Errors in postcode to enumeration district mapping and their effect on small area analyses of health data

J Public Health Med. 1998 Sep;20(3):325-30. doi: 10.1093/oxfordjournals.pubmed.a024776.


Background: Health research often seeks to associate individuals to their socio-economic circumstances by linking an individual's postcode to their Census enumeration district (ED). As part of a study into health visitor resource allocation the objective here is to quantify the errors that arise in attaching ED level deprivation scores to records and counts of records by ED when records are matched to EDs via their postcodes rather than their exact address.

Methods: The result of routine matching of postcodes to EDs was compared with the more accurate method of matching addresses to EDs. Townsend scores were then attributed to records according to the two different methods and the results compared. A sample of 4013 births registered in Sheffield in 1996 was used.

Results: The comparative work showed that the mismatching of individual addresses arising from matching postcodes to EDs was 16.4 per cent. (The 95 per cent confidence interval is 15.1-17.7 per cent.) Over one-third of mismatched records (about 6 per cent of the total records) were found to have Townsend scores greater than +/- 2 compared with the score obtained through the more accurate process of address matching.

Conclusions: The evidence of the study is that it is important to recognize there are errors inherent in matching individual addresses to EDs via the address postcode. For problems involving resource allocation and for research into relationships between health outcomes or service uptake and deprivation it may be necessary to seek to quantify the level of error introduced through using postcode to ED matching.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bias*
  • Censuses*
  • Data Interpretation, Statistical*
  • England / epidemiology
  • Epidemiologic Studies
  • Humans
  • Postal Service / statistics & numerical data*
  • Poverty Areas*
  • Small-Area Analysis
  • Socioeconomic Factors
  • Wales / epidemiology