Geographic variation in caesarean delivery in India

Background The rate of caesarean delivery has increased markedly both globally and within India. However, there is considerable variation within countries. No previous studies have examined the relative importance of multiple geographic levels in shaping the distribution of caesarean delivery and to what extent they can be explained by individual-level risk factors. Objectives To describe geographic variation in caesarean delivery and quantify the contribution of individual-level risk factors to the variation in India. Methods We conducted four-level logistic regression analysis to partition total variation in caesarean delivery to three geographic levels (states, districts and communities) and quantify the extent to which variance at each level was explained by a set of 20 sociodemographic, medical and institutional risk factors. Stratified analyses were conducted by the type of delivery facility (public/private). Results Overall prevalence of caesarean delivery was 19.3% in India in 2016. Most geographic variation was attributable to states (44%), followed by communities (32%), and lastly districts (24%). Adjustment for all risk factors explained 44%, 52% and 46% of variance for states, districts and communities, respectively. The proportion explained by individual risk factors was larger in public facilities than in private facilities at all three levels. A substantial proportion of between-population variation still existed even after clustering of individual risk factors was comprehensively adjusted for. Conclusions Diverse contextual factors driving high or low rate of caesarean delivery at each geographic level should be explored in future studies so that tailored intervention can be implemented to reduce the overall variation in caesarean delivery.

Automated summary

The overall prevalence of caesarean delivery in India in 2016 was 19.3%, with most geographic variation attributable to states (44%), communities (32%), and districts (24%). After adjusting for all risk factors, the variance explained was 44%, 52% and 46% for states, districts, and communities, respectively. In public facilities, individual risk factors accounted for a larger proportion of variation compared to private facilities.