An unsupervised cluster analysis of multimorbidity patterns in older adults in Shenzhen, China
Xiaolong Guo, Peiyi Liu, Jing Guo, Naiwen Zhang, Haiyan Huang, Jianjun Liu, Zhen Tan, Guo Dan

TL;DR
This study identifies common health condition patterns in older adults in Shenzhen, China, to help improve healthcare strategies for aging populations.
Contribution
The study introduces a novel unsupervised clustering approach to explore multimorbidity patterns in older adults in Shenzhen.
Findings
Cardiometabolic comorbidities affect 15.83% of older adults in Shenzhen.
Hypertension is the most common comorbidity among older adults in the region.
Hyperuricemia is frequently associated with other chronic conditions in multimorbidity patterns.
Abstract
Population aging challenges health care systems due to the high prevalence and impact of multimorbidity in older adults. Studies on multimorbidity in Shenzhen have primarily focused on the quantity of multimorbidity, lacking in-depth exploration of multimorbidity patterns. Based on baseline data from the Shenzhen aging-related disease cohort, this study analyzed information from 8,911 people aged 60 and above after excluding missing and abnormal values from interview results. Using self-organizing map combined with weighted k-means, the distribution of diseases in the population was visualized, dividing the overall population into four clusters. The study also analyzed comorbidity and association rules for each cluster. This study found a high prevalence of cardiometabolic comorbidities among the older adult in Shenzhen, reaching 15.83%, and detailed the distribution of specific…
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Taxonomy
TopicsChronic Disease Management Strategies · Healthcare Systems and Reforms · Health disparities and outcomes
