Annals of Epidemiology
Volume 18, Issue 5 , Pages 371-377, May 2008

Validation of a GIS Facilities Database: Quantification and Implications of Error

  • Janne E. Boone, MPH

      Affiliations

    • Department of Nutrition, Schools of Public Health & Medicine, University of North Carolina at Chapel Hill
    • Carolina Population Center, University of North Carolina at Chapel Hill
  • ,
  • Penny Gordon-Larsen, PhD

      Affiliations

    • Department of Nutrition, Schools of Public Health & Medicine, University of North Carolina at Chapel Hill
    • Carolina Population Center, University of North Carolina at Chapel Hill
    • Corresponding Author InformationCorrespondence and reprint requests to: Penny Gordon-Larsen, PhD, University of North Carolina at Chapel Hill, Carolina Population Center, University Square, 123 W Franklin St, Chapel Hill, NC 27516-3997. Tel.: 919-843-9966; fax: 919-966-9159.
  • ,
  • James D. Stewart, MA

      Affiliations

    • Carolina Population Center, University of North Carolina at Chapel Hill
  • ,
  • Barry M. Popkin, PhD

      Affiliations

    • Department of Nutrition, Schools of Public Health & Medicine, University of North Carolina at Chapel Hill
    • Carolina Population Center, University of North Carolina at Chapel Hill

Received 17 July 2007; accepted 14 November 2007. published online 13 February 2008.

Purpose

To validate a commercial database of community-level physical activity facilities that can be used in future research examining associations between access to physical activity facilities and individual-level physical activity and obesity.

Methods

Physical activity facility characteristics and locations obtained from a commercial database were compared to a field census conducted in 80 census block groups within two U.S. communities. Agreement statistics, agreement of administratively defined neighborhoods, and distance between locations were used to quantify count, attribute, and positional error.

Results

There was moderate agreement (concordance: nonurban: 0.39; urban: 0.46) of presence of any physical activity facility and poor to moderate agreement (κ range: 0.14 to 0.76) of physical activity facility type. The mean Euclidean distance between commercial database versus field census locations was 757 and 35 m in the nonurban and urban communities, respectively. However, 94% and 100% of nonurban and urban physical activity facilities, respectively, fell into the same 5-digit ZIP code, dropping to 92% and 98% in the same block group and 71% along the same street.

Conclusions

Our findings suggest that the commercial database of physical activity facilities may contain appreciable error, but patterns of error suggest that built environment-health associations are likely biased downward.

Key Words: Geographic Information Systems, Validation Studies, Environment Design

Selected Abbreviations and Acronyms: GIS, geographic information system, GPS, global positioning system, SIC, Standard Industrial Classification (codes), UTM, Universal Transverse Mercator, YMCA, Young Men's Christian Association, YWCA, Young Women's Christian Association

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PII: S1047-2797(07)00487-5

doi:10.1016/j.annepidem.2007.11.008

Annals of Epidemiology
Volume 18, Issue 5 , Pages 371-377, May 2008