title: [Evaluation of the diagnostic criteria of gestational metabolic syndrome and analysis of the risk factors].
abstract: OBJECTIVE
  To investigate gestational multiple metabolic abnormalities aggregation and diagnostic criteria for gestational metabolic syndrome (GMS), and to analyze the risk factors of GMS.
  
  
  METHODS
  A cohort study recruiting 309 pregnant women with preeclampsia, 627 pregnant women with gestational diabetes mellitus (GDM) and 1245 normal pregnant women was performed from January 2008 to December 2011 in Guangdong Women and Children's Hospital. Information regarding age, gestational weeks, basic blood pressure, admission blood pressure, height and body mass index(BMI)before pregnancy was recorded. Biochemical indicators including fasting plasma glucose (FPG), fasting insulin (FINS), total cholesterol (TC), triglyceride (TG), high density lipoprotein (HDL-C), low density lipoprotein (LDL-C), free fatty acids (FFA) were tested. GMS was diagnosed with three or all of the following conditions: (1) overweight and/or obesity before pregnancy (BMI ≥ 25 kg/m(2)); (2) hypertension with blood pressure ≥ 140/90 mm Hg (1 mm Hg = 0.133 kPa); (3) hyperglycemia:diagnosed as GDM; (4) dyslipidemia with TG ≥ 3.23 mmol/L. The incidence of GMS of the three groups were calculated and the risk factors were analyzed.
  
  
  RESULTS
  (1) The age, gestational weeks, basic blood pressure, admission blood pressure, BMI before pregnancy of women with preeclampsia and women with GDM were significantly different compared to normal women, respectively (P < 0.01). (2) Biochemical indicators of women with preeclampsia were as following: FPG (4.6 ± 1.0) mmol/L, FINS (10.1 ± 5.6) mU/L, TC (6.3 ± 1.6) mmol/L, TG (3.9 ± 1.8) mmol/L, HDL-C (1.4 ± 0.4) mmol/L, LDL-C (3.0 ± 1.0) mmol/L, FFA (0.8 ± 0.4) mmol/L. And those in women with GDM were: FPG (4.7 ± 0.9) mmol/L, FINS (10.2 ± 5.8) mU/L, TC (5.7 ± 1.3) mmol/L, TG (3.2 ± 1.1) mmol/L, HDL-C (1.4 ± 0.4) mmol/L, LDL-C (2.7 ± 0.9) mmol/L, FFA (0.6 ± 0.3) mmol/L. In normal pregnant women they were: FPG (4.3 ± 0.5) mmol/L, FINS (9.0 ± 4.4) mU/L, TC (5.7 ± 1.1) mmol/L, TG (2.8 ± 1.1) mmol/L, HDL-C (1.5 ± 0.4) mmol/L, LDL-C (2.9 ± 0.8) mmol/L, FFA (0.6 ± 0.2) mmol/L. Statistic differences were found in preeclampsia and GDM women compared to normal women respectively (P < 0.01). (3) The prevalence of GMS in preeclampsia group and in GDM group was 26.2% (81/309) and 13.6% (85/627), statistically different from that of the control group (0)(P < 0.01). (4) Compared to normal women, women with preeclampsia had higher risk of developing GMS (OR = 1.62, 95%CI 1.31 - 2.00, P < 0.01). The risk factors were BMI (OR = 1.29, 95%CI 1.13 - 1.47) and TG (OR = 2.49, 95%CI 1.87 - 3.31). Also, women with GDM had higher risk of developing GMS than normal women (OR = 1.27, 95%CI 1.09 - 1.49, P < 0.01), and the risk factors were BMI (OR = 1.13, 95%CI 1.04 - 1.23) and TG (OR = 1.16, 95%CI 1.02 - 1.33). TG was the independent risk factor in both preeclampsia women and GDM women (P < 0.01, P < 0.05). HDL-C seemed to have less importance in identifying GMS (P > 0.05).
  
  
  CONCLUSIONS
  According to the GMS diagnostic criteria used in this study, some preeclampsia patients and some GDM women had aggregation of multiple metabolic abnormalities including pre-pregnancy overweight/obesity, hyperglycemia, high blood pressure and dyslipidemia. TG was the independent risk factor for GMS. HDL-C seemed to have less importance in identifying GMS.
authors.affiliation: Department of Obstetrics, Guangdong Women and Children's Hospital, Guangzhou, China. njianmin@163.com
authors.forename: Jian-min
authors.initials: JM
authors.lastname: Niu
authors.forename: Qiong
authors.initials: Q
authors.lastname: Lei
authors.forename: Li-juan
authors.initials: LJ
authors.lastname: Lü
authors.forename: Ji-ying
authors.initials: JY
authors.lastname: Wen
authors.forename: Xiao-hong
authors.initials: XH
authors.lastname: Lin
authors.forename: Dong-mei
authors.initials: DM
authors.lastname: Duan
authors.forename: Xi
authors.initials: X
authors.lastname: Chen
authors.forename: Yu-heng
authors.initials: YH
authors.lastname: Zhou
authors.forename: Cai-yuan
authors.initials: CY
authors.lastname: Mai
authors.forename: Guo-cheng
authors.initials: GC
authors.lastname: Liu
authors.forename: Ming-min
authors.initials: MM
authors.lastname: Hou
authors.forename: Li-na
authors.initials: LN
authors.lastname: Zhao
authors.forename: Jing
authors.initials: J
authors.lastname: Yi
mesh_terms: D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure; D015992:Body Mass Index; D015331:Cohort Studies; D016640:Diabetes, Gestational / Q000097:blood / Q000453:epidemiology*; D005260:Female; D006801:Humans; D052439:Lipid Metabolism Disorders / Q000150:complications* / Q000453:epidemiology; D008074:Lipoproteins / Q000097:blood; D024821:Metabolic Syndrome / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology*; D050177:Overweight / Q000150:complications* / Q000453:epidemiology; D011225:Pre-Eclampsia / Q000097:blood / Q000453:epidemiology*; D011247:Pregnancy; D012189:Retrospective Studies; D012307:Risk Factors; D014280:Triglycerides / Q000097:blood
chemical_list: D001786:Blood Glucose; D008074:Lipoproteins; D014280:Triglycerides