ABSTRACT
India bears 14% of the world's burden of malnutrition, with approximately 32% of the population in the country being undernourished/malnourished, as per NFHS 2019–21. While the Government of India (GoI) has been implementing several schemes, the problem of malnutrition needs to be addressed holistically through a multi-pronged strategy. This would have to include improving income levels of households and generating awareness around factors that cause malnutrition. This chapter makes a case for engaging with the community-based institutions of rural poor women promoted under the Deendayal Antyodaya Yojana—National Rural Livelihoods Mission (DAY-NRLM) across the country to address the issue of malnutrition holistically. It makes a case that the large outreach under NRLM, the network of women's institutions promoted, the social capital created and the different models already developed under the Mission make this programme or similar efforts very suitable for effectively dealing with the problem of malnutrition. The community institutions provide a ready-made network for knowledge dissemination with multiple touchpoints for repeated messaging to promote behaviour change. The livelihoods promotion under the farm and non-farm sectors not only generates income for the households of SHG members but also increases the availability of nutritious produce for consumption. Additionally, aspects like addressing gender-based issues, convergence with the line departments and integration of community demands in Gram Panchayat Development Plans (GPDPs) are being stressed. The chapter also analyses the performance of State Rural Livelihoods Missions (SLRMs) of a few states and highlights state-specific interventions, which have shown positive outcomes.
As of June 2024, Food, Nutrition, Health and Water and Sanitation (FNHW) activities have been initiated in 678 districts and 5049 blocks across the 34 States/Union Territories through the SRLMs. Enough evidence is now available to prove the efficacy of these community-driven models.
