ECE2024 Eposter Presentations Reproductive and Developmental Endocrinology (78 abstracts)
1University Hospitals Coventry and Warwickshire NHS Trust, Diabetes and Endocrinology, Coventry, United Kingdom; 2University Hospital Coventry & Warwickshire, WISDEM, United Kingdom; 3University Hospital Coventry & Warwickshire, WISDEM, Coventry, United Kingdom
Introduction: Polycystic Ovary Syndrome (PCOS) affects 5-10% of childbearing females and, up to 20% in specific ethnic populations (i.e. South Asians and Hispanics). It is linked with a higher prevalence of obesity and metabolic dysfunction, resulting in increased risk for dyslipidaemia, impaired glucose tolerance, type 2 diabetes mellitus (T2DM) and cardiovascular diseases.
Methods: This is a retrospective study of patients diagnosed with PCOS (n=142) based on the European Society of Human Reproduction and Embryology (ESHRE) criteria. Data was collected from case notes and electronic records for patients diagnosed from January to December 2019. Medical history, anthropometric and bioimpedance data, including fat percentage (fat%), total fat mass and total fat-free mass, were recorded. Biochemical assessments were carried out in the early follicular phase of the menstrual cycle to assess biochemical androgen excess (Free Androgen Index FAI) and screen for metabolic co-morbidities. Patients were grouped based on phenotype: A - anovulatory cycles (ANOV), clinical and/or biochemical hyperandrogenism (HA), and polycystic ovarian morphology (PCO), B (ANOV+HA), C (HA+PCO) and D (ANOV+PCO). Statistical analysis was performed using SPSS statistics version 29.0, considering P<0.05 statistically significant.
Results: The mean age was 29.08±5.95 years. Most women had BMI greater than 40 kg/m2 (40.6%). Hyperandrogenic PCOS phenotypes were most common: Phenotype A in 51.7%, Phenotype B in 25.2% and Phenotype C in 11.9%. The analysis revealed significant correlations for Fat% in PCOS patients. There was a positive correlation between fat% and age (r=0.227, P<0.05), and a strong positive correlation with the Free Androgen Index (FAI) (r=0.292, P<0.01), indicating higher fat mass is associated with older age and increased androgen levels. Additionally, fat% was positively correlated with total cholesterol (TC) (r=0.234, P<0.05), the TC to high-density lipoprotein ratio (TC: Hdl) (r=0.379, P<0.001), triglycerides (r=0.327, P<0.01) and Haemoglobin A1c (HbA1c) (r=0.312, P<0.01). These correlations suggest that higher body fat percentage may be related to a greater risk of dyslipidaemia and impaired glucose metabolism.
Conclusion: This study showed that adiposity is significantly linked to key metabolic markers such as TC, TC:HDL ratio, triglycerides, and HbA1c, all of which are known risk factors for cardiovascular diseases. It highlights that body fat%, as measured by bioimpedance, is an important variable in the metabolic profile of women with PCOS, with implications for cardiovascular risk and impaired glucose metabolism. These results suggest that monitoring and managing adiposity is essential to reduce cardiovascular and metabolic risk in women with PCOS.