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Citation: Górka-Chowaniec, A.;
Niewczas-Dobrowolska, M.;
Akba¸s, A.; Bezuglov, E.; Sikora, T.;
Wa´skiewicz, Z. Socio-Demographic
Influences on Dietary Habits and
Nutritional Awareness: A Case Study
of Polish Biathlon Association
National Team Members. Nutrients
2024,16, 3784. https://doi.org/
10.3390/nu16213784
Academic Editor: Miguel Mariscal
-Arcas
Received: 3 October 2024
Revised: 28 October 2024
Accepted: 30 October 2024
Published: 4 November 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Socio-Demographic Influences on Dietary Habits and
Nutritional Awareness: A Case Study of Polish Biathlon
Association National Team Members
Agnieszka Górka-Chowaniec 1, Magdalena Niewczas-Dobrowolska 2, Anna Akba¸s 3, Eduard Bezuglov 4,
Tadeusz Sikora 5and Zbigniew Wa´skiewicz 3,*
1Sport and Tourism Management Faculty, Jerzy Kukuczka Academy of Physical Education,
40-065 Katowice, Poland; gorkachowaniec@interia.eu
2Institute of Quality Sciences and Product Management, Cracow University of Economics,
31-510 Cracow, Poland; niewczam@uek.krakow.pl
3Institute of Sport Science, Jerzy Kukuczka Academy of Physical Education, 40-065 Katowice, Poland;
a.akbas@awf.katowice.pl
4
Department of Sports Medicine and Medical Rehabilitation, Sechenov First Moscow State Medical University,
119435 Moscow, Russia; e.n.bezuglov@gmail.com
5Department of Quality Management, Cracow University of Economics, 31-510 Cracow, Poland;
sikorat@uek.krakow.pl
*Correspondence: z.waskiewicz@awf.katowice.pl
Abstract: Introduction: This study investigated the influence of sociodemographic factors on the
dietary habits of athletes of the Polish Biathlon Association. Focusing on age, education, employment
status, and gender, this research assesses food choices, meal preparation, and nutritional awareness
within a structured sports environment. A cross-sectional survey of 54 athletes was conducted using
a modified “Eating Habits of Poles” questionnaire to explore food selection, preparation methods,
consumption patterns, and nutritional perspectives. This focus on biathletes emphasizes their distinct
dietary needs, which arise from the demanding combination of endurance and precision in their
sport, providing valuable insights for tailored dietary strategies to enhance their performance and
overall health. Results: The results indicate that age, education, and employment status significantly
influence Polish biathletes’ dietary habits and nutritional awareness. Older athletes (under 23 years)
demonstrated significantly higher nutritional awareness regarding modern dietary trends (p= 0.015).
In contrast, 50% of higher-education athletes were more engaged in meal planning and healthier food
choices than those with elementary education (p= 0.031). Employment status also played a role; 70%
of the athletes were students who exhibited more convenience-based food choices, whereas 30% were
employed and maintained more structured eating patterns (p= 0.008). Minimal gender differences
were found, with 50% of male and 50% of female athletes showing similar dietary habits, likely due to
standardized nutrition programs provided to all athletes. Conclusions: This indicates a potential need
for further research to determine whether professional dietary support can effectively address typical
gender-related variations in food behavior and lead to improvements in dietary outcomes. This study
highlights the importance of targeted nutrition education and professional support for optimizing
the nutritional habits of professional athletes. This emphasizes that socio-demographic factors such
as age, education, and employment status significantly shape these behaviors, underscoring the need
for personalized nutritional strategies within athletic programs.
Keywords: dietary habits; nutritional awareness; socio-demographic factors; professional athletes
1. Introduction
Athletes’ diets, shaped by their daily choices, are pivotal in influencing their prepa-
ration, performance, and recovery after competitions. Optimal nutrition is essential not
only for supporting physical activity and enhancing sports performance [
1
–
4
] but also for
Nutrients 2024,16, 3784. https://doi.org/10.3390/nu16213784 https://www.mdpi.com/journal/nutrients
Nutrients 2024,16, 3784 2 of 16
minimizing the risk of injuries [
5
] and speeding up recovery after intense exertion [
6
,
7
].
Athletes are expected to adhere to well-structured eating habits, ensuring their food intake
meets the necessary quantity and quality for high-level performance.
Athletes form a group with specific nutritional needs, and a well-balanced diet is criti-
cal for maintaining their health and exercise performance. Eating behaviors are shaped by
various individual and environmental factors [
8
]. Research has shown that athletes’ dietary
behaviors are dynamic and influenced by multiple factors [
9
–
13
]. Despite expectations,
studies have uncovered certain irregularities in the eating habits of athletes [14–18].
These behaviors are influenced by an integrated and interacting system of factors,
including genetic predispositions, hormonal regulation, sensory development, and envi-
ronmental and cultural contexts. These influences can be grouped into biological traits,
demographic characteristics, and socioeconomic factors such as age, gender, family size,
and income level. Studies have frequently highlighted the importance of sociodemographic
factors in shaping individual eating habits [19–21].
Age, sex, socioeconomic status (SES), nutritional knowledge, and cultural influences
are critical determinants of dietary habits among athletes. Younger athletes and women
often exhibit different nutritional patterns than older athletes and men, with gender differ-
ences evident in meal preparation and fast-food consumption [
22
,
23
]. SES impacts access to
nutritious foods and knowledge, influencing athletes’ dietary practices [
24
–
26
]. Access to
resources like sports dietitians also significantly enhances nutritional practices, particularly
for less experienced athletes [
11
,
24
]. Moreover, cultural norms and food environments
shape athletes’ dietary choices, emphasizing the importance of tailored nutritional inter-
ventions [14]
Education is a critical determinant among significant factors, with more educated
individuals generally displaying excellent nutritional knowledge and healthier eating
behaviors. Research has consistently shown a positive correlation between nutritional
awareness and the adoption of health-promoting dietary habits, although the strength of
this correlation can vary [
10
,
27
,
28
]. Additionally, economic status is crucial in shaping
dietary habits, influencing food quality and the frequency of nutrient deficiencies [
24
–
26
].
Furthermore, athletes’ competitive environments and emotional states may challenge their
ability to follow optimal nutritional guidelines [
11
]. While many factors affecting the
general population also apply to athletes [
11
,
29
–
33
], the athletic environment introduces
specific challenges related to performance, such as the influence of coaches and peers and
competition-related stress [
10
,
27
,
28
,
34
–
36
]. These stimuli and attitudes toward food can
significantly impact dietary choices. As the literature reveals, socio-demographic factors
influence dietary habits in sports settings [
1
,
2
,
6
]. However, more research should focus
explicitly on biathletes, suggesting a need for further exploration [9,36–41].
This research builds on previous studies by focusing on a relatively underexplored
group—professional biathletes—whose dietary habits differ significantly from those of
athletes in other disciplines due to the unique combination of endurance and precision
required in their sport. Unlike previous works broadly examining athletes’ nutrition across
different sports, this study examines how sociodemographic factors such as age, education,
and employment status influence biathletes’ food choices and nutritional awareness. By
doing so, we aim to contribute to more tailored and effective dietary strategies that support
the distinct demands of biathletes, providing new insights that extend beyond the scope of
the existing literature.
Understanding the dietary behaviors of athletes, particularly within structured sports
environments, can provide valuable insights for designing interventions to promote opti-
mal health and performance. This study, therefore, sought to analyze how critical socio-
demographic factors, such as age, education, employment status, household size, and
region of residence, influence the dietary habits of athletes from the Polish Biathlon Associ-
ation. Specifically, it aimed to explore how these variables affect food choices, preparation,
consumption, and athletes’ attitudes toward nutrition to identify the critical determinants
of their dietary behavior.
Nutrients 2024,16, 3784 3 of 16
After defining the aims of the study, several objectives were established to guide the
investigation. The first aim was to examine how age and education influence athletes’
dietary habits and nutritional awareness within the context of Polish biathlon. We hypoth-
esized that younger and higher-educated athletes would demonstrate a more significant
understanding of modern dietary trends. The second aim was to explore the impact of
employment status on food choice and meal planning among athletes in a structured sports
environment. Additionally, this study sought to investigate whether gender differences
influence dietary habits when standardized nutritional programs are implemented among
professional athletes.
2. Materials and Methods
2.1. Study Design and Setting
The adopted cross-sectional research design used the original “Eating Habits of Poles”
research tool with a descriptive phenomenological approach to collect qualitative data
in naturalistic conditions. The demographic characteristics section (the third part of the
questionnaire) was adapted in agreement with the Polish Biathlon Association (PZB)
management to suit the specific group, the PZB Team. The modifications concerned the
demographic characteristics of the studied population, such as the age of respondents
(junior under 23 years old and senior over 23 years old), employment status (student,
unemployed), number of household members (1–3 family members and more than four
members), and place of residence. Due to the personal declaration of residence (province),
it was decided to retain three of the 16 provinces in Poland (Silesian, Lower Silesian, and
Lesser Poland).
Before proceeding with the primary research, pilot studies were conducted using
a research method based on in-depth individual interviews involving a target group of
20 respondents—athletes. The primary research examining the influence of sociodemo-
graphic factors on the eating habits of the Polish Biathlon Association’s team by sport level
(juniors vs. seniors) was conducted between March and June 2022. The research instrument
used at this stage of the study was an original questionnaire that included the characteristics
of the respondents and 35 main questions classified into four areas of analysis (research
constructs): selection of food products based on their consumption type (SP), preparation
and production of food (EP), methods of consuming food (EF), and opinions on food and
nutrition (VF). The respondents’ task was to assess the extent to which they agreed with
the statements regarding their eating habits, which were grouped into four areas. The
respondents’ evaluations, reflecting the degree of acceptance of a given phenomenon or
opinion, was conducted using a 5-point Likert scale, ranging from 1 (strongly disagree)
to 5 (strongly agree). The original assumptions of the research process aimed to reach
respondents through indirect and direct channels using the same research tool, namely a
survey: “Eating Habits of the Staff of the Polish Biathlon Association”. However, consider-
ing the period of intense sports activity that the team was experiencing and the athletes’
travel schedule, the author abandoned one of the planned initial data collection methods
(face-to-face interviews) and opted to conduct the study using the CAWI method.
2.2. Study Population and Sampling Procedure
This study was conducted in Poland among the National Team of the Polish Biathlon
Association population for the 2022/2023 season. It involved 100% of the population of
athletes from the Regulatory Team of the Polish Biathlon Association for the 2022/2023
season, divided into specific subsections according to age range: Senior Women’s Team,
Senior Men’s Team, Junior Women’s Team, and Junior Men’s team. The study sample
comprised 61 athletes. The response rate was 54.
2.3. Data Collection and Quality Assurance
The guide for computer-assisted online interviews was prepared by one of the authors
of this study and the team involved in the research. The guide was comprehensive and cov-
Nutrients 2024,16, 3784 4 of 16
ered all aspects of the team’s goals. He encouraged participants to share their experiences
in their own words and in their way, without forcing them into categories or classifications
imposed by the interviewer. The tool was prepared in Poland. The interview guide was
preliminarily tested and refined to improve its clarity.
2.4. Data Management and Analysis
The Shapiro–Wilk test was used to check for normal distribution, and variance homo-
geneity was assessed using Levene’s test. Since the assumption of normality was not met,
we applied the non-parametric Mann–Whitney U test to examine the influence of sex, age,
employment, and number of household members on the total score (summed across all
questions) for each of the four questionnaire categories (SP, FP, EF, VF). Additionally, the
non-parametric Kruskal–Wallis test was employed to evaluate the effects of education and
voivodship on the total score within each category.
In the second analysis, we focused on individual responses within each category.
Mann–Whitney U and Kruskal–Wallis tests were used to compare responses to personal
questions (Likert scale 1–5) within the four categories across different demographic and
socioeconomic groups. These tests were chosen owing to the ordinal nature of the data.
Effect sizes were reported as r-values for the Mann–Whitney U test, with thresholds
for small (0.1), medium (0.3), and large effects (0.5). For the Kruskal–Wallis test, partial
eta-squared (
η2
) values were reported, with thresholds for small (0.01), medium (0.06), and
large effects (0.14).
All statistical analyses were performed using Statistica v.13.3 (TIBCO Software Inc.).
The results are presented as the mean
±
standard deviation. The alpha level was set at 0.05.
2.5. Ethics Approval and Consent to Participate
This study was approved by the Bioethical Committee of the Academy of Physical
Education in Katowice (KB/54/2021). All procedures in this study were conducted in
accordance with the Declaration of Helsinki, ensuring the complete anonymity and con-
fidentiality of all participants. Personal and sensitive data were thoroughly safeguarded,
and the collected data could not be used to identify individuals or personal cases. Since
the study used online surveys, completing the survey was considered as informed consent,
eliminating the need for a separate consent form. The participants were fully informed of
the study objectives and retained the right to withdraw at any time. No personal identifiers,
such as names, were disclosed.
3. Results
3.1. Characteristics of Participants
Table 1presents the demographic and socioeconomic characteristics of the Polish
athletes who participated in the study. These characteristics were described by sociodemo-
graphic factors, such as sex, age, level of education, employment, number of households,
and voivodship. The initial sample used in the study of the Polish Biathlon Team’s dietary
habits consisted of 54 respondents (61 team members in the 2022/2023 season). Table 1
presents the preliminary demographic characteristics of the respondents along with their
division into individual consumer segments. The athletes participating in the study were
representatives of three provinces in Poland. Among the 54 complete responses, 27 (50%)
were from women, and 27 (50%) were from men. Most respondents were under 23 years of
age (junior category), representing nearly 75% of the sample, with 38 individuals (70.37%)
falling within this age group. The next group consisted of respondents who presented
a family model with to 1–3 members (n= 22; 40.74% of the surveyed). A significant
share was held by respondents who created family models with four or more household
members (n= 32; 59.25% of respondents). As the data in Table 1indicate, students were
predominant among the surveyed individuals (n= 38, 70.37%). The remaining group
comprised unemployed individuals (n= 16, 29.63%). Almost 1/4 of the respondents (n= 13,
24.07%) declared having a primary education. A slightly larger percentage was comprised
Nutrients 2024,16, 3784 5 of 16
of individuals with higher education (n= 14, 25.93%). The most significant percentage of
respondents was athletes with higher education (n= 27, 50%). These constituted half of the
respondents.
Table 1. Demographical characteristics of participants.
Variables n %
Sex
Women 27 50
Men 27 50
Age
Less than 23 38 70.37
23 and over 16 29.63
Education
Elementary 13 24.07
Secondary 27 50
Higher 14 25.93
Employment
Student 38 70.37
Employed 16 29.63
No. of household members
1 to 3 22 40.74
4 and more 32 59.25
Voivodship
Silesia 13 24.07
Lower Silesia 19 35.19
Lesser Poland 22 40.74
3.2. Questionnaire
The study was conducted using a modified questionnaire, “Eating Habits of Poles”,
(Table 2), which aims to examine the lifestyles of consumers and their food purchasing deci-
sions. In developing the original research tool, “Eating Habits of Poles”, the methodological
assumptions were based on several established models and methods. These included:
Khan’s food preference model [
41
], FRL model [
42
,
43
], customer retention model [
44
], RPB
model [
45
], DINESERV method [
46
,
47
], SERVQUAL method [
48
], and Ecoserv method [
49
].
The “PZB Eating Habits Questionnaire” measures 69 questions regarding food product
choices, preferred meal preparation methods, food consumption methods, and opinions
about food and nutrition. Consumers typically rated these items on a 5-point Likert scale
(from 1 (“strongly disagree”) to 5 (“strongly agree”)). The questionnaire used in this study
encompassed 35 dimensions across four interconnected areas: food product selection, food
preparation and production, methods of food consumption, and perspectives on food and
nutrition. This research tool can be used widely in empirical markets. The questionnaire
can be used for consumer segmentation, market segmentation, or for studying the eating
habits of consumers in general or of a specific type of consumer.
In this research, the modified “The Eating Habits of Poles” questionnaire was used to
examine the food behavior of the Polish Biathlon Association Team. A modified version of
the questionnaire was administered. It was based on the original “The Eating Habits of
the Poles” questionnaire. “The Eating Habits of Poles” questionnaire implemented in this
study consists of five domains: food purchase, food preparation, food consumption, and
food opinions/attitudes. There were 35 statements (items) to be assessed by consumers
using a 5-point scale (from 1 (“completely disagree”) to 5 (“completely agree”)).
This questionnaire was tested for reliability in a study of biathletes. Cronbach’s alpha
coefficient was calculated. Its value ranges from 0 to 1. A high Cronbach’s alpha value
indicates that the response values for each participant across a set of questions were consistent.
The accepted Cronbach’s alpha coefficient value is
≥
0.7 or more (maximum of 1). In this
research, the Cronbach’s alpha value was 0.8287; therefore, this questionnaire is consistent
and can be used to examine food-related lifestyles among the National Biathlon Team.
Nutrients 2024,16, 3784 6 of 16
Table 2. “The Eating Habits of PZB” questionnaire used in this research.
Code Food Product Selection
SP1 I read the information on the labels of various products and, based on this, I make choices about
products that are beneficial to my health.
SP2
When purchasing food products, I take into account the opinions of other people (experts on the subject).
SP3 I don’t attach much importance to buying food products, I usually buy what is “at hand”.
SP4 I like to buy products from “health” food and organic food stores.
SP5 When I buy food products, I pay attention to the price.
SP6 Current promotions are important to me when making product purchasing choices.
SP7 Usually, I make the final decision on what to buy only in the store.
FP Food preparation and production
FP1 I don’t like to spend too much time preparing and making meals.
FP2 My cooking process is influenced by my knowledge of the cuisines of other nations.
FP3 In our home, instead of cooking, we often use ready-made meals (dumplings, breaded meat, bigos,
beans, ready-made sauces, soups, etc.).
FP4 I use a lot of instant products, e.g., ready-made baking mixes, soups, and powdered sauces.
FP5 Meals should be planned in advance.
FP6 In modern times, shopping and cooking should be shared equally between women and men.
FP7 When planning my menu, I take into account the seasonality of food products (i.e., in winter I eat more
pickled/fermented foods and in summer I eat more tomatoes, radishes, cucumbers, etc.)
FP8 Having a small child, I try to prepare meals at home more often rather than eating out.
EF Methods of food consumption
EF1 Eating with friends is a great way to spend your free time.
EF2 I pay great attention to ensuring that the products I buy are as minimally processed as possible.
EF3 I compare similar products to make sure the quality matches the price.
EF4 I like trying new foods that I have never eaten before.
EF5 I pay attention to ecological products for which I am willing to pay more.
EF6 I prefer fresh products over frozen ones.
EF7 Eating out is a regular part of my family’s eating habits.
EF8 I prefer to invite family (friends) to a restaurant than prepare a meal for them at home.
EF9 I eat 4–5 meals a day every 3–4 h.
EF10 I have been on a “boxed” diet at least once in my life.
VF Views on food and nutrition
VF1 I am characterized by great nutritional awareness.
VF2
I know what the Healthy Eating Plate looks like, which includes the latest recommendations for healthy eating.
VF3
In view of the problems I have discovered, I am trying to limit the meat and meat product I buy in stores.
VF4 In my family home, a lot of attention is paid to eating meals together.
VF5
I believe that the obesity problem in modern society is due to the frequent consumption of fast food and
highly processed foods.
VF6
Awareness of the existence of many diet-related diseases encourages me to pay more attention to what I
and my family eat.
VF7
I prefer to take dietary supplements rather than attach greater importance to eating fully balanced meals.
VF8 Taste is more important to me than the energy value of the food I consume.
VF9 Since having a child/children, I attach more importance to the quality of the food I consume.
VF10 It is important to me that the quality of the food products I buy is appropriate to the price I pay.
Nutrients 2024,16, 3784 7 of 16
In the first domain, “food purchase”, the aspects of food labeling and choice, informa-
tion consumers use to choose food products, and preferred places to buy food are rated.
In the second domain, “food preparation”, respondents were asked how they planned
and prepared meals. In the third domain, “food consumption”, participants rated their
preferences regarding how they want to consume food. In the last domain, “food opinion,”
participants expressed their views about the characteristics of food and diets that were
important to them.
3.3. The Influence of Demographic and Socioeconomic Factors on Nutritional Habits in Polish
Biathletes—A Total Score Analysis
There was no significant effect of sex, number of household members, or voivodship on
any of the four questionnaire categories (p> 0.05). However, a significant main effect of age
was found in the VF category (food opinion), indicating significantly higher scores in the
older group (more than 23 years old) compared to those aged 23 years or less. Additionally,
a significant difference was found in the type of employment in the SP category (food
purchase), with higher scores among students than among employed individuals (Table 3).
Table 3. The results of U Mann–Whitney (U) and Kruskal–Wallis test (H).
Variables SP FP EF VF
Mean (Std)
U or H(DoF)
Statistic
Mean (Std)
U or H(DoF)
Statistic
Mean (Std)
U or H(DoF)
Statistic
Mean (Std)
U or H(DoF)
Statistic
SexWomen 22.7 (2.93) ns 25 (3.94) ns 36.22 (7.14) ns 36.11 (4.52) ns
Men 22.74 (3.39) 23.81 (3.81) 34.78 (7.69) 34.78 (3.4)
Age
Less than
23 21.75 (2.14) ns 25.44 (4.62) ns 37.56 (8.17) ns 34.47 (3.38) U = 175.5
p= 0.015
r = 0.33
23 and
more 23.13 (3.42) 23.97 (3.51) 34.63 (6.96) 37.75 (4.57)
Education
Elementary
23.85 (1.77) ns
22.69 (2.32)
*
H
(2,54)
= 6.94
p= 0.031
η2= 0.097
31.85 (4.85)
*
H
(2,54)
= 7.72
p= 0.021
η2= 0.11
33.31 (2.98)
*H(2, 54) = 8.67
p= 0.013
η2= 0.13
Secondary 22.7 (3.86) 24.37 (3.64) 34.78 (7) 35.26 (3.75)
Higher 21.71 (2.27) 26.07 (4.92)
*40.29 (7.97)
*37.79 (4.35)
*
Employment
Student 23.29 (3.36) U = 163
p= 0.008
r = −0.36
24.03 (3.58) ns 34.61 (7.08) ns 34.74 (3.64) ns
Employed 21.38 (2.06) 25.31 (4.54) 37.63 (7.88) 37.13 (4.49)
No. of household members
1 to 3 22.82 (2.59) ns 24.86 (4.21) ns 37.59 (7.46) ns 36.59 (4.06) ns
4 and more 22.66 (3.51) 24.09 (3.68) 34.06 (7.09) 34.66 (3.86)
Voivodship
Silesian 23.15 (3.16) ns 23.92 (4.29) ns 36.31 (7.58) ns 36.23 (4.17) ns
Lower
Silesian 23.26 (4.04) 24.68 (3.97) 34 (6.94) 34.37 (3.7)
Lesser
Poland 22 (2.07) 24.45 (3.73) 36.32 (7.77) 35.91 (4.17)
Legend: ns, not significant; U, results of Mann–Whitney U test when comparing two groups, H—results of
Kruskal–Wallis test when comparing more than two groups, SP, Food product selection, FP, Food preparation and
production, EF, Methods of food consumption, VF, Views on food and nutrition, *—indicates significant post-hoc
between elementary and higher education levels.
The type of education significantly impacted the food preparation (FP), food consump-
tion (EF), and food opinion (VF) categories, with post hoc analysis revealing considerably
higher scores among individuals with higher education than among those with elementary
education (FP: p= 0.026; EF: p= 0.021; VF: p= 0.01) (Table 3). The effects of age on food
opinion (VF), employment on food purchase (SP), and education on food preparation (FP),
food consumption (EF), and food opinion (VF) were further explored by considering the
responses to individual questions within those categories.
Nutrients 2024,16, 3784 8 of 16
3.4. The Influence of Demographic and Socioeconomic Factors on Nutritional Habits in Polish
Biathletes—An Analysis of Individual Questions
3.4.1. Effect of Age
The U Mann–Whitney test revealed significantly higher scores in responses to ques-
tions VF1 (“I am characterized by great nutritional awareness”) (U = 197.5, n
1
= 16, n
2
= 38,
p= 0.044, r = 0.27) and VF3 (“Because of the problems I have discovered, I am trying to limit
the meat and meat product I buy in stores”) (U = 182.5, n
1
= 16, n
2
= 38, p= 0.022, r = 0.31)
among older individuals (Figure 1). This suggests that those aged 23 years and older were
more likely to be interested in food products and an active approach to food quality and
safety issues. The older the biathlete, the higher their food awareness. Older respondents
ranked higher in the VF domain (food opinions) (Figure 1). There was no significant impact
of sex on the answers, as the biathletes had the same diet specialists responsible for their
diets. For this reason, they have a limited ability to decide on the food they consume.
Nutrients 2024, 16, x FOR PEER REVIEW 9 of 17
respondents ranked higher in the VF domain (food opinions) (Figure 1). There was no
significant impact of sex on the answers, as the biathletes had the same diet specialists
responsible for their diets. For this reason, they have a limited ability to decide on the food
they consume.
3.4.2. Effect of Education
The Kruskal–Wallis test revealed a significant main effect of education on the
“Preparation and Production of Food” category in questions FP4, FP6, and FP7 (H
(2, 54)
=
7.047, p = 0.03, η
2
= 0.1). However, post hoc analysis did not show any specific differences
between the groups with different education levels (Figure 2). The significant main effects
of education on the “Ways of Consuming Food” category were found in questions EF2
(H
(2, 54)
= 8.87, p = 0.012, η
2
= 0.13), EF6 (H
(2, 54)
= 7.62, p = 0.022, η
2
= 0.11), EF8 (H
(2, 54)
= 8.83,
p = 0.012, η
2
= 0.13), EF9 (H
(2, 54)
= 9.7, p = 0.008, η
2
= 0.15), and EF10 (H
(2, 54)
= 8.5, p = 0.014,
η
2
= 0.13). Post hoc analysis revealed particular differences between those with higher
versus secondary education (p = 0.049) and higher versus elementary education (p = 0.043)
in EF2, which may suggest that the higher the level of education, the higher the
involvement in the degree of food processing and food awareness. Additionally, there
were significant differences between higher- versus elementary-educated individuals in
EF8 and EF10 (see Figure 3), which may indicate that consumers with higher education
levels pay more aention to how they consume food and the food they consume, such as
their nutritional value.
Figure 1. The effect of age on views on food and nutrition (VF). The bars represent the mean scores,
while the error bars indicate the standard deviations (* p < 0.05).
Figure 1. The effect of age on views on food and nutrition (VF). The bars represent the mean scores,
while the error bars indicate the standard deviations (* p< 0.05).
3.4.2. Effect of Education
The Kruskal–Wallis test revealed a significant main effect of education on the “Prepa-
ration and Production of Food” category in questions FP4, FP6, and FP7 (H
(2, 54)
= 7.047,
p= 0.03,
η2
= 0.1). However, post hoc analysis did not show any specific differences between
the groups with different education levels (Figure 2). The significant main effects of educa-
tion on the “Ways of Consuming Food” category were found in questions EF2 (H
(2, 54)
= 8.87,
p= 0.012,
η2
= 0.13), EF6 (H
(2, 54)
= 7.62, p= 0.022,
η2
= 0.11), EF8 (H
(2, 54)
= 8.83,
p= 0.012,
η2
= 0.13), EF9 (H
(2, 54)
= 9.7, p= 0.008,
η2
= 0.15), and EF10 (H
(2, 54)
= 8.5,
p= 0.014,
η2
= 0.13). Post hoc analysis revealed particular differences between those with
higher versus secondary education (p= 0.049) and higher versus elementary education
(p= 0.043) in EF2, which may suggest that the higher the level of education, the higher
the involvement in the degree of food processing and food awareness. Additionally, there
were significant differences between higher- versus elementary-educated individuals in
EF8 and EF10 (see Figure 3), which may indicate that consumers with higher education
levels pay more attention to how they consume food and the food they consume, such as
their nutritional value.
Nutrients 2024,16, 3784 9 of 16
Nutrients 2024, 16, x FOR PEER REVIEW 10 of 17
Figure 2. The effect of education on preparation and production of food (FP). The bars represent the
mean scores, while the error bars indicate the standard deviations.
Figure 3. The effect of education on ways of consuming food (EF). The bars represent the mean
scores, while the error bars indicate the standard deviations (* p < 0.05).
The significant main effects of education on the “Views on Food and Nutrition”
category were found in questions VF3 (H
(2, 54)
= 12.82, p = 0.002, η
2
= 0.21) and VF6 (H
(2, 54)
=
7.71, p = 0.021, η
2
= 0.11). Post hoc analysis revealed differences between those with higher
versus elementary education in both VF3 (p= 0.002) and VF6 (p = 0.023) (see Figure 4). This
also shows a higher awareness of food and the influence of food on our health and well-
being. Moreover, they showed greater engagement in food choices and food ingredients.
Figure 2. The effect of education on preparation and production of food (FP). The bars represent the
mean scores, while the error bars indicate the standard deviations.
Nutrients 2024, 16, x FOR PEER REVIEW 10 of 17
Figure 2. The effect of education on preparation and production of food (FP). The bars represent the
mean scores, while the error bars indicate the standard deviations.
Figure 3. The effect of education on ways of consuming food (EF). The bars represent the mean
scores, while the error bars indicate the standard deviations (* p < 0.05).
The significant main effects of education on the “Views on Food and Nutrition”
category were found in questions VF3 (H
(2, 54)
= 12.82, p = 0.002, η
2
= 0.21) and VF6 (H
(2, 54)
=
7.71, p = 0.021, η
2
= 0.11). Post hoc analysis revealed differences between those with higher
versus elementary education in both VF3 (p= 0.002) and VF6 (p = 0.023) (see Figure 4). This
also shows a higher awareness of food and the influence of food on our health and well-
being. Moreover, they showed greater engagement in food choices and food ingredients.
Figure 3. The effect of education on ways of consuming food (EF). The bars represent the mean scores,
while the error bars indicate the standard deviations (* p< 0.05).
The significant main effects of education on the “Views on Food and Nutrition”
category were found in questions VF3 (H
(2, 54)
= 12.82, p= 0.002,
η2
= 0.21) and VF6
(H
(2, 54)
= 7.71, p= 0.021,
η2
= 0.11). Post hoc analysis revealed differences between those
with higher versus elementary education in both VF3 (p= 0.002) and VF6 (p= 0.023) (see
Figure 4). This also shows a higher awareness of food and the influence of food on our
health and well-being. Moreover, they showed greater engagement in food choices and
food ingredients.
Nutrients 2024,16, 3784 10 of 16
Nutrients 2024, 16, x FOR PEER REVIEW 11 of 17
Figure 4. The effect of education on views on food and nutrition (VF). The bars represent the mean
scores, while the error bars indicate the standard deviations (* p < 0.05).
3.4.3. Effect of Employment
The U Mann–Whitney test revealed significantly higher scores in responses to
question SP3 (“I do not aach much importance to buying food products, I usually buy
what is ‘at hand’”) (U = 171, n
1
= 16, n
2
= 38, p = 0.012, r = −0.34) among students when
compared to employed individuals (Figure 5). This suggests that students were more
likely to agree with this statement. This also corresponds to education level and age.
Higher involvement in food purchase and food preparation comes with education level
and age.
As in the group of general consumers, this research among biathletes showed that
age influenced awareness about food’s nutritional value and taking an active approach
towards the product they consume. A similar situation occurs in the case of the
respondents’ education level. The higher the education, the greater the awareness and
interest in food issues and the active approach towards food, diets, ingredients, and food
processing. Usually, in consumer food studies, sex plays an essential role in influencing
the answers. In the present study, no impact of sex was observed. This may indicate that
this activity plays a central role in professional sports activities, not sex. A more extended
period of involvement in professional sports activities (as well as a higher level of
education) results in a greater interest in food and nutrition issues and shapes aitudes
towards food.
Figure 4. The effect of education on views on food and nutrition (VF). The bars represent the mean
scores, while the error bars indicate the standard deviations (* p< 0.05).
3.4.3. Effect of Employment
The U Mann–Whitney test revealed significantly higher scores in responses to question
SP3 (“I do not attach much importance to buying food products, I usually buy what is ‘at
hand’”) (U = 171, n
1
= 16, n
2
= 38, p= 0.012, r =
−
0.34) among students when compared
to employed individuals (Figure 5). This suggests that students were more likely to agree
with this statement. This also corresponds to education level and age. Higher involvement
in food purchase and food preparation comes with education level and age.
Nutrients 2024, 16, x FOR PEER REVIEW 12 of 17
Figure 5. The effect of employment on the selection of food products according to their consumption
type (SP). The bars represent the mean scores, while the error bars indicate the standard deviations
(* p < 0.05).
4. Discussion
This study aimed to explore the sociodemographic determinants of dietary habits
among athletes of the Polish Biathlon Association. The findings provide insights into how
age, education, employment status, gender, and household structure shape professional
athletes’ food choices, meal preparation, and nutritional awareness. Understanding these
relationships is crucial because proper nutrition is key to athletic performance, recovery,
and overall health. In a highly controlled environment such as professional sports, it is
essential to identify the specific influences that lead to variations in dietary behavior. The
results highlight both expected and unexpected paerns, discussed in detail in the
following sections, each addressing a core area of influence on athletes’ dietary habits.
4.1. Age and Nutritional Awareness
This study found that older athletes (<23 years) exhibited higher scores in food
awareness and nutritional consciousness than their younger counterparts, particularly in
the “Views on Food and Nutrition” category. According to their experience, older athletes
proactively engaged with modern dietary trends, particularly meat consumption. These
findings do not align with the existing literature, which suggests that age alone does not
directly affect nutritional knowledge. Taye et al. [50] and Kathure et al. [51] found no
significant differences in nutrition knowledge across age groups. However, research by
Murathan [52] indicated that older athletes tend to have more positive aitudes toward
nutrition, which is essential for maintaining a balanced diet.
Furthermore, Staśkiewicz et al. [53] observed that athletes with higher nutritional
awareness demonstrated beer dietary practices irrespective of age, which can positively
influence performance. The role of coaches and nutritionists is paramount in enhancing
nutritional knowledge. Athletes often rely on informal sources of information, which can
lead to suboptimal food choices [52]. This emphasizes the need for professional guidance
in nutrition, particularly for athletes [54].
4.2. Education as a Major Determinant of Food Behavior
The study revealed that higher-education athletes scored significantly higher on food
preparation, consumption, and food opinions than those with lower educational
aainment. Higher education has been linked to greater food awareness, involvement in
meal planning, and healthier food choices. These results are consistent with the findings
of broader research. Higher educational aainment has been shown to correlate with
Figure 5. The effect of employment on the selection of food products according to their consumption
type (SP). The bars represent the mean scores, while the error bars indicate the standard deviations
(* p< 0.05).
As in the group of general consumers, this research among biathletes showed that
age influenced awareness about food’s nutritional value and taking an active approach
towards the product they consume. A similar situation occurs in the case of the respondents’
Nutrients 2024,16, 3784 11 of 16
education level. The higher the education, the greater the awareness and interest in food
issues and the active approach towards food, diets, ingredients, and food processing.
Usually, in consumer food studies, sex plays an essential role in influencing the answers.
In the present study, no impact of sex was observed. This may indicate that this activity
plays a central role in professional sports activities, not sex. A more extended period of
involvement in professional sports activities (as well as a higher level of education) results
in a greater interest in food and nutrition issues and shapes attitudes towards food.
4. Discussion
This study aimed to explore the sociodemographic determinants of dietary habits
among athletes of the Polish Biathlon Association. The findings provide insights into how
age, education, employment status, gender, and household structure shape professional
athletes’ food choices, meal preparation, and nutritional awareness. Understanding these
relationships is crucial because proper nutrition is key to athletic performance, recovery,
and overall health. In a highly controlled environment such as professional sports, it
is essential to identify the specific influences that lead to variations in dietary behavior.
The results highlight both expected and unexpected patterns, discussed in detail in the
following sections, each addressing a core area of influence on athletes’ dietary habits.
4.1. Age and Nutritional Awareness
This study found that older athletes (<23 years) exhibited higher scores in food aware-
ness and nutritional consciousness than their younger counterparts, particularly in the
“Views on Food and Nutrition” category. According to their experience, older athletes
proactively engaged with modern dietary trends, particularly meat consumption. These
findings do not align with the existing literature, which suggests that age alone does not
directly affect nutritional knowledge. Taye et al. [
50
] and Kathure et al. [
51
] found no
significant differences in nutrition knowledge across age groups. However, research by
Murathan [
52
] indicated that older athletes tend to have more positive attitudes toward
nutrition, which is essential for maintaining a balanced diet.
Furthermore, Sta´skiewicz et al. [
53
] observed that athletes with higher nutritional
awareness demonstrated better dietary practices irrespective of age, which can positively
influence performance. The role of coaches and nutritionists is paramount in enhancing
nutritional knowledge. Athletes often rely on informal sources of information, which can
lead to suboptimal food choices [
52
]. This emphasizes the need for professional guidance
in nutrition, particularly for athletes [54].
4.2. Education as a Major Determinant of Food Behavior
The study revealed that higher-education athletes scored significantly higher on food
preparation, consumption, and food opinions than those with lower educational attainment.
Higher education has been linked to greater food awareness, involvement in meal planning,
and healthier food choices. These results are consistent with the findings of broader
research. Higher educational attainment has been shown to correlate with healthier dietary
patterns, including increased consumption of fiber, vitamins, and antioxidants [
55
,
56
]. In
the Tromsø Study, Jacobsen and Nilsen [57] reported that educated individuals had lower
fat and higher dietary fiber, which is particularly beneficial for athletes. Furthermore,
socioeconomic factors associated with higher education, such as better access to food and
more significant cultural capital, influence food choices [58,59].
4.3. Employment Status and Spontaneity in Food Choices
Athletes who were students exhibited more spontaneous food choices, often driven
by convenience rather than careful planning, compared to their employed counterparts.
This pattern is likely influenced by time constraints and financial limitations student-
athletes face. Previous research corroborates these findings by showing that employment
status significantly affects dietary habits. Caban-Martinez et al. [
60
] found that employed
Nutrients 2024,16, 3784 12 of 16
individuals tend to have more structured meal patterns, whereas students or unemployed
individuals exhibit more erratic eating behaviors. Additionally, social influences in the
workplace can shape food choices, with employed athletes potentially benefiting from
healthier dietary norms [
61
]. The intersection of employment, education, and access to
nutritional resources further supports the need for targeted interventions for student-
athletes [62].
4.4. Professional Sports and Gender Differences
This study found no significant differences in dietary habits between male and female
athletes, which may be attributed to the structured dietary programs provided by profes-
sional nutritionists. This contrasts with trends in the general population, where sex often
plays a crucial role in nutritional choices due to cultural and social factors. This finding is
supported by the literature showing that professional support can neutralize gender-based
differences in food behavior [
63
,
64
]. However, female athletes often face unique nutritional
challenges, including body image concerns and physiological fluctuations, which require
tailored interventions [
65
,
66
]. The lack of gender differences observed in this study suggests
that professional guidance may mitigate these issues in elite sports settings.
4.5. Limited Influence of Household Size and Region
Household size and region of residence did not significantly influence athletes’ dietary
habits, likely because of the standardized nature of their sports environment, which over-
rides personal or regional differences. While this finding may seem surprising, it aligns
with research suggesting that income and education play a more decisive role in food
choices than household size or region [
67
]. Cohen and Babey [
68
] argued that external food
environments, marketing, and individual attitudes toward health are often more robust
determinants of dietary behavior than demographic variables. These findings highlight
that professional sports are controlled and uniform, and that standardized programs guide
athletes’ food choices.
5. Conclusions
Age and education significantly influence dietary habits. Older athletes showed
greater nutritional awareness, particularly regarding adopting modern dietary trends.
Higher education was correlated with healthier food choices and greater involvement in
meal planning, underscoring the importance of nutrition education for performance. Em-
ployment status affects food choices. Due to time and financial constraints, student-athletes
exhibited more spontaneous, convenience-driven eating, whereas employed athletes had
more structured eating habits. Tailored nutritional strategies are required for student-
athletes. Due to standardized nutritional programs, sex differences in dietary habits were
minimal, suggesting that professional support neutralizes typical gender-related variations.
However, attention to the specific needs of female athletes is essential for their optimal
health and performance.
6. Practical Recommendations for Coaches and Sports Nutritionists
1.
Targeted Nutrition Education: Coaches and nutritionists should focus on providing
targeted nutrition education to younger athletes and those with lower education levels
to enhance awareness of modern dietary trends and promote healthier meal planning.
2.
Support for Student-Athletes: Since student-athletes often make convenience-based
food choices, practical time management and budget-friendly meal preparation work-
shops can help them make better dietary decisions within their constraints.
3.
Standardized Nutritional Programs: Nutritionists should continue implementing stan-
dardized nutritional programs that minimize gender differences, ensuring equitable
access to nutrition resources across all athletes.
Nutrients 2024,16, 3784 13 of 16
4.
Individualized Strategies: Given the role of sociodemographic factors, nutritionists are
encouraged to develop individualized strategies that consider athletes’ age, education,
and employment status to optimize nutritional outcomes and performance.
7. Contribution to Sports Nutrition
The study reinforces the importance of socio-demographic factors in shaping athletes’
dietary habits, emphasizing the value of personalized nutrition programs. By understand-
ing specific needs based on age, education, and employment, sports nutritionists can design
tailored interventions that enhance nutritional awareness and dietary behaviors, ultimately
contributing to improved health and athletic performance. This targeted approach provides
actionable insights for professional practice within structured sports environments.
8. Limitations of the Study
The cross-sectional design limits the ability to establish causal relationships between
sociodemographic factors and dietary habits, thus restricting the findings to associations.
Additionally, the relatively small sample size of 54 respondents may have reduced the
generalizability of the results to broader athletic populations. The study also relied on
self-reported data, which can introduce bias due to potential inaccuracies in participants’
recall or reporting of their dietary behaviors. A fundamental limitation of this study is the
lack of a formal sample size calculation. Due to the study’s focus on the Polish Biathlon
Association, the sample consisted of all 54 available athletes from the official national teams,
surveyed using the CAWI (computer-assisted web interview) method. While this represents
nearly the entirety of this specific group, it may limit the broader generalizability of the
findings. Additionally, the absence of sample size estimation using statistical methods
such as G*Power was due to the practical constraints of studying a fixed population.
Future research could expand the sample to include biathletes beyond the national team
to enhance generalizability and provide further validity to the findings. Furthermore,
the relatively large standard deviations observed in categories such as food preparation,
consumption, and nutritional awareness indicated substantial response variability. This
variability suggests that the observed effects may not be uniformly distributed across all
participants, potentially weakening the reliability and robustness of our findings.
Author Contributions: Conceptualization: A.G.-C.; formal analysis: A.G.-C., M.N.-D., A.A., Z.W.
and T.S.; investigation: A.G.-C.; methodology: A.G.-C.; project administration: A.G.-C.; supervision:
Z.W. and T.S.; statistical analysis: A.A.; visualization: A.A. and Z.W.; writing—original draft: A.G.-C.,
M.N.-D., A.A., Z.W., T.S. and E.B.; writing—review and editing: A.G.-C., M.N.-D., A.A., Z.W., T.S.
and E.B. All authors have read and agreed to the published version of the manuscript.
Funding: This study received no external funding.
Institutional Review Board Statement: The study was conducted according to the guidelines of the
Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of
NAME OF INSTITUTE (KB/54/2021 approved 11 December 2021).
Informed Consent Statement: Informed consent was obtained from all the subjects involved in the
study.
Data Availability Statement: Data will be available on request from the corresponding author.
Conflicts of Interest: The authors declare no conflicts of interest.
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