Error and Bias in Determining Exposure Potential of Children at School Locations Using Proximity-Based GIS Techniques

Abstract

BackgroundThe widespread availability of powerful tools in commercial geographic information system (GIS) software has made address geocoding a widely employed technique in spatial epidemiologic studies.ObjectiveThe objective of this study was to determine the effect of the positional error in geocoding on the analysis of exposure to traffic-related air pollution of children at school locations.MethodsFor a case study of Orange County, Florida, we determined the positional error of geocoding of school locations through comparisons with a parcel database and digital orthophotography. We used four different geocoding techniques for comparison to establish the repeatability of geocoding, and an analysis of proximity to major roads to determine bias and error in environmental exposure assessment.ResultsResults indicate that the positional error in geocoding of schools is very substantial: We found that the 95% root mean square error was 196 m using street centerlines, 306 m using TIGER roads, and 210 and 235 m for two commercial geocoding firms. We found bias and error in proximity analysis to major roads to be unacceptably large at distances of < 500 m. Bias and error are introduced by lack of positional accuracy and lack of repeatability of geocoding of school locations.ConclusionsThese results suggest that typical geocoding is insufficient for fine-scale analysis of school locations and more accurate alternatives need to be considered.

Error and Bias in Geocoding School and Students’ Home Addresses

“…The collective findings of Zandbergen and Green (2007) nonetheless differ from those based on a previously described 5% random sample of 2,608 street addresses from the Environmental Epidemiology of Arrhythmogenesis in WHI (EEAWHI) (Whitsel et al 2006). In that study, we found that the fraction of participants’ addresses determined to be < 100 m from the nearest highway was relatively constant across mean positional errors of 150–600 m, a finding driven by the counterbalance of approximately equal false positive and negative rates over the same range.…”

“…Zandbergen and Green (2007) recently described the effect of positional error on the distance between geocoded addresses and major roads, an often-used proxy for traffic-related exposures. They found a 200–500 m range of mean positional errors in their study of 126 Orange County, Florida, public school addresses, a somewhat higher range than that associated with geocodes assigned by four commercial vendors to a larger variety and number of street addresses in the 48 contiguous U.S. states (Whitsel et al 2006).…”

Influence of street reference data on geocoding quality

“…Results in urban areas are generally more accurate than in rural areas (Bonner et al 2003;Cayo and Talbot 2003;Ward et al 2005). The positional error in geocoded addresses may adversely affect spatial analytic methods (Waller 1996, Jacquez and Waller 2000, Burra et al 2002, Whitsel et al 2006, Griffith et al 2007, Zandbergen 2007, Zandbergen and Green 2007, Mazumdar et al 2008.…”

Evaluation of the positional difference between two common geocoding methods

“…This is known to be especially problematic for small area analysis (e.g. studies characterising neighbourhoods using finer spatial scales such as a 400 m buffer distance around participant residences) (Zimmerman and Sun, 2006;Whitsel et al, 2006;Zandbergen and Green, 2007;Mazumdar et al, 2008). The use of smaller spatial scales has surged in recent years in geospatial health studies, which may be due to increased interest in GIS and spatial analyses of health and health behaviour particularly at the individual level (Moore and Carpenter, 1999;Elliot et al, 2000;Cromley and McLafferty, 2002;Rushton, 2003); perhaps also due to criticisms associated with the use of administrative boundaries (e.g.…”

“…"In-house" geocoding may offer other important advantages, including improved technical transparency and facilitated input, possible cost savings and faster turnaround times (McElroy et al, 2003;Ward et al, 2005). Such rewards might be especially important in light of some evidence demonstrating that the accuracy of geocoding varies widely between different commercial geocoding firms (Krieger et al, 2001;Whitsel et al, 2004Whitsel et al, , 2006Zandbergen and Green, 2007). One study found that the use of a commercial geocoding firm did not improve geocoding accuracy as compared to geocoding data "in-house" with ArcGIS software (Environmental System Research Institute; Redlands, CA, USA) and in several instances the geocodes provided by the commercial firm had more positional error than that of those provided by ArcGIS (Ward et al, 2005).…”