Associations of the metabolic syndrome of different definitions and their individual components and cardiovascular disease in Chinese women.

<p>Adjusted for age, education, physical exercise, smoking, alcohol use, family history of coronary heart disease.</p><p>WHO, World Health Organization; NCEP-ATPIII, National Cholesterol Education Program Adult Treatment Panel III; IDF, International Diabetes Federation; CDS, Chinese Diabetes Society; JIS, Joint Interim Statement; WHR, waist/hip rate; BMI, body mass index; HDL-C, high density lipoprotein cholesterol; TGs, triglycerides; FPG, fasting plasma glucose; CHD, coronary heart disease; PAD, peripheral arterial disease.</p><p>Associations of the metabolic syndrome of different definitions and their individual components and cardiovascular disease in Chinese women.</p

Flow diagram of recruitment of participants in the analysis.

<p>Flow diagram of recruitment of participants in the analysis.</p

Associations of the metabolic syndrome of different definitions and their individual components with cardiovascular disease in Chinese men.

<p>Adjusted for age, education, physical exercise, smoking, alcohol use, family history of coronary heart disease.</p><p>WHO, World Health Organization; NCEP-ATPIII, National Cholesterol Education Program Adult Treatment Panel III; IDF, International Diabetes Federation; CDS, Chinese Diabetes Society; JIS, Joint Interim Statement; WHR, waist/hip rate; BMI, body mass index; HDL-C, high density lipoprotein cholesterol; TGs, triglycerides; FPG, fasting plasma glucose; CHD, coronary heart disease; PAD, peripheral arterial disease.</p><p>Associations of the metabolic syndrome of different definitions and their individual components with cardiovascular disease in Chinese men.</p

Baseline characteristics of participants.

<p>Data are presented as mean±SD, median (interquartile range) or percent. Chi-square test for categorical variables, the unpaired t test or Mann-Whitney U test for continuous variables.</p><p>^aData on hsCRP was available for 1887 men and 2286 women.</p><p>BMI, body mass index; WHR, waist/hip rate; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; hsCRP, high sensitivity C-reactive protein; CHD, coronary heart disease; PAD, peripheral arterial disease.</p><p>Baseline characteristics of participants.</p

Comparisons of Different Metabolic Syndrome Definitions and Associations with Coronary Heart Disease, Stroke, and Peripheral Arterial Disease in a Rural Chinese Population

<div><p>Objectives</p><p>We estimated the prevalence of metabolic syndrome (MetS) and compared associations of different MetS definitions with coronary heart disease (CHD), stroke, and peripheral arterial disease (PAD) in a rural Chinese population.</p><p>Methods</p><p>Among 4,748 residents (2,145 men and 2,603 women) aged 30+ years in rural China from 2006 to 2007, the prevalence of MetS was estimated by using five different definitions: modified World Health Organization (WHO), Chinese Diabetes Society (CDS), the updated National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) for Asian-Americans, International Diabetes Federation (IDF), and Joint Interim Statement (JIS). Multivariable logistic regression analyses were implemented to estimate the association between MetS and the prevalence of CHD, stroke and PAD, respectively.</p><p>Results</p><p>Prevalence of MetS in men was 11.5% (WHO), 14.8% (CDS), 32.4% (NCEP-ATP III), 27.5% (IDF) and 39.7% (JIS) and in women was 15.7% (WHO), 20.7% (CDS), 54.2% (NCEP-ATP III), 51.5% (IDF) and 54.2% (JIS), respectively. Respective ORs (95% CI) for associating MetS with CHD in men were 1.79 (1.02-3.17), 1.25 (0.69-2.26), 1.61 (1.01-2.58), 1.84 (1.14-2.96), and 1.53 (0.96-2.43). Corresponding ORs (95% CI) for stroke in men were 2.18 (95% CI 1.20 to 3.97), 2.20 (95% CI 1.25 to 3.89), 1.71 (95% CI 1.02 to 2.84), 1.30 (95% CI 0.77 to 2.23), and 1.61 (95% CI 0.97 to 2.68), respectively. In women, CHD and stroke were significantly associated with MetS using all five definitions of MetS. In addition, PAD was associated with all five MetS definitions in men, but not in women. Only hyperglycemia and BMI were significantly associated with PAD in women.</p><p>Conclusions</p><p>In this rural Chinese population, the JIS, IDF and CDS criteria may not be more suitable than WHO and updated NCEP-ATPIII definitions for screening high-risk individuals and estimating the risk of CHD and stroke from MetS, especially in men.</p></div

Distribution of participants according to the number of definitions of metabolic syndrome.

<p>Distribution of participants according to the number of definitions of metabolic syndrome.</p

Cumulative incidence (%) of diabetes among men (A) and women (B) by educational level.

<p>Cumulative incidence (%) of diabetes among men (A) and women (B) by educational level.</p

Definition of study participants.

<p>Definition of study participants.</p

Characteristics of the study groups at baseline in 2000, means ± SD, or N (%).

<p>Educational level differences were compared using chi-square test for categorical variables and ANOVA analysis for continuous variables.</p><p>Age, occupation, cigarette smoking, alcohol consumption, physical exercise, BMI, WC, RHR, BP, TC, TG, UA, and FPG were collected annually from 2000 to 2011.</p><p>Family history of diabetes, marriage status, and work strength were collected annually from 2000 to 2003.</p><p>Dietary intake and salt taste preference were collected in 2000 and 2003.</p

Association between educational level and incidence of diabetes among men and women at each BMI category.

<p>Model 1: unadjusted. Model 2: adjusted for baseline age, family history of diabetes, marriage status and occupation. Model 3: adjustments in model 2 plus baseline cigarette smoking, alcohol consumption, physical exercise, work strength, dietary intake and salt taste preference. Model 4: adjustments in model 3 plus baseline WC, RHR, BP, TC, TG, UA and FPG. Model 5: adjustments for risk factors in model 4 as time dependent variables.</p