Sexuality and psychological well-being in different polycystic ovary syndrome phenotypes compared with healthy controls: a cross-sectional study
Abstract
Introduction Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. The present study aimed to compare the women with different PCOS phenotypes with the healty group in terms of sexual function, depression, anxiety and quality of life scale. Materials and methods The present cross-sectional study was carried out on 192 women with PCOS (classified on the basis of Rotterdam criteria into four categories) and 50 healthy controls. All participants were asked to fill out the valid and reliable questionnaires of FSFI (Female Sexual Function Index), HADS (Hospital Depression and Anxiety Scale) and SF-12. Results In the HADS questionnaire, phenotype B achieved the highest mean score in anxiety and depression domains, whereas, phenotype B had the lowest mean score in the FSFI and SF-12 quassionnaires. Furthermore, there was a significant difference between the women with PCOS phenotypes and the control grroup in arousal, lubrication, pain, and mean total score of FSFI (P < 0.05). In regression logistic analysis, age, infertility and depression were predictors of sexual dysfunction (P < 0.05). Conclusion The results indicated significant differences in terms of sexual dysfunction, depression, anxiety and quality of life in the women suffering from different phenotypes of PCOS compared with the healthy group. These results provide evidence that care and recommendations for improving women’s QoL and sexual function should be considered…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 192 participants or records.
Read the paper
Related studies
- Increased expression of circulating miRNA-93 in women with polycystic ovary syndrome may represent a novel, non-invasive biomarker for diagnosis
- Identification of key genes associated with polycystic ovary syndrome (PCOS) and ovarian cancer using an integrated bioinformatics analysis
- Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
- Regulation of Androgen Receptor Expression Alters AMPK Phosphorylation in the Endometrium: In Vivo and In Vitro Studies in Women with Polycystic Ovary Syndrome
- Effect of oral administration of low-dose follicle stimulating hormone on hyperandrogenized mice as a model of polycystic ovary syndrome
- Systems pharmacology to investigate the interaction of berberine and other drugs in treating polycystic ovary syndrome
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.