Biological Age and 12-Year Cognitive Change in Older Adults: Findings from the Victoria Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: Although recent cross-sectional findings indicate that markers of biological age (BA) mediate chronological age (CA) differences in cognitive performance, little is known about their influence on actual cognitive changes. OBJECTIVE: The purpose of this investigation is to examine CA and BA as predictors of 12-year cognitive change in a longitudinal sample of older adults. METHODS: Data from the Victoria Longitudinal Study (VLS) were examined for 125 adults between 67 and 95 years of age. Biomarkers, including visual and auditory acuity, grip strength, peak expiratory flow, blood pressure, and body mass index, were submitted to a factor analysis and a composite BA variable was computed based on factor loadings. Intraindividual change across 5 waves of measurement (3-year intervals) was examined as a function of CA and BA for 5 cognitive domains: verbal processing speed, working memory, reasoning, episodic memory, and semantic memory. RESULTS: The latent structure of biomarkers was consistent with previous investigations of functional age and a common factor view of biological aging. Results of hierarchical linear modeling showed that BA predicted actual cognitive change (decline) independent of CA. CONCLUSIONS: As a predictor of cognitive performance in late life, CA is a proxy for biological and environmental influences. We have shown that biological influences are independent predictors of actual cognitive change in older adults. This supports the view that cognitive decline is not due to aging per se, but rather is likely due to causal factors that operate along the age continuum.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".