The Impact of Cognitive Engagement on Cognitive Decline: Investigating Sex and Life‐Stage Differences
Bibliographic record
Abstract
BACKGROUND: Engaging in cognitively stimulating activity (CSA) enhances cognitive reserve and reduces cognitive decline in aging. However, limited research has compared CSA's impact across different life stages (e.g., childhood, middle adulthood, older adulthood) or explored whether its protective effects differ by sex. This study was designed to examine (1) sex differences in how CSA engagement across life stages influences cognitive decline, and (2) whether a drop in late-life engagement impacts cognitive decline compared to consistently high or low engagement throughout life. METHODS: Data from 2,747 participants (2,068 females, 679 males) with 19,523 timepoints and a mean of 6.8 ± 4.5 follow-up years from the Rush Alzheimer's Disease Center database were analyzed. CSA engagement levels were categorized as high or low using a median split for early (ages 6 and 12), middle (ages 30-40), and late (ages 65+) life. Participants were grouped by sex and categorized according to their CSA engagement in each life stage and their lifelong engagement patterns: Always Engaged (high engagement in all stages), Always Disengaged (low engagement in all stages), and Disengaged in Late Life (high engagement in early/middle life, low in late life). Linear mixed-effects models assessed cognitive change over time. RESULTS: Early-life engagement did not impact cognitive decline in females or males. In middle-life, females with high engagement experienced slower decline, while males experienced faster decline than their low engagement counterparts. In late-life, females and males with high engagement experienced slower decline than their low-engagement counterparts, with females benefiting more than males (Figure 1). Females who disengaged in late life declined faster than those always disengaged but did not differ from those always engaged. Males who disengaged in late life declined faster than those always engaged but did not differ from those always disengaged (Figure 2). CONCLUSIONS: The relationship between CSA and cognitive decline varies by sex, timing of engagement, and lifelong engagement patterns. These findings emphasize the need to consider these factors in cognitive aging research, and in the development of interventions promoting cognitive health. Although CSA engagement in late-life is beneficial across sexes, midlife engagement may be particularly important for females.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".