Visceral and Dysfunctional Adiposity Indices as Predictors of Insulin Resistance and Metabolic Syndrome in Women with Polycystic Ovary Syndrome: A Cross-Sectional Study

<i>Background and Objectives</i>: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age. Women with PCOS often have metabolic disorders such as insulin resistance (IR), type 2 diabetes (T2DM), obesity, and metabolic syndrome (MetS). The assessment of visceral adiposity and dysfunctional adipose tissue is crucial for understanding the metabolic risks associated with PCOS. The visceral adiposity index (VAI) and the dysfunctional adiposity index (DAI) are two novel metabolic indices that more specifically assess adipose tissue dysfunction and visceral fat accumulation. This study aimed to evaluate the clinical utility of VAI and DAI as predictive markers for metabolic complications such as insulin resistance (IR) and metabolic syndrome (MetS) in women with PCOS. <i>Materials and Methods</i>: This cross-sectional study included 92 women diagnosed with PCOS based on the 2023 revised Rotterdam criteria, as well as 68 healthy controls. Anthropometric and biochemical parameters, including fasting glucose, insulin, lipid profile, and hormonal markers, were recorded. VAI and DAI were calculated using established formulas derived from previous validated studies. <i>Results</i>: The mean VAI in PCOS patients was 4.26 ± 3.23, compared to 2.61 ± 1.92 in controls (<i>p</i> = 0.003). The mean DAI in PCOS patients was 3.00 ± 1.86, while in controls it was 1.86 ± 1.22 (<i>p</i> = 0.003). Both VAI (Area Under the Curve [AUC] = 0.639) and DAI (AUC = 0.635) did not demonstrate statistically significant diagnostic performance for PCOS itself, but they were strongly associated with metabolic disturbances within the PCOS group. VAI and DAI values were significantly elevated in PCOS patients with IR (<i>p</i> < 0.001) and MetS (<i>p</i> < 0.001). For MetS in PCOS patients, VAI demonstrated the highest predictive ability, with an AUC of 0.87 and a cutoff of 4.73 (sensitivity 62%, specificity 92%), while DAI had an AUC of 0.86 with a cutoff of 2.44 (sensitivity 74%, specificity 80%). Regarding IR in PCOS patients, VAI had an AUC of 0.75 with a cutoff of 2.56 (sensitivity 82%, specificity 56%), while DAI had an AUC of 0.74 with a cutoff of 1.59, showing a sensitivity of 82% and a specificity of 55%. <i>Conclusions</i>: Although VAI and DAI are not suitable for diagnosing PCOS, they provide valuable insights into the metabolic risks associated with the condition. VAI and DAI can serve as promising biomarkers for identifying IR and MetS risk in women with PCOS. Their integration into clinical practice may facilitate the early detection of cardiometabolic complications, offering a more specific metabolic risk assessment compared to traditional anthropometric measures.

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Journal
Medicina
Published
2025-02-28
DOI
https://doi.org/10.3390/medicina61030424
Citations
7
Primary Topic
Ovarian function and disorders
Type
article
Field-Weighted Citation Impact
11.89
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article

Visceral and Dysfunctional Adiposity Indices as Predictors of Insulin Resistance and Metabolic Syndrome in Women with Polycystic Ovary Syndrome: A Cross-Sectional Study

Ali Yavuzcan, Betül Keyif
7 citations
Medicina
Ovarian function and disorders
11.89
article

Visceral and Dysfunctional Adiposity Indices as Predictors of Insulin Resistance and Metabolic Syndrome in Women with Polycystic Ovary Syndrome: A Cross-Sectional Study

Ali Yavuzcan, Betül Keyif
article en
7 citations

Abstract

<i>Background and Objectives</i>: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age. Women with PCOS often have metabolic disorders such as insulin resistance (IR), type 2 diabetes (T2DM), obesity, and metabolic syndrome (MetS). The assessment of visceral adiposity and dysfunctional adipose tissue is crucial for understanding the metabolic risks associated with PCOS. The visceral adiposity index (VAI) and the dysfunctional adiposity index (DAI) are two novel metabolic indices that more specifically assess adipose tissue dysfunction and visceral fat accumulation. This study aimed to evaluate the clinical utility of VAI and DAI as predictive markers for metabolic complications such as insulin resistance (IR) and metabolic syndrome (MetS) in women with PCOS. <i>Materials and Methods</i>: This cross-sectional study included 92 women diagnosed with PCOS based on the 2023 revised Rotterdam criteria, as well as 68 healthy controls. Anthropometric and biochemical parameters, including fasting glucose, insulin, lipid profile, and hormonal markers, were recorded. VAI and DAI were calculated using established formulas derived from previous validated studies. <i>Results</i>: The mean VAI in PCOS patients was 4.26 ± 3.23, compared to 2.61 ± 1.92 in controls (<i>p</i> = 0.003). The mean DAI in PCOS patients was 3.00 ± 1.86, while in controls it was 1.86 ± 1.22 (<i>p</i> = 0.003). Both VAI (Area Under the Curve [AUC] = 0.639) and DAI (AUC = 0.635) did not demonstrate statistically significant diagnostic performance for PCOS itself, but they were strongly associated with metabolic disturbances within the PCOS group. VAI and DAI values were significantly elevated in PCOS patients with IR (<i>p</i> < 0.001) and MetS (<i>p</i> < 0.001). For MetS in PCOS patients, VAI demonstrated the highest predictive ability, with an AUC of 0.87 and a cutoff of 4.73 (sensitivity 62%, specificity 92%), while DAI had an AUC of 0.86 with a cutoff of 2.44 (sensitivity 74%, specificity 80%). Regarding IR in PCOS patients, VAI had an AUC of 0.75 with a cutoff of 2.56 (sensitivity 82%, specificity 56%), while DAI had an AUC of 0.74 with a cutoff of 1.59, showing a sensitivity of 82% and a specificity of 55%. <i>Conclusions</i>: Although VAI and DAI are not suitable for diagnosing PCOS, they provide valuable insights into the metabolic risks associated with the condition. VAI and DAI can serve as promising biomarkers for identifying IR and MetS risk in women with PCOS. Their integration into clinical practice may facilitate the early detection of cardiometabolic complications, offering a more specific metabolic risk assessment compared to traditional anthropometric measures.

MedicinaVol. 61(3)
Sağlık Bilimleri Üniversitesi (TR), Ankara Bilkent City Hospital (TR), Düzce Üniversitesi (TR)
Good health and well-being
Openalex Percentile: Top 2%
Ovarian function and disorders
11.89
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