Prevalence and determinant factors of premenstrual syndrome among secondary and preparatory school students in Dessie city administration, Northeast Ethiopia.

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.

Household food security status and its associated factors among pensioners in Arba Minch town, South Ethiopia.

Introduction: Food insecurity has remained a serious public health problem in developing countries, such as Ethiopia, over the past two decades. Vulnerable populations, such as pensioners, have been affected by this problem because of emerging socio-demographic changes, a global financial crisis, and climate change, all of which have contributed to the high food prices. Hence, this study aimed to assess household food security status and associated factors among pensioners in Arba Minch town, South Ethiopia. Methods: A community-based cross-sectional study design was conducted from September to October 2023. Two hundred forty-four pensioners were chosen using a simple random sampling technique. Data were collected, cleaned, and entered into EPI-Data version 4.6 and exported to SPSS version 25 for analysis. Variables with a p-value of ≤0.25 in the bivariate analyses were candidates for the multivariable regression analysis. In the multivariable logistic regression, variables with a p-value of 0.05 were considered to have a significant association with the dependent variable. Results: A total of 238 retired people were interviewed, with a response rate of 97.5%. Among the interviewed pensioners, 223 (91.4%) households were food insecure. Having more than one dependent member [AOR = 2.4, 95% C.I: 1.30, 6.64], being jobless after retirement [AOR = 3, 95% C.I:1.17, 5.61], and being in the lowest tertile of wealth status [AOR = 2, 95% C.I:1.36, 4.99] were identified as predictors of food insecurity. Conclusion: The magnitude of household food insecurity was higher compared to the national average, and factors such as the current occupational status of the household head, dependency ratio, and wealth status of the household were significantly associated with household food insecurity. Therefore, policymakers and programmers should provide new strategies focusing on additional income-generating activities and salary increments and consider free services such as school fees and healthcare.