Analyzing Consumer Purchase and Consumption Behavior in High Risk Foods

According to the Centers for Disease Control and Prevention, one in six American become ill or die from foodborne contamination. Flaws in security, quality control, or transportation are some examples of how food may be accidentally or intentionally contaminated. In order to build a secure and resilient food supply chain network, food producers and manufacturers need to have the ability to assess contamination risk as a function of consumer behavior. Specifically, we explore the likelihood of being exposed to contaminated food product as a function of food choice, shopping frequency, and consumption patterns. Using the data from an IRB-approved survey, characterizing consumer risk by demographic information, food choice, shopping frequency, and consumption patterns. A logistic regression model is developed to determine the likelihood of purchasing certain foods that are more susceptible to contamination. The results of this research identify which factors are significant in predicting the likelihood an individual will experience foodborne illness.