PDF(Pubmed)
Abstract：
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%.
METHODS: 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.
CONCLUSIONS: 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.
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%.
METHODS: 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.
CONCLUSIONS: 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.
摘要：
背景：在埃塞俄比亚，经前综合症（PMS）主要在20岁出头的大学生中进行研究；结果，关于青春期女孩中经前综合症的患病率知之甚少。因此,这项研究的目的是确定经前综合征的患病率，并确定与经前综合征相关的因素在中学女学生在德西市政府，2023年。
方法：进行了一项基于机构的横断面研究，涉及630名参与者的样本。使用结构化的自我管理数据收集工具来收集必要的信息。为了确保数据质量，对数据收集者和监督者进行了预先测试和培训。将收集的数据输入到Epi-data软件中,并使用SPSS版本25进行分析。频率表,graphs,means,和中位数被用来描述研究参与者的特征。采用二元逻辑回归来确定重要因素。在最终的多变量逻辑回归中，p值≤0.05，调整比值比（AOR）的95％置信区间（CI）的变量被报告为与PMS相关的具有统计学意义的因素。使用Hosmer和Lemeshow拟合优度测试评估模型适合度。
结果：在本研究中，PMS的患病率为22%,95%CI=19-26%。
方法：年龄≥18岁（AOR=0.54；95%CI：0.34，0.86），月经持续时间≥7天（AOR=3.61;95％CI：1.25，10.37），存在慢性病（AOR=2.08；95%CI：1.04，4.16），咖啡摄入量(AOR=6.05；95%CI：2.05，17.87)，酒精摄入量（AOR=0.49；95%CI：0.28，0.86），使用止痛药（AOR=2.06;95％CI：1.10，3.86），使用激素避孕药（AOR=3.9；95％CI：1.58，9.62），睡眠障碍(AOR=3.82;95%CI:2.29,6.42)和体育锻炼(AOR=0.50;95%CI:0.28,0.87)与PMS显著相关。
结论：本研究中相当多的学生受经前期综合征的影响。年龄,月经持续时间，慢性疾病的存在，咖啡摄入量，使用止痛药，使用荷尔蒙避孕药，睡眠障碍与PMS显著相关。学生应避免过度饮酒，咖啡摄入量和使用止痛药没有处方。
方法：进行了一项基于机构的横断面研究，涉及630名参与者的样本。使用结构化的自我管理数据收集工具来收集必要的信息。为了确保数据质量，对数据收集者和监督者进行了预先测试和培训。将收集的数据输入到Epi-data软件中,并使用SPSS版本25进行分析。频率表,graphs,means,和中位数被用来描述研究参与者的特征。采用二元逻辑回归来确定重要因素。在最终的多变量逻辑回归中，p值≤0.05，调整比值比（AOR）的95％置信区间（CI）的变量被报告为与PMS相关的具有统计学意义的因素。使用Hosmer和Lemeshow拟合优度测试评估模型适合度。
结果：在本研究中，PMS的患病率为22%,95%CI=19-26%。
方法：年龄≥18岁（AOR=0.54；95%CI：0.34，0.86），月经持续时间≥7天（AOR=3.61;95％CI：1.25，10.37），存在慢性病（AOR=2.08；95%CI：1.04，4.16），咖啡摄入量(AOR=6.05；95%CI：2.05，17.87)，酒精摄入量（AOR=0.49；95%CI：0.28，0.86），使用止痛药（AOR=2.06;95％CI：1.10，3.86），使用激素避孕药（AOR=3.9；95％CI：1.58，9.62），睡眠障碍(AOR=3.82;95%CI:2.29,6.42)和体育锻炼(AOR=0.50;95%CI:0.28,0.87)与PMS显著相关。
结论：本研究中相当多的学生受经前期综合征的影响。年龄,月经持续时间，慢性疾病的存在，咖啡摄入量，使用止痛药，使用荷尔蒙避孕药，睡眠障碍与PMS显著相关。学生应避免过度饮酒，咖啡摄入量和使用止痛药没有处方。
