Tehran University Medical Journal

Background: The aim of the study was to investigate associations between maternal characteristics, with emphasis on hematological status, and risk of low birth weight and preterm delivery among pregnant women

Methods: In a cohort study, 1,500 pregnant women attending Hazrat Zaynab Hospital for prenatal care and delivery in the period 2000-2001, without any risk factors for preterm delivery and low birth weight were included. Maternal characteristics including hematocrit values were recorded at the first antenatal visit. Main outcome measures included birth weight and gestation at delivery. Linear and logistic regression models were used to analyze data.

Results: Severe anemia (hematocrit< 24%) was associated with a significantly increased risk of low birth weight (<2500 g) and preterm delivery (< 37 weeks gestation). High hematocrit values (> 40%) did not increase the risk of low birth weight and preterm delivery. Teenagers, women with short height or low body mass index had significantly higher risk of delivering low birth weight infants.

Conclusion.: Severe maternal anemia, particularly in the first trimester, was significantly associated with adverse pregnancy outcome. Low maternal age, height or body mass index also increased the risk of low birth weight. Improved nutritional status of young women could contribute to improved health among their infant.

Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 !mso]> ject classid="clsid:38481807-CA0E-42D2-BF39-B33AF135CC4D" id=ieooui> Background: Gestational diabetes mellitus is diagnosed as carbohydrate in tolerance demonstrated for the first time in the course of pregnancy. The aim of this study was to evaluate the selective screening method for gestational diabetes mellitus (GDM) based on: 1- recommendation of the fourth workshop- conference on GDM 2- evaluation of risk factors
Methods: A case- control study was performed on 370 pregnancies inflicted by GDM in Hazrat Zaynab Hospital, Shahed University. The maternal and perinatal outcomes and prevalence of risk factors based on recommendation of the fourth workshop- conference on GDM in these women with GDM were compared with the same data and risk factors of randomly selected 600 pregnant women at the same time and in the same hospital, they all underwent universal testing for GDM, and their OGTT were normal.
Results: The prevalence of all risk factors was significantly higher in the group with GDM, but 45 of these women (12%) had no risk factors. 107 women (29%) with GDM were at low risk and would remain undiagnosed if selective screening method was used. The main neonatal complications in the low- risk group did not differ from the complications in other women with GDM.
Conclusions: The universal screening of all pregnant women seems to justified whereas the recommendations for not screening low- risk group are doubtful and require further examination.

Background: Cancer and obesity are two major public health concerns. More than 12 million cases of cancer are reported annually. Many reports confirmed obesity as a risk factor for cancer. The molecular relationship between obesity and breast cancer has not been clear yet. The purpose of this study was to investigate priorities of effective genes in the molecular relationship between obesity and breast cancer. Methods: In this study, computer simulation method was used for prioritizing the genes that involved in the molecular links between obesity and breast cancer in laboratory of systems biology and bioinformatics (LBB), Tehran University, Tehran, Iran, from March to July 2014. In this study, ENDEAVOUR software was used for prioritizing the genes and integrating multiple data sources was used for data analysis. Training genes were selected from effective genes in obesity and/or breast cancer. Two groups of candidate genes were selected. The first group was included the existential genes in 5 common region chromosomes (between obesity and breast cancer) and the second group was included the results of genes microarray data analysis of research Creighton, et al (In 2012 on patients with breast cancer). The microarray data were analyzed with GER2 software (R online software on GEO website). Finally, both training and candidate genes were entered in ENDEAVOUR software package. Results: The candidate genes were prioritized to four style and five genes in ten of the first priorities were repeated twice. In other word, the outcome of prioritizing of 72 genes (Product of microarray data analysis) and genes of 5 common chromosome regions (Between obesity and breast cancer) showed, 5 genes (TNFRSF10B, F2, IGFALS, NTRK3 and HSP90B1) were the priorities in the molecular connection between obesity and breast cancer. Conclusion: There are some common genes between breast cancer and obesity. So, molecular relationship is confirmed. In this study the possible effect of gene F2 polymorphism in making breast cancer associated with obesity risk factor was confirmed, the fact that past studies have not been reported.