Understanding Sociodemographic Determinants of Voluntary Cesarean Section Deliveries in India through Geospatial Modeling using Multiscale Geographically Weighted Regression (MGWR)

Over the period of time, the increasing trend of voluntary cesarean section (CS) delivery has become a serious maternal health concern. Previous studies have shown wide geographic variations in the prevalence of voluntary CS delivery constraints by several sociodemographic determinants. However, none of them have attempted to disentangle this phenomenon by using spatially varying coefficient models to consider local factors. This study aims to identify the spatially heterogeneous relationships among voluntary CS deliveries against the backdrop of sociodemographic determinants in India. This study utilized data from the National Family Health Survey (NFHS-5), 2019-21. The ordinary least square (OLS) model was used as a base model, and multiscale geographically weighted regression (MGWR) was employed at the district level to consider the local factors associated with voluntary CS delivery. An appropriate model diagnostic check was also performed to make our model robust and reliable. Several maps were produced using ArcGIS Pro to visualize the distribution of coefficients of several factors. More than half (58%) of the total CS deliveries were voluntary; however, choropleth maps have shown that southern peninsular and northeastern districts have a higher prevalence than the rest. The distribution of voluntary CS deliveries with a Moran’s Index of 0.22 was also spatially autocorrelated. Moreover, the values of Jarque–Bera statistics and Koenker (BP) Statistics show that the OLS model residuals were not normally distributed and reflected heteroskedasticity. The estimates from the MGWR show that four and above ANC visits and mass media exposure show a positive relationship with voluntary CS deliveries. The local R-squared map explains nearly half of the variation for voluntary CS deliveries for all northeastern districts. The model fit metric shows higher R square and lower corrected Akaike’s Information Criterion (AICc) values for the MGWR model, which validates that the MGWR model is more robust and parsimonious. The present study revealed that although voluntary CS deliveries are at an increasingly alarming pace, the geographic distribution of voluntary CS deliveries is, albeit unequally. Therefore, this investigation has made an effort to examine how spatial analysis can help identify the geographic patterns and factors that explain this variation in voluntary CS deliveries across space. These findings add value to our understanding of how geographic space and scale matter when health is examined. Public health practitioners can recognize such variations when devising targeted interventions for CS deliveries in India and other developing nations.