Predictive Factors of Dysmenorrhea Among Women of Reproductive Age: A Multivariate Logistic Regression Analysis of Lifestyle and Biological Determinants

Dysmenorrhea is a prevalent gynecological condition that adversely affects women’s daily functioning and quality of life. This cross-sectional study examined associations between lifestyle and biological factors and dysmenorrhea among 310 women of reproductive age recruited from community settings in Padang, West Sumatra, Indonesia. Data on menstrual patterns, history of candidiasis, alcohol consumption, medication use, sleep quality, and body mass index (BMI) were collected using structured questionnaires and anthropometric measurements. In bivariate analysis, candidiasis and alcohol consumption were associated with dysmenorrhea; however, these associations were attenuated and did not remain statistically significant in the adjusted multivariate model. Multivariate logistic regression identified two independent associations, poor sleep quality was associated with increased odds of dysmenorrhea (OR = 6.12, 95% CI: 2.07–18.08, p = 0.001), while medication use was associated with decreased odds of dysmenorrhea (OR = 0.27, 95% CI: 0.08–0.99, p = 0.048). These findings indicate that, after adjustment for other factors, sleep quality and use of medication were the primary correlates of dysmenorrhea in this sample. Interventions that promote sleep hygiene and ensure appropriate symptom management may help reduce the burden of dysmenorrhea.