Reclassified cognitive leisure activity and risk of cognitive impairment in Chinese older adults aged ≥80 years: A 16‐year prospective cohort study
Bibliographic record
Abstract
AIM: There is accumulating evidence that participation in cognitive leisure activities might be related to a reduced risk of cognitive impairment. However, there is no consensus regarding the classification of cognitive leisure activities, and it cannot clearly define each activity and quantitatively evaluate the effect of it. In the present study, we propose a new classification method, and examine the relationship between reclassified cognitive leisure activities and cognitive function. METHODS: The analysis included 4830 participants of the Chinese Longitudinal Healthy Longevity Survey, who were aged >80 years and free of cognitive impairment at 1998. They were followed up six times. Six cognitive leisure activities were mainly grouped into intrapersonal and interpersonal cognitive leisure activity by categorical principal component analysis. Cox proportional hazards analysis was used to evaluate the relationship between reclassified cognitive leisure activities and the risk of cognitive impairment. RESULTS: After a median follow-up period of 16 years, 1763 participants suffered from cognitive impairment (Mini-Mental State Examination score <24). Reading newspapers or books, taking part in some social activities and sometimes playing cards or mahjong were associated with a decreased risk of cognitive impairment (P < 0.05 for all). In multivariable adjusted models, compared with those with lower intensities, the hazard ratios (95% confident intervals) of cognitive impairment were 0.86 (0.74-0.99) and 0.71 (0.60-0.83) for participants with high intensities of intrapersonal and interpersonal cognitive leisure activity, respectively. CONCLUSION: A high frequency of participation in intrapersonal and interpersonal cognitive leisure activities showed a lower risk of cognitive impairment among the oldest-old in China. Geriatr Gerontol Int 2019; 19: 1041-1047.
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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 | 0.000 | 0.000 |
| 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".