Aims: This study aimed to compare body compositions, as assessed by bioelectrical impedance analysis (BIA), hormonal parameters, and metabolic profiles of women with polycystic ovary syndrome (PCOS) according to their IR status.
Methods: Ninety-four women diagnosed with PCOS according to the Rotterdam criteria were included. IR was assessed in 86 patients and defined as HOMA-IR >2.5. Participants were classified as insulin-resistant (IR+) or insulin-sensitive (IR–). Anthropometric measurements, body composition parameters, oral glucose tolerance test results, lipid profiles, and hormonal parameters were compared.
Results: IR was present in 51 patients, while 35 were IR–. Compared with the IR–, IR+ patients had significantly higher body weight, BMI, waist and hip circumferences, body fat percentage, fat mass, fat-free mass, muscle mass, bone mass, total body water, basal metabolic rate, metabolic age, and visceral fat ratio (p<0.0001). In contrast, total body water percentage was significantly lower in the IR+ group (p<0.001). In multivariable logistic regression analysis, fat mass emerged as the only independent predictor of insulin resistance (OR=1.115, 95% CI: 1.053–1.180, p<0.001), whereas BMI was not significant. Insulin resistance prevalence did not differ significantly across Rotterdam PCOS phenotypes. IR+ patients also exhibited higher fasting and 120-minute glucose and insulin levels during oral glucose tolerance testing, higher triglyceride and VLDL levels, and lower HDL levels (p<0.05). No significant differences were observed between groups in total testosterone, DHEAS levels, or Ferriman–Gallwey scores.
Conclusion: Although IR can be observed in both lean and obese women with PCOS, obesity appears to aggravate the metabolic severity of the disease. Hyperandrogenism may be more severe in IR+ women but is also present in IR– patients, indicating that androgen excess in PCOS cannot be explained solely by IR. Assessment of body composition, including fat mass, may provide a more sensitive tool than BMI alone for identifying metabolic risk in PCOS.
| Primary Language | English |
|---|---|
| Subjects | Endocrinology |
| Journal Section | Research Article |
| Authors | |
| Submission Date | December 27, 2025 |
| Acceptance Date | February 4, 2026 |
| Publication Date | March 12, 2026 |
| DOI | https://doi.org/10.32322/jhsm.1850275 |
| IZ | https://izlik.org/JA38XN27XF |
| Published in Issue | Year 2026 Volume: 9 Issue: 2 |
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