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[Research on the pattern and influencing factors of cardiometabolic multimorbidity in China].

Authors: Y F, Wang; Z W, Wang; C Y, Zheng; X, Wang; Y X, Tian; X, Cao; R H, Feng;

[Research on the pattern and influencing factors of cardiometabolic multimorbidity in China].

Abstract

Objective: To investigate the prevalence, comorbidity patterns, and associated factors of cardiometabolic multimorbidity (CMM) in China. Methods: From 2012 to 2015, a total of 34 994 residents aged ≥35 years were enrolled using a stratified multistage random sampling method across 31 provinces, autonomous regions, and municipalities in China. Data were collected through questionnaires, covering demographic characteristics, behavioral and lifestyle factors, and self-reported history of cardiometabolic diseases. CMM was defined as the coexistence of two or more cardiometabolic diseases in the same individual. Association rule analysis using the Apriori algorithm from the arules package was employed to identify strong CMM patterns. Multivariable logistic regression was employed to explore factors associated with CMM. Results: The mean age of the participants was 55.6 years. Among them, 15 926 were male (45.51%). The prevalence of cardiometabolic multimorbidity (CMM) was 11.25% (3 937/34 994). A total of 35 distinct CMM combinations (each with a frequency ≥10) were identified. The most prevalent dyad, triad, and tetrad comorbidity patterns were hypertension+hyperlipidemia (1 036 cases), hypertension+hyperlipidemia+diabetes (352 cases), and hypertension+stroke+hyperlipidemia+diabetes (54 cases), respectively. Nine strong CMM patterns were identified using the Apriori association rule algorithm. Multivariable logistic regression analysis showed that older age (≥70 years: OR=17.39,95%CI 13.92-21.71,P<0.01), junior high school education (OR=1.31, 95%CI 1.17-1.48, P<0.01), senior high school or above education (OR=1.45, 95%CI 1.27-1.65, P<0.01), retirement (OR=3.09, 95%CI 2.76-3.46, P<0.01), unemployment or being laid-off (OR=1.16, 95%CI 1.06-1.28, P<0.01), a family history of cardiometabolic disease (OR=4.37, 95%CI 4.04-4.72, P<0.01), regular smoking (OR=1.38, 95%CI 1.24-1.53, P<0.05), and occasional smoking (OR=1.21, 95%CI 1.00-1.49, P<0.01) were significantly associated with an increased risk of CMM. Conclusion: The prevalence of cardiometabolic multimorbidity in China is relatively high, with the most common comorbidity patterns involving combinations of hypertension and hyperlipidemia, often accompanied by diabetes and stroke. Older age, retirement status, smoking, and a family history of cardiovascular disease are associated with an increased risk of both single and multiple cardiometabolic conditions. Greater attention should be paid to individuals with a single cardiometabolic disorder due to their elevated risk of developing multimorbidity.

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Keywords

Male, Adult, China, Multimorbidity, Hyperlipidemias, Comorbidity, Middle Aged, Logistic Models, Metabolic Diseases, Cardiovascular Diseases, Risk Factors, Surveys and Questionnaires, Hypertension, Prevalence, Diabetes Mellitus, Humans, Female, Aged

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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