Optimal Cutoff Points for Anthropometric Variables to Predict Insulin Resistance in Polycystic Ovary Syndrome
| Author | Hossein Hatami | en |
| Author | Seyed Ali Montazeri | en |
| Author | Nazanin Hashemi | en |
| Author | Fahimeh Ramezani Tehrani | en |
| Issued Date | 2017-10-31 | en |
| Abstract | Background: Insulin resistance (IR) is a major cardiometabolic risk factor in females with polycystic ovary syndrome (PCOS). The euglycemic clamp is the gold standard method to measure IR. However, considering the time and cost that it takes, surrogate markers of IR are now widely used. The current study aimed at evaluating the cutoff points of even less invasive anthropometric and body composition variables to predict IR in females with PCOS. Methods: The current cross sectional study selected 224 females with PCOS, using Rotterdam criteria, referred to reproductive endocrinology research center; 88 of which were diagnosed with insulin resistance. Receiver operating characteristics curve was used to explore the best cutoff values of each anthropometric and body composition measures. IR was defined as homeostasis model assessment formula greater or equal to 2.6: HOMA-IR = fasting insulin (mU/L) × fasting plasma glucose (mM/L)/22.5. Results: The highest area under the curve (0.751) was for the multiplication of waist circumference (WC) by body mass index (BMI), as a single index. The highest sensitivity and specificity were for body water (BW) percentage (82% for values greater than 32.85%) and WC (79% for values greater than 88 cm), respectively. Conclusions: It was concluded that there were simple anthropometric variables; e.g., WC × BMI, percentage of BW, and WC that could help to estimate IR in clinical settings especially when the gold standard or surrogate markers of IR were unavailable. | en |
| DOI | https://doi.org/10.5812/ijem.12353 | en |
| Keyword | Anthropometry | en |
| Keyword | Insulin Resistance | en |
| Keyword | Polycystic Ovary Syndrome | en |
| Keyword | Body Composition | en |
| Keyword | Homeostasis Model Assessment | en |
| Keyword | Body Weights and Measures | en |
| Publisher | Brieflands | en |
| Title | Optimal Cutoff Points for Anthropometric Variables to Predict Insulin Resistance in Polycystic Ovary Syndrome | en |
| Type | Research Article | en |
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