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Article

Examining the Relationship Between Urban Park Quality and Residents’ Health in South Korean Cities Using Public Data

Department of Landscape Architecture, Chonnam National University, Gwangju 61186, Republic of Korea
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Authors to whom correspondence should be addressed.
Land 2025, 14(6), 1191; https://doi.org/10.3390/land14061191
Submission received: 7 April 2025 / Revised: 22 May 2025 / Accepted: 1 June 2025 / Published: 2 June 2025
(This article belongs to the Section Land, Biodiversity, and Human Wellbeing)

Abstract

Urban parks are critical components of green infrastructure, supporting recreation and public health. This study investigates the association between urban park quality and health outcomes in 85 South Korean cities, utilizing a localized version of the ParkScore Index. The Korean ParkScore evaluates five dimensions: acreage, amenities, investment, accessibility, and equity. The health indicators include municipal-level rates of mental health disorders (anxiety, depression, insomnia, ADHD, and schizophrenia) and obesity. Pearson’s correlation analysis revealed significant negative associations between ParkScore rankings and mental health indicators, particularly depression and anxiety. Higher-quality, more accessible parks correlated with lower levels of psychological distress, emphasizing the public health benefits of urban green spaces. While the cross-sectional design limits causal inference, the results support the role of urban parks as essential infrastructure for mental well-being. The findings underscore the need for equitable and data-driven urban park policies in fostering health-supportive urban environments and highlight the importance of considering specific ParkScore dimensions in urban planning.

1. Introduction

Urban parks are critical public health resources that significantly impact physical and mental well-being. In South Korea, the increasing prevalence of mental health disorders and obesity presents significant public health challenges. For instance, recent statistics indicate a rising trend in anxiety and depression diagnoses across various age groups, alongside a persistent issue of obesity, which is often linked to sedentary lifestyles and a lack of accessible spaces for physical activity. Urban parks, by providing opportunities for exercise and active recreation, play a crucial role in combating this public health challenge. Korean city parks, while diverse in their characteristics, often serve as vital community hubs, offering spaces for relaxation, exercise, and social interaction within densely populated urban environments. Various studies have demonstrated that residents in areas with high park accessibility have higher levels of physical activity, lower obesity rates, and direct improvements in mental health conditions such as depression, anxiety disorders, and stress [1,2]. Notably, frequent visits to green spaces are associated with a reduced reliance on mental health-related medications, with a more pronounced effect observed among socioeconomically disadvantaged groups [1]. Additionally, parks facilitate social interactions, which can alleviate depression [2].
Researchers have increasingly identified causal mechanisms linking park accessibility to mental health, moving the relationship beyond simple correlation. These mechanisms include stress reduction through exposure to nature, promotion of physical activity, and facilitation of social cohesion. As a result, developing data-driven policies and continuously monitoring long-term effects have become critical priorities. Urban planning requires an integrated multidimensional approach, encompassing physiological benefits, socioeconomic impacts, and spatial design elements. This approach highlights urban parks as essential infrastructure that extends beyond recreational spaces, actively contributing to the psychological well-being of urban residents [3].
In New York City, which faced significant setbacks from the coronavirus disease 2019 (COVID-19) pandemic, generally recognized in March 2020, officials have initiated recovery efforts through public infrastructure, particularly urban parks. Scholars have found that well-designed and accessible green spaces enhance neighborhood connections, attract visitors, and contribute to job creation. Furthermore, increased investment in parks has led to higher park utilization, which has, in turn, resulted in reduced stress and improved mental health among residents [3]. From this perspective, researchers increasingly recognize urban parks as a key indicator of urban competitiveness and use them as a means to address climate crises, promote equity, and strengthen democracy in the pursuit of a more just city [4].
In this context, the present study explores the value of urban parks and reevaluates their role in public health by examining their relationship to the well-being of urban residents. This research provides a solid policy foundation for strengthening the role of parks in future urban planning. These findings suggest recognizing urban public parks as essential mental health infrastructure and ensuring their accessibility as a fundamental right. This shift in perspective can help create healthier urban environments that better support the well-being of all citizens.

2. Literature Review

The Trust for Public Land (TPL) developed the ParkScore Index in 2012 as a tool for assessing urban park systems in the United States and evaluating the accessibility and quality of urban parks. Initially, the index focused on identifying disparities in park accessibility using Geographic Information System (GIS)-based spatial analysis techniques and emphasized three key metrics: the percentage of residents without park access within a 10 min walk, the average park size, and the per capita park budget (per 1000 residents). Over time, the assessment framework expanded to include five broader categories: accessibility, investment, amenities, acreage, and equity. The ParkScore Index is widely recognized for its standardized, data-driven approach to evaluating urban park systems, offering a comparative benchmark across cities [5].
We can determine a city’s ParkScore ranking by evaluating the index scores based on 14 specific measurement criteria spanning five categories: park size, investment, facilities, accessibility, and equity. Researchers then comparatively assess these 14 criteria against the 100 largest cities in the United States, establishing a relative benchmark for evaluation. Through this methodology, the ParkScore Index provides a quantitative measure of the social contributions of urban parks. Table 1 summarizes the ParkScore Index indicators.
Based on the evaluation results from this system, cities with lower rankings in the ParkScore Index are actively using ParkScore data to develop strategies for improvement. Since 2015, in collaboration with the National Recreation and Park Association (NRPA) [5], cities have standardized the data collection methodology, establishing ParkScore as a nationally recognized evaluation framework. Notably, within the park investment indicator, the assessment incorporates public funding at the federal, state, and county levels and donations from nonprofit organizations and volunteer hours, allowing for a more comprehensive analysis of financial structures. Since 2023, policymakers have strengthened the integration of climate resilience and public health considerations into the evaluation [3]. Additionally, there have been efforts to reflect actual community usage patterns by promoting participatory data collection (Public Participation Geographic Information System: PPGIS) and incorporating residents’ experiences into park planning and management.
According to the latest 2024 data, 76% of residents in the 100 largest U.S. cities have access to a park within a 10 min walk. However, low-income and minority communities still experience 45% less park space on average compared to other areas. To address this disparity, the Trust for Public Land (TPL) aims to achieve 100% 10 min walk access in all cities by 2030 and continues to monitor annual progress through the ParkScore Index [3]. Cities like Minneapolis and Seattle, which consistently have top ParkScore rankings, are investing in qualitative park management and demographic equity improvements [6,7]. These efforts show that ParkScore is a critical policy tool, helping to strengthen the role of urban parks in future city planning by providing evidence to guide strategic development. The ParkScore Index’s value lies in its ability to provide a comprehensive, data-driven framework that integrates multiple dimensions of park quality and accessibility into a single, comparable metric, which is often lacking in other park quality assessment methods that may focus on specific attributes like safety or aesthetics [8,9].
The ParkScore Index is not just shaping urban park evaluations in the United States; it is laying the foundation for a new global paradigm in park assessments. Cities worldwide are adapting and expanding upon this framework to fit their unique urban landscapes. For instance, Vancouver, Canada, has incorporated the ParkScore methodology into its “Green Access 2030” plan to enhance equitable access to green spaces across the city. Meanwhile, Mexico City, in collaboration with the Trust for Public Land, has developed ParqueScore MX, a localized adaptation that factors in park drainage capacity and Indigenous cultural elements to reflect the region’s distinct environmental and social characteristics. This adaptability underscores the potential of the ParkScore framework to be tailored to diverse urban contexts and policy priorities.
On an even broader scale, the United Nations Human Settlements Programme (UN-Habitat) will be launching a global urban park evaluation framework in 2025, drawing upon ParkScore’s methodology as a key reference. This progression signifies more than just the export of an assessment tool—it represents an evolutionary adaptation of ParkScore to diverse urban contexts. These developments highlight how cities worldwide are leveraging ParkScore as a benchmarking tool and catalyst for innovative park management systems. As urban centers increasingly prioritize resilient and equitable green infrastructure, ParkScore’s role as a core instrument for strategic urban planning will only continue to grow.
The correlation between urban parks, green spaces, and residents’ mental health has long been a subject of interest for researchers. In their study on urban park improvement projects in Los Angeles, Sturm and Cohen [10] found that residents in areas with higher park accessibility reported experiencing less psychological distress and had higher MHI-5 (Mental Health Inventory-5) scores. Their findings provided empirical evidence that urban parks play a significant role in promoting mental and physical well-being. Similarly, Triguero-Mas et al. [11] highlighted that access to natural environments contributes to stress reduction and increased life satisfaction, emphasizing that contact with nature enhances mental restoration and self-esteem. Jiang et al. [12] further reinforced this perspective by demonstrating that a higher urban green density correlates with lower stress levels and better mental health among city dwellers. These findings are further supported by comprehensive reviews that highlight the broad ecosystem services provided by nature, including significant mental health benefits [13].
Beyond mental well-being, urban parks are also recognized for their crucial role in promoting physical health. Studies consistently show that greater access to green spaces is associated with increased physical activity levels and reduced prevalence of obesity, particularly in urban settings [14].
In the Korean context, Lim [15] analyzed the relationship between urban environmental factors and mental health, confirming that the physical characteristics of parks positively influence psychological recovery. Her study underscored the importance of urban parks in city planning. Moreover, Lee [16] found that residents in areas with higher park accessibility tend to visit parks more frequently, which, in turn, contributes to stress relief and mental health improvements. These studies largely validate their findings through physiological and psychological measurements, including hormone levels, heart rate, mood, concentration, and other biological and psychological indicators. The collective body of research supports the argument that urban parks are an essential mental health infrastructure, reinforcing their significance in urban planning and public health policies.
Meanwhile, Rigolon et al. [17] examined disparities in park accessibility and quality across major U.S. cities, focusing on how these factors contribute to mental health inequalities across racial and socioeconomic groups. Additionally, Lou and Taylor [14] used TPL’s regional park accessibility data to analyze its relationship with physical activity and mental health among children and adolescents. Their findings suggest that children in areas with inadequate park infrastructure are at a higher risk of experiencing poor physical and mental health outcomes. Thus, a growing body of research confirms the positive impact of park accessibility and quality on residents’ mental health. However, despite the recognized value of ParkScore, a limited number of studies directly link the index to objective mental health indicators.
This gap in the literature serves as the basis for the present study, which investigates the relationship between urban park accessibility and mental well-being through a more comprehensive and data-driven approach. This study builds on the observation that, despite ParkScore’s value, few studies have directly examined its relationship with objective measures of urban residents’ mental health.
This study advances existing research by adapting ParkScore evaluation criteria to South Korea’s urban environment, allowing for a localized assessment of urban parks and their impact on public health. It analyzes the correlation between ParkScore-based park accessibility and key health indicators, including mental health and obesity rates. While most prior research focuses on cities in the United States and Europe and emphasizes physical outcomes, this study broadens the scope by applying the methodology to Korean cities and examining both physical and mental health dimensions. Notably, it incorporates data on major mental health disorders, such as attention deficit hyperactivity disorder (ADHD), depression, insomnia, and anxiety disorders, to offer a more comprehensive understanding of park access and well-being. In addition to this, this study evaluates park equity, moving beyond physical accessibility to explore how equitable access influences mental health, thereby offering a more holistic perspective on the role of urban parks in public health.
This study also expands the scope of analysis by including small- and mid-sized cities rather than focusing solely on major metropolitan areas. Prior research on urban parks and health has predominantly focused on large metropolitan areas, potentially overlooking the unique characteristics and needs of smaller urban contexts. Examining the relationship between park accessibility and mental health across diverse urban settings offers more inclusive and applicable insights. These findings can inform urban planning and park policies in South Korea, providing a foundation for strategies that better integrate accessibility and mental health considerations at the national and local levels.

3. Research Scope and Methodology

3.1. Research Scope

This study evaluates the quality of urban parks across 85 metropolitan and municipal governments in South Korea, ranks them based on their performance, and examines their impact on public health. The primary objective is to assess the role of urban parks in enhancing quality of life, emphasizing their significance as essential infrastructure for urban well-being and sustainable development. The specific provinces and cities assessed in this study are listed in Table 2.
We selected 85 municipal-level cities in South Korea for this study since county-level areas are predominantly rural or have low population densities, making them less suitable for analyzing urban park accessibility and its public health impact. In contrast, municipal cities tend to have higher population densities and more diverse park distribution and usage patterns, offering a better context for evaluating urban park indicators. Focusing on these 85 cities allows for a clearer research scope and a more accurate assessment of the role urban parks play in public health and city planning.

3.2. Analysis Method for the Korean ParkScore

The following sections elaborate on this study’s analysis process for establishing the Korean ParkScore.

3.2.1. Selection of Evaluation Indicators

This study develops the Korean ParkScore by preserving the core structure of the Trust for Public Land’s (TPL) five key indicators—acreage, amenities, investment, accessibility, and equity—while adapting each metric to fit Korea’s urban context using publicly available government and municipal data.
  • We evaluated acreage by calculating the average park size and the proportion of park area relative to the total urban area.
  • We measured amenities as the density of park facilities, using the ratio of total park facilities to the total park area within each city. This approach was chosen over simply counting the number of physical activity facilities to provide a more standardized measure of amenity provisions relative to the available park space, reflecting the intensity of park use potential.
  • We assessed investment based on the average annual municipal budget allocated to urban parks over the past three years.
  • We defined accessibility as the percentage of the population living within 0.75 km (km) of an urban park. The 0.75 km radius was selected as a proxy for a 10 min walk, a commonly used standard in urban planning and public health research for assessing convenient access to local amenities. This specific distance was chosen based on its practical applicability to available national spatial data in South Korea.
  • For equity, we departed from TPL’s race- and income-based approaches and instead used the Gini coefficient of park distribution within each city to reflect spatial fairness. The Gini coefficient, typically used to measure income inequality, was adapted here to quantify the equitable distribution of park resources across different areas within a city. A lower Gini coefficient indicates a more even distribution of park space. This approach was chosen because, while income disparities exist in South Korea, direct, publicly available, fine-grained income data linked to park access at the municipal level are limited. Furthermore, focusing on the spatial distribution of parks provides a robust measure of equity regardless of the specific demographic characteristics, aligning with the goal of creating a globally adaptable framework. By tailoring these indicators to the Korean context, the Korean ParkScore offers a more accurate and locally relevant tool for evaluating urban parks and informing public policy. Since TPL operates primarily in North America, using race and income levels as indicators of equity poses few limitations in that context. However, for a globally adaptable framework, particularly in countries with a predominantly single-race population, assessing equity based on the spatial distribution of parks is more appropriate. Therefore, this study adjusted the equity metric by using the Gini coefficient to assess whether park resources are concentrated in specific areas or evenly distributed across the urban landscape.
To calculate the access score, we applied Equation (1) as follows:
Access score = Population within   0.75   km of a park Total Population × 100
where the data are the population within the 0.75 km Urban Park Service Area, sourced from the National Geographic Information Institute (Ministry of Land Infrastructure and Transport); the data field is “demographics”. The “population within 0.75 km of a park” was calculated by overlaying urban park polygons with fine-grained population grid data (e.g., census block data or population density maps) to determine the number of residents residing within the specified buffer zone around each park. This calculation directly reflects the convenience of park use for citizens.
To calculate the acreage score, we applied Equation (2a–c):
Average Park Size = Total Urban Park Area Νumber of Parks
Parkland Ratio = Total Urban Park Area Total Urban Area × 100
Per Captita Park Area = Total Urban Park Area Total Population
In Equation (2), we used the National Urban Park Standard Data from the Public Data Portal (Ministry of the Interior and Safety). The data field is the “urban area and urban park area analysis”. The urban park represents the size of the space available for public use. For indicators that do not naturally range from 0 to 100 (e.g., average park size), a min–max normalization method was applied to rescale the values to a 0–100 scale. Specifically, the formula used was (Value − Min)/(Max − Min) × 100, where Min and Max represent the minimum and maximum values observed for that indicator across all 85 cities, respectively.
To calculate the facilities score, we applied Equation (3):
Facility Score = Total Νumber of Park Facilities Total Urban Park Area
Park facilities include exercise, recreational, educational, convenience, and other facilities. For this calculation, we used the National Urban Park Standard Data and the Urban Park Facility Data obtained from the Public Data Portal and the Open Data Portal from the Ministry of the Interior and Safety. The data field is the “urban park facility statistics by park”. Park facilities are a crucial factor in determining the functionality and convenience of urban parks.
Finally, to calculate the equity score, we applied Equation (4), as follows:
1 G i n i   C o e f f i c i e n t × 100
For this calculation, we used Regional Statistics (Local Government Basic Statistics) on Land, Climate, and Administrative District Data, which was obtained from the Korean Statistical Information Service and local government statistics. The data field is “administrative districts and land statistics in South Korea”. This calculation evaluates the equity of urban park distribution.

3.2.2. Data Collection

This study ensures data reliability for the five Korean ParkScore indicators by actively sourcing publicly available government datasets. The data collection process was as follows:
  • Acreage data came from the National Urban Park Standard Dataset on the Public Data Portal.
  • Amenities data were primarily from the same dataset and the Information Disclosure Portal. When data were incomplete, we contacted the relevant government agencies and local municipalities to fill in the gaps.
  • Investment data were from budget reports issued by the urban park departments of local governments.
  • Accessibility data came from the National Spatial Information Platform, using population data within a 0.75 km service radius of urban parks.
  • Equity data were from regional statistics and administrative district datasets, allowing us to assess the equity of park resource distribution across urban areas.
Data on the health of residents, including municipal-level mental health statistics (ADHD, insomnia, anxiety disorders, depression, bipolar disorder, and schizophrenia) and obesity rate statistics, were sourced from the Health Insurance Review and Assessment Service (HIRA) via the government’s public data portal. Obesity rate statistics were specifically obtained from regional obesity treatment records within the HIRA dataset.
By integrating these sources, this study builds a comprehensive, data-driven framework for evaluating the quality and accessibility of urban parks in South Korea.

3.3. Analysis Method for the Relationship Between ParkScore and Mental Health

This study used Pearson’s correlation coefficient to analyze the relationship between ParkScore rankings and mental health indicators across municipalities. This statistical method measures the strength and direction of a linear relationship between two variables, making it well-suited for evaluating how urban park quality and accessibility relate to mental health outcomes.
Pearson’s correlation coefficient ranges from +1 and −1, as defined by the Cauchy–Schwarz inequality: +1 indicates a perfect positive correlation, 0 indicates no correlation, and −1 indicates a perfect negative correlation.
In this study, a negative correlation indicates that as the ParkScore rankings increase, the incidence of certain mental disorders decreases. We applied Pearson’s correlation because the data met the necessary conditions of normal distribution and linearity. This approach provides a quantitative basis for assessing how urban park infrastructure impacts mental health, offering valuable insights for data-driven urban planning and public health policy. Equation (5) shows the formula used to calculate Pearson’s correlation coefficient:
r X Y = i n X i X ¯ Y i Y ¯ i n X i X ¯ 2 i n Y i Y ¯ 2
This study examined the correlation between each city’s overall ParkScore and major mental health disorders, including ADHD, insomnia, anxiety disorders, depression, bipolar disorder, and schizophrenia. We used municipal-level mental health data from 2023, sourced from the Health Insurance Review and Assessment Service (HIRA). To explore the link between park accessibility and physical health, we also included obesity rate data. Furthermore, to provide more nuanced insights for policymakers and urban managers, we conducted additional Pearson’s correlation analyses between each of the five individual ParkScore dimensions (acreage, amenities, investment, accessibility, and equity) and each health outcome.
To assess the impact of park accessibility and quality on mental health outcomes, we normalized the incidence rates of mental disorders by city population and compared them with the ParkScore rankings. This approach offers quantitative insights into how urban parks influence mental and physical well-being, providing evidence to support data-driven urban planning and public health policies.

4. Results

4.1. Results of Parkscore Evaluation

Table S1 (Table S1 has been moved to Supplementary Materials to streamline the main text) presents the evaluation results based on ParkScore. The findings highlight Ansan-si, Changwon-si, and Dongducheon-si as some of the highest-ranking cities (These results represent rankings that are calculated using equal weights for the five evaluation indicators. It is notable that many cities achieved a score of 100 in Investment and Amenities. This occurs when a city’s values for these indicators are at or above the maximum observed value across all 85 cities due to the min–max normalization applied to scale all indicators to a 0–100 range. For more details and to explore the interactive visualization tool, please visit the following link: https://korea-parkscore.pages.dev/ (accessed on 5 May 2025)).

4.2. Relationship Between ParkScore, Mental Health, and Obesity Rates

The analysis revealed a statistically significant negative correlation between higher ParkScore rankings and the incidence of mental health disorders such as anxiety disorders, depression, bipolar disorder, and schizophrenia. Specifically, the Pearson’s correlation coefficients were −0.3514 for anxiety disorders (p = 0.0010), −0.2923 for depression (p = 0.0066), −0.3255 for bipolar disorder (p = 0.0024), and −0.3444 for schizophrenia (p = 0.0012). This finding suggests that greater park accessibility and higher park quality can have a positive impact on residents’ mental health. Specifically, increased access to parks appears to reduce stress and enhance psychological stability, which may help lower the prevalence of mental health conditions.
Similarly, the correlation analysis between ParkScore and obesity rates showed a statistically significant negative relationship, indicating that cities with higher ParkScore rankings tend to have lower obesity rates. The findings highlight the role of accessible parks in promoting physical activity, which contributes to healthier lifestyles. By providing dedicated spaces for exercise and recreation, urban parks support mental and physical health, reinforcing their importance in creating healthier urban environments. Table 3 summarizes these findings.
As shown in Table 4, the Accessibility and Equity dimensions of the ParkScore consistently showed the strongest negative correlations with mental health disorders, indicating that ensuring easy access to parks and equitable distribution of park resources are particularly impactful for mental well-being. Investment also showed significant correlations, suggesting that financial commitment to parks plays a role. Acreage and Amenities, while contributing to the overall ParkScore, showed weaker or non-significant correlations with individual health outcomes when disaggregated. This suggests that while overall park quality is important, the availability (accessibility) and fair distribution (equity) of parks may be more critical factors influencing mental health outcomes than sheer size or the number of specific facilities. These findings provide more nuanced insights for urban planners, suggesting that strategies focusing on improving accessibility and equitable distribution could yield more pronounced public health benefits.
These findings confirm the positive association that improved park accessibility and quality can have on the mental and physical health of urban residents. These results suggest that enhancing urban parks may help reduce the prevalence of mental health disorders and obesity, reinforcing the role of green spaces as essential public health infrastructure.
Moreover, this study offers empirical evidence that can inform urban planning and park policy development. By integrating ParkScore-based assessments into planning strategies, policymakers can create healthier, more equitable cities where parks actively support mental well-being and promote physical activity for all residents.

5. Discussion and Conclusions

This study used the Korean ParkScore system to empirically analyze the relationship between urban parks, mental health, and obesity rates. These findings confirm that park accessibility and quality significantly influence the mental and physical well-being of residents. Cities with greater park access showed lower rates of mental health disorders, including anxiety, depression, and insomnia. Parks support psychological stability and encourage physical activity, helping to lower obesity rates. The disaggregated analysis further highlights that accessibility and equity are particularly influential dimensions of park quality in relation to mental health outcomes, providing actionable insights for targeted urban interventions.
These findings emphasize that urban parks are more than recreational spaces—they are critical public health resources that promote overall well-being and social equity. This study highlights the importance of equitable park distribution and improved accessibility in addressing health disparities. Expanding and enhancing urban green spaces should be a central strategy in public health and urban development.
However, this study has limitations. Since it relies on cross-sectional data and focuses on correlation analysis, it does not establish causal relationships. Furthermore, it does not fully integrate factors such as socioeconomic variables, transportation infrastructure, or civic engagement. These gaps underscore the need for a more comprehensive multivariate approach. Future research should adopt longitudinal designs and qualitative methods to elucidate the complex interactions between urban parks and public health. A deeper exploration of these dynamics will clarify causal mechanisms and support more effective policy development.
Based on the findings, we recommend the following directions for future urban planning and park management. These recommendations are directly informed by our results, particularly the strong correlations observed between the overall ParkScore and its accessibility and equity dimensions with mental health outcomes.
First, strengthen the quantitative and qualitative evaluation systems. Urban park assessments should integrate additional variables, including socioeconomic characteristics, transportation networks, and civic engagement, alongside traditional indicators. For example, future studies could explore the availability of local-level income data or conduct surveys to gather information on residents’ perceived safety and social interactions within parks. Collaborations with local health centers could provide more granular health data. A more holistic evaluation framework, supported by international benchmarking, can offer deeper insights into how parks influence public health.
Second, establish a long-term monitoring and feedback system. Developing a sustained monitoring mechanism will help track the long-term impacts of park improvement efforts. Linking public health data with park accessibility metrics will enable policymakers to make informed, adaptive decisions. Regular health surveys and park usage analyses should be part of this system.
Third, develop inclusive urban park policies to reduce health disparities. Urban planners should prioritize park access in underserved areas and for vulnerable groups. Collaborative models involving local government and the private sector can facilitate equitable development. Public/private partnerships can support sustainable and inclusive park spaces. Given the strong correlation between park equity and mental health outcomes observed in this study, policies aimed at improving the spatial distribution of parks in historically underserved neighborhoods are particularly crucial.
Fourth, advance research through longitudinal, multivariate, and qualitative analyses. Overcoming the limitations of cross-sectional studies will require more rigorous methods. Longitudinal research, combined with multivariate and qualitative approaches, can offer strong empirical foundations for future urban and public health policies.
By implementing these strategies, urban parks can play a pivotal role in enhancing city competitiveness and improving the quality of life for all residents. This study demonstrates how the Korean ParkScore system serves as a foundational tool in shaping equitable and health-focused urban park policies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/land14061191/s1, Table S1: ParkScore evaluation scores and rankings of 85 cities.

Author Contributions

Conceptualization, Y.K. and S.L.; methodology, Y.K. and K.P.; software, K.P.; data curation, I.K. and C.S.; writing—original draft preparation, K.P., I.K. and C.S.; writing—review and editing, Y.K., S.L. and G.L.; visualization, S.L.; supervision, Y.K.; project administration, Y.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Acknowledgments

We thank Eunil Kim for their construction comments. We also thank the editors and anonymous reviewers for their valuable comments and suggestions on our paper.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Turunen, A.W.; Halonen, J.; Korpela, K. Cross-sectional associations of different types of nature exposure with psychotropic, antihypertensive and asthma medication. Occup. Environ. Med. 2023, 80, 111–118. [Google Scholar] [CrossRef] [PubMed]
  2. Hazlehurst, M.F.; Muqueeth, S.; Wolf, K.L. Park access and mental health among parents and children during the COVID-19 pandemic. BMC Public Health 2022, 22, 800. [Google Scholar] [CrossRef] [PubMed]
  3. Foderaro, L.W.; Klein, W. The Power of Parks to Promote Health; Trust for Public Land: San Francisco, CA, USA, 2023. [Google Scholar]
  4. City of New York. OneNYC 2050: Strategic Plan. NYC Mayor’s Office of Sustainability. 2024. Available online: https://climate.cityofnewyork.us/wp-content/uploads/2024/09/OneNYC_2050_Strategic_Plan.pdf (accessed on 2 May 2025).
  5. National Recreation and Park Association (2015). Available online: https://beachlab.sc.edu/2015-national-recreation-and-park-association-conference/ (accessed on 2 May 2025).
  6. Minneapolis Park and Recreation Board. Minneapolis Places Second in Trust for Public Land’s 2024 ParkScore® Index. 2024. Available online: https://www.minneapolisparks.org/news/2024/05/22/minneapolis-places-second-in-trust-for-public-lands-2024-parkscore-index/ (accessed on 21 February 2025).
  7. Schulkin, R. Trust for Public Land Names Seattle 6th Best Parks and Recreation System in the Nation. Pathways Seattle Parks and Recreation. 2024. Available online: https://parkways.seattle.gov/2024/05/22/trust-for-public-land-names-seattle-6th-best-parks-and-recreation-system-in-the-nation/ (accessed on 24 December 2024).
  8. Corley, E.A.; Ahn, J.J.; Kim, Y.; Lucio, J.; Rugland, E.; Molina, A.L., Jr. Conceptualizing lenses, dimensions, constructs, and indicators for urban park quality. Environ. Justice 2018, 11, 208–221. [Google Scholar] [CrossRef]
  9. Chen, S.; Sleipness, O.; Xu, Y.; Park, K.; Christensen, K. A systematic review of alternative protocols for evaluating non-spatial dimensions of urban parks. Urban For. Urban Green. 2020, 53, 126718. [Google Scholar] [CrossRef]
  10. Sturm, R.; Cohen, D. Proximity to urban parks and mental health. J. Ment. Health Policy Econ. 2014, 17, 19–24. [Google Scholar] [PubMed] [PubMed Central]
  11. Triguero-Mas, M.; Dadvand, P.; Cirach, M.; Martínez, D.; Medina, A.; Mompart, A.; Basagaña, X.; Gražulevičienė, R.; Nieuwenhuijsen, M.J. Natural outdoor environments and mental and physical health: Relationships and mechanisms. Environ. Int. 2015, 77, 35–41. [Google Scholar] [CrossRef] [PubMed]
  12. Jiang, B.; Chang, C.-Y.; Sullivan, W.C. A dose of nature: Tree cover, stress reduction, and gender differences. Landsc. Urban Plan. 2014, 132, 26–36. [Google Scholar] [CrossRef]
  13. Bratman, G.N.; Anderson, C.B.; Berman, M.G.; Cochran, B.; De Vries, S.; Flanders, J.; Folke, C.; Frumkin, H.; Gross, J.J.; Hartig, T.; et al. Nature and mental health: An ecosystem service perspective. Sci. Adv. 2019, 5, eaax0903. [Google Scholar] [CrossRef] [PubMed]
  14. Lou, D.; Taylor, W. Do All Children Have Places to Be Active? Disparities in Access to Physical Activity Environments in Racial and Ethnic Minority and Lower-Income Communities; Active Living Research: San Diego, CA, USA, 2011; Available online: www.activelivingresearch.org (accessed on 21 February 2025).
  15. Lim, Y. A research review of urban environment factors affecting mental health. SH Urban Res. Insight 2021, 11, 79–101. [Google Scholar] [CrossRef]
  16. Lee, S. A Study on the Effect of Urban Parks on Human Health and Well-Being. Master’s Thesis, Hanyang University, Seoul, Republic of Korea, 2021. [Google Scholar]
  17. Rigolon, A.; Browning, M.; Jennings, V. Inequiteis in the quality of urban park systems: An environmental justice investigation of cities in the United States. Landsc. Urban Plan. 2018, 178, 156–169. [Google Scholar] [CrossRef]
Table 1. Scoring methodology for each indicator in the Trust for Public Land (TPL) ParkScore Index.
Table 1. Scoring methodology for each indicator in the Trust for Public Land (TPL) ParkScore Index.
CategoryIndicator
AccessibilityPercent of residents within a 10 min walk to the park
AcreageMedian park size
Parkland as % of city area
InvestmentSpending per resident (3 years)
AmenitiesBasketball hoops per 10,000 residents
Dog parks per 100,000 residents
Playgrounds per 10,000 residents
Recreation and senior centers per 20,000 residents
Restrooms per 10,000 residents
Splashpads and spraygrounds per 100,000 residents
Equity% of people of color within 10 min walk to park
% of low-income households Neighborhoods of color have a—distribution of park space than white neighborhoods
Low-income neighborhoods have a—distribution of park space than high-income neighborhoods
Table 2. List of assessed provinces and cities in South Korea.
Table 2. List of assessed provinces and cities in South Korea.
ProvinceCity Name
Metropolitan CitiesBusan, Daegu, Daejeon, Gwangju, Incheon, Sejong, Seoul, Ulsan
Gangwon-doDonghae, Gangneung, Samcheok, Sokcho, Taebaek, Wonju, Chuncheon
Gyeonggi-doAnsan, Anseong, Anyang, Bucheon, Dongducheon, Gimpo, Goyang, Gwacheon, Gwangju, Gwangmyeong, Gunpo, Guri, Hanam, Hwaseong, Icheon, Namyangju, Osan, Paju, Pocheon, Pyeongtaek, Seongnam, Siheung, Suwon, Uijeongbu, Uiwang, Yangju, Yeoju, Yongin
Gyeongsangnam-doChangwon, Gimhae, Geoje, Jinju, Miryang, Sacheon, Yangsan, Tongyeong
Gyeongsangbuk-doAndong, Gimcheon, Gumi, Gyeonju, Gyeongsan, Mungyeong, Pohang, Sangju, Yeongcheon, Yeongju
Jeollanam-doGwangyang, Mokpo, Naju, Suncheon, Yeosu
Jollabuk-doGimje, Gunsan, Iksan, Jeonju, Jeongeup, Namwon
Jeju Special Self-Governing ProvinceJeju, Seogwipo
Chungcheongnam-doAsan, Boryeong, Cheonan, Dangjin, Gongju, Gyeryong, Nonsan, Seosan
Chungcheongbuk-doCheongju, Chungju, Jecheon
Table 3. Correlation analysis between ParkScore, mental health disorders, and obesity rates.
Table 3. Correlation analysis between ParkScore, mental health disorders, and obesity rates.
DiseasePearson’s Correlation Coefficientp-Value
Mental Health DisordersInsomnia−0.31450.0034
Anxiety Disorders−0.35140.0010
Depression−0.29230.0066
Bipolar Disorder−0.32550.0024
Schizophrenia−0.34440.0012
Attention Deficit Hyperactivity Disorder (ADHD)−0.28480.0082
Obesity Rates−0.25610.0180
Table 4. Correlation analysis between individual ParkScore dimensions and health outcomes.
Table 4. Correlation analysis between individual ParkScore dimensions and health outcomes.
ParkScore
Dimension
InsomniaAnxiety
Disorders
DepressionBipolar DisorderSchizophreniaADHDObesity Rates
Access−0.28 *−0.32 **−0.25 *−0.29 **−0.30 **−0.24 *−0.20
Acreage−0.15−0.18−0.12−0.16−0.17−0.10−0.08
Investment−0.20−0.23 *−0.18−0.21 *−0.22 *−0.17−0.15
Equity−0.25 *−0.28 *−0.22 *−0.26 *−0.27 *−0.21 *−0.19
Amenities−0.10−0.12−0.08−0.10−0.11−0.07−0.05
* p < 0.05; ** p < 0.01.
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Kwon, Y.; Park, K.; Kang, I.; Shin, C.; Lee, G.; Lee, S. Examining the Relationship Between Urban Park Quality and Residents’ Health in South Korean Cities Using Public Data. Land 2025, 14, 1191. https://doi.org/10.3390/land14061191

AMA Style

Kwon Y, Park K, Kang I, Shin C, Lee G, Lee S. Examining the Relationship Between Urban Park Quality and Residents’ Health in South Korean Cities Using Public Data. Land. 2025; 14(6):1191. https://doi.org/10.3390/land14061191

Chicago/Turabian Style

Kwon, Yoonku, Kyeongjun Park, Ingu Kang, Changyeong Shin, Giyeol Lee, and Sanghoon Lee. 2025. "Examining the Relationship Between Urban Park Quality and Residents’ Health in South Korean Cities Using Public Data" Land 14, no. 6: 1191. https://doi.org/10.3390/land14061191

APA Style

Kwon, Y., Park, K., Kang, I., Shin, C., Lee, G., & Lee, S. (2025). Examining the Relationship Between Urban Park Quality and Residents’ Health in South Korean Cities Using Public Data. Land, 14(6), 1191. https://doi.org/10.3390/land14061191

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