Prevalence and Severity of Premenstrual Symptoms Among Urban Working Indian Women: A Cross-Sectional Study
Year: 2024
Type: article
Study design: Observational Study
Abstract: Background: Premenstrual Syndrome (PMS) affects many working women of reproductive age, but its prevalence and symptom patterns in urban Indian populations are not well characterized. This study aims to assess the prevalence and severity of premenstrual symptoms among working urban Indian women. Methods: A cross-sectional study was conducted among 67 women aged 23-39 from Mumbai and Delhi. Participants completed the Premenstrual Symptom Screening Tool (PSST) questionnaire by Steiner et al., for assessing the severity of 19 common premenstrual symptoms. Descriptive statistics were performed to examine symptom prevalence and severity. Results: The most commonly reported ‘moderate to severe’ symptoms were ‘physical symptoms’ (breast tenderness, headaches, joint or muscle pain, bloating and weight gain), ‘fatigue or lack of energy’ and ‘anger or irritability’ whereas ‘Insomnia’, decreased interest in home activities, difficulty in concentrating were found to be the least severe. Conclusion: This study provides insights into the prevalence and severity of premenstrual symptoms among urban working Indian women. The high rates of emotional and physical symptoms highlight the need for increased awareness and management strategies for PMS in this population. Major Findings: This study found that urban working Indian women commonly experience moderate to severe physical symptoms, fatigue and anger/irritability during their premenstrual phase. The symptoms significantly impact work efficiency, social relationships, and home responsibilities. Interestingly, hypersomnia was more prevalent than insomnia among the participants, suggesting a unique sleep disturbance pattern in these women.
Authors: Upama Misra, Saamdu Chetri, Hina Sharma
Institution: Shoolini University
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4408312943