Both short and long sleep durations are associated with cognitive impairment among community-dwelling Chinese older adults
Bibliographic record
Abstract
This study aims to examine the association between sleep duration and cognitive impairment in community-dwelling Chinese older adults.The associations between sleep duration and cognitive function have been widely studied across various age ranges but are of particular importance among older adults. However, there are inconsistent findings regarding the relationship between sleep duration and cognitive function in the literature.This study is an observational cross-sectional study. We analyzed data from 1115 Chinese individuals aged 60 and older from 3 Chinese communities (Beijing, Hefei, and Lanzhou). Cognitive impairment was defined as a Mini-Mental State Examination total score less than 24 points. Odds ratios (ORs) of associations were calculated and adjusted for potential confounders in logistic regression models.The prevalence of cognitive impairment was 25.7% (n = 287). Controlling for all demographic, lifestyle factors, and coexisting conditions, the adjusted OR for cognitive impairment was 2.54 (95% CI = 1.70-3.80) with <6 hours sleep and 2.39 (95% CI = 1.41-4.06) with >8 hours sleep.Both short and long sleep durations were related to worse cognitive function among community-dwelling Chinese elderly 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 | 0.000 | 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 | 0.000 | 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".