ORIGINAL RESEARCH article
Front. Public Health
Sec. Aging and Public Health
This article is part of the Research TopicLifestyle behaviors and chronic diseases: pathways, interventions, knowledge and public health challengesView all 10 articles
Analysis of Potential Categories and Influencing Factors of Chronic Disease Comorbidity Patterns Among Residents of Yantai City Based on a Health Ecology Model
Provisionally accepted
- 1Huazhong University of Science and Technology, Wuhan, China
- 2Yantai Institute of Technology, Yantai, China
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Objective To identify latent classes of chronic disease comorbidity and their influencing factors among residents in Yantai, China. Methods A cross-sectional survey of 10,681 adults (≥18 years) was conducted in 2024. Latent class analysis (LCA) was used to identify comorbidity patterns, and multinomial logistic regression was applied to analyze associated factors based on a health ecology model. Results LCA revealed four distinct comorbidity patterns: C1: Low Comorbidity Group (82.39%); C2: Musculoskeletal-Chronic Disease Mixed Group (9.48%); C3: Metabolic Syndrome-Dominant Group (7.01%); and C4: High Comorbidity-Complex Group (1.12%). Older age was a common risk factor for all comorbidity groups (OR=10.84, 95% CI: 8.85–13.28). Male sex was a protective factor for C2 (OR=0.66, 95% CI: 0.55–0.80) but a risk factor for C3 (OR=1.75, 95% CI: 1.44–2.12). Regular exercise (OR=0.76) and adequate sleep (OR=0.44) were protective, while frequent pickled food intake was a consistent risk factor (OR=1.63). Alcohol consumption specifically increased the risk of C3 (OR=1.43). Higher income raised the risk of C2 and C3 (OR=1.39). Conclusion Comorbidity patterns in Yantai show clear heterogeneity. Interventions should be pattern-specific, integrating local dietary culture and addressing factors across the health ecology model to reduce comorbidity burden.
Keywords: Chronic Disease Comorbidity, latent class analysis, health ecology model, Health, Yantai City
Received: 26 Aug 2025; Accepted: 27 Oct 2025.
Copyright: © 2025 liu, Cui, du, zhen, jiang, xu, gong and ye. 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:
qing ya liu, 1296029025@qq.com
ming chun ye, cynthiacui746@gmail.com
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