Individual and population level impact of chronic conditions on functional disability in older adults
Bibliographic record
Abstract
BACKGROUND: It is unknown if the relationship between multimorbidity and disability differs by combinations of chronic conditions. The objective of our study was to elucidate how joint effect of different combinations of chronic conditions impact the five year risk of functional disability at the population level. METHODS: Participants ≥65 years from the Canadian Study of Health and Aging were assessed for functional disability measured using activities of daily living (ADL) and instrumental ADL (IADL), and the presence of conditions in five disease domains; cardiometabolic, neurological, sensory, musculoskeletal, and respiratory. Logistic regression was used to assess the relationship between each disease domain and incident ADL and IADL measured at five years of follow up and population attributable risk (PAR) was modeled for diseases domains that were significantly associated with disability. Results were stratified by sex and age (65-74 years, ≥75 years). RESULTS: There were 6272 participants free of ADL disability and 4571 participants free from IADL disability at baseline. For incident ADL, the greatest PAR values were 21.3 (9.8-32.8) for the cardiometabolic domain in males 65-74 years, 22.7 (4.7-40.8) for the musculoskeletal domain for females aged 65-74 years, and 11.2 (2.8-19.7) for the musculoskeletal domain in males ≥75 years. The PAR for the musculoskeletal, sensory, and neurological domains were similar in females ≥75 years(9.3-9.9). PAR values were lower but followed similar patterns for IADL disability. CONCLUSION: The chronic disease domains which most strongly predicted incident ADLs and IADLs did not account for the greatest amount of disability at the population level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".