Association between depression and incident dementia: Longitudinal findings from the share study
Bibliographic record
Abstract
BACKGROUND: The association between depression and dementia is still unclear, particularly regarding depression as a potential risk factor preceding dementia. Therefore, we aimed to verify if the presence of depression at baseline may increase the risk of dementia and cognitive impairment during 15 years of follow-up in the SHARE (Survey of Health, Aging and Retirement in Europe) study. METHODS: Depressive symptoms were defined using the EURO-D, with a score ≥4 indicative of depression. Incident dementia was ascertained using self-reported data and caregivers' information, cognitive impairment using objective cognitive tests. Cox regression analysis, adjusted for 10 baseline confounders, was run and hazard ratios (HRs), with their 95% confidence intervals, were estimated. RESULTS: In total 22,789 participants were included in the present analysis (mean age 64.2 years) and were predominantly female. The prevalence of depression at baseline was 24.9%. Over 15 years of follow-up, the onset of dementia occurred a median 2 years earlier in people with depression compared to those without. Depression at the baseline significantly increased the risk of dementia in the overall sample (HR = 1.74; 95% CI: 1.54-1.95) and the risk of cognitive impairment (HR = 1.15; 95% CI: 1.06-1.25). For dementia, the association was stronger in people less than 60 years (HR = 2.07; 95% CI: 1.42-3.02) than in participants aged ≥80 years (HR = 1.47; 95% CI: 1.14-1.91). A similar trend was observed for cognitive impairment. Among the single items of the EURO-D, loss of concentration was the strongest individual variable predicting the onset of dementia. CONCLUSIONS: Depression increased the risk of dementia and cognitive impairment, particularly in younger adults, whereas loss of concentration was the strongest individual predicting variable of dementia. These findings demonstrate the need for early detection of depression for preventing future cognitive worsening.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".