Evidence map›Paper›PMID 42492227›Full record

ArticleThe journal of nutrition, health & aging2026

Intrinsic capacity subtypes in healthy Chinese older adults: links to possible sarcopenia and fall risk.

Boyang Yu, Zechen Zhou, Guanzhou Chen, Chuanyu Zhou, Peiying Lv, Jiangyu Guo, Fei He, Hexin Li, Beidong Chen, Lina Ma and 8 more

Abstract read
In one paragraph

Article in The journal of nutrition, health & aging, 2026. 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

What it found

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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

18 authors.

Boyang YuDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Zechen ZhouDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Guanzhou ChenDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Chuanyu ZhouDepartment of Geriatrics, Deyang People's Hospital, No.173 Taishan North Road, Deyang 618000, China.
Peiying LvDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Jiangyu GuoDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Fei HeDepartment of Geriatrics, The Yongchuan Affiliated Hospital, Chongqing Medical University, Chongqing 402160, China.
Hexin LiDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Beidong ChenDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Lina MaDepartment of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Disorders, Beijing 100053, China.
Qiaomei LinDepartment of Geriatrics, Deyang People's Hospital, No.173 Taishan North Road, Deyang 618000, China.
Qi ZhouDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Jing PangDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Ji ShenDepartment of Geriatrics, Beijing Hospital, National Centre of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100053, China.
Hong ShiDepartment of Geriatrics, Beijing Hospital, National Centre of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100053, China.
Ruiyue YangDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China. Electronic address: ruiyue_yang@163.com.
Yan WangDepartment of Geriatrics, Deyang People's Hospital, No.173 Taishan North Road, Deyang 618000, China. Electronic address: yanerw1980@163.com.
Liang SunDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The NHC Key Laboratory of Geriatrics, Beijing Key Laboratory of Aging Mechanism and Intervention Research on Aging-Related Diseases, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China. Electronic address: sunbmu@foxmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntrinsic capacity (IC) reflects physiological reserve in older adults. However, most studies have focused on hospital-based populations or summed IC scores. Evidence on IC impairment patterns and their associations with possible sarcopenia and falls among community-dwelling healthy older adults remains limited.

objectiveTo characterize domain-specific and clustered patterns of IC impairment among community-dwelling healthy older adults and evaluate their associations with falls and possible sarcopenia, with the aim of improving precision screening and risk stratification.

methodsThis cross-sectional study enrolled 1,607 community-dwelling adults aged ≥60 years who broadly met the Standard for Healthy Chinese Older Adults (2022), with generally good health, functional independence, and adequate cognitive and communication abilities. IC was assessed using the Integrated Care for Older People (ICOPE) screening tool across five domains: cognition, locomotion, vitality, sensory function, and psychology. Fall risk and possible sarcopenia were evaluated according to the World Guidelines by The World Falls Task Force and the Asian Working Group for Sarcopenia (AWGS) 2025 Updated Consensus, respectively. K-means clustering was used to identify IC impairment subtypes. Multivariate logistic regression, extreme gradient boosting (XGBoost) models, and structural equation modeling (SEM) were applied to examine associations of individual IC domains and clustered subtypes with fall risk and possible sarcopenia.

resultsOver 92% of participants exhibited impairment in ≥1 IC domain, with sensory impairment being most prevalent (80.9%) and locomotion least common (5.8%). Four distinct IC subtypes were identified: isolated cognitive impairment (17.4%), predominant sensory impairment (49.7%), sensory-psychological-vitality impairment (27.1%), and multi-domain impairment (5.8%). Overall, each additional impaired IC domain increased fall risk by 37% and possible sarcopenia risk by 41%, respectively. Locomotion impairment demonstrated a strong association with fall risk (OR = 4.78, 95% CI: 2.21-7.62), whereas cognitive impairment showed a strong association with possible sarcopenia (OR = 3.40, 95% CI: 2.18-5.32). Only multi-domain impairment exhibited significant associations with both outcomes (OR = 4.10, 95% CI: 2.21-7.62 for falls; OR = 2.78, 95% CI: 1.65-4.67 for possible sarcopenia). The five-domain IC XGBoost model showed higher AUCs than the age-sex model for fall risk (0.742 vs. 0.677) and possible sarcopenia (0.726 vs. 0.679). SEM identified significant paths linking age, cognition, locomotion, possible sarcopenia, and falls (β = 0.05-0.27), as well as an inter-domain sensory-psychological-vitality pathway (β = 0.16-0.59; all P < 0.001).

conclusionIC impairment was common even among healthy community-dwelling older adults. Sensory impairment may be an early marker of IC decline, whereas multidomain impairment was linked to higher fall risk and possible sarcopenia. Community prevention should prioritize ICOPE-based sensory screening, timely vision/hearing management, and targeted muscle strength, gait, and fall-risk assessment for high-risk IC subtypes.

Indexed as

Accidental FallsGeriatric AssessmentSarcopeniaAgedAged, 80 and overChinaCognitionCross-Sectional StudiesEast Asian PeopleFemaleHumansIndependent LivingMaleMiddle AgedRisk AssessmentRisk FactorsCommunity-dwelling older adultsFallsIntegrated care for older peopleIntrinsic capacityPossible sarcopenia

Identifiers

PMID42492227
PMCPMC13427436

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LicenceCC BY-NC-ND
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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.