Tufts University (IANDA)

Friedman School of Nutrition Science and Policy, Tufts University

Indicators of Affordability of Nutritious Diets in Africa (IANDA)


Summary of the project:

Food security rests on consistent access to sufficient, safe, nutritious foods to meet dietary needs. In recognition of its importance to nutrition, more funds have been committed to nutrition-sensitive agriculture than any other single area of nutrition (e.g. at the 2013 Nutrition for Growth Summit). A primary way that agriculture can influence food security and nutrition is through improving the food environment: including increasing year-round availability and affordability of diverse, nutritious foods and diets. However, valid, low-cost indicators of that level have not been developed. Thus, meaningful information on food availability and affordability has not been tracked, either through national/ global monitoring systems or as indicators of desired impacts from nutrition-sensitive agricultural interventions and investments. 

The “Indicators of Affordability of Nutritious Diets in Africa” (IANDA) Project is comprised of a team of researchers from the Tufts Friedman School or Nutrition Science and Policy, University of Ghana, Sokoine University in Tanzania, and the Johns Hopkins Bloomberg School of Public Health.

It will aim to achieve the following objectives:

  1. to use currently available price and market data to develop valid, feasible metrics of the availability and affordability of nutritious, diverse foods and diets in markets throughout the year;
  2. to ensure that these indicators serve the needs of national policy makers and program planners across agriculture and health & nutrition sectors, through a participatory process of data identification and user consultation in two countries;
  3. to recommend methods for indicator construction and suggestions for modifying food price monitoring and other data collection systems that will encourage the widespread adoption of these indicators at national and global levels. 

To this end, linear programming and other statistical methods will be applied to secondary data derived from existing food price monitoring systems and other information sources identified through participatory data mapping process in two countries (Tanzania, Ghana) to test and validate a dashboard of key indicators.

These indicators include:

  • availability of foods in each food group;
  • costs of diverse food groups;
  • cost of a minimally diverse diet;
  • cost of nutrient adequacy; 
  • cost of a recommended diet.

In Tanzania, our project offers a unique opportunity for adoption: the indicators will be developed in the context of the National Evaluation Platform (NEP), as a proof of concept for mainstreaming nutrition-sensitive agriculture indicators into a national information platform. The Canada and JHU-supported NEP serves as a model to be scaled up through the incipient EC and DfID-supported National Information Platform for Nutrition (NIPN) in other Scaling Up Nutrition (SUN) countries.