Caesarean section delivery & determining factors in northeastern State, India: A Bayesian spatio-temporal analysis of areal data

Background & objectives Caesarean Section (CS) is a crucial life-saving surgical procedure for maternal delivery when normal delivery is ruled out for the safety of mother and infant. This study investigated the spatio-temporal pattern of CS rates to assess the significant factors boosting this delivery in the northeastern States of India. Methods We analysed cross-sectional data from three rounds of the National Family Health Survey (NFHS 3, NFHS 4, and NFHS 5). We estimated the relative risk (RR) of CS delivery and assessed the global and local spatial autocorrelation for each year from 2011 to 2019. Furthermore, the posterior median RR with credible interval was estimated using Bayesian Spatio-temporal modelling with Markov Chain Monte Carlo simulation. Results The CS rates in the northeastern States have escalated by nearly 15 per cent over the last two decades, from 5.4 per cent in 2001 to 19.9 per cent in 2019. Furthermore, we observed a substantial increase in the high-high Local Indicator of Spatial Analysis clusters from 2011 to 2019. The estimated posterior median RR exceeded one for four significant predictors: maternal age, maternal education, obesity, and household wealth status. This analysis also revealed that the estimated spatio-temporal trend displayed a clear upward trend in CS risk during the nine-year study period. Interpretation & conclusions This study found a substantial increase in CS delivery rate over the nine-year period (2011 to 2019) in the northeastern States of India. The findings of the study provide important policy input for strengthening healthcare intervention and regulations by initiating targeted programmes to monitor and avert excessive use of CS facilities in districts with high CS delivery.