Publication:

Comorbidity patterns and predictive factors in polycystic ovary syndrome: a cross-sectional study

Background Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women of reproductive age and is often associated with multiple metabolic and medical co-morbidities. Understanding the influence of demographic and laboratory parameters can aid in early identification and management. study aimed to evaluate the prevalence of medical co-morbidities in women diagnosed with PCOS and assess the impact of demographic and laboratory findings on these co-morbidities.

Methods A cross-sectional study was conducted on 393 women diagnosed with PCOS based on the Rotterdam criteria. Data on age, body mass index (BMI), menstrual history, and family history were collected. Laboratory evaluations included fasting glucose, insulin levels, lipid profile, and hormonal assays (LH, FSH, testosterone. Statistical analyses assessed associations between variables using chi-square and logistic regression.

Results Among 94 participants comorbid conditions, metabolic syndrome was identified in 27.65% of participants, while type 2 diabetes mellitus (T2DM) and hypertension were present in 14.89% and19.14%respectively. Mental health co-morbidities were also notable, with depression affecting18.05% and anxiety seen in 17.02% of the cohort higher BMI and elevated testosterone levels were significantly associated with metabolic abnormalities (p<0.05). Younger age at diagnosis and higher LH/FSH ratio were predictive of certain co-morbidities.

Conclusions Women with PCOS are at high risk for multiple medical co-morbidities, with demographic and laboratory parameters showing significant associations. Early identification of high-risk profiles can facilitate timely intervention and improve long-term outcomes.