Cardiovascular disease (CVD) has become a serious public health problem in recent years in China. Aggregation of CVD risk factors in one individual increases the risk of CVD and the risk increases substantially with each additional risk factor. This study aims to explore the relationship between the number of clustered CVD risk factors and different types of obesity. A multistage stratified random cluster sampling design was used in this population-based cross-sectional study in 2012. Information was collected by face to face interviews. One-way analysis of variance (ANOVA), chi-square test, Kruskal-Wallis test and multiple logistic regression were used in this study. The prevalence of general obesity, central obesity and compound obesity were 0.3%, 36.1% and 14.7%, respectively. The prevalence of hypertension, hyperlipidemia and diabetes in the compound obesity group were higher than those in other groups (compound obesity > central obesity > general obesity > non-obesity), while smoking rate in the non-obesity group was higher than those in other groups (non-obesity > general obesity > central obesity > compound obesity). People with obesity were more likely to have one or more CVD risk factor compared with non-obesity subjects (general obesity (OR: 2.27, 95% CI: 1.13-4.56), central obesity (OR: 2.64, 95% CI: 2.41-2.89), compound obesity (OR: 5.09, 95% CI: 4.38-5.90). The results were similar when the number of clustered CVD risk factors was ≥ 2 and ≥ 3. As a conclusion, more than half of the residents in Jilin Province have a problem of obesity, especially central obesity. Government and health department should take measures to improve people's awareness of central obesity in Jilin Province of China. The prevalence of hypertension, hyperlipidemia and diabetes are associated with obesity types. Compound obesity has a greater risk to cluster multiple CVD risk factors than central obesity and general obesity. Taking measures to control obesity will reduce the prevalence of CVD in Jilin Province.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4962226PMC
http://dx.doi.org/10.3390/ijerph13070685DOI Listing

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