<p>Hunger and undernutrition remain critical global challenges, disproportionately affecting developing nations. India, despite its economic growth, faces alarming disparities in hunger levels across its districts. This study investigates the Global Hunger Index (GHI) across 692 Indian districts, in an attempt to understand the spatial distribution of hunger within the country. The GHI which incorporates indicators such as child stunting, child wasting, undernourishment and child mortality, was computed using data from the National Family Health Survey (NFHS-5) and the National Sample Survey (NSS). Multidimensional Poverty Index (MPI) and additional socio-economic factors were examined to understand their association with hunger using spatial and linear regression models. Our spatial analysis revealed high spatial disparity, with 90 districts identified as hunger hotspots. Factors such as MPI, lack of education, and inadequate sanitation were significant contributors to higher hunger levels. These findings emphasize the multidimensional nature of hunger and highlight the need for district-specific interventions addressing socio-economic inequalities and improving nutrition to effectively combat hunger in India.</p>

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Understanding the global hunger index and its correlates across districts of india: a spatial analysis

  • Nehal Amin,
  • Vasudeva Guddattu

摘要

Hunger and undernutrition remain critical global challenges, disproportionately affecting developing nations. India, despite its economic growth, faces alarming disparities in hunger levels across its districts. This study investigates the Global Hunger Index (GHI) across 692 Indian districts, in an attempt to understand the spatial distribution of hunger within the country. The GHI which incorporates indicators such as child stunting, child wasting, undernourishment and child mortality, was computed using data from the National Family Health Survey (NFHS-5) and the National Sample Survey (NSS). Multidimensional Poverty Index (MPI) and additional socio-economic factors were examined to understand their association with hunger using spatial and linear regression models. Our spatial analysis revealed high spatial disparity, with 90 districts identified as hunger hotspots. Factors such as MPI, lack of education, and inadequate sanitation were significant contributors to higher hunger levels. These findings emphasize the multidimensional nature of hunger and highlight the need for district-specific interventions addressing socio-economic inequalities and improving nutrition to effectively combat hunger in India.