Frontiers in Sustainable Food Systems (Jan 2025)
“We need workable micronutrient data!”: a qualitative study assessing the need for integrated micronutrient data to support evidence-based decisions by Indian food system stakeholders
Abstract
Stakeholders in decision-making roles require that data are available, accessible and useable to ensure evidence-informed design, implementation and evaluation of programs and policies to alleviate micronutrient deficiencies in India. This study determined the typical uses, data sources, priority and unmet needs, common challenges, and aspirations of key Indian food system stakeholders in relation to usage and interpretation of publicly available micronutrient data from health, nutrition, agriculture, and program domains. A qualitative, descriptive study was conducted, with purposive sampling of stakeholders from state and national-level government, development agencies, non-governmental organisations, research institutes, private organisations, and academia. Data were generated through focus group discussions and semi-structured key informant interviews. Themes and sub-themes were identified using framework analysis with a deductive approach. Stakeholders emphasized the pressing need for consolidated, harmonized district-level data from health, nutrition, and agriculture sources to better understand the causes and sources of variation in micronutrient deficiencies, and to inform decision-making on supplementation and fortification program planning, and policy evaluation. Biomarker data, nutrition dashboards and food consumption data were most used; data on food composition, program cost, and soil/crop micronutrient composition were not typically used, despite their relevance. A need for district-level data with further geographical and temporal (including seasonal) disaggregation, with improved accessibility was also identified. Current challenges include limited district-level data, outdated surveys, and data accessibility, while there is demand for customisable tools that integrate varied datasets, reflecting a shared vision for evidence-based decision-making and policy formulation.
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