Late-life physical activity, midlife-to-late-life activity patterns, APOE ε4 genotype, and cognitive impairment among Chinese older adults: a population-based observational study
Bibliographic record
Abstract
BACKGROUND: Although physical activity (PA) has been linked to cognitive health, the nuanced relationships between different dimensions of PA and cognitive impairment remain inconclusive. This study investigated associations between late-life PA levels, midlife-to-late-life activity patterns, and cognitive impairment in Chinese older adults, considering potential moderation by apolipoprotein E (APOE) ε4 genotype. METHODS: We analyzed baseline data from 6,899 participants (median age 68 years, 55.78% female) in the West China Health and Aging Cohort study, with 6,575 participants having APOE genotyping data. Late-life PA and midlife-to-late-life activity patterns were assessed using the Global Physical Activity Questionnaire and a standardized question, respectively. Cognitive function was evaluated using the Chinese version of Mini-Mental State Examination. Logistic regression models were used to examine associations. RESULTS: Compared to low PA level, moderate (odds ratio [OR] = 0.74, 95% confidence interval [CI] = 0.55 ~ 0.99) and high PA levels (OR = 0.60, 95%CI = 0.48 ~ 0.75) were associated with lower risk of cognitive impairment. Engaging in work-, transport-, recreation-related, and moderate-intensity PA were each significantly associated with lower cognitive impairment risk. Maintaining activity levels from midlife to late life was associated with lower cognitive impairment risk compared to decreasing levels (OR = 0.75, 95%CI = 0.60 ~ 0.94). These associations were more pronounced in APOE ε4 non-carriers, with an interaction observed between APOE ε4 genotype and recreation-related PA (P-value = 0.04). CONCLUSIONS: Our findings underscore the multifaceted benefits of PA in mitigating cognitive impairment risk among older Chinese adults. Public health strategies should focus on promoting overall late-life PA levels, especially moderate-intensity PA, and maintaining activity levels comparable to midlife, with potential for personalized interventions based on genetic risk profiles.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".