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<p>This study examines spatial heterogeneity in multidimensional poverty across selected districts in Uttar Pradesh, highlighting disparities in health, education, standard of living, energy, assets, and geographical accessibility. The study utilizes household survey data collected from 800 households across selected districts in Uttar Pradesh, employing a multi-stage sampling technique to ensure a representative sample. A Multidimensional Poverty Index (MPI) is constructed by incorporating six dimensions using equal weighting for each dimension and GIS tools to analyze the spatial distribution of poverty. The research reveals stark contrasts between the selected districts of Uttar Pradesh in terms of MPI. Banda and Badaun emerge as the most deprived, with acute challenges in health access, educational opportunities, sanitation, and energy use. While districts like Lucknow and Ghaziabad show better outcomes but face peri-urban inequities, particularly in housing quality and environmental conditions. The spatial analysis uncovers systemic infrastructural deficits, financial vulnerabilities, and limited access to essential services, exacerbated by geographical isolation in rural areas. By integrating spatial analysis and regional poverty dimensions, the study provides actionable insights for sustainable and equitable development strategies in Uttar Pradesh.</p>

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Examining Poverty Through Multiple Lenses: A Study of Selected Districts in Uttar Pradesh, India

  • 期刊论文

  • 发表日期：

    2026年1月22日

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  • Priyabrata Sahoo,
  • Vikram Sharma,
  • Soumyabrata Mondal

摘要

This study examines spatial heterogeneity in multidimensional poverty across selected districts in Uttar Pradesh, highlighting disparities in health, education, standard of living, energy, assets, and geographical accessibility. The study utilizes household survey data collected from 800 households across selected districts in Uttar Pradesh, employing a multi-stage sampling technique to ensure a representative sample. A Multidimensional Poverty Index (MPI) is constructed by incorporating six dimensions using equal weighting for each dimension and GIS tools to analyze the spatial distribution of poverty. The research reveals stark contrasts between the selected districts of Uttar Pradesh in terms of MPI. Banda and Badaun emerge as the most deprived, with acute challenges in health access, educational opportunities, sanitation, and energy use. While districts like Lucknow and Ghaziabad show better outcomes but face peri-urban inequities, particularly in housing quality and environmental conditions. The spatial analysis uncovers systemic infrastructural deficits, financial vulnerabilities, and limited access to essential services, exacerbated by geographical isolation in rural areas. By integrating spatial analysis and regional poverty dimensions, the study provides actionable insights for sustainable and equitable development strategies in Uttar Pradesh.