Spatial Fertility Patterns in North-East India: A State-Level Clustering Analysis
Chayanika Baruah
Department of Statistics, Cotton University, Guwahati, Assam, India.
Ruma Talukdar
Department of Statistics, Cotton University, Guwahati, Assam, India.
Saurav Sarma *
Department of Statistics, Cotton University, Guwahati, Assam, India.
*Author to whom correspondence should be addressed.
Abstract
Background: Examining regional fertility trends is crucial for shaping informed demographic strategies and policy decisions. This research calculates the state-level Age-Specific Fertility Rate (ASFR) across India’s eight northeastern states and employs cluster analysis to group them by their fertility lines. The method reveals distinct clusters with comparable fertility behaviours, shedding light on both regional disparities and evolving demographic shifts. The results highlight marked differences in fertility rates across these states, underscoring the role of socio-economic and cultural factors in shaping these variations.
Methods: The eight northeastern states were divided into discrete clusters using the K-means clustering method.
Results: By examining the calculated single-year ASFRs, we grouped the eight north-eastern states into four distinct clusters. Cluster 1, predominantly tribal and Christian, shows relatively high education levels and moderate contraceptive use, while Cluster 2, primarily Hindu and rural, displays a higher proportion of anaemia and lower education levels, reflecting traditional fertility patterns. Cluster 3, with its high fertility rates, is marked by low contraceptive use and high parity, while on the other hand Cluster 4, with its Buddhist majority and high contraceptive adoption, demonstrates a strong preference for smaller family sizes. This distinction highlights the importance of socio-demographic factors in shaping these regional fertility trends.
Conclusion: The eight northeastern states can be categorized into four distinct clusters, each of which can be characterized by markedly divergent fertility trends and maternal demographic profiles. These insights offer a basis for developing focused reproductive health strategies in the region.
Keywords: Age-specific fertility rate, multivariate analysis, cluster analysis, demography