Literature DB >> 24199881

[The prevalence and risk factors of metabolic syndrome among adult residents in Guangdong and Jiangsu provinces in China].

Jin Li1, Yi-ming Shi, Jin-hua Yan, Wen Xu, Jian-ping Weng.   

Abstract

OBJECTIVE: To determine the current prevalence and risk factors of metabolic syndrome (MS) among adult residents in Chinese developed areas.
METHODS: The clinical data of 6614 adult residents, including 4051 women, from Guangdong and Jiangsu provinces from China Diabetes and Metabolic Disorders Study (2007-2008) were analyzed. Age and sex standardized prevalences of MS were calculated according to the criteria of Chinese Diabetes Society (CDS), US National Cholesterol Education Program Adult Treatment Panel III (ATP III), International Diabetes Federation (IDF) and Joint Interim Statement (JIS), respectively. Logistic regression analysis was performed to identify the risk factors of MS.
RESULTS: Age and sex standardized prevalences of MS were 17.88% (CDS), 28.50% (ATPIII), 21.99% (IDF) and 31.50% (JIS), respectively. The prevalences of residents with at least one metabolic abnormality were 67.86% (CDS) 79.56% (ATPIII), 79.62% (IDF) and 80.74% (JIS), respectively. MS was more common in female than in male by the ATPIII and IDF criterion (ATPIII: 30.63% vs 26.45%, P < 0.01; IDF: 26.04% vs 17.91%, P < 0.01), while the prevalence was higher in male by CDS criteria (15.94% vs 19.87%, P < 0.01). There was no significant difference in the MS prevalence between the rural and the urban residents. Kappa test showed ATPIII and JIS criteria were most homogenous (κ = 0.95, P < 0.01). The risk factors for MS by the logistic regression model were male, older age, lower degree of education, family history of hypertension and obesity, drinker as well as uncontrolled diet.
CONCLUSION: The prevalence of MS is high in the adult residents of Chinese developed areas (Guangdong and Jiangsu provinces), whatever diagnostic criterion was used .Effective measures should be taken to control the modifiable MS risk factors.

Entities:  

Mesh:

Year:  2013        PMID: 24199881

Source DB:  PubMed          Journal:  Zhonghua Nei Ke Za Zhi        ISSN: 0578-1426


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