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Article

Regional Disparities and Determinants of Paediatric Healthcare Accessibility in Poland: A Multi-Level Assessment of Socio-Economic Drivers and Spatial Convergence (2010–2023)

by
Tadeusz Zienkiewicz
1,*,
Aleksandra Zalewska
1 and
Ewa Zienkiewicz
2
1
Department of Management, Lublin University of Technology, 20-059 Lublin, Poland
2
Faculty of Paediatrics, Medical University of Lublin, 20-093 Lublin, Poland
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(18), 8210; https://doi.org/10.3390/su17188210
Submission received: 23 July 2025 / Revised: 24 August 2025 / Accepted: 3 September 2025 / Published: 12 September 2025
(This article belongs to the Section Health, Well-Being and Sustainability)
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Abstract

This study examines regional disparities and convergence dynamics in paediatric healthcare accessibility across Poland’s 16 provinces between 2010 and 2023. A synthetic Paediatric Service Accessibility Index (PSA Index), constructed with Hellwig’s method, is combined with socio-economic indicators such as employment, urbanisation, and disposable income to evaluate the alignment between healthcare provision and regional development. The analysis employs non-parametric regional tests (Spearman’s rank correlation, Wilcoxon signed-rank test) and national panel regression models (Fixed and Random Effects). Results demonstrate significant spatial heterogeneity: economically advanced regions, including Mazowieckie and Małopolskie, show moderate to strong convergence between socio-economic progress and healthcare access, whereas structurally weaker regions such as Lubuskie and Podkarpackie reveal persistent divergence. Disposable income and urbanisation emerge as significant predictors of healthcare availability (p < 0.01), while employment is not statistically significant. The findings highlight enduring inequalities that are relevant in the context of the European Union’s (EU) cohesion policy and indicate that economic growth alone is insufficient to ensure equitable access to paediatric care. Comparative evidence from Romania, Bulgaria, and Spain points to similar patterns and emphasises the importance of EU Structural and Investment Funds in promoting healthcare equity. The study concludes that territorially sensitive, multidimensional interventions are necessary to advance social sustainability and to align healthcare infrastructure with the Sustainable Development Goals, particularly SDG 3 (Good Health and Well-Being) and SDG 10 (Reduced Inequalities).

1. Introduction

Equitable access to healthcare services remains a fundamental part of sustainable development and social justice, particularly in the context of vulnerable populations such as children [1]. Paediatric healthcare accessibility not only reflects the structural capacity of health systems but also signals broader patterns of socio-economic cohesion, territorial development, and public investment [2,3]. In recent years, disparities in access to specialised medical care have become an increasingly critical concern across European countries, including Poland, where regional heterogeneity continues to challenge the efficiency and fairness of healthcare delivery [4,5].
The aim of the study is to analyse regional disparities in the accessibility of paediatric service in Poland between 2010 and 2023 and to examine their relationship with key socio-economic factors such as disposable income, urbanisation, and employment. A central role will be played by the Paediatric Service Accessibility Index (PSA Index), designed as a tool for the multidimensional assessment of healthcare accessibility at the regional level. Derived via the Hellwig method [5,6], the PSA Index incorporates various determinants of healthcare availability, including infrastructure, workforce, socio-demographic context, and economic status. By combining rank-based non-parametric testing with panel data regression models, this research aims to provide a comprehensive empirical assessment of the spatial patterns and socio-economic determinants underpinning paediatric care accessibility across the 16 Polish provinces.
We intend to investigate whether increases in socio-economic indicators are associated with improved accessibility of paediatric services and to what extent processes of convergence or divergence shape the functioning of the Polish healthcare system. The study seeks to contribute to the scientific debate on health inequalities and to provide empirical evidence supporting regional and health policy. We expect that the findings will enable the formulation of recommendations relevant to the implementation of the Sustainable Development Goals, particularly SDG 3 and SDG 10.
Earlier studies have shown that healthcare accessibility is strongly influenced by factors such as urbanisation, disposable income, and labour market participation [7,8]. Employment has been used as a proxy for social inclusion and economic resilience, with higher employment rates often associated with improved healthcare use and better child health outcomes [9,10]. Although the healthcare system typology proposed by Nadine Reibling et al. (2019) was an important framework classifying OECD models based on accessibility, the public–private mix, and the orientation towards primary healthcare, more recent studies indicate an alternative financial approach. Gabani, Mazumdar, and Suhrcke (2023) propose a typology grounded in financing structures—distinguishing between government-funded systems, social insurance schemes, and those based on out-of-pocket payments—which broadens our understanding of the mechanisms of equity and efficiency in healthcare systems [11]. However, the extent to which employment correlates with paediatric care access, especially in regions with diverse structural characteristics, stays insufficiently explored.
The relevance of this inquiry is further heightened by growing concerns about spatial inequalities in health service distribution. As described by Allin & Masseria (2009) and van Doorslaer et al. (2000), regional health disparities are not merely a function of geographic location but result from the interplay of economic, institutional, and demographic variables [12,13]. Poland has experienced pronounced east–west and urban–rural divides in health infrastructure, workforce availability, and public investment [14,15]. The COVID-19 pandemic has further worsened these disparities, underscoring the need for evidence-based, regionally targeted policy interventions [16].
Methodologically, this study employs a dual-level approach. At the regional level, Spearman’s rank correlation coefficients and Wilcoxon signed-rank tests are used to capture localised dependencies and disparities. At the national level, Fixed and Random Effects panel models are estimated to account for structural determinants over time. The Hausman test is used to determine the right model specification, ensuring consistency and validity in parameter estimation [17].
The novelty of this research lies in the construction and application of the PSA Index as a multidimensional proxy for healthcare accessibility, integrated with socio-economic metrics over a long observation window. By evaluating convergence trends and associational patterns between the PSA Index and variables such as employment rate, urbanisation, and income, the study aims to illuminate the complex interdependencies that characterise regional health equity in Poland.
This work looks to inform both academic debate and public policy. As Poland and other EU countries pursue Agenda 2030 goals and strengthen their health systems post-pandemic, understanding the socio-spatial dynamics of paediatric care accessibility becomes imperative. The insights generated here could support a more fair and efficient allocation of resources, thereby contributing to the social sustainability of regional development.

2. Theoretical Consideration and Previous Research

2.1. Theoretical Considerations

Understanding the theoretical underpinnings of paediatric healthcare accessibility requires a multidimensional approach. At its core, accessibility to healthcare services is a part of social equity and sustainability, aligning with the Sustainable Development Goals (SDGs), particularly Goal 3: Good Health and Well-Being, and Goal 10: Reduced Inequalities [18]. Theories of spatial justice and human capability [19,20] provide a foundational framework for assessing disparities in access to health services. Spatial justice argues for equitable distribution of services across regions, while the human capability approach focuses on expanding individuals’ freedoms to achieve well-being, including the ability to access essential healthcare.
From a theoretical standpoint, this research aligns with the growing body of literature examining the social determinants of health and their spatial manifestations [21]. It also contributes to the discourse on spatial convergence in public services—a dimension recently investigated in the European context highlighting convergence in public service quality across regions [22], as well as through the lens of fiscal equalisation aimed at achieving equitable provision across jurisdictions [23]. Additionally, studies from China reveal significant spatial disparities without clear σ-convergence in healthcare service availability, underscoring persistent regional imbalances [24].
Healthcare access is frequently conceptualised through a framework of availability, accessibility, accommodation, affordability, and acceptability [25,26]. In the context of paediatric healthcare, these dimensions are particularly salient, as children are dependent on caregivers and public infrastructure. Regional disparities in these dimensions often reflect broader structural inequalities rooted in economic geography, labour markets, and administrative capacity [27,28].
From a systems theory perspective, healthcare systems are complex adaptive systems, influenced by interactions between demand-side and supply-side factors [29]. In such systems, changes in socio-economic conditions like employment rates, income levels, and urbanisation may produce non-linear effects on service accessibility. The PSA Index constructed in this study synthesises multiple indicators—health workforce, infrastructure, and demographic demand—to assess paediatric healthcare accessibility more comprehensively.
Another theoretical pillar stems from regional economic development theory. The concept of regional convergence, derived from neoclassical growth theory [30,31], posits that less developed regions should, over time, catch up with more developed ones in terms of income and other indicators. Applied to healthcare, convergence suggests that regional differences in service access should diminish under effective policies. Beta (β-convergence) and sigma (σ-convergence) convergence models are often employed to test these hypotheses, although convergence may occur from above or below depending on initial conditions and policy interventions [32]. In economic and social sciences, convergence analysis is often used to examine whether disparities between regions decrease over time and the two main approaches mentioned are applied. Beta convergence refers to the process in which less developed regions grow faster than more advanced ones, suggesting a “catch-up” effect. Empirically, this is tested by analysing the relationship between the initial level of a variable and its subsequent growth rate. Sigma convergence, on the other hand, focuses on whether overall dispersion between regions declines over time, commonly measured using indicators such as the standard deviation or the coefficient of variation. In simple terms, β-convergence indicates a mechanism of equalising growth rates, while σ-convergence reveals whether disparities diminish. Taken together, these approaches provide complementary insights into whether socio-economic integration or improved access to public services contributes to greater territorial cohesion [33].
Healthcare accessibility is also increasingly viewed through the lens of sustainable development. This encompasses not only economic sustainability but also social and spatial dimensions, recognising that regional disparities in access violate principles of territorial cohesion and intergenerational equity [34]. In this respect, assessing paediatric healthcare availability becomes a matter of social justice, long-term resilience, and public policy design [35].
The relationship between employment and healthcare accessibility is further intersected with labour economics. Higher employment rates are associated with improved income security, insurance coverage, and social capital, factors that enhance both individual health outcomes and systemic healthcare provision [36,37]. Moreover, regions with robust labour markets tend to attract more healthcare professionals and infrastructural investments, reinforcing spatial inequalities in service distribution.
Urbanisation, as another key variable, influences healthcare systems both positively and negatively. On one hand, higher urbanisation correlates with better access due to service concentration. On the other hand, rapid urban expansion can strain public infrastructure and worsen inequities within metropolitan regions [38]. Thus, understanding its role requires nuanced, region-specific analysis.
Previous studies in Poland have focused primarily on quantitative and cross-sectional approaches, without analysing the long-term dynamics of convergence in access to paediatric care. This gap is underscored by recent findings showing that, despite economic growth, social convergence across Polish voivodeships remains elusive [31]. Moreover, the latest Country Health Profile for Poland (2023) highlights persistent challenges in health service accessibility, system effectiveness, and regional resilience [39].
The research gap therefore concerns the lack of coherent, multi-level analyses in the context of the Sustainable Development Goals (SDGs), especially SDG 3 (Good Health and Well-Being) and SDG 10 (Reduced Inequalities). In this context, referencing the Horizon Europe programme is crucial: its Health Work Programme (2023–2025) explicitly aims to reduce health inequalities and promote equitable access to healthcare across Europe (European Commission, 2024) [40]. Our study addresses this gap by providing empirical, policy-relevant evidence for health and regional policy through multi-level, longitudinal analysis.
In sum, the theoretical considerations underlying this study rest on interrelated pillars of spatial equity, human development, sustainability, regional economics, and complex systems thinking. These perspectives provide a robust foundation for the empirical analysis conducted here, which looks to uncover the socio-economic drivers of paediatric healthcare accessibility in Poland and evaluate patterns of regional convergence over time.
To organise the analysis, the following research hypotheses were formulated: H1: The increase in socio-economic indicators (disposable income, urbanisation) is associated with an increase in the availability of paediatric services on a regional basis. H2: In Poland, there are significant regional differences in the convergence of the availability of paediatric services in relation to socio-economic development. H3: Economic improvements do not automatically lead to increased access to paediatric care, which indicates the need for public policy intervention.

2.2. Previous Research on Regional Disparities in Healthcare Accessibility

Earlier empirical studies on healthcare accessibility and regional disparities provide critical context for the present investigation. In the field of paediatric healthcare, much research has underscored the spatial imbalance in the availability of specialised services. For instance, Zienkiewicz et al. (2022) proved significant intra-national disparities in paediatric access in Poland, emphasising the need for multidimensional indicators like the PSA Index to capture regional heterogeneity [5]. Similar findings were echoed by Murphy et al. (2023), who reported that service accessibility tends to favour urban over rural regions in European contexts [41]. These findings are often linked to broader systemic inequalities, including funding allocation, health workforce distribution, and transportation infrastructure [42,43].
From a socio-economic perspective, labour market indicators, especially employment rates, have often been used as proxies for regional development and social inclusion. Studies by Blanchard and Katz (1992) and later by Ezcura and Rodríguez-Pose (2013) found robust associations between employment levels and health outcomes, suggesting that regions with higher economic activity also tend to offer better healthcare access [22,44,45]. Within the Polish context, the question of how structural labour shifts have affected healthcare equity, particularly in the aftermath of post-socialist transformations, was explored [46,47].
Research on convergence in healthcare outcomes and accessibility stays sparse but growing. A study by Medeiros and Schwierz (2015) applied the concept of beta-convergence to health spending across EU countries, finding that cohesion funds contributed to reduced disparities. In the domain of paediatric care, Goryakin et al. (2015) linked healthcare convergence to infrastructural improvements and decentralised governance models, suggesting that regional capacity plays a critical mediating role [7,48].
Panel econometric approaches have become increasingly popular in regional health research due to their ability to account for unobserved heterogeneity and temporal dynamics [17,49]. For example, Macinko et al. (2003) employed FE and RE models to study access to primary care across OECD countries, underscoring the explanatory power of employment, income, and urbanisation [50].
Non-parametric correlation techniques have also been widely used to explore associations among socio-economic and health variables in non-normally distributed datasets. Spearman’s rho and Kendall’s tau have proven useful in finding monotonic trends where traditional parametric methods fall short [51]. The use of these techniques has been confirmed in studies examining maternal care [52], paediatric immunisation [53], and rural service access [54,55].
Other studies have emphasised the importance of urbanisation and spatial density in shaping healthcare demand and supply. For instance, Neutens et al. (2010) introduced a spatiotemporal model to understand healthcare accessibility in urban contexts, noting that population density, commuting time, and service distribution are key components [56]. Meanwhile, Cutler and Miller (2005) provided longitudinal evidence of how infrastructure investment reduces health disparities over time [57].
Recent scholarships have also drawn attention to gender-specific factors influencing healthcare access. Women’s labour force participation has been linked not only to household health outcomes but also to patterns in paediatric service use [58]. In Central and Eastern Europe, this issue intersects with broader demographic challenges, such as population ageing and youth outmigration [59,60].
Although the Paediatric Service Accessibility (PSA) Index was introduced in our earlier work (2022), this paper significantly advances its application and analytical scope. First, the study adopts a long-term perspective (2010–2023), enabling the assessment of regional dynamics and patterns of convergence or divergence in paediatric healthcare accessibility. Unlike previous cross-sectional analyses, we apply panel regression models (Fixed and Random Effects), which allow us to control for unobserved heterogeneity and to identify robust predictors of healthcare access. The PSA Index is also employed for the first time in a multi-level convergence framework, covering both β- and σ-convergence, thereby shifting the focus from measurement to structural processes of inequality. Furthermore, comparative evidence from Romania, Bulgaria, and Spain situates Polish findings within a broader European context. Finally, by linking results to EU cohesion policy and the Sustainable Development Goals (SDG 3 and SDG 10), the study demonstrates the PSA Index’s practical utility as a tool for policy evaluation and for formulating recommendations aimed at reducing healthcare disparities.
Overall, the literature highlights a growing consensus on the multidimensional nature of healthcare accessibility and the necessity of spatially sensitive, data-driven analyses. However, few studies offer a comprehensive multi-level evaluation combining socio-economic indicators, composite accessibility indices, and convergence metrics within a panel framework. By integrating these approaches, the present study addresses a significant gap and offers novel insights into regional disparities in paediatric healthcare in Poland.

3. Materials and Methods

3.1. Data

All data used in this study come from publicly available databases of the Central Statistical Office of Poland (CSO) [61]. The study investigates the relationship between employment, as a proxy for socio-economic development, and the accessibility of paediatric healthcare services in Poland, with a particular focus on potential convergence trends across provinces. The dataset covers a 14-year period (2010–2023) and includes panel data from all 16 Polish provinces.
The primary dependent variable is the Paediatric Service Accessibility Index (PSA Index), a synthetic measure constructed using the Hellwig method. This approach aggregates multiple standardised indicators into a composite index, accounting for their distance from an ideal solution. Following the methodology outlined by Zienkiewicz et al. (2022), the PSA Index was calculated using the following indicators: number of paediatricians, healthcare expenditure, number of patients treated in paediatric departments per paediatrician, number of residents under 17 years of age per paediatric bed, length of public roads per 10,000 inhabitants, monthly disposable income per capita, employment rate (% of working-age population employed), urbanisation rate, and population density.
The explanatory variables selected for this study include the employment rate, urbanisation rate, and disposable income, due to their hypothesised links to healthcare accessibility and socio-economic well-being.

3.2. Model Specifications and Estimation Techniques

The research method combines regional-level non-parametric analyses with panel econometric modelling to assess both static relationships and dynamic structural trends.
Descriptive statistics were calculated for each variable, and the normality of distributions was assessed using four complementary tests: Shapiro–Wilk test, Lilliefors test, Jarque–Bera test, Doornik–Hansen test. These tests allowed for the choice of proper non-parametric methods in the next steps.
To examine the relationship between the PSA Index and each explanatory variable at the province level, due to the number of periods being less than 15, we used the Spearman rank correlation coefficient (rho). These statistics were calculated independently for each region to identify localised patterns of dependence between healthcare accessibility and socio-economic indicators.
To further explore the directional differences between paired variables (e.g., PSA Index vs. employment rate), the Wilcoxon signed-rank test was employed. This non-parametric alternative to the paired t-test is proper for variables with non-normal distributions, as confirmed by earlier normality tests.
To assess aggregate relationships and structural effects across provinces and over time, we specified the following panel regression model:
PSA Indexit = β0 + β1 × Employment rateit + β2 × Urbanisation rateit
+ β3 × Disposable Incomeit + εit
Both Fixed Effects (FE) and Random Effects (RE) estimators were applied. The choice of estimator was guided by the F-test for Fixed Effects (testing heterogeneity in intercepts across regions), the Breusch–Pagan Lagrange Multiplier test for Random Effects, and the Hausman test for model specification.
Diagnostic statistics such as R-squared, standard error of residuals, log-likelihood, and information criteria (AIC, BIC) were evaluated to assess model performance and fit. All statistical analyses were conducted using Gretl 2024d (x86_64, UCRT, GTK3) software [62].

4. Results

4.1. Normality Tests and Justification for Non-Parametric Methods

The results of the Shapiro–Wilk, Lilliefors, and Doornik–Hansen tests revealed that the PSA Index and selected explanatory variables (notably for many provinces) do not follow a normal distribution. In contrast, the employment rate, urbanisation rate, and disposable income showed greater alignment with normality in some regions. However, due to the observed distributional heterogeneity across the dataset, non-parametric techniques were considered more robust and proper for local-level analyses.

4.2. Local Rank-Based Correlations and Wilcoxon Tests

Correlation analysis using Spearman’s rho yielded mixed results across regions. Positive, statistically significant correlations between the PSA Index and employment rate were seen in provinces with more consistent socio-economic development (e.g., Mazowieckie, Małopolskie). In contrast, provinces with weaker healthcare infrastructure or more volatile employment patterns, such as Lubuskie and Podkarpackie, showed low or non-significant associations.
The Wilcoxon signed-rank tests confirmed significant differences between paired variables such as the PSA Index and employment rate or urbanisation rate in most provinces. These findings suggest systematic disparities between accessibility to paediatric care and broader socio-economic indicators, reinforcing the hypothesis that socio-economic development and healthcare accessibility are not always synchronised.
A summary of Spearman correlation coefficients, along with Wilcoxon test outcomes for each province, is provided in Table 1.
The data presented in the table highlight the spatial variation in the relationship between the PSA Index and socio-economic variables, revealing which regions prove convergence or divergence. The Mazowieckie region demonstrated strong positive correlations across all indicators, suggesting a mature and cohesive socio-economic system that translates into improved access to paediatric care. At the opposite extreme, the Lubuskie, Świętokrzyskie, and Podkarpackie regions showed weak or statistically insignificant correlations, showing fragmentation or structural gaps. In contrast, the Zachodniopomorskie and Warmińsko-Mazurskie regions demonstrated positive but moderate correlations, suggesting transitional dynamics or partial convergence.
These distinctions provide a framework for finding best practices, vulnerable regions, and candidates for targeted interventions.

4.3. Panel Regression Results

The panel data regression model applied to all provinces over the 2010–2023 period confirms a statistically significant relationship between the PSA Index and the included socio-economic indicators. The Fixed Effects model showed a strong within-group explanatory power, with significant coefficients for disposable income (positive) and urbanisation rate (negative). The employment rate was not statistically significant. The Random Effects model confirmed the significance of all three variables, though with smaller magnitudes (Table 2). The Hausman test showed that the Fixed Effects model is preferred (p < 0.01), confirming the necessity to account for unobserved heterogeneity across regions.

4.4. Interpretation and Implications

The assessment of paediatric healthcare accessibility in Poland, operationalised through the Paediatric Service Accessibility Index (PSA Index), reveals a highly differentiated landscape across voivodeships. Spearman rank correlation coefficients between the PSA Index and socio-economic variables such as employment rate, average disposable income, and urbanisation level range from weak to moderate, underscoring the limited systemic coherence between economic progress and healthcare access in many regions. This disconnect is further reinforced by the results of the Wilcoxon signed-rank tests, which often report statistically significant differences between the PSA Index and key explanatory variables (p < 0.05), pointing to structural imbalances in how healthcare services are aligned with broader regional development.
In several eastern and south-eastern regions, such as Dolnośląskie, Lubelskie, Podkarpackie, Lubuskie, and Świętokrzyskie, correlation coefficients stay particularly low (rho between 0.10 and 0.18), showing a weak monotonic relationship between the PSA Index and employment. However, the Wilcoxon tests in these same areas yield highly significant results (p ≈ 0.001), suggesting that despite socio-economic improvements, paediatric healthcare infrastructure has not been expanded or reorganised in proportion to the rising needs. These findings underscore the risk of growing spatial inequality in health service access, particularly in peripheral or historically underfunded regions. From a policy perspective, such disparities highlight the importance of embedding health equity considerations within broader territorial development strategies and investment planning. Sustainable development in these contexts must prioritise not just macro-economic indicators but also equity in essential services.
Moving toward central and northern regions such as Kujawsko-Pomorskie, Podlaskie, Opolskie, and Warmińsko-Mazurskie, we see slightly stronger Spearman correlations (rho between 0.23 and 0.33), pointing to an emerging though incomplete convergence between socio-economic drivers and paediatric care accessibility. However, Wilcoxon test results in these regions also stay significant (p < 0.01), reflecting persistent mismatches. While urbanisation and income levels in these areas are improving, access to paediatric healthcare has yet to fully catch up. These provinces may benefit from targeted support programmes aimed at improving infrastructural adequacy and workforce deployment, complemented by regionally adapted policy instruments.
In provinces such as Łódzkie, Pomorskie, Śląskie, and Zachodniopomorskie, the correlation coefficients climb to moderate levels (rho from 0.31 to 0.39), and the consistent Wilcoxon test significance suggests more structured, albeit partial, convergence. These regions illustrate greater systemic maturity, where socio-economic and healthcare indicators are beginning to co-evolve. Urban concentration in these areas facilitates service delivery but may also obscure intra-regional disparities. Consequently, sustainable regional strategies should continue to focus on territorial cohesion to avoid internal stratification, especially between urban cores and surrounding peri-urban or rural zones.
The most advanced convergence patterns are evident in Małopolskie, Wielkopolskie, and Mazowieckie. These provinces exhibit the highest correlation coefficients (rho ≥ 0.42), signifying a robust association between employment, income, urbanisation, and paediatric healthcare access. Nonetheless, Wilcoxon tests continue to show statistically significant differences, indicating that absolute convergence is yet to be achieved. These leading regions can serve as benchmarks for others, showcasing the effectiveness of integrated development policies that harmonise labour markets, social infrastructure, and healthcare systems. They exemplify the potential for scaling up best practices, especially regarding the strategic allocation of health investments and evidence-based policy coordination.
An additional layer of insight is provided by the results of the panel regression analysis. The Fixed Effects (FE) model revealed that among the socio-economic determinants, disposable income and urbanisation were statistically significant predictors of the PSA Index, while the employment rate lacked statistical power. This suggests that income and spatial development exert more direct and consistent influence on paediatric service availability than employment alone. The Random Effects (RE) model yielded similar patterns, but the Hausman test favoured the Fixed Effects approach, validating the importance of accounting for time-invariant regional heterogeneity.
These findings support a broader interpretation: employment, although indicative of economic vitality, may not adequately capture healthcare access disparities without incorporating additional contextual variables such as healthcare spending, institutional efficiency, or demographic shifts. In contrast, income directly reflects household capacity to utilise services, while urbanisation affects the physical presence of healthcare facilities. Over-urbanisation, however, may result in concentration without equitable distribution, particularly in metropolitan peripheries. Thus, regional planning must go beyond density metrics and focus on spatial justice and accessibility within urbanised zones.
A consistent observation across all voivodeships is that statistically significant differences persist between the PSA Index and its socio-economic predictors. This implies that even in regions where development is progressing rapidly, healthcare services, especially in paediatrics, may be lagging. Such mismatches present a challenge to the social dimension of sustainable development. They call into question the assumption that economic growth will automatically translate into improved public services and reinforce the necessity for deliberate, policy-driven adjustments.
From the standpoint of sustainable development, these results are crucial. They indicate that paediatric healthcare access in Poland is not purely a function of economic prosperity, but a composite outcome shaped by planning efficiency, political will, and institutional capability. Territorial cohesion, a central tenet of the European Union’s Cohesion Policy and the UN’s Agenda 2030, demands a commitment to reducing regional disparities not only in income but also in essential services such as healthcare. The findings of this study affirm the need for integrated planning that links socio-economic development with health system strengthening.
In conclusion, the regional analysis of the PSA Index and socio-economic variables reveals a complex mosaic of partial convergence, structural mismatch, and systemic imbalance across Poland.
The spatial disparities in paediatric healthcare accessibility are symptomatic of deeper regional inequalities that threaten long-term social sustainability. Bridging these gaps requires a concerted policy effort combining fiscal redistribution, health workforce reform, and spatially sensitive planning tools. Only through such integrative approaches can Poland move toward achieving equitable paediatric healthcare access for all its regions in line with sustainable development principles.
Based on the values of the Spearman’s coefficients and Wilcoxon tests, four groups of provinces can be distinguished in terms of the degree of convergence of the PSA Index with respect to explanatory variables (Table 3).
Strong convergence is shown by regions such as Mazowieckie, Małopolskie, Wielkopolskie, and Śląskie. They are characterised by a high correlation (rho > 0.35) and significant differences in Wilcoxon tests (p < 0.01), which indicate a gradual convergence of the level of paediatric accessibility to socio-economic conditions. The direction of convergence is clearly “from below”; the PSA is making up for it in the face of rising employment and income values.
Moderate convergence is represented by coastal and central provinces, e.g., Pomorskie and Łódzkie, where differences remain significant, but correlation values are slightly lower (rho ≈ 0.30). In these regions, there is a partial convergence of trends, but incomplete adaptation of the healthcare system.
Another group are regions with potential convergence, in which irregular results are observed, e.g., in Świętokrzyskie or Podlaskie, indicating a heterogeneous direction of change, which may be related to the internal structural diversity of the region or the effects of sectoral policies.
At the end, we can find the provinces with no convergence, Dolnoślaskie, Lubelskie, Lubuskie, and Podkarpackie. Low correlation values and insignificant or borderline Wilcoxon tests indicate persistent discrepancies. In these regions, the PSA Index does not follow socio-economic change, which may be due to structural constraints, insufficient health expenditure or inefficient spatial planning.
The analysis of changes in the PSA Index between 2010 and 2023 reveals clear regional disparities in the accessibility of paediatric services. Figure 1 presents the spatial distribution of changes in the PSA Index across Polish provinces in the period 2010–2023.
The largest increase in the PSA Index was observed in Wielkopolskie (+0.174), indicating a significant improvement in accessibility in this region, clearly exceeding national average trends. Positive changes were also recorded in Podlaskie and Lubelskie (+0.089), as well as in Podkarpackie (+0.065) and Małopolskie (+0.033). The increase in accessibility in these provinces may be associated both with the development of healthcare infrastructure and with targeted regional investments.
In contrast, several provinces experienced stagnation or regression. The sharpest declines were observed in Opolskie (−0.106) and Warmińsko-Mazurskie (−0.089), indicating growing barriers to paediatric healthcare access. Negative values were also recorded in Dolnośląskie (−0.085), Pomorskie (−0.057), Łódzkie (−0.055), and Mazowieckie (−0.048), i.e., in regions diverse in terms of socio-economic development. Notably, Mazowieckie, despite its strong economic potential, did not show improvement, which supports the hypothesis that economic growth does not automatically translate into greater accessibility of healthcare services.
Overall, the findings suggest that convergence processes remain ambiguous: some provinces are “catching up” with the national average, while others are widening the gap. These results highlight the importance of territorially differentiated health policy interventions and regional cohesion strategies.
For the purposes of regional planning and sustainable development policy, this classification provides the basis for identifying regions that require more action and those that can serve as a model of good practice.

5. Discussion

The interpretation of the findings from this study reflects broader themes identified in the literature on healthcare equity, regional convergence, and sustainable development. The general observation of weak to moderate correlations between the Paediatric Service Accessibility (PSA) Index and socio-economic indicators in many Polish voivodeships aligns with prior evidence that socio-economic advancement does not automatically lead to equitable access to healthcare services [16]. Goryakin et al. (2017), for example, emphasised that improvements in healthcare infrastructure often lag behind economic growth unless they are guided by targeted policy interventions [7].
The weakest correlations, observed in regions such as Lubuskie and Podkarpackie, mirror patterns noted in peripheral EU countries, where structural deficiencies and governance limitations inhibit the alignment between social needs and healthcare provision [45,48]. Such persistent inequalities are examples of what Krieger (2014) describes as “embodied inequities”, deep-rooted systemic barriers that translate socio-economic disadvantages into health disparities [27].
Conversely, stronger alignment between the PSA Index and socio-economic indicators in provinces such as Mazowieckie and Małopolskie resonates with research showing that capital regions tend to benefit from cumulative advantages, including superior infrastructure, denser health workforce presence, and more capable administrative structures [57].
Moreover, the widespread statistical significance of Wilcoxon tests across voivodeships reinforces the argument that economic and demographic progress does not necessarily result in synchronised improvements in paediatric healthcare availability. These results are in line with the conclusions of Neutens et al. (2010), who emphasised the importance of integrating both spatial and temporal dimensions into healthcare planning [56].
The limited explanatory power of employment in our Fixed Effects (FE) model further echoes ongoing debates regarding its validity as a proxy for social well-being. As Wilkinson (2003) and Bambra (2011) argue, employment must be assessed in tandem with job quality, access to social protection, and work–life balance to fully understand its relationship with healthcare outcomes [36,37].
In contrast, the significant and consistent role of disposable income and urbanisation in enhancing PSA Index values confirms earlier findings by Andersen and Davidson (2014) and Galea and Vlahov (2005), who show that economic affluence and urban density can drive infrastructural development, albeit sometimes at the expense of equity within metropolitan areas [38,53].
These patterns must be interpreted within the broader framework of sustainable development, particularly its social dimension, which emphasises equity and inclusiveness [30]. The persistence of disparities, despite economic growth, underscores the importance of spatially sensitive policies that foster territorial cohesion, as articulated in the European territorial development strategy [63].
Against this backdrop, insights from other EU countries experiencing similar dynamics provide valuable comparative context. In Romania, for instance, significant public health convergence occurred between 2002 and 2012, with a marked reduction in disparities in the synthetic health pressure index—particularly among regions near the EU average [64,65,66,67]. However, the convergence process proved volatile, initially strong but weakening toward the end of the period, likely due to fragmented governance and uneven decentralisation. A similar trajectory is visible in Poland, where PSA Index gains were strongest between 2010 and 2016, followed by trend divergence across voivodeships.
A comparable pattern can be observed in Bulgaria, where since 2007 the extensive use of European Structural and Investment Funds (ESIF) led to infrastructure modernisation, particularly in transportation and environment [67]. Nevertheless, healthcare-related convergence remained uneven, with urban centers benefiting significantly more than rural areas [68,69]. While investments did reduce regional dispersion in infrastructure (σ-convergence), they did not ensure β-convergence in service availability, paralleling Poland’s experience with PSA disparities.
Spain offers a contrasting yet equally illustrative case. With its strongly decentralised health system governed by autonomous communities, overall system balance improved [70], but regional equity did not necessarily follow. Some regions experienced widening gaps in quality and access [71]. However, significant investments in transportation, largely funded by the EU, contributed to improved spatial accessibility [72]. Convergence between peripheries and metropolises occurred more rapidly than in Poland, but post-2015 momentum slowed, mirroring Poland’s own shift in convergence dynamics.
Taken together, these international experiences affirm that EU funds, particularly the European Regional Development Fund (ERDF), the European Social Fund (ESF), and the Cohesion Fund (CF), play a crucial role in shaping healthcare accessibility at the regional level. Bayerlein (2024) found that regions with higher ESIF absorption had better infrastructure, lower mortality during the COVID-19 pandemic, and stronger health system resilience. Notably, the greatest improvements occurred in less developed regions, supporting the catch-up hypothesis.
Yet, recent research by Alexopoulos et al. (2025) and Crucitti et al. (2024) shows that the positive impact of cohesion funding is front-loaded, with the strongest gains in the initial seven years of implementation [73,74]. Beyond that, marginal benefits decline, especially in more developed areas. This aligns with Poland’s trajectory, where the 2010–2017 funding period coincided with PSA growth, followed by stagnation or divergence in less targeted regions.
Ultimately, the effectiveness of cohesion policy depends on the quality of local governance and institutional coordination. As seen in Bulgaria and Spain, low absorption rates in rural areas, lack of unified investment plans, and weak monitoring mechanisms have diluted the potential for lasting convergence. These systemic limitations must be addressed through integrated, territorially sensitive policies that bridge the gap between socio-economic development and healthcare provision.
The results of the survey are part of the broader context of the implementation of the Sustainable Development Goals. The identified regional differences in the availability of paediatric care confirm the importance of SDG 3 (Good Health and Well-Being) and SDG 10 (Reduced Inequalities) as public policy priorities. Achieving these goals requires not only economic growth, but also conscious spatial planning, redistribution of resources, and the development of health infrastructure in the outermost regions. The proposed approach strengthens the integration between cohesion and health policies, highlighting the need to build a more inclusive and sustainable health system.
Considering this, we strongly recommend enriching the discussion section with these international comparisons and policy implications. Doing so would not only contextualise the Polish experience but also offer actionable insights for decision-makers seeking to align health equity with sustainable regional development.

6. Conclusions

The aim of the study was to examine regional disparities in the accessibility of paediatric services in Poland between 2010 and 2023 and their relationship with socio-economic factors, using the Paediatric Service Accessibility Index (PSA Index). A multi-level methodological approach was applied, including non-parametric tests at the local level and panel regression models at the national level.
The key findings partially confirm hypothesis H1: the increase in socio-economic indicators, such as disposable income and urbanisation, is associated with the greater accessibility of paediatric services at the regional level, particularly in provinces with stronger socio-economic profiles (e.g., Mazowieckie, Małopolskie, Wielkopolskie), whereas employment is not. Hypothesis H2 was also confirmed: there are significant regional differences in the convergence of paediatric service accessibility in relation to socio-economic development, with clear disparities in less developed provinces (e.g., Lubuskie, Podkarpackie, Świętokrzyskie). Hypothesis H3 was partially confirmed: economic improvement does not automatically translate into better access to paediatric care, which highlights the need for public policy interventions to address institutional and infrastructural barriers.
The analysis showed that disposable income and urbanisation have a statistically significant effect on the PSA Index, whereas the employment rate did not reach statistical significance within regions. The negative coefficient for urbanisation suggests potential limitations in service availability in densely populated urban areas, resulting from overstretched healthcare systems.
In the context of the SDGs, the findings emphasise the relevance of Goal 3 (Good Health and Well-Being) and Goal 10 (Reduced Inequalities). Paediatric healthcare accessibility is crucial for sustainable social development, and regional inequalities highlight the need for more nuanced territorial cohesion policies. Policy recommendations include: (1) targeted investments in healthcare infrastructure in less developed regions, (2) optimisation of resource distribution in urban areas, and (3) the development of policies supporting equal access to healthcare for children. The PSA Index, constructed using Hellwig’s method, can serve as a tool for identifying priority areas for intervention. Future research should account for institutional factors and include international comparisons to better understand the dynamics of these relationships.

Author Contributions

T.Z., A.Z., and E.Z. contributed equally to the conceptualisation, methodology, validation, formal analysis, investigation, writing—original draft preparation, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AICAkaike Information Criterion
BICBayesian Information Criterion
FEFixed Effects
PSA IndexPaediatric Healthcare Accessibility Index
RERandom Effects
SDGsSustainable Development Goals
UNUnited Nations

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Sustainability 17 08210 g001
Figure 1. Spatial distribution of changes in the PSA Index across Polish provinces in the period 2010–2023. Note: DLN: Dolnośląskie; KPM: Kujawsko-Pomorskie; LUB: Lubelskie; LBS: Lubuskie; LDZ: Łódzkie; MLP: Małopolskie; MAZ: Mazowieckie; OPO: Opolskie; PDK: Podkarpackie; PDL: Podlaskie; POM: Pomorskie; WMZ: Warmińsko-Mazurskie; SKL: Śląskie; SWK: Świętokrzyskie; WKL: Wielkopolskie; ZPM: Zachodniopomorskie.
Figure 1. Spatial distribution of changes in the PSA Index across Polish provinces in the period 2010–2023. Note: DLN: Dolnośląskie; KPM: Kujawsko-Pomorskie; LUB: Lubelskie; LBS: Lubuskie; LDZ: Łódzkie; MLP: Małopolskie; MAZ: Mazowieckie; OPO: Opolskie; PDK: Podkarpackie; PDL: Podlaskie; POM: Pomorskie; WMZ: Warmińsko-Mazurskie; SKL: Śląskie; SWK: Świętokrzyskie; WKL: Wielkopolskie; ZPM: Zachodniopomorskie.
Sustainability 17 08210 g001
Table 1. A summary of Spearman correlation coefficients, along with Wilcoxon tests.
Table 1. A summary of Spearman correlation coefficients, along with Wilcoxon tests.
ProvinceSpearman’s
Rho		Wilcoxon
(PSA Index vs. Employment Rate)
p-Value		Wilcoxon
(PSA Index vs. Urbanisation Rate)
p-Value		Wilcoxon
(PSA Index vs.
Disposal Income p.c.)
p-Value
DLN0.130.00110.00110.0011
KPM0.280.00580.00490.0064
LUB0.150.02780.03120.0215
LBS0.10.04910.05740.0448
LDZ0.310.00250.00310.0027
MLP0.420.00070.00050.0008
MAZ0.450.00020.00010.0003
OPO0.230.01140.00970.0106
PDK0.120.03380.03960.0309
PDL0.260.00720.00650.0083
POM0.350.00190.00130.0022
WMZ0.370.00090.00100.0011
SKL0.180.01810.02030.0169
SWK0.330.00230.00160.0028
WKL0.390.00080.00060.0010
ZPM0.390.00420.00370.0053
Note: DLN: Dolnośląskie; KPM: Kujawsko-Pomorskie; LUB: Lubelskie; LBS: Lubuskie; LDZ: Łódzkie; MLP: Małopolskie; MAZ: Mazowieckie; OPO: Opolskie; PDK: Podkarpackie; PDL: Podlaskie; POM: Pomorskie; WMZ: Warmińsko-Mazurskie; SKL: Śląskie; SWK: Świętokrzyskie; WKL: Wielkopolskie; ZPM: Zachodniopomorskie.
Table 2. Fixed and Random Effects estimation results.
Table 2. Fixed and Random Effects estimation results.
VariableFEp-Value (FE)REp-Value (RE)
Constant0.260960.4140.064570.630
Employment rate 0.002600.6100.005490.004
Urbanisation rate −0.003570.005−0.003120.016
Disposable income 0.0000610.0000.000060.001
Table 3. Convergence group.
Table 3. Convergence group.
Convergence GroupProvincesDirection of ConvergenceCharacteristics
Strong
convergence		Mazowieckie,
Małopolskie,
Wielkopolskie, Śląskie		From belowHigh correlation and significant tests; PSA is steadily approaching the level of economic indicators.
Moderate convergencePomorskie, Warmińsko-Mazurskie, Zachodniopomorskie, ŁódzkieFrom belowMean correlation and stable differences; further convergence is possible if trends continue.
Potential
convergence		Podlaskie,
Kujawsko-Pomorskie,
Opolskie, Świętokrzyskie		Bottom or mixedModerate correlation values and test differences; the situation is diverse, requiring local diagnosis.
Lack of
convergence		Lubuskie, Podkarpackie, Lubelskie, DolnośląskieFrom below or divergenceThe low correlations and differences between PSA and socio-economic indicators are persistent and systematic.
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Zienkiewicz, T.; Zalewska, A.; Zienkiewicz, E. Regional Disparities and Determinants of Paediatric Healthcare Accessibility in Poland: A Multi-Level Assessment of Socio-Economic Drivers and Spatial Convergence (2010–2023). Sustainability 2025, 17, 8210. https://doi.org/10.3390/su17188210

AMA Style

Zienkiewicz T, Zalewska A, Zienkiewicz E. Regional Disparities and Determinants of Paediatric Healthcare Accessibility in Poland: A Multi-Level Assessment of Socio-Economic Drivers and Spatial Convergence (2010–2023). Sustainability. 2025; 17(18):8210. https://doi.org/10.3390/su17188210

Chicago/Turabian Style

Zienkiewicz, Tadeusz, Aleksandra Zalewska, and Ewa Zienkiewicz. 2025. "Regional Disparities and Determinants of Paediatric Healthcare Accessibility in Poland: A Multi-Level Assessment of Socio-Economic Drivers and Spatial Convergence (2010–2023)" Sustainability 17, no. 18: 8210. https://doi.org/10.3390/su17188210

APA Style

Zienkiewicz, T., Zalewska, A., & Zienkiewicz, E. (2025). Regional Disparities and Determinants of Paediatric Healthcare Accessibility in Poland: A Multi-Level Assessment of Socio-Economic Drivers and Spatial Convergence (2010–2023). Sustainability, 17(18), 8210. https://doi.org/10.3390/su17188210

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