Disability Statistics

All States Parties to the UN Convention on the Rights of Persons with Disabilities commit to collecting appropriate information, including statistical and research data, to enable them to formulate and implement policies (Article 31). This page centers disabled people’s expertise and supports data collection that serves disabled communities.

Reliable statistics are fundamental to understanding disability prevalence, disparities, access gaps, and unmet needs. But data must be collected thoughtfully, analyzed carefully, and interpreted with awareness of limitations.

Why Good Disability Statistics Matter

Quality disability data serves multiple purposes:

Revealing the size and diversity of disabled populations across different contexts and communities
Exposing disparities in employment, education, health, housing, and social inclusion
Supporting policy advocacy by documenting needs and outcomes
Tracking progress toward inclusion, accessibility, and rights implementation
Allocating resources effectively to programs and services

Without good data, disabled people remain invisible in policy decisions and resource allocation.

Key Global Standards and Tools

Washington Group on Disability Statistics

The Washington Group developed internationally recognized question sets to measure disability prevalence and functioning consistently across countries. Their Short Set of six questions assesses functioning in seeing, hearing, mobility, cognition, communication, and self-care.

Key features:

Based on WHO’s International Classification of Functioning, Disability, and Health (ICF)
Designed for comparability across countries and cultures
Adopted by the UN Statistical Commission for census and survey use
Used in over 100 countries worldwide

The Washington Group also offers extended question sets, child functioning modules (developed with UNICEF), and labor force survey modules.

Website: Washington Group on Disability Statistics

World Health Organization Tools

WHO supports disability data collection through several frameworks:

Model Disability Survey (MDS): Comprehensive population survey providing detailed information on disability distribution
Brief MDS: Shorter version suitable for integration into existing household surveys
Functioning and Disability Disaggregation Tool (FDD11): Supports disaggregation of data by disability status

Website: WHO Collection of Data on Disability

Common Challenges and Pitfalls

Disability data collection often faces significant problems:

Methodological Issues

Using inappropriate or medical-model questions that miss social barriers
Underrepresenting certain disabilities (cognitive, mental health, episodic, or less visible conditions)
Excluding disabled people from sample frames or making participation inaccessible
Relying on proxy respondents who may not accurately represent disabled people’s experiences

Interpretation Issues

Misinterpreting functioning data as individual “deficits” rather than outcomes of social barriers
Ignoring intersectional disparities (race, gender, socioeconomic status, geography)
Aggregating data in ways that hide important differences between disability types
Treating all disabled people as a homogeneous group

Ethical Issues

Collecting data without involving disabled communities in design or interpretation
Using data to restrict rather than expand rights and access
Failing to share findings with the communities studied
Privacy and confidentiality concerns, especially for small populations

Best Practices for Researchers and Advocates

Data Collection

Use validated tools like Washington Group question sets when possible for comparability
Disaggregate data and cross-tabulate by disability status plus other demographics to reveal inequities
Combine quantitative and qualitative methods — statistics alone rarely tell full stories
Make data collection accessible to disabled participants (multiple formats, accommodations, flexible timing)
Engage disabled communities in design, collection, interpretation, and dissemination

Data Use

Respect privacy and confidentiality, especially when publishing data about small or identifiable populations
Apply social/rights-based frameworks when interpreting data — focus on barriers, not deficits
Acknowledge limitations clearly in any publication or presentation
Share findings with disabled communities in accessible formats
Use data to advocate for policy changes and resource allocation that benefit disabled people

Resources

Data Collection Standards

Washington Group Question Sets: Short Set, Extended Set, Child Functioning Module, and more
WHO Disability Data Collection: Model Disability Survey and related tools
UN Statistics Division Disability Guidelines: International standards for disability measurement

Data Sources

American Community Survey (ACS): U.S. disability data
Annual Disability Statistics Compendium: Comprehensive U.S. disability statistics
Eurostat Disability Data: European Union disability statistics

Guides and Toolkits

CBM Disability Data Advocacy Toolkit: Guidance on using and protecting disability data
USAID How to Collect Data on Disability: Practical guidance for data collection
AFB Resource Guide to Disability Statistics: Overview of U.S. and international data sources

This page centers disabled people’s expertise and supports data collection that serves disabled communities. For questions or to suggest additions, see How to Contribute.

Contribute to This Page

Have lived experience or expertise that could strengthen this page? We especially welcome perspectives on models not well represented here, including those from the Global South and Indigenous communities.

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This page centers disabled people’s expertise and is informed by disabled-led organizing globally. For questions or to suggest additions, see How to Contribute.