Does club convergence matter in health outcomes? Evidence from Indian states

Abstract

Background: Population health is vital to a nation’s overall well-being and development. To achieve sustainable human development, a reduction in health inequalities and an increase in interstate convergence in health indicators is necessary. Evaluation of the convergence patterns can aid the government in monitoring the health progress across the Indian states. This study investigates the progressive changes in the convergence and divergence patterns in health status across major states of India from 1990 to 2018. Methods: Sigma plots (σ), kernel density plots, and log t-test methods are used to test the convergence, divergence, and club convergence patterns in the health indicators at the state level. Results: The result of the sigma convergence suggests that life expectancy at birth has converged across all states. After 2006, however, the infant mortality rate, neonatal mortality rate, and total fertility rate experienced a divergence pattern. The study’s findings indicate that life expectancy at birth converges in the same direction across all states, falling into the same club (Club One). However, considerable cross-state variations and evidence of clubs’ convergence and divergence are observed in the domains of infant mortality rate, neonatal death rate, and total fertility rate. As suggested by the kernel density estimates, life expectancy at birth stratifies, polarizes, and becomes unimodal over time, although with a single stable state. A bimodal distribution was found for infant, neonatal, and total fertility rates. Conclusions: Therefore, healthcare strategies must consider each club’s transition path while focusing on divergence states to reduce health variations and improve health outcomes for each group of individuals.