CFSAN receives passive adverse event reports related to foods, dietary supplements and cosmetics from individuals, industry and other sources. These data are analyzed for suspicious or unexpected reporting patterns using a variety of techniques including several types of disproportionality analyses. The goal of the analysis is to detect higher-than-expected numbers of reports of product-symptom combinations. Due to the lack of information on product usage and reporting, signal detection techniques rely on deviations in the symptom profile of a specific product compared to that of the database as a whole. The choice of the comparison products for the analysis will have profound effects on the signal scores. Examples of disproportionality analyses of CFSAN-regulated products, such as the dietary supplement Hydroxycut, using several disproportionality techniques will be described.