Evaluating Linkage Approaches for Address-Level Socioenvironmental Exposure Assessment

评估地址级社会环境暴露评估的关联方法

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Abstract

Accurate linkage of addresses to parcel-level data is essential for hyperlocal environmental exposure assessment, yet the performance of methods, including their impact on exposure misclassification and bias, remains poorly characterized. Using a gold standard match of 853,255 National Address Database records to authoritative datasets from Hamilton and Franklin Counties, Ohio, we evaluated address tag fuzzy matching and geocoding-based (geomatching) approaches on accuracy of linked parcel identifier and parcel market total value and usage type. Address tag fuzzy matching achieved 100% agreement; address point geomatching performed moderately well (65.1% - 76.1%), and street range geomatching performed poorly (7.2% - 59.2%). Poorer agreement was more common in neighborhoods with higher address densities and more community material deprivation, highlighting potential for differential misclassification of exposure assessment. These findings emphasize a need for precise, scalable, and standardized linkage approaches to support valid address- and parcel-level exposure assessment in clinical and population health research.

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