Birth Cohorts and Cognitive Reserve Influence Cognitive Performances in Older Adults
Bibliographic record
Abstract
BACKGROUND: Evidence suggests birth cohort differences in cognitive performance of older adults. Proxies of cognitive reserve (CR), such as educational attainment and occupational complexity, could also partly account for these differences as they are influenced by the sociocultural environment of the birth cohorts. OBJECTIVE: To predict cognitive performance using birth cohorts and CR and examine the moderating influence of CR on cognitive performance and structural brain health association. METHODS: Using ADNI data (n = 1628), four birth cohorts were defined (1915-1928; 1929-1938; 1939-1945; 1946-1964). CR proxies were education, occupational complexity, and verbal IQ. We predicted baseline cognitive performances (verbal episodic memory; language and semantic memory; attention capacities; executive functions) using multiple linear regressions with CR, birth cohorts, age, structural brain health (total brain volume; total white matter hyperintensities volume) and vascular risk factors burden as predictors. Sex and CR interactions were also explored. RESULTS: Recent birth cohorts, higher CR, and healthier brain structures predicted better performance in verbal episodic memory, language and semantic memory, and attention capacities, with large effect sizes. Better performance in executive functions was predicted by a higher CR and a larger total brain volume, with a small effect size. With equal score of CR, women outperformed men in verbal episodic memory and language and semantic memory in all cohorts. Higher level of CR predicted better performance in verbal episodic memory, only when total brain volume was lower. CONCLUSION: Cohort differences in cognitive performance favor more recent birth cohorts and suggests that this association may be partly explained by proxies of CR.
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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 | 0.001 | 0.005 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".