Environmental Contaminant Concentrations in Canada Goose ( Branta canadensis ) Muscle: Probabilistic Risk Assessment for Human Consumers

• Main Authors: Horak, Katherine E., Chipman, Richard, Murphy, Lisa, Johnston, John
• Format: Text
• Language: unknown
• Published: DigitalCommons@University of Nebraska - Lincoln 2014
• Subjects: Life Sciences; Canada; Branta canadensis; Canada Goose
• Online Access: https://digitalcommons.unl.edu/icwdm_usdanwrc/1511; https://digitalcommons.unl.edu/context/icwdm_usdanwrc/article/2508/viewcontent/Horak_JFP_2014_Environmental_contaminant.pdf

The issue of food insecurity affects millions of people in the United States every year. Often these people rely on soup kitchens, food banks, and shelters for proper meals, and these organizations often depend on donations to meet needs. One of the most limited food resources is meat. To help alleviate this problem, the U.S. Department of Agriculture Wildlife Services donates more than 60 tons of wild game (deer, moose, feral hogs, goats, geese, and ducks) to a variety of charitable organizations each year. Although commercially produced meat routinely undergoes screening for contaminants, potential exposure to environmental contaminants from eating wild game is not well characterized. In this study, the concentration of 17 contaminants of concern in the breast meat of wild geese was examined. These concentrations were then used in a probabilistic model to estimate potential risk associated with consumption of this meat. Based on model predictions, more than 99% of all adults were below exposure limits for all of the compounds tested. For all consumer age classes modeled, consumption of wild goose meat may expose a small fraction of these populations to levels of lead higher than the recommended exposure limits. Similarly, mercury exposure was predicted to be higher than the recommended limits when the meat was served as steaks. This information about concentrations of contaminants of concern in goose meat and potential exposures associated with meat consumption based on probabilistic models will enable others to make informed decisions about the risks associated with the consumption of wild meat.