Journal of Urban Health: Bulletin of the New York Academy of Medicine, Vol. 88, No. 2
* 2011 The New York Academy of Medicine
Reconsidering Access: Park Facilities
and Neighborhood Disamenities in New York City
ABSTRACT With increasing concern about rising rates of obesity, public health researchers
have begun to examine the availability of parks and other spaces for physical activity,
research in this field has shown that proximity to parks may support increased physical
activity in urban environments; however, as yet, there has been limited consideration of
environmental impediments or disamenities that might influence individuals’ perceptions or
usage of public recreation opportunities. Prior research suggests that neighborhood
disamenities, for instance crime, pedestrian safety, and noxious land uses, might dissuade
people from using parks or recreational facilities and vary by neighborhood composition.
Motivated by such research, this study estimates the relationship between neighborhood
compositional characteristics and measures of park facilities, controlling for variation in
neighborhood disamenities, using geographic information systems (GIS) data for New
York City parks and employing both kernel density estimation and distance measures. The
central finding is that attention to neighborhood disamenities can appreciably alter the
relationship between neighborhood composition and spatial access to parks. Policy efforts
to enhance the recreational opportunities in urban areas should expand beyond a focus on
availability to consider also the hazards and disincentives that may influence park usage.
KEYWORDS Built environment, Parks, Spatial accessibility, GIS
Increasing concerns about persistentlyrising obesity rates have led to researchon avariety
of factors that might contribute to overweight and obesity. Prior studies on the risk of
obesity have found that individual-level factors have limited ability to explain patterns of
obesity or disparities in such patterns. Recent research on environmental factors has
focused, in part, on the recreational opportunities available in the neighborhood—with
increased attention to the location and features of parks and the association between park
access and physical activity and, in turn, the risk of overweight or obesity.
Previous research has repeatedly shown that proximity and access to parks and
outdoor recreational opportunities is positively correlated with active behaviors.1–5
Moreover, research examining the distribution of environmental conditions—both
Weiss, Quinn, and Rundle are with the Institute for Social and Economic Research and Policy, Columbia
University, New York, NY, USA; Purciel is with the Human Impact Partners, Oakland, CA, USA; Bader is
with the Health and Society Scholars Program and Leonard Davis Institute for Health Economics,
University of Pennsylvania, Philadelphia, PA, USA; Lovasi is with the Mailman School at Public Health,
Department of Epidemiology, Columbia University, New York, NY, USA; Neckerman is with the Center
for Health and the Social Siences, University of Chicago, Chicago, IL, USA.
Correspondence: Christopher C. Weiss, Institute for Social and Economic Research and Policy,
Columbia University, New York, NY, USA. (E-mail: firstname.lastname@example.org)
Christopher C. Weiss, Marnie Purciel, Michael Bader, James
W. Quinn, Gina Lovasi, Kathryn M. Neckerman, and Andrew
negative (e.g., pollutants, crime) and positive (e.g., recreational opportunities, open
space)—has examined whether and how environmental disparities contribute to social
and health disparities.6,7
Although concern about the inequitable distribution of parks and open space is
not new, geographic information systems (GIS) software and data have enabled a
significant expansion of research on disparities in the recreational opportunities and
their implications for obesity. A set of studies over the past decade has advanced our
understanding of how access to parks varies across neighborhoods and whether
park access varies across neighborhoods of differing racial/ethnic and socioeconomic
compositions.8–10Despite this growing body of work, however, a key question has
been neglected: whether and how the social context of the neighborhood,
particularly negative characteristics or disamenities of the neighborhood environment,
influence access to parks. By focusing exclusively on spatial dimensions of park
availability and characteristics of parks, such as facilities, size, and quality, previous
research has neglected to study other neighborhood contextual factors likely to
influence whether and how nearby residents access and utilize outdoor space. For
example, high neighborhood crime rates and hazardous traffic patterns may reduce
park usage and decrease the potential benefits of a park. In short, physical proximity to
a park may provide the potential for park usage, but neighborhood disamenities may
reduce park usage for physical activity. Thus, it is important to consider both spatial
access and neighborhood disamenities in thinking about racial/ethnic and socio-
economic disparities in park access and the role of parks in health promotion.
To address this gap in our knowledge, this study presents a series of analyses to
examine how adjustments for spatial variation in characteristics such as crime,
traffic, and noxious land uses affect measured disparities in access to parks in New
York City. In doing so, we provide evidence to help explain the paradoxical finding
that Blacks and Hispanics have higher rates of obesity in New York City despite
having more accesses to parks and recreational facilities.11Examining this wider set
of contextual factors, we demonstrate that the parks that Blacks and Hispanics have
access to are disproportionately adjacent to disamenities, including crime, lack of
traffic safety, and noxious land uses, compared to the parks accessible by Whites.
Much of the recent attention in public health to parks and open space is motivated
by the assumption that differentials in park access affect exercise and recreation and,
thus, body size. Previous research on access to parks has shown that geographic
proximity to various forms of open space has a positive effect on physical activity
levels.4,12,13Moreover, recent research has documented the relationship between
park access and lower rates of obesity and other health problems.14–16
Another dimension of variability in previous studies is in how parks are
characterized. Some studies have examined proximity to or density of parks and open
space by area income and/or racial composition.9,10,17For the most part, these studies
have documented disparities by socioeconomic characteristics in access to parks and
other sites for physical activity. For example, one study documented that low- and
middle-income neighborhoods have significantly fewer physical activity resources
than higher income areas.10Another, using data from Los Angeles, found the lowest
levels of park resources in areas with concentrations of low-income residents.9This
same study found that areas with more African Americans, Latinos, and Asians in the
city had lower rates of park access as compared with predominantly White areas.
WEISS ET AL.298
The evidence of such disparities has not been uniform, however.18Some have
found that poor and predominantly minority areas have greater access to parks. A
multisite study of the presence and density of physical activity resources found that
minority and low-income neighborhoods had higher densities of public recreation
facilities, even after population was taken into account.8Similarly, a recent study of
New York City found that areas of the city with higher percentages of Black and
Latino residents had greater access to physical activity sites.11And a recent
study of Phoenix found that disadvantaged subpopulations have better access to
A third group of studies has found no relationship between neighborhood
characteristics and park space. For example, a study of Tulsa, Oklahoma, found that
although playgrounds were not evenly distributed across the city, variations in their
location were not predicted by any socio-demographic variables.17A recent study of
Baltimore found that racial variation in access to parks depended upon the specific
park measure assessed.20These sets of papers suggest the benefit of examining park
access while taking into account other features of the neighborhood environment,
such as environmental risks or park quality, that might influence usage.
Conclusions about disparities in access to parks and their relation to health are
valid only to the extent that park access measures are valid proxies for the
accessibility of recreational opportunities. In addition, informed by research in
geography and urban planning,17,21public health studies have used GIS-based
measures such as network distance and kernel density measures that more
appropriately represent local accessibility than administratively defined units.22,23
Disamenities that Might Influence Park Use
In addition to the spatial accessibility of parks and recreational opportunities, there
are other features of the environment that might negatively influence the use of
parks and open space. Research from the perspective of environmental justice has
called attention to the inequities in the spatial distribution of both amenities and
hazards in the environment. Specifically, much of this research has documented the
disproportionate exposure of the less well-off and racial and ethnic minorities to
environmental hazards such as pollution, as well as the limited access of these same
groups to environmental amenities.9,24There is also evidence that fear of crime and
other safety-related concerns discourage neighborhood walking or other forms of
outdoor physical activity.25,26Concerns about various factors related to safety may
inhibit use of parks, which may lead potential users to avoid parks altogether or
seek other parks.
A small number of studies have considered the influence of perceived or
measured safety with respect to park access and usage.27,28However, only one
paper has explicitly considered the implications of these neighborhood conditions
for the measurement of economic and racial/ethnic disparities in the park access,19
an analysis that found that while low-income, African American, and Latino
neighborhoods had better walking access to parks, this advantage was offset by
higher crime. In addition to problems of poor safety, noxious land uses such as
industrial facilities or vacant lots may deter walking and thus discourage use of
parks. Industrial facilities are sometimes unsightly and may involve odors or noise or
generate heavy truck traffic. Vacant lots are often unkempt and may prompt concern
about safety because of the lack of “eyes on the street.”29
Because variation in characteristics such as crime, traffic safety, and land use
may be correlated with neighborhood poverty and racial/ethnic composition,
PARK FACILITIES AND NEIGHBORHOOD DISAMENITIES IN NEW YORK CITY299
adjusting park access measures for these characteristics may affect our conclusions
about disparities in the neighborhood environment. To address this question, we
conduct a series of analyses using data for New York City, comparing disparities in
access to parks and features of parks before and after adjustment for crime,
pollution, and traffic safety.
The unit of analysis in this study is the Census tract, with all 2,172 populated
New York City Census tracts included in our models. For each tract, we
constructed multiple measures of the spatial accessibility of parks. Using data
drawn from the 2000 US Census Summary File 3, we created a measure of the
percentage of the population of a tract that was African American and a
separate measure to assess the percentage Hispanic/Latino. To describe
economic composition, we used data on poverty rates defined as the proportion
of residents living below the federal poverty line.
Data on parks were provided by the New York City Department of Parks and
Recreation through the Parks Inspection Program (PIP). PIP is a comprehensive data
collection and measurement system used by the Parks Department to provide
information on the condition of New York City parks. Data for PIP are created by a
team of trained evaluators who use digital cameras and handheld devices to record
conditions of the city’s parks. We accessed these data to create measures of 1,795
park properties in New York City. In the case of some of the city’s larger parks (e.g.,
Central Park), we use park “zones,” which are city-defined subdivided areas of
parks. Whether a park is large enough to be divided into zones is determined by the
New York City Parks Department. For further details about the classification of
parks and how these data were created, please see the Appendix.
Previous studies have noted the need for more accurate measures in examining
available opportunities at parks.11We examine 4 dimensions of parks in our
analysis: the number of parks accessible from a tract, the number of acres of
parkland accessible from a tract, the total number of facilities in the parks accessible
from a tract, and the number of unique facility types accessible from a tract. Each of
these measures is described in greater detail below.
For the first 2 measures, number of parks and acreage of parks, a quarter-mile
straight-line distance buffer was created around the population-weighted centroid of
each Census tract. Parks accessible to a tract (the number of parks or park zones) are
those that intersect a quarter-mile straight-line distance buffer around the Census tract
centroid. The number of acres of accessible parkland is defined as the average total
area, in acres, of parks that similarly intersect quarter-mile buffers around tracts. We
use the total area of the park rather than the area of the tract buffer and park
intersection because we consider tract inhabitants with a part of a park within
walking distance to have access to the entire park.
Spatial access to park facilities was measured using data on the location of park
entrance points. For this set of parks, in our analysis, we used park access points
generated and provided by the New York City Parks Department. These geographic
data were checked and cleaned for accuracy by comparing their locations against
high-resolution aerial photography. We then digitized additional access points based
on the same aerial photography for cases in which it appeared that the original data
file was not an accurate representation of access points. Figure 1 illustrates access
points within a quarter mile of the tract centroid. To calculate the total number of
WEISS ET AL. 300
facilities, we included any facility (court, field, etc.) falling within a quarter mile of a
park access point (straight-line distance) when the park access point fell within the
quarter-mile buffer around the tract polygon. A list of all facilities included in this
measure can be found in the Appendix. Finally, the total number of types is defined
as the number of unique facility types that the tract has access to using park access
points and quarter-mile buffers around tracts.
Given the skewed distribution of these data in their original form, their use
without transformation would potentially bias the analytical techniques we use. For
2 measures—number of parks and number of park features—we take the square
root of the original value. For the variable of park acreage, we take the natural log
of the original value. The number of facility types is used in its untransformed state
in our analysis.
Area Safety and Desirability
Our measures of neighborhood safety near parks include indicators of crime and
traffic hazards, as well as noxious land uses. We assumed that hazardous or
unpleasant conditions were more likely to deter use of a park if they occurred within
close proximity; thus, we assigned each tract the noxious use, crime, or traffic safety
values. For all 3 of these measures, we use kernel estimation techniques as a way to
smooth trends in point data. Kernel smoothing is often used as a means for
examining how levels of some event vary continuously across a study area based on
the patterning of a sample of points, resulting in a smoothed map of values.30
We used data on homicides to represent the risk of serious crime. We obtained point
dataonhomicidesoccurringin2003–2005fromapublicNew York Times web site.31We
estimated a spatially smoothed kernel density grid using inverse distance weighting for
homicide point locations, combining data for all 3 years, and calculated the average
density of homicides for each tract. The benefit of this method is that it better captures
the effect of a murder on a community, with greatest effects at the specific location of the
event and substantial-though-diminishing effects the farther away a point is from the site
of the homicide. That is to say that the spatially smoothed kernel density surface allows
Image of census tract and corresponding park access points.
PARK FACILITIES AND NEIGHBORHOOD DISAMENITIES IN NEW YORK CITY301
for the influence of a homicide to affect an entire area rather than a single point, though
the effect of the homicide decreases the farther one moves from the original point where
the homicide occurred.
Using a similar approach, we measured traffic hazards with data on the
locations of automobile accidents resulting in pedestrian injuries or fatalities, with
data geocoded to the nearest street intersection. These data were obtained for 2002–
2005 through a Freedom of Information Letter submitted to the New York City
Department of Transportation by a local nonprofit organization, Transportation
Alternatives. We estimated a kernel density grid for accident point locations and
calculated the average density of accidents for each tract.
Additionally, to capture another dimension of park disamenity, we developed a
measure of noxious land uses in the environment. To do so, we created a measure of
the average kernel density of the square footage of tax parcels with noxious uses,
defined as industrial and manufacturing (based upon the Land Use field in New
York City’s GIS database, MapPLUTO—classes 06 and 11), as well as vacant lots,
and assigned this density value to the tract.
We use ordinary least squares regression to examine the effects of neighborhood
characteristics on access to parks and open spaces. We estimate identical models for
each of the 4 physical park access measures described in the previous section. In the
initial set of models, we examine the relationship between the socio-demographic
characteristics of neighborhoods and the measures of park size, number of facilities,
and number of parks. We then extend these analyses by including measures of
neighborhood disamenities to examine whether and how the relationships observed
in the first set of models change.
Data on the distribution of park measures and these demographic characteristics of
tracts are presented in Table 1. The upper panel of the table contains information
about the characteristics of parks. On average, a tract in New York City has
multiple parks within a quarter mile of the tract’s center, with a median value of 3
and a mean of 4 parks. The average acreage of parkland within a quarter mile of the
tract shows a highly skewed distribution, with a median value of 5.2 and a mean
value of more than 60. The total number of facilities and total number of facility
types are also presented in the table.
The second panel of Table 1 shows the distribution of transformed park
measures, which are used as the outcomes in our analysis. The third panel of the
table presents information about the distribution of the socio-demographic
characteristics of tracts used in our analysis. The data presented on the racial
characteristics attest to the racial diversity of the city, with the measure of foreign-
born residents offering evidence of the high levels of immigration that the city has
Results presented in Table 2 examine the relationship between the socio-
demographic characteristics of a neighborhood and the availability of parks and
recreation facilities. The figures presented in Table 2 show that the relationships
between neighborhood characteristics and park access are consistent with those
found by Maroko et al.11The first column of the table shows results from the model
examining the measure of the number of parks in a quarter-mile buffer. Both the
percentage of the population that is African American and the percentage that is
Latino are positively related to the number of parks in the area. Similarly, the
WEISS ET AL.302
percentage of the population of an area that lives below the poverty line is also
positively associated with the number of parks, a finding also consistent with
previous analyses. The percentage of the population that is foreign-born, in contrast,
is negatively related to the square root of the number of parks in an area.
The findings of the relationship between socio-demographic characteristics of
neighborhoods and the number of parks in the area are consistent with some of the
other outcome measures presented in Table 2. Areas that have higher proportions of
African American and Latino residents have a significantly greater number of park
facilities and greater number of types of park facilities. Similarly, both outcome
measures are positively related to the percentage of residents whose incomes fall
below the poverty line.
The final outcome presented in Table 2, the measure of park acreage accessible to
residents of a neighborhood, has a different relationship to neighborhood characteristics
than the other outcomes. For this outcome, the greater the percentage of residents who
are African American, who are Latino, and who are poor, the lower is the amount of
park acreage. Similarly, areas with higher percentage of residents born outside the United
States have less park acreage, as do areas with higher population density.
Taken together, although different geospatial approaches to measuring park
access were used, the results presented in Table 2 confirm some prior research on the
TABLE 1 Count of accessible park, by tract composition—all New York City tracts
MeanSD MedianHigh Low
No. of Parks
No. of facilities
No. of facility types
Transformed park measures
Square root (no. of parks)
Ln (park acreage)
Square root (no. of facilities)
Percent African American
facilities, and park acreage
Associations of neighborhood composition and density with park availability, park
(no. of parks)
(no. of facilities)
Percent in poverty
*pG0.05, **pG0.01, ***pG0.001
PARK FACILITIES AND NEIGHBORHOOD DISAMENITIES IN NEW YORK CITY303
relationship between socio-demographic characteristics of neighborhoods and park
access. Specifically, neighborhoods with higher concentrations of traditionally
disadvantaged social groups have access to more parks with a greater number of
facilities and greater number of types of facilities. In the next phase of this analysis,
we look at whether these relationships persist once we take into account potential
disamenities in the neighborhood environment.
Examining Models with Measures of Neighborhood
Table 3 shows the results of models that include the neighborhood disamenities as
predictors, along with the predictors included in Table 2. With the inclusion of these
new variables in the model, some of the relationships between neighborhood socio-
demographic characteristics and park access are changed. The most substantial
changes are in the relationship for the measure “Percent Black.” While the
percentage of a neighborhood’s residents who are Black was positively related to
the number of parks measure in Table 2, the relationship is negative once the
neighborhood disamenity measures are included. Additionally, for both measures
related to park facilities, while Percent Black was positively and significantly related to
the outcomes in Table 2, neither relationship is significant in Table 3. The apparent
advantage that African Americans have in respect to physical access to parks is
diminished or even reversed once neighborhood disamenities are adjusted for.
The other relationships in Table 3 change less dramatically. Across all 4
outcomes, the effect of the measure of the percentage of residents who are Latino
decreases in magnitude and, for some outcomes, in statistical significance as well.
The first column of the table shows results from the model examining the measure of
the number of parks in a quarter-mile buffer. Both the percentage of the population
that is African American and the percentage that is Latino are positively related to
the number of parks in the area. Similarly, the percentage of the population of an
area that lives in poverty is also positively associated with the number of parks. The
percentage of the population that is foreign-born, in contrast, is negatively related to
the square root of the number of parks in an area.
Another Way of Incorporating Measures of Neighborhood
Another means of examining how consideration of environmental disamenities
alters the picture of socio-demographic disparities in access to parks excludes parks
in neighborhoods with high levels of crime, vehicular accidents, or pollution. We
make the assumption that parks in the upper end of the distribution of these
problems are less accessible and/or less attractive to potential users. For this portion
of the analysis, we assumed that parks in the highest quintile of homicide,
pedestrian–auto fatalities, or pollution were unavailable to potential users. Although
a strong assumption, it is likely that poor safety or environmental conditions might
reduce park usage. The data with these parks removed can be reanalyzed by
neighborhood characteristics—and the results can be compared to the results of
analyses of the full park dataset.
Figure 2a shows 4 sets of 2 bars (1 for the full parks dataset and 1 for the
reduced parks dataset) looking at the amount of park acreage accessible to a
neighborhood by quartile of neighborhood poverty. Examining only the darker bars
of the figure, the data show a relationship such that areas with more poor residents
have lower levels of park acreage—a finding consistent with the results presented in
WEISS ET AL.304
the previous tables. When we exclude those parks with the highest levels of
homicide, traffic fatalities, and pollution, these disparities become even starker, as
evidenced in the series of lighter bars in the figure. These results suggest that lower
income neighborhoods have even less access to parks once spatial access is
discounted for negative social conditions.
Figure 2b presents a similar analysis, examining the number of total park
facilities by poverty quartile, with the darker bars showing the unadjusted
values and lighter bars for adjusted park measures. Here, the story is even
more striking. Focusing first on the darker bars, Figure 2b shows an inverse
relationship between level of poverty and the total number of park facilities. That
is, areas with poorer residents have more park facilities in their neighborhoods.
However, when we exclude those parks with the highest levels of homicide, traffic
fatalities, and pollution, the relationship is inverse, such that poorer neighbor-
hoods have fewer park facilities. The data presented in Figure 2a, b offer further
evidence of the importance of accounting for disamenities when examining the
relationship between neighborhood socio-demographic characteristics and park
Research using GIS measures of access to parks has greatly enhanced our
understanding of the availability of exercise and recreational opportunities in urban
environments. However, in order to fully realize the benefits of GIS, it is important
to address a number of conceptual and methodological issues. As this paper has
highlighted, one set of issues concerns the difference with spatial access and what we
might call social access. Spatial access describes the physical availability or distance
to park space and recreational facilities. When considering disparities in spatial
access across neighborhoods with differing socio-demographic compositions, one
might consider discounting or weighting apparent spatial access for population-level
differences affecting the ability to physically traverse space. For instance, in
measuring spatial access, one might consider differences in neighborhood trans-
portation systems or population level of disability that interferes with mobility.
Here, we have sought to develop and address the notion of social access, which
use mix with park availability, park facilities, and park acreage
Adjusted associations between neighborhood composition, density, safety, and land
(no. of parks)
(no. of facilities)
Percent in poverty
Avg. Homicide Density
Avg. Ped. Fatality
Noxious Usage Density
−0.003 (0.002) 0.002 (0.003)
*pG0.05, **pG0.01, ***pG0.001
PARK FACILITIES AND NEIGHBORHOOD DISAMENITIES IN NEW YORK CITY 305
describes how neighborhood-level differences in disamenities, for instance crime,
pedestrian safety, and noxious land uses, might dissuade people from using parks or
recreational facilities. In studies of neighborhood disparities in park access, high
spatial access might be discounted or nullified by low social access—the dispropor-
tionate concentration of crime, pedestrian accidents, and noxious land uses in some
The analyses presented here offer 2 contributions to our understanding of
neighborhood-level disparities in park access. One is substantive: our results
demonstrate that adjustment of analyses for differences in neighborhood social
access measures affects our understanding of apparent disparities in spatial access to
recreational opportunities. While areas of the city with large African American and
Latino populations have higher spatial access to parks and facilities, their apparent
traffic, and noxious land usage problems: *pG0.05, **pG0.01, ***pG0.001. Tests of significance are
within category of adjustment, with Most Poor as the reference group. b Poverty and park facilities,
overall and after exclusion of parks with the worst crime, traffic, and noxious land usage problems:
*pG0.05, **pG0.01, ***pG0.001. Tests of significance are within category of adjustment, with Most
Poor as the reference group.
a Poverty and park acreage, overall and after exclusion of parks with the worst crime,
WEISS ET AL.306
advantage is diminished when neighborhood conditions likely to dissuade people
from using parks are considered. We measured this diminished advantage as spatial
access that has been discounted for higher crime, lower pedestrian safety, and more
noxious land uses.
This study also makes a methodological contribution by demonstrating a
straightforward, easy-to-implement method of adjusting physical park access
measures for differences in neighborhood conditions. These techniques can help
researchers in other settings and in other analyses of spatial disparities account for
features of the environment that are often overlooked and that may materially affect
whether residents use or perceive that they have good access to a neighborhood
resource. These techniques are also appropriate for use by policymakers as well.
One primary implication of our findings is the importance of expanding the
frame typically used to examine the relationship between socioeconomic characteristics
of neighborhood residents and access to park resources in a neighborhood. In our
models presented in Table 2, the findings are generally counter to the usual
assumptions regarding racial/ethnic and socioeconomic disparities in access to
desirable neighborhood resources. The environmental justice literature generally finds
that minority and lower-income neighborhoods have higher exposure to noxious uses
of physical space and other negative environmental characteristics such as liquor
stores and fast-food restaurants, and lower access to positive resources like
supermarkets. The one finding that is consistent with the usual environmental justice
paradigm is that neighborhoods with higher minority populations have lower acreage
of park space. This, combined with the finding that minority neighborhoods have
higher numbers of parks, indicates that minority neighborhoods have more small
parks. Since neighborhood-level access to large, but not small parks, has been found
to be associated with lower BMI, even after controlling for individual- and
neighborhood-level socio-demographics, the lower park acreage observed in minority
neighborhoods may indicate an environmental justice concern. Maroko and
colleagues have found that in New York City, minority and lower socioeconomic
groups have higher spatial access to parks and recreation facilities.32While using
different measures of spatial access, our results are similar to that of Maroko and
colleagues. However, when we account for features of the environment that are likely
to negatively influence park usage, the relationship between neighborhood socio-
demographic characteristics and spatial access to parks is quite different.
The data and methods used in this study have a number of strengths. Few
studies examining these relationships are able to include multiple measures of park
characteristics. Similarly, we were able to draw on multiple sources of rich
contextual data to examine the environments surrounding parks. However, there
are limitations that should be noted. The primary limitation of our analysis is that
we do not have direct measures of individuals’ park usage or their perceptions of
environmental risk and threat. In addition, the buffer approach used to measure
park number and acreage is subject to the limitations of the “container effect” in
which all residents of a defined neighborhood are assumed to have equal access to
any resource falling within the neighborhood boundary and no access at all to
resources falling outside the boundary. In future research, use of more sophisticated
spatial measures will provide more precise estimates of spatial accessibility.
The corresponding policy implication from these findings is that public health
and park advocates need to move beyond a traditional focus on expanding spatial
access to parks as a priority. Efforts to increase the number of parks or park facilities
will likely not be sufficient. Rather, current efforts to expand recreational
PARK FACILITIES AND NEIGHBORHOOD DISAMENITIES IN NEW YORK CITY307
opportunities should be themselves expanded to incorporate efforts to reduce crime and
pollution and make streets safer. As elsewhere, ethnic minority and lower-income
populations in New York City are at highest risk for obesity despite these populations
having higher spatial access to parks and recreation facilities, as well as streets that, from
an urban design perspective, are more walkable. An expansion of the concept of park
access to include safe walkable streets around parks and greater safety from crime may
allow the higher spatial access minorityandlowerincomepopulations have toparks and
recreation facilities to translate into lower disparities in physical activity and obesity.
In conclusion, we propose that the incorporation of what we term “social access”
measures into studies of neighborhood disparities and park access can alter our
understanding of which populations have higher or lower access to parks. Social access
can be considered a modifier of spatial access; that is, without the presence of parks
there is no access, but the value of spatial access may be diminished if social conditions
dissuade residents from using the parks. The approaches employed here can be adapted
for environmental justice studies of other types of positive neighborhood amenities.
Supportfor this researchwasprovidedbyaPartnershipsforEnvironmentalPublicHealth
administrative supplement to NIEHS grant R01ES014229. “Obesity, Physical Activity
and Built Space in New York City” (PI: Andrew Rundle). The authors additionally would
like to thank the National Heart Lung and Blood Institute (Grant # HL068236), the
National Institute of Environmental Health Sciences (Grant # P30 ES009089), and the
Robert Wood Johnson Health and Society Scholars program for their financial support.
APPENDIX: CREATING MEASURES OF PARKS IN NEW YORK
In the PIP data provided by the New York City Parks Department, there are 4,815
park properties with information. Park properties can be standalone parks, park
zones (which is a specific PIP designation), playgrounds, or other park areas.
However, many of the park properties coded in the PIP data file are ones we
would expect to have minimum effect on physical activity. Specifically, parks with
one of the designations listed below were excluded from our analysis, resulting in a
total number of park properties of 1,795.
EXCLUDED PARK DESIGNATIONS
WEISS ET AL. 308
Four additional, unclassified park types were also excluded.
The following park facilities were included in both facility measures in this analysis:
? Baseball fields
? Basketball courts
? Football fields
? Golf courses
? Handball courts
? Hockey fields
? Soccer fields
? Tennis courts
? Volleyball courts
? Bicycle routes
? Recreation centers
1. Ball K, Bauman A, Leslie E, Owen N. Perceived environmental aesthetics and convenience
and company are associated with walking for exercise among Australian adults. Prev
Med. 2001; 33(5): 434–40.
2. Cohen DA, Ashwood JS, Scott MM, et al. Public parks and physical activity among
adolescent girls. Pediatrics. 2006; 118(5): e1381–9.
3. Cohen DA, McKenzie TL, Sehgal A, Williamson S, Golinelli D, Lurie N. Contribution of
public parks to physical activity. Am J Public Health. 2007; 97(3): 509–14.
4. Diez Roux AV, Evenson KR, McGinn AP, et al. Availability of recreational resources and
physical activity in adults. Am J Public Health. 2007; 97(3): 493–9.
5. Duncan M, Mummery K. Psychosocial and environmental factors associated with
physical activity among city dwellers in regional Queensland. Prev Med. 2005; 40(4):
6. Maantay J. Mapping environmental injustices: pitfalls and potential of geographic
information systems in assessing environmental health and equity. Environ Health
Perspect. 2002; 110(Suppl 2): 161–71.
7. Taylor WC, Floyd MF, Whitt-Glover MC, Brooks J. Environmental justice: a framework
for collaboration between the public health and parks and recreation fields to study
disparities in physical activity. J Phys Act Health. 2007; 4(Suppl 1): S50–63.
8. Moore LV, Diez Roux AV, Evenson KR, McGinn AP, Brines SJ. Availability of
recreational resources in minority and low socioeconomic status areas. Am J Prev Med.
2008; 34(1): 16–22.
9. Wolch J, Wilson JP, Fehrenbach J. Parks and park funding in Los Angeles: an equity-
mapping analysis. Urban Geogr. 2005; 26(1): 4–35.
10. Estabrooks PA, Lee RE, Gyurcsik NC. Resources for physical activity participation: does
availability and accessibility differ by neighborhood socioeconomic status? Ann Behav
Med. 2003; 25(2): 100–4.
11. Maroko AR, Maantay JA, Sohler NL, Grady KL, Arno PS. The complexities of
measuring access to parks and physical activity sites in New York City: a quantitative
and qualitative approach. Int J Health Geogr. 2009; 8: 34.
PARK FACILITIES AND NEIGHBORHOOD DISAMENITIES IN NEW YORK CITY309
12. Giles-CortiB,BroomhallMH,KnuimanM,etal.Increasingwalking:howimportantisdistance Download full-text
to, attractiveness, and size of public open space? Am J Prev Med. 2005; 28(2S2): 169–76.
13. Wendel-Vos GCW, Schuit AJ, De Niet R, Boshuizen HC, Saris WHM, Kromhout D.
Factors of the physical environment associated with walking and bicycling. Med Sci
Sports Exerc. 2004; 36(4): 725–30.
14. Bell JF, Wilson JS, Liu GC. Neighborhood greenness and 2-year changes in body mass
index of children and youth. Am J Prev Med. 2008; 35(6): 547–53.
15. Gordon-Larsen P, Nelson MC, Page P, Popkin BM. Inequality in the built environment
underlies key health disparities in physical activity and obesity. Pediatrics. 2006; 117(2):
16. Rundle A, Field S, Park Y, Freeman L, Weiss CC, Neckerman K. Personal and
neighborhood socioeconomic status and indices of neighborhood walk-ability predict
body mass index in New York City. Soc Sci Med. 2008; 67(12): 1951–8.
17. Talen E, Anselin L. Assessing spatial equity: an evaluation of measures of accessibility of
public playgrounds. Environ Plann A. 1998; 30: 595–613.
18. Lovasi GS, Hutson MA, Guerra M, Neckerman KM. Built environments and obesity in
disadvantaged populations. Epidemiol Rev. 2009; 31(1): 7–20.
19. Cutts BB, Darby KJ, Boone CG, Brewis A. City structure, obesity, and environmental
justice: an integrated analysis of physical and social barriers to walkable streets and park
access. Soc Sci Med. 2009; 69(9): 1314–22.
20. Boone CG, Buckley GL, Grove JM, Sister C. Parks and people: an environmental justice
inquiry in Baltimore, Maryland. Ann Assoc Am Geogr. 2009; 99(4): 767–87.
21. Guagliardo MF, Ronzio CR, Cheung I, Chacko E, Joseph JG. Physician accessibility: an
urban case study of pediatric providers. Health Place. 2004; 10(3): 273–83.
22. Moore LV, Diez Roux AV, Nettleton JA, Jacobs DR Jr. Associations of the local food
environment with diet quality—a comparison of assessments based on surveys and
geographic information systems: the Multi-Ethnic Study of Atherosclerosis. Am J
Epidemiol. 2008; 167(8): 917–24.
23. Rundle A, Neckerman KM, Freeman L, et al. Neighborhood food environment and
walkability predict obesity in New York City. Environ Health Perspect. 2009; 117(3):
24. Albrecht SL. Equity and justice in environmental decision making—a proposed research
agenda. Soc Nat Resour. 1995; 8(1): 67–72.
25. Foster S, Giles-Corti B. The built environment, neighborhood crime and constrained
physical activity: an exploration of inconsistent findings. Prev Med. 2008; 47(3): 241–51.
26. Harrison RA, Gemmell I, Heller RF. The population effect of crime and neighbourhood
on physical activity: an analysis of 15 461 adults. J Epidemiol Community Health. 2007;
27. Brownlow A. An archaeology of fear and environmental change in Philadelphia.
Geoforum. 2006; 37: 227–45.
28. Troy A, Grove JM. Property values, parks, and crime: a hedonic analysis in Baltimore,
MD. Landsc Urban Plan. 2008; 87: 233–45.
29. Jacobs J. The Death and Life of Great American Cities. New York: Random House;
30. Bailey TC, Gatrell AC. Interactive Spatial Data Analysis. New York: Wiley; 1995.
31. Bloch M, Carter S, Evans T, et al. Murder: New York City. New York Times. June 18,
2009. http://projects.nytimes.com/crime/homicides/map/. Accessed 3 May 2010.
32. Maroko AR, Maantay JA, Sohler NL, Grady KL, Arno PS. The complexities of
measuring access to parks and physical activity sites in New York City: a quantitative
and qualitative approach. Int J Health Geogr. 2009 Jun 22; 8: 34.
WEISS ET AL.310