学生痛经的特点和预测因素

F. Abid, Musa Aamer, Samira Faiz, F. Azam, A. Shaheen, N. Javed
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摘要

痛经是一种非常常见的生殖问题,存在于年轻女性中,严重影响她们的生活。目的:了解巴基斯坦大学生原发性痛经的患病率,痛经与各种因素的关系,以及痛经对学习成绩的影响。方法:在巴基斯坦不同的大学进行了一项观察性研究。数据是通过自行设计、预先测试的问卷收集的。在网上发布。使用IBM Statistical Package for Social Sciences (SPSS) version (Armonk, NY) 26.0对数据进行分析。定性变量采用描述性统计。计算定量变量的均值和标准差。采用卡方法确定周期长度的差异是否与痛经显著相关。应用t检验来确定痛经患者的年龄和体重指数是否有显著差异。结果:共有226名学生参与了本研究。有193人(85.40%)报告痛经,其中97人(50.26%)服用药物或联合用药来缓解痛经。痛经伴睡后疲劳的应激症状发生率较高(p<0.05)。体力活动对痛经没有任何影响。体力活动、疼痛的平均程度和每个周期疼痛的存在是痛经的显著预测因子(p<0.05)。结论体力活动和疼痛特征,如周期性和强度,是痛经的预测因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dysmenorrhea in students: Characteristics and predictors
Introduction: Dysmenorrhea is a very common reproductive issue present in young females that severely impacts their life. Objectives: To determine the prevalence of primary dysmenorrhea amongst undergraduate students of Pakistan, the association of dysmenorrhea with various factors, and the impact on academic performance. Methodology: An observational study was carried out at different Pakistani universities. The data was collected using a self-designed, pre-tested questionnaire. which was distributed online. The data was analyzed using IBM Statistical Package for Social Sciences (SPSS) version (Armonk, NY) 26.0. Descriptive statistics were applied for qualitative variables. Mean and standard deviation were calculated for quantitative variables. Chi-square was applied to determine if the differences in cycle length were significantly related to dysmenorrhea. T-tests were applied to determine if there were significant differences in age and body mass index in participants with dysmenorrhea. Result: There were 226 students who had participated in the study. There were 193 (85.40%) participants who reported experiencing dysmenorrhea out of which 97 students (50.26%) took a drug or a combination of drugs to alleviate the pain. There was a high prevalence of stress symptoms associated with dysmenorrhea with fatigue after sleep (p<0.05). Physical activity did not have any effect on dysmenorrhea. Physical activity, the average grade of pain, and the presence of pain in each cycle were significant predictors of dysmenorrhea (p<0.05). Conclusion Physical activity and characteristics of pain, such as cyclical nature and intensity, are predictors of dysmenorrhea. 
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