COHORT EFFECTS IN OLD-AGE COGNITIVE AGING: A STUDY OF SOCIAL CONTEXT IN CHILDHOOD IN 140,030 OLDER ADULTS
Bibliographic record
Abstract
Abstract Researchers have reported that later-born cohorts often have higher scores on cognitive tests, potentially indicating that some of the differences normally attributed to cognitive aging may reflect developmental differences. The present study examined the hypotheses that social factors at birth and in early adolescence might partially explain birth cohort effects. This secondary analysis of data collected prospectively as part of four internationally comparable and nationally representative studies of individuals aged 50 and older residing in 17 European countries and the United States (N=140,030). Cognition was prospectively measured longitudinally 360,150 observations spanning, on average, 4.27 (SD=5.12) years allowing us to leverage age/cohort variability. Multilevel longitudinal modeling was used incorporated random intercepts and slopes at the country and individual levels to model lifetime cognition while adjusting for contextual factors. Birth cohort was associated with height (B=0.095, SE=0.002, P< 1E-06), episodic memory (B=0.105, SE=0.001, P< 1E-06), and verbal fluency (B=0.217, SE=0.002, P< 1E-06). Approximately 7.72% (95% C.I.=[7.60-7.86]) of participants were exposed to at least two years of famine in childhood, and were born into countries with moderate levels of income inequality. Multivariable adjustment accounted for 15.10-24.96% of birth cohort effects in episodic memory and verbal fluency respectively. Longitudinal modeling revealed that after adjusting for famine, war, income inequality, educational attainment, and height, these factors explained 81.58-63.65% of the birth cohort effect in episodic memory and verbal fluency respectively. Global research has reported that early life factors can have an impact on development, so this study extends this to suggest these factors have a lifelong impact.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".