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. 2024 Mar 25:10:1327568.
doi: 10.3389/fmed.2023.1327568. eCollection 2023.

Predicted risk factors associated with secondary infertility in women: univariate and multivariate logistic regression analyses

Wafa Fatima  1 , Abdul Majeed Akhtar  1 , Asif Hanif  1 , Aima Gilani  2 , Syed Muhammad Yousaf Farooq  3
Affiliations

Predicted risk factors associated with secondary infertility in women: univariate and multivariate logistic regression analyses

Wafa Fatima et al. Front Med (Lausanne). .

Abstract

Introduction: Infertile women are those who regularly engage in unprotected intercourse for a period of at least 1 year and are unable to become clinically pregnant. Primary infertility means the inability of couples to conceive, without any previous successful pregnancies. Secondary Infertility refers to the inability to get pregnant for 12 months, after having a previous pregnancy for one time at least. The objectives of the current study were to analyze risk factors for secondary infertility and compare the predictive accuracy of artificial neural network (ANN) and multiple logistic regression models.

Methods: The study was conducted at The University Institute of Public Health collecting data from Gilani Ultrasound Center 18 months after approval of synopsis. A total of 690 women (345 cases and 345 controls) were selected. The women selected for the case group had to be 20-45 years of age, had any parity, and had a confirmed diagnosis of secondary infertility.

Results: Multiple logistic regression (MLR) and ANN were used. The chance of secondary infertility was 2.91 times higher in women living in a joint family [odds ratio (OR) = 2.91; 95% confidence interval (CI) (1.91, 4.44)] and was also 2.35 times higher for those women who had relationship difficulties with their husband [OR = 2.35; 95% CI (1.18, 4.70)]. Marriage at an earlier age was associated with secondary infertility with β being negative and OR being < 1 [OR = 0.94; 95% CI (0.88, 0.99)]. For the logistic regression model, the area under the receiver operative characteristic curve (ROC) was 0.852 and the artificial neural network was 0.87, which was better than logistic regression.

Discussion: Identified risk factors of secondary infertility are mostly modifiable and can be prevented by managing these risk factors.

Keywords: artificial neural network (ANN); logistic regression analysis; multivariate; secondary infertility; univariate.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Receiver operating characteristic (ROC) of logistic regression model.
Figure 2
Figure 2
Normalized importance through artificial neural network.
Figure 3
Figure 3
Receiver operating characteristic (ROC) for ANNs.
See this image and copyright information in PMC

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