Best Practices in Demographic Data Collection for Equity, Diversity, and Inclusion in Rare Disease Research: A Systematic Review

PURPOSE: Rare diseases affect small, dispersed populations and are often studied through multisite designs where equity-relevant demographic data are essential for inclusive recruitment and accurate interpretation. This study examined how sociodemographic variables are collected and reported in rare disease research and evaluated their alignment with the PROGRESS-Plus framework, which outlines Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, social capital, and additional "Plus" factors such as age and disability status. METHODS: A systematic review of peer-reviewed articles was conducted alongside an environmental scan of demographic instruments from governmental, health-system, academic, and rare disease organizations. Screening and extraction coded variables as reported, indirectly derivable, or not reported and compared them with established standards. RESULTS: Of 647 records identified, 37 met inclusion criteria. Reporting was dominated by age and sex, while most other equity-relevant variables including gender identity, sexual orientation, race/ethnicity, distinctions-based Indigenous identity, socioeconomic position, language, migration, disability/function, religion, occupation, and social capital, were inconsistently captured. Environmental scan instruments were more comprehensive, revealing a capture-to-reporting gap. CONCLUSION: Demographic reporting in rare disease research is heterogeneous and insufficient for equity-focused analyses. A concise, standards-aligned sociodemographic dataset is needed to improve transparency, comparability, and detection of inequities across rare disease populations.

Authors

Institutions

Publication Details

Journal
Genetics in Medicine
Published
2026-05-01
DOI
https://doi.org/10.1016/j.gim.2026.102592
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Best Practices in Demographic Data Collection for Equity, Diversity, and Inclusion in Rare Disease Research: A Systematic Review

Israa Sinan, Molly Johnston, Ashish Marwaha
Genetics in Medicine
Genomics and Rare Diseases
article

Best Practices in Demographic Data Collection for Equity, Diversity, and Inclusion in Rare Disease Research: A Systematic Review

Israa Sinan, Molly Johnston, Ashish Marwaha
article en

Abstract

PURPOSE: Rare diseases affect small, dispersed populations and are often studied through multisite designs where equity-relevant demographic data are essential for inclusive recruitment and accurate interpretation. This study examined how sociodemographic variables are collected and reported in rare disease research and evaluated their alignment with the PROGRESS-Plus framework, which outlines Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, social capital, and additional "Plus" factors such as age and disability status. METHODS: A systematic review of peer-reviewed articles was conducted alongside an environmental scan of demographic instruments from governmental, health-system, academic, and rare disease organizations. Screening and extraction coded variables as reported, indirectly derivable, or not reported and compared them with established standards. RESULTS: Of 647 records identified, 37 met inclusion criteria. Reporting was dominated by age and sex, while most other equity-relevant variables including gender identity, sexual orientation, race/ethnicity, distinctions-based Indigenous identity, socioeconomic position, language, migration, disability/function, religion, occupation, and social capital, were inconsistently captured. Environmental scan instruments were more comprehensive, revealing a capture-to-reporting gap. CONCLUSION: Demographic reporting in rare disease research is heterogeneous and insufficient for equity-focused analyses. A concise, standards-aligned sociodemographic dataset is needed to improve transparency, comparability, and detection of inequities across rare disease populations.

Genetics in Medicine
University of Calgary (CA), Queens University (BD)
Reduced inequalities
Openalex Percentile: Top 11%
Genomics and Rare Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Best Practices in Demographic Data Collection for Equity, Diversity, and Inclusion in Rare Disease Research: A Systematic Review — Israa Sinan, Molly Johnston, et al. · Genetics in Medicine (2026) | TGRS Research Map | TGRS