Older Asian Americans and Pacific Islanders with Activities of Daily Living (ADL) Limitations: Immigration and Other Factors Associated with Institutionalization
Bibliographic record
Abstract
This study determined the national prevalence and profile of Asian Americans with Activities of Daily Living (ADL) limitations and identified factors associated with institutionalization. Data were obtained from 2006 American Community Survey, which replaced the long-form of the US Census. The data are nationally representative of both institutionalized and community-dwelling older adults. Respondents were Vietnamese (n = 203), Korean (n = 131), Japanese (n = 193), Filipino (n = 309), Asian Indian (n = 169), Chinese (n = 404), Hawaiian/Pacific Islander (n = 54), and non-Hispanic whites (n = 55,040) aged 55 and over who all had ADL limitations. The prevalence of institutionalized among those with ADL limitations varies substantially from 4.7% of Asian Indians to 18.8% of Korean Americans with ADL limitations. Every AAPI group had a lower prevalence of institutionalization than disabled Non-Hispanic whites older adults (23.8%) (p < 0.001). After adjustment for socio-demographic characteristics, Asian Indians, Vietnamese, Japanese, Filipino, and Chinese had significantly lower odds of institutionalization than non-Hispanic whites (OR = 0.29, 0.31, 0.58, 0.51, 0.70, respectively). When the sample was restricted to AAPIs, the odds of institutionalization were higher among those who were older, unmarried, cognitively impaired and those who spoke English at home. This variation suggests that aggregating data across the AAPI groups obscures meaningful differences among these subpopulations and substantial inter-group differences may have important implications in the long-term care setting.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".