Abstract
The literature on urban parks and green spaces has demonstrated that these spaces in a city can have a significant and positive impact on human health, including physical, mental, and psychological health. In fact, living near parks has been shown to reduce mortality rates in residents and significantly reduce depression and stress levels. Yet, the environmental justice literature has shown that the quality of parks (measured by a variety of variables including park size) is not evenly distributed within metropolitan areas. Lower socio-economic status (SES) neighborhoods tend to have access to poorer quality parks than residents in higher SES areas. Some researchers have even shown how health disparities in cities (across a variety of SES variables) could be partly explained by reduced access to high-quality greenspace. In this article, EJSCREEN data from the U.S. Environmental Protection Agency are merged with park data from the City of Phoenix to explore whether neighborhood parks in the City of Phoenix display these trends from the environmental justice literature. These trends are analyzed across a variety of demographic variables, including income level and percentage of under-represented residents. The results indicate that environmental justice issues are prevalent in the Phoenix metropolitan area in terms of environmental quality for neighborhood parks.
INTRODUCTION
Previous studies have demonstrated that urban green space and urban parks have a significant and positive impact on human health. 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 These benefits include boosting physical health, 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 as well as improving mental and psychological health. 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 For example, studies have shown that people who live near parks are about three times more likely to get daily exercise than people who live farther than walking distance to parks. 29 Since parks are often used by residents as places for physical activities (such as walking, jogging, and sports), living near parks is correlated with reductions in chronic disease and mortality rates. 30 , 31 , 32 Coutts et al. 33 found that mortality increases when residents lack of access to parks and green spaces.
Related to the mental and psychological health benefits of parks, Alcock et al. 34 found that residents in greener urban areas have better mental health than residents living in less green areas. Lee and Maheswaran 35 demonstrated that green spaces reduce stress for individuals. These positive mental health benefits have also been reported for symptoms of depression 36 and self-reported stress. 37 Further, the trends of improved mental health with increased access to green space are relevant for both adults and children. 38
In addition, urban parks can support the growth of vegetation, which has numerous ecological and community benefits, 39 , 40 such as the reduction in urban heat island effects, 41 opportunities for recreation, 42 and the regulation of water and air pollution. 43 Larger parks can have significant cooling effects on the local area. 44 Studies have concluded that the richness and diversity of bird species in parks is correlated with park size. 45
Yet, all residents in cities do not have equal access to high-quality parks. Some scholars have demonstrated that health disparities in cities across ethnicity and income level could be partly explained by reduced access to greenspace. 46 , 47 , 48 , 49 , 50 For example, there are correlations between poor health and low-quality parks near residences. 51 , 52
Rigolon 53 concluded that differences in park quality and size could exacerbate health issues for low income, ethnic minority young people in Denver. Scholars have argued that the physical health benefits of urban greenspace can be more important for those in low socioeconomic groups, because they might have lower baseline health and live in more polluted neighborhoods. 54
The environmental justice literature has demonstrated that city parks also tend to be higher in quality when they are located near areas with less racial diversity and higher levels of income and education. Urban park quality has been measured in a variety of ways within the literature, 55 , 56 , 57 , 58 , 59 , 60 , 61 including measurements of density of parks in a spatial area or by population, 62 measures of park size, 63 measures of park safety, 64 , 65 , 66 the presence of park amenities, 67 , 68 measures of park maintenance levels, and measures of park attractiveness. 69 , 70 , 71 Many of these studies have demonstrated inequities in park quality with lower-income and ethnic minority neighborhoods being disadvantaged. 72 , 73 , 74 , 75 , 76 , 77 , 78 For example, several studies have concluded that park acreage is higher when house prices are higher. 79 , 80 Heo et al. 81 highlight the importance of park safety when considering accessibility to high-quality urban green spaces.
Some scholars have outlined how unsafe parks can be viewed as a disadvantage for a neighborhood and this can reduce park visits. 82 In addition, park amenities have also been rated as higher quality in higher socio-economic status (SES) neighborhoods. The definitions of park amenities can vary and have included measures such as tree canopy coverage, recreational facilities (such as playgrounds and sport facilities), and aesthetics. 83 , 84 , 85
Kaczynski et al. 86 state that park amenities (as well as park availability) can be important determinants of park use among residents in neighborhoods. Further, scholars have shown that discrepancies in access to high-quality urban green spaces can limit positive social exchange and reduce park benefits for lower income groups and ethnic minorities. 87 , 88
There are also ecological benefits of urban green space. For example, parks have been suggested as one mechanism for climate change adaptation by many scholars. 89 , 90 , 91 , 92 , 93 , 94 , 95 Yet, several scholars have identified how climate change adaptation mechanisms can often have a prominent environmental justice challenge, with some adaptation methods not being equitably distributed. 96 , 97 , 98
Some studies have demonstrated that public green space is even more important for lower SES and marginalized groups. In these cases, more affluent residents often have access to large lawns and private green space, whereas lower income residents rely on public green spaces for recreation and exercise. For example, Rigolon 99 conducted a comprehensive review of existing studies to conclude that lower SES people in the United States have access to fewer parks and fewer acres of parks.
Often, these lower SES areas have fewer natural resources and lower quality parks. 100 In 2010, Talen 101 argued that parks should be distributed according to “social need,” taking into account the fact that higher density housing areas tend to have fewer (and smaller) public green spaces. Boone et al. 102 have also argued that parks should be distributed based on which groups are more likely to need and use the parks.
Even though urban green space can provide many benefits for physical and mental human health as well as ecological benefits, several studies have demonstrated the negative impacts of air pollution (and other environmental toxins) on the human brain, which can lead to negative physical health impacts as well as negative impacts on mental health. Therefore, if parks are located near areas that are environmentally contaminated, the residents in that area will not receive the full benefits of the park (and might, in fact, be harmed by the exposure to increased pollution).
For example, Dimitrov-Discher et al. 103 explain that air pollution has been shown to be correlated with neurodegeneration and lowered cognitive performance, as well as depression and increased risk of suicide. 104 Ju et al. 105 found a significant association between perceived environmental pollution and reduced quality of sleep. Specifically, they concluded that air pollution, noise pollution, and soil pollution were all correlated with poor sleep quality. Further, as study respondents perceived more pollution, they had significantly higher odds of reduced quality of sleep.
Van Den Bosch et al. 106 , 107 explain that particulate matter (PM2.5) is particularly harmful for the human brain, because the particles are small enough to enter the circulatory system in the body and reach the brain. 108 Studies have demonstrated that exposure to air pollutants can cause systemic inflammation in children and teens. 109 There are also a variety of diseases that have been associated with air pollution, such as asthma and cardiovascular diseases. 110
In this article, we explore whether neighborhood parks in the City of Phoenix display these trends from the environmental justice literature. We also explore several environmental quality variables to test the hypothesis that neighborhood parks near wealthier and less racially diverse residential areas are of higher quality and less environmentally contaminated. The research question for this study is: Are there significant differences in park quality and environmental quality measures for parks across neighborhoods in different SES areas in Phoenix, Arizona?
HYPOTHESES
The hypotheses for this study have been developed based on the literature mentioned earlier. In particular, the focus is on the relationship between park quality variables and the demographic characteristics of the neighborhoods in the Phoenix, Arizona area. We also explore several environmental quality variables to test the hypothesis that neighborhood parks near wealthier, more educated, and less racially diverse residential areas are of higher quality and less environmentally contaminated. The first hypothesis is related to discrepancies in park and environmental quality across neighborhoods with different racial/ethnic compositions.
Hypothesis 1: Parks in Phoenix, Arizona located near areas with more under-represented and disadvantaged residents will be smaller in acreage size and have more environmental contamination near them than parks located in areas with fewer under-represented and disadvantaged residents.
The second hypothesis is related to discrepancies in park size and environmental quality across neighborhoods with different income levels.
Hypothesis 2: Parks in Phoenix, Arizona located near lower income areas will be smaller in acreage size and have more environmental contamination near them than parks located near higher income areas.
METHODS
The data used for this study come from two sources that were merged into a single dataset for analysis in the statistical software package R. The first data source is the City of Phoenix park data. For the analysis conducted here, the City of Phoenix park data were downloaded on November 4, 2021. The dataset consisted of 224 parks in the city.
There were 14 different park types in the original dataset: cemetery, community, educational, event space, golf course, linear, mixed use, mountain preserve, museum, natural park, neighborhood, pocket, regional, and stadium. The focus for this analysis is on the neighborhood parks so the dataset was filtered to focus only on this park type. In addition, there were three property types in the dataset (which overlap with park type): flatland park, natural area, and specialty area.
For the analysis in this article, the focus was only on flatland parks as the property type because these are the parks that are located near neighborhoods and that have typical park amenities. Natural area and specialty area park types can include preserves and other special features that are not comparable to flatland parks. Therefore, the original City of Phoenix park dataset was filtered to focus only on “neighborhood” and “flatland” style parks. This filtering process yielded 83 parks in the City of Phoenix that were included in the analysis.
The second data source was the software program EJSCREEN that is available through the U.S. Environmental Protection Agency (EPA) website. EJSCREEN is the EPA's Environmental Justice Screening and Mapping (EJSM) Tool. EJSCREEN was designed by the EPA within the context of two policies: Executive Order 128988 and the EPA's environmental justice policies (e.g., EPA's Guidance on Considering Environmental Justice During the Development of an Action). 111
The analysis here uses the data from the 2020 version of the EJSCREEN program. 112 The data from the EJSCREEN program used in this analysis were downloaded from the EPA website between November 30, 2021 and December 14, 2021. For each of the 83 neighborhood, flatland style parks in the City of Phoenix dataset, the full range of EJSCREEN data were downloaded. The location of the park was identified in the EJSCREEN dataset by typing the address for the park that was available from the City of Phoenix park database.
We did not adjust the location of the park beyond entering the formal address from the City of Phoenix dataset and visually making sure that the EJSCREEN datapoint was located somewhere on the park location. After the EJSCREEN data were downloaded for all 83 parks, the park data from the City of Phoenix were merged with the environmental and demographic data from EJSCREEN to create one large database for analysis of the 83 parks in a statistical software package.
Before delving into the results of the analysis, some brief descriptive statistics will be summarized for the 83 parks in the dataset. For park acreage, the minimum size was 2.178 acres and the maximum size was 37.37 acres (with a mean of 10.26, median of 8.34, and standard deviation of 7.31). For turf square footage within the parks, the minimum was 20,674.43 square feet and the maximum was 1,094,623.64 square feet (with a mean of 263,540.19, median of 195,387.50, and standard deviation of 214,349.77).
Demographic and environmental quality variables in EJSCREEN
EJSCREEN reports several demographic indicators, and the EPA states that these are general indicators of “a community's potential susceptibility to the types of environmental exposures included in this screening tool.” 113 For this article, several demographic variables from EJSCREEN were used, including the following: the percentage of population in the area that identifies as being part of an under-represented group (i.e., the percentage of individuals in a block group who list their racial status as a race other than non-Hispanic white-alone individuals, with alone meaning of a single race), percentage of the population in the area that is low income (i.e., the percentage of a block group's population in households where the household income is less than or equal to twice the federal poverty level), and the percentage of the population in the area that has less than a high school education (i.e., this variable is the percentage of people aged 25 or older without a high school diploma).
Within the EJSCREEN software, the EPA has also provided a series of environmental quality indicators. As outlined in the EPA Technical documentation for EJSCREEN, 114 these indicators “represent a spectrum in terms of the quality of information about potential impacts, ranging from direct estimates of risk to rough indicators of proximity or exposure to pollution or other environmental hazards.” The demographic variables in EJSCREEN are reported on the census block group level.
Note that some of the publicly available environmental quality estimates are at the census tract resolution, and tract level is the resolution used for EJSCREEN for these variables. However, when data were available at the census tract level, the EPA assigns each block group the environmental quality variable data of the tract containing it. According to the Technical Documentation for EJSCREEN, 115 all “indicators or statistics then were calculated using block group data, whether or not those block group scores had been assigned based on tracts.”
Therefore, the data reported in EJSCREEN (and used for this analysis) are prepared for the census block group unit and therefore the demographic variables can be analyzed with the environmental quality variables (as they are all reported on the census block group level). The park quality data are from the City of Phoenix, Arizona data set and it is specific to the park in the neighborhood. The demographic and environmental quality variables from the EJSCREEN dataset characterize the area around the neighborhood park at the census block group level.
The environmental quality indicators that were chosen for analysis for this study are outlined next. The descriptions given next for each indicator are taken from the 2019 Technical Documentation for EJSCREEN. 116
Lead paint
This indicator is a measure of the percentage of housing units built before 1960.
National Air Toxics Assessment air toxics cancer risk
This indicator is a measure of lifetime inhalation cancer risk. On the exposure-risk continuum, the EPA categorizes this indicator as “risk/hazard” and the key medium for pollution is “air.”
NATA diesel PM
This indicator is a measure of the Diesel PM in an area (reported as micrograms of PM2.5 per cubic meter of air). On the exposure-risk continuum, the EPA categorizes this indicator as “potential exposure” and the key medium for pollution is “air.”
NATA respiratory hazard index
This indicator is the ratio of the exposure concentration to the reference concentration from the EPA's Integrated Risk Information System. On the exposure-risk continuum, the EPA categorizes this indicator as “risk/hazard” and the key medium for pollution is “air.”
Ozone
This indicator is a measure of the summer seasonal average of daily maximum 8-hour concentration of ozone in air (parts per billion). On the exposure-risk continuum, the EPA categorizes this indicator as “potential exposure” and the key medium for pollution is “air.”
Particulate matter 2.5
This indicator is a measure of the PM in an area that is composed of particles smaller than 2.5 microns in width (reported as micrograms of PM2.5 per cubic meter of air). On the exposure-risk continuum, the EPA categorizes this indicator as “potential exposure” and the key medium for pollution is “air.”
Proximity to National Priorities List sites
This indicator is a count of the proposed and listed National Priorities List (NPL; i.e., Superfund program) sites within 5 km (or nearest neighbor outside 5 km), divided by distance. The count of NPL sites excludes deleted sites and sites in U.S. territories. On the exposure-risk continuum, the EPA categorizes this indicator as “proximity/quantity” and the key medium for pollution is a combination of “waste/water/air.”
Proximity to Risk Management Plans sites
This indicator is a count of the facilities required by the Clean Air Act to file Risk Management Plans (RMP) within 5 km (or nearest neighbor outside 5 km), divided by distance. On the exposure-risk continuum, the EPA categorizes this indicator as “proximity/quantity” and the key medium for pollution is a combination of “waste/water/air.”
Proximity to Hazardous Waste Treatment, Storage, and Disposal Facilities
This indicator is a count of the major Hazardous Waste Treatment, Storage, and Disposal Facilities (TSDFs) within 5 km (or nearest neighbor outside 5 km), divided by distance. On the exposure-risk continuum, the EPA categorizes this indicator as “proximity/quantity” and the key medium for pollution is a combination of “waste/water/air.”
Traffic proximity and volume
This indicator is a count of the vehicles (average annual daily traffic) at major roads within 500 m (or nearest neighbor outside 500 m), divided by distance in kilometers. On the exposure-risk continuum, the EPA categorizes this indicator as “proximity/quantity” and the key medium for pollution is “air.”
RESULTS
In this section, the results for each hypothesis will be discussed in detail. The first hypothesis outlined hypothesized that parks in Phoenix, Arizona located near neighborhoods with more under-represented residents will be smaller in acreage size and have more environmental contamination near them than parks located near neighborhoods with fewer under-represented residents.
Some descriptive statistics for the variables are listed in Table 1. The demographic and environmental quality variables were extracted from the EJSCREEN software when the address for the neighborhood park was entered into EJSCREEN as the location. The park size variable was extracted from the City of Phoenix dataset.
Descriptive Statistics (N = 83)
Total sample size is 83 neighborhood, flatland parks in the City of Phoenix as of November 2021.
According to EJSCREEN documentation, minority or under-represented percentage is the percent of individuals in a census block group who list their racial status as a race other than white alone and/or list their ethnicity as Hispanic or Latino. That is, all people other than non-Hispanic white-alone individuals. The word “alone” in this case indicates that the person is of a single race, since multiracial individuals are tabulated in another category—a non-Hispanic individual who is half white and half American Indian would be counted as identifying as a minority or being part of an under-represented group by this definition.
According to EJSCREEN documentation, the variable low-income percentage is the percent of a census block group's population in households where the household income is less than or equal to twice the federal poverty level.
NATA, National Air Toxics Assessment; NPL, National Priorities List; PM, particulate matter; RMP, Risk Management Plans; SD, standard deviation; TSDFs, Hazardous Waste Treatment, Storage, and Disposal Facilities.
To test both hypotheses, 11 ordinary least squares (OLS) regression models were run with different dependent variables (i.e., with the park acreage variable and each of the 10 environmental quality variables). To explore the correlation between the park quality (measured as both park size and environmental quality) and demographics near the parks, the OLS models were run with two independent variables (i.e., the percentage of parks in under-represented areas and the percentage of parks in low-income areas).
These two independent variables were tested for multicollinearity as well. The tolerance value was 0.203 and the variance inflation factor was 4.915, indicating that multicollinearity was not a significant problem for these models.
The results of the analysis indicate that although justice concerns are not present in Phoenix neighborhood parks with respect to park size, there are environmental justice issues related to the environmental pollution variables near park areas in Phoenix (Table 2).
Ordinary Least Squares Regression Models for Park Acreage and Air Pollution Variables
Significance level: **p < 0.01.
According to EJSCREEN documentation, minority or under-represented percentage is the percent of individuals in a census block group who list their racial status as a race other than white alone and/or list their ethnicity as Hispanic or Latino. That is, all people other than non-Hispanic white-alone individuals. The word “alone” in this case indicates that the person is of a single race, since multiracial individuals are tabulated in another category—a non-Hispanic individual who is half white and half American Indian would be counted as identifying as a minority or being part of an under-represented group by this definition.
VIF = 4.914, TOL = 0.203.
According to EJSCREEN documentation, the variable low-income percentage is the percent of a census block group's population in households where the household income is less than or equal to twice the federal poverty level.
VIF = 4.914, TOL = 0.203.
VIF, variance inflation factor; TOL, tolerance.
Specifically, several environmental pollutant measures had significantly higher concentrations near parks in higher under-represented neighborhoods, including PM2.5, National Air Toxics Assessment (NATA) Air Toxics Cancer Risk, Respiratory Hazard Index, and proximity to RMP sites. On the other hand, two environmental pollutant measures (i.e., ozone and traffic proximity/volume) were lower near parks in the higher under-represented neighborhoods.
Since mobile air pollution sources (like vehicles) are one large contributor to ground-level ozone concentrations, it seems reasonable that the ozone levels would be lower in an area where there is less traffic volume (Table 3).
Ordinary Least Squares Regression Models for Hazardous Materials and Traffic Proximity
Significance level: **p < 0.01.
According to EJSCREEN documentation, minority or under-represented percentage is the percent of individuals in a census block group who list their racial status as a race other than white alone and/or list their ethnicity as Hispanic or Latino. That is, all people other than non-Hispanic white-alone individuals. The word “alone” in this case indicates that the person is of a single race, since multiracial individuals are tabulated in another category—a non-Hispanic individual who is half white and half American Indian would be counted as identifying as a minority or being part of an under-represented group by this definition.
VIF = 4.914, TOL = 0.203.
According to EJSCREEN documentation, the variable low-income percentage is the percent of a census block group's population in households where the household income is less than or equal to twice the federal poverty level.
VIF = 4.914, TOL = 0.203.
For the parks near neighborhoods with lower income residents, there were five environmental pollutant measures that were significantly higher than in the higher income areas: ozone, NATA Diesel PM, lead paint, proximity to TSDFs, and traffic proximity/volume. There was only one environmental pollutant measure that was lower near parks in the lower income areas and that was PM2.5.
DISCUSSION
The results of the analysis presented here indicate that environmental justice issues are present in the Phoenix metropolitan area in terms of environmental quality for neighborhood parks. Using the EJSCREEN software, these trends were uncovered for most of the environmental quality variables included in the dataset. In addition, these trends were consistent across various socio-economic variables, including race/ethnicities and income.
This study contributes to the literature related to environmental justice and park quality, accessibility, and quality. Environmental pollution near a park can serve as a measure of lower park quality, because air pollution is detrimental to human health and ecosystems within the park. Residents utilize parks for a variety of uses, including recreation and exercise.
Air and water quality are both important in these public areas. Although much of the environmental justice literature has focused on park size and park characteristics, this study demonstrates that environmental quality of the area near a part is also an important measure of environmental justice related to urban green spaces.
In their study, Yang and Chen 117 argued that high levels of PM2.5 near parks are particularly harmful for elderly residents. They explained how PM2.5 concentrations can be reduced in China through careful environmental planning. These possible plans include adjusting the airflow in the greenspace, adjusting the green coverage, and also jointly adjusting both airflow and green coverage. 118
Although some airflow can help move PM through an area, a high degree of air flow can create more PM in a park through heavy winds. 119 This is particularly relevant in an area like Phoenix where the desert does not naturally have a lot of vegetation to reduce wind flow. In this case, city planners in Phoenix could measure PM2.5 levels nears parks and add tall trees and other vegetation to parks with high PM2.5 levels to reduce heavy winds. Therefore, by increasing the green coverage, the city would be able to reduce air flow and therefore reduce PM2.5 levels.
Brugge et al. 120 discuss the proximity to traffic and highways can increase the likelihood of adverse cardiovascular events for people. They provide some options for reducing near-highway housing in an urban environment. They argue that city planners should attempt to locate new parks away from highways to reduce exposure to air pollution by children and others visiting the parks. Although this recommendation is not directly relevant for existing parks, it is certainly an important consideration for city planners in Phoenix for the siting of future urban green spaces and parks.
The results of this analysis demonstrate that neighborhood park size does not vary in size across ethnicity and income variables. Yet, the analysis does indicate that there are environmental injustices in Phoenix related to ethnicity for air pollution variables (i.e., PM2.5, NATA Air Toxics Cancer Risk, and NATA Respiratory Hazard Index) and hazardous substances (i.e., proximity to RMP sites). Similarly, the analysis illustrates that there are environmental injustices in Phoenix related to income for air pollution (i.e., ozone, NATA Diesel PM), lead paint, hazardous substances (proximity to TSDFs), and traffic proximity.
Caveats and limitations
The variables in EJSCREEN are reported on the Census block group level, as defined by the U.S. Census Bureau. The estimates for the demographic and environmental variables reported in EJSCREEN are, therefore, compiled by the block group and, according to the U.S. EPA, “that is the most detailed level at which results can be viewed.” 121 Yet, there are some caveats outlined by the EPA related to the data uncertainty.
As they outline in their technical documentation, 122 the demographic estimates for census block group could be based on a small sample of the local population and have a degree of uncertainty. Likewise, some of the environmental quality variables are computed from lower-resolution data and might also have some uncertainty associated with them.
Given these limitations, the U.S. EPA suggests that EJSCREEN be used largely as a screening-level tool to identify the potential areas of environmental justice. 123 The relative comparison of environmental pollution variables across Phoenix parks in this study indicates a discrepancy in environmental quality between parks in areas with higher SES compared with those of a lower SES. However, a follow-up study could estimate health outcomes and exposure levels to give a more detailed picture of the discrepancies and their impacts on human health.
Several scholars have outlined the limitations of EJSM tools, such as EJSCREEN. For example, Ravichandran et al. prepared a 2021 report for the National Wildlife Federation that outlined some of the limitations of these tools. 124 Although the authors highlight that EJSM tools (such as EJSCREEN) can be useful for equitable decision making for communities, they also emphasize that some current tools might omit important data about issues such as health disparities, vulnerabilities, resilience, and social progress, among others.
Ravichandran et al. explain that some states have addressed shortcomings in EJSCREEN data by introducing a state-level EJSM tool. Several scholars have reviewed these state-level tools and outlined some benefits and limitations for these tools as well. For example, Konisky et al. have criticized static tools that are not interactive. 125
Yet, they do highlight that state-level tools are more customizable to regional issues. In addition, Williams et al. have argued that state-level EJSM tools can provide more contextual and nuanced data for environmental justice at a regional or local level than a federal level tool can provide. 126 Yet, state-level tools like this are only available in a few U.S. states currently. Therefore, federal level tools (like EJSCREEN) can still provide insight into discrepancies in environmental quality by SES.
CONCLUSION
These results demonstrate that the City of Phoenix should pay attention to the air quality and potential exposure to hazardous substances near parks and urban green spaces in higher under-represented and lower income neighborhoods, because these areas are significantly more likely to be polluted. Clean-up programs could be implemented near these parks to help residents gain access to cleaner green spaces.
Given that previous studies have demonstrated that neighborhood parks are critical for physical, mental, and psychological health, it is important for local governments and urban planners to pay close attention to park placement and park quality for planning purposes. In addition, mitigation measures could be taken in lower SES neighborhoods to reduce the higher levels of environmental pollution in those areas. This would improve the quality of life for residents who visit neighborhood parks for recreation and exercise.
Footnotes
AUTHORs' CONTRIBUTIONS
The author (E.A.C.) confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.
AUTHOR DISCLOSURE STATEMENT
No competing financial interests exist.
FUNDING INFORMATION
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.