BACKGROUND: Geographic information system (GIS)-based health studies require information on the physical location of data points, such as subject addresses. In a study of California women diagnosed with breast cancer between 1988 and 1997, we needed to locate the residential addresses of 4,537 women with post office boxes (POBs). METHODS: We investigated the feasibility of tracing street addresses for the POBs and examined potential selection biases and case attribute misclassifications introduced by different methods of handling POBs in GIS-based health studies. RESULTS: Our tracing method yielded street addresses for only 34% of POBs in our study. Examination of subjects' case characteristics revealed that boxholders were not representative of the full population. Geocoding using a POB's delivery-weighted five-digit zip code centroid, as a proxy for street address, resulted in case attribute misclassification for 81% of boxholders. CONCLUSIONS: Disease registries should modernize their infrastructure to complement GIS technologies. Epidemiologists should understand GIS data limitations and consider potential biases introduced by incomplete or inaccurate geocoding.
BACKGROUND: Geographic information system (GIS)-based health studies require information on the physical location of data points, such as subject addresses. In a study of California women diagnosed with breast cancer between 1988 and 1997, we needed to locate the residential addresses of 4,537 women with post office boxes (POBs). METHODS: We investigated the feasibility of tracing street addresses for the POBs and examined potential selection biases and case attribute misclassifications introduced by different methods of handling POBs in GIS-based health studies. RESULTS: Our tracing method yielded street addresses for only 34% of POBs in our study. Examination of subjects' case characteristics revealed that boxholders were not representative of the full population. Geocoding using a POB's delivery-weighted five-digit zip code centroid, as a proxy for street address, resulted in case attribute misclassification for 81% of boxholders. CONCLUSIONS: Disease registries should modernize their infrastructure to complement GIS technologies. Epidemiologists should understand GIS data limitations and consider potential biases introduced by incomplete or inaccurate geocoding.
Authors: Jennifer C Robinson; Sharon B Wyatt; DeMarc Hickson; Danielle Gwinn; Fazlay Faruque; Mario Sims; Daniel Sarpong; Herman A Taylor Journal: J Urban Health Date: 2010-01 Impact factor: 3.671
Authors: Jennifer S Sonderman; Michael T Mumma; Sarah S Cohen; Elizabeth L Cope; William J Blot; Lisa B Signorello Journal: Geospat Health Date: 2012-05 Impact factor: 1.212
Authors: Daniel W Goldberg; John P Wilson; Craig A Knoblock; Beate Ritz; Myles G Cockburn Journal: Int J Health Geogr Date: 2008-11-26 Impact factor: 3.918
Authors: James D Hibbert; Angela D Liese; Andrew Lawson; Dwayne E Porter; Robin C Puett; Debra Standiford; Lenna Liu; Dana Dabelea Journal: Int J Health Geogr Date: 2009-10-08 Impact factor: 3.918