Relationships of leisure activities with physical and cognitive functions among Chinese older adults: A prospective community-based cohort study
Bibliographic record
Abstract
OBJECTIVES: Based on a prospective design, this study aimed to investigate the relationships of leisure activities with physical and cognitive functions among Chinese older adults. METHODS: The respondents aged 65 years or more were selected from the 2014-2018 of the Chinese Longitudinal Healthy Longevity Survey. Physical function measurement indicators were reflected by activities of daily living (ADL), instrumental activities of daily living (IADL), and physical performance (PP), while cognitive function was assessed by Mini-Mental State Examination. Fine-Gray competing risk regression models were used to analyze the data. RESULTS: Using the figures for 2014 as a baseline for the study, we included 6047, 6216, 5951, and 5916 respondents in the ADL, IADL, PP, and cognitive function analyses, respectively. The prospective results showed that keeping domestic animals or pets was related to a lower risk of ADL disability of respondents after adjustment (SHR: 0.619, 95% CI: 0.486, 0.788). Similarly, taking part in social activities (SHR: 0.781, 95%CI: 0.658, 0.929) and reading books or newspapers (SHR: 0.793, 95% CI: 0.656, 0.958) were associated with a lower risk of IADL disability. Playing cards or mahjong was correlated with a lower risk of cognitive impairment (SHR: 0.669, 95% CI: 0.507, 0.882), while keeping domestic animals or pets was related to a higher risk of cognitive impairment (SHR: 1.279, 95% CI: 1.047, 1.562). CONCLUSION: Participation in leisure activities moderately may decrease the risk of a decline in physical and cognitive functions among Chinese older adults.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".