Research Of Gestational Weight Management And Pregnancy Outcome Among Women With Advanced Maternal Age

ObjectiveTo access the effect of age,pre-pregnancy body mass index(BMI)as well as gestational weight gain(GWG)on pregnancy outcome.MethodsWe retrospectively collected the antenatal record and inpatient record of 1015 women in advanced maternal age(AMA)who deliveried in the Maternal and Child Care Service Center of Fujian Province from January 1st to June 30th 2017.The data of age,pre-pregnancy weight,weight before deliveIy,diagnosis with gestational diabetes mellitus(GDM),hypertensive disorder complicating pregnancy(HDCP),preterm birth(PTB),macrosomia,small for gestational age(SGA)and neonatal birth weight(NBW)were collected.The AMA were divided into aged group(ages at delivery35~40 years)and super aged group(ages at delivery 40 years and older)according to their ages at delivery:chi-squared test were used for comparison of general conditions,GDM,HDCP,PTB,macrosomia and SGA between groups.The AMA were divided into low weight group(pre-pregnancy BMI<18.5kg/m~2),normal weight group(pre-pregnancyBMI18.5~24.9kg/m~2),overweightgroup(pre-pregnancyBMI25.0~29.9kg/m~2)and obese(pre-pregnancy BMI≥30kg/m~2)group according to their pre-pregnancy BMI,logistic regression analysis was used to examine the association between pre-pregnancy BMI and the risk of GDM,HDCP,PTB,macrosomia and SGA,one-way analysis of variance was used to examine the association between pre-pregnancy BMI and NBW.Refer to Institute of Medicine(IOM)guideline,normal pre-pregnancy weight women were divided into inadequate GWG group(GWG<11.5kg),normal GWG group(GWG 11.5~16.0kg),excessive GWG group(GWG>16.0kg)according to GWG,logistic regression analysis was used to examine the association between GWG and the risk of GDM,HDCP,PTB,macrosomia and SGA,one-way analysis of variance was used to examine the association between GWG and NBW.BP artificial neural network was used to examine the influence of pre-pregnancy BMI and GWG on pregnancy outcome.Results1.The incidence of GDM,HDCP and macrosomia increased with age while the prevalence of PTB and SGA does not.2.Pre-pregnancy overweight or obese increased the incidence of GDM and HDCP.Low pre-pregnancy weight and pre-pregnancy obese increased the incidence of PTB.The incidence of macrosomia as well as NBW increased with pre-pregnancy BMI.Low pre-pregnancy weight increased the incidence of SGA while pre-pregnancy overweight decreased the incidence of SGA.3.Within normal pre-pregnancy weight women,inadequate GWG decreased the incidence of GDM while increased the incidence of PTB and SGA,excessive GWG increased the incidence of HDCP and macrosomia,NBW increased with GWG.Conclusions1.Advanced childbearing age is a risk factor for multiple adverse pregnancy outcomes.2.Abnormal pre-pregnancy BMI,inadequate or excessive GWG are associated with increasing risk of adverse pregnancy outcomes.The incidence of adverse pregnancy outcomes can be effectively reduced by controlling BMI within normal range and GWG within the recommended range of IOM guidelines.3.BP neural network is applicable to the study of weight change during pregnancy in elderly pregnant women.