ArticleBMC public health2024
Dynamic relations between longitudinal morphological, behavioral, and emotional indicators and cognitive impairment: evidence from the Chinese Longitudinal Healthy Longevity Survey.
Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Association between subjective well-being and the risk of cardiovascular diseases among older adults: evidence from the Chinese longitudinal healthy longevity survey.BMC geriatrics · 2025Article
- Study on the needs of the older adults with dementia in care institutions based on a hierarchical interaction model: a case study of an institution in Hangzhou, China.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe aimed to assess the effects of body mass index (BMI), activities of daily living (ADL), and subjective well-being (SWB) on cognitive impairment and propose dynamic risk prediction models for aging cognitive decline.
methodsWe leveraged the Chinese Longitudinal Healthy Longevity Survey from 1998 to 2018. Cognitive status was measured using the Chinese Mini-Mental State Examination. We employed repeated measures correlation to assess associations, linear mixed-effect models to characterize the longitudinal changes, and Cox proportional hazard regression to model survival time. Dynamic predictive models were established based on the Bayesian joint model and deep learning approach named dynamic-DeepHit. Marginal structural Cox models were adopted to control for time-varying confounding factors and assess effect sizes.
resultsADL, SWB, and BMI showed protective effects on cognitive impairment after controlling observed confounding factors, with respective direct hazard ratios of 0.756 (0.741, 0.771), 0.912 (0.902, 0.921), and 0.919 (0.909, 0.929). Dynamic risk predictive models manifested high accuracy (best AUC = 0.89). ADL was endowed with the best predictive capability, although the combination of BMI, ADL, and SWB showed the most remarkable performance.
conclusionsBMI, ADL, and SWB are protective factors for cognitive impairment. A dynamic prediction model using these indicators can efficiently identify vulnerable individuals with high accuracy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.