BMI and Polycystic Ovary Syndrome: Demographic Trends in Weight and Health

Cureus. 2024 Mar 3;16(3):e55439. doi: 10.7759/cureus.55439. eCollection 2024 Mar.

Abstract

Introduction Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects women in adolescence and reproductive age. The distribution of PCOS across different body mass index (BMI) categories can vary, and research has shown associations between PCOS and weight status. This study tries to evaluate the distribution of PCOS in relation to BMI in women attending the PCOS clinic in a tertiary hospital in eastern India. Methodology This hospital-based cross-sectional study was carried out in the gynecology outpatient department of a tertiary care center. The study population included all the women in the age group between 15 and 45 years diagnosed as having PCOS using the Rotterdam definition. The various physical, clinical, and biochemical parameters were measured in the study population and compared among the obese and lean PCOS patients. Results and discussion A total of 143 women were included in the study. The mean age of the study population was 26.8 years. Among these, the underweight and normal weight patients were categorized as lean PCOS patients, 35 in number (24.5%), and overweight and obese patients were categorized as obese PCOS patients, 108 in number (75.5%). All the physical parameter measures like age (mean = 28.05, SD = 5.722), height (mean = 153.384, SD = 6.679), weight (mean = 68.182, SD = 11.501), waist circumference (mean = 95.135, SD = 10.291), hip circumference (mean = 101.47, SD = 9.320), waist-to-hip ratio (mean = 0.940, SD = 0.0831), and neck circumference (mean = 34.85, SD = 2.445) were significantly higher in the obese group as compared to the lean group. Menstrual irregularity was significantly more common in the obese PCOS patients as compared to the lean PCOS group (p = 0.02). There was a significant difference (p < 0.05) between the obese and lean PCOS patients when the biochemical parameters like fasting insulin, fasting glucose, and homeostatic model assessment of insulin resistance (HOMA-IR) were compared. There is a strong link between obesity, insulin resistance, and PCOS. Obesity can exacerbate insulin resistance, a common feature of PCOS, leading to increased levels of insulin and androgens. Conclusion The demographic distribution of PCOS in relation to BMI is essential for tailoring interventions and treatments.

Keywords: insulin resistance; lean pcos; lifestyle modification (lsm); obese pcos; obesity; polycystic ovary syndrome; polycystic ovary syndrome (pcos).