Socially disadvantaged youth is one of the social groups that are considered vulnerable. When developing appropriate health and social programs and measures, it is important to take into account specific factors linked to youth in structurally disadvantaged regions or neighborhoods [1]. Structurally disadvantaged regions are characterized by lower development in socio-economic indicators such as economic development and unemployment [2]. Differences between regions within European countries are growing [3], and the issue of structurally disadvantaged regions becomes urgent. At a European level, one objective of the drug strategy is to improve preventive measures, taking into account cultural and social factors [4]. Therefore, a study of the influence of socioeconomic status (SES) on gambling, internet use, and/or substance use in adolescents from a structurally disadvantaged region may provide useful insights.

Regarding SES and both gambling and internet use, Lee and McKenzie [5] highlighted the lack of research focused on risky behaviors connected with the use of the internet, and Reith [6] accented the same concerning gambling. As for gambling, Molinaro et al. [7] did not find any relationship between parental education, family structure, and gambling. Consistent with Vitaro et al. [8] and Langhinrichsen-Rohling et al. [9], the analysis by Molinaro et al. [7] showed that family structural characteristics do not have an influence on gambling compared to family relationship characteristics (family support, awareness of free time activities, and rules). However, in a more recent study, Molinaro et al. [10] described the effect of family economic status, the parental education, and the structure of the family on gambling prevalence. The families with medium economic status had significantly lower odds of gambling, while stepfamilies and other family structures except single-parent families had significantly higher odds of gambling than traditional families [10]. The parental education had a rather small effect; the father´s high schooling increased the odds of gambling and the mother´s decreased the odds of gambling [10]. Furthermore, in a recent systematic review, Henkel and Zemlin [11] reported on the relationship between SES and problematic gambling, when the unemployment and migration status were associated with higher prevalence of problematic gambling. The review of longitudinal studies by Dowling et al. [12] also revealed the effect of socioeconomic status on the addiction in question, and Canale et al. [13] examined the influence of socioeconomic status on problematic gaming, both at the individual and regional levels, showing that students living in unequal and poorer regions have higher odds of at-risk gambling. Elgar´s study [14] suggested that youth who live in economically unequal settings and perceive a lack of social support are at higher risk of disordered gambling. The relationship between gambling and SES might be also explained by the higher density of electronic gambling machines in areas with lower SES [15]. Based on a longitudinal study, Auger et al. [16] showed that individuals with lower SES and impulsivity had earlier age of gambling onset. Van der Maas [17] showed—although among adults—that social setting, which has been downplayed in current problem gambling research, has an important influence on gambling.

In the literature, diverse results were found regarding SES and risky internet use. Blinka et al. [18] did not find any influence of the family type and parental education on an excessive use of the internet. Additionally, Spilková et al. [19] found no connection between the family environment and an excessive internet use. On the contrary, Durkee et al. [20] found that the composition of the parents’ household and their employment had an impact on problematic internet use, parental unemployment, and absence of biological parents increasing the risk of problematic use. Lee and McKenzie [5] also found a relationship between low SES and internet addiction, and Ko et al. [21] found that single-parent families are at a higher risk. More recent results from Slovakia showed evidence of the relationship between SES and excessive internet use [22,23]. Urbanová [22] found that adolescents with an unemployed father and perceived low family wealth were more at-risk of excessive internet use. Another study showed that overprotection and lower socioeconomic status were related to the risk of excessive internet use. Contradictory findings were also reported regarding SES and substance use among adolescents [14,15,16,17,18,19,20,21,22,23,24,25,26]. The review by Patrick et al. [27] found evidence of a relationship between SES and substance use, although the shape of this relationship varied.

One explanation for the different findings regarding the role of SES in all three types of risky behaviors discussed in this paper, besides differences in research methodology used in the studies, may be that the social structure and its effect on risky behaviors vary across countries with different social structures. For example, this might have been the case of Molinaro et al. [7], who did not take into account the different structures of countries included in the model. Similarly, the study on internet use by Blinka et al. [18] used a single model for all different countries. Studies that took SES into consideration have been listed as well, e.g., one study of repeated drunkenness showed that the relationship between SES and repeated drunkenness differed between countries [28]. Canale et al. [13] and Gori et al. [29] identified regional differences in the problematic gaming incidence within Italy that corresponded to the socioeconomic characteristics of the regions. Exploration of the connection between substance or behavioral addictions and the socioeconomic inequality at country levels were recommended for the objective of further studies, according to Molinaro et al. [10] and Reith [6] in the case of youth gambling, and according to Galea et al. [30] in the case of substance use.

Our study is focused on the relationship between addictive behaviors (internet use, gaming, and gambling), substance use, and SES in a structurally disadvantaged region. In contrast to previous studies focusing on the national-wide [19] or all-European [10,18] populations of adolescents, we focused on adolescents in a structurally disadvantaged region. According to our knowledge, this is the first study to investigate the relationship between SES and the risk of behavioral addictions in a structurally disadvantaged region among the student population. The aim of this was to study the relationship between SES and risky internet use, gambling, and substance use in structurally disadvantaged region particularly in the Ústí nad Labem Region, one of the most structurally disadvantaged regions in Central Europe. In many terms, the Ústí nad Labem Region may be considered an example of a structurally disadvantaged region in Central Europe, including lower life expectancy, higher poverty rate, high unemployment, poor educational structure, negative internal migration from the region, and a high number of socially excluded locations (see [31]).