Abstract Background: India has witnessed a fall in fertility rates, but there are regional variations. Spatial planning requires an understanding of the spatial pattern of fertility rates and the factors affecting them. This research was undertaken with the objective of understanding the spatial pattern of total fertility rates and socioeconomic factors in India. Materials and Methods: This ecological study used state-level data from the National Family Health Survey-5 (2019–2021). TFR was the outcome variable. Explanatory variables included early marriage, female literacy, women’s workforce participation, urbanization, poverty, and the multidimensional poverty index (MPI). Exploratory spatial data analysis assessed global spatial autocorrelation using Moran’s I and identified clusters using Local Indicators of Spatial Association (LISA). Spatial regression models—ordinary least squares (OLS), spatial lag (SLM), and spatial error (SEM)—examined associations while accounting for spatial dependence. Results: TFR ranged from 1.1 to 3.0 across states (mean 1.81). Global spatial autocorrelation was weak (Moran’s I = 0.020). LISA analysis identified high-fertility clusters in Bihar, Jharkhand, and Assam and low-fertility clusters in Tamil Nadu and Kerala. MPI was the only significant predictor of TFR. In OLS, a one-unit increase in MPI was associated with a 9.443 increase in TFR ( P < 0.001); similar associations were observed in SLM (β = 9.309, P < 0.001) and SEM (β = 9.174, P < 0.001). Conclusion: India has shown declining fertility rates with localized and regional variations. The need for addressing poverty reduction and reproductive health together has been emphasized by the fact that multidimensional poverty still remains the largest predictor of increasing fertility.
Deshmukh et al. (Fri,) studied this question.