Evidence mapPaperPMID 41460460Full record

ArticleAging clinical and experimental research2025

Measuring and decomposing inequalities in intrinsic capacity among older adults in china: from an urban-rural divide perspective.

Tian Zheng, Li Chenyang, Liu Shangjun, Xiao Shuqin, Dai Jiaqi, Zhang Yanyan, Jing Liwei

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Article in Aging clinical and experimental research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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5 · Who and what money

Authors and funding

7 authors.

Tian ZhengSchool of Nursing, Capital Medical University, Beijing, 100069, China.
Li ChenyangSchool of Nursing, Capital Medical University, Beijing, 100069, China.
Liu ShangjunSchool of Nursing, Capital Medical University, Beijing, 100069, China.
Xiao ShuqinSchool of Nursing, Capital Medical University, Beijing, 100069, China.
Dai JiaqiSchool of Nursing, Capital Medical University, Beijing, 100069, China.
Zhang YanyanSchool of Nursing, Capital Medical University, Beijing, 100069, China.
Jing LiweiSchool of Nursing, Capital Medical University, Beijing, 100069, China. lwjing2004@ccmu.edu.cn.

Funding

National Social Science Fund of China 22BSH112
6 · The paper itself

Abstract

backgroundThe growing population of older adults in China has drawn attention to the significant disparities in health resources and overall health status exist between urban and rural older adults. Intrinsic capacity (IC), a key indicator of comprehensive health levels in older adults, plays a crucial role in achieving healthy aging. This study aimed to systematically evaluate the inequality in IC among Chinese older adults from an urban-rural divide perspective, identify the factors influencing these inequalities, and decompose the sources of inequality.

methodsOn the basis of data from the China Health and Retirement Longitudinal Study (CHARLS), 7,695 adults aged 60 years and above were included. Concentration curves and concentration index (CI) were used to measure economic-related inequality in IC. Using the Dahlgren-Whitehead model of social determinants of health, generalized estimating equations (GEEs) were applied to analyze factors influencing IC among urban and rural older adults. Wagstaff's decomposition method was further employed to decompose the CI.

resultsA pro-rich inequality in IC (CI > 0) was observed among both urban and rural older adults, with a higher degree of inequality in urban areas that continued to widen over time. In 2013, age was the largest contributor to inequality in rural areas (contribution to CI: 27.55%), while social activity was the main contributor in urban areas (contribution to CI: 26.02%). By 2015, social activity had become the primary contributor in both rural (contribution to CI: 22.69%) and urban (contribution to CI: 28.91%) areas. Multivariate analysis showed that increased age, higher Instrumental Activities of Daily Living (IADL)/Activities of Daily Living (ADL) scores, and the presence of chronic diseases were associated with lower IC, whereas longer sleep duration, more social activities, higher education levels, and improved green coverage in built-up areas were associated with higher IC. Having more children was positively associated with IC only among urban older adults, while being married and engaging in exercise were positively associated with IC only among rural older adults.

conclusionChinese older adults showed inequality in IC, with more pronounced inequality in urban areas. Social activity and age are major contributing factors. Interventions such as promoting social participation, optimizing environmental resources, and implementing tailored urban-rural health policies are recommended to mitigate IC inequality and advance health equity.

Indexed as

Health Status DisparitiesRural PopulationUrban PopulationAgedAged, 80 and overChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedSocioeconomic FactorsDahlgren–Whitehead modelInequalityIntrinsic capacityUrban‒rural divide

Identifiers

PMID41460460
PMCPMC12775099

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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.