# Exploring spatial clusters of caesarean sections across India - Insights from National Family Health Survey data

## TL;DR

This study uses Indian health survey data to show that C-section rates are rising, especially in rural areas and private hospitals, with notable geographic clustering.

## Contribution

The study identifies spatial clusters of C-sections in India and reveals rising rates in rural and private healthcare settings.

## Key findings

- C-section rates increased from 17.2% in 2015–16 to 21.5% in 2019–21.
- Private hospitals showed significantly higher C-section rates compared to public facilities.
- Spatial clustering was confirmed in both public and private healthcare settings (p < 0.01).

## Abstract

The rising prevalence of caesarean sections (C-sections) in India, surpassing the World Health Organization’s recommended rate of 10–15%, has become a significant public health concern. This study aims to analyze the patterns and spatial clustering of C-sections across India’s states and districts, utilizing data from the National Family Health Survey (NFHS-4 and NFHS-5). Spatial autocorrelation analysis was applied to summarize the extent to which districts with similar proportions of C-sections tend to occur next to each other, forming spatial clusters. This was done using Global Moran’s I index for the fourth and fifth rounds of the National Family Health Survey (NFHS) data conducted in 2015–16 and 2019–21, respectively. LISA cluster maps were produced to test for global spatial autocorrelation, and the Getis-Ord General G statistic was used to test for local clustering. Our research reveals a substantial increase in caesarean deliveries, from 17.2% in NFHS-4 (2015–16) to 21.5% in NFHS-5 (2019–21). This trend is more pronounced in rural areas, challenging previous assumptions about urbanization as a primary driver. We observed marked disparities between public and private healthcare facilities, with private hospitals showing significantly higher rates of caesarean births. Public hospitals exhibited clustering in southern India and parts of northern India, while private facilities showed clustering along the eastern coast and in northeastern regions. Global Moran’s I and Getis-Ord General G statistics confirmed significant spatial autocorrelation and clustering (p < 0.01) for both public and private facilities. This study highlights the complex interplay of factors influencing caesarean section rates, including healthcare access, institutional policies, and the urban-rural differential. It underscores the need for targeted interventions and policy adjustments to address the disproportionate increase in caesarean deliveries.