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Use of multilevel frameworks and area-based socioeconomic measures (ABSMs) for public health monitoring can potentially overcome the absence of socioeconomic data in most US public health surveillance systems. To assess whether ABSMs can meaningfully be used for diverse race/ethnicity-gender groups, we geocoded and linked public health surveillance data from Massachusetts and Rhode Island to 1990 block group, tract, and zip code ABSMs. Outcomes comprised death, birth, cancer incidence, tuberculosis, sexually transmitted infections, childhood lead poisoning, and nonfatal weapons-related injuries. Among White, Black, and Hispanic women and men, measures of economic deprivation (e.g., percentage below poverty) were most sensitive to expected socioeconomic gradients in health, with the most consistent results and maximal geocoding linkage evident for tract-level analyses.
Krieger et al. (2003) studied this question.