Disability Diagnoses Identified by the American Community Survey 6-Question Sequence.

Area of Science:

• Public Health
• Epidemiology
• Sociology of Health

Background:

• Federal disability data collection primarily uses the American Community Survey-6 (ACS-6) to identify individuals with disabilities through functional impairment questions.
• Little is known about the specific diagnoses captured by the ACS-6 or their consistency across different demographic subgroups.

Purpose of the Study:

• To characterize the disability diagnoses identified by the ACS-6.
• To assess the consistency of the population identified by the ACS-6 across demographic subgroups.

Main Methods:

• A cross-sectional study analyzed data from 13,341 individuals with disabilities in the 2023/2024 Survey of Income and Program Participation (SIPP).
• Prevalence of 36 diagnosis groupings from the ACS-6 was assessed overall, by individual questions, and across age, race/ethnicity, sex, and education, with further disaggregation by cognitive disability status.

Main Results:

• Anxiety/OCD, depression, musculoskeletal issues, back/spinal problems, and neurologic disorders were common diagnoses among working-age adults.
• Disability diagnoses identified by the ACS-6 showed variation across age groups.
• However, diagnoses were largely similar across demographic groups defined by sex, race/ethnicity, and educational attainment.

Conclusions:

• The ACS-6 identifies a consistent population across demographic subgroups, excluding age.
• Substantial heterogeneity exists within disability diagnoses across age groups and within subgroups.
• Future federal disability data collection revisions should consider this heterogeneity in survey design.