Trends in School Coverage, Enrolment, and Child Nutrition under the Mid-Day Meal Scheme in Assam: A Secondary-Data Analysis, 2004–05 to 2021–22

Abstract

This study examines the long-term institutional development, administrative coverage, and public health context of the Mid-Day Meal (MDM) Scheme, formally renamed Pradhan Mantri Poshan Shakti Nirman (PM POSHAN), in Assam, India—a state characterized by substantial structural and geographic diversity. Using a retrospective secondary-data trend analysis, the study evaluates the program’s progress over 18 academic years, from 2004–05 to 2021–22. The analysis integrates administrative education indicators from Annual Work Plan and Budget (AWP&B) reports with school enrollment data from the District Information System for Education (DISE), Unified DISE (UDISE), and UDISE+ databases. To assess broader child health outcomes, these data are examined alongside anthropometric indicators of nutritional status—stunting, wasting, and underweight—derived from successive rounds of the National Family Health Survey (NFHS-3, NFHS-4, and NFHS-5). From 2004 to the early 2010s, confirmed trend data indicate a substantial expansion in the number of eligible institutions and beneficiaries. Thereafter, administrative coverage plateaued, entering a period of systemic stabilization. At the same time, primary and upper-primary enrollment in state-run schools declined over multiple years, reflecting changes in fertility patterns, demographic shifts, and migration to private-sector education. Public health data indicate uneven reductions in nutritional deficiencies; stunting and underweight remain prevalent, suggesting that structural improvements in educational safety nets have not translated fully into better nutritional outcomes. The study concludes that, although the scheme’s administrative mechanisms have established a universal social-protection floor, household poverty, longstanding infrastructure deficits, and dietary vulnerabilities constrain its capacity to produce immediate population-level health improvements. It recommends decentralized district-level data integration and strengthened local monitoring. The study also acknowledges limitations in causal inference arising from the integration of administrative systems and population-based surveys, particularly because anthropometric indicators for children under five do not directly correspond to school-age cohorts.