Background: Excessive expenditure and financial harms are core features of problem gambling. There are various forms of gambling and their nature varies. The aim was to measure gambling expenditure by game type while controlling for demographics and other gambling participation factors. A further aim was to find out how each game type was associated with gambling expenditure when the number of game types played is adjusted for. Methods: Using data from the 2015 Finnish Gambling survey on adult gamblers (n = 3555), multiple log-linear regression was used to examine the effects of demographics, gambling participation, and engaging in different game types on weekly gambling expenditure (WGE) and relative gambling expenditure (RGE). Results: Male gender, lower education level, higher gambling frequency and higher number of game types increased both WGE and RGE, while younger age decreased WGE but increased RGE. Furthermore, seven specific game types increased both WGE and RGE. Weekly horse race betting and non-monopoly gambling had the strongest increasing effect on expenditure. Betting games and online poker were associated with higher expenditure even when they were played less often than weekly. Among weekly gamblers the highest mean WGE was recorded for those who played non-monopoly games (146.84 €/week), online poker (59.61 €/week), scratch games (51.77 €/week) and horse race betting (48.67 €/week). Those who played only 1–2 game types a week had the highest mean WGE and RGE on horse race betting and other betting games. Conclusions: It seems that overall gambling frequency is the strongest indicator of high gambling expenditure. Our results showed that different game types had different effect sizes on gambling expenditure. Weekly gambling on horse races and non-monopoly games had the greatest increasing effect on expenditure. However, different game types also varied based on their popularity. The extent of potential harms caused by high expenditure therefore also varies on the population level. Based on our results, future prevention and harm minimization efforts should be tailored to different game types for greater effectiveness. Keywords: Cross-sectional, Game type, Gambling expenditure, Net income, Population study, Relative gambling expenditure Background other hand, it has been suggested, that some game types Early research into the adverse consequences of gambling may be more like indicators of unhealthy gambling in- was focused on the presence of pathological or problem volvement, rather than critical factors associated with gambling, but recently it has become commonplace to take gambling-related problems [9, 10]. Gambling expenditure, a broader view on gambling harm [1, 2]. Some game types, one of the indicators of unhealthy gambling involvement, for example, slot machine gambling, casino games, poker, shows the strongest association with gambling-related betting games, bingo and/or scratch games have been asso- harm as many of the negative impacts of excessive ciated with gambling-related problems (e.g. [3–8]). On the gambling are due to financial problems [1, 2, 11–14]. Despite this association, gambling problem or even * Correspondence: email@example.com gambling-related financial harm are not synonymous Alcohol, Drugs and Addictions Unit, National Institute for Health and with excessive expenditure [15, 16]. For harm preven- Welfare, P.O. Box 30, FI-00271 Helsinki, Finland 2 tion and minimization purposes it is essential that we Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Salonen et al. BMC Public Health (2018) 18:697 Page 2 of 12 build our understanding of different game types and There is gender differences in game type preferences: associated harms. There is as yet very little research men tend to favour skill-based games, whereas women on gambling expenditurebygametype. prefer games of chance . Game type preferences Finland has one of the highest per capita gambling ex- were highly gendered in Sweden, although men in penditure rates in Europe . For research purposes Sweden have decreased their participation in games of gambling expenditure is usually assessed by questions strategy and increased participation in games of chance concerning wins and losses, or most typically by direct in public spaces . In any assessment of gambling par- questions on spending; the latter is the most common way ticipation, it is therefore important to consider both the . However, it has been suggested that in order to gain number of different game types played and the fre- a clearer picture of gambling-related harm, gambling ex- quency of gambling [7, 9, 10, 46]. Playing multiple game penditure should be examined in relation to the gambler’s types is associated with online gambling, and among fe- net income . We use the dual measures of weekly gam- males in particular online gambling may be related to bling expenditure and gambling expenditure in relation to higher gambling expenditure and at-risk and problem the gambler’s net income. gambling . Gambling expenditure is higher among men than In 2015, 23% of Finns gambled only one game type, pre- women [19–23]. Furthermore, low education and un- dominantly weekly lottery games . It is beneficial to employment are associated with higher gambling expend- take a broader view on gambling participation and also iture [20, 24, 25]. Overall, people with high monthly consider overall gambling frequency, gambling mode and gambling expenditure relative to net income, and men in number of game types gambled. Furthermore, an examin- particular, are more likely to be socio-economically vul- ation of different game types played by active gamblers nerable individuals . and more occasional gamblers is a novel way of studying Gambling frequency is typically assessed by asking patterns of gambling expenditure and relative expenditure people how many times they have engaged in gambling concurrently. within a certain period of time, or by asking their aver- age frequency of participation within a certain time Methods frame . A high frequency of gambling, participation Aim, design and setting in multiple game types and high gambling severity are This cross-sectional study aims to measure gambling ex- associated with high total expenditure [27–29]. Although penditure by game type while controlling for demo- high gambling frequency is associated with gambling graphics and other gambling participation factors, such harms, only some frequent gamblers experience harm as gambling frequency, number of game types played . On the other hand, even occasional gamblers may and gambling mode. We used two measures of gambling experience harm [11, 13, 31]. expenditure: weekly gambling expenditure and gambling There are various forms of gambling and their nature expenditure in relation to net income. A further aim was varies . A simple classification distinguishes between to find out how each game type is associated with gam- lottery-style and wagering-style games. Another classifica- bling expenditure when the number of game types tion is based on game provider . Finland is one of the played is adjusted for. countries where games are provided by a government reg- Until December 2016, Finland had a three-way monop- ulated monopoly, although non-monopoly games are oly system (Veikkaus, Finland’s Slot Machine Association available online. Game types can also be classified based [FSMA] and Fintoto) in which each game provider had on means of access, such as direct face-to-face gambling the right to offer gambling services . In 2017, these or remote access . Another access-based classification service operators were merged into a single company. distinguishes between online and land-based games . Furthermore, game types are classified based on whether their outcome is determined by chance, skill or a combin- Data collection ation of chance and skill . Games such as slot ma- Thedataweredrawn from the Finnish Gambling2015 sur- chines, lotteries, scratch cards, bingos, roulettes and dice vey . A random sample of 7400 persons aged 15–74 games are fundamentally chance-based games, whereas whose mother tongue was Finnish or Swedish and who re- poker and blackjack, for instance, also include elements sided in mainland Finland were approached by Statistics of skill . Another way to categorize game types is to Finland. In total 4515 computer-assisted telephone inter- look at their structural characteristics, which are event views lasting on average 18 min were completed. The study frequency, event duration, bet frequency and pay out was described to the potential participants as a survey interval . In population studies, a common way of in- about ‘gambling and opinions about gambling’.The re- quiring about participation in different gambling types sponse rate was 62% (men 62%; women 61%). Attrition is is to use a list of available game types . described in more detail elsewhere [20, 39]. Salonen et al. BMC Public Health (2018) 18:697 Page 3 of 12 The data were weighted based on gender, age and re- included slot machines, horse race betting and private bet- gion of residence. Respondents who were allowed to ting. Online poker included poker on the FSMA website; gamble legally (≥ 18 years) and who had gambled during on the website of a private gaming company Ålands Pen- the past year were included in the study (n = 3555). ningautomatförening (PAF), while non-poker games on the FSMA online casino were treated as a separate game Gambling expenditure type. Finally, non-monopoly gambling included non-poker Gambling expenditure (GE) was inquired with the ques- gambling outside the Finnish monopoly system, including tion: ‘Roughly how much money do you spend on gam- non-monopoly and PAF games both online and on ferries bling in a typical week (€)?’. If the respondent did not between Finland, Estonia and Sweden. gamble each week, the interviewer was instructed to ad- Then, the number of game types played was calculated vise the respondent to give an estimate of their spending and recoded into four categories, since the association when they did gamble. In this study, GE was examined between gambling expenditure and number of game using two measures: weekly gambling expenditure in types was not linear. Also, we wanted to have estimates euros (€) and relative gambling expenditure (%). for different numbers of game types instead of only one Weekly gambling expenditure (WGE) was rescaled if estimate for a continuous variable. A cutoff of four or respondents indicated an overall gambling frequency of more games types was used to create roughly equal sized less than once a week using the formula WGE = F*GE/ groups. Furthermore, there was a clear increase in the 365.25*7 [7–8], where proportion of problem gamblers between gamblers with three and four game types (3.9 and 7.4%), and this cutoff a) F = 30 if past-year gambling frequency was 2–3 point has been associated with problem gambling . times a month Overall gambling frequency was calculated based on the b) F = 12 if past-year gambling frequency was once a game type in which the gambler was most active. Then, month gambling frequency was also recoded: at least once a c) F = 6 if past-year gambling frequency was less than week, 1 to 3 times a month and less often than once a monthly month. Following the example of previous studies [40, 41], For weekly gamblers WGE = GE. gambling mode was classified as online gambling if the Relative gambling expenditure (RGE) was calculated person had gambled online during the past year. Online using WGE and 2014 register data on personal net income gamblers included gamblers who may have participated provided by Statistics Finland. Personal net income con- in land-based gambling. The rest of the responses were sisted of total gross income (wages and salaries, invest- classified as land-based gambling only. ment income, benefits and allowances) minus taxes. The relative expenditure measure was formed by estimating Weekly gambling yearly expenditure (WGE/7*365.25) and dividing it by per- Game types were categorized by distinguishing active sonal net income. RGE thus represented the percentage of gamblers (‘at least once a week’) and more occasional income used on gambling. For 361 participants it was not gamblers (‘less than once a week’) and ‘non-players. This possible to calculate relative expenditure either because classification was used to assess the added effect of fre- their net income was 0 euros (n =12), or they did not re- quent gambling on 12 game types on gambling expend- port their gambling expenditure (n =353). iture when controlling for overall gambling frequency. Gambling participation Data analysis Participants were asked whether they had gambled on 18 Two separate multiple log-linear regression models were predefined game types during the past 12 months (yes/ used to explain the variation of WGE and RGE, since no). These game types were recoded into 12 game types the distributions of both dependent variables were because of the small size of groups among certain game skewed to the right. In both models the independent types and to limit the number of variables added to the variables were gender, age group, education level (demo- model. The recoded game types were: weekly lottery graphic variables), overall gambling frequency, number games, fast-paced daily lottery games (such as instant of game types played and gambling mode (participation e-lotteries and e-Bingo), low-paced daily lottery games factors). Additionally, the nine game types were entered (such as Keno), scratch cards, betting games (including into the models using a stepwise forward method to find betting several teams at once, fixed odds betting, correct out which specific game types contributed to explaining score and live betting) and casino games (live casino WGE and RGE after controlling for demographics and games in a casino or table games, such as roulette or Black participation factors. Casino games, non-poker games on jack run by a croupier outside a casino). Game types also the FSMA online casino and private gambling were Salonen et al. BMC Public Health (2018) 18:697 Page 4 of 12 excluded before stepwise regression because of the small Table 1 Demographics and factors related to gambling participation group size of weekly gamblers. Exponentiations of beta coefficients (exp(β)) were interpreted as percentage dif- %N ferences between a subcategory and a reference category. Gender WGE and RGE means were calculated separately for Woman 46.2 1644 each of the nine game types by gambling frequency, and Man 53.8 1911 means were presented in two figures for the whole data Age group and by number of game types (1–2 game types vs. at 18–24 9.1 325 least three game types). If there were less than three re- 25–34 14.9 529 spondents in a subcategory the corresponding mean was rounded to lower disclosure risk. All analyses were 35–44 15.8 563 weighted based on gender, age and region of residence. 45–54 18.3 649 Log-linear regression analysis was conducted using SPSS 55–64 22.7 806 version 23.0 and the mean figures were constructed 65–74 19.2 683 using R . Education level Up to lower secondary education 15.2 542 Results Upper secondary 7.9 281 Demographics Basic vocational qualification 33.4 1188 Nearly half (46.2%) of the 3555 respondents were women (Table 1). The respondents’ mean age was Short cycle tertiary education 16.6 591 48.38 years. Most participants had basic vocational qual- Bachelor’s or equivalent 14.9 530 ifications (33.4%) or a higher degree (42.9%). Master’s or equivalent 11.4 407 Missing 0.5 16 Weekly gambling Overall gambling frequency The different game types differed in popularity (Table 2). Less often than monthly 27.5 979 More than one-third (37.8%) of the gamblers played lot- 1 to 3 times a month 27.4 975 tery games on a weekly basis. The second most common Weekly or more often 45.0 1600 game types played on a weekly basis were low-paced daily lottery games (9.3%), slot machines (7.1%) and bet- Number of game types ting games (5.0%). 1 29.6 1051 2 26.8 953 Models explaining WGE and RGE 3 17.3 616 WGE was available for 3202 respondents and averaged 4 or more 26.3 935 9.71 €/week (SD 43.72). RGE was available for 3194 re- Gambling mode spondents and averaged 3.0% of personal net income Strictly land-based 71.4 2539 (SD 12.73). Using the stepwise forward method, eight Online 28.69 1016 game type variables were included in the models; only fast-paced lottery games were excluded. The models ex- Total 100 3555 plained the higher amount of weekly expenditure (χ2 Weighted based on gender, age and region of residence (N = 3555, non-weighted) (33) = 3716.19, p < .001) and relative gambling expend- iture (χ2 (33) = 3314.94, p < .001) statistically signifi- cantly (Table 3). Males’ weekly spending was 39% higher less spent nearly three times more than their highly edu- than females’, and relative to their annual net income cated counterparts. 22% higher than females’ spending. Age also had an ef- All participation factors had an effect on expenditure. fect on both expenditure measures. Almost all age Those who gambled once a week or more spent 14 times groups spent less on gambling than persons aged 65–74. more than those who only gambled rarely and 16 times Relative to personal net income, however, gamblers more relative to their personal net income. Engaging in under 25 spent 79% more than those aged 65–74. The four or more game types increased weekly expenditure effect of education level on both expenditure measures and relative expenditure by 52 and 62%, respectively, was reversed as almost all education groups spent more compared to those who played one game type. Gambling on gambling than those with the highest education level online increased weekly expenditure by just 10% and (Master’s or equivalent). Relative to their personal net was not statistically significantly associated with relative income, those who had a lower secondary education or gambling expenditure. Salonen et al. BMC Public Health (2018) 18:697 Page 5 of 12 Table 2 Weekly gambling by game types Table 2 Weekly gambling by game types (Continued) %N %N a b,c Weekly lottery games Non-monopoly gambling non-player 11.5 408 non-player 85.7 3046 less than once a week 50.7 1802 less than once a week 13.6 484 at least once a week 37.8 1344 at least once a week 0.7 25 Fast-paced daily lottery games Total 100 3555 Weighted based on gender, age and region of residence (N = 3555, non- non-player 92.3 3282 a b weighted). Finnish gambling monopoly games; PAF, Ålands less than once a week 7.1 252 Penningautomatförening’s games; Gambling internationally outside the Finnish gambling monopoly. FSMA Finland’s Slot Machine Association at least once a week 0.6 21 Low-paced daily lottery games Those who played non-monopoly games at least once a non-player 72.2 2566 week had a four times higher expenditure and a less than once a week 18.4 655 three-and-a-half times higher relative expenditure than at least once a week 9.3 332 gamblers who did not play abroad. Other game types where weekly gambling had an effect on expenditure mea- Scratch cards sures were low-paced daily lottery games, scratch games, non-player 47.3 1680 betting games, slot machines, horse race betting and on- less than once a week 50.8 1805 line poker, where weekly gamblers had a 31–155% higher at least once a week 2.0 70 expenditure than the corresponding non-players. Betting games non-player 82.3 2925 WGE and RGE by game types Those who played non-monopoly games had the highest less than once a week 12.7 452 mean WGE (146.84 €/week) among weekly gamblers at least once a week 5.0 178 (Fig. 1). Other game types with high mean WGE were Casino games online poker (59.61 €/week), scratch games (51.77 non-player 91.8 3265 €/week) and horse race betting (48.67 €/week). RGE less than once a week 8.0 285 means were highest among those who gambled weekly at least once a week 0.1 5 non-monopoly games (30.63%), scratch games (14.77%), betting games (14.20%) and online poker (13.65%) Slot machines (Fig. 2). non-player 65.0 2309 Fast-paced daily lottery games (n = 2), scratch games less than once a week 27.9 993 (n = 9), horse race betting (n = 5), online poker (n =1) at least once a week 7.1 253 and non-monopoly gambling (n = 0) had less than 10 Horse games weekly gamblers who gambled only one or two game non-player 93.0 3306 types (Figs. 1-2). Among those who gambled only one or two game types, the highest WGE and RGE means were less than once a week 5.6 200 recorded for horse race betting and other betting games. at least once a week 1.4 49 WGE and RGE means were lower for those who played Private betting one or two game types compared to the corresponding non-player 95.2 3383 means for all gamblers, except for horse race betting less than once a week 4.7 168 (WGE means 53.40 €/week vs. 48.67 €/week and RGE at least once a week 0.1 4 means 15.50% vs. 11.02%) and betting games (RGE a,b,c means 19.16% vs. 14.20%). The WGE and RGE means Online poker for those who played at least three game types weekly non-player 96.5 3430 were similar to the corresponding means for all less than once a week 3.0 106 gamblers. at least once a week 0.5 19 Non-poker games on FSMA online casino Discussion non-player 98.1 3489 Male gender, lower education level, higher gambling fre- quency and higher number of game types increased both less than once a week 1.7 60 WGE and RGE, which is in line with previous research at least once a week 0.2 6 (e.g. [20–22]). Our results also indicated that younger Salonen et al. BMC Public Health (2018) 18:697 Page 6 of 12 Table 3 Multiple log-linear regression models explaining weekly and relative gambling expenditure Weekly gambling expenditure (€) Relative gambling expenditure (%) exp(β) 95% CI exp(β) CI 95% CI Gender Female 1.0 1.0 Male 1.39*** 1.28–1.50 1.22*** 1.12–1.34 Age group 65–74 1.0 1.0 55–64 0.97 0.87–1.08 0.89 0.79–1.01 45–54 0.90 0.80–1.01 0.77*** 0.67–0.88 35–44 0.87* 0.76–0.99 0.76*** 0.65–0.88 25–34 0.74*** 0.64–0.85 0.86 0.73–1.01 18–24 0.69*** 0.59–0.82 1.79*** 1.48–2.16 Education level Master’s or equivalent 1.0 1.0 Bachelor’s or equivalent 1.32*** 1.14–1.53 1.66*** 1.41–1.95 Short cycle tertiary education 1.40*** 1.21–1.61 1.96*** 1.67–2.30 Basic vocational qualification 1.48*** 1.30–1.68 2.20*** 1.90–2.54 Upper secondary 1.17 0.98–1.40 1.97*** 1.61–2.40 Up to lower secondary education 1.48*** 1.28–1.72 2.88*** 2.43–3.41 Overall gambling frequency Rarely than monthly 1.0 1.0 1–3 times a month 4.68*** 4.21–5.20 5.00*** 4.44–5.63 Once a week or more 14.20*** 11.91–16.93 16.22*** 13.29–19.78 Number of game types 1 1.0 1.0 2 1.06 0.93–1.19 1.07 0.93–1.23 3 1.24* 1.05–1.47 1.32** 1.08–1.60 4 or more 1.52** 1.19–1.94 1.62** 1.23–2.13 Gambling mode Strictly land-based 1.0 1.0 Online 1.10* 1.00–1.20 1.01 0.92–1.12 Weekly lottery games Non-player 1.0 1.0 Less than once a week 0.88 0.76–1.01 0.67*** 0.56–0.79 At least once a week 1.17 0.97–1.42 0.83 0.67–1.03 Low-paced daily lottery games Non-player 1.0 1.0 Less than once a week 1.08 0.97–1.21 1.03 0.91–1.17 At least once a week 1.67*** 1.44–1.93 1.62*** 1.37–1.91 Scratch games Non-player 1.0 1.0 Less than once a week 0.99 0.89–1.10 0.91 0.81–1.03 At least once a week 1.79*** 1.37–2.33 1.44* 1.07–1.94 Betting games Non-player 1.0 1.0 Salonen et al. BMC Public Health (2018) 18:697 Page 7 of 12 Table 3 Multiple log-linear regression models explaining weekly and relative gambling expenditure (Continued) Weekly gambling expenditure (€) Relative gambling expenditure (%) exp(β) 95% CI exp(β) CI 95% CI Less than once a week 1.20** 1.05–1.36 1.16* 1.01–1.34 At least once a week 1.78*** 1.49–2.12 1.80*** 1.47–2.20 Slot machines Non-player 1.0 1.0 Less than once a week 0.84** 0.75–0.95 0.83** 0.73–0.94 At least once a week 1.31** 1.10–1.56 1.43*** 1.18–1.74 Horse games non-player 1.0 1.0 less than once a week 1.09 0.93–1.27 1.08 0.91–1.30 at least once a week 2.46*** 1.82–3.31 2.55*** 1.82–3.57 Online poker non-player 1.0 1.0 less than once a week 1.27* 1.03–1.58 1.24 0.97–1.58 at least once a week 1.83* 1.13–2.97 1.79* 1.03–3.09 Non-monopoly gambling non-player 1.0 1.0 less than once a week 1.06 0.94–1.19 1.03 0.89–1.18 at least once a week 4.09*** 2.68–6.25 3.59*** 2.23–5.79 Weighted based on gender, age and region of residence (N = 3202 in WGE model and N = 3194 in RGE model). Significance probabilities * p < .05; ** p < .01; *** p < .001 Fig. 1 Mean weekly gambling expenditure (euros) by game type (all, 1–2 game types, ≥ 3 game types) Salonen et al. BMC Public Health (2018) 18:697 Page 8 of 12 Fig. 2 Mean relative gambling expenditure (%) by game type (all, 1–2 game types, ≥ 3 game types) age decreased WGE, but increased RGE. This may be examined the risk factors for low risk gambling, moderate partly explained by lower overall income, since low in- risk gambling and problem gambling amongst sports bet- come in general [15, 16] is a risk factor for excessive ters . Their results indicate, that gambling expend- gambling it can be seen as possibly posing greater harm iture, number of accounts with different operators, to this specific age group, such as indebtedness that may number of different types of promotions used and gam- in turn increase harmful gambling. bler’s impulsiveness were significantly higher for all above Overall gambling frequency was the strongest explana- mentioned risk groups, while age, gender, some normative tory factor of both WGE and RGE, which supports the factors, and particular sports betting variables only applied results of previous research . Weekly horse race bet- to those with the highest level of gambling-related prob- ting, non-monopoly gambling and online poker had the lems. These results suggest, that when assessing risk fac- greatest increasing effect on expenditure, but scratch tors for problematic gambling, severity of gambling games, betting games and daily low-paced lottery games should be taken into account, when possible, thus differ- also contributed significantly to overall expenditure. Fur- ent levels of gambling problems should be assessed separ- thermore, betting games and online poker were associ- ately when possible. ated with higher expenditure even when they were Weekly gambling outside the Finnish gambling mon- played less often than weekly. Our results suggest, in opoly had the greatest increasing effect on gambling ex- certain circumstances high WGE on these particular penditure. This result must be interpreted with caution, game types may be seen as indicators of unhealthy gam- however, since there was only a small number of weekly bling involvement, as has been previously suggested non-monopoly gamblers. Non-monopoly gamblers tend (e.g.[9, 10]). to be heavy consumers of several game types [5, 6, 45], Some studies indicate, that sports betting is associated including monopoly games. In addition, non-monopoly with problem gambling [8, 45] while some studies indicate gambling remains as a somewhat indefinite game type that it is not [7, 10]. Sports betting and poker can be category, since it may, in fact, include any number of viewed as a lifestyle practice, often a regular feature of so- game types, as well as, any number of player accounts cial interaction and leisure time . Gamblers may be in- with different international gaming operators. Therefore, clined to take unnecessary risks to demonstrate their it may represent merely a time spent on gambling rather “knowledge” of the game and enhance their social esteem. than a certain game type. The unique feature of sports betting and poker is competi- Frequent playing of several games is associated with tion . Game providers should avoid targeting this gambling problems [7, 9, 10]. In addition, online prob- group with advertisements that create false notions of ex- lem gamblers are often mixed-mode gamblers who play pertise . Furthermore, a recent Australian study multiple types of games [47–49]. The major justification Salonen et al. BMC Public Health (2018) 18:697 Page 9 of 12 for the Finnish gambling monopoly is that it has the po- EGMs (69%), betting games (9%), poker (5%) and casino tential to reduce gambling harms, and the updated Lot- games (5%) . On the other hand, some studies indi- teries Act furthermore places emphasis on prevention cate that slot machines are not among the top five game . As in many other countries, Finnish gambling oper- types associated with problem gambling [4, 10]. ators have in recent years been working to develop tools The results provide useful information about gambling for responsible gambling (RG). Recent Finnish surveys expenditure patterns by game type. At the same time, indicate that RG tools are used quite rarely and that they underscore the fact that gambling participation gamblers’ awareness about these tools must be improved needs to be studied in its entirety. This was particularly [11, 12]. clear in Figs. 1, 2, which showed that for those gambling One of the games that increased gambling expenditure at least three game types weekly, WGE and RGE means was weekly horse race betting. Based on register data were similar to the corresponding means for all gam- provided by gambling operators, a typical gambler is a blers. Gambler profiles can be grouped based on gam- middle-age man who gambles seven times a month, bling participation and the combination of different spending on average 33 euros a day when gambling . game types played [46, 54]. A study on gambling clusters In Finland, online horse race betting seems to be con- indicates that gambling on slot machines, sports betting centrated: most gamblers spend rather small amounts of and playing multiple games are the strongest indicators money, but there is a small group of active bettors who of gambling problems . These clusters provide useful contribute a large proportion of total turnover . Par- leads for future studies on game types and gambling ticipation and interest in horse racing and betting seems expenditure. to be a social cross-generational process , which is There is evidence that high gambling expenditure is not the case with other types of betting. LaPlante and associated with gambling-related harms [18, 31, 46, 55, colleagues studied gambling problems, type of gambling 56]. However, we still have an incomplete picture of and gambling involvement and noticed that the relation- what level of expenditure indicates harms. A Finnish ship between both horse race betting and private betting study that used the South Oaks Gambling Screen  and problem gambling changed when gambling involve- indicates that on average, problem gamblers spend ment factors were adjusted for . In other words, gam- 11.8%, probable pathological gamblers spend 17.3%, and bling only these two particular betting games seemed to non-problem gamblers spend 1.6% of their monthly net protect gamblers from problems [7, 9]. In fact, they sug- income on gambling . Gender differences have also gest that engaging in game types including peers might been reported in the relative amount of income associ- encourage control and preclude excessive gambling , ated with problematic gambling in Finland . which is opposite to the findings for sports betting . Weekly lottery games were not associated with high Study limitations expenditure, but daily lottery games were. Weekly lottery Phrasing of the question and response instructions mat- games are slow pace and sometimes perceived as a ‘soft’ ter when inquiring about gambling expenditure [58, 59]. type of game , or indeed not even viewed as a form of In our study, was inquired by one question instead of gambling at all . Nevertheless, there are some addict- assessing it separately for each game types, and gambling ive features of lottery games that are salient to the expenditure was not explained in the instructions for the psychology of lottery gambling . Recent develop- respondents. Furthermore, game types were inquired ments of lottery games have extended gambling fre- using a list of available game types provided by different quency from weekly to biweekly and daily gambling, but operators. These gaming providers have their own RG also changed their geography from regional or national tools, but we were unable control for the use of these to transnational and gambling mode from land-based to tools. Furthermore, the number of games varies in differ- online platforms. These changes have increased the ent game type categories. Moreover, specific game types addictiveness of this game type. We suggest that future may be played more frequently than others due to the studies should make a clear distinction between different nature of the games . For example, it is quite rare types of lottery games. that live casino games are played on a weekly basis. In Finland has one of the highest per capita numbers of our study, however, live casino games included table slot machines in Europe. In our model, weekly slot ma- games such as roulette and Blackjack run by a croupier chine gambling was also associated with higher expend- outside a casino. PAF games on cruise ferries are rarely, iture, but it was not among the most significant game if ever, played on a weekly basis. Weekly non-monopoly types. Slot machine gambling is nevertheless associated gambling therefore mainly reflect non-monopoly online with gambling-related harms [7, 8, 38, 43, 45]. Moreover, gambling. The game type list which includes several based on the national helpline Peluuri, the primary game gambling modes and game characteristics can create types that cause problems among Finnish gamblers are overlapping categories . Furthermore, there is the Salonen et al. BMC Public Health (2018) 18:697 Page 10 of 12 possibility of incomplete coverage, meaning that some Acknowledgements The authors wish to thank Mr. David Kivinen for revising the language of this game types are assessed by subtypes and others are not paper. . For example, betting games were divided into horse games and other types of betting, and three subtypes of Funding This research was funded by the Ministry of Social Affairs and Health, lottery games were identified. Helsinki, Finland (section 52 of the Appropriation of the Lotteries Act). Overall, gamblers frequently underestimate their losses However, the Ministry had no role in the study design, analysis or [59, 61–65]. Despite this, it has been shown that interpretation of the results nor in any phase of the publication process. self-reported gambling losses correlate with register-based Availability of data and materials losses. Gamblers with higher losses, however, tend to have The Finnish gambling 2015 dataset is available from the Finnish Social more difficulty estimating their gambling expenditure [64, Science Data Archive (http://www.fsd.uta.fi/en/). 65]. A high intensity of play, problem gambling and the Authors’ contributions type of game gambled may also cause estimation bias. AHS, JK, RP and SC were responsible for the study conception and design; People who play games that carry a social stigma (such as SC & AS conducted literature searches and provided summaries of previous research studies. JK and RP performed the analysis; AHS, JK, RP, and SC were EGMs) may underestimate their expenditure . Further- responsible for the interpretation of the data and manuscript preparation; more, self-reported losses have proved to be more accurate HA made critical revisions to the paper for important intellectual content; all when using a 3-month rather than a 12-month time frame authors read and approved the final version. . Our results therefore give an estimation of overall ex- Ethics approval and consent to participate penditure. One of strengths of this study is its high re- The survey was conducted in accordance with the ethical standards of the sponse rate. Declaration of Helsinki. The Ethics Committee of the National Institute for Health and Welfare, Finland, approved the research protocol (THL/1122/ 6.02.01/2014). Potential participants received written and verbal information about the study and the principles of voluntary participation. Verbal Conclusions informed consent was obtained from all participants. Permission to use the register data was obtained from Statistics Finland. Gambling frequency was the strongest indicator of high ex- penditure, as also suggested in previous studies [7, 9]. How- Competing interests ever, this study provides some useful information about The authors do not hold any position, receive ongoing or significant funding, and are not engaged in any business or with any organization that gambling expenditure patterns by game type. Different creates a real or perceived conflict of interest in their work on this game types had different effect sizes on gambling expend- manuscript. iture, and we identified several games types that increase both WGE and RGE. Weekly gambling on horse races and Publisher’sNote non-monopoly games had the greatest increasing effect on Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. expenditure. Great effort should be made by game pro- viders and policy makers to inform individuals about these Author details particular games and possible harms related to them. In Alcohol, Drugs and Addictions Unit, National Institute for Health and Welfare, P.O. Box 30, FI-00271 Helsinki, Finland. Faculty of Health Sciences, addition, betting games, sports betting and online poker in University of Eastern Finland, Kuopio, Finland. Public Health Evaluation and particular, were associated with higher expenditure even Projection Unit, National Institute for Health and Welfare, Helsinki, Finland. when they were played less often than weekly. Similarly, Abdominal Center, University and University Hospital of Helsinki, Helsinki, Finland. Department of Psychology and Speech-Language Pathology, more active harm-minimizing initiatives are recommended Faculty of Social Sciences, University of Turku, Turku, Finland. particularly for sports bettors and online poker players. However, different game types also varied according to their Received: 28 June 2017 Accepted: 25 May 2018 popularity, and therefore the extent of potential harms caused by high expenditure also varies on the population References level. Studies of gambling problems have found that few 1. Browne M, Langham E, Rawat V, Greer N, Li E, Rose J, Rockloff M, Donaldson P, Thorne H, Goodwin B, Bryden G, Best T. 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