Determination of maternal risk factors of preterm delivery: Adjusted for sparse data bias; results from a population-based case-control study in Iran

Objective To determine the maternal risk factors associated with preterm delivery in Iran. Methods A population-based case-control study was conducted including 48 women having preterm delivery (case group) and 100 women having term delivery (control group) between March 2007 and March 2012 in the maternity hospitals of the Selseleh County, Lorestan province, Iran. Information regarding maternal risk factors was collected by structured interview and reviewing the medical records. The maternal risk factors associated with preterm delivery were identified using univariate and multivariable logistic regression analysis after adjusting the sparse data bias. The area under the receiver operating characteristic (ROC) curves was estimated to evaluate the discrimination power of the statistical models. Results Multivariable analysis demonstrated that multiparty (odds ratio OR, 14.23; 95% confidence interval CI, 1.60-127.05), history of gestational diabetes (OR, 0.10; 95% CI, 0.01-0.99), thyroid dysfunction (OR, 97.32; 95% CI, 5.78-1,637.80), urinary tract infection (OR, 16.60; 95% CI, 3.20-85.92), and taking care during pregnancy (OR, 0.12; 95% CI, 0.03-0.50) had significant impact on preterm delivery after adjusting the potential confounders. The area under the ROC curve for the aforementioned maternal risk factors was 0.86 (95% CI, 0.80-0.92). Conclusion Our study provides evidence for the associations between multiparty, history of gestational diabetes, thyroid dysfunction, urinary tract infection, as well as taking care during pregnancy, and preterm delivery. © 2020 Korean Society of Obstetrics and Gynecology