Depressive Trajectories and Risk of Disability and Mortality in Older Adults: Longitudinal Findings From the Health, Aging, and Body Composition Study
Bibliographic record
Abstract
BACKGROUND: Depression and disability are closely linked. Less is known regarding clinical and subclinical depressive symptoms over time and risk of disability and mortality. METHODS: Responses to the Center for Epidemiologic Studies Short Depression scale (CES-D10) were assessed over a 4-year period in men (n = 1032) and women (n = 1070) aged 70-79 years initially free from disability. Depressive symptom trajectories were defined with group-based models. Disability (2 consecutive reports of severe difficulty walking one-quarter mile or climbing 10 steps) and mortality were determined for 9 subsequent years. Hazard ratios (HRs) were estimated using Cox proportional hazards adjusted for covariates. RESULTS: Three trajectories were identified: persistently nondepressed (54% of men, 54% of women, mean baseline CES-D10: 1.16 and 1.46), mildly depressed and increasing (40% of men, 38% of women, mean baseline CES-D10: 3.60 and 4.35), and depressed and increasing (6% of men, 8% of women, mean baseline CES-D10: 7.44 and 9.61). Disability and mortality rates per 1,000 person years were 41.4 and 60.3 in men and 45.8 and 41.9 in women. Relative to nondepressed, men in the mildly depressed (HR = 1.45, 95% confidence interval [CI] 1.11-1.89) and depressed trajectories (HR = 2.12, 95% CI 1.33-3.38) had increased disability; women in the depressed trajectory had increased disability (HR = 2.02, 95% CI 1.37-2.96). Men in the mildly depressed (HR = 1.24, 95% CI 1.01-1.52) and depressed trajectories (HR = 1.63, 95% CI 1.10-2.41) had elevated mortality risk; women exhibited no mortality risk. CONCLUSIONS: Trajectories of depressive symptoms without recovery may predict disability and mortality in apparently healthy older populations, thus underscoring the importance of monitoring depressive symptoms in geriatric 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".