Evidence map›Paper›PMID 41820884›Full record

ArticleBMC public health2026

The association between social support and depressive symptoms in rural older adults with cardiometabolic multimorbidity: a network analysis.

Zhiwei Wang, Shengjia Xu, Xueqing Song, Lan Gao, Siya Meng, Xiaorong Luan, Wenzhe Qin

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Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zhiwei Wang *School of Nursing and Rehabilitation, Shandong University, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Shengjia Xu *The First Clinical College, Cheeloo College of Medicine, University of Shandong, Jinan, Shandong, China.
Xueqing SongSchool of Nursing and Rehabilitation, Shandong University, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Lan GaoSchool of Nursing and Rehabilitation, Shandong University, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Siya MengSchool of Nursing and Rehabilitation, Shandong University, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Xiaorong LuanSchool of Nursing and Rehabilitation, Shandong University, Qilu Hospital of Shandong University, Jinan, Shandong, China. 199162000814@sdu.edu.cn.
Wenzhe QinCenter for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, University of Shandong, Jinan, Shandong, China. qinwenzhe@sdu.edu.cn.

Funding

National Natural Science Foundation of China (NSFC) 72204145National Natural Science Foundation of China (NSFC) 72474121
6 · The paper itself

Abstract

backgroundCardiometabolic multimorbidity and late-life depression are increasingly prevalent among rural older adults in China, imposing a compounded health burden. Although social support is recognized as a protective factor, the specific linkages between its dimensions and individual depressive symptoms in this population remain unclear. Network analysis provides a novel approach to explore these nuanced relationships. This study employed network analysis to examine the detailed associations between multidimensional social support and specific depressive symptoms in rural older adults with cardiometabolic multimorbidity.

methodsA cross-sectional survey was conducted among 1,486 rural adults aged ≥ 60 years with cardiometabolic multimorbidity in Shandong Province, China. Depressive symptoms were assessed using the Patient Health Questionnaire-9, and social support was measured with the Social Support Rating Scale. A regularized partial correlation network was constructed to visualize symptom-level interactions. Centrality and bridge centrality indices were calculated to identify core and bridging nodes.

resultsThe strongest connections were within depressive symptoms, notably between anhedonia and sad mood (edge weight = 0.55), and anhedonia and fatigue (0.33). Subjective and objective support were closely linked (0.45). The strongest (negative) bridge connection emerged between subjective support and sad mood (-0.05). Sad mood, fatigue, and anhedonia were the most central symptoms, while subjective support and sad mood were key bridge nodes. The network showed high stability.

conclusionInterventions targeting central depressive symptoms—sad mood, anhedonia, and fatigue—may effectively alleviate depression in this population. Given the modest strength of bridge connections within the network, interventions focusing on bridge nodes such as subjective support should be implemented in conjunction with those addressing core depressive symptoms, rather than in isolation. These findings underscore the necessity for integrated psychosocial and medical care within rural health services.

Indexed as

Cardiovascular DiseasesDepressionRural PopulationSocial SupportAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedMultimorbiditySocial Network AnalysisCardiometabolic multimorbidityDepressionNetwork analysisRural older adultSocial support

Identifiers

PMID41820884
PMCPMC13094186

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