Functional limitations in people with multimorbidity and the association with mental health conditions: Baseline data from the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
INTRODUCTION: Increasing multimorbidity is often associated with declining physical functioning, with some studies showing a disproportionate impact on functioning when mental health conditions are present. More research is needed because most multimorbidity studies exclude mental health conditions. OBJECTIVES: This study aims to improve our understanding of the association between functional limitation and multimorbidity, including a comparison of those with multimorbidity that includes versus excludes mental health conditions. METHODS: This is a population-based, cross-sectional analysis of data from The Canadian Longitudinal Study on Aging. Functional limitation was defined as the presence of any of 14 activities of daily living (ADLs) or instrumental activities of daily living (IADLs). Multimorbidity, measured by the number of chronic conditions, included mood and anxiety disorders. Logistic regression explored the association between multimorbidity (with and without mental health conditions) and functional limitation. Factor analysis identified common condition clusters to help understand clinical complexity in those with mood/anxiety disorders and the potential influences on functional limitation. RESULTS: There were 51,338 participants, with a similar proportion of men and women (49% versus 51%) and 42% age 65 years or older. Fifteen percent (15%) had no chronic conditions and 17% had 5+. Ten percent (10%) reported at least one ADL or IADL limitation. Odds ratios (ORs) for functional limitation increased with multimorbidity and were generally higher for those with versus without mental health conditions (e.g., ORs from 1 to 5+ chronic conditions increased 1.9 to 15.8 for those with mood/anxiety disorders versus 1.8 to 10.2 for those without). Factor analysis showed that mood/anxiety conditions clustered with somatic conditions (e.g., migraines, bowel/gastrointestinal disorders). CONCLUSION: This study found higher odds of functional limitation for those with multimorbidity that included versus excluded mental health conditions, at all levels of multimorbidity. It highlights the need for concurrent management of mental and physical comorbidities to prevent functional limitations and future decline. This approach is aligned with the NICE clinical assessment and management guidelines for people with multimorbidity.
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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 | 0.001 | 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) | 0.000 | 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".