Journal of Urban Health

, Volume 90, Issue 4, pp 618–631 | Cite as

The Geography of Recreational Open Space: Influence of Neighborhood Racial Composition and Neighborhood Poverty

  • Dustin T. DuncanEmail author
  • Ichiro Kawachi
  • Kellee White
  • David R. Williams


The geography of recreational open space might be inequitable in terms of minority neighborhood racial/ethnic composition and neighborhood poverty, perhaps due in part to residential segregation. This study evaluated the association between minority neighborhood racial/ethnic composition, neighborhood poverty, and recreational open space in Boston, Massachusetts (US). Across Boston census tracts, we computed percent non-Hispanic Black, percent Hispanic, and percent families in poverty as well as recreational open space density. We evaluated spatial autocorrelation in study variables and in the ordinary least squares (OLS) regression residuals via the Global Moran’s I. We then computed Spearman correlations between the census tract socio-demographic characteristics and recreational open space density, including correlations adjusted for spatial autocorrelation. After this, we computed OLS regressions or spatial regressions as appropriate. Significant positive spatial autocorrelation was found for neighborhood socio-demographic characteristics (all p value = 0.001). We found marginally significant positive spatial autocorrelation in recreational open space (Global Moran’s I = 0.082; p value = 0.053). However, we found no spatial autocorrelation in the OLS regression residuals, which indicated that spatial models were not appropriate. There was a negative correlation between census tract percent non-Hispanic Black and recreational open space density (r S = −0.22; conventional p value = 0.005; spatially adjusted p value = 0.019) as well as a negative correlation between predominantly non-Hispanic Black census tracts (>60 % non-Hispanic Black in a census tract) and recreational open space density (r S = −0.23; conventional p value = 0.003; spatially adjusted p value = 0.007). In bivariate and multivariate OLS models, percent non-Hispanic Black in a census tract and predominantly Black census tracts were associated with decreased density of recreational open space (p value < 0.001). Consistent with several previous studies in other geographic locales, we found that Black neighborhoods in Boston were less likely to have recreational open spaces, indicating the need for policy interventions promoting equitable access. Such interventions may contribute to reductions and disparities in obesity.


Recreational open space Neighborhood racial composition Neighborhood poverty Racial/socioeconomic segregation Spatial demography Boston, US 



D.T. Duncan was supported by the Alonzo Smythe Yerby Postdoctoral Fellowship at Harvard School of Public Health. We thank Jeff Blossom for providing technical assistance with building the geospatial dataset used in this research.


  1. 1.
    Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA. 2012; 307(5): 491–497.PubMedCrossRefGoogle Scholar
  2. 2.
    Estimated prevalence of overweight in the United States. Public Health Rep. 1954;69(11):1084–1086.Google Scholar
  3. 3.
    Massey DS, Denton NA. American apartheid: segregation and the making of the underclass. Cambridge: Harvard University Press; 1993.Google Scholar
  4. 4.
    Williams DR, Collins C. Racial residential segregation: a fundamental cause of racial disparities in health. Public Health Rep. 2001; 116(5): 404–416.PubMedGoogle Scholar
  5. 5.
    Lopez R. Black-white residential segregation and physical activity. Ethn Dis. 2006; 16(2): 495–502.PubMedGoogle Scholar
  6. 6.
    Mellerson J, Landrine H, Hao Y, Corral I, Zhao L, Cooper DL. Residential segregation and exercise among a national sample of Hispanic adults. Health Place. 2010; 16(3): 613–615.PubMedCrossRefGoogle Scholar
  7. 7.
    Chang VW. Racial residential segregation and weight status among US adults. Soc Sci Med. 2006; 63(5): 1289–1303.PubMedCrossRefGoogle Scholar
  8. 8.
    Chang VW, Hillier AE, Mehta NK. Neighborhood racial isolation, disorder and obesity. Soc Forces. 2009; 87(4): 2063–2092.PubMedCrossRefGoogle Scholar
  9. 9.
    Wen M, Maloney TN. Latino residential isolation and the risk of obesity in Utah: the role of neighborhood socioeconomic, built-environmental, and subcultural context. J Immigr Minor Health. 2011; 13(6): 1134–1141.PubMedCrossRefGoogle Scholar
  10. 10.
    Corral I, Landrine H, Hao Y, Zhao L, Mellerson JL, Cooper DL. Residential segregation, health behavior and overweight/obesity among a national sample of African American adults. J Health Psychol. 2012; 17(3): 371–378.PubMedCrossRefGoogle Scholar
  11. 11.
    Kirby JB, Liang L, Chen HJ, Wang Y. Race, place, and obesity: the complex relationships among community racial/ethnic composition, individual race/ethnicity, and obesity in the United States. Am J Public Health. Aug;102(8):1572–78.Google Scholar
  12. 12.
    Acevedo-Garcia D, Lochner KA. Residential segregation and health. In: Kawachi I, Berkman LF, eds. Neighborhoods and health. Oxford: Oxford University Press; 2003: 265–287.CrossRefGoogle Scholar
  13. 13.
    Acevedo-Garcia D, Lochner KA, Osypuk TL, Subramanian SV. Future directions in residential segregation and health research: a multilevel approach. Am J Public Health. 2003; 93(2): 215–221.PubMedCrossRefGoogle Scholar
  14. 14.
    Lovasi GS, Hutson MA, Guerra M, Neckerman KM. Built environments and obesity in disadvantaged populations. Epidemiol Rev. 2009; 31: 7–20.PubMedCrossRefGoogle Scholar
  15. 15.
    Tarrant MA, Cordell HK. Environmental justice and the spatial distribution of outdoor recreation sites: an application of geographic information systems. J Leis Res. 1999; 31(1): 18–34.Google Scholar
  16. 16.
    Timperio A, Ball K, Salmon J, Roberts R, Crawford D. Is availability of public open space equitable across areas? Health Place. 2007; 13(2): 335–340.PubMedCrossRefGoogle Scholar
  17. 17.
    Crawford D, Timperio A, Giles-Corti B, et al. Do features of public open spaces vary according to neighbourhood socio-economic status? Health Place. 2008; 14(4): 889–893.PubMedCrossRefGoogle Scholar
  18. 18.
    Smiley MJ, Diez Roux AV, Brines SJ, Brown DG, Evenson KR, Rodriguez DA. A spatial analysis of health-related resources in three diverse metropolitan areas. Health Place. 2010; 16(5): 885–892.PubMedCrossRefGoogle Scholar
  19. 19.
    Billaudeau N, Oppert JM, Simon C, et al. Investigating disparities in spatial accessibility to and characteristics of sport facilities: direction, strength, and spatial scale of associations with area income. Health Place. Sep 17 2010 [Epub ahead of print].Google Scholar
  20. 20.
    Talen E. The social equality of urban service distribution an exploration of park access in Pueblo Colorado and Macon Georgia. Urban Geogr. 1997; 18(6): 521–541.CrossRefGoogle Scholar
  21. 21.
    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.PubMedCrossRefGoogle Scholar
  22. 22.
    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): 767–787.CrossRefGoogle Scholar
  23. 23.
    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): 1314–1322.PubMedCrossRefGoogle Scholar
  24. 24.
    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.PubMedCrossRefGoogle Scholar
  25. 25.
    Franzini L, Taylor W, Elliott MN, et al. Neighborhood characteristics favorable to outdoor physical activity: disparities by socioeconomic and racial/ethnic composition. Health Place. 2010; 16(2): 267–274.PubMedCrossRefGoogle Scholar
  26. 26.
    LeSage J, Pace KR. Introduction to spatial econometrics. Boca Raton: CRC Press; 2009.CrossRefGoogle Scholar
  27. 27.
    Ward MD, Gleditsch KS. Spatial regression models. Thousand Oaks: Sage Publications, Inc; 2008.Google Scholar
  28. 28.
    Waller LA, Gotway CA. Applied spatial statistics for public health data. Hoboken: Wiley-Interscience; 2004.CrossRefGoogle Scholar
  29. 29.
    Bailey TC, Gratrell AC. Interactive spatial data analysis. Harlow Essex: Longman Scientific & Technical; J. Wiley; 1995.Google Scholar
  30. 30.
    Anselin L, Bera AK. Spatial dependence in linear regression models with an introduction to spatial econometrics. In: Ullah A, Giles DEA, eds. Handbook of applied economic statistics. New York: Marcel Dekker; 1998: 237–289.Google Scholar
  31. 31.
    Logan JR, Stults B. The persistence of segregation in the metropolis: new findings from the 2010 Census. Census Brief prepared for Project US2010 2011.Google Scholar
  32. 32.
    Iceland J, Weinberg DH, E. S. Racial and ethnic residential segregation in the United States: 1980–2000. Washington, DC 2002.Google Scholar
  33. 33.
    Bedimo-Rung AL, Mowen AJ, Cohen DA. The significance of parks to physical activity and public health: a conceptual model. Am J Prev Med. 2005; 28(2 Suppl 2): 159–168.PubMedCrossRefGoogle Scholar
  34. 34.
    Subramanian SV, Chen JT, Rehkopf DH, Waterman PD, Krieger N. Comparing individual- and area-based socioeconomic measures for the surveillance of health disparities: a multilevel analysis of Massachusetts births, 1989–1991. Am J Epidemiol. 2006; 164(9): 823–834.PubMedCrossRefGoogle Scholar
  35. 35.
    Subramanian SV, Chen JT, Rehkopf DH, Waterman PD, Krieger N. Racial disparities in context: a multilevel analysis of neighborhood variations in poverty and excess mortality among black populations in Massachusetts. Am J Public Health. 2005; 95(2): 260–265.PubMedCrossRefGoogle Scholar
  36. 36.
    Krieger N, Chen JT, Waterman PD, Rehkopf DH, Subramanian SV. Race/ethnicity, gender, and monitoring socioeconomic gradients in health: a comparison of area-based socioeconomic measures—the Public Health Disparities Geocoding Project. Am J Public Health. 2003; 93(10): 1655–1671.PubMedCrossRefGoogle Scholar
  37. 37.
    Krieger N, Chen JT, Waterman PD, Soobader MJ, Subramanian SV, Carson R. Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter?: the Public Health Disparities Geocoding Project. Am J Epidemiol. 2002; 156(5): 471–482.PubMedCrossRefGoogle Scholar
  38. 38.
    Duncan DT, Aldstadt J, Whalen J, White K, Castro MC, Williams DR. Space, race and poverty: spatial inequalities in walkable neighborhood amenities? Demogr Res. 2012; 26(17): 409–448.CrossRefGoogle Scholar
  39. 39.
    US Census Bureau. Decennial Management Division Glossary 2012.Google Scholar
  40. 40.
    Cradock AL, Kawachi I, Colditz GA, et al. Playground safety and access in Boston neighborhoods. Am J Prev Med. 2005; 28(4): 357–363.PubMedCrossRefGoogle Scholar
  41. 41.
    Chen JT, Rehkopf DH, Waterman PD, et al. Mapping and measuring social disparities in premature mortality: the impact of census tract poverty within and across Boston neighborhoods, 1999–2001. J Urban Health. 2006; 83(6): 1063–1084.PubMedCrossRefGoogle Scholar
  42. 42.
    Block JP, Scribner RA, DeSalvo KB. Fast food, race/ethnicity, and income: a geographic analysis. Am J Prev Med. 2004; 27(3): 211–217.PubMedGoogle Scholar
  43. 43.
    Franco M, Diez Roux AV, Glass TA, Caballero B, Brancati FL. Neighborhood characteristics and availability of healthy foods in Baltimore. Am J Prev Med. 2008; 35(6): 561–567.PubMedCrossRefGoogle Scholar
  44. 44.
    Moore LV, Diez Roux AV. Associations of neighborhood characteristics with the location and type of food stores. Am J Public Health. 2006; 96(2): 325–331.PubMedCrossRefGoogle Scholar
  45. 45.
    Kelly CM, Schootman M, Baker EA, Barnidge EK, Lemes A. The association of sidewalk walkability and physical disorder with area-level race and poverty. J Epidemiol Commun Health. 2007; 61(11): 978–983.CrossRefGoogle Scholar
  46. 46.
    Cliff AD, Ord JK. Spatial processes: models and applications. Bristol, PA: Taylor & Francis; 1981.Google Scholar
  47. 47.
    Clifford P, Richardson S. Testing the association between two spatial processes. Stat Decis. 1985; 2: 155–160.Google Scholar
  48. 48.
    Student. The elimination of spurious correlation due to position in time or space. Biometrika 1914;10(1):179–180.Google Scholar
  49. 49.
    Haining R. Bivariate correlation with spatial data. Geogr Anal. 1991; 23(3): 210–227.CrossRefGoogle Scholar
  50. 50.
    Anselin L. Lagrange multiplier test diagnostics for spatial dependence and spatial heterogeneity. Geogr Anal. 1988; 20(1): 1–17.CrossRefGoogle Scholar
  51. 51.
    Bivand RS, Pebesma EJ, Gómez-Rubio V. Applied spatial data analysis with R. New York: Springer; 2008.Google Scholar
  52. 52.
    Kelejian HH, Prucha I. Generalized moments estimator for the autoregressive parameter in a spatial model. Int Econ Rev. 1999; 40(2): 509–533.CrossRefGoogle Scholar
  53. 53.
    Anselin L, Bera AK, Florax R, Yoon MJ. Simple diagnostic tests for spatial dependence. Reg Sci Urban Econ. 1996; 26(1): 77–104.CrossRefGoogle Scholar
  54. 54.
    Akaike H. A new look at the statistical model identification. IEEE Trans Autom Control. 1974; 19(6): 716–723.CrossRefGoogle Scholar
  55. 55.
    Pace K, LeSage JP. A spatial Hausman test. Econ Lett. 2008; 101(3): 282–284.CrossRefGoogle Scholar
  56. 56.
    Reardon SF. A conceptual framework for measuring segregation and its association with population outcomes. In: Oakes JM, Kaufman JS, eds. Methods in social epidemiology. San Francisco: Jossey-Bass; 2006: 169–192.Google Scholar
  57. 57.
    Frank AI. Using measures of spatial autocorrelation to describe socio-economic and racial residential patterns in US urban areas. In: Kidner D, Higgs G, White S, eds. Socio-economic applications of geographic information science (innovations in GIS). London: Taylor & Francis; 2003: 147–162.Google Scholar
  58. 58.
    Duncan DT, Aldstadt J, Whalen J, Melly SJ. Validation of walk scores and transit scores for estimating neighborhood walkability and transit availability: a small-area analysis. GeoJournal; 2012. doi: 10.1007/s10708-011-9444-4.
  59. 59.
    Duncan DT, Aldstadt J, Whalen J, Melly SJ, Gortmaker SL. Validation of walk score for estimating neighborhood walkability: an analysis of four US metropolitan areas. Int J Environ Res Public Health. 2011; 8(11): 4160–4179.PubMedCrossRefGoogle Scholar
  60. 60.
    Talen E, Anselin L. Assessing spatial equity: an evaluation of measures of accessibility to public playgrounds. Environ Plan A. 1998; 30: 595–613.CrossRefGoogle Scholar
  61. 61.
    Loukaitou-Sideris A, Stieglitz O. Children in Los Angeles parks: a study of equity, quality and children’s satisfaction with neighbourhood parks. Town Plan Rev. 2002; 73(4): 467–488.CrossRefGoogle Scholar
  62. 62.
    Powell L, Slater S, Chaloupka F. The relationship between community physical activity settings and race, ethnicity and socioeconomic status. Evid Based Prev Med. 2004; 1(2): 135–144.Google Scholar
  63. 63.
    Wolch J, Wilson JP, Fehrenbach J. Parks and park funding in Los Angeles: an equity-mapping analysis. Urban Geogr. 2005; 26(1): 4–35.CrossRefGoogle Scholar
  64. 64.
    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): 417–424.PubMedCrossRefGoogle Scholar
  65. 65.
    Powell LM, Slater S, Chaloupka FJ, Harper D. Availability of physical activity-related facilities and neighborhood demographic and socioeconomic characteristics: a national study. Am J Public Health. 2006; 96(9): 1676–1680.PubMedCrossRefGoogle Scholar
  66. 66.
    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): 100–104.PubMedCrossRefGoogle Scholar
  67. 67.
    Duncan DT, Castro MC, Gortmaker SL, Aldstadt J, Melly SJ, Bennett GG. Racial differences in the built environment–body mass index relationship? A geospatial analysis of adolescents in urban neighborhoods. Int J Health Geogr. 2012; 11(1): 11.PubMedCrossRefGoogle Scholar
  68. 68.
    Hoehner CM, Schootman M. Concordance of commercial data sources for neighborhood-effects studies. J Urban Health. 2010; 87(4): 713–725.PubMedCrossRefGoogle Scholar
  69. 69.
    Oreskovic NM, Winickoff JP, Kuhlthau KA, Romm D, Perrin JM. Obesity and the built environment among Massachusetts children. Clin Pediatr (Phila). 2009; 48(9): 904–912.CrossRefGoogle Scholar
  70. 70.
    Boone JE, Gordon-Larsen P, Stewart JD, Popkin BM. Validation of a GIS facilities database: quantification and implications of error. Ann Epidemiol. 2008; 18(5): 371–377.PubMedCrossRefGoogle Scholar
  71. 71.
    Brownson RC, Hoehner CM, Day K, Forsyth A, Sallis JF. Measuring the built environment for physical activity: state of the science. Am J Prev Med. 2009; 36(4 Suppl): S99–123 e112.PubMedCrossRefGoogle Scholar
  72. 72.
    Openshaw S, Taylor P. A million or so correlation coefficients: three experiments on the modifiable area unit problem. In: Wrigley N, ed. Statistical applications in the spatial sciences. London: Pion Ltd; 1979: 127–144.Google Scholar
  73. 73.
    Wong D. The modifiable areal unit problem (MAUP). In: Fotheringham AS, Rogerson PA, eds. The SAGE handbook of spatial analysis. London: SAGE Publications; 2009: 105–124.CrossRefGoogle Scholar
  74. 74.
    Li W, Kelsey JL, Zhang Z, et al. Small-area estimation and prioritizing communities for obesity control in Massachusetts. Am J Public Health. 2009; 99(3): 511–519.PubMedCrossRefGoogle Scholar
  75. 75.
    Li W, Land T, Zhang Z, Keithly L, Kelsey JL. Small-area estimation and prioritizing communities for tobacco control efforts in Massachusetts. Am J Public Health. 2009; 99(3): 470–479.PubMedCrossRefGoogle Scholar
  76. 76.
    Reynolds H, Amrhein C. Using a spatial data set generator in an empirical analysis of aggregation effects on univariate statistics. Geogr Environ Model. 1997; 1: 199–220.Google Scholar
  77. 77.
    Weiss CC, Purciel M, Bader M, et al. Reconsidering access: park facilities and neighborhood disamenities in New York City. J Urban Health. 2011; 88(2): 297–310.PubMedCrossRefGoogle Scholar
  78. 78.
    Matthews SA. Spatial polygamy and the heterogeneity of place: studying people and place via egocentric methods. In: Burton LM, Kemp SP, Leung M, Matthews SA, Takeuchi DT, eds. Communities, neighborhoods, and health: expanding the boundaries of place. New York, NY: Springer; 2011: 35–55.CrossRefGoogle Scholar
  79. 79.
    Ries AV, Gittelsohn J, Voorhees CC, Roche KM, Clifton KJ, Astone NM. The environment and urban adolescents’ use of recreational facilities for physical activity: a qualitative study. Am J Health Promot. 2008; 23(1): 43–50.PubMedCrossRefGoogle Scholar
  80. 80.
    Rothwell JT. Racial enclaves and density zoning: the institutionalized segregation of racial minorities in the United States. Am Law Econ Rev. 2011; 13(1): 290–358.CrossRefGoogle Scholar
  81. 81.
    Perry C. The neighbourhood unit (1929). Reprinted Routledge/Thoemmes: London; 1998.Google Scholar
  82. 82.
    Cohen DA, Sehgal A, Williamson S, Marsh T, Golinelli D, McKenzie TL. New recreational facilities for the young and the old in Los Angeles: policy and programming implications. J Public Health Policy. 2009; 30(Suppl 1): S248–S263.PubMedCrossRefGoogle Scholar
  83. 83.
    Gustat J, Rice J, Parker KM, Becker AB, Farley TA. Effect of changes to the neighborhood built environment on physical activity in a low-income African American neighborhood. Prev Chronic Dis. 2012; 9: E57.PubMedGoogle Scholar
  84. 84.
    Bhatia R. Protecting health using an environmental impact assessment: a case study of San Francisco land use decision making. Am J Public Health. 2007; 97(3): 406–413.PubMedCrossRefGoogle Scholar
  85. 85.
    Dannenberg AL, Bhatia R, Cole BL, Heaton SK, Feldman JD, Rutt CD. Use of health impact assessment in the U.S.: 27 case studies, 1999–2007. Am J Prev Med. 2008; 34(3): 241–256.PubMedCrossRefGoogle Scholar

Copyright information

© The New York Academy of Medicine 2012

Authors and Affiliations

  • Dustin T. Duncan
    • 1
    Email author
  • Ichiro Kawachi
    • 1
  • Kellee White
    • 2
  • David R. Williams
    • 1
    • 3
  1. 1.Departments of Society, Human Development, and HealthHarvard School of Public HealthBostonUSA
  2. 2.Department of Epidemiology and Biostatistics, Arnold School of Public HealthUniversity of South CarolinaColumbiaUSA
  3. 3.Departments of African and African American Studies, and SociologyHarvard UniversityCambridgeUSA

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