Exploratory research on estimation of consumer-level food loss conversion factors, Agreement No. 58-4000-6-0121, Final Report
The Economic Research Service’s (ERS’s) Loss Adjusted Food Availability Data System provides per capita annual estimates of food consumption calories and weights for over 200 food categories. These data are an often used proxy for actual consumption in studies related to measuring and analyzing changes in food consumption behavior over time. In addition, they are useful for analyzing changes due to major nutrition education and policy initiatives. ERS derives food consumption estimates from per capita food availability data for 217 food categories broadly classified as ?? meat, fish, and poultry (including nuts); ?? dairy products; ?? fruits and vegetables; ?? grain products; ?? added fats; and ?? added sugars. When deriving food consumption estimates, ERS adjusts food availability data by the following four sets of food loss factors: ?? primary to retail weight loss ?? retail/institutional to consumer-level loss ?? consumer-level inedible share ?? other consumer-level loss (cooking loss and uneaten food) The other consumer-level loss category occurs because of cooking losses, plate loss (also referred to as plate waste), spoilage, and other types of losses other than the inedible portion of the food. The degree of these losses might depend on whether the food is perishable; the typical shelf-life of perishable foods; whether the food is usually an ingredient in cooking or eaten without further preparation; and whether the food is typically consumed by children, adults, or seniors. Consumer-level losses also differ depending on whether the food is prepared at home or away from home. Because food consumed away from home accounts for nearly half of total food purchase dollars, it is important to understand how food loss for food consumed away from home differs from food loss at home. In particular, types of food, cooking methods, and spoilage or discarding of unused food likely differ substantially.