ORIGINAL RESEARCH article
Front. Public Health
Sec. Aging and Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1597224
This article is part of the Research TopicInnovative Personalized Medicine Strategies for Managing Multi-MorbidityView all 8 articles
Identification and Trajectory of Multimorbidity Patterns Among Older People in China: A Longitudinal Study Based on the China Health and Retirement Longitudinal Study 2011-2020 Data
Provisionally accepted
- Xi'an Jiaotong University, Xi'an, China
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Background: Multimorbidity presents a significant global health challenge, particularly among older people in China; however, research on its patterns and dynamic evolution remains limited.This study examines chronic disease co-occurrence and associated risk factors, identifying multimorbidity trends to inform health management and policy.Methods: This study utilized the latest five-wave national survey data from the China Health and Retirement Longitudinal Study (CHARLS) on 2,798 individuals aged 60 years or older with multimorbidity. Latent class analysis (LCA) identified distinct multimorbidity patterns from 14 self-reported chronic conditions. Longitudinal follow-up data were then used to construct transition frequency matrices, modeling the trajectory and dynamic evolution of multimorbidity among older people in China over time.Results: Using LCA, 2,798 participants were classified into four patterns: the multi-system disorder group (10.33%), the gastrointestinal metabolism group (44.07%), the cardiovascular disease group (37.81%), and the respiratory disease group (7.79%). Over five waves, the gastrointestinal metabolism group declined (from 74.70% in 2011 to 44.07% in 2020), while the cardiovascular group increased (from 15.87% to 37.81%). The multi-system and respiratory groups also grew. Transition analysis showed the gastrointestinal metabolism group was the least
Keywords: Multimorbidity1, older populations2, disease trajectory3, Public Health4, China5
Received: 20 Mar 2025; Accepted: 30 Jun 2025.
Copyright: © 2025 Liu, Lin, Yin, Liu, Zhu, Li, Shen and Feng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Bianling Feng, Xi'an Jiaotong University, Xi'an, China
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