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Table 5 Linear regression analyses: Relationship between maternal exposure to smoking, preeclampsia and fetal growth

From: Smoking in preeclamptic women is associated with higher birthweight for gestational age and lower soluble fms-like tyrosine kinase-1 levels: a nested case control study

Model Unadjusted β (95% CI) p-value Adjusted β# (95% CI) p-value
Model 1a z-score BWGA = smoker + preeclampsia + interaction term     
Smoker -0.29 (-0.51,-0.08) 0.008 -0.38 (-0.61, -0.15) 0.0013
Preeclampsia -0.67 (-0.91,-0.43) < 0.0001 -0.67 (-0.93, -0.41) < 0.0001
Smoker* preeclampsia 0.86 (0.36, 1.36) 0.0008 0.86 (0.33, 1.39) 0.0015
Model 1b z-score BWGA = smoker + preeclampsia + interaction term + z-score PWGA     
Smoker -0.30 (-0.50, -0.09) 0.004 -0.32 (-0.54, -0.09) 0.0067
Preeclampsia -0.61 (-0.86, -0.35) < 0.0001 -0.60 (-0.87, -0.33) < 0.0001
Smoker* preeclampsia 0.74 (0.25, 1.23) 0.003 0.69 (0.16, 1.22) 0.0112
z-score PWGA 0.56 (0.48, 0.65) < 0.0001 0.52 (0.43, 0.61) < 0.0001
Model 2a z-score BWGA = log hair nicotine + preeclampsia + interaction term     
Log nicotine -0.12 (-0.16, -0.05) 0.0004 -0.086 (-0.16, -0.01) 0.0234
Preeclampsia -0.31 (-0.55, -0.07) 0.011 -0.36 (-0.63, -0.09) 0.0087
Log hair nicotine * preeclampsia 0.28 (0.11, 0.46) 0.002 0.26 (0.07, 0.46) 0.0091
Model 2b z-score BWGA = log hair nicotine + preeclampsia + interaction term + z-score PWGA     
Log nicotine -0.09 (-0.16, -0.03) 0.005 -0.06 (-0.13, 0.01) 0.0912
Preeclampsia -0.31 (-0.54, -0.08) 0.009 -0.33 (-0.60, -0.07) 0.0131
Log hair nicotine * preeclampsia 0.25 (0.07, 0.42) 0.007 0.25 (0.06, 0.44) 0.0095
z-score PWGA 0.56 (0.48, 0.64) < 0.0001 0.52 (0.42, 0.62) < 0.0001
  1. Dependent variable for all models: z-score birthweight for gestational age (BWGA), as defined in Kramer et al [14]
  2. PWGA = placental weight for gestational age; z-score PWGA calculated as defined by McNamara [15, 16]
  3. # analyses adjusted for age, pre-pregnancy body mass index, maternal language other than French or English, diabetes, chronic hypertension and parity (nullipara vs. other). For adjusted models 1a and 1b, diabetes was statistically significant (p = 0.03 and p = 0.03, respectively). No other variables were statistically significant in any of the models.
  4. R-square for models: Model 1a unadjusted, 0.057, Model 1a adjusted, 0.096; Model 1b unadjusted, 0.388, Model 1b adjusted, 0.391; Model 2a unadjusted, 0.062, Model 2a adjusted, 0.100; Model 2b unadjusted, 0.395, Model 2b adjusted, 0.384.