Evidence map›Paper›PMID 39738602›Full record

ArticleScientific reports2024

The bidirectional relationships between social isolation and cognitive function among older adults in China: separating between-person effects from within-person effects.

Xinlong Xie, Fanfan Wu, Zhiruo Zhuang, Aijun Xu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xinlong XieSchool of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China.
Fanfan WuSchool of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China.
Zhiruo ZhuangSchool of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China.
Aijun XuSchool of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China. xuaijun2000@njucm.edu.cn.

Funding

National Social Science Fund of China 2018VJX065
6 · The paper itself

Abstract

This study investigates the bidirectional relationship between social isolation and cognitive function among older adults in China, utilizing data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The baseline survey, which commenced in 2008, tracked 1,662 participants over four waves of data collection spanning a decade. We employed Cross-Lagged Panel Models (CLPM) and Random Intercept Cross-Lagged Panel Models (RI-CLPM) to analyze these relationships at both the between-person and within-person levels. CLPM results indicated significant cross-lagged effects between social isolation (β = - 0.119, p < 0.001; β = - 0.162, p < 0.001) and cognitive function (β = - 0.073, p < 0.001; β = - 0.091, p < 0.001) at the between-person level over the last three waves. Specifically, higher prior levels of social isolation were associated with a significant decline in subsequent cognitive function, and vice versa. Furthermore, RI-CLPM results showed that, after controlling for random intercepts and covariates, only social isolation had a significant negative impact on cognitive function across all waves (β = - 0.051, p < 0.05; β = - 0.047, p < 0.05; β = - 0.028, p < 0.05). Overall, this study demonstrates that, when considering both between-person and within-person effects, social isolation exerts a stronger lag effect on cognitive function among older adults in China. This suggests that, over a specific timeframe, reducing social isolation is crucial for promoting healthy aging in this population.

Indexed as

CognitionSocial IsolationAgedAged, 80 and overChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedBetween-person effectsCognitive functionCross-lagged panel modelsRandom intercept cross-lagged panel modelsSocial isolationWithin-person effects

Identifiers

PMID39738602
PMCPMC11686255

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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 OpenQuestion graph.