Black–White Racial Disparities in Disabilities Among Older Americans Between 2008 and 2017: Improvements in Cognitive Disabilities but no Progress in Activities of Daily Living or Functional Limitations
Bibliographic record
Abstract
The objectives of this study were to examine the prevalence of race-based disparities in cognitive problems, functional limitations (FLs), and activity of daily living (ADL) limitations between US Black and White older adults in 2008 and 2017, to explore how age, sex, income, and education attenuate these racial disparities, and to determine if Black–White health disparities are narrowing. Secondary analysis of the nationally representative American Community Surveys including 423,066 respondents aged ≥65 (388,602 White, 34,464 Black) in 2008 and 536,984 (488,483 White, 48,501 Black) in 2017. Findings indicate that Black–White racial disparities were apparent for all three outcomes in 2008 and 2017. Approximately half of the racial disparities was attenuated when adjustments were made for education and income. Racial disparities in cognition declined between 2008 and 2017 ( p < .001) but persisted unabated in FLs and ADL limitations. Further exploration on the mechanisms of racial disparities is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".