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Social Network Model Reveals Global Food Trade Patterns Tied to Food Safety Standards

Food safety regulations can determine which countries trade corn with one another. That’s according to a new study by the University of Pittsburgh that used social network modeling to determine global trade patterns. Lead Author and Pitt Associate Professor Felicia Wu said it began with looking at the way countries regulate the contaminate aflatoxin, which grows on corn.

“What we were interested in examining is whether the nations that have similar food safety standards, that is they’re more relaxed in their food safety standards, or they’re more strict in their food safety standards, do they tend to trade more with each other, or is there no pattern whatsoever?” said Wu.

The study found there is a clear link between countries with similar regulations. Nations tend to cluster into trading patterns, with nations with similar standards trading with each other, and there’s very little trade with nations with vastly different standards. Researchers identified three “trade clusters” with the United States at the center of one of them.

“The U.S. is by far the largest producer of corn around the world and it’s exporting a lot of corn to a variety of different nations that either have very similar food safety standards to the United States, or they don’t have aflatoxin standards at all, that’s one part of the global trading network,” said Wu.

The United States allows five times as much of the fungus aflatoxin in food products as is allowed by the European Union.  Aflatoxin consumption in large amounts and in small amounts has been linked to liver cancer.

Another network is the European countries, which make up a separate corn trading network. They tend to trade a lot with one another and with other countries that have extremely strict standards for aflotoxin. They do hardly any corn trade with the U.S, which Wu said is odd considering how much corn the U.S. produces. The third cluster includes Argentina, China, and Brazil, which trade with both of two main clusters.

The linkages were made using social network modeling, a method that has a basis in graph theory.

“Social network modeling enables you to determine patterns as far as ‘how are people interconnected within a particular social network? Or how are nations connected to each other in a network as far as trade?’ There can be many different applications because there can be all kinds of relationship,” said Wu.

Researchers will take information from this study to determine the “why” – Wu said it’s sort of a “chicken or the egg” type question.

“Is it in fact the case that nations have already set their food trading patterns and then they apply their food safety standard accordingly so they can all, in a sense, match with each other? Or is it that the nations have set particular food safety standards and then over time the trading patterns shift such that they tend to be trading more with each other, the nations that have similar food safety regulations,” asked Wu.

The study appears in “PLOS One” The journal of the Public Library of Science, and was funded by the National Cancer Institute of the National Institutes of Health grant.