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Reflecting on this summer’s MNDA data collection: Our indispensable enumerators


TCi intern Andrew Pike (pictured in white hat), a student of applied economics and management at Cornell, reflects on his participation during the final phase of this summer’s Minimum Nutrition Dataset for Agriculture (MNDA), dietary diversity module pilot test. He shares what it was like to return from the field, start the analysis phase and begin to digest what the challenges are for operationalizing its dietary diversity module. Read additional posts about TCi’s work in creating a minimum set of nutrition metrics for use in agriculture surveys here.

It’s an exciting time for the TCI intern team – we’ve just completed data collection and are now analyzing the results to see how the MNDA household dietary diversity scores compare with ICRISAT’s extensive nutrition survey. TCi director Prabhu Pingali arrives on Sunday and we present our findings to him and the whole of ICRISAT on Monday. It’s go time, my sweet mango lassis!

Now, while writing our final report, I’ve been reflecting on how the data collection process can be generalized across different countries and cultures. What strikes me most, is that the field investigators (enumerators) are indispensable. We relied on them to accurately and impartially relay questions and responses, but also to provide context and facilitate relationships with respondents. The importance of this role means that investigators with certain skills and qualities are needed.

The interviewer and investigators must be able to communicate and so it is crucial that the investigator can read and speak English well (or another common language). The onus is on the interviewer to develop a rapport to improve communication. We found that role-playing in training was very helpful in this.

Investigators must also understand the survey methodology, specifically how and when to probe for foods. Again, role playing in training helped because it highlighted potential miscommunications and mistakes that might occur, such as other household members trying to answer questions.

We were fortunate to work with the experienced field investigators for the ICRISAT Village Level Surveys (VLS), an intensive nutritional survey that captures all ingredients, no matter how small the quantity (as opposed to just major food groups with the MNDA). However, we still needed to explain our instrument’s purpose and what information we were looking for due to confusion with the purpose of the ICRISAT instrument. It was also necessary to ask investigators to relay all information that might help contextualize dietary diversity, and not just the meal ingredients and their sources. For example, one respondent bought pigeon pea from the market, but this was unusual and only because the public distribution system (PDS) was out of stock.

The enumerators also had advanced education – most had or were pursuing masters in agricultural economics or nutrition – which was useful but not necessary, because the MNDA is designed so that it can be administered without a background in nutrition.

It is critical that investigators understand local customs and cultures and can brief the interviewer on how to act appropriately. It was useful that our investigators lived in the village because they had relationships with the households, who were therefore comfortable with the interview. This could be seen in the way they laughed and willingly answering questions. Also, through living in the village, investigators knew about household occupations, government welfare programs, and the ingredients in local dishes.

Researchers have a strong role to play in enabling enumerators to do this kind of quality work. Productive communication between the interviewer and the researcher is essential. Before this experience, I did not realize how important my relationship, including my communication style and training, would affect the data collection process. As a result, I realize now that for the MNDA to succeed, we are going to need to ensure that rigorous trainings are held prior to and during any data collection effort. Those in charge of implementation should select critically and train comprehensively, with emphasis on productive communication. The interviewer should also take the time to talk to question the investigator so that asking questions in the interview becomes habitual, and also so that investigators feel confident clarifying concepts.