NIFAM

Nov 30, 2022

The understanding of food environments can give insights into the complex problem of malnutrition that affects all countries around the world. Cause-effect relationships in complex socioecological systems such as the food environment are unclear and data are often scarce or lacking. Development-oriented research struggles to offer timely and practical support for complex development conditions. The alternative approaches used in this project offer support by both forecasting and monitoring different interventions. We propose a transdisciplinary action research and development project to co-develop a scientific framework for decision support applicable to situations where resources are limited and costs, benefits and risks of different possible nutrition interventions are uncertain.
The NIFAM project aims to support policy makers in Vietnam (and Myanmar) by forecasting, implementing and monitoring effective nutrition interventions within a transdisciplinary research approach. The two countries have highly dynamic food environments, both struggle with food safety and food security issues. NIFAM’s objective is to identify and implement cost-effective interventions to sustainably improve the diets and reduce different forms of malnutrition (contributing to SDG 2). Various possible nutrition interventions will be collaboratively identified, modeled and monitored. These will be largely aimed at digital options for communication to influence better food choices e.g. provision of knowledge via short movies (TV, YouTube), nutrition labeling of produce, restrictions on marketing that targets children, an e-learning platform or mobile phone app on healthy diets.
The key result of the NIFAM project will be a set of recommendations to decision makers about which of a collection of possible nutrition interventions within these highly complex food environments will be best suited for the local situations of Vietnam. “Best” in this context means having the highest and most cost-effective impact on the nutrition of local consumers, considering all known uncertainties of the food environment.