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. 2023 Sep 25;13(10):1959.
doi: 10.3390/life13101959.

The Role of Different Methods in Defining Cardiometabolic Risk and Metabolic Syndrome in Women with Polycystic Ovary Syndrome

Nihan Çakır Biçer  1 , Asime Aleyna Ermiş  1 , Dilşat Baş  2
Affiliations

The Role of Different Methods in Defining Cardiometabolic Risk and Metabolic Syndrome in Women with Polycystic Ovary Syndrome

Nihan Çakır Biçer et al. Life (Basel). .

Abstract

Polycystic ovary syndrome (PCOS) is one of the most frequent endocrine illnesses, often accompanied by visceral adiposity and metabolic syndrome (MetS). Visceral adiposity is an accurate predictor of MetS and cardiometabolic risk. This study aims to evaluate different anthropometric indices that can be used in PCOS and MetS risk assessment. A total of 66 women with PCOS (50%) and 66 controls (50%) were included, and clinical and biochemical parameters were evaluated. The body mass index (BMI), body shape index (ABSI), body roundness index (BRI), dysfunctional adiposity index (DAI), lipid accumulation (LAP) index, and visceral adiposity index (VAI) were calculated. The means of all indices were higher in the PCOS group (p < 0.05). The marker with the lowest discriminatory ability for PCOS and MetS was ABSI (AUC = 0.762 and AUC = 0.714, respectively, p = 0.000). According to the multivariate logistic regression model, the VAI and WC are strong predictors of PCOS (AUC, 98%; accuracy, 92%; sensitivity, 92%; and specificity, 91%), and WC, LAP index, and BRI are strong predictors of MetS (AUC, 0.95%; accuracy, 86%; sensitivity, 83%; and specificity, 88%). The use of different anthropometric indices in the detection of PCOS and MetS may allow for early diagnosis and treatment, and are simple and cost-effective.

Keywords: a body shape index; body mass index; body roundness index; dysfunctional adiposity index; lipid accumulation index; metabolic syndrome; polycystic ovary syndrome; visceral adiposity; visceral adiposity index.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
ROC curves of anthropometric measurements and indices for predicting PCOS.
Figure 2
Figure 2
ROC curves of anthropometric measurements and indices for predicting MetS.
Figure 3
Figure 3
ROC curve of a multivariate logistic regression model of anthropometric measures and indices to predict PCOS.
Figure 4
Figure 4
ROC curve of a multivariate logistic regression model of anthropometric measures and indices to predict MetS.
See this image and copyright information in PMC

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