Prevalence and risk factors of metabolic syndrome among pre-menopausal and post-menopausal women in Hebei province

  Objective  To examine the prevalence and risk factors of metabolic syndrome (MS) among pre-menopausal and post-menopausal adult women in Hebei province and to provide references for developing comprehensive measures on chronic disease prevention and control.

  Methods  Using multistage random cluster sampling, we recruited 3 751 female residents aged 18 years and older and living in 13 counties or districts across Hebei province at least 6 months during previous one year; then we conducted a questionnaire survey, physical examination, and laboratory test among the women between October and December 2015. Four factor models of MS were firstly constructed by Amos 21.0 and then the four models were evaluated with confirmatory factor analysis (CFA) to obtain risk factor models applicable in the pre-menopausal (less than 50 years old) and post-menopausal (50 years old and older) women.

  Results  Significantly higher waist circumference (WC), body mass index (BMI), waist/height ratio (WHtR), systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), fasting plasma glucose (FPG), glycosylated hemoglobin (HbA₁c), total cholesterol (TC), triglyceride (TG), and high density lipoprotein cholesterol (HDL-C) but significantly lower density lipoprotein cholesterol(LDL-C) and height were observed among the post-menopausal women than among the pre-menopausal women (all P < 0.05). The MS prevalence rate was 26.55% among all the women and the prevalence rate was significantly higher among the post-menopausal women than among the pre-menopausal women (45.53% vs. 17.63% , χ² = 188.926; P < 0.001). Confirmatory factor analysis revealed that the established model B had a better fit for pre-menopausal women (χ² = 11.271, P = 0.004, root mean square residual RMR = 0.001, root mean square error of approximation RMSEA = 0.049, goodness-of-fit index GFI = 0.997, Akaike information criteria AIC = 27.271, Bayes information criteria BIC = 71.106, consistent Akaike information criteria CAIC = 79.106, expected cross-validation index ECVI = 0.015 and its 95% confidence interval 90% CI ECVI: 0.011 – 0.024); while the model A had a better fit for post-menopausal women (χ² = 4.312, P = 0.11, RMR = 0.043, RMSEA = 0.024, GFI = 0.999, AIC = 20.312, BIC = 65.038, CAIC = 73.038, ECVI = 0.010 90% CI: 0.009 – 0.015). Multivariate analysis results demonstrated that WHtR, TG, FPG, and SBP were main components of MS risk factors model for pre-menopausal women, with TG as a major factor (factor loadings: 0.62 > 0.50) reflecting main characteristics of the model; whereas, WC, TG/HDL-C, FPG, and MAP were main components of MS risk factors model for post-menopausal adult women, with WC as a major factor (factor loadings: 0.56 >0.50) reflecting the main characteristics of the model.

  Conclusion  The MS prevalence is relatively high among post-menopausal women in Hebei province and different single factor models composed of different factors are applicable for pre-menopause and post-menopause women separately, suggesting that specific intervention measures on MS should be taken according to risk factor characteristics of the two population groups.