What factors are linked to PMS in school-age girls?

Background: In Ethiopia, premenstrual syndrome (PMS) was predominantly studied among university students who were in their early 20s; as a result, little is known about the prevalence of premenstrual syndrome among adolescent girls. Therefore, this study aimed to determine the prevalence of premenstrual syndrome and identify factors associated with premenstrual syndrome among secondary school female students in the Dessie city administration, 2023. Methods: An institutional-based cross-sectional study was conducted involving a sample of 630 participants. A structured self-administered data collection tool was used to gather the necessary information. To ensure data quality, the pretesting and training of the data collectors and supervisors were conducted. The collected data were entered into Epi-data software and analyzed using SPSS version 25. Frequency tables, graphs, means, and medians were used to describe the characteristics of the study participants. Binary logistic regression was employed to identify significant factors. Variables with a p-value ≤ 0.05 with 95% confidence interval (CI) of adjusted odds ratio (AOR) in the final multivariable logistic regression were reported as statistically significant factors associated with PMS. Model fitness was evaluated using the Hosmer and Lemeshow goodness-of-fit test. Results: In the present study, the prevalence of PMS was 22%, 95% CI = 19-26%. Factors: Age ≥ 18 years (AOR = 0.54; 95% CI: 0.34, 0.86), duration of menstruation ≥ 7 days (AOR = 3.61; 95% CI: 1.25, 10.37), presence of chronic illness (AOR = 2.08; 95% CI:1.04, 4.16), coffee intake (AOR = 6.05; 95% CI: 2.05, 17.87), alcohol intake (AOR = 0.49; 95% CI: 0.28, 0.86), use of pain medication (AOR = 2.06; 95% CI:1.10, 3.86), use of hormonal contraceptives (AOR = 3.9; 95% CI:1.58, 9.62), sleep disturbance (AOR = 3.82; 95% CI: 2.29, 6.42) and physical exercise (AOR = 0.50; 95% CI: 0.28, 0.87) were significantly associated with PMS. Conclusion: A significant number of students in this study were affected by premenstrual syndrome. Age, duration of menstruation, presence of chronic illness, coffee intake, use of pain medication, use of hormonal contraceptives, and sleep disturbance were significantly associated with PMS. Students should avoid excessive use of alcohol, coffee intake and use of pain medication without prescription.

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