Parks are critical components of healthy communities. This study explored neighborhood socioeconomic and racial/ethnic inequalities in park access and quality in a large U.S. southeastern metropolitan region. A total of 241 block groups were examined, including 77 parks. For each block group, we obtained multiple sociodemographic indicators, including unemployment rate, education level, renter-occupied housing, poverty rate, and racial/ethnic minority composition. All parks were mapped using geographical information systems and audited via the Community Park Audit Tool to evaluate their features and quality. We analyzed seven diverse elements of park quality (transportation access, facility availability, facility quality, amenity availability, park aesthetics, park quality concerns, and neighborhood quality concerns), as well as an overall park quality score by calculating the mean for all parks within each block group. The mean percent of residents below 125% of the poverty level and the percentage of renter-occupied housing units were significantly higher among block groups with any parks in comparison to block groups with no parks. In addition, there were significant positive associations between park transportation access scores and both the percentage of residents with less than high school education and the percent identifying as non-Hispanic white. Moreover, there was a significant negative association between park amenity availability and the block group’s unemployed population. Further, a significant negative association between park aesthetics and the population with a lower than high school education percentage was observed. Revealed differences in park availability, park acreage, and park quality dimensions emphasized the need for targeted policy, programmatic, and infrastructure interventions to improve park access and quality and address health disparities.

Objectives: Limited access to high-quality green spaces could contribute to growing rates of chronic diseases and unhealthy behaviors. Public parks provide numerous benefits for population well-being. However, past research has shown mixed results regarding the association between proximal parks and residents’ physical and mental health. This study examined the relationship between diverse elements of park access and quality and multiple health outcomes.Methods: Seventy-three unique parks within 70 census tracts in 4 cities in South Carolina were analyzed. Data about 7 aspects of park quality (transportation access, facility availability, facility quality, amenity availability, park aesthetics, park quality concerns, neighborhood quality concerns) were collected via on-site observations using the Community Park Audit Tool. Health data for each tract (obesity, no leisure time physical activity, high blood pressure, coronary heart disease, high cholesterol, diabetes, depression, poor mental health) were collected from the CDC PLACES dataset. Linear regression analyses examined the association between 10 park access and quality metrics and 8 health metrics, controlling for socio-demographic characteristics.Results: All associations were in the unexpected direction except 1 relationship involving mental health. Specifically, positive associations were found between the number of parks and obesity, the number of parks and no leisure time physical activity, transportation access and obesity, and transportation access and high blood pressure. As concerns about neighborhood quality increased, poor mental health status worsened.Conclusions: This study provides valuable information for public health professionals and researchers. Further research is needed to expand on and elucidate these findings.

Little research has considered associations between walkability and multiple health outcomes and the moderating effect of social determinants of health. This study examined relationships between walkability and diverse health issues (depression, poor mental health, poor physical health, mobility disability, obesity) and no leisure-time physical activity and whether these relationships were moderated by social vulnerability. Then, we assessed whether these moderated effects varied between urbanicity. For 1089 census tracts in South Carolina, we compiled EPA National Walkability Index, 6 health metrics from the CDC-PLACES dataset, and the CDC Social Vulnerability Index. Multilevel regression models were employed to account for the nested structure of the data, with census tracts (level 1) nested within counties (level 2). Overall, tract walkability was significantly negatively associated with poor mental health, poor physical health, obesity, and no leisure-time physical activity. The interaction between National Walkability Index and Social Vulnerability Index suggested that the relationship between health metrics and walkability varied depending on the level of social vulnerability in the community. In addition, tract rural or urban classification significantly affected the relationship between walkability and some health metrics. This study’s findings provide valuable insights for equitable urban planning and strategies to address walkability and public health issues.

Background: Physical activity (PA) levels and health frequently differ by sociodemographic characteristics and neighborhood features. The walkability level of neighborhoods is one of the significant reasons for such differences. Research about access to specific neighborhood walkability features according to population and community characteristics is limited and inconsistent. Methods: The purpose of this study was to examine how multiple aspects of neighborhood walkability, as measured by sidewalk access and the National Walkability Index (NWI), varied according to four themes of the Social Vulnerability Index (SVI) across census block groups ( N = 115) in Columbia, South Carolina. Linear regression models were used to analyze the relationship between overall SVI and its four themes for both sidewalk access and NWI, while controlling for block group population density. Results: Results showed that the Housing Type & Transportation theme of SVI was significantly and positively associated with both sidewalk coverage and NWI of block groups within the study setting. Other themes had a variety of positive and negative nonsignificant associations with the two outcome variables. Conclusions: These findings highlight the importance of considering social vulnerability and neighborhood characteristics, such as walkability and sidewalk access, in promoting PA and addressing disparities in chronic diseases.

Background: Environmental factors such as food access, walkability, and recreation opportunities are associated with childhood obesity risk and urban–rural obesity disparities. Although the Childhood Obesogenic Environment Index (COEI) was previously developed to characterize obesogenic environments across US counties, limited research has examined how combinations of obesogenic environment features relate to childhood overweight/obesity rates across the urban–rural continuum. The purpose of this study was to assess associations between obesogenic environments and childhood overweight/obesity rates and to develop a revised COEI composed of variables associated with childhood overweight/obesity rates. Methods: Data from 3140 US counties were analyzed using 10 environment variables associated with childhood obesity estimates. Counties were classified by Rural-Urban Continuum Codes (RUCC) and Census divisions. Regressions identified best-fit models nationally and by RUCC level, and beta coefficients from the national model were used to develop a weighted COEI. Results: The national and all rurality-stratified models were significant ( p < 0.001), although associations between individual obesogenic environment variables and childhood overweight/obesity rates varied across RUCC classifications. The revised weighted COEI demonstrated a modestly stronger association with childhood overweight/obesity rates than the original index ( r = 0.25 vs. r = 0.22) while remaining correlated with the original measure ( r = 0.80, p < 0.001). The revised COEI varied significantly by rurality and Census division ( p < 0.001), with the highest COEI scores concentrated in rural counties. Conclusions: Obesogenic environment features appear to operate differently across geographic contexts, highlighting the importance of place-based approaches to childhood obesity prevention.