Tracking India’s progress on addressing malnutrition and enhancing the use of data to improve programs

Menon, Purnima; Avula, Rasmi; Sarswat, Esha; Mani, Sneha; Jangid, Manita; et al. 2020. Tracking India’s progress on addressing malnutrition and enhancing the use of data to improve programs. POSHAN Report 12. New Delhi, India: International Food Policy Research Institute (IFPRI). https://doi.org/10.2499/p15738coll2.134227.

Data systems and their usage are of great significance in the process of tracking malnutrition and improving programs. The key elements of a data system for nutrition include (1) data sources such as survey and administrative data and implementation research, (2) systems and processes for data use, and (3) data stewardship across a data value chain. The nutrition data value chain includes the prioritization of indicators, data collection, curation, analysis, and translation to policy and program recommendations and evidence based decisions. Finding the right fit for nutrition information systems is important and must include neither too little nor too much data; finding the data system that is the right fit for multiple decision makers is a big challenge. Developed together with NITI Aayog, this document covers issues that need to be considered in the strengthening of efforts to improve the availability and use of data generated through the work of POSHAN Abhiyaan, India’s National Nutrition Mission. The paper provides guidance for national-, state-, and district-level government officials and stakeholders regarding the use of data to track progress on nutrition interventions, immediate and underlying determinants, and outcomes. It examines the availability of data across a range of interventions in the POSHAN Abhiyaan framework, including population-based surveys and administrative data systems; it then makes recommendations for the improvement of data availability and use. To improve monitoring and data use, this document focuses on three questions: what types of indicators should be used; what types of data sources can be used; and with what frequency should progress on different indicator domains be assessed.