Evidence map›Paper›PMID 42420892›Full record

ArticleBMC geriatrics2026

Chronic disease comorbidity and its impact on healthcare utilization among older adults in China: a cross-sectional and longitudinal analysis.

Houyu Chen, Xinru Huang, Yu Xiang, Ru Meng, Muwei Zhu

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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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5 · Who and what money

Authors and funding

5 authors.

Houyu ChenSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Xinru HuangSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China. xinruhuangxz@163.com.ORCID https://orcid.org/0000-0002-4975-5071
Yu XiangSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Ru MengSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Muwei ZhuSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China. zmwjsxz@163.com.

Funding

The Humanities and Social Sciences Research Project of the Ministry of Education No. 22YJC630040the National Natural Science Foundation of China 72202201the Youth Project of Social Science Foundation of Jiangsu Province No. 22GLC003
6 · The paper itself

Abstract

backgroundThe comorbidity rate of chronic diseases among the elderly in China is rising steadily, significantly influencing their healthcare utilization. This study aims to identify latent trajectories of chronic disease accumulation in the elderly and assess the impact of comorbidity and changes in the number of chronic diseases on outpatient and inpatient service use, providing clues for precise intervention and optimization of medical resource allocation.

methodsData from five waves (2011, 2013, 2015, 2018, 2020) of the China Health and Retirement Longitudinal Study (CHARLS) were utilized. Cross-sectional analysis (2020, n = 8,316, aged ≥ 60) employed multivariable logistic regression and zero-inflated negative binomial regression to assess comorbidity's impact. Longitudinal analysis (n = 1,178, followed from 2011 to 2020, aged ≥ 60) used latent class growth model (LCGM) to identify chronic disease number trajectories. Multivariable logistic regression evaluated the dynamic impact of change in the number of diseases on service use. Binary and ordered logistic regressions analyzed baseline disease count's effect on future increases.

resultsThe comorbidity rate among Chinese elderly (≥ 60) was 66.7%. Comorbidity and increasing disease numbers significantly raised the risk and frequency of outpatient and inpatient service utilization. Latent class growth model identified four distinct chronic disease development trajectories: relative stabilized trajectory, low-increment trajectory, medium-increment trajectory, and high-increment trajectory, all showing varying degrees of upward trend. Individuals in higher increment trajectories faced significantly greater risks of increased healthcare utilization. Higher baseline disease counts also predicted greater risk of accumulating additional diseases.

conclusionsChronic disease comorbidity is highly prevalent and increasing among Chinese elderly. Both the number of chronic diseases and their progression significantly drive higher healthcare utilization and demand. There are also significant differences in the development of the number of chronic diseases among the population. The findings stress dynamic risk prevention, identifying high-risk populations for coordinated, proactive health management and precise resource allocation to relieve system strain from comorbidities.

Indexed as

Patient Acceptance of Health CareAgedAged, 80 and overChinaChronic DiseaseComorbidityCross-Sectional StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedChronic diseaseComorbidityElderlyHealthcare utilization

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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.