Reproducible Area Deprivation Index (ReADI)

Methodology

About the Reproducible Area Deprivation Index (ReADI)
The Reproducible Area Deprivation Index (ReADI) is a transparent, factor-based measure of neighborhood socioeconomic deprivation designed to improve the reproducibility, comparability, and interpretability of traditional Area Deprivation Index (ADI) measures. ReADI summarizes socioeconomic disadvantage using publicly available U.S. Census and American Community Survey data and is intended to support research, public health monitoring, and policy analysis across geographic scales.

ReADI is constructed from 17 socioeconomic indicators spanning four conceptual domains: education, income and employment, housing, and household characteristics. Index scores are derived using a single-factor model, with factor scores extracted directly from the standardized factor analysis output. Population-based weights are incorporated to reflect differences in population size across geographic units and to improve comparability across areas.

ReADI values are reported as national percentile ranks ranging from 0 to 100, where lower values indicate less deprivation and higher values indicate greater socioeconomic disadvantage. National ranks reflect each area’s position relative to all areas nationwide. Unlike some ADI implementations, ReADI re-estimates factor loadings for each data release to ensure that index construction reflects contemporary socioeconomic conditions rather than fixed historical weights.

County and Tract-Level Scores
For tract- and county-level geographies, ReADI scores are calculated as population-weighted averages of underlying census block-group ReADI scores, using total population from the Decennial Census. This approach preserves consistency across geographic scales while maintaining the interpretability of the index.

For additional documentation, methodology details, and reproducible code, please visit the ReADI project website.