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<p>Childhood undernutrition is the major public health concern in India, leading to anthropometric growth failures among children. The prevalence of childhood undernutrition varies significantly between demographic groups and geographies. The study looks at the relationship between the socioeconomic determinants and the geographical analysis of childhood undernutrition in India. Using NFHS-5 (2019–21) data of 152,244 children aged 6–59&#xa0;months, the study employed multilevel binary logistic regression to analyse individual, household, and community-level factors. Advanced geospatial techniques, including Global Moran’s I, Anselin Local Moran’s I, and Bivariate Local Indicators of Spatial Association (BiLISA), were used to identify undernutrition hotspots and socioeconomic correlations. The findings of the study revealed that selected individual, household, and community-level factors were significantly associated with undernutrition. Moreover, spatial analyses showed the significant clustering of childhood undernutrition, with high prevalence in Bihar, Jharkhand, and Uttar Pradesh. Further, Global Moran’s I (0.41, <i>p</i> &lt; 0.001) indicated non-random spatial patterns, while hotspot analyses highlighted concentrated undernutrition in socioeconomically marginalized districts. Bivariate LISA maps demonstrated spatial correlations between undernutrition and socio-economic factors. The study underscores the importance of integrating geospatial techniques and multilevel analyses to understand the regional disparities in childhood undernutrition. It emphasizes the need to strengthen ICDS, food fortification, sanitation, maternal health, and education initiatives in high-prevalence areas. These efforts are crucial to meet the SDG goal 2 for reducing inequalities and ensuring equitable child nutrition and health.</p>

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Regional Heterogeneities and Socio-economic Determinants of Childhood Undernutrition in India: A Geospatial Analysis

  • 期刊论文

  • 发表日期：

    2025年6月11日

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  • Manabindra Barman,
  • Jalandhar Pradhan

摘要

Childhood undernutrition is the major public health concern in India, leading to anthropometric growth failures among children. The prevalence of childhood undernutrition varies significantly between demographic groups and geographies. The study looks at the relationship between the socioeconomic determinants and the geographical analysis of childhood undernutrition in India. Using NFHS-5 (2019–21) data of 152,244 children aged 6–59 months, the study employed multilevel binary logistic regression to analyse individual, household, and community-level factors. Advanced geospatial techniques, including Global Moran’s I, Anselin Local Moran’s I, and Bivariate Local Indicators of Spatial Association (BiLISA), were used to identify undernutrition hotspots and socioeconomic correlations. The findings of the study revealed that selected individual, household, and community-level factors were significantly associated with undernutrition. Moreover, spatial analyses showed the significant clustering of childhood undernutrition, with high prevalence in Bihar, Jharkhand, and Uttar Pradesh. Further, Global Moran’s I (0.41, p < 0.001) indicated non-random spatial patterns, while hotspot analyses highlighted concentrated undernutrition in socioeconomically marginalized districts. Bivariate LISA maps demonstrated spatial correlations between undernutrition and socio-economic factors. The study underscores the importance of integrating geospatial techniques and multilevel analyses to understand the regional disparities in childhood undernutrition. It emphasizes the need to strengthen ICDS, food fortification, sanitation, maternal health, and education initiatives in high-prevalence areas. These efforts are crucial to meet the SDG goal 2 for reducing inequalities and ensuring equitable child nutrition and health.