| Objectives To study the the influencing factors of the incidence of gestational diabetes mellitus(GDM), and to explore the factors that result in GDM that tends to have negative pregnancy outcome. This experiment is designed for investigating the treatment of GDM, and thus improving the quality of maternal and perinatal health.Methods There are 168 GDM female patients who received prenatal examination from January 2013 to March 2015 at North China University of Science and Technology Affiliated Hospital and they were selected as researching subjects. Among these 168 cases, 6 cases of reentry for repetition symptoms, 5 cases without ultimate childbirths and continuous treatments, and 7 cases of incomplete medical records were excluded. There were 150 cases left as our research objects at last. Meanwhile, we chose 150 women who held a normal amount of glucose tolerance during pregnancy as our normal group. In order to explore the factors that result in GDM patients who tend to have a negative pregnancy outcome, 150 GDM women were divided into two groups: one for those who had an unsatisfied pregnancy outcome, and the other one for positive outcomes. By fulfilling questionnaires and collecting medical records befoe hospitalization, those clinical information and pregnancy outcome were all stored in SPSS 20.0 statistical software package. The measurement data(ages, gravidity, weight) were done with independent sample T-test and showed by mean±standard deviation( x ±s). The count data(occupation, residence) were done with Chi-square in single factor analysis and showed by percentage and multivariate correlation analysis were done with logistic regression.Results 1 Comparing the GDM patients group with the normal group, our single factor analysis shows there is a tremendous statistical difference among age, pregnancy BMI, educational backgrounds, family history of diabetes, and abnormal pregnant and delivery histories(P<0.05). What’s more, our multiple-facotor logistic analysis also showed significant statistical difference among age[OR=3.137, 95%CI(1.103,8.920)], pregnant BMI[OR=3.100, 95%CI(1.701,5.651)], and the family history of diabetes[OR=2.524, 95%CI(1.091,5.838)], and the abnormal pregnancy and delivery histories[OR=3.468, 95%CI(1.196,10.058)]. And the incidence of preeclampsia, and cesarean section and macrosomia for GDM group is higher than normal group(P<0.05). 2 By looking at the outcomes for both negative and positive pregnancy groups, our single factor analysis shows again that there is a different among pregnancy BMI, diagnosis BMI, the amounts of OGTT glucose, fast insulin, and HOMA-IR(P<0.05)which makes sense from a statistical perspective. And for the multiple-factor logistic analysis, our outcomes represented a distinct difference among pregnancy BMI[OR=1.500, 95%CI(1.132,1.988)] and the fasting blood glucose that retrieved from oral glucose tolerance test[OR=2.078, 95%CI(1.020,4.233)] which also demonstrates a statistical significance.Conclusions 1 The pregnant age(≥35 years old), the pregnancy BMI(≥24.0kg/m2), the family history of diabetes and abnormal pregnancy and delivery histories is the independent risk factors of GDM. Pregnant women with the above factors are at increased risk of GDM. 2 The risk of preeclampsia and macrosomia in GDM was significantly higher than that in normal pregnant women, and the rate of cesarean section was also significantly increased. 3 The increased pregnancy BMI and elevated OGTT fast blood glucose are risk factors of adverse pregnancy outcomes in GDM women. |
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