Evaluation of the Background Causes, Associated Factors, and Trends in the Increasing Caesarean Section Rates Observed in Primigravid Women in an Irish Obstetric Population

There has been a major increase in caesarean section rates among first time mothers in Ireland in the last 10-15 years. Caesarean section rates among such mothers varied between 25-30% in Irish maternity hospitals in the years 2008-2010. The published rate of caesarean sections among primigravida nationally in Ireland for 2021 was 38.3%, with a significant proportion of hospitals reporting rates greater than 40%. There is a continuing upward trend in such rates. This increase in caesarean section rates is associated with significant morbidity for the mother, and has an adverse impact on management of subsequent pregnancies. There are also established risks of caesarean section for the infant in the neonatal period and during childhood.

It is recognised that the potential causes of such increased rates are likely to be multifactorial, but they are poorly defined. The hypothesis of this study is that the increasing use of caesarean section among this group of mothers may be linked to older age at childbirth, a higher prevalence of obesity or gestational diabetes mellitus (GDM), higher levels of medical intervention in pregnancy and labour, and maternal request. The relative contributions of each of these factors is unknown. The aims of this study are to examine these possible causes and their associated factors.

The data for this study will be obtained from an obstetric computerised database, the EuroKing system, which has been in operation at Galway University Hospital for many years. Data are entered prospectively at different stages during pregnancy, at the time of delivery, and postnatally. These include maternal age, parity, BMI, medical interventions in labour (induction, augmentation, use of epidural analgesia) duration of labour, and indication for caesarean section, including maternal request. Descriptive statistics and multinomial logistic regression analysis will be used to investigate causes and independent associated factors.