Region-specific body mass index (BMI) thresholds as a non-invasive predictor of polycystic ovary syndrome and insulin resistance in women in the United Arab Emirates: A retrospective observational study

Background Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder among women of reproductive age, strongly associated with obesity and insulin resistance. Despite its global significance, research on PCOS within the United Arab Emirates (UAE) context remains limited. This study explores the relationship between Body Mass Index (BMI) and the incidence of PCOS and insulin resistance in UAE women. Methods This retrospective observational study included 111 women, divided into PCOS and control groups. Data were collected from medical records at Thumbay University Hospital, Ajman, UAE, covering demographic, clinical, and biochemical parameters. BMI was calculated, and various hormonal and metabolic markers were analyzed. Statistical analyses, including Receiver Operating Characteristic (ROC) curve analysis, were performed to identify BMI thresholds predictive of PCOS and insulin resistance. Results Significant differences were observed between the PCOS and control groups in BMI, waist circumference, and metabolic markers, including fasting insulin and lipid profiles. The study identified a BMI cut-off of 27.2 kg/m² for predicting PCOS (sensitivity: 60.7%, specificity: 94.5%). For predicting insulin resistance within the PCOS group, the optimal BMI cut-off was 28.0 kg/m² (sensitivity: 64.3%, specificity: 90.9%). Conclusion BMI showed moderate predictive ability for PCOS and insulin resistance among women in the UAE. The BMI thresholds identified in this study may serve as a simple, non-invasive indicator to aid in the identification of women at increased risk of PCOS and related metabolic disturbances in this population.