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Related Experiment Videos

Accuracy of commercial geocoding: assessment and implications.

Eric A Whitsel1, P Miguel Quibrera, Richard L Smith

  • 1Department of Epidemiology, University of North Carolina, Cardiovascular Disease Program, Bank of America Center Suite 306, 137 East Franklin Street, Chapel Hill, NC 27514, USA. ewhitsel@email.unc.edu

Epidemiologic Perspectives & Innovations : EP+I
|July 22, 2006
PubMed
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Geocoding accuracy varies significantly by vendor and address type, impacting exposure assessment in health studies. Careful vendor selection and analysis adjustments are crucial for reliable spatial data.

Area of Science:

  • Environmental Epidemiology
  • Geographic Information Systems (GIS)
  • Biostatistics

Background:

  • Existing geocoding accuracy studies often lack scope, failing to account for address characteristics or impacts on exposure measures.
  • This study addresses these limitations within the Women's Health Initiative (WHI) Environmental Epidemiology of Arrhythmogenesis study.

Purpose of the Study:

  • To evaluate geocoding accuracy across multiple vendors and assess the influence of address characteristics on accuracy.
  • To examine the impact of geocoding inaccuracy on exposure measures in epidemiological research.

Main Methods:

  • Geocoded 3,615 addresses across 49 U.S. states using four vendors (A-D), comparing results to established coordinates.
  • Analyzed address match rates, census tract concordance, and coordinate distances (mean rho) across vendors.

Related Experiment Videos

  • Utilized mixed models to adjust for address characteristics, within-address correlation, and heteroscedasticity.

    • Main Results:

    • Significant vendor differences observed in match rates (30%-98%), census tract concordance (85%-98%), and coordinate accuracy (mean rho: 228-1809 meters).
    • Street-type matches showed minimal bias (mean rho 268-280m) among acceptable vendors (A-C), while centroid-type matches exhibited substantial, variable differences.
    • Geocoding inaccuracy (mean rho) increased misclassification of exposure (distance to highway), biasing associations with mortality toward the null.

    Conclusions:

    • Geocoding error is influenced by evaluation metrics, address attributes, and the chosen vendor.
    • Vendor selection involves a trade-off between data completeness and spatial accuracy.
    • Informed vendor selection and analytical adjustments are essential for mitigating geocoding error effects in health studies.