More Parks Are Linked to Lower Tract-Level Mental Distress in Less-Walkable Neighborhoods: A South Carolina Analysis

Abstract

Mental health concerns have risen substantially over the last decade. Access to health-promoting environments, like parks, may significantly improve mental health issues such as depression and stress. Yet, despite limited access to traditional mental health services in many US communities, there remains limited research that jointly considers the role of nonclinical interventions such as park availability and neighborhood walkability. Walkability is a crucial determinant of access to green spaces and may shape how individuals benefit from park presence. This study examined the relationship between park availability and mental distress (i.e., stress, depression, and problems with emotions) and the potential moderating role of neighborhood walkability levels. For all census tracts in South Carolina (n = 1,089), the number of available parks was extracted from Google Maps utilizing the OutScraper Application Programming Interface and expressed per 10,000 residents. For each tract, we also obtained the National Walkability Index, mental distress rates from the CDC PLACES dataset, the CDC Social Vulnerability Index, population density, percentage of people living in the same house in the past year, and the population aged 18 years old or above. Using linear regression models, we analyzed the relationship between park availability and mental distress and tested the interaction between park availability and walkability. Greater park availability was associated with lower mental distress rates (b = −0.05, p < 0.05), adjusting for population density, residential stability, social vulnerability, and age. The association between park availability and mental distress significantly varied by walkability levels (b = 0.004, p < 0.05). In neighborhoods with low walkability, park availability was associated with lower mental distress rates, but this association was not significant for medium- and high-walkability neighborhoods. These findings highlight the important role of park access in mitigating mental distress, especially in neighborhoods with low and medium walkability.

Keywords

Mental health—Green spaces—Physical activity—Neighborhood environment—Social vulnerabilities

Introduction

Trends over the past decade demonstrate that the United States has been experiencing a growing mental health crisis (CDC, 2025). Currently, 18.4% of US adults have major depression (Lee et al., 2023), and mental/behavioral disorders account for approximately 5.1% of emergency department visits as of March 2025 (Mental Health-CDC & M.H.-R.E.D.V, 2025). Several studies have documented the significant role of parks and greenery in a neighborhood in either healing mental issues or preventing their development or progression (Gerlach-Spriggs, Kaufman, & Warner, 1998; Bustamante, Guzman, Kobayashi, & Finlay, 2022).

Access to green spaces is linked to increased park use and physical activity, as well as reduced stress and restorative environments that mitigate the risk of depression (Besenyi et al., 2014; Van Cauwenberg, Van Holle, De Bourdeaudhuij, Van Dyck, & Deforche, 2016; Van Holle et al., 2016; Mathis, Rooks, Tawk, & Kruger, 2017; Anderson & Durstine, 2019; Rundle et al., 2023). Various theories support such connections, such as stress reduction theory (Ulrich, 2023) and attention restoration theory (Kaplan, 1995), which refer to the positive effects of nature and greenery in the built environment on mental health status. One study found that women who lived in the highest quintile of cumulative average greenness areas around their homes had a 12% lower mortality rate from all causes, and the association between greenness and mortality was partially mediated by physical activity, particulate matter, social engagement, and depression (James, Hart, Banay, & Laden, 2016). Another study examining the relationship between parks and mental health showed that people who lived closer to parks tended to report better mental health than those who lived farther away, and the number of visits and physical activity minutes was significantly related to the distance (Sturm & Cohen, 2014). However, not all studies have found consistent benefits of park availability on mental health issues, suggesting that their impact may vary based on additional factors (Taylor, Leckey, Lead, & Hochuli, 2020; Kim, Blesoff, Tussing-Humphrys, Fitzgibbon, & Peterson, 2023). For example, other aspects of the built environment, such as neighborhood walkability and social vulnerability, may play important roles. Understanding such relationships is critical for identifying the most effective strategies for utilizing urban green spaces to support mental health and mitigate depressive symptoms (Liu et al., 2023).

Neighborhood walkability, as a critical component of the built environment, contributes significantly to individual and community well-being (Zuniga-Teran et al., 2017). The walkability of a neighborhood is the ease with which residents are able to walk to work, exercise, and access services (Leslie et al., 2007; Kaczynski & Glover, 2012). It is determined by factors such as mixed land use, street connectivity, and population density, all of which enable people to engage in active transportation daily while enhancing safety (Lovasi, Grady, & Rundle, 2012; Thomas, Hesam Shariati, Hallum, & Kaczynski, 2025). Walkable neighborhoods can promote low-cost physical activity, social interaction, and reduced stress, all of which are known to mitigate the global burden of chronic conditions like mental distress (Berke, Koepsell, Moudon, Hoskins, & Larson, 2007; Van Holle et al., 2016; Anderson & Durstine, 2019; Roe et al., 2020; McCormack, Spence, McHugh, & Mummery, 2022; Wang, Narcisse, & McElfish, 2023). Whereas the main effects of walkability have been well studied in the literature, minimal research has examined how walkability may interact with other neighborhood factors in affecting health outcomes. One study reported that proximity to green space and perceptions of walkability were linked to frequent outdoor use of green space, which was associated with multiple benefits for well-being (Zuniga-Teran et al., 2019). With respect to safety in accessing parks, Kaczynski, Koohsari, Stanis, Bergstrom, and Sugiyama (2014) found that greater intersection density and lower traffic speeds on routes to nearby parks were related to increased park use among adults. These findings support the utility of further research examining how park access may interact with other neighborhood characteristics, such as walkability, in their effect on mental health outcomes (Pellizzari, Hesam Shariati, & Kaczynski, 2025).

Social vulnerability significantly influences access to and usage of community resources (e.g., parks, walkable neighborhoods) as well as overall health and well-being (Hallum et al., 2024). Social vulnerability is described as a threat to communities caused by negative outcomes related to environmental, economic, and social challenges (Felton et al., 2022). It encompasses several factors, including socioeconomic status, household characteristics, racial and ethnic minority status, and housing type (CDC/ATSDR, 2024). Different levels of social vulnerability are often exacerbated by scarce resources and a lack of support systems (Burton, Rufat, & Tate, 2018) and put vulnerable groups at greater risk. Indeed, prior research has shown that those with high social vulnerability are 70% more likely to experience moderate or high levels of depressive symptoms than those with low vulnerability (Yamaguchi, Kawata, Murofushi, & Ota, 2022). Another study showed that the relationship between green space and depression is complex and depends on many factors, including the societal and sociodemographic characteristics of surrounding neighborhoods (Fossa, 2023). In this context, parks and green spaces can be considered valuable resources to mitigate the adverse impacts of social vulnerability (e.g., Shepley, Sachs, Sadatsafavi, Fournier, & Peditto, 2019). Taken together, these findings highlight the importance of accounting for social vulnerability as a control variable, alongside park availability and other environmental factors, when examining mental health outcomes.

To advance the literature on the mental health benefits of parks, the purpose of the present study was to examine the effect of park availability on mental distress rates using data on census tracts in South Carolina (SC). Specifically, we examined (1) the relationship between the number of parks/green spaces per 10,000 residents and rates of mental distress in a census tract and (2) the potential moderating role of walkability in the relationship between the number of parks/green spaces and mental distress. In doing so, this research has the potential to clarify mixed findings in prior literature (Astell-Burt, Mitchell, & Hartig, 2014; Sturm & Cohen, 2014; Derose, Wallace, Han, & Cohen, 2021). In addition, only limited research has examined the relationship between parks and mental distress, such as depression, stress, and problems with emotions, while considering the moderating effect of neighborhood walkability. Specifically, most of these studies have examined particular components of walkability (e.g., safety) instead of considering a more comprehensive walkability index (e.g., Juul & Nordbø, 2023). Considering neighborhood walkability as a moderator is essential in that it shapes how individuals access and use parks, thereby influencing the strength of the association between park availability and mental distress.

Methods

Study setting and measures

Study setting

This study utilized data from census tracts in SC in the United States. SC had a total population of approximately 4.6 million people and contained 1,103 census tracts as of 2019. Of the 1,103 census tracts in SC, 1,089 with complete data for all variables were included in the final analytic sample.

Park availability

Park availability was assessed based on the number of parks within each census tract and then expressed as a per capita figure per 10,000 residents. Parks across SC were identified using the OutScraper Application Programming Interface (OutSraper, 2024), which has been used successfully in past studies about parks (Yang et al., 2024; Yang, Mu, & Grigsby-Toussaint, 2025). Using OutScraper, we extracted all park-related Points of Interest (POIs) from Google Maps, including parks, playgrounds, and recreational green spaces. Each POI included latitude and longitude coordinates that were geocoded and spatially joined to census tract boundaries using ArcGIS Pro Version 3.5 (ESRI, 2025). This allowed each POI to be allocated to a specific tract. Duplicate POIs representing the same park were manually removed during data cleaning.

Mental health

Mental health was assessed as the rate of mental distress in each census tract. Rates were obtained from the CDC PLACES data source (CDC PLACES, 2019). The CDC PLACES program employs advanced statistical techniques, specifically small area estimation and multilevel regression with poststratification, to generate detailed geographic estimates of health outcomes and behaviors for adults 18 years old and older. This approach combines geocoded health surveys, comprehensive data from the CDC’s Behavioral Risk Factor Surveillance System, 5-year estimates from the American Community Survey, and state- and county-level random effects to obtain health metric values at the tract level. Specifically, mental distress was measured as the percentage of adults aged ≥18 years in each census tract who reported that their mental health (i.e., stress, depression, and problems with emotions) was not good for 14 or more days during the past 30 days (CDC & Mental distress, 2024).

Neighborhood walkability

The walkability of each census tract was assessed using the Environmental Protection Agency National Walkability Index (NWI; US EPA & O, 2021). The NWI consists of three built environment metrics—street intersection density, proximity to transit stops, and land use diversity—that affect whether people walk as a mode of transportation (Ewing & Cervero, 2010). These metrics were measured using variables in the Smart Location Database (US EPA & O, 2014), which has nationwide data availability and consistency at the block group level. Specifically, the NWI assigns census block groups a score from 1 (least walkable) to 20 (most walkable). The walkability of all block groups within each census tract in SC was averaged to obtain an overall walkability score.

Social vulnerability

The social vulnerability of each census tract was assessed using the CDC Social Vulnerability Index (SVI; CDC/ATSDR SVI, 2024). The SVI is a tool for identifying and quantifying vulnerable communities’ social needs during public health emergencies. Within the SVI, census tracts are ranked according to four themes—socioeconomic status, household characteristics, race and ethnicity, and housing type—which each contain multiple subfactors. All variables have possible continuous scores ranging from 0 (lowest vulnerability) to 1 (highest vulnerability). Variables within each theme were averaged, then scores across the four themes were averaged to create an overall social vulnerability score for each census tract.

Population

Residential stability, population density, and age were also included as control variables. Residential stability, as a proxy for population movement within a census tract, was assessed based on the percentage of residents who reported living in the same house over the past year, obtained from the US Census Bureau’s American Community Survey 5-year estimates. Population density, the number of residents per square kilometer in each census tract, was calculated by dividing the total population by the land area of the tract (US Census Bureau & U.C, 2019). Finally, age, the percentage of the population that was above 18 years old for each tract, was obtained from the US Census Bureau’s American Community Survey 5-year estimates (US Census Bureau & U.C, 2019).

Analyses

Stata 18 SE software was used for all statistical analyses (StataCorp, 2023). Ordinary Least Squares regression models were employed to examine relationships between the number of parks per 10,000 residents and rates of mental distress across census tracts in SC. The models included an interaction term between park availability and walkability to explore potential moderation. All models controlled for census tract-level covariates, including overall social vulnerability, percentage of residents living in the same house in the past year, population density (per km²), and proportion of the population aged 18 or above. Continuous predictors were mean-centered prior to modeling. To graphically probe the significant interaction, predicted levels of mental distress were plotted at low, medium, and high walkability values (±1 SD from the mean). The coefficients reported are unstandardized regression coefficients (b). A p value and 95% confidence interval were calculated to assess statistical significance.

Results

Descriptive statistics for all variables are shown in Table 1. On average, census tracts had 4.27 parks per 10,000 residents (SD = 7.49), with substantial variation in park availability (range: 0–123.18). The mean neighborhood walkability for all included tracts in SC (M = 6.89, SD = 3.33) fell in the category of “below average walkable” (5.76–10.50). Across all census tracts in the study, an average of 17.79% (SD = 3.21) of individuals reported experiencing mental distress for more than 14 days over the past month. Table 2 displays the Pearson correlation coefficients (r) among focal variables. Results showed that higher park availability was associated with lower rates of mental distress (r = −0.07, p < 0.05) and higher neighborhood walkability (r = 0.14, p < 0.001). Similarly, mental distress was positively but not significantly related to neighborhood walkability (r = 0.05, p = 0.114) and was positively and significantly associated with social vulnerability (r = 0.66, p < 0.001).

Table 1.

Descriptive Statistics of Census Tract-Level Variables in South Carolina in 2019 (N = 1,089)

TRACTS’ CHARACTERISTIC	MEAN	SD	MEDIAN	MIN	MAX
Mental distress (%)	17.79	3.21	17.9	8.5	36.4
Parks per 10,000 residents	4.27	7.49	2.33	0.00	123.18
Neighborhoods walkability	6.89	3.32	6.19	1.00	18.70
Overall social vulnerability	0.50	0.28	0.50	0.01	0.99
Total population	4,557.17	2,436.41	4,127	152	29,083
Living in same house in the past year (%)	85.71	9.14	87.40	0.47	99.64
Age 18 or above (%)	78.63	6.09	78.00	61.80	100
Population density per km²	444.49	571.75	242.65	2.81	5,653.79

Table 2.

Correlations Between Focal Independent and Dependent Variables (N = 1,089)

VARIABLES	1	2	3	4
1. Parks per 10,000 residents	—	0.14^***	−0.08^**	−0.07^*
2. Neighborhood walkability	—	—	−0.04	0.05
3. Social vulnerability	—	—	—	0.66^***
4. Mental distress	—	—	—	—

p < 0.05, ^**p < 0.01, ^***p < 0.001.

Table 3 illustrates the results of multivariate models predicting mental distress based on the number of parks per 10,000 residents, adjusting for control variables. Results show that greater park availability was significantly associated with lower mental distress (b = −0.05, p < 0.05). Specifically, for each additional park per 10,000 residents in a census tract, the predicted mental distress rate decreased by 0.05 percentage points. The interaction term between the number of parks per 10,000 residents and neighborhood walkability revealed a significant interaction effect (b = 0.004, p < 0.05), indicating that the relationship between park availability and mental distress varied depending on the level of neighborhood walkability. Specifically, as illustrated in Figure 1, simple slopes analyses revealed significant negative effects of park availability at low levels of walkability (b = −0.02, p < 0.05). This suggests that in less walkable neighborhoods, a higher number of parks was associated with lower mental distress rates. Also, a negative but nonsignificant association between park availability and mental distress was observed in neighborhoods with medium levels of walkability. Finally, at high levels of walkability, there was no significant relationship between park availability and mental distress rates (b = 0.00, p = 0.878).

Fig. 1.

Relationship between the number of parks and mental distress at different levels of neighborhood walkability. *Low neighborhood walkability has significant simple slope.

Table 3.

Ordinary Least Squares Regression Between Park Availability and Mental Distress across Census Tracts in South Carolina (N = 1,089)

	COEFFICIENT	SE	T	p	[95% CONF. INTERVAL]
Parks per 10,000 residents	−0.05	0.02	−2.33	0.02	−0.0986	−0.0085
Neighborhood walkability	−0.23	0.03	−6.75	0.000	−0.2989	−0.1642
Overall social vulnerability	7.53	0.24	31.75	0.000	7.0636	7.9941
Living in same house in the past year (%)	−12.49	0.84	−14.92	0.000	−14.1377	−10.8519
Age 18 or above (%)	−0.01	0.01	−1.15	0.252	−0.0370	−0.0097
Population density	0.00	0.00	6.13	0.000	0.0006	0.0013
Number of parks × neighborhood walkability	0.004	0.00	2.04	0.041	0.0001	0.0076
_Cons	28.02	1.39	20.16	0.000	25.2912	30.7440

Discussion

This study investigated the relationship between park availability and mental distress across a large geographic area, with a particular focus on how this relationship is moderated by neighborhood walkability. Overall, we found a significant negative association between park availability and mental distress across census tracts in SC, demonstrating a robust relationship between these two variables above and beyond the effects of sociodemographic characteristics, social vulnerability, and neighborhood walkability. Studying the relationship between parks and mental distress, such as stress, depression, and problems with emotions, is essential because parks play a protective role in mental health through multiple pathways, such as physical activity, social engagement, and exposure to greenery (Gascon et al., 2015; Chen, Zhang, Liu, Zhang, & Song, 2021; White et al., 2021). By accounting for sociodemographic characteristics and social vulnerability as covariates, this research sought to isolate the unique contributions of parks as a protective factor against mental distress and how variations in walkability levels influence this association.

Our findings are consistent with prior research examining the association between park availability and mental distress (Reklaitiene et al., 2014; Sturm & Cohen, 2014; Min, Kim, Kim, & Min, 2017; Fossa, 2023). Our results also advance this line of research by showing that the benefits of park availability for mental distress are not uniform across neighborhoods, emphasizing a significant moderating effect of neighborhood walkability. This nuanced finding both supports and extends the conceptual framework proposed by Zumelzu and Herrmann-Lunecke (2021), which positions parks as vehicles for health promotion but now invites further consideration of elements of the built environment that have the potential to enhance people’s overall well-being. Specifically, we found that park availability significantly reduced mental distress percentage in neighborhoods with low walkability, suggesting that parks can provide a crucial source of physical activity, social interaction, and restorative experiences in such environments (Foderaro & Klein, 2023). Turning vacant lots into green spaces where people can pause, interact, and have meaningful experiences, in the absence of high-quality sidewalks or walkable neighborhoods, contributes substantially to promoting their overall mental health status (South, Hohl, Kondo, MacDonald, & Branas, 2018; Callaghan et al., 2021). The effect of park availability was not significant in medium- and highly walkable neighborhoods. This finding is logical since medium to highly walkable neighborhoods may already provide sufficient opportunities for physical activity and social interaction (Zhu et al., 2013; Zhu, Yu, Lee, & Lu, 2023), diminishing the additional benefits that park availability could offer for mental distress symptoms. In addition, in these areas, other green spaces, such as private gardens or green streetscapes, may already serve similar functions and make park availability less impactful. Furthermore, in highly walkable neighborhoods, other factors, such as access to various services, street connectivity, and perceived safety, might also play a more critical role in influencing mental health issues (Siqueira Junior et al., 2022).

The findings of this study have important implications for public health experts and urban designers. First, the presence of parks is an important factor in promoting community well-being. According to a framework proposed by Bedimo-Rung, Mowen, and Cohen (2005), parks have substantial physical and psychological benefits, as they provide the community with opportunities for physical activity (Kaczynski & Henderson, 2008) and social interaction (Mowen & Rung, 2016), thereby mitigating mental distress symptoms (Fossa, D’Souza, Bergmans, Zivin, & Adar, 2024; Samsudin, Bailey, Ries, Hashim, & Fernandez, 2024). Thus, equitable access to parks should be considered when developing policies and programs aimed at improving healthy neighborhoods (Hallum et al., 2024; Pellizzari et al., 2025). Second, based on our findings, emphasis needs to be placed within environmental planning and strategies in low-walkable neighborhoods, where an increase in the presence of parks significantly contributes to lower rates of mental distress. Therefore, creating greater park access or availability in such neighborhoods may be a valuable urban design intervention, particularly in areas lacking other supportive features of walkability, such as street connectivity or land use mix. Indeed, acquiring private land and repurposing it—or designating portions of existing public land—for park development appears to be a more practical and cost-effective strategy compared with the substantial investment and systemic changes required to enhance neighborhood walkability infrastructure. In doing so, urban designers can help offset some of the mental health disadvantages that lower walkable communities face with respect to daily active transportation and safe pedestrian infrastructure.

Limitations and strengths

Several study limitations should be acknowledged. First, we only considered the availability of parks and did not investigate their quality. While it has been well documented that the quality and proximity of parks within neighborhoods are as important as their availability (Kaczynski, Potwarka, & Saelens, 2008), this study prioritized the sample size over measuring quality (which would necessitate a smaller sample). Also, the number of parks within a census tract was tabulated, but proximity to parks within a smaller boundary (e.g., block groups, zip codes) was not examined. Studies have shown that proximity to parks may contribute to increased park use and decrease mental distress (Sturm & Cohen, 2014; Orstad, Szuhany, Tamura, Thorpe, & Jay, 2020), making this factor a vital consideration. Furthermore, this study used secondary self-reported survey data on mental distress at the tract level. This may not fully capture the experiences of certain populations who often face barriers to health care access and diagnosis, thereby potentially underestimating the prevalence of mental distress in these groups. This study also had multiple strengths, including being among the first to examine the moderating effect of walkability on the relationship between park availability and mental health issues. Furthermore, social vulnerability was included as a primary control variable, offering a broader context on neighborhood factors that might affect mental distress and addressing potential confounding. Finally, this study used an approach to collecting data on the availability of parks across a large study setting (i.e., 1,089 census tracts throughout SC) without need for extensive skills such as machine learning, which is often a barrier for researchers conducting environmental and ecological research (Dietterich, 2009).

Conclusion

This study demonstrated that neighborhoods with low walkability have significantly lower mental distress rates when more parks are present. The benefits of parks on mental health appear to diminish in medium and highly walkable areas where other factors, such as connectivity and access to services, likely play more significant roles. These findings emphasize the importance of considering both environmental attributes and social context when designing public health interventions and urban design policies to mitigate mental distress and address the growing epidemic of poor mental health in the United States.

Footnotes

Author Disclosure Statement

The authors declare that they have no competing interests.

Funding Information

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

References

Anderson

, & Durstine

J. L

. (2019). Physical activity, exercise, and chronic diseases: A brief review. Sports Medicine and Health Science, 1, 3–10.

Astell-Burt

, Mitchell

, & Hartig

. (2014). The association between green space and mental health varies across the lifecourse. A longitudinal study. Journal of Epidemiology and Community Health, 68, 578–583.

Bedimo-Rung

A. L.

, Mowen

A. J.

, & Cohen

D. A

. (2005). The significance of parks to physical activity and public health: A conceptual model. American Journal of Preventive Medicine, 28, 159–168.

Berke

E. M.

, Koepsell

T. D.

, Moudon

A. V.

, Hoskins

R. E.

, & Larson

E. B

. (2007). Association of the Built Environment With Physical Activity and Obesity in Older Persons. American Journal of Public Health, 97, 486–492; doi: 10.2105/AJPH.2006.085837

Besenyi

G. M.

, Kaczynski

A. T.

, Stanis

S. A. W.

, Bergstrom

R. D.

, Lightner

J. S.

, & Hipp

J. A

. (2014). Planning for health: A community-based spatial analysis of park availability and chronic disease across the lifespan. Health & Place, 27, 102–105; doi: 10.1016/j.healthplace.2014.02.005

Burton

, Rufat

, & Tate

. (2018). “Social vulnerability,” Vulnerability and resilience to natural hazards, 53. Available from: https://books.google.com/books?hl=en&lr=&id=fgRNDwAAQBAJ&oi=fnd&pg=PA53&dq=The+concept+of+social+vulnerability+refers+to+the+risk+that+communities+face+as+a+result+of+the+negative+outcomes+that+may+result+from+environmental,+economic,+and+social+challenges.+&ots=CDuNf-CC2N&sig=W1XPXTZwdM4OqTo-0ZtWmtn-bKk [Last accessed: August 18, 2024].

Bustamante

, Guzman

, Kobayashi

L. C.

, & Finlay

. (2022). Mental health and well-being in times of COVID-19: A mixed-methods study of the role of neighborhood parks, outdoor spaces, and nature among US older adults. Health & Place, 76, 102813.

Callaghan

, McCombe

, Harrold

, McMeel

, Mills

, … Moore-Cherry

. (2021). The impact of green spaces on mental health in urban settings: A scoping review. Journal of Mental Health (Abingdon, England), 30, 179–193; doi: 10.1080/09638237.2020.1755027

CDC PLACES. (2019) CDC PLACES.

10.

CDC, Mental distress. (2024). Health Outcomes Measure Definitions, Centers for Disease Control and Prevention. Available from: https://www.cdc.gov/places/measure-definitions/health-status.html [Last accessed: September 27, 2024].

11.

CDC. (2025). Protecting the Nation’s Mental Health, Mental Health. Available from: https://www.cdc.gov/mental-health/about/what-cdc-is-doing.html [Last accessed: May 21, 2025].

12.

CDC/ATSDR SVI. (2024). CDC/ATSDR Social Vulnerability Index (CDC/ATSDR SVI). Available from: https://www.atsdr.cdc.gov/placeandhealth/svi/index.html [Last accessed: September 27, 2024].

13.

CDC/ATSDR. (2024). Social Vulnerability Index. Available from: https://hazards.fema.gov/nri/social-vulnerability [Last accessed: August 18, 2024].

14.

Chen

, Zhang

, Liu

, Zhang

, & Song

. (2021). How does urban green space impact residents’ mental health: A literature review of mediators. International Journal of Environmental Research and Public Health, 18, 11746.

15.

Derose

K. P.

, Wallace

D. D.

, Han

, & Cohen

D. A

. (2021). Effects of park-based interventions on health-related outcomes: A systematic review. Preventive Medicine, 147, 106528.

16.

Dietterich

T. G

. (2009) “Machine learning and ecosystem informatics: Challenges and opportunities,” In Zhou

Z.-H

and Washio

(eds.) Advances in Machine Learning. (Lecture Notes in Computer Science), (pp. 1–5) Berlin, Heidelberg: Springer Berlin Heidelberg; doi: 10.1007/978-3-642-05224-8_1

17.

ESRI. (2025). Desktop GIS Software | Mapping Analytics | ArcGIS Pro. Available from: https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview [Last accessed: May 21, 2025].

18.

Ewing

, & Cervero

. (2010). Travel and the built environment: A meta-analysis. Journal of the American Planning Association, 76, 265–294; doi: 10.1080/01944361003766766

19.

Felton

J. W.

, Rabinowitz

J. A.

, Strickland

J. C.

, Maher

B. S.

, Summers

, … Key

. (2022). Social vulnerability, COVID-19 impact, and decision making among adults in a low-resource community. Behavioural Processes, 200, 104668.

20.

Foderaro

L. W.

, & Klein

. (2023). “The Power of Parks to Promote Health,”. Trust for Public Land. Available from: https://www.tpl.org/parks-promote-health-report [Last accessed: May 5, 2025].

21.

Fossa

A. J.

, D’Souza

, Bergmans

R. S.

, Zivin

, & Adar

S. D

. (2024). Different types of greenspace within urban parks and depressive symptoms among older US adults living in urban areas. Environment International, 192, 109016.

22.

Fossa

. (2023. Depression, Equity, and Greenspace in Parks and Residential Areas. PhD Thesis. Available from: https://deepblue.lib.umich.edu/handle/2027.42/178043 [Last accessed: November 15, 2024].

23.

Gascon

, Triguero-Mas

, Martínez

, Dadvand

, Forns

, … Plasència

M. J

. (2015). Mental health benefits of long-term exposure to residential green and blue spaces: A systematic review. International Journal of Environmental Research and Public Health, 12, 4354–4379.

24.

Gerlach-Spriggs

, Kaufman

R. E.

, & Warner

S. B

. (1998. Restorative gardens: The healing landscape. Yale University Press. Available from: https://books.google.com/books?hl=en&lr=&id=whmUs-VhdxsC&oi=fnd&pg=PP11&dq=Gerlach-Spriggs,+N.,+Kaufman,+R.+E.,+%26+Warner,+S.+B.+(1998).+Restorative+gardens:+The+healing+landscape.+Yale+University+Press.&ots=_1AdswCiOs&sig=K0GLKuzxOxUM6-RBNHzdHvgojng [Last accessed: November 15, 2024].

25.

Hallum

S. H.

, Wende

M. E.

, Hesam Shariati

, Thomas

K. M.

, Chupak

A. L.

, … Witherspoon

A. T

. (2024). Unearthing inequities in the relationship between multiple sociodemographic factors and diverse elements of park availability and quality in a major Southern Metropolitan Region. International Journal of Environmental Research and Public Health, 21, 204.

26.

James

, Hart

J. E.

, Banay

R. F.

, & Laden

. (2016). Exposure to greenness and mortality in a nationwide prospective cohort study of women. Environmental Health Perspectives, 124, 1344–1352; doi: 10.1289/ehp.1510363

27.

Juul

, & Nordbø

E. C. A

. (2023). Examining activity-friendly neighborhoods in the Norwegian context: Green space and walkability in relation to physical activity and the moderating role of perceived safety. BMC Public Health, 23, 259; doi: 10.1186/s12889-023-15170-4

28.

Kaczynski

A. T.

, & Glover

T. D

. (2012). Talking the talk, walking the walk: Examining the effect of neighbourhood walkability and social connectedness on physical activity. Journal of Public Health (Oxford, England), 34, 382–389.

29.

Kaczynski

A. T.

, & Henderson

K. A

. (2008). Parks and recreation settings and active living: A review of associations with physical activity function and intensity. Journal of Physical Activity & Health, 5, 619–632.

30.

Kaczynski

A. T.

, Koohsari

M. J.

, Stanis

S. A. W.

, Bergstrom

, & Sugiyama

. (2014). Association of street connectivity and road traffic speed with park usage and park-based physical activity. American Journal of Health Promotion: AJHP, 28, 197–203.

31.

Kaczynski

A. T.

, Potwarka

L. R.

, & Saelens

B. E

. (2008). Association of park size, distance, and features with physical activity in neighborhood parks. American Journal of Public Health, 98, 1451–1456; doi: 10.2105/AJPH.2007.129064

32.

Kaplan

. (1995). The restorative benefits of nature: Toward an integrative framework. Journal of Environmental Psychology, 15, 169–182.

33.

Kim

S. J.

, Blesoff

J. R.

, Tussing-Humphrys

, Fitzgibbon

M. L.

, & Peterson

C. E

. (2023). The association between neighborhood conditions and weight loss among older adults living in a large urban city. Journal of Behavioral Medicine, 46, 882–889; doi: 10.1007/s10865-023-00410-0

34.

Lee

, Wang

, Carlson

S. A.

, Greenlund

K. J.

, Lu

, … Liu

C. W

. (2023). National, state-level, and county-level prevalence estimates of adults aged ≥18 years self-reporting a lifetime diagnosis of depression—United States, 2020. MMWR. Morbidity and Mortality Weekly Report, 72, 644–650; doi: 10.15585/mmwr.mm7224a1

35.

Leslie

, Coffee

, Frank

, Owen

, Bauman

, & Hugo

. (2007). Walkability of local communities: Using geographic information systems to objectively assess relevant environmental attributes. Health & Place, 13, 111–122.

36.

Liu

, Chen

, Cui

, Ma

, Gao

, … Li

. (2023). Green space exposure on depression and anxiety outcomes: A meta-analysis. Environmental Research, 231, 116303.

37.

Lovasi

G. S.

, Grady

, & Rundle

. (2012). Steps forward: Review and recommendations for research on walkability, physical activity and cardiovascular health. Public Health Reviews, 33, 484–506; doi: 10.1007/BF03391647

38.

Mathis

A. L.

, Rooks

R. N.

, Tawk

R. H.

, & Kruger

D. J

. (2017). Neighborhood influences and BMI in urban older adults. Journal of Applied Gerontology: The Official Journal of the Southern Gerontological Society, 36, 692–708; doi: 10.1177/0733464815584670

39.

McCormack

G. R.

, Spence

J. C.

, McHugh

T.-L.

, & Mummery

W. K

. (2022). The effect of neighborhood walkability on changes in physical activity and sedentary behavior during a 12-week pedometer-facilitated intervention. PloS One, 17, e0278596; doi: 10.1371/journal.pone.0278596

40.

Mental Health-CDC, M.H.-R.E.D.V. (2025). Mental Health. Available from: https://www.cdc.gov/mental-health/about-data/emergency-department-visits.html

41.

Min

K.-B.

, Kim

H.-J.

, Kim

H.-J.

, & Min

J.-Y

. (2017). Parks and green areas and the risk for depression and suicidal indicators. International Journal of Public Health, 62, 647–656; doi: 10.1007/s00038-017-0958-5

42.

Mowen

A. J.

, & Rung

A. L

. (2016). Park-based social capital: Are there variations across visitors with different socio-demographic characteristics and behaviours? Leisure/Loisir, 40, 297–324; doi: 10.1080/14927713.2016.1253178

43.

Orstad

S. L.

, Szuhany

, Tamura

, Thorpe

L. E.

, & Jay

. (2020). Park proximity and use for physical activity among urban residents: Associations with mental health. International Journal of Environmental Research and Public Health, 17, 4885.

44.

OutSraper. (2024). Outscraper. Available from: https://outscraper.com/ [Last accessed: September 6, 2024].

45.

Pellizzari

, Hesam Shariati

, & Kaczynski

A. T

. (2025). The relationship between park access and quality and various health metrics in a Metropolitan Area in South Carolina Using the CDC PLACES Dataset. Journal of Preventive Medicine and Public Health = Yebang Uihakhoe Chi, 58, 208–217.

46.

Reklaitiene

, Grazuleviciene

, Dedele

, Virviciute

, Vensloviene

, … Tamosiunas

M. J

. (2014). The relationship of green space, depressive symptoms and perceived general health in urban population. Scandinavian Journal of Public Health, 42, 669–676; doi: 10.1177/1403494814544494

47.

Roe

, Mondschein

, Neale

, Barnes

, Boukhechba

, & Lopez

. (2020). The urban built environment, walking and mental health outcomes among older adults: A pilot study. Frontiers in Public Health, 8, 575946.

48.

Rundle

A. G.

, Neckerman

K. M.

, Judd

S. E.

, Colabianchi

, Moore

K. A.

, … Quinn

J. W.

G. S

. (2023). Cumulative experience of neighborhood walkability and change in weight and waist circumference in REGARDS. American Journal of Epidemiology, 192, 1960–1970.

49.

Samsudin

, Bailey

R. P.

, Ries

, Hashim

S. N. A. B.

, & Fernandez

J. A

. (2024). Assessing the impact of physical activity on reducing depressive symptoms: A rapid review. BMC Sports Science, Medicine & Rehabilitation, 16, 107; doi: 10.1186/s13102-024-00895-5

50.

Shepley

, Sachs

, Sadatsafavi

, Fournier

, & Peditto

. (2019). The impact of green space on violent crime in urban environments: An evidence synthesis. International Journal of Environmental Research and Public Health, 16, 5119.

51.

Siqueira Junior

J. D A.

, Lopes

A. A. D. S.

, Godtsfriedt

C. E. S.

, Justina

M. D. D.

, de Paiva

K. M.

, … d’Orsi

C. R

. (2022). Neighbourhood walkability and mental health in older adults: A cross-sectional analysis from EpiFloripa Aging Study. Frontiers in Aging, 3, 915292.

52.

South

E. C.

, Hohl

B. C.

, Kondo

M. C.

, MacDonald

J. M.

, & Branas

C. C

. (2018). Effect of greening vacant land on mental health of community-dwelling adults: A cluster randomized trial. JAMA Network Open, 1, e180298–e180298.

53.

StataCorp. (2023). “Stata Statistical Software: Release 18. College Station, TX: StataCorp LLC.” Available from: https://www.stata.com/support/faqs/resources/citing-software-documentation-faqs/

54.

Sturm

, & Cohen

. (2014). Proximity to urban parks and mental health. The Journal of Mental Health Policy and Economics, 17, 19.

55.

Taylor

, Leckey

E. H.

, Lead

P. J.

, & Hochuli

D. F

. (2020). What visitors want from urban parks: Diversity, utility, serendipity. Frontiers in Environmental Science, 8, 595620.

56.

Thomas

K. M.

, Hesam Shariati

, Hallum

S. H.

, & Kaczynski

A. T

. (2025). Examining the relationship between social vulnerability and sidewalk access and walkability across a large Southeastern US City. Environmental Justice.

57.

Ulrich

R. S

. (2023). “Stress reduction theory,” Marchand

, Pol

., & Weiss

(eds.), 100 Key Concepts in Environmental Psychology. (pp. 143–146) Routledge.

58.

US Census Bureau, U.C. (2019). 2019 National and State Population Estimates, Census.gov. Available from: https://www.census.gov/newsroom/press-kits/2019/national-state-estimates.html [Last accessed: April 30, 2025].

59.

US EPA, O. (2014). Smart Location Mapping. Available from: https://www.epa.gov/smartgrowth/smart-location-mapping [Last accessed: November 30, 2022].

60.

US EPA, O. (2021). National Walkability Index User Guide and Methodology. Available from: https://www.epa.gov/smartgrowth/national-walkability-index-user-guide-and-methodology [Last accessed: August 18, 2024].

61.

Van Cauwenberg

, Van Holle

, De Bourdeaudhuij

, Van Dyck

, & Deforche

. (2016). Neighborhood walkability and health outcomes among older adults: The mediating role of physical activity. Health & Place, 37, 16–25.

62.

Van Holle

, Van Cauwenberg

, Gheysen

, Van Dyck

, Deforche

, … Van de Weghe

. (2016). The association between Belgian older adults’ physical functioning and physical activity: What is the moderating role of the physical environment? PloS One, 11, e0148398.

63.

Wang

M. L.

, Narcisse

, & McElfish

P. A

. (2023). Higher walkability associated with increased physical activity and reduced obesity among United States adults. Obesity (Silver Spring, Md.), 31, 553–564; doi: 10.1002/oby.23634

64.

White

M. P.

, Elliott

L. R.

, Grellier

, Economou

, Bell

, … Bratman

G. N.

L. E

. (2021). Associations between green/blue spaces and mental health across 18 countries. Scientific Reports, 11, 8903.

65.

Yamaguchi

, Kawata

, Murofushi

, & Ota

. (2022). The influence of vulnerability on depression among Japanese university athletes. Frontiers in Sports and Active Living, 4, 1003342.

66.

Yang

, Cheng

, Yang

, Cai

, Li

, & Yang

. (2024). Unveiling disparities: A social media analysis of urban park usage and sentiments in Oklahoma City. GeoJournal, 89, 173.

67.

Yang

, Mu

, & Grigsby-Toussaint

D. S

. (2025). Public perceptions and expectations of urban park environments on children’s play: A GIS and text mining analysis on children’s activity in Atlanta’s parks using social media data. Environment and Planning B: Urban Analytics and City Science, 52, 412–429; doi: 10.1177/23998083241260484

68.

Zhu

, et al. (2013). Walkable communities: Impacts on residents’ physical and social health: Researchers from Texas A&M University studied residents in a newly developed ‘walkable community’in Austin, Texas to see how it changed their habits for physical activity and whether it increased social interaction and cohesion in the community. World Health Design, 6, 68.

69.

Zhu

, Yu

C.-Y.

, Lee

, & Lu

. (2023). From walkable communities to active lifestyles: Exploring causal pathways through a case study in Austin, Texas. Journal of Planning Education and Research, 43, 538–549; doi: 10.1177/0739456X19900528

70.

Zumelzu

, & Herrmann-Lunecke

M. G

. (2021). Mental well-being and the influence of place: Conceptual approaches for the built environment for planning healthy and walkable cities. Sustainability, 13, 6395.

71.

Zuniga-Teran

A. A.

, Orr

B. J.

, Gimblett

R. H.

, Chalfoun

N. V.

, Guertin

D. P.

, & Marsh

S. E

. (2017). Neighborhood design, physical activity, and wellbeing: Applying the walkability model. International Journal of Environmental Research and Public Health, 14, 76.

72.

Zuniga-Teran

A. A.

, Stoker

, Gimblett

R. H.

, Orr

B. J.

, Marsh

S. E.

, … Guertin

D. P.

N. V

. (2019). Exploring the influence of neighborhood walkability on the frequency of use of greenspace. Landscape and Urban Planning, 190, 103609.