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Misclassification errors from postal code-based geocoding to assign census geography in Nova Scotia, Canada.

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Geocoding Canadian postal codes to census geography causes significant misclassification errors, particularly in non-urban areas. Accurate health data analysis requires using precise location data like civic addresses or coordinates instead.

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Area of Science:

  • Geographic Information Systems (GIS)
  • Public Health Data Analysis
  • Spatial Epidemiology

Background:

  • Postal codes are frequently the sole geographic identifiers in Canadian health datasets.
  • Geocoding postal codes to census geography is standard practice for linking health data with ecological information.
  • The accuracy and extent of geographic misclassification errors associated with postal code geocoding remain poorly understood.

Purpose of the Study:

  • To estimate the extent of misclassification errors when geocoding postal codes to census geography in Nova Scotia, Canada.
  • To assess the impact of rurality on these geocoding errors.

Main Methods:

  • Compared counts and match rates of postal-code geocoded locations against actual building locations in Nova Scotia.
  • Analyzed data at two census administrative levels: dissemination areas (DAs) and census subdivisions (CSDs).
  • Utilized provincial government data with actual building latitude/longitude and Statistics Canada's rurality classification.

Main Results:

  • Significant misclassification errors were observed, with many non-urban DAs showing >30% differences in counts and <40% match rates.
  • Even urban areas exhibited substantial errors, with 10% of DAs having large misclassification issues.
  • Misclassification errors at the CSD level were too high for reliable analysis without further aggregation.

Conclusions:

  • Routine reliance on postal code geocoding for health data analysis should be discontinued.
  • Geocoding using more precise identifiers like civic addresses or latitude/longitude is recommended.
  • In-house geocoding by data holders using enhanced identifiers would improve geographic analysis accuracy and protect confidentiality.