Abstract
Objective: Premenstrual syndrome (PMS) is a common condition affecting women’s physical, mental, and social well-being.
Objective: To determine the prevalence of PMS, identify associated risk factors, and assess its impact on quality of life.
Methods: This cross-sectional study was conducted at a university-affiliated teaching hospital. PMS was assessed using the Premenstrual Assessment Form (PAF), and quality of life was measured with the Short Form-36 (SF-36). Sociodemographic factors, body mass index (BMI), smoking/caffeine consumption, and marital status were recorded. Statistical analyses were performed using SPSS 28.0, with significance set at p<0.05. Results: A total of 500 women aged 18–45 were included. Mean age was 28.0 ± 6.1 years, and mean BMI was 25.0 ± 4.8 kg/m². Nearly half were single (45.7%), and 67.4% had at least a high school education. Smoking and caffeine intake were reported by 17.1% and 18.3%, respectively. PMS prevalence was 70.0% (95% CI: 66.0–74.0), with 41.6% mild, 19.6% moderate, and 8.8% severe cases. Multivariate logistic regression identified younger age (18–30 years), BMI ≥ 30 kg/m², lower education, unmarried status, and smoking as independent PMS predictors (all p <0.05). Caffeine intake was not significantly associated (p=0.075). SF-36 analysis revealed significant differences in the scores of the Physical Functioning (p=0.006) and Mental Health (p=0.003) domains across PMS severity groups. However, Spearman’s correlation indicated low positive correlations between PMS severity and the scores of the Physical Function (r=0.32, p=0.003) and the Mental Health domains (r=0.45, p<0.001). Conclusion: PMS was significantly associated with multiple sociodemographic and lifestyle factors. Although the scores of the physical functioning and mental health domains of the SF-36 varied between different degrees of PMS severity, the correlation between these scores and PMS severity was low.
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