In spatial epidemiologic and public health research it is common to use spatially aggregated units such as centroids of postal/zip codes, census tracts, dissemination areas, blocks or block groups as proxies for sample unit locations. Few studies, however, address the potential problems associated with using these units as address proxies. The purpose of this study is to quantify the magnitude of distance errors and accessibility misclassification that result from using several commonly-used address proxies in public health research. The impact of these positional discrepancies for spatial epidemiology is illustrated by examining misclassification of accessibility to several health-related facilities, including hospitals, public recreation spaces, schools, grocery stores, and junk food retailers throughout the City of London and Middlesex County, Ontario, Canada. Positional errors are quantified by multiple neighborhood types, revealing that address proxies are most problematic when used to represent residential locations in small towns and rural areas compared to suburban and urban areas. Findings indicate that the shorter the threshold distance used to measure accessibility between subject population and health-related facility, the greater the proportion of misclassified addresses. Using address proxies based on large aggregated units such as centroids of census tracts or dissemination areas can result in very large positional discrepancies (median errors up to 343 and 2088 m in urban and rural areas, respectively), and therefore should be avoided in spatial epidemiologic research. Even smaller, commonly-used, proxies for residential address such as postal code centroids can have large positional discrepancies (median errors up to 109 and 1363 m in urban and rural areas, respectively), and are prone to misrepresenting accessibility in small towns and rural Canada; therefore, postal codes should only be used with caution in spatial epidemiologic research.
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