Prevalence of the Activities of Daily Living Disability among Seniors in China: A Meta-Analysis
Bibliographic record
Abstract
This meta-analysis aimed to systematically assess the prevalence of Activities of Daily Living (ADL) disability among elderly in China. Two reviewers conducted a meta-analysis using articles available in nine databases. Methods: The Newcastle–Ottawa Scale (NOS) was used to assess the quality of the studies. The random-effects model was used to estimate the prevalence of ADL disability. The source of heterogeneity among subgroups was determined by subgroup analysis of different parameters. Publication bias was assessed using a funnel plot and Egger test. A total of 100 studies involving 291235 subjects were included. The aggregate prevalence of ADL disability was 31.7% (95% CI = 28.2%–35.2%). The prevalence rate of IADL disability was 43.3% (95% CI: 30.5%–56.1%), and that of PADL disability was 14.4% (95% CI: 7.8%–20.7%). The prevalence of male was 17.9% (95%CI: 17.6%–18.1%), and that of female was 21.4% (95%CI: 21.1%–21.6%). For subgroup analysis by age, the prevalence of disability was 10.8% (95% CI: 10.5%–11.0%) in 60–69 year-old participants, 21.2% (95% CI: (20.8%–21.6%) in 70–79 year-old participants, and 47.0% (95% CI: (46.2%–47.8%) in participants aged ≥80 years. The prevalence of ADL disability in married elderly was 13.4% (95% CI: 13.1%–13.6%), and that in single elderly was 29.7% (95% CI: 29.2%–30.2%). The prevalence rate of chronic ADL disability was 29.6% (95%CI: 29.2%–30.0%), and that of non-chronic ADL disability was (15.9% CI: 15.5%–16.4%). The prevalence of living alone ADL disability was 19.6% (95% CI: 19.0%–20.2%), and that of living with their families or living in institutions was 18.5% (95% CI: 18.2%–18.7%). The prevalence rates were 28.6% (95% CI: 28.1%–29.1%), 19.1% (95% CI: 18.5 %–19.8%), and 18.8% (95% CI: 17.4%–20.2%) among primary school graduates to university graduates. Given the high prevalence of ADL disability and its negative health outcomes, preventive measures need to be implemented for the high-risk group. Our study may help the development of strategies for ADL disability management.
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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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.058 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".