Obstetric, sociodemographic, and clinical factors influencing C-section trends in Australia, from 2007 to 2017: An analysis of population-based perinatal data in Queensland using the Robson classification

BACKGROUND: More than one-third of births in Australia are by caesarean section (C-section), projected to reach 45% by 2030. Understanding sociodemographic, clinical, and obstetric practice factors shaping C-section trends is critical for informing policy and maternity care. METHODS: We conducted a population-based study of 642,857 pregnancies in Queensland (July 2007-December 2017) using the Perinatal Data Collection. Births were classified with the Robson Classification System. Trends in group size, C-section rates, and indications were described. Modified Poisson regression with generalised estimating equations estimated crude and adjusted incidence rate ratios (IRRs) for major Robson groups (RGs). FINDINGS: Of 214,569C-sections, key contributors were repeat C-sections (RG5, 38.2%), nulliparous elective (RG2, 20.9%), nulliparous spontaneous labour (RG1, 10.7%), and preterm (RG10, 7.0%) births. Although overall C-section rates remained relatively stable (33.3% in 2007 vs 34.4% in 2017), increasing clinical, demographic, and service-related risk profiles and substantial within-group variation were observed. Between 2007 and 2010 and 2015-2017, C-section declined in RG1 (IRR 0.84) but increased with maternal age ≥ 40 years (IRR 2.27) and pharmacological induction (IRR 1.93). Smaller reductions occurred in RG2 (IRR 0.93), with higher risk for BMI ≥ 30 (IRR 1.24) and private care (IRR 1.18). Minimal change was seen in RG5 and RG10 (IRR 1.00), though hypertension (IRR 1.54) and fetal risk (IRR 1.44) strongly influenced RG10. Midwifery-led care consistently reduced C-section across RGs (IRR 0.83-0.95). Elective C-sections were largely due to non-absolute indications and maternal preference. CONCLUSION: Stable overall C-section rates mask clinically important heterogeneity driven by maternal and fetal risk profiles and obstetric practices. Expanded analytic use of Robson classification can support group-specific benchmarking, identify modifiable drivers, and inform targeted strategies to optimise C-section use nationally.