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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.

Moving forward

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 emb56@cornell.edu