Multimorbidity, disability, and mortality in community-dwelling older adults.
Bibliographic record
Abstract
OBJECTIVE: To describe factors associated with multimorbidity in community-dwelling older adults; to determine if a simple measure of multimorbidity predicts death over 5 years; and to assess if any effect of multimorbidity on mortality is independent of key covariates. DESIGN: Analysis of an existing population-based cohort study. Cox proportional hazards models were constructed for time to death. SETTING: Manitoba. PARTICIPANTS: A total of 1751 community-dwelling adults aged 65 and older were interviewed and followed for 5 years. MAIN OUTCOME MEASURES: Age, sex, marital status, living arrangement, education, Mini-Mental State Examination (MMSE) score, Center for Epidemiologic Studies Depression Scale score, and the Older Americans Resource and Services Multidimensional Functional Assessment Questionnaire score were recorded for each participant. Multimorbidity was defined based on a simple list of common health complaints and diseases, followed by an open-ended question about other problems. These were summed and the scores ranged from 0 to 16. Death and time of death were determined during the 5-year interval by death certificate, administrative data, or proxy report. RESULTS: Multimorbidity was more prevalent in women; older age groups; and those with lower educational levels, lower MMSE scores, more depressive symptoms, and higher levels of disability. Multimorbidity was a predictor of mortality in unadjusted models (hazard ratio 1.09, 95% CI 1.05 to 1.12). In models adjusting for age, sex, education, marital status, living arrangement, and Center for Epidemiologic Studies Depression Scale and MMSE scores, this effect persisted (hazard ratio 1.04, 95% CI 1.00 to 1.08). However, after adjusting for functional status, the effect of multimorbidity was no longer significant. CONCLUSION: Multimorbidity predicts 5-year mortality but the effect might be mediated by 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 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".