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Predictive factors for infertility of women: an univariate and multivariate logistic regression analysis

机译:女性不孕的预测因素:单因素和多因素logistic回归分析

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摘要

Background and aims: Infertility is a major problem during reproductive age. Physical and psychological effects of infertility in women are problematic. The aim of this study was to determine the potential predictive factors of infertility, among women referring both public and private health centers in Ilam province, western Iran, in 2013. Methods: In this cross-sectional study, 1013 women referring the health care centers of Ilam province were enrolled in 2013. The participants were selected by simple random sampling method and their demographic, medical and obstetric variables were collected. The univariate and multiple logistic regression analyses were used to predict the potential risk factors of infertility. Results: The husband’s education and occupation showed to be suitable independent predictor variables for infertility by multivariate logistic regression analysis (OR: 1.36 and 2, respectively). Overall percentage of correct classification of the model was 88.7. It means that, considering the husband’s education and women’s occupation, the ability of the model to predict the actual category of the cases was 88.7. Conclusions: It seems that husband education level and women occupation are independent predictive variables. The women at risk of infertility have to be identified and high-quality counseling should be given in order to minimize the complications of infertility in both genders.
机译:背景与目的:不育是生育年龄的主要问题。妇女不育的生理和心理影响是成问题的。这项研究的目的是确定在2013年伊朗西部伊兰省同时转诊到公共和私人卫生中心的妇女中不育的潜在预测因素。方法:在本横断面研究中,转诊卫生中心的1013名妇女2013年招募了伊拉姆省的伊利诺伊州。通过简单的随机抽样方法选择了参与者,并收集了他们的人口统计学,医学和产科变量。单因素和多元逻辑回归分析用于预测不孕的潜在危险因素。结果:通过多元logistic回归分析,丈夫的受教育程度和职业是不育的合适独立预测变量(或:分别为1.36和2)。该模型正确分类的总体百分比是88.7。这意味着,考虑到丈夫的学历和妇女的职业,该模型预测病例实际类别的能力为88.7。结论:看来丈夫的受教育程度和妇女的职业是独立的预测变量。必须确定有不孕风险的妇女,并应提供高质量的咨询,以最大程度地减少两性的不孕并发症。

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