The Sow and Grow Study: Linking Nutrition and Agriculture for Healthy Infant Growth (Part II)
Emily Bielecki, a Ph.D. Candidate in International Nutrition at Cornell University with Dr.Shambhavi Singh, Community Empowerment Lab (CEL) Project Director, and Dr.Swati Dixit, Post Doctoral Fellow at CEL share their experiences with the insertion of an agriculture module into a multi-component nutrition and child growth survey in Shivgarh, Uttar Pradesh, where they are studying how agricultural seasonality and the various factors that are affected by seasonality (i.e. maternal work patterns, infant feeding, food security etc.) affect infant growth outcomes.
Nutrition into Agriculture or Agriculture into Nutrition?
Interest in understanding the linkages between Nutrition and Agriculture has increased in recent years. Hand in hand with this increased interest has come a great deal of discussion about how to insert nutrition goals and outcomes into agricultural programs and interventions. Our experiences with the somewhat reverse scenario of inserting agricultural goals and outcomes into a nutrition survey revealed some important insights relevant for future consideration and research.
1. Agriculture modules are long!
Respondent burden is always a concern in the administration of household surveys. However, keeping the number of questions to a minimum is an extraordinary task, especially when dealing with a subject, such as nutrition, which has complex and interacting determinants. In our particular case, the goal was to restrict our interaction with the participants to a one-hour visit at each of 10 planned monthly visitations. However, a review of available agriculture modules revealed that collecting this information alone could easily consume an hour of time! This meant it was clearly time to return to the drawing board!
2. If we can’t ask it all, how do we streamline it?
Sitting with sample agriculture modules strewn across my desk, I found myself overwhelmed with questions about land size and plot number and endless listings of crops! I realized that I had a lot of uncertainty about which agriculture variables were the critical variables and if/which variables represented a bare minimum set of agriculture variables that would be defensible to not only a nutrition community, but also to an agriculture community. I also found myself struggling with how to translate agricultural survey questions designed for a cross-sectional survey in a way that enabled us to take full advantage of our longitudinal design (i.e. understanding the static/dynamic nature of the variables to determine the frequency with which to ask different agricultural questions). In this process I consulted with several agriculture experts and other colleagues with experience working on nutrition-agriculture linkages. These thought provoking discussions solidified my suspicions that many of the complexities in the design of agriculture modules for use in multi-dimension nutrition surveys remains to be adequately addressed.
3. It is not easy to collect agricultural data!
As part of the process to inform our agriculture module, we spent a substantial amount of time conducting formative research and then pilot testing various drafts of our module. From this experience, I can confidently confirm that collecting agricultural data is not an easy task! Especially for those of us who are not specifically trained in agriculture, the complexity of the subject is fascinating, and also likely to be underestimated. A seemingly simple question such as “how much land do you own” must be investigated to understand local concepts of land ownership, and carefully constructed so as to imply actual deed ownership of land (as opposed to other forms of land usage that might be considered as a form of ownership). It was also worthwhile to become aware of the fact that asking for agriculture information can be a surprisingly sensitive topic. For example, we found that certain types of land usage were stigmatized in our study area and that at times our questions were treated with suspicion, likely due to the existence of government assistance programs linked to agriculture. It was critical for us to consider these factors and also to make sure that they were adequately communicated to our survey enumerators.
An important body of literature is developing to describe the methods and evaluation for inserting nutrition goals and outcomes into agricultural programs and interventions. However documentation of the reverse scenario is substantially less. Further discussions about the design and evaluation of agriculture modules, as well as increased documentation of field considerations would be of great value to researchers interested in better understanding nutrition and agriculture linkages.
*If you are interested in the agriculture module we used, please contact Emily at firstname.lastname@example.org.