Outcomes of High-Risk Pregnancies in Northern Iran: Multivariate Logistic Regression Model

Background and purpose: High-risk pregnancy is referred to a situation in which mother, fetus or neonate are in higher risk of morbidity or mortality. Because of adverse outcomes of high-risk pregnancies, this study aims to determine these outcomes in the North of Iran. Materials and Methods: We recruited 803 urban and rural pregnant women in this crosssectional study via consensus method. Data were collected by a questionnaire and analyzed using descriptive statistics [mean, standard deviation (SD)], chi-square test and multivariate logistic regression model. All data analyses were performed using SPSS software and P 0.05 was considered significant. Results: Mean ± SD, minimum and maximum age of participants were 27.0 ± 6.2, 14 and 44 years, respectively, 26.3% of which were urban residences. The frequency of adverse outcomes of pregnancy (stillbirth, abortion, and weight under 2500 g) was 10.8%. According to the multivariate logistic regression model, preeclampsia was significantly associated with adverse outcomes of high-risk pregnancy (Odds ratio = 2.7, 95% confidence interval: 1.03-7.10). Conclusion: Our study showed that preeclampsia during pregnancy is a predictive factor of adverse outcomes of pregnancy such as abortion, stillbirth, and low birth weight.