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Multimorbidity has become a widely recognized public health problem worldwide. Identifying multimorbidity patterns can improve not only the efficiency of healthcare resource utilization but also patients' prognosis. This article summarizes three common approaches for the identification of multimorbidity patterns: association analysis methods (including association rule mining and network analysis), classification methods (including cluster analysis, latent class analysis, and latent transition analysis), and dimensionality reduction and feature extraction methods (including principal component analysis, factor analysis, and multiple correspondence analysis), introduces the application of these methods using data from the UK Biobank to identify multimorbidity patterns and discusses and compares the results of case analysis to provide reference for the selection of appropriate methods for multimorbidity pattern research.
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http://dx.doi.org/10.3760/cma.j.cn112338-20241127-00753 | DOI Listing |
PLoS One
September 2025
School of Public Health, Changzhi Medical College, Changzhi, China.
Background: In China, the prevalence of chronic diseases is increasing, especially in rural areas, affecting younger populations and associating with multimorbidity. However, in resources-limited rural areas, there is a lack of primary data to the prevalence and patterns of multimorbidity in young populations. This study aims to analysis the differences in multimorbidity prevalence and patterns across different age groups and genders among adults in rural Shanxi Province.
View Article and Find Full Text PDFCureus
August 2025
Department of Conservative Dentistry and Endodontics, Amrita Vishwa Vidyapeetham, Amrita School of Dentistry, Kochi, IND.
Oral health is important for the overall health of an individual, particularly older adults. However, a number of obstacles frequently prevent older people from receiving timely and appropriate dental care. These obstacles are intricate and multifaceted, involving systemic diseases, cognitive elements, and psychological, financial, and educational issues.
View Article and Find Full Text PDFDiabetes Obes Metab
September 2025
Phase I Clinical Trial Research Ward, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China.
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is an emerging global health concern, and its presence increases the risk of multi-system diseases. This study aimed to investigate the multimorbidity trajectories of chronic diseases in people living with MASLD.
Methods: We identified 137 859 MASLD patients in UK Biobank and used 'propensity score matching' to match an equal number of non-MASLD controls.
Front Med (Lausanne)
August 2025
Chongqing General Hospital, Chongqing, China.
Background: The prevalence, patterns, and impact of multimorbidity on health-related quality of life (HRQoL) remain inadequately understood among rural populations in southwest China. This study seeks to fill this knowledge gap by systematically examining these aspects.
Methods: Participants were recruited from the China Multi-Ethnic Cohort (CMEC) study.
Compr Physiol
October 2025
School of Pharmacy and Medical Sciences, Griffith University, Southport, Queensland, Australia.
Mechanisms underlying cardiovascular, affective, and metabolic (CAM) multimorbidity are incompletely defined. We assessed how two risk factors-chronic stress (CS) and a Western diet (WD)-interact to influence cardiovascular function, resilience, adaptability, and allostatic load (AL); explore pathway involvement; and examine relationships with behavioral, metabolic, and systemic AL. Male C57Bl/6 mice (8 weeks old, n = 64) consumed a control (CD) or WD (12%-65%-23% or 32%-57%-11% calories from fat-carbohydrate-protein) for 17 weeks, with half subjected to 2 h daily restraint stress over the final 2 weeks (CD + CS and WD + CS).
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