Adiposity Measures Derived from Bioelectrical Impedance are Associated with Cardiometabolic Markers in Women with Polycystic Ovary Syndrome

To compare bioelectrical impedance analysis (BIA)-derived body composition between women with polycystic ovary syndrome (PCOS) and body mass index (BMI)-matched controls, and to investigate associations with metabolic, hormonal, and inflammatory markers.

This cross-sectional study included 35 women with PCOS and 37 BMI-matched healthy controls, aged 18-40 years, with BMI <35 kg/m². Clinical, anthropometric, metabolic, hormonal, and inflammatory parameters were assessed. Body composition was determined by direct segmental multifrequency BIA, including fat mass (FM), trunk fat mass (trunk FM), lean mass (LM), FM index, fat-to-lean mass ratio (F/L ratio), and trunk-to-peripheral fat ratio.

Women with PCOS (28 ± 5.3 years, 26.6 ± 3.6 kg/m²) had higher FM index, trunk FM, and F/L ratio, while LM did not differ. They also showed higher fasting insulin, homeostatic model assessment for insulin resistance (HOMA-IR), glycated hemoglobin type A1c (HbA1c), low-density lipoprotein cholesterol, free androgen index, testosterone, androstenedione, and dehydroepiandrosterone sulfate, and lower sex hormone-binding globulin (SHBG). Among BIA parameters, FM, FM index, and F/L ratio showed more consistent associations with insulin resistance and selected inflammatory markers than trunk FM. In women with PCOS, these measures were positively correlated with fasting insulin and HOMA-IR and inversely correlated with SHBG. Associations with HbA1c and IL-6 were modest and not uniformly observed across all adiposity measures. No significant correlations were found with fasting glucose, HDL-c, triglycerides, or androgen levels.

Women with PCOS exhibit higher adiposity, particularly reflected by FM index and F/L ratio, which show closer associations with metabolic and inflammatory dysfunction than trunk FM. These findings support the potential use of BIA as an accessible, low-cost, and noninvasive tool for the cross-sectional assessment of metabolic dysfunction in PCOS. Longitudinal studies are needed to clarify the clinical relevance of these associations.