Associations Between Lifestyle and Cognitive Function Over Time in Women Aged 40–79 Years
Bibliographic record
Abstract
BACKGROUND: Smoking, excessive drinking, and physical inactivity are associated with reduced cognitive function but the independence, domain specific cognitive effects, and trajectories of these associations are not firmly established. OBJECTIVE: Our aim was to examine these lifestyle-cognitive function associations in middle-to-older aged women across time. METHODS: Cohort study design with repeat surveys (2001, 2005, and 2008). Participants were volunteers from a random sample of Australian women on the Brisbane electoral roll; mean (±SD) age 60 ± 11 years in 2001. Outcome measures were the Mini-Mental State Examination (MMSE), Auditory Delayed Index (ADI), Visual Delayed Index (VDI), Working Memory Index (WMI), and Processing Speed Index (PSI). RESULTS: 489 women completed cognitive testing in 2001, 451 in 2005, and 376 in 2008. Mean (±SD) cognitive scores in 2001 were MMSE: 29.1 ± 1.2, ADI: 104.6 ± 13.4, VDI: 107.2 ± 14.0, WMI: 104.1 ± 12.3, and PSI: 102.7 ± 11.8. Multivariate adjusted mean scores (95% CI) over the 7-year study period were higher for moderate drinkers than non-drinkers for the MMSE (β = 0.32; 0.04, 0.61), the VDI (β = 4.33; 0.96, 7.70), and the WMI (β = 3.21; 0.34, 6.07). Current smokers performed worse than never-smokers for the MMSE (β = -0.35; 0.64, -0.06), the VDI (β = -3.91; -7.57, -0.26), the WMI (β = -3.42; -6.67, -0.18), and the PSI (β = -5.89; -8.91, -2.87). PSI was higher in women performing strenuous physical activity compared to inactive women (β = 2.14; 0.37, 3.90). None of the three lifestyle parameters influenced the changes in cognition across time. CONCLUSIONS: Alcohol and exercise were associated with selective protective effects and tobacco with selective harmful effects on cognitive function in middle-to-older aged women. Associations remained consistent across time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".