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NAŠE GOSPODARSTVO / OUR ECONOMY 68 (3) 2022 Prodky, I.
The Social and Economic Importance of Sports
Ivan Prudky
University of Rijeka, Faculty of Economics and Business, Croatia 
ivan.prudky@efri.hr
                        
ARTICLE INFO
         
Original Scientific Article
Article History:
Received June 2022
Revised August 2022
Accepted August 2022
         
JEL Classification:
Z20
Z28
         
Keywords:
Sports participation
Sports and social aspects
Sports and economic aspects
Sports policy regulation
         
UDK: 796.01:33:316
DOI: 10.2478/ngoe-2022-0018
         
Cite this article as: Prudky, I. (2022). 
The Social and Economic Importance 
of Sports. Naše Gospodarstvo/Our 
Economy, 68(3),  61-71. DOI: 10.2478/
ngoe-2022-0018. 
         
©2022 The Authors. Published by Sciendo 
on behalf of University of Maribor, Faculty 
of Economics and Business, Slovenia. This 
is an open access article under the CC 
BY-NC-ND license (http://creativecommons.
org/licenses/by-nc-nd/4.0/). 
         
Abstract
Sports participation does not produce benefits solely on a personal level but 
also numerous benefits on different societal levels, as well as the level of 
economies. The paper represents a contribution to the exploration of factors of 
individuals influencing regularity in sports participation. A logistic regression 
model was used based on the data from the Eurobarometer special survey 
from 2018. According to the findings, middle-aged men are the most likely 
to regularly participate in sports activities and individuals with active socio-
professional status are also more likely to practice regular sports activities 
than individuals who are passive. The same is true for individuals living in less 
urbanised areas and those with positive life satisfaction compared to those 
living in urban areas or those who are not satisfied with their life. The results 
of our research are important for economic policymakers both at the national 
and regional levels, as well as at the level of individual municipalities. They 
facilitate the management of sports activities of individuals but are limited 
to a smaller number of factors with measurement specifics. Suggestions for 
further research are also presented.
Introduction
Sports participation goes beyond influencing an individual's quality of life 
and has a significant social and economic impact on the whole community. 
Policymakers aim for better management of sports activities, with the goal 
of a more successful valorization of positive effects produced by sports 
activities. Institutions invest in research on the socio-economic impacts of 
individual sports participation habits to determine the economic and public 
health benefits of regular physical activity (Ács et al., 2016; Schüttoff et al., 
2021). Based on acquired knowledge, institutions adapt and tailor incentive 
measures and guidelines, aiming for benefits to individuals and the community 
(Official Journal of the European Union, 2013) and develop indicators to 
measure the effectiveness of government policies regarding sports and 

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NAŠE GOSPODARSTVO / OUR ECONOMY 68 (3) 2022 Prodky, I.
costs. An increase in subjective well-being and social 
benefits urges governments and policymakers to put more 
effort and means aiming for the population’s increase in 
sports participation (Ruseski et al., 2014). Inclusiveness 
and seizing inequality are social benefits associated with 
increased population sports activity (Van Tuyckom, 2011; 
Hoekman et al., 2016). The European Union, based on the 
premise of equality for all citizens, recognizes the potential 
of sports and successfully uses sport to achieve one of its 
primary goals (European Commission, n.d. a, n.d. b, n.d. c). 
Policymakers use sports programs in lower socio-economic 
areas to overcome class-based inequalities (Hoekman et al., 
2016). Moving down, the local administration encourages 
increased sports participation by investing in infrastructure 
(Downward et al., 2014) and holding sports events where the 
population is an active participant, not a passive observer. 
All offer the possibility of achieving economic, social, and 
psychological gains for the local community (Andersen et 
al., 2019; Hautbois et al., 2020). 
A short bibliometric analysis shows an exponential increase 
in published scientific documents on “sports participation” 
(Figure 1). Searching the Scopus database (category: 
Title-Abstract-Keywords), the term „sports participation“ 
presents 18,582 document results (as of June 2022). The 
spikes in increase coincide with major world organizations’ 
publications regarding the importance of physical activity 
(World health organisation in 2004, 2010, 2016, 2018). 
Numerous governing institutions finance research on the 
topic of "sports participation". Highly positioned funding 
sponsors include the U.S. Department of Health and Human 
Services, the Government of Canada and the European 
Commission.
Figure 1
Number of publications with the topic "sports participation", 
1990-2021
Source: Author’s research, based on Scopus, 2022
Areas of research dealing with sports participation 
are presented in Figure 2. In addition to medicine and 
health professions, high shares of research occur within 
social sciences, economic and business sciences, and 
environmental sciences. All stated research areas support 
sports activity (World Health Organisation, 2016, 2018). An 
EU-level survey investigates individuals’ habits on physical 
and sports activities tied with their socio-economic and 
demographic characteristics (European Commission, n.d. 
b). The result is an overview of participation in sports, 
motives, barriers, and potential opportunities for local 
communities (European Commission, 2018). Research 
findings prove that national government spending and 
public health policies focused on sports and physical 
activity are positively related to the increase in the share 
of people with perceived good health and negatively 
related to obesity (Szczepaniak, 2020).
A bibliometric analysis emphasizes the rising importance 
of the sports participation issue. Scientific research 
focusing on individual sports and physical activity will 
provide valuable knowledge (Hovermann & Wicker, 2009; 
Downward et al., 2014; Ley, 2020), and the most recent 
data on a large sample represents a valuable source of 
information for the analysis of new impacts influencing 
sports participation. Gradual, constant changes in 
population and economy create a need for understanding 
based on the latest available data to form and adopt new 
directives stimulating sports participation, with the overall 
goal of improving the social and economic well-being of 
the community. 
In this paper, we focus on determining an individual’s 
socio-demographic and economic factors (age, gender, 
socio-professional status, degree of urbanization of 
residential area, life satisfaction) recognized as significant 
impacts on regular participation in sports. Based on these 
findings, it is possible to form precise campaigns adapted 
to target groups, encouraging individuals' greater sports 
participation and consequently forming a better social and 
economic situation on a personal and community level.
Literature Review and Research Framework
The importance of sports participation and physical activity 
impacts multiple levels of the community. On a national 
level, an increase in residents’ sports participation leads 
to numerous economic (Ács et al., 2016; Hautbois et al., 
2020; Schüttoff et al., 2021) and social (Ruseski et al., 
2014; Hoekman et al., 2016; Mills et al., 2019) benefits. An 
increase in public health directly decreases government 
public health service expenditures (Ács et al., 2016, 2020; 
Schüttoff et al., 2021). Sports encouragement measures are 
seen as positive expenditures to prevent future negative 
consequences of the population’s inactivity, as opposed 
to post-damage repairing expenses, such as public health 

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research on improving individuals or communities on a 
socio-economic level.
Figure 2
Sports participation in different research areas
Source: Author’s research, based on Scopus, 2022
Different internal and external factors determine the 
individual's willingness to participate regularly in sports. 
Economic, social, and demographic characteristics were 
most frequently researched (Hovemann & Wicker, 2009; 
Kokolakakis et al., 2012; Downward et al., 2014; Hallmann 
& Breuer, 2014; Laczkó et al., 2020; Magno et al., 2020). 
The age of individuals negatively affects the regularity, 
frequency, or intensity of sports participation, in some 
country-specific cases (e. g. Slovakia) (Laczkó et al., 2020). 
Men tend to engage in sports and physical activities more 
regularly, as show studies for the EU (Hovemann & Wicker, 
2009), England and Spain (Kokolakakis et al., 2012), and 
for Brazil (Magno et al., 2020). Contrary, in the case of 
Germany (Hallmann & Breuer, 2014), women are the ones 
who participate more regularly in sports activities. Gender 
as a factor of influence can be impacted by the underlying 
aspect of country and culture. Men and women also have 
different reasoning for active sports participation (Magno 
et al., 2020; Ley, 2020). Thus, a gender-sensitive approach 
should be considered when making policies encouraging 
sports activity (Ley, 2020; Laczkó et al., 2020). 
Personal social characteristics such as level of education, 
socio-professional status, and marital status determine an 
individual's free time. In the 2000s, more educated and 
employed people spent significantly less time in sports 
activities (Hovemann & Wicker, 2009). In the 2010s, the 
population changed its habits, and people with higher 
levels of education (Kokolakakis et al., 2012; Hallmann 
& Breuer, 2014; Magno et al., 2020, Laczkó et al., 2020), 
as well as people in active employment and with longer 
working hours (Kokolakakis et al., 2012; Hallmann & 
Breuer, 2014), start to engage more in physical and sports 
activities. Most recently, white-collar job holders see sports 
participation as part of their lifestyle (Laczkó et al., 2020). 
Married individuals and those with children engage in 
sports activities less regularly (Hovemann & Wicker, 2009) 
than single individuals (Laczkó et al., 2020). The level of life 
satisfaction is directly related to sports participation. Sports 
activity positively impacts life satisfaction (Wiese et al., 
2018; Zhang & Chen, 2019). Still, the relationship goes both 
ways, as higher levels of subjective well-being stimulate 
the desire for sports participation (Mutz et al., 2020).
The residence size can also impact one’s possibilities for 
regular sports activity, as the availability of infrastructure 
suggests greater sports participation. People in big cities 
(Hovemann & Wicker, 2009; Magno et al., 2020; Laczkó et 
al., 2020) and more urbanized areas (Van Tuyckom, 2011; 
Magno et al., 2020) participate more regularly in sports 
activities. Still, specific country and cultural characteristics 
are other underlying factors (Van Tuyckom, 2011). The 
Netherlands is an example: more urbanized areas offer 
lower opportunities to participate in sports activities 
(Hoekman et al., 2016). Promoting sports programs in lower 
socio-economic regions is advisable for policymakers to 
overcome class-based inequalities.
Research Model and Hypotheses Development
The research model was formulated based on the 
literature review and the Eurostat statistical data and 
surveys (presented in the following paragraphs). The 
statistical data provided by Eurostat (2022) show (Figure 
3) the relative proportion of the population over 15 years 
of age participating in sports and recreational (leisure) 
physical activities at least once a week for the years 2014 
and 2019. The EU average is 43% in 2014 and 44% in 
2019. Most countries recorded an increase in the value 
of sports participation, except Malta, Austria, France, 
Portugal, Latvia, and Slovakia.
Figure 3
Level of sports participation at least once a week
Source: Eurostat, 2022

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General trends across the EU can be observed from the 
latest data. Men are more active as 47% partake in sports, 
while the average value for women is 42%. The trend 
is valid in most countries, excluding Denmark, Sweden, 
Luxembourg, and Latvia. With the aging population, 
sports participation decreases, starting with the EU 
average value of 65% for the age group from 15 to 24 
years and ending with the average EU value of 31% for 
the age group 65 years and over.
Citizens with different income levels show other habits in 
engaging in sports activities. According to the EHIS data 
(Eurostat, 2022), with an increase in income, the average 
participation in sports activities also increases: (1) first 
income quintile – 37% of people, (2) second income 
quintile – 38% of people, (3) third income quintile – 44% 
of people, (4) fourth income quintile – 48% of people 
and (5) fifth income quintile – 55% of people. Different 
level of education is also associated with varying 
habits in sports participation. Grouped according to 
the International Standard Classification of Education 
(ISCED) (Eurostat, 2020), the average share of EU citizens 
who spend at least 150 minutes on health-enhancing, 
non-work-related physical activity weekly is as follows: 
(1) low level education (ISCED 0-2) – 25% of people, (2) 
medium level education (ISCED 3-4) – 33% of people and 
(3) high level education (ISCED 5-8) – 42% of people. 
The well-being of the population is one of the main 
goals of every country. Encouraging the people to engage 
in sports activities is one of the institutional goals of 
governments and regional integrations. Knowledge 
of relevant factors influencing engagement in sports 
activities presents a critical research gap. Based on the 
findings from Eurostat, the EHIS survey results (Eurostat, 
2022), and relevant scientific research, a general 
hypothesis is set: personal characteristics and external 
factors significantly influence an individual's intention 
to participate in sports activities. The specific knowledge 
can be of great benefit to different policymakers. Proper 
management aims to engage irregular participants 
in more sports activities, ultimately creating socio-
economic benefits for the community.
Derived from the general hypothesis, five different sub-
hypotheses (Figure 4) will be tested: 
• H1: Age has a significant negative influence on sports 
participation.
Age is the incremental part of every conducted survey on 
sports activity and participation (Eurobarometer, EHIS) 
and scientific research of multiple authors (Hovemann 
& Wicker, 2009; Kokolakakis et al., 2012; Downward et 
al., 2014; Hallmann & Breuer, 2014; Laczkó et al., 2020; 
Magno et al., 2020). Previous findings and statistical 
data (Eurostat, 2022) suggest that with increasing age, 
participation in sports decreases. Certain EU countries 
show irregular trends (Eurostat, 2022; Laczkó et al., 
2020), giving additional reasoning for researching age 
as a specific factor influencing sports participation.
• H2: Gender has a significant influence on sports 
participation.
Gender is another indispensable researched factor 
in conducted surveys (Eurobarometer, EHIS) and the 
subject of scientific analysis regarding the impact on 
sports participation. Based on the previously stated 
statistics (Eurostat, 2022), the male population seems 
more likely to participate regularly in sports activities, 
with some countries as exceptions. Scientific research 
comes to the same conclusion (Hovemann & Wicker, 
2009; Kokolakakis et al., 2012; Laczkó et al., 2020), but 
not unanimously (Hallmann & Breuer, 2014).
• H3: An active socio-professional status has a significant 
favorable influence on sports participation.
The Eurobarometer survey on sports participation 
collects data on individuals' socio-professional status 
as the subject of the analysis. Eurostat’s (2022) statis-
tics present data where the population with an active 
working status more regularly participates in sports 
activities. Previously conducted research has come to 
non-uniform conclusions, stating negative (Hovemann 
& Wicker, 2009) and positive correlations (Kokolakakis 
et al., 2012; Hallmann & Breuer, 2014; Laczkó et al., 
2020).
• H4: Urbanisation level has a significant positive influence 
on sports participation.
The Eurobarometer survey on sports participation 
provides data on the perceived urbanization level of 
residency. Previous scientific research gives mixed 
results for the correlation effect (Van Tuyckom, 2011; 
Heokman et al., 2016; Magno et al., 2020). Based on 
the assumption that the availability of infrastructure 
in urban areas makes regularity in sports participation 
more possible, available data and inconclusiveness in 
previous research make the urbanisation levels as an 
impact very relevant to the study.
• H5: Life satisfaction is positively correlated to sports 
participation. 
Based on the previously stated statistics, it is 
observed and concluded that the population with 
more regular participation in sports activities has 
higher life satisfaction levels. The connection has 
proven to be mutual: subjective well-being has a 
positive impact on sports activity, as does sports 
activity on the subjective well-being of individuals 
(Mutz et al., 2020).

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NAŠE GOSPODARSTVO / OUR ECONOMY 68 (3) 2022 Prodky, I.
Figure 4
Sports participation influential factors
Age
Gender
Socio-professional
Urbanisation
Life satisfaction
Sports
participation
H1
H2
H3
H4
H5
Source: Author’s research
Data and Methodology
Eurobarometer publication »Sport and physical activity« 
provides data based on a large sample to test the stated 
hypotheses. Performed periodically (2002, 2009, 2013, and 
2017) in EU member states, the survey from December 
2017 had a sample size (N) of 28,031 citizens of diverse 
demographic and social characteristics. The survey 
participant characteristics are shown in Table 1.
Data on the citizen’s involvement in sports activities and 
their essential demographic and social characteristics were 
selected. Based on the European Health Interview Survey 
(Eurostat, 2022) definition of sports participation and 
physical activity, the citizen’s sports participation regularity 
was determined by the provided answers to the questions 
„How often do you exercise or play sport?“ and „And how 
often do you engage in other physical activity such as 
cycling from one place to another, dancing, gardening, etc.?“. 
The offered answers to the cited questions were identical 
on a scalar basis and thus comparable (5 times a week or 
more, 3 to 4 times a week, 1 to 2 times a week, 1 to 3 times 
a month, less often, never, and don’t know). For the analysis, 
a binary logistic regression model will be constructed 
(Tabachnick & Fidell, 2019). 
The binary logistic regression model is:
Ln
p
p
SEXA G PROFD URBS AT e
1
01 23 45







     
(1)
where the variables are:
• SP sports participation, 
• SEX gender, 
• AG age group,
• PROFD socio-professional status, 
• URB subjective urbanization, 
• SAT life satisfaction.
Table 1
Characteristics of survey participants
Variable Number (%)
Gender
Male 13586 (48.5)
Female 14445 (51.5)
Age group (years)
15-24 3730 (13.3)
25-34 4096 (14.6)
35-44 4576 (16.3)
45-54 4778 (17.0)
55-64 4395 (15.7)
65-74 3833 (13.7)
75 and over 2623 (9.4)
Socio-professional status
Active 13348 (47.6)
Passive 14683 (52.4)
Subjective urbanization
Rural village 8314 (29.7)
Small/medium size town 12467 (44.5)
Large town 7250 (25.9)
Life satisfaction
Yes 23813 (85.0)
No 4218 (15.0)
N = 28031 participants
Source: Author
The overview of variables and their operationalization is 
shown in Table 2. For the sake of „sports participation“, the 
results from the two beforementioned survey questions 
were merged and used for the analysis. The variable 
sports participation (SP) is used as the model’s dependent 
variable. The dependent variable SP was defined as a 
nominal dummy variable: 0 representing irregular sports 
participation (constructed from the answer values: never, 
less often, and 1–3 times a month), and 1 representing 
regular sports participation (constructed from the answer 
values: 1–2 times a week, 3–4 times a week and five 
times a week or more). The independent variables are 
gender (SEX; dummy: male – 0, female – 1), age group 
(AG; nominal; groups: 15–24 years, 25–34 years, 35–44 
years, 45–54 years, 55–64 years, 65–74 years, 75+ years), 
socio-professional status (PROFD, dummy: active status 
(constructed of groups: self-employed, managers, other 

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NAŠE GOSPODARSTVO / OUR ECONOMY 68 (3) 2022 Prodky, I.
white collars, manual workers) – 0, passive status (created 
of groups: house person, unemployed, retired, students) – 1), 
subjective urbanisation (URB; nominal; groups: rural village, 
Table 2
Model variables operationalization
Variable Operationalisation Scale
Dependent variable: Sports participation (SP) Regular weekly participation in sports (0 = no, 1 = yes) Dummy
Independent variables: Gender (SEX) 0 = male, 1 = female Dummy
Age group (AG)
0 = 15–24 years, 1 = 25–34 years, 2 = 35–44 years, 3 = 45–54 
years, 4 = 55–64 years, 5 = 65–74 years, 6 = 75 years and over
Nominal
Socio-professional status (PROFD) 0 = active, 1 = passive Dummy
Subjective urbanisation (URB) 0 = rural village, 1 = small/mid-size town, 2 = large town Nominal
Life satisfaction (SAT) 0 = no, 1 = yes Dummy
Source: Author’s research.
small/mid-size town, large town) and life satisfaction (SAT; 
dummy: not satisfied – 0, satisfied – 1).
The model is constructed as a binary logistic regression 
(Tabachnick & Fidell, 2019). The dependent variable is a 
binary nominal variable. The independent variables gender, 
socio-professional status, and life satisfaction are binary 
dummy variables. The variables age group and subjective 
urbanization are categorical covariates with three and 
seven categorical group values, respectively. A demi-dummy 
coding for the categorical variables was enforced starting 
from the last category. Maximum likelihood estimates were 
used to estimate the logistic regression function, denoting 
changes in the log odds of independent variables. We used 
the Wald test to test the significance of the regression 
coefficients, the Omnibus test to test the predictive capacity 
of the regression equation, and the Nagelkerke R squared 
value to assess the goodness to fit of the model. For testing 
purposes, the threshold for the significance will be at the 
0.01 level to reduce the possibility of Type I error.
Results
The results of the model are presented in Table 3. Using 
the Wald statistic (Tabachnick & Fidell, 2019), a hypothesis 
was tested if the probability of being a defaulter versus a 
non-defaulter is equal. We can reject the null hypothesis 
(sig. = 0.000) that there is an equal number of people 
within the sampling variability. The negative value of the 
regression model intercept indicates a higher likelihood for 
an individual not regularly participating in sports activity 
than the likelihood to participate. 
Based on the Omnibus test of model coefficients, the listed 
Chi-square values are statistically significant to test if there 
is some predictive capacity in the regression equation (sig. 
level < 0.01). Additional information about the predictivity 
capacity of the modes was provided using the Nagelkerke 
R squared value, giving an insight into the explained 
variation of the independent variable (Tabachnick & Fidell, 
2019). The independent variables account for only 4% of the 
dependent variable, which is expected since other factors 
influence one’s regular sports participation.
The model’s validity was tested using the Hosmer and 
Lemeshow test – the Chi-square value is statistically 
insignificant (sig level > 0.01), indicating the predictability 
possibility of the model. The contingency table for the test 
for the segregated probabilities in the categories shows 
that the accounted difference in the number of people in 
those categories for the expected and observed values is 
zero indicating a high predictive capacity in the model. The 
classification table of the model shows that irregular sports 
participation was correctly predicted by 81.7%, while the 
same value for regular sports participation is 27.1%. Overall, 
the model’s predictive capacity is 57 .9% (+1.5 PPS compared 
to the null model).
Based on the unstandardized beta coefficient (Table 3), we 
draw interpretations in terms of the movement of the value 
of the dependent variable. All values represent a change in 
a log scale, with negative signs suggesting that the log of 
the odds of regular sports participation is decreasing, or if 
positive, the log of the odds of regular sports participation 
is increasing. Model (1) is expressed in the form (2):

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NAŠE GOSPODARSTVO / OUR ECONOMY 68 (3) 2022 Prodky, I.
Odds SP e
SEXA G PROFD URBS AT
() 
  
1
01 23 45
  
(2)
The interpretation of the influence of variables is transformed 
into ratios instead of the difference in change of variable units. 
Based on the results, we found evidence to support hypothesis 
2. On average, the probability that women regularly participate 
in sports activities equals 43.1% (sig. < 0.01) of the likelihood 
for men, indicating that gender affects the regularity of sports 
participation. Also evident is that the socio-professional 
status of an individual affects the individual’s sports activity. 
The probability that socio-professionally passive individuals 
(house person, unemployed, retired, students) regularly 
participate in sports activities equals 53.3% (sig. < 0.01) of 
the probability that holds for socio-professionally active 
individuals (self-employed, managers, other white collars, 
manual workers) on average, supporting hypothesis 3. The 
findings give an insight into the connection of a person’s life 
satisfaction, as it increases the odds that a person regularly 
participates in sports activities by a ratio of 2.805 (sig. < 0.01). 
The upper value rises to the value of 3.234, meaning those 
who stated positive life satisfaction are three times more 
likely to participate in sports activities regularly, proving 
hypothesis 5.
Table 3
Results of logistic regression
Variable 
β
Wald df Sig. Exp( β)
95% C.I. for Exp( β)
Lower Upper
AG 214.272 6 0.000
AG(1) 0.148 0.748 1 0.387 1.160 0.829 1.623
AG(2) -0.044 0.067 1 0.796 0.957 0.684 1.338
AG(3) 0.278 3.845 1 0.050 1.320 1.000 1.743
AG(4) 0.677 29.181 1 0.000 1.967 1.539 2.514
AG(5) 0.552 23.544 1 0.000 1.737 1.390 2.171
AG(6) -0.401 30.781 1 0.000 0.670 0.581 0.772
SEX -0.842 93.250 1 0.000 0.431 0.363 0.511
PROFD -0.629 67.863 1 0.000 0.533 0.459 0.619
URB 191.238 2 0.000
URB(1) -0.610 22.788 1 0.000 0.544 0.423 0.698
URB(2) -1.085 166.779 1 0.000 0.338 0.287 0.398
SAT 1.032 202.438 1 0.000 2.805 2.434 3.234
Constant 0.077 0.630 1 0.427 1.080
Model χ
2
859.473 11
Block χ
2
859.473 11
Nagelkerke R2 0.040
% of correct predictions 57.9
Notes: AG = age group 75 years and over; AG(1) = age group 15–24 years; AG(2) = age group 25–34 years;  AG(3) = age group 
35–44 years;  AG(4) = age group 45–54 years;  AG(5) = age group 55–64 years;  AG(6) = age group 65–74 years;   SEX = gender; 
PROFD = socio-professional status; URB = large town; URB(2) = rural village; URB(2) = small/medium size town; SAT = life 
satisfaction.
Source: Authors

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The values for the independent variable age group, while 
comparing the age group 75+ years to the younger age 
groups (15–24, 25–34, and 34–44 years), prove to be 
insignificant (sig. > 0.01). While comparing the difference 
between the age group 75+ years to the older age groups 
(45–54, 55–64, and 65–74 years), the values in change 
prove to be significant (sig. < 0.01). The results say that the 
odds that a person aged 45–54 years regularly participates 
in sports activity is 1.967 more likely, a person aged 55–64 
years is 1.737 times more likely, and a person aged 65–74 
years is 0.670 times more likely to regularly participate in 
a sports activity than a 75+ years old person. Additionally, 
when comparing the age groups 15–24, 25–34, and 34–44 
years to the base age group of 75+ years, the insignificant 
results suggest that their sports participation habits are 
entirely different. Based on these conclusions, we can 
prove hypothesis 1, stating that age significantly affects the 
regularity of an individual’s sports participation. 
The urbanization level negatively affects the regulatory 
sports participation level – the odds that a person regularly 
participates in a sports activity gets lower by the ratio of 
0.544 when comparing people living in small/medium-
sized towns to people living in rural villages, and the value 
further decreases when comparing regular sports activity 
of people living in large cities to people living in rural 
villages. Hypothesis 4 is rejected (sin < 0.01), as the results 
show that the increase in urbanization level actual decision 
to be involved negatively affects the regularity of sports 
participation.
Discussion
Sports participation has long ceased to be a point of 
interest at an individual’s level. Governments, institutions 
and policymakers are actively interested in studying sports 
and physical activity effects on the community. The positive 
impact on individuals directly expands to economic and 
social conditions of the community – for example, lower 
total health care costs generated at the state level (Sato 
et al., 2019; De Boer et al., 2020; Coughlan et al., 2021; 
European Commission, n.d. c). Governments and regional 
institutions recognize the positive effects – the European 
Union is widely known for wanting to create coherence, unity 
and identity conditions within its population, and sport is 
one of the ways they intend to achieve this goal (European 
Union, 2019; European Commission, n.d. b). Therefore, the EU 
makes efforts and invests significant funds in designing and 
constituting decisions and rules on sports to gain numerous 
benefits it can provide to the community. The Scopus 
database provides insights into numerous institutions that 
fund the research and publication of scientific papers based 
on sports participation, putting the topic under the scrutiny 
of scientific research. Various study areas deal with different 
viewpoints of “sports participation”, all contributing to 
raising awareness of sports having a profound potential to 
influence the socio-economic status of communities.
Numerous benefits on multiple levels stemming from sports 
participation and activity create the need for knowledge 
about factors impacting the individual's motivation for 
regular sports participation. Based on the data of the 
Eurobarometer research, an analysis of factors influencing 
sports participation was conducted. As in previous 
studies (Hovemann & Wicker, 2009; Van Tuyokom, 2011; 
Kokolakakis et al., 2012; Downward et al., 2014; Hallman 
& Brener, 2014; Hoekman et al., 2016; Magno et al., 2020), 
some socio-economic and demographic characteristics 
have positively influenced sports participation. Still, some 
negative ones have also been determined. This research 
also found that socio-professional status positively impacts 
sports participation, with individuals in an active working 
status more regularly participating in sports activities, 
which is in line with the results of studies conducted after 
2010 (Laczkó et al., 2020). Research has shown that men are 
slightly more involved in sports participation than women, 
but the ratio is close to an equal distribution. It is possible 
to notice a slight shift from the findings of Hovemann 
and Wicker (2009) and Kokolakakis et al. (2012) based 
on a general EU level. The individual’s age was proved 
statistically significant, in line with previous research. The 
research highlights the differences in sports participation 
between younger and older age groups. Urbanization was 
also a variable of significant influence, although the impact 
proved to be negative, contrary to the stated assumption 
and previous findings (Magno et al., 2020; Laczkó et al., 
2020). People living in more urbanized environments are 
less involved in regular sports participation than people 
living in less urbanized areas, although the availability 
of infrastructure would suggest otherwise. It seems that 
outdoor activities are more likely to occur in a more 
rural environment. Lastly, people who stated positive life 
satisfaction are prone to participate more regularly in sports 
activities than individuals with negative life satisfaction 
(approx. three times more likely). This is in line with the 
findings of Mutz et al. (2020), adding to the theory that 
higher levels of subjective well-being stimulate the desire 
for sports participation.
Knowledge of the benefits of sports participation is 
essential. Still, knowing which factors influence individuals’ 
participation in sports is necessary. It is easier to achieve 
multi-level socio-economic benefits from sports participation 
if known. Thus, the results of our research are important 

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for policymakers at the regional, national and local levels 
of government. It is necessary to encourage horizontal 
and vertical implementation of measures to increase 
participation in sports to achieve the desired positive socio-
economic effects. The actions and directives must be aimed 
at the inactive population, and it is necessary to tailor them 
according to observed factors of significant impact.
Conclusion
Our research shows that regular sports activity is, on 
average, the domain of men, especially between the ages 
of 34 and 64, those with active socio-professional status 
who do not live in a highly urbanized environment, all of 
which describe men who have achieved a certain position 
in their professional career. Therefore, the results of our 
research show that it makes sense to take appropriate 
measures to encourage women to participate in regular 
sports activities on an equally frequent basis, which 
means that it makes sense to determine the obstacles or 
reservations that prevent this. An efficient measure may 
be an organized workout for women at the municipality 
level, especially for women in different age groups. The 
results of our research are also crucial for the designers 
of study programs, as younger people, especially students, 
are less likely to regularly participate in sports activities 
than the group mentioned above (middle-aged men who 
are professionally active). Regular sports activity should 
thus become an important part of extracurricular activities, 
which should be regularly organized or even part of 
traditional study programs. Given the EU directives and the 
established positive impact of regular sports activity on an 
individual's physical and mental well-being, research in this 
field, presented in this paper only from the point of view of 
some selected influencing factors, is important. 
The research conducted is limited to a few personal 
characteristics of individuals, which is reflected in the 
overall explanatory value of the model. The individual 
characteristics were carefully selected concerning previous 
studies that did not provide unambiguous results. Another 
limitation of the research is the operationalization of 
selected independent variables – socio-professional status 
divided into an active and passive state, instead of choosing 
occupation of individuals as a determinant, and the life 
satisfaction measurement defined as a binary variable 
instead of a specific scalar value.
Several extensions to our research are possible. Future 
research may include additional different characteristics 
(such as working-class affiliation, generational groups, 
level of education, marital status and experience in sports) 
or otherwise determine categorical variables (e.g. other 
age groups, multiple levels of socio-professional status, 
grouping by gender and age at the same time, various levels 
of life satisfaction).
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Družbeni in ekonomski pomen športa
Izvleček
Športno udejstvovanje ne prinaša koristi le na osebni ravni, temveč tudi številne koristi na različnih družbenih ravneh, pa tudi 
na ravni gospodarstva. Članek predstavlja prispevek k raziskovanju dejavnikov posameznikov, ki vplivajo na rednost športnega 
udejstvovanja. Uporabljen je bil logistični regresijski model na podlagi podatkov posebne raziskave Eurobarometra iz leta 
2018. Na podlagi ugotovitev je najbolj verjetno, da se bodo redno ukvarjali s športnimi dejavnostmi moški srednjih let, prav 
tako je bolj verjetno, da se bodo redno ukvarjali s športnimi dejavnostmi posamezniki z aktivnim socialno-profesionalnim 
statusom kot posamezniki, ki so pasivni. Enako velja za posameznike, ki živijo na manj urbaniziranih območjih, in tiste, ki so 
zadovoljni z življenjem, v primerjavi s tistimi, ki živijo na urbanih območjih oz. tistimi, ki s svojim življenjem niso zadovoljni. 
Rezultati naše raziskave so pomembni za oblikovalce gospodarske politike tako na nacionalni in regionalni ravni kot tudi 
na ravni posameznih občin. Olajšujejo upravljanje športnih aktivnosti posameznikov, vendar so omejeni na manjše število 
dejavnikov s posebnostmi merjenja. Predstavljeni so tudi predlogi za nadaljnje raziskave.
Ključne besede: športno udejstvovanje, šport in družbeni vidiki, šport in ekonomski vidiki, ureditev športne politike