Evidence map›Paper›PMID 40826485›Full record

ArticleBMC psychology2025

A network analysis study of anxiety, depression and loneliness among middle-aged and elderly people in Xining area.

Bixuan Dong, Bin Li, Xiaowei Fan, Hongru Chen, Zhancui Dang, Ze Li

Erratum issuedAbstract read
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Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Bixuan DongDepartment of Public Health, Qinghai University Medical College, Xining, China.
Bin LiDepartment of Public Health, Qinghai University Medical College, Xining, China. libin@qhu.edu.cn.
Xiaowei FanDepartment of Public Health, Qinghai University Medical College, Xining, China.
Hongru ChenDepartment of Public Health, Qinghai University Medical College, Xining, China.
Zhancui DangDepartment of Public Health, Qinghai University Medical College, Xining, China.
Ze LiDepartment of Public Health, Qinghai University Medical College, Xining, China.

Funding

Qinghai Provincial Office of Science and Technology 2024-SF-125
6 · The paper itself

Abstract

backgroundLow oxygen levels, low atmospheric pressure, and intense sunlight characterize high-altitude regions. These environmental factors can disrupt the body's biochemical mechanisms and neural functions, which may increase the risk of mental health issues in affected individuals. Depression, anxiety, and loneliness are common mental health conditions. Our study conducted network analysis methods to investigate the relationships among anxiety, depression, and loneliness in middle-aged and older individuals in Xining City, Qinghai Province, China (average altitude: 2,261 m). Additionally, the study conducted a comparative analysis of the network structures to explore gender differences.The objective of this study was to provide theoretical intervention strategies and practical guidelines for the mental health of middle-aged and older individuals in high-altitude regions.

methodThis study utilized convenience sampling to select 673 middle-aged and older individuals from Xining City, Qinghai Province, China (average altitude 2,261 m). The following instruments were utilized in the study: a basic demographic survey questionnaire, the Nine-item Patient Health Questionnaire (PHQ-9), the Seven-item Generalized Anxiety Disorder scale (GAD-7), and the UCLA Loneliness Scale Chinese Simplified Version (ULS-8). R version 4.4.1 was used for the statistical description and network analysis.Descriptive analysis was presented using mean (SD) or number(percentage).We explored the network structure comprising anxiety, depression, and loneliness. It also compared the network structures of male and female samples to explore gender differences.

resultsIn the network, the strongest association was found between GAD2 "Cannot stop/control worrying" and GAD3 "Worrying too much". The core symptoms identified were GAD4 "Trouble relaxing"; PHQ2 "Depressed mood"; and ULS3 "Feeling left out". Bridge symptoms included GAD5 "Being restless"; PHQ8 "Psychomotor retardation or agitation"; and ULS6 "Feeling lonely". A comparison of male and female networks indicated that there was no difference in the global network; however, a significant difference in the global strength was observed. The top three pairs with the strongest associations were: ULS7 "I would like to make friends" -ULS8 "I can find someone to be with me when I want to be"; GAD3 "Worrying too much" -GAD2 "Cannot stop/control worrying"; and PHQ1 "Anhedonia" -PHQ2 "Depressed mood". However, the weight of PHQ1 "Anhedonia" - PHQ2 "Depressed mood" was significantly higher in the female network than in the male network, while the weights of the other two pairs were similar. The core symptoms of the male network were GAD4 "Trouble relaxing"; GAD5 "Being restless" and PHQ2 "Depressed mood". The core symptoms of the female network were identified as: PHQ2 "Depressed mood"; ULS3 "Feeling left out"; and GAD3 "Worrying too much".The PHQ2 "Depressed mood" was identified as a core symptom in both the male and female networks. However, the expected influence index of the PHQ2 "Depressed mood" for the female network was found to be higher than that for the male network.

conclusion"Trouble relaxing", "Depressed mood", "Feeling left out", "Being restless", "Psychomotor retardation or agitation", and "Feeling lonely" could be key targets for the prevention of anxiety, depression, and loneliness in the middle-aged and older population in high-altitude areas.Additionally, there were significant differences in overall intensity between male and female networks, with gender-specific strategies recommended.

Indexed as

AnxietyDepressionLonelinessAgedAged, 80 and overAltitudeChinaFemaleHumansMaleMiddle AgedSex FactorsAnxietyDepressionHigh altitudeLonelinessNetwork analysis

Identifiers

PMID40826485
PMCPMC12359986

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.