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. 2016 Jun 9;11(6):e0157081. doi: 10.1371/journal.pone.0157081

Table 2. Comparison of pregnancy outcomes between pre-pregnancy underweight, normal weight, overweight and obese women.

Underweight Normal weight Overweight Obesity p-value*
BMIa < 18.5kg/m2 18.5≦BMI < 25kg/m2 25≦BMI < 30kg/m2 BMI≧30kg/m2
n = 17724 n = 69126 n = 7502 n = 2805
PIHb
%(n) 3.34%(n = 592) 4.68%(n = 3237) 10.08% (n = 756) 14.65%(n = 411) <0.001
OR(95%CI) 0.724(0.657–0.798) 1 2.373 (2.125–2.649) 3.693 (3.170–4.302)
GDMc
%(n) 2.66%(n = 472) 3.86%(n = 2665) 10.72% (n = 804) 20.61%(n = 578) <0.001
OR(95%CI) 0.737(0.663–0.819) 1 2.905 (2.645–3.189) 6.582 (5.833–7.427)
SGAd
%(n) 13.21%(n = 2341) 8.67%(n = 5992) 7.24% (n = 543) 7.06% (n = 198) <0.001
OR(95%CI) 1.657 (1.557–1.764) 1 0.807 (0.731–0.891) 0.790(0.688–0.908)
LGAe
%(n) 5.46%(n = 967) 10.05%(n = 6944) 17.36% (n = 1302) 22.60% (n = 634) <0.001
OR(95%CI) 0.50 (0.466–0.536) 1 1.96 (1.834–2.094) 2.709 (2.457–2.988)
Preterm birth
%(n) 12.2%(n = 2154) 10.2%(n = 7063) 11.6%(n = 873) 12.1% (n = 338) <0.001
OR(95%CI) 1.236(1.164–1.313) 1 1.133 (1.043–1.230) 1.187 (1.044–1.350)
Spontaneous preterm birth
%(n) 10.2%(n = 1810) 8.3%(n = 5751) 8.8%(n = 662) 9.1% (n = 256) <0.001
OR(95%CI) 1.275(1.196–1.359) 1 1.037 (0.937–1.134) 1.085 (0.937–1.256)
PPROMf
%(n) 3.78%(n = 670) 3.01%(n = 2081) 3.35%(n = 251) 3.35% (n = 94) <0.001
OR(95%CI) 1.261(1.145–1.3890) 1 1.114 (0.976-Ⅰ.273) 1.115 (0.893–1.392)
Induce preterm birth
%(n) 1.9%(n = 344) 1.9%(n = 1317) 2.8%(n = 211) 2.9% (n = 82) <0.001
OR(95%CI) 1.034(0.922–1.160) 1 1.509 (1.302–1.748) 1.573 (1.232–2.010)
Total C/Sg
%(n) 22.54%(n = 3995) 26.95%(n = 18627) 36.78%(n = 2759) 42.96% (n = 1205) <0.001
OR(95%CI) 0.857 (0.818–0.897) 1 1.506 (1.420–1.597) 2.042 (1.855–2.248)
PPHh with VDi
%(n) 19.57%(n = 3468) 20.94% (n = 14476) 21.22% (n = 1592) 22.07% (n = 619) <0.001
OR (95%CI) 0.886 (0.842–0.932) 1 1.070 (0.999–1.146) 1.104 (0.995–1.226)
PPH with C/S
% (n) 4.74% (n = 840) 7.64% (n = 5281) 11.37% (n = 853) 13.80% (n = 387) <0.001
OR (95%CI) 0.659 (0.601–0.722) 1 1.461 (1.338–1.595) 1.91 (1.684–2.167)
macrosomia>4000g
% (n) 0.27% (n = 47) 0.69% (n = 474) 1.76% (n = 132) 3.07% (n = 86) <0.001
OR (95%CI) 0.375 (0.280–0.503) 1 2.609 (2.159–3.154) 4.599 (3.667–5.767)
post-term pregnancy
% (n) 0.16% (n = 28) 0.24% (n = 169) 0.41% (n = 31) 0.57% (n = 16) <0.001
ORj (95%CIk) 0.623 (0.431–0.901) 1 1.879 (1.250–2.824) 2.524 (1.546–4.120)

aBMI, body mass index

bPIH, pregnancy-induced hypertension

cGDM, gestational diabetes mellitus

dSGA, small for gestational age

eLGA, large for gestational age

fPPROM, preterm prelabor rupture of membranes

gC/S,cesarian section

hPPH,postpartum hemorrhage

iVD,Vaginal delivery

jOR, odds ratio

kCI, confidence interval

Logistic regression was used to adjust for confounding variables, including maternal age, maternal height and parity, and generalized estimating equations (GEE) for logistic regression was used to adjust for the clustering of deliveries by hospitals. The results were expressed as odds ratios (OR) and 95% confidence intervals (CI).