Measures of body adiposity and visceral adiposity index as predictors of metabolic syndrome among Thai women with PCOS

Abstract

Aim: To evaluate the relationship between measures of body adiposity and visceral adiposity index (VAI) and risk of metabolic syndrome (MS) and to identify the optimal cut-off points of each measurement in Thai polycystic ovary syndrome (PCOS).

Methods: A cross-sectional study was completed physical examination, fasting plasma glucose, lipid profiles of 399 PCOS and 42 age-matched normal controls. Body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and VAI were calculated. Associations between different measures and MS were evaluated and the receiver-operating characteristic (ROC) curve was performed to determine appropriate cut-off points for identifying MS.

Results: Percentage of MS in PCOS was 24.6%, whereas none MS in controls. Previously recommended cut-off values for body adiposity and VAI were significantly associated with MS. ROC curve analysis of the only PCOS showed newly obtained optimal cut-off points for BMI and VAI of ≥28 kg/m² (AUC = 0.90) and >5.6 (AUC = 0.94), respectively. Values found to be more accurate than the original ones. VAI was the best predictor, followed by BMI and WHtR.

Conclusion: All body adiposity and VAI parameters can predict the risk of MS. Optimal values for Thai PCOS were ≥28 kg/m² for BMI, ≥0.85 for WHR, ≥0.5 for WHtR and >5.6 for VAI.

Chinese abstract

目的：评估身体肥胖和内脏肥胖指数(VAI)与代谢综合征(MS)风险之间的关系，并确定泰国多囊卵巢综合症(PCOS)患者中每个指标的最佳临界点。

方法：对399例PCOS患者及42例年龄匹配正常对照组的体格检查、空腹血糖及脂质分布进行横断面研究。计算体质量指数(BMI),腰臀比（WHR），腰高比(WHtR)和VAI。不同评估措施和MS的联系被评估，特征曲线下（ROC）面积用来确定判断MS的适当临界点。

结果：PCOS患者中代谢综合征的发生率为24.6%，对照组中无代谢综合征发生。之前推荐的身体肥胖和内脏肥胖指数的临界值与代谢综合征（MS）显著相关。PCOS患者的ROC曲线分析显示了BMI≥28 kg/m²（AUC=0.90）和VAI=45.6的最佳临界点。其价值比原来更精确。VAI是最好的预测指标，其次是BMI和WHtR。

结论：所有身体肥胖和内脏肥胖指数（VAI）可以预测MS的风险。泰国PCOS的最优值是BMI≥28 kg/m²、WHR≥0.85，WHtR≥0.5和 VAI> 5.6。

• Body adiposity
• metabolic syndrome
• polycystic ovary syndrome
• Thai
• visceral adiposity index

Acknowledgements

The authors gratefully acknowledge Mr. Sutthipon Udompunturak for statistical support.

Declaration of interest

The authors hereby declare no personal or professional conflicts of interest regarding any aspect of this study.