Agrobiodiversity Diet Diagnosis Interventions Toolkit (ADD-IT)

ADD-IT is especially useful in contexts where local health workers and community volunteers need structured, reliable information about local food systems to guide their work. This includes settings where understanding what foods are available in markets, which foods are in season, and the nutritional value of different food groups is essential for improving dietary guidance.

The tool is relevant when programs aim to connect individual dietary information with broader community monitoring. Data collected from individuals benefits them directly, while aggregated results can inform planning and decision-making at community, county, and national levels.

ADD-IT is also useful in initiatives focused on behavior change. Its structured process—data collection, analysis, feedback, and action planning—supports informed discussions and practical steps toward improved eating habits. By combining local food availability (wild, cultivated, and market-based options) with systematic feedback, it helps translate information into coordinated nutrition action across different levels.

In the first year, the project established strong partnerships with the National Museums of Kenya, JICAV, and Tokyo University of Agriculture.

• The National Museums of Kenya contributes scientific and genetic expertise on plant and animal species.

• Tokyo University of Agriculture provides technical support through the Hara initiative.

• Additional specialists in data collection and analysis were engaged to manage the database, along with a communications officer to document and share project progress.

In the second year, the focus shifts to nutritional analysis of selected foods. The team will collect food samples and work with laboratories to assess their nutrient content, strengthening the evidence base behind the tool.

Early contributions and impact

The tool is helping stimulate the use of local food resources, with potential benefits for local economies, food security, public health, poverty reduction, and biodiversity conservation. It is also strengthening institutional collaboration and capacity for nutrition research.

Research linked to the project has already generated peer-reviewed publications in journals (see below), covering topics such as dietary patterns in rural Kenya, validation of the app-based questionnaire, and the relationship between local food production and nutrient intake.

Looking ahead

The next phase aims to expand the network to additional countries to test and adapt ADD-IT in new contexts.

Flexible Design

ADD-IT is built to be adaptable. It can be customized to reflect the food culture, dietary habits, and available ingredients of different regions.

Adapting to Local Food Cultures

Food List Customization
The foods included in the questionnaire and recipe suggestions can be modified to match local diets. For example, a staple such as “ugali” in Kenya can be replaced with a staple food relevant to another region.

Culturally Relevant Education Materials
Nutrition education content can be adjusted to suit the cultural context and comprehension level of the target audience, ensuring that messages are clear and meaningful.

Future Development

ADD-IT continues to evolve, with several planned improvements:

Data Sharing
Currently, results are stored only on the researcher’s device. Future versions aim to allow secure sharing of results and feedback between researchers and participants.

Data Storage and Privacy
Expanding data-sharing features will require clear data storage systems and strengthened consent procedures to ensure privacy and responsible data use.

How Researchers Can Adapt and Reuse ADD-IT

Researchers can apply the tool in new settings by:

1. Reflecting Local Diets
Adapting food lists, portion-size images, recipes, and educational materials to align with local dietary practices.

2. Measuring Intervention Impact
Using the app for baseline and endline assessments to evaluate nutrition interventions. A consent form is already integrated into the system.

3. Monitoring Over Time
Applying the tool regularly during programs to track changes in dietary habits. Previous survey results remain accessible within the app.

4. Managing Data Collaboratively
Storing collected data in the cloud to support team-based analysis and coordination. Further development of data-sharing features is ongoing.