Modifiable Risk Factors Associated With Cognitive Decline in Late Life Depression: Findings From the Canadian Longitudinal Study on Aging: Facteurs de risque modifiables associés au déclin cognitif dans la dépression en fin de vie : constatations de l'Étude longitudinale canadienne sur le vieillissement
Bibliographic record
Abstract
Objective Depression in later life is associated with a two-fold increased risk of dementia. It is not clear to what extent potentially modifiable risk factors account for this association. Method Older adults (age 50 + ) with objective health measures ( n = 14,014) from the Canadian Longitudinal Study on Aging were followed for a mean duration of 35 months. Linear regression analyses were used to determine if clinically significant depression (Centre for Epidemiologic Studies Depression scale score (CESD) ≥ 10) was associated with global cognitive decline, assessed with a neuropsychological battery during follow-up, and if modifiable risk factors mediated this association. Results Depression was associated with an excess of risk factors for cognitive decline including: vascular disease, hypertension, diabetes, apnoea during sleep, higher body mass index, smoking, physical inactivity and lack of social participation. In regression analyses depression remained independently associated with cognitive decline over time (beta −0.060, P = 0.038) as did cerebrovascular disease (beta −0.197, P < 0.001), HbA1C (beta −0.059, P < 0.001), visual impairment (beta −0.070, P = 0.007), hearing impairment (beta −0.098, P < 0.001) and physical inactivity (beta −0.075, P = 0.014). In mediation analyses, we found that cerebrovascular disease ( z = −3.525, P < 0.001), HbA1C ( z = −4.976, P < 0.001) and physical inactivity ( z = −3.998, P < 0.001) partially mediated the association between depression and cognitive decline. Conclusions In this large sample of Canadian older adults incorporating several objective health measures, older adults with depression were at increased risk of cognitive decline and had an excess of potentially modifiable risk factors. Clinicians should pay particular attention to control of diabetes, physical inactivity and risk factors for cerebrovascular disease in older adults presenting with depression as they can contribute to accelerated cognitive decline and may be addressed during routine clinical care.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".