The current study demonstrated that the prevalence of metabolic syndrome was dramatically high in hypertensive women, even in the rural areas of China. Further, our study indicated that remarkable ethnic differences exist in the prevalence of metabolic syndrome. Obese and moderate levels of physical activity were a modifiable risk factor.

BackgroundThe Body Mass Index (BMI) has long been used as an anthropometric measurement. Waist circumference (WC) and waist-to-height ratio (WHtR) have been proposed as alternatives to BMI. Recently, two new anthropometric indices, the A Body Shape Index (ABSI) and Body Roundness Index (BRI) have been developed as possible improved alternatives to BMI and WC. The main research aim is to assess the capacity of the ABSI and BRI to identify subjects with diabetes mellitus (DM) and the secondary aim is to determine whether ABSI and/or BRI is superior to the traditional body indices (BMI, WC, and WHtR).Methods and ResultsThis cross-sectional study was conducted in the rural areas of northeast China from January 2012 to August 2013, and the final analysis included data obtained form 5253 men and 6092 women. 1182 participants (10.4 %) suffered from DM. Spearman rank test showed that BRI and WHtR showed the highest Spearman correlation coefficient for DM whereas ABSI showed the lowest. The prevalence of DM increased across quartiles for ABSI, BMI, BRI, WC and WHtR. A multivariate logistic regression analysis of the presence of DM for the highest quartile vs. the lowest quartile of each anthropometric measure, showed that the WHtR was the best predictor of DM (OR: 2.40, 95 % CI: 1.42–3.39 in men; OR: 2.67, 95 % CI: 1.60–3.74 in women, both P < 0.001), and the ABSI was the poorest predictor of DM (OR: 1.51, 95 % CI: 1.05–1.97 in men; OR: 1.55, 95 % CI: 1.07–2.04 in women, both P < 0.05). ABSI showed the lowest AUCs (AUC: 0.61, 95 % CI: 0.58–0.63 for men; AUC: 0.61, 95 % CI: 0.59–0.63 for women) for DM in both sexes, while BRI (AUC: 0.66, 95 % CI: 0.63–0.68 for men; AUC: 0.67, 95 % CI: 0.65–0.69 for women) had high AUCs for DM that equaled those of WHtR.ConclusionsOur results showed neither ABSI nor BRI were superior to BMI, WC, or WHtR for predicting the presence of DM. ABSI showed the weakest predictive ability, while BRI showed potential for use as an alternative obesity measure in assessment of DM.

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We aimed to compare the relative strength of the association between anthropometric obesity indices and chronic kidney disease (CKD). Another objective was to examine whether the visceral adiposity index (VAI) and lipid accumulation product index (LAPI) can identify CKD in the rural population of China. There were 5168 males and 6024 females involved in this cross-sectional study, and 237 participants (2.12%) suffered from CKD. Obesity indices included body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), VAI and LAPI. VAI and LAPI were calculated with triglyceride (TG), high-density lipoprotein (HDL), BMI and WC. VAI = [WC/39.68 + (1.88 × BMI)] × (TG /1.03) × (1.31/ HDL) for males; VAI = [WC/36.58 + (1.89 × BMI)] × (TG/0.81) × (1.52/HDL) for females. LAPI = (WC-65) × TG for males, LAPI = (WC-58) × TG for females. CKD was defined as an estimated glomerular filtration rate (eGFR) of less than 60 mL/min per 1.73 m2. The prevalence of CKD increased across quartiles for WHtR, VAI and LAPI. A multivariate logistic regression analysis of the presence of CKD for the highest quartile vs. the lowest quartile of each anthropometric measure showed that the VAI was the best predictor of CKD in females (OR: 4.21, 95% CI: 2.09–8.47, p < 0.001). VAI showed the highest AUC for CKD (AUC: 0.68, 95% CI: 0.65–0.72) and LAPI came second (AUC: 0.66, 95% CI: 0.61–0.70) in females compared with BMI (both p-values < 0.001). However, compared with the traditional index of the BMI, the anthropometric measures VAI, LAPI, WC, and WHtR had no statistically significant capacity to predict CKD in males. Our results showed that both VAI and LAPI were significantly associated with CKD in the rural population of northeast China. Furthermore, VAI and LAPI were superior to BMI, WC and WHtR for predicting CKD only in females.