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Methods for defining equity-stratifying variables: a systematic review of validation studies
Hana Osman1, Taylor Hecker1, Zarin Hossain1
1Department of Medicine, University of Calgary, Calgary, Canada.
Journal of Clinical Epidemiology
|July 15, 2026
Summary
This systematic review found varied accuracy in health data definitions for social disadvantage factors. More validation is needed to reliably measure health equity and social inequalities.
Area of Science:
- Epidemiology
- Health Informatics
- Social Determinants of Health
Background:
- Disease burden disproportionately affects socially disadvantaged populations.
- The PROGRESS-Plus framework categorizes key social determinants of health.
- Accuracy of case definitions for these variables in health data is largely unknown.
Purpose of the Study:
- Systematically review definitions and validation of PROGRESS-Plus variables in health data.
- Assess the application of equity-stratifying variables in epidemiologic studies.
- Evaluate data sources like administrative health, population-level, and EHR data.
Main Methods:
- Searched Medline, EMBASE, CINAHL, Web of Science, and Google Scholar up to 2024.
- Included validation studies of equity-stratifying variables in adults using administrative or EHR data.
- Extracted and synthesized data sources, algorithms, and performance measures; meta-analysis was not feasible due to heterogeneity.
Main Results:
- 116 studies were included from 9099 citations; most (55%) published 2019-2024.
- Race/ethnicity definitions were most common (57%), using codes or surname algorithms.
- High variability in performance measures (sensitivity, PPV, Cohen's Kappa) for race/ethnicity; lowest variation for occupation.
Conclusions:
- Increasing publications validate equity-stratifying variables, but performance measures vary widely.
- Significant heterogeneity in variable definitions and validation methods exists.
- Further rigorous validation of equity-stratifying variables in health data is essential.
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