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Record W4408246005 · doi:10.2196/65075

Associations Between Sleep Duration and Activity of Daily Living Disability Among Older Adults in China: Cross-Sectional Study

2025· article· en· W4408246005 on OpenAlexvenueno aff
Huimin Fan, Weijie Yu, Hongguo Rong, Xiaokun Geng

Bibliographic record

VenueInteractive Journal of Medical Research · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsActivities of daily livingCross-sectional studyMarital statusLongitudinal studyBathingGerontologyMedicineResidencePopulationDepression (economics)Quality of life (healthcare)PsychologyDemographyPhysical therapyEnvironmental health

Abstract

fetched live from OpenAlex

Background: China has the largest elderly population globally; the growth rate of the aged tendency of the population was higher than that of Western countries. Given the distinctions in historical, ethnic, and economic status as well as socio-cultural background, Chinese adults had different sleep patterns compared with adults in other countries. Considering the heavy disease burden caused by activities of daily living (ADL) disability, we conducted a cross-sectional analysis using data from the China Health and Retirement Longitudinal Study (CHARLS) to test the hypothesis that individuals with short and longer sleep duration are more likely to have ADL disability. Objective: ADL disability is a common condition affecting the quality of life among older people. This study aimed to explore the associations between sleep duration and ADL disability among middle-aged and older adults in China. Methods: This cross-sectional study used data from 17,607 participants from the 2018 CHARLS (from 2018 to 2020), an ongoing representative survey of adults aged 45 years or older and their spouses. Self-reported sleep duration per night was obtained from face-to-face interviews. The ADL was measured using a 6-item summary assessed with an ADL scale that included eating, dressing, getting into or out of bed, bathing, using the toilet, and continence. Multiple generalized linear regression models-adjusted for age, sex, education, marital status, tobacco and alcohol use, depression, place of residence, sensory impairment, self-reported health status, life satisfaction, daytime napping, chronic disease condition, and sample weights-were used. Results: Data were analyzed from 17,607 participants, of whom 8375 (47.6%) were men. The mean (SD) age was 62.7 (10.0) years. Individuals with 4 hours or less (odds ratio [OR] 1.91, 95% CI 1.60-2.27; P<.001), 5 hours (OR 1.33, 95% CI 1.09-1.62; P=.006), 9 hours (OR 1.48, 95% CI 1.13-1.93; P<.001), and 10 hours or more (OR 1.88, 95% CI 1.47-2.14; P<.001) of sleep per night had a higher risk of ADL disability than those in the reference group (7 hours per night) after adjusting for several covariates. Restricted cubic splines analysis suggested a U-shaped association between sleep duration and ADL disability. When sleep duration fell below 7 hours, an increased sleep duration was associated with a significantly low risk of ADL disability, which was negatively correlated with sleep duration until it fell below 7 hours (OR 0.83, 95% CI 0.79-0.87; P<.001). When sleep duration exceeded 7 hours, the risk of ADL disability would increase facing prolonged sleep duration (OR 1.19, 95% CI 1.12-1.27; P<.001). ADL disability should be monitored in individuals with insufficient (≤4 or 5 hours per night) or excessive (9 or ≥10 hours per night) sleep duration. Unlabelled: In this study, a U-shaped association between sleep duration and ADL disability was found. Future longitudinal studies are needed to establish temporality and examine the mechanisms of the associations between sleep duration and ADL disability.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.460
Teacher spread0.427 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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