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.

Association between depression with glycemic control and its complications in type 2 diabetes.

AIMS: This study aims to determine the association between depression with glycemic control (HbA1c) and its complications. MATERIALS AND METHODS: This was a cross-sectional study that included 514 diabetic patients. The patients were randomly selected from among all type 2 diabetes patients referred to health and medical centers in Khorramabad town (Iran). Two questionnaires used for data collection. The first questionnaire included demographic information, diabetes and its complications and the second questionnaire was Beck Depression Inventory (BDI-II) which was used to assess depression. The stata software version 14 was used for data analysis. Then, for evaluate the association between depression with glycemic contol and its complications, Univariate and multiple logistic regression analysis were employed. RESULTS: The prevalence of depression in diabetic patients under study was 46.3% and for female and male was 49.6 and 36.8%; respectively. The results showed that 48.6% of diabetic patients did not have appropriate glycemic control status (HbA1c > 8). There was no significant association between glycemic control expressed as HbA1c levels and depression (OR: 1.11, 95% CI: 0.87-1.57). By contrast, sex (OR: 2.03, CI 95%: 1.03-3.99), residence (OR: 1.92, 95% CI: 1.28-2.91) and sexual complications (OR: 5.54, 95% CI: 1.07-27.87) have a significant statistical association with depression. CONCLUSION: The study highlights the high prevalence of depression in diabetic patients. However, there was no significant association between depression and glycemic control. The implementation of mental health screening for rapid diagnosis and timely treatment of depression seems essential in diabetic patients.