Age-Related Differences in the Association between Life’s Essential 8 and Cognition in Cognitively Normal Adults: The CABLE Study
Bibliographic record
Abstract
BACKGROUND: This study investigated the relationship between Life's Essential 8 (LE8), a recently updated lifestyle-related health factor, and cognition across multiple life stages. METHODS: We enrolled 1098 cognitively normal participants from the Chinese Alzheimer's Biomarker and Lifestyle (CABLE) study. We investigated the interactions between age and LE8 on cognition. Multiple linear regression models were utilized to explore the relationship between the LE8 total scores and its two subscales scores with cognition in the total sample, as well as in the mid-age (≤65 years) and the late-age (>65 years) subgroups. In addition, mediation analyses were performed to explore the biologically plausible pathways between LE8 and cognition. RESULTS: There was a significant interaction effect between age and LE8 total scores on MOCA score (P = 0.030). The mid-age subgroup showed a positive correlation between LE8 total scores and CM-MMSE (β = 0.110, P = 0.005) and MOCA (β = 0.112, P = 0.005) scores. However, no significant associations were found in the late-age subgroup. In the mid-age subgroup, CSF p-tau partially mediated the relationship between LE8 total scores and its two subscales and cognition, with a mediation proportion ranging from 6% to 12%. CONCLUSION: Our findings revealed that the association of the LE8 total scores with MOCA and CM-MMSE scores were significant in mid-age adults rather than late-age adults, indicating that the association might be age-specific and emphasizing the importance of lifestyle interventions in mid-life.
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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 | 0.001 |
| 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 | 0.001 | 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".