Statistics
For each of the ten biomarkers the data was log-transformed using the natural logarithm in order to obtain normal distribution. The mode of delivery was stratified into three groups; VD, pre-labour CS and in-labour CS, as classified by obstetrician at the time of birth. Two-way ANOVA was used to test for overall difference between birth type, where GA was included in the model as well as the interaction, and to test for the overall difference between genders, where birth type was included in the model as well as the interaction. A t-test with un-pooled variance was used to detect pairwise significant differences with Holms method (28) to adjust for multiple testing.
One-way ANOVA was used to test for the overall difference of the biomarkers between gestational age. A pairwise t-test with un-pooled variance, adjusted for multiple testing using Holms method, was used to test for differences between the weeks.
Maternal age, BMI, and neonatal birth weight and age at sampling were initially included in the models, but did not contribute to the explanation of the variation, and these parameters were therefore excluded from the final models (data not shown). The birth weight and GA was lower in the pre-labour CS group. Birth weight was included in the first calculations, but did not make any differences as long as GA was included, and thus were excluded in the final calculation.
No difference was found in the use of anaesthetics between pre-labour and in-labour CS (data not shown), thus we did not correct for this in the analysis. The analysis was re-run excluding the cases with pre-labour rupture of the membranes (PROM). No difference in the result was found (data not shown). Only 0.8% of the infants were registered with an infection the first 4 days after birth, thus this was not adjusted for in the statistics.
All statistical analyses and figures were performed using the dplyr (29) and ggplot2 (30) packages in R software version 3.5.2.