Premenstrual Symptoms in High School and University Students in Taif City, Saudi Arabia

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Introduction: Premenstrual symptoms are common, including both psychological and physical symptoms, affecting 80% of women during the luteal phase of the menstrual cycle and resolving a few days following menstruation. The importance of early diagnosis and treatment for premenstrual syndrome and PMDD could not be underestimated, given the burden and serious complications. In accord, our study aims to describe the prevalence of different premenstrual symptoms among high school and university students in Taif city, Saudi Arabia, while also identifying predictors of worse symptoms. Methods: Our cross-sectional study will target females in two different cohorts: those will enroll in a public high school in Taif city, Saudi Arabia, and the second belonging to university female students at the University of Taif, Taif city, Saudi Arabia. All participants and legal guardians, in case the participant will be younger than eighteen, will ask to provide written consent for their participation and will interviewe privately and confidentially to answer questions of questionnaire that include about participants' sociodemographic, gynecologic history, and premenstrual symptoms using the validated version of Premenstrual Symptoms Questionnaire (PSQ-S), a nineitem scale with eight questions focusing on premenstrual symptoms and one on social impairment. Data will entere and analyze using IBM SPSS 26. Result: There were 400 participants with the vast majority being university students (96.5%). The most noticeable were emotional and functional symptoms, especially mood swings, loss of interest, and effects on the daily life. There were significant differences in the PSQ-S scores between the educational levels and more symptoms were found with age increase (r = 0.343, p < 0.001). Another significant correlation was observed between age at menarche and severity of symptoms (r = 0.890, p < 0.001). Symptoms were also significantly linked to socioeconomic factors, such as parental education and income. Regression analysis revealed that age, maternal education, income, smoking status, and height were good predictors of the severity of the symptoms, and these factors accounted 16.4 percent of the variation.

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