Introduction

Children aged 9-12 years are increasingly exposed to lifestyle factors that may adversely affect their health and well-being, including insufficient physical activity, unhealthy dietary habits, excessive screen time, and inadequate sleep. These behaviours have been associated with physical health problems as well as symptoms of psychological distress, including stress, anxiety, and sleep disturbances [1-4].

The Supreme Audit Office report [5] highlights the lack of systematic health education at schools and insufficient family support. According to the World Health Organization [6] recommendations, children and adolescents aged 9-12 should engage in at least 60 minutes of moderate to vigorous physical activity daily. Studies show that regular physical activity improves both physical fitness and cognitive functions, mood, and sleep quality [7]. In Poland, data [8] indicate that less than half of students aged 9-12 meet these recommendations, with activity levels decreasing with age [9]. Numerous studies point to the fact that children aged 9-12 who eat regular and healthy meals (vegetables, fruits, whole grains, no sweets or carbonated drinks) are less likely to exhibit symptoms of illness, fatigue, or concentration difficulties [10-12] Meanwhile, in Poland, up to 60% of children aged 9-12 do not eat breakfast regularly [13-15].

Medical data are important, but subjective information from surveys which provide insights into daily habits, behaviours, and parent-reported health assessment (HP-RA) by children or their caregivers is increasingly significant. HP-RA represents a subjective perception of the child’s health reported by the parent rather than a clinically verified health status. Self-assessed health SAH, as reported in the literature, demonstrates strong associations with objective health outcomes, is a widely used subjective indicator reflecting a child’s overall perception of physical and mental well-being. SAH has shown strong associations with objective health outcomes, psychosomatic symptoms, and lifestyle patterns in international child health surveys, including Health Behaviour in School-aged Children (HBSC) [16, 17]. Despite a growing number of studies exploring children’s lifestyle behaviours, most research focuses on isolated components such as physical activity [7, 17], diet [16, 18], or sleep [16-21], without analysing their joint effects. Comprehensive approaches integrating both protective and risk lifestyle factors remain limited [22-24].

Although numerous studies worldwide have investigated selected aspects of children’s health behaviours [19, 22], there is still limited research combining dietary habits, physical activity levels, and psychosocial determinants within a unified analytical model in the Lublin Region [8, 16].

Importantly, physical education (PE) lessons are compulsory across Europe for this age group; therefore, the present study focused on lifestyle behaviours beyond school requirements, particularly leisure-time physical activity, sleep routines, screen exposure, and everyday dietary practices. Leisure-time activity may be strongly affected by environmental constraints, such as limited sports infrastructure or longer commuting distances in rural areas, as indicated in previous regional studies.

Most evidence on children’s health behaviours in Poland derives from nationwide HBSC surveys, which provide valuable population-level trends but do not fully capture regional variability in socio-environmental conditions. Regional analyses are particularly relevant in Eastern Poland, where lifestyle patterns may differ due to socioeconomic and infrastructural factors. The Lublin Voivodeship is characterised by low urbanisation, a predominance of rural areas, and more limited access to recreational and health-promoting resources. Economic indicators also point to structural disadvantage, as GDP per capita and household disposable income remain below national and European Union averages. This region is one of the least economically developed in Poland and the European Union, as confirmed by data from the Central Statistical Office and Eurostat – in 2022, the GDP per capita in the Lublin Region was only 48% of the EU average and 68.8% of Poland’s average, and the disposable income of households was lower than the national average. In 2024, the Lublin Region paid out the highest amount of benefits for children under 18 in the country. On average, 360 out of every 10,000 people received social assistance benefits [25].

These contextual factors may shape children’s daily behaviours differently than in large national samples, potentially modifying the relationship between lifestyle and perceived health. Only little is known about how protective behaviours (physical activity, adequate sleep, healthy diet) and risk behaviours (screen time and consumption of sweets) jointly influence children’s subjective health within such a regional context.

By providing region-specific estimates, the present study complements nationwide research and offers new empirical insight into how lifestyle factors interact in shaping parent-reported health among school-aged children in the Lublin Region.

This study adds novel value to the existing literature by examining lifestyle–health associations in a region that remains underrepresented in national and international datasets. These findings could serve as a crucial basis for implementing local interventions, and inspire further comparative studies in other regions of the country.

We hypothesised that higher physical activity, longer sleep, and regular consumption of breakfast and vegetables among children from the Lublin Region would be associated with better parent-reported child health (PRCH), whereas excessive screen time and high intake of sweets would be associated with poorer PRCH.

Literature review

The health of school-aged children is increasingly examined in the context of lifestyle factors, including physical activity, dietary habits, sleep duration, and exposure to electronic media. Research indicates that these daily habits significantly influence subjective health perceptions and the occurrence of somatic symptoms, such as headaches and fatigue [16-17].

Physical activity is one of the most thoroughly studied factors affecting children’s health. A systematic review [4] found that regular physical activity is associated with cardiovascular health and musculoskeletal function, reduced risk of obesity, and improved mental health. Similar findings were reported in Norwegian studies, in which school-aged children with higher physical activity levels more frequently exhibited good health according to their parents’ assessment and greater life satisfaction [17].

Sleep also plays a critical role in children’s physical and mental development. Owens et al. (2014) [19] noted that sleep deprivation is associated with impaired cognitive function, reduced mood, and behavioural issues. In a population-based study, Chaput et al. (2016) [20] found that children with insufficient sleep were at a higher risk of developing obesity and experiencing emotional regulation difficulties. Research by Grasaas et al. (2024) [17] and Chałdaś-Majdańska et al. (2020) [21] further confirmed the positive impact of sleep and physical activity on subjective health perception and well-being in children. An average sleep duration aligned with WHO recommendations (i.e., 9-11 hours per night for school-aged children) is considered the minimum requirement for maintaining health and well-being [26].

Rampersaud et al. (2005) [18] demonstrated that daily breakfast consumption was associated with better concentration, memory, and overall energy levels. Children who regularly eat breakfast are less likely to experience weight-related issues and tend to report a more positive HP-RA. Additionally, vegetable consumption is associated with better mental health and lower levels of stress and depressive symptoms, as reported by studies within the international HBSC project [16].

Excessive exposure to screen-based devices has emerged as an important factor associated with children’s health and well-being. Based on population data, Przybylski and Weinstein (2019) [27] found that screen time exceeding two hours per day was associated with reduced life satisfaction, fatigue, sleep disturbances, and anxiety. Twenge and Campbell (2018) [28] observed that children who excessively used digital devices more frequently experienced lower self-esteem and depressive symptoms, suggesting that digital media may negatively affect health self-perception.

Research by Malczyk et al. (2015) [29] indicated that excessive consumption of sweets and products high in sugar may contribute to headaches in children and adolescents. Similarly, Gazerani (2020) [30] suggested that a diet high in simple sugars can adversely affect the nervous system, leading to hyperactivity or headaches, particularly with regular consumption. In their study of 11-year-old children, Straube et al. (2013) [31] identified irregular meals, sleep deprivation, and low physical activity as risk factors for headaches. Sixsmith and Starr (2015) [32] highlight that lifestyle is one of the most significant modifiable risk factors for chronic headaches in children.

Material and methods

Research procedure and tools

The study employed a diagnostic survey method using a direct questionnaire technique. The research design required parent-reported data and quantitative daily estimates of children’s lifestyle behaviours, including sleep duration, screen exposure, physical activity, and dietary habits.

Standardised instruments such as the HBSC questionnaire were considered during the study design phase. However, they are primarily intended for adolescent self-reports and focus mainly on categorical behavioural frequencies. Because the present study concerned younger children (9-12 years) and required precise quantitative indicators suitable for regression modelling, a more tailored instrument was necessary.

Therefore, the study subject is not self-assessed health (questionnaire completed by child), but the related sub­ject of PRCH. This approach enabled the collection of detailed behavioural measures while maintaining clarity and feasibility in a school-based survey.

The questionnaire was based on previous research on children’s lifestyle and health [4, 16-21] and underwent a multi-step content validation and refinement process validity.

First, the questionnaire was evaluated by an expert panel consisting of three independent specialists: a paediatrician with clinical experience in child health assessment, a university lecturer in physical education with expertise in motor development, and a behavioural scientist specialising in child and adolescent lifestyle behaviours. Each expert had more than 10 years of professional experience in their respective fields, ensuring appropriate evaluation of item clarity, developmental appropriateness, and conceptual relevance. Experts rated each question using a 4-point relevance scale and provided qualitative comments regarding item formulation and potential sources of misunderstanding. Items identified by the experts as requiring clarification or modification were revised to improve wording precision and reduce ambiguity.

Second, a pilot test was conducted among 30 parents of children aged 9-12 years to assess comprehension, response feasibility, and the clarity of instructions. Parents were asked to complete the questionnaire and indicate which items were unclear, difficult to interpret, or required additional explanation. Response distribution patterns were also examined to identify items with unusually high non-response rates or inconsistent answering behaviour. Feedback from the pilot resulted in several refinements, including simplifying phrasing, specifying time frames (e.g., ‘during the last 30 days’), and clarifying definitions of lifestyle behaviours such as screen time and physical activity.

Measurement quality was ensured through expert review (content validity), pilot testing (face validity and cognitive clarity), and alignment with established definitions in prior child lifestyle and health research.

The final questionnaire consisted of 10 questions. Each lifestyle component was measured with a separate item: (1) physical activity (minutes per day), (2) average sleep duration (hours per night), (3) time spent on electronic devices (hours per day), and three dietary behaviours: (4) breakfast consumption (yes/no), (5) daily vegetable intake (min. 300 g – yes/no), and (6) consumption of sweets (max. 24 g – yes/no). In addition, PRCH was measured using a single 5-point Likert item (1 = very poor, 5 = very good). Three demographic questions (age, sex, place of residence) were also included. All questions referred to the child’s typical behaviour over the previous 30 days, ensuring a consistent recall period. Parents were asked to report their 9-12-year-old children’s physical activity, average sleep duration, time spent on electronic devices, and dietary habits (breakfast, vegetable, and consumption of sweets). To facilitate estimation, examples of standard portion sizes were provided. Table 1 presents an overview of the questionnaire variables, measurement scales, and recall periods.

Sleep duration was assessed as a single average over the previous 30 days, without differentiating between weekdays and weekends.

Screen time was assessed based on parental reports of the average number of hours per day the child spent using screen-based devices. Screen time was defined as the average daily time spent using electronic devices, including television, computers, tablets, and smartphones, for both recreational and educational purposes. Parents were asked to estimate the child’s typical daily exposure during weekdays and weekends.

The research was conducted between 2024 and 2025 in the Lublin Voivodeship. The selection of this region as the study location was deliberate and justified by both cognitive and practical relevance, because 61.6% of households were below the income criterion. This situation directly affects the living conditions of families, the availability of healthy food, and the opportunities for children to participate in sports and extracurricular activities. Another important factor is the demographic structure of the region. The urbanisation rate for the Lublin region is 48%, which is lower than the national average of 60%. These areas are characterised by limited sports and recreational infrastructure and less access to specialist health services, which may hinder the development of healthy habits among children. Research also indicates a lower level of health education and health awareness among parents and guardians in this region, which contributes to the perpetuation of unhealthy patterns related to nutrition and leisure activities.

Furthermore, the Lublin Region remains relatively under-researched in terms of the lifestyle of children and young people, while most of the available analyses focus on populations from large cities and more economically developed regions. Meanwhile, children from the Lublin Region live in a distinct socio-environmental context characterised by lower urbanisation, a higher proportion of rural residents, and more limited access to health and sports infrastructure. Such social and environmental conditions may directly influence children’s lifestyles. A study conducted in this region provides valuable data that may differ from findings obtained in more urbanis­ed or affluent parts of Poland.

Characteristics of the research sample

The research sample was selected to reflect the regio­nal specificity described above.

A total of 320 schools were randomly selected from the official registry of schools in the surveyed region and invited to participate. Of these, 108 agreed (response rate = 33.75%). Parents of 1,350 eligible children were approached, and 1,200 complete questionnaires were returned (completion rate = 88.9%). The sample structure reflected the demographic composition of the surveyed region, including the distribution of urban and rural residents. The proportional representation resulted from the random selection of schools across different locations rather than from a quota sampling procedure. Similarly, the gender distribution in the final sample reflected the natural distribution of boys and girls within the participating schools, and no participants were excluded based on gender. The questionnaire was completed by parents on behalf of their children (parental proxy report). Participation in the study was voluntary and anonymous. All parental gave informed oral consent, and the study was conducted in accordance with the ethical principles set out in the Declaration of Helsinki [33].

The sample structure was designed to reflect the demographic distribution of children in the Lublin Voivodeship by age, sex, and place of residence. Although the final recruitment relied on availability due to the need for school and parental consent, the resulting proportions corresponded closely to the regional demographic profile. Therefore, the results should be interpreted as exploratory and generalisable primarily within this regional context. The structure of the sample is presented in Table 2.

Data analysis

Data were analysed using STATISTICA 13.3 (StatSoft Polska). Descriptive statistics included the mean (Mx), standard deviation (SD), median (Me), and coefficient of variation (Vc). Associations between demographic variables and self-rated health were examined using the Mann-Whitney and Kruskal-Wallis tests. Multiple regression was also calculated to assess the relationship between independent (explanatory) variables and the dependent (understood) variable. Model fit was assessed using the F test, the Durbin-Watson statistic, and the variance inflation factor (VIF < 3.5) to confirm the absence of multicollinearity. Statistical significance was set at p < 0.05 [29, 30]. Normality of distribution of key variables was assessed using Kolmogorov-Smirnov tests and visual analysis (histograms, Q-Q plots). Although some variables deviated from perfect normality, linear regression is robust to moderate deviations in large samples (N = 1200).

Before conducting statistical analyses, the dataset was examined for missing values. Missing responses were extremely rare and accounted for only 0.05% of all data points. Given that incomplete questionnaires indicated errors in completion rather than random omissions, cases with any missing data were excluded entirely from the analytic dataset. As a result, all analyses were conducted on fully complete questionnaires. Because the overall missingness was negligible and non-systematic, no imputation procedures were applied.

All regression models were adjusted for child’s age, sex, and place of residence to control for potential confounding effects.

Results

Descriptive statistics of lifestyle variables

Table 3 presents basic measures of central tendency and variation for physical activity, sleep time, and screen time. The average time spent being physically active was just under 57 minutes per day, with a median of 50 minutes, indicating that most children were physically active for less than one hour per day. The high coefficient of variation of 48.57% suggests significant variation in activity levels among children. Sleep time was more uniform across the population and centred around 7 hours per day (V_c = 24.06%), suggesting a relatively stable circadian rhythm among the subjects. However, screen time was clearly high (an average of about 3.5 hours per day) and, like physical activity, varied greatly among children, indicating different patterns of digital media use (Table 3).

Distribution of the dependent variable (HP-RA)

Most often, parents assessed their children’s health as average or good, with the categories “good” and “very good” accounting for 41.2% of respondents, while negative assessments were less common. This indicates a moderately positive perception of children’s health in the analysed population. Most children ate breakfast and vegetables in the recommended amounts every day, which applied to about three-quarters of the participants. At the same time, only 10.6% of children reported eating sweets every day, which suggests a limited occurrence of this unhealthy eating habit (Table 4).

HP-RA by demographic characteristics (univariate analysis)

The one-dimensional analysis did not reveal any statistically significant differences in the assessment of children’s health depending on gender, place of resi­dence, or age. The average health assessment was very similar for girls and boys, and the Mann-Whitney test did not show any differences between the groups (p = 0.968). Similarly, place of residence did not differentiate perceived health status – children living in rural and urban areas obtained comparable results, and the differences were not statistically significant (p = 0.346). Analysis by age group also showed no significant differences in health assessment (p = 0.253), despite a slight tendency for slightly lower scores among the oldest children. The results indicate that the subjective health assessment of children was stable in the study population and did not depend significantly on basic demographic characteristics (Table 5).

Multivariate analysis – regression model

A multiple regression model was developed (Table 6) to identify factors associated with parents’ assessment of their children’s health. Variance inflation factors (VIF) were examined and found to be below 3.5, indicating acceptable levels of multicollinearity.

The overall regression model was statistically significant (F = 256.67, p < 0.0001), indicating that the set of predictors explained a significant proportion of the variance in the outcome variable. The Durbin-Watson statistic (DW = 1.925) was close to 2, suggesting no substantial autocorrelation of residuals. Similarly, the serial correlation of residuals (0.036) was close to zero, supporting the assumption of independent errors.

Physical activity (β = 0.224) and sleep duration (β = 0.222) showed the strongest positive associations with HP-RA, whereas screen time demonstrated the strongest negative association (β = –0.212). Daily vegetable consumption (β = 0.093) and breakfast consumption (β = 0.088) were also positively associated with HP-RA, while daily consumption of sweets was negatively associated (β = –0.158). These findings indicate that behaviours related to physical activity, sleep, diet, and sedentary lifestyle are important correlates of parent-reported health assessment in children (Table 6).

The coefficient of determination (R² = 0.554) indicates that the model explains 55.4% of the variability in parents’ assessment of their child’s health, which indicates a high fit of the model to the empirical data (Table 6).

Discussion

Unlike nationwide HBSC surveys, the present study provides a region-specific perspective, allowing identification of behavioural patterns within a more homogeneous socio-environmental context. This approach reduces population heterogeneity and enables more precise interpretation of associations between lifestyle behaviours and perceived child health.

This study examined the associations between the behaviours of children aged 9-12 years and HP-RA. This developmental stage is particularly important because health habits become consolidated while children are still strongly influenced by family and school environments. The results indicate that behavioural factors related to physical activity, sleep, and screen exposure are more strongly associated with perceived health than demographic characteristics.

Numerous international studies consistently demonstrate that children’s lifestyles – including physical activity, diet, sleep, and screen time – are closely associated with their health outcomes [7, 17, 19, 22, 26, 34]. Particular emphasis in the literature is placed on physical activity as one of the critical factors promoting health. Research by Janssen and LeBlanc (2010) [7] and Telama (2009) [22] indicates that physically active children are less likely to experience psychosomatic disorders, have a lower risk of obesity, and report a higher quality of life. Norwegian studies [17] further confirm that school-aged children who regularly engage in sports are much more likely to rate their health as good or very good. Alongside physical activity, sleep is recognised as a second pillar of healthy child development. Owens et al. (2014) [19] highlight that sleep deprivation leads to concentration difficulties, poorer emotional regulation, and reduced mood, affecting not only well-being but also subjective HP-RA. Children adhering to WHO sleep recommendations (approxima­tely 9-11 hours for children aged 9-12) are better socially adjusted and experience fewer psychosomatic symptoms [20, 26]. The present study’s findings align with these reports, with the strongest positive correlations observed between HP-RA and both physical activity and sleep duration, confirming their fundamental role in perceived health and well-being. In the multiple regression model developed, these factors were also the most predictive.

The positive association between physical activity and HP-RA observed in our study is consistent with international findings showing that physically active children report better well-being, fewer psychosomatic complaints, and higher life satisfaction [7, 17, 22].

Similarly, the strong relationship between sleep duration and health perception aligns with previous research demonstrating that insufficient sleep contributes to emotional and behavioural difficulties, as well as poorer subjective HP-RA [19-20, 26]. The average sleep duration observed in this study (7 hours per night) appears to be below international sleep recommendations for school-aged children, which generally range between 9 and 11 hours per night [34].

Nutrition, particularly regular breakfast and vege­table consumption, is another significant factor [29]. Rampersaud et al. (2005) [18] found that children who eat breakfast daily perform better at school, exhibit greater concentration, and report higher self-efficacy. Additionally, HBSC studies have confirmed that high vegetable intake is associated with better physical and mental health and lower stress levels in children [8, 16]. Our results also confirm earlier findings indicating that healthy dietary habits – such as eating breakfast and consuming vegetables daily – are associated with better HP-RA and psychological functioning [16, 18]. The regression model further confirmed that, while less influential than physical activity and sleep, these variables remain statistically significant.

Excessive screen time has been identified as an important lifestyle factor associated with children’s health and well-being. Studies have reported that prolonged screen exposure is associated with sleep disturbances, obesity, and impaired psychosocial functioning [24, 27]. Twenge and Campbell (2018) [28] found that children and adolescents spending more than two hours daily on screens reported lower life satisfaction, increased irritability, and more frequent sleep problems. In the present study’s multiple regression model, screen time was negatively associated with subjective HP-RA, consistent with literature linking excessive digital technology use to poorer well-being and health outcomes among children. The negative association between screen time and health aligns with studies showing that excessive screen use is associated with lower well-being, fatigue, and sleep disturbances [27, 28].

Consumption of simple sugars, particularly sweets, has long been associated with mood deterioration, metabolic issues, and an increased risk of feeling unwell [29, 30, 35]. In the present study, both screen time and daily consumption of sweets were negatively associated with HP-RA. These findings are consistent with previous research suggesting that frequent consumption of sugary foods is associated with headaches, fatigue, and poorer mood among children [29, 30].

Our findings support previous research suggesting that less favourable patterns of physical activity, sleep, and dietary habits are associated with poorer subjecti­vely rated child health [31, 36].

Effective prevention should focus on strengthening parental role modelling and structured school-based health education. Educational programmes can improve health knowledge, helping children understand and gradually adopt healthy habits, while the home environment provides behavioural reinforcement. A supportive socio-educational environment appears essential for sustainable health behaviour development.

Practical implications

The results indicate several areas that may warrant attention in school and family health promotion efforts. The relatively short sleep duration, high screen exposure, and dietary patterns observed in this study suggest that school-aged children may benefit from increased awareness and structured support in these domains.

Schools could consider reviewing their health education content with greater emphasis on sleep hygiene, balanced nutrition, and responsible screen use. In parallel, parental guidance programmes may help families better monitor screen time and daily routines, as parents play a central role in shaping children’s health behaviours.

Limitations and future research directions

While the findings are consistent with existing literature and statistically significant, several limitations should be acknowledged.

First, the data were based on parental proxy reports rather than objective measurements or direct child self-reports. Such reports may be affected by recall bias and social desirability bias, potentially influencing the strength and precision of the observed associations. In particular, parental estimates of screen time and food intake expressed in grams may be subject to memory inaccuracies or misclassification of portion sizes. Children may also use electronic devices without their parents’ knowledge.

Second, the study was conducted in a single region of Poland. Although schools were randomly selected within this region, the findings may not be fully representative of the entire Polish population or generalizable to other countries with different socio-cultural and environmental contexts.

Third, the cross-sectional design does not allow causal relationships to be established between lifestyle behaviours and children’s health. Although significant associations were identified, their directionality remains uncertain. For example, children with better perceived health may be more inclined to engage in physical acti­vity and maintain regular daily routines, whereas those with poorer perceived health may prefer more sedentary behaviours, suggesting the possibility of reverse causality.

Another limitation concerns the questionnaire itself. Despite expert review and pilot testing, it remains an author-constructed instrument, and further validation across diverse populations and settings would strengthen its reliability and external applicability. The use of simplified binary dietary variables (daily vs. not daily) reduced data complexity but limited the ability to capture variability in eating behaviours. Similarly, sleep duration was measured as a single average estimate over the previous 30 days without distinguishing between weekdays and weekends, which may have obscured potential variations related to compensatory weekend sleep.

Despite these limitations, the study has several notable strengths. It included a relatively large and well-balanced regional sample of school-aged children, and schools were randomly selected, reducing the risk of selection bias and strengthening the robustness of the findings within the studied region. In addition, the simultaneous evaluation of several key lifestyle behaviors enabled a comprehensive assessment of factors associated with children’s health perception.

Future research should consider employing objective measurement tools (e.g., accelerometers for physical activity, actigraphy or sleep diaries for sleep, and device-based monitoring for screen time) as well as longitudinal designs to better capture developmental trends and clarify potential causal pathways.

Conclusions

Children’s lifestyles were significantly associated with HP-RA in this sample of school-aged children. Higher levels of physical activity and adequate sleep duration were associated with more favourable HP-RA, suggesting that these behaviours may represent important components of health promotion in school-aged children. Daily breakfast and vegetable consumption were associated with better HP-RA, highlighting the potential importance of nutritional education in both school and home environments. Increased screen time and daily consumption of sweets were associated with less favourable HP-RA, suggesting that these behaviours may be markers of poorer perceived child well-being. The results support comprehensive health-promotion strategies involving both families and schools, emphasising physical activity, balanced diet, adequate sleep, and responsible screen use.

Disclosures

1. Institutional review board statement: Bioethics Committee at the Siedlce University of Natural Sciences and Humanities no. 1/2018, 16 November 2018.

2. Assistance with the article: None.

3. Financial support and sponsorship: None.

4. Conflicts of interest: None.

References