Evidence map›Paper›PMID 40613358›Full record

ArticleJournal of primary care & community health

Intrinsic Capacity of Chinese Community-Dwelling Older Adults Using WHO Integrated Care for Older People (ICOPE) Framework: Structural Equation Model Analysis.

Junjun Sun, Kwanjai Amnatsatsue, Patsri Srisuwan, Patcharaporn Kerdmongkol, Dechavudh Nityasuddhi

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Article in Journal of primary care & community health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Junjun SunMahidol University, Bangkok, Thailand.ORCID 0000-0002-0086-0647
Kwanjai AmnatsatsueMahidol University, Bangkok, Thailand.ORCID 0000-0002-6064-3038
Patsri SrisuwanPhramongkutklao Hospital, Bangkok, Thailand.
Patcharaporn KerdmongkolMahidol University, Bangkok, Thailand.ORCID 0009-0001-7784-6405
Dechavudh NityasuddhiIndependent Scholar, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to examine the intrinsic capacity in Chinese older adults and its determinants (sociodemographic, lifestyle-related, environmental, and health-related factors) based on the WHO Integrated Care for Older People (ICOPE) framework.

methodsA cross-sectional community-based study was conducted among 485 community-dwelling older adults recruited from 4 community health service centers in Xinxiang City, Henan Province between August 2024 and February 2025. Intrinsic capacity was assessed across 5 domains: locomotion, cognition, vitality, psychology, and sensory capacity (hearing and vision). Structural equation model (SEM) was used to examine relationships among intrinsic capacity, sociodemographic factors, lifestyle, family support, social participation, healthcare access, and health conditions.

resultsMore than a half of subjects were female (61.2%), married (84.7%), having less than high school education (52%), with a mean age of 73.7 years (SD = 5.5). About 55.9% showed intrinsic capacity impairment, with most impairment of cognition (49.9%), followed by vision (44.9%), hearing (23.7%), locomotion (22.5%), vitality (18.1%), and psychological capacity (13%). The SEM demonstrated good fit and explained 83% of the variance in intrinsic capacity. Significant determinants, ranked by effect size, included dietary habits (β = .544), age (β = -.303), pain (β = -.240), handgrip strength (β = .205), social participation (β = .181), access to healthcare services (β = .138), hospitalization (β = -.10), and physical exercise (β = .089). All paths in the model were statistically significant (

conclusionsThe SEM analysis demonstrated that dietary habits, handgrip strength, social participation, access to healthcare services, and physical exercise were positively associated with intrinsic capacity, while age, pain, and hospitalization showed negative associations. These findings suggest that primary care approaches focusing on multi-domain interventions, particularly health promotion, self-care, and early screening, may be promising areas for future public health initiatives. Community-based programs integrating these modifiable factors should be prioritized to promote intrinsic capacity and functional independence among Chinese community-dwelling older adults.

Indexed as

Delivery of Health Care, IntegratedGeriatric AssessmentIndependent LivingAgedAged, 80 and overChinaCross-Sectional StudiesEast Asian PeopleFemaleHealth Services AccessibilityHumansLatent Class AnalysisLife StyleMaleSocial ParticipationChinese older adultsICOPE frameworkintrinsic capacityprimary healthcarestructural equation model

Identifiers

PMID40613358
PMCPMC12227898

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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.