Social support factors and cognitive outcomes in mid‐life
Bibliographic record
Abstract
Abstract Background A growing body of evidence suggests that social support is associated with cognitive outcomes including dementia in late‐life. Yet few studies have examined the association between social support and cognition in mid‐life, a critical time of transition to aging. Furthermore, little is known about the effects of other aspects of social function such as emotional support, social strain and loneliness on cognition. Our goal was to investigate the association between several social support factors and cognitive performance in mid‐life. Method We studied 2,732 Black and White adults from the Coronary Artery Risk Development in Young Adults (CARDIA) Study who completed a social support questionnaire at baseline (CARDIA Year 20, mean age 45.2 years, 57% female, 45% Black) which assessed aspects of emotional support, social strain, and loneliness. At the 10‐year follow‐up, cognitive performance was evaluated with a battery of five tests: Digit Symbol Substitution Test (DSST), Rey Auditory Verbal Learning Test (RAVLT), Stroop Test, Verbal Fluency (category and letter fluency), and the Montreal Cognitive Assessment (MOCA) and standardized to z‐scores. We used linear regression to determine the association between emotional support, social strain, and loneliness, categorized as tertiles (comparing high to low), with mid‐life cognition. Result In unadjusted models, all three social support factors were associated with cognition 10 years later. After adjusting for age, sex, race, education, marital status, income, and depression, participants reporting higher levels of emotional support performed better on all cognitive tests (DSST High vs. Low (z‐score)=0.13 [95%CI 0.03, 0.23]; RAVLT=0.17 [95%CI 0.07, 0.27]; reverse Stroop=0.15 [95%CI 0.05, 0.26]; Verbal Fluency=0.12 [95%CI 0.01, 0.23]; MOCA=0.19 [95%CI 0.09, 0.28]). Less social strain was associated with higher scores on most tests (DSST Low vs. High=0.16 [95%CI 0.06, 0.26]; RAVLT=0.11 [95%CI 0.01, 0.21]; and MOCA=0.13 [95%CI 0.04, 0.23]). Loneliness was not associated with mid‐life cognition. Conclusion Greater level of social support, particularly emotional support, was associated with better mid‐life cognitive outcomes 10 years later. To better inform risk and prevention efforts, more research should be conducted to investigate the associations between various dimensions of social support and cognitive outcomes across the life course.
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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 | 0.002 |
| 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 | 0.001 | 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".