Image: Vegetables stalls at Auki market, Malaita Province, Solomon Islands. Credit: Filip Milovac, WorldFish
The term “food systems” refers to the web of actions and interactions involving the production, processing, transport, trade, marketing and consumption of the food we eat, and surrounding biophysical and socioeconomic environments - and they are complex.
To untangle this web and reveal a picture of the current state of the food system, how it looked in the past, and how it is likely to be shaped in the future, data are vital.
Using data to describe food systems clearly allows us to develop better policies for sustainable and resilient food systems.
At a recent “Pacific Data Community of Practice” * Talanoa focused on food systems, Michael Sharp, Economic Statistics and Microdata Specialist working for the Statistics for Development Division of the Pacific Community (SPC) outlined why data is essential in this space.
“To measure and form a picture of food systems we can use agricultural data to view production over time, trade data helps us see trends in exports and imports, and consumption data reveals who is eating what. Without data we can do none of this. Without data we are blind,” said Michael.
Using consumption data as an example, Michael pointed out that working with this data enables us to better understand food consumption patterns of Pacific people. This includes factors such as how much dietary energy they are consuming and their access to various the macro and micronutrients that are essential for growth and good health.
“Monitoring health data is in one way for us to get an idea of consumption”, said Michael.
“Health is of course complex and multifaceted, but a large part of our health is the food we eat. In the Pacific with dietary related non-communicable diseases, understanding consumption patterns and drivers of consumption are important to developing policy to try to support alleviation of non-communicable diseases in the region”, he said.
Data is useful in that it reveals trends, patterns and stories. Using agricultural production data as an example, Michael pointed out, how, over time, it is possible to see a per capita decline in agricultural production in the region since the 1960’s.
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