Sociodemographic determinants of youth sports club participation across two generations: the Young Finns Study

This study provided valuable insights into youth SCP among Finnish children and adolescents across two generations in the 1980s and the 2020s. It examined how sociodemographic and geographical factors, such as sex, family income, parental education, urbanity of residential area, and geographical region, were associated with youth SCP. The findings showed that SCP was more prevalent among Finnish children and adolescents in the 2020s than in the 1980s. In the 1980s, participation in sports club activities several times a week was less common in girls than in boys. However, by the 2020s, this difference was no longer observed, indicating more sex-equitable access in sports clubs. Parental education and, particularly, family income were positively associated with youth SCP, with these associations appearing at younger ages in the 2020s than in the 1980s. Children and adolescents living in rural areas or Eastern-Northern Finland had less frequent SCP than those in urban areas or Western-Southern regions.

Age- and sex-related tendencies in youth SCP across two generations

The current study aligns with previous findings that SCP, especially SCP several times a week (Vuori et al. 2004), has increased in Finland over recent decades (Laakso et al. 2008; Mathisen et al. 2019). Similar trends have been reported in other Nordic countries, such as Iceland (Eiosdóttir et al. 2008) and Norway (Mathisen et al. 2019). Based on a 2022 report by the European Commission, Finland, along with Denmark, Sweden, Luxembourg, and the Netherlands, has the highest rates of exercise and sports participation in Europe in the twenty-first century (European Commission for Education 2022). Thus, sports clubs play an important role in promoting PA among youth in the twenty-first century.

The observed increase in youth SCP in Finland across the two generations, particularly among younger age groups participating several times a week, suggests a shift toward earlier sports engagement. This tendency likely reflects societal and political changes (Lehtonen 2012; Hoekman et al. 2015) shaping norms and attitudes toward physically active lifestyle, an increase in parental awareness of the health benefits of PA (European Commission for Education 2022), and more diverse sports options (Koski et al. 2015). Notably, many parents now dedicate resources (e.g., time, fees, transportation, equipment, and emotions) to their children’s sports, finding it beneficial for both child development and parental satisfaction (Sutcliffe et al. 2024). However, for those participating in a single sport several times a week, there is a risk of early specialization (defined as engaging in a single sport for over 8 months annually before age 14; Sugimoto et al. 2024). Early specialization has been associated with higher dropout rates and health risks (Sugimoto et al. 2024), including injury (Jayanthi et al. 2019). Sports medicine organizations encourage multi-sport participation for children and adolescents for balanced physical and psychological benefits (Jayanthi et al. 2019). Thus, it is important to promote fundamental movement skills programs rather than focusing solely on a specific sport in young children.

Lower participation rates among older adolescents compared to younger children align with findings that PA (Lounassalo et al. 2019) and SCP (Vuori et al. 2004; Blomqvist et al. 2019; Emmonds et al. 2024) tend to decline with age. This trend remained consistent across both generations, highlighting the major challenge of sustaining adolescent involvement in organized sports, which is important because sports engagement in adolescence is often linked to lifelong PA (Batista et al. 2019; Lagestad 2019). The primary reasons for dropping out from organized sports among youth include lack of enjoyment, lack of perceived competence, social pressures, competing priorities, and physical factors such as maturation and injuries (Crane and Temple 2015). To retain older adolescents in sports, more flexible and noncompetitive options for participation are needed that align with the interests of youth and accommodate their schedules.

The current study showed that in the 1980s, boys were more likely than girls to participate in SCP several times a week, highlighting past sex differences in SCP in Finland. By the 2020s, this difference largely disappeared. The change concerning reduced sex disparity in Finnish youth SCP has been reported in other data as well (Mathisen et al. 2019). Meanwhile, a recent study analyzing data from over 5 million participants aged 8–18 across 27 European countries found that boys were four times as likely to participate in organized youth sports as girls, with this trend consistent across age groups and most sports (Emmonds et al. 2024). Sex disparity in youth SCP in Finland appears to have decreased over the decades, possibly due to advances in sports sector and policy (Lehtonen et al. 2022) and general sex equality, which is higher in Finland than the EU average (EIGE—European Institute for Gender Equality 2023).

Socioeconomic and areal disparities in youth SCP across two generations

As discovered previously (Telama et al. 2009; Post et al. 2023), both SES indicators, family income and parental education, were positively associated with youth SCP. While in the 1980s, income disparities in SCP were seen mainly among 15- and 18-year-olds, by the 2020s, these gaps extended to all younger age groups. A Norwegian study showed similar results: little evidence of social class differences was found in youth SCP through the 1980s to the early 2000s, while later studies revealed widening SES-based disparities (Strandbu et al. 2017). It might be that the more educated and wealthier parents, with more changes, choices, and resources, are more likely to enroll their children in sports clubs than those with lower SES.

In Finland, key trends in the youth sports sector over recent decades include increased professionalism, differentiation, rising costs, and greater parental involvement (Strandbu et al. 2017; Koski and Mäenpää 2018; Post et al. 2018), all of which may limit access to organized sports for less affluent families. The rising costs of running sports clubs reflect higher standards and expectations (Koski et al. 2015). For example, paid employees, once limited to large competitive clubs, are now common even in smaller clubs (Koski and Mäenpää 2018). Additionally, Finnish parents have learned to be “customers” of sports clubs, reflected, for example, in the decrease in volunteer fundraising in sports clubs - down by one third between 1986 and 2006 (Koski 2012). As seen in studies from other developed countries (Vandermeerschen et al. 2016; Hobza et al. 2022; Post et al. 2023), this direct association between SES and SCP shows how SES increasingly shapes youth SCP and widens disparities.

While SES is associated with youth organized sports (Telama et al. 2009), it does not necessarily impact general PA levels in children (Nielsen et al. 2012). For example, a Finnish study found no difference between high and low SES families in unorganized or school-based PA (Telama et al. 2009). To promote inclusivity, affordable and flexible PA options, such as school-based activities (e.g., physical education, structured recess breaks, active school breaks, after-school multi-sport clubs), neighborhood playgrounds for self-organized activities, and accessible public community-based sports facilities, should be provided and prioritized. These options can make PA more accessible to children of all socioeconomic backgrounds.

The study highlights the influence of geographical region and residential area on SCP across both generations. Living in Western-Southern Finland was associated with higher SCP in the 2020s when compared to those living in Eastern-Northern Finland, especially among younger children. This difference may be due to work-related migration from Northern and Eastern Finland to the South and Southwest, regions with higher SES (Fina et al. 2021), over recent decades (Heikkilä 2003). Rural youth, especially in sparsely populated areas, were less likely to engage in SCP several times a week compared to urban youth. Previous findings also showed remoteness associated with decreased SCP (Palomäki and Heikinaro-Johansson 2011; Eime et al. 2015), likely due to fewer sports clubs, programs, and facilities (Koski et al. 2015), as well as longer travel distances in rural areas (Yousefian et al. 2009).

This may contribute to regional disparities in SCP, particularly with the ongoing urbanization since the 1960s (Koski and Mäenpää 2018). Transportation challenges in rural areas make school-based physical activities critical, often the only way for children and adolescents to be active. In Finland, the long distances in the sparsely populated areas can make walking and biking an unrealistic option for youth, and even traveling by car may be a challenge. Addressing rural transportation issues, such as offering late school buses and car pools, could provide affordable access to sports after school for children living in rural areas (Yousefian et al. 2009). It has also been suggested that collaboration with municipalities and community organizations, such as parks and recreation centers, could strengthen youth sports programs and increase local capacity in less affluent areas (Kellstedt et al. 2021).

Strengths and limitations

The strengths of this study include its two-generation population-based sample representing both sexes. The study design enabled the assessment of changes in SCP over time between the original YFS population (G1) living their youth in the 1980s and their offspring’s SCP in the 2020s (G2). The study population was extensive, with over 3000 participants from the 1980s and over 1000 participants from the years 2018–2020. SCP was assessed at different ages during childhood and adolescence, providing a wide perspective on the prevalence of youth SCP. This is important because PA tends to decline among these age groups (Lounassalo et al. 2019). The study identified several factors contributing to disparities in youth SCP. However, the explanatory power of the multinomial logistic regression analysis, based on Cragg and Uhler’s pseudo-R-squared, was relatively weak (0.09–0.29), indicating that the majority of the variation in participants’ SCP remains unexplained by the correlates in the selected models. Other factors potentially contributing to SCP disparities, such as disabilities (Sahlin and Lexell 2015), injuries (Pandya 2021), attitudes (Adell et al. 2019), perceived physical competence (Mehtälä et al. 2020), sociocultural norms (Sport England 2004), ethnic and cultural background (Wijtzes et al. 2014), discrimination (Kalina and Moustakas 2024), social support (Sheridan et al. 2014), parental PA (Van Der Horst et al. 2007; Schoeppe et al. 2016), parental co-participation in PA (Laukkanen et al. 2018), and parental experience in youth sports (Sutcliffe et al. 2024), were not included in this study.

This study also has limitations regarding the generalization of results, as the findings may either overestimate or underestimate the true associations. First, the longitudinal design of this study with the G1 population resulted in some participants being included in the data multiple times, for example, once as a 12-year-old and later as a 15-year-old. This approach utilized all available data from each age group. Second, while the original YFS population (G1) was randomly selected and representative of the general population, the G2 group was not, as they were the offspring of the G1 participants. Additionally, the G2 data include some siblings, whose results may be more closely correlated with each other than with those of non-siblings. Third, the G1 participants in the analytical sample may differ systematically from those who dropped out of the study. Previous attrition analysis shows that remaining G1 participants were more often female and older than those who dropped out, but did not differ, for example, by PA or parents’ study years (Raitakari et al. 2008). Finally, the age structure differs between the two generations, which may affect comparability: G1 cohorts were sampled and followed at steady 3-year intervals, while the coincidental age distribution of G2 participants was grouped into four broader corresponding age categories.

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