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.