Age and Gender Differences in the Relation of Chronic Diseases to Activity of Daily Living (ADL) Disability for Elderly South Koreans: Based on Representative Data
Bibliographic record
Abstract
OBJECTIVES: This study investigated the gender and age differential effect of major chronic diseases on activity of daily living (ADL) disability. METHODS: Surveyfreq and Surveylogistic regression analyses were employed on the 2005 Korean National Health and Nutrition Examination Survey (KNHANES) with a sample of 3609 persons aged 65-89. RESULTS: After adjusting for potential covariates, stroke, among elderly men more so than women, had a 2-3 times greater odds of engendering ADL disability in the 65-69 (p < 0.05) and 70-79 age groups (p < 0.01). In comparison to elderly women, cancer, diabetes, and incontinence in elderly men was associated with a higher risk of ADL disability in the 70-79 age group (p < 0.05), and this association was also observed for pulmonary disease in the 80-89 age group. Among elderly women, however, a significant association between incontinence and ADL disability was identified in all three age groups. In addition, this association was found in pulmonary disease and diabetes in elderly women aged 70-79 years. Significant gender differences were observed in the association between stroke in the 60-79 age group and cancer in the 70-79 age group. CONCLUSIONS: Age and gender differences were observed in the effect of chronic diseases on ADL disability.
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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 | 0.001 |
| 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".