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Obesity (Silver Spring). 2013 Aug;21(8):1690-4. doi: 10.1002/oby.20096. Epub 2013 Apr 13.

The visceral adiposity index as a predictor of insulin resistance in young women with polycystic ovary syndrome.

Author information

  • 1Department of Internal Medicine, Ewha Womans University School of Medicine, Ewha Womans University Mokdong Hospital, Yangcheon-Ku, Seoul 158710, Korea. jyoh@ewha.ac.kr

Abstract

OBJECTIVE:

Visceral fat accumulation is more strongly related to insulin resistance than to excess total adiposity. The visceral adiposity index (VAI) has recently been suggested as an indicator of the visceral adiposity measured by magnetic resonance imaging. To evaluate whether the VAI could replace visceral computed tomography (CT) scanning and predict insulin resistance in young women with polycystic ovary syndrome (PCOS) was presented.

DESIGN AND METHODS:

One hundred and eighty Korean women aged 16-41 years who were diagnosed with PCOS using the Rotterdam criteria were included. The VAI was derived from a formula using body mass index, waist circumference, triglycerides, and high-density lipoprotein cholesterol. Visceral adiposity was defined as a visceral fat area (VFA) measuring > 100 cm(2) by CT scanning. Insulin sensitivity was evaluated by insulin-mediated glucose utilization (M value), which was obtained using a euglycemic hyperinsulinemic clamp.

RESULTS:

The VAI positively correlated with VFA, the visceral-to-subcutaneous fat ratio, and systolic and diastolic blood pressure, and negatively correlated with the M value. In a linear regression analysis, the VAI was an independent determinant of the insulin sensitivity after controlling for age, systolic blood pressure, fasting glucose, fasting insulin, and testosterone levels. In a logistic regression analysis, the VAI odds ratio was 3.5 (95% CI 1.2-9.8) for predicting visceral adiposity after controlling for the various metabolic parameters and testosterone.

CONCLUSION:

The VAI can replace visceral CT scanning as a marker for visceral adiposity, and it predicts insulin resistance in young women with PCOS.

PMID:
23585246
DOI:
10.1002/oby.20096
[PubMed - indexed for MEDLINE]
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