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Table 1 Summary of selected park accessibility research.

From: The complexities of measuring access to parks and physical activity sites in New York City: a quantitative and qualitative approach

Research Study Study Area(s)/Unit of Analysis/Independent Variables Measuring Methods Findings
Abercrombie et al, 2008
[31]
Study Area: Metro Baltimore/DC area (MD)
Unit: census block groups
Independent Variables: % minority, median income, pop size, geographic size, and % pop < 18.
Number of private rec. facilities and public parks per block group; size of rec. space. Number of parks and facilities were recoded into categories based on # per block group and the park size was divided into four categories based on Mertes and Hall's classification system. Neighborhoods selected by variation in walkability and median income. Socio-demographic variables in tertiles (low, medium, and high). Two way analysis of covariance: # private facilities, # parks, & largest park size across block groups. No signif. effect of income or % minority on # private rec. Mixed-race neighborhoods had highest number of parks, regardless of income. Low- and middle-income pop. in white block groups and high-income groups in minority block groups had lowest park access.
Estabrooks et al, 2003
[29]
Study Area: small American Midwestern city (not specified)
Unit: census tracts
Independent Variables: % unemployed, per capita income; % pop. below poverty threshold, education (less than h.s. diploma). Racial/ethnic characteristics
Availability of PA resources and accessibility as pay-for-use and free-for-use. Raw counts of numbers of PA facilities per census tract. Multivariate analyses of variance of PA resource availability and accessibility by neighborhood SES; Univariate analyses of variance to determine whether income differed on the number of pay-per-use and free-for-use facilities. Low- and medium-SES neighborhoods have signif. fewer PA resources than high-SES neighborhoods. Low- and medium-SES neighborhoods have signif. fewer free-for-use resources than high-SES neighborhoods
Moore et al, 2008
[39]
Study Areas: Forsyth County, NC; Manhattan & Bronx, NY; Baltimore City & County, MD
Unit: census tracts, blocks, and 100-meter grid cells (kernel density)
Independent Variables: total pop, racial/ethnic pop, land area, median household income.
Presence of resources, as well as densities & types of resources. Public-use parks, commercial and public rec. The total number of resources obtained by summing the resources at each location, weighted by the count when appropriate. Kernel density of recreational resources, weighted by # of resources and types; binomial regression for probability of having access as function of SES and demographic factors. Minority & low income areas signif. less likely to have fee-for-use rec. Densities of public rec. within parks were signif. higher in minority and low-income tracts, even after adjustment for pop.
Nicholls, 2001
[34]
Study Area: Bryan, TX
Unit: census tracts
Independent Variables: Pop density, % non-White; % black; % Hispanic; % < 18; % > 64; % renter occupied housing units; mean housing value; mean rent
Equity and accessibility to parks: ease with which a site can be reached and fairness of distribution of parks. Buffering Euclidean & street network distance for accessibility; comparison of pop. factors of areas w/good access to pop. factors in areas w/o good access Large areas of the city are not within 1/2 mile of a park access point, by either the straight-line or network distance. < 40% of pop has good access. All pops seem equally well-served by the parks, and the parks are well-distributed amongst less advantaged groups
Talen, 1997
[32]
Study Areas: Pueblo, CO, and Macon, GA
Unit: census blocks
Independent Variables: % non-white (Macon); % Hispanic (Pueblo); % < 18 years; vacant units; owner occupied units; Median housing value; % housing units w/> 1 person per room; % households w/no spouse present
The spatial clustering of park access scores with the spatial clustering of SES variables. Also used a measure of accessibility at the census block level based on amounts of park acreage within certain distances of residential areas. Access measure consists of the total amount of park acreage located within a specified travel distance between each block and each park, using street network distance between centroids of blocks and centroids of parks. Spatial autocorrelation for both cities is significant for park access measures. Park access in Pueblo favors higher-income areas. In Macon, access to parks tends to favor lower-income areas.
Talen and Anselin, 1998
[35]
Study Area: Tulsa, OK
Unit: census tracts
Independent Variables: % pop < 18; % non-white; median housing value
Spatial distribution of playgrounds using the shortest path distances over street network from census tract centroids. Compares the results of "container method" w/the geographic access measures obtained by gravity model (travel cost measure). The playgrounds are not distributed evenly throughout the city, but are also not predicted by any specific socio-demographic variables.
Timpiero et al, 2007
[30]
Study Area: Melbourne, AU
Unit: postal districts
Independent Variables: Index of relative SES disadvantage (income, education, occupation, family composition, dwelling structure).
Density and area of various categories of open space in relation to SES within each postal district. container approach was used correlating numerous variables (# of OS facilities, OS area, OS density, etc) to SES index Greater # of o.s in lowest SES districts; once normalized by pop, differences not signif.
Wolch et al, 2005
[33]
Study Area: Los Angeles, CA
Unit: census tracts
Independent Variables: Total pop; racial/ethnic pop; pop < 18; median household income; % persons in poverty.
Park access = park acres/1,000 pop (total pop and < 18 pop); % of tract pop (total and < 18) within 1/4 mile of a park boundary; Park acres/1,000 pop (total and < 18) living within the 1/4 mile buffer. 1/4 mile buffers around parks creating accessible park acreage per census tract. Estimates of total area within a 1/4 mile of park and total accessible population per tract were calculated. Low-income and concentrated poverty areas have relatively low levels of park resources and accessibility. African American,, Latino, and Asian American pops have low rates of park access compared to white-dominated areas.
  1. Abbreviations used in table: o.s. = open space; rec. = recreational facilities; pop = population(s); PA = Physical Activity; SES = socio-economic status