Evidence map›Paper›PMID 41765893›Full record

ArticleBMC geriatrics2026

Social capital, objective social integration, subjective social integration, and utilization of public health services among older migrant population: a structural equation modeling analysis of multi-group chain mediating effect.

Ting Wang, Xiaolong Bu, Naijiao Xing, Qian Dong, Feng Zhong, Cuiping Liu

Abstract read
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Article in BMC geriatrics, 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

6 authors.

Ting WangSchool of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, 271000, China.
Xiaolong BuSchool of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, 271000, China.
Naijiao XingPulmonary and Critical Care Medicine, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, Shandong Province, 266071, China.
Qian DongShandong Provincial Chronic Disease Hospital, Qingdao, Shandong Province, 266071, China.
Feng ZhongInstitute of Nutrition & Health, Qingdao University, Qingdao, Shandong Province, 266071, China.
Cuiping LiuSchool of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, 271000, China. lcping0926@126.com.

Funding

Shandong Province Humanity and Social Science Project 2022-JCFX-05
6 · The paper itself

Abstract

backgroundEnhancing accessibility and equity in basic public health services for older migrants constitutes a pivotal objective within global healthcare systems. Previous research has elucidated the impact of social capital, as well as objective and subjective social integration, on the utilization of public health services. However, there exists a dearth of studies investigating the specific pathways linking these factors.

methodsThe present study conducted an analysis of data obtained from the 2017 China Mobile Population Dynamic Monitoring Survey, which involved a sample of 5729 older migrants. Structural equation modelling was employed to examine our hypothesized model encompassing social capital, objective social integration, subjective social integration, and the utilization of public health services. Multi-group analysis was utilized to validate the moderating role of migrant reasons within the proposed model.

resultsThe findings indicated a positive association between social capital and the utilization of public health services (β = 0.037, p < 0.05). Social capital was positively correlated with two mediating variables, objective (β = 0.216, p < 0.001) and subjective social integration (β = 0.095, p < 0.001). Objective social integration was positively correlated with subjective social integration (β = 0.144, p < 0.001). Both objective (β = 0.386, p < 0.001) and subjective social integration (β = 0.144, p < 0.001) exhibited a positive relationship with the utilization of public health services. Finally, the impact of social capital on the utilization of public health services varied depending on the reason for migration.

conclusionsSocial capital was positively associated with the utilization of public health services. Objective and subjective social integration were crucial factors in this process. The impact of social capital on the utilization of public health services varied based on migration motivations. These insights are valuable for policies promoting equal access to public health services and overall well-being for older migrants in an aging society.

Indexed as

Patient Acceptance of Health CarePublic HealthSocial CapitalSocial IntegrationTransients and MigrantsAgedChinaFemaleHumansLatent Class AnalysisMaleMediation analysisObjective social integrationOlder migrant populationSocial capitalSubjective social integrationUtilization of public health services

Identifiers

PMID41765893
PMCPMC13182055

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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.