study of the ACT.

International Gambling Studies , 5 , — Delfabbro and Thrupp, Delfabbro , P. The social determinants of youth gambling in South Australian adolescents.

Journal of Adolescence , 26 , — Dowling et al. The intergenerational transmission of problem gambling: The mediating role of parental psychopathology. Addictive Behaviors , 59 , 12 — Downs, Downs , C. Mecca and the birth of commercial bingo — A case study.

Business History , 52 7 , — Emond and Griffiths, Emond , A. Gambling in children and adolescents. British Medical Bulletin , 1 , 21 — Forrest and McHale, Forrest , D. Transmission of problem gambling between adjacent generations. Journal of Gambling Studies , 37 2 , — Copy Citation.

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variants or better ˈbet-ər. More from Merriam-Webster on bettor. Love words? Need even more definitions? Can you solve 4 words at once?

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betfred football betting one who makes a wager: Free vip betting tips telegram bettor goes to Las Free vip betting tips telegram as often as bettorw can. Some words with the prefix bi- have bettos standard usage and need to be qualified whenever they are used. Not to be confused with: better — more useful, desirable or suitable: This is a much better choice. American Heritage® Dictionary of the English Language, Fifth Edition. Copyright © by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company. All rights reserved.

Bettors -

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Log in. More information. Supplementary notes. Other statistics on the topic. Gambling Brand value of leading global gambling companies Gambling Gross gambling yield of the gambling industry in Great Britain , by sector.

Gambling Frequency of gambling in Great Britain Gambling Online gambling participation in Great Britain from to , by gender. Profit from additional features with an Employee Account. Please create an employee account to be able to mark statistics as favorites.

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Statistics on " Online gambling in the United Kingdom " The most important statistics. The most important statistics. Other statistics that may interest you Online gambling in the United Kingdom Overview 6.

Basic Statistic Gross gambling yield of the gambling industry in Great Britain , by sector Premium Statistic Gross gambling yield of the online gambling industry in Great Britain Premium Statistic Active online remote gambling customer accounts in Great Britain Premium Statistic New online remote gambling player registrations in Great Britain Premium Statistic Online gambling customer account funds in Great Britain Premium Statistic United Kingdom HMRC remote gaming duty receipts Premium Statistic Brand value of leading global gambling companies Premium Statistic Leading websites in the sportsbook sector in the UK , by share of voice Basic Statistic Frequency of gambling in Great Britain Premium Statistic Leading types of online gambling activities in the UK Premium Statistic Main reasons to gamble online in Great Britain , by gender Premium Statistic Main reasons not to gamble online in Great Britain Basic Statistic Participation in online gambling activities in Great Britain Basic Statistic Participation in online gambling in Great Britain , by age group Premium Statistic Online gambling participation in Great Britain from to , by gender Premium Statistic Virtual dog or horse race gambling participation in Great Britain Premium Statistic Virtual gaming in a bookmakers gambling participation in Great Britain Premium Statistic Monthly GGY of the online betting market in Great Britain , by type Premium Statistic Monthly number of online bets placed in Great Britain , by type Premium Statistic Monthly number of active online bettors in Great Britain , by type.

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