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

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.