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. |