Validation of a GIS facilities database: quantification and implications of error

Abstract

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 (kappa 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.

Figure 1. Illustration of count, positional, and attribute errors

Dark lines represent census block group boundaries; ✦ GPS location • Geocoded location A: Distance between geocoded and GPS locations is moderate, but they fall within the same block group. This error will contribute to positional error but not facility count within this block group. B: Geocoded and GPS locations are very close, contributing little positional error and no error to facility count. If the commercial database classifies this facility as a member facility, while the field census deemed it a public facility, it would contribute to attribute error. C: Distance between geocoded and GPS locations is moderate, but they fall into different block groups. This error will contribute to positional and facility count error within this block group. Further, if the upper right block group fell outside of the study area, this error will also contribute to the total count error.