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Frequency and types of clusters of major chronic diseases in 0.5 million adults in urban and rural China

on behalf of the China Kadoorie Biobank Collaborative Group; Hariri Parisa; Yu Canqing; Lv Jun; Clarke Robert; Chen Yiping; Chen Zhengming; Yang Ling; Bragg Fiona; Li Liming; Guo Yu; Bennett Derrick A

Frequency and types of clusters of major chronic diseases in 0.5 million adults in urban and rural China

on behalf of the China Kadoorie Biobank Collaborative Group
Hariri Parisa
Yu Canqing
Lv Jun
Clarke Robert
Chen Yiping
Chen Zhengming
Yang Ling
Bragg Fiona
Li Liming
Guo Yu
Bennett Derrick A
Katso/Avaa
26335565221098327.pdf (903.4Kb)
Lataukset: 

SAGE journals
doi:10.1177/26335565221098327
URI
https://journals.sagepub.com/doi/full/10.1177/26335565221098327
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2022081154505
Tiivistelmä

Background: Little is known about the frequency and types of disease clusters involving major chronic diseases that contribute to multimorbidity in China. We examined the frequency of disease clusters involving major chronic diseases and their relationship with age and socioeconomic status in 0.5 million Chinese adults.

Methods: Multimorbidity was defined as the presence of at least two or more of five major chronic diseases: stroke, ischaemic heart disease (IHD), diabetes, chronic obstructive pulmonary disease (COPD) and cancer. Multimorbid disease clusters were estimated using both self-reported doctor-diagnosed diseases at enrolment and incident cases during 10-year follow-up. Frequency of multimorbidity was assessed overall and by age, sex, region, education and income. Association rule mining (ARM) and latent class analysis (LCA) were used to assess clusters of the five major diseases.

Results: Overall, 11% of Chinese adults had two or more major chronic diseases, and the frequency increased with age (11%, 24% and 33% at age 50-59, 60-69 and 70-79 years, respectively). Multimorbidity was more common in men than women (12% vs 11%) and in those living in urban than in rural areas (12% vs 10%), and was inversely related to levels of education. Stroke and IHD were the most frequent combinations, followed by diabetes and stroke. The patterns of self-reported disease clusters at baseline were similar to those that were recorded during the first 10 years of follow-up.

Conclusions: Cardiometabolic and cardiorespiratory diseases were most common disease clusters. Understanding the nature of such clusters could have implications for future prevention strategies.

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