Loss-Adjusted Food Availability Documentation
The ERS Loss-Adjusted Food Availability (LAFA) Data Series is derived from ERS's food availability data by adjusting for food spoilage, plate waste, and other losses to more closely approximate actual intake. The LAFA data are recommended primarily for daily estimates of the per capita number of:
- Calories, and
- Food pattern equivalents of the five major food groups plus the amounts of added sugars & sweeteners and added fats & oils.
ERS also uses the loss assumptions embedded in the Loss-Adjusted Data Series to estimate the amount and value of food loss at the retail and consumer levels in the United States (see Usefulness of the loss-adjusted food availability data in estimating food loss). A report estimates the amount, value, and calories of the available U.S. food supply at retail and consumer levels in 2010 that went uneaten, as indicated in the link below:The Estimated Amount, Value, and Calories of Postharvest Food Losses at the Retail and Consumer Levels in the United States
This page provides the following information:
- Definitions and assumptions
- Coverage of the data
- Background and history of food loss estimates
- Initiatives to update ERS's food loss assumptions and data
- Initiatives to improve ERS's food loss assumptions underlying the LAFA per capita availability estimates
- Construction of the data
- Limitations of the data
- Food availability as a proxy for per capita consumption
- Usefulness of the loss-adjusted food availability data in estimating food loss
- Publications on food loss
Food loss represents the edible amount of food, postharvest, that is available for human consumption but is not consumed for any reason. It includes cooking loss and natural shrinkage (for example, moisture loss); loss from mold, pests, or inadequate climate control; and food waste.
The Loss-Adjusted Food Availability Data Series can be accessed through Excel spreadsheets which provide all of the current loss assumptions for the data series. ERS has completed a set of initiatives to update and document the underlying loss assumptions. ERS also has other initiatives underway to further refine the data series, and thus, this data series is considered to be preliminary.
Per capita calorie consumption and food pattern equivalents are estimated for over 200 agricultural commodities from 1970 to the most recent year of data available. Per capita data are reported for both individual commodities and aggregated food groups. The data for individual commodities are aggregated into food groups to facilitate comparison with recommendations for average daily intakes for the U.S. population.
In 2000, the number of firms reporting vegetable oil production to the U.S. Census Bureau increased noticeably. As a result, estimates of the availability of salad & cooking oils and shortening spiked. ERS surmises that it is unlikely that this unusually large increase in the number of firms occurred in one year; it is more likely that the number increased incrementally over time. The spike suggests that the availability estimates in a few years before 2000 could have been somewhat underestimated. However, ERS does not have additional information from the U.S. Census Bureau to support or clarify that supposition. Therefore, the data must be interpreted with care when discussing particular estimates for salad & cooking oils and shortening around 2000 or when discussing aggregated numbers based on these estimates, such as estimates for total vegetable fats and oils, total added fats and oils, and total calories from added fats and oils and from all foods (See U.S. Trends in Food Availability and a Dietary Assessment of Loss-Adjusted Food Availability, 1970-2014, in the link below). For additional details about data for individual commodities, see Food Availability Documentation.U.S. Trends in Food Availability and a Dietary Assessment of Loss-Adjusted Food Availability, 1970-2014
The release of the Food Guide Pyramid in 1992 provided researchers with a new framework for assessing U.S. dietary status, going beyond an evaluation of the adequacy of individual nutrients to a food-based approach linking diet and chronic disease risk. In the mid-1990s, ERS conducted a major effort to expand the usefulness of the Food Availability Data Series for diet and nutrition monitoring to take advantage of this food-based assessment. ERS converted the annual food availability data into daily per capita loss-adjusted intake data for over 200 foods (for example, peaches, corn, or beef) by subtracting estimated spoilage, plate waste, and other types of food loss at different stages in the food supply and consumption chain.
ERS gathered existing food loss coefficients from published reports and discussions with commodity experts and then applied these coefficients to the food availability data to create the Loss-Adjusted Food Availability Data Series (formerly called the Food Guide Pyramid Servings data). At the time, there was limited documentation in the literature on food loss at different marketing levels, such as retail and consumer levels, or for individual foods. In particular, ERS accounted for losses in food available for consumption in three selected sectors of the marketing system—retail stores, foodservice institutions, and the home. This was a challenge in that some of the underlying loss assumptions of the data were prone to error and also poorly documented. Thus, in adjusting for food losses, unknown errors could be introduced into the series.
In the January-April 1997 edition of Food Review magazine (see "Estimating and Addressing America's Food Losses" by Linda Kantor), ERS published its first summary tabulations of food loss. The article focused on understanding the magnitude of food losses at the retail, foodservice, and consumer levels and looked for solutions to reduce these losses through food recovery, recycling, and education. Losses were estimated for over 250 individual foods and commodity groups aggregated into 10 food groups with varying levels of food loss. For example, in 1995, the fresh fruit and vegetable category had the greatest food losses at 19.6 percent, while the added fats and oils category had losses amounting to 7.1 percent.
In 1998, ERS released a second report, A Dietary Assessment of the U.S. Food Supply: Comparing Per Capita Food Consumption with Food Guide Pyramid Serving Recommendations, December 1998 (see link below). This publication applied the loss coefficients from the previous study to a broader time period (1970-96), with the assumption that the loss rates remained constant over time. Servings based on the 1996 Food Guide Pyramid (in Home and Garden Bulletin Number 252) were calculated for the same 250 individual foods and commodity groups, which were aggregated into five Pyramid food groups, plus added sugars & sweeteners and added fats & oils.A Dietary Assessment of the U.S. Food Supply: Comparing Per Capita Food Consumption with Food Guide Pyramid Serving Recommendations
Another major effort to revise, refine, and restructure the Food Availability Data System was completed in 2005 and launched on the ERS website (February 1, 2005). This new online data system provided users with individual spreadsheets for over 200 commodities in the Loss-Adjusted Food Availability Data Series, with all of ERS's food loss assumptions presented in the spreadsheets. Each fruit and vegetable also has a separate spreadsheet for different processing types. For example, apples have spreadsheets for fresh, frozen, dehydrated/dried, and canned apples, as well as for apples made into juice. ERS has provided data users with access to the core spreadsheets in this data series for increased transparency of the loss assumptions, with a footnote on each spreadsheet stating that these assumptions were initial estimates intended as a basis for additional research and discussion.
By 2005, despite ERS's improvements to documenting food loss assumptions, ERS's documentation of these assumptions ranged from scant to nonexistent for retail- and consumer-level estimates to substantial for estimates of the nonedible share for individual foods. These loss assumptions were based on data and studies from the mid-1970s or earlier, but the food marketing system has changed dramatically since then, with innovations in processing technology and unprecedented growth in the foodservice sector. Despite these limitations, the food loss estimates were the best available at that time and continued to be used, with appropriate caveats, in assumptions in ERS's Loss-Adjusted Food Availability Data System. For these and other reasons, ERS recognized the need to systematically update and improve all loss assumptions for each commodity by three general types of losses:
- Losses at the primary level (for example, farm to retail weight),
- Losses at the retail level, such as in supermarkets, supercenters, convenience stores, mom-and-pop grocery stores, and other retail outlets (but not including restaurants and other foodservice outlets), and
- Losses at the consumer level. This includes losses for food consumed at home and away from home (for example, restaurants and fast food outlets) by consumers and food services. There are two components:
- "Nonedible share" of a food, such as an asparagus stalk or apple core. Data on the nonedible share are from the National Nutrient Database for Standard Reference, compiled by USDA's Agricultural Research Service (U.S. Department of Agriculture, 2007), and
- "Edible share" of a food, such as cooking loss and uneaten food (or plate waste).
ERS's long-run goal for the Loss-Adjusted Food Availability Data Series is to review, update, and document each loss estimate for individual commodities for the most recent year of data available, and to ascertain if any of these loss estimates have changed since 1970 (the first year in the data series). It was necessary to update and improve these estimates in a series of initiatives due to resource limitations and to the diverse nature of the three types of loss assumptions—farm to retail, retail, and consumer levels.
To date, ERS has completed multipart initiatives to update the three types of loss assumptions for many of the 200 plus commodities in the data series. Data from two of the initiatives are now used directly in the Loss-Adjusted Food Availability Data Series, and select data from the third initiative are used by ERS commodity analysts who provide some of the foundational data for the series. ERS is in the process of determining the next steps for the data series to fill in remaining data gaps. Hence, the data series is considered to be preliminary.
1. Losses at the primary level—farm to retail weight
Under a cooperative agreement, ERS and the University of Minnesota's Food Industry Center (TFIC) compiled revised agricultural conversion factors from farm to retail. Loss estimates are sometimes called conversion factors, particularly when describing how a farm commodity is transformed into a consumer-ready product (for example, fresh chicken to boneless fresh chicken). Through information from a series of industry interviews, TFIC updated the conversion factors for the main categories of meats and poultry, as well as for several fruits and vegetables.
In 2007, the cooperative agreement with TFIC was completed and a new cooperative agreement was started with Pennsylvania State University and the International Life Sciences Institute (ILSI) to review TFIC estimates, collect data on the remaining commodities not covered by TFIC (for example, grains, fats, and dairy products), and explore areas of concern, such as conversion factors identified as most likely to change in the near future. Information from this study is being used by some ERS commodity analysts to update the supply and disappearance spreadsheets—the foundation of the Food Availability Data System.
2. Losses at the retail level
In September 2007, ERS obtained updated food loss estimates at the retail/institutional level to the consumer level (for example, from supermarkets) for fresh fruits, vegetables, meat, poultry, and seafood through a competitive grant with Nielsen's Perishables Group, Inc. (PG). PG compared supplier shipment data with point-of-sale data from stores in large, national supermarket retail chains to identify loss percentages. PG supplemented this with qualitative information from retail contacts. The updated loss estimates from this study had little impact on per capita food loss estimates because the new estimates were generally close to the previous loss assumptions. The updated loss estimates were incorporated into ERS's Loss-Adjusted Food Availability Data Series in February 2009 and are documented in the following report:Supermarket Loss Estimates for Fresh Fruit, Vegetables, Meat, Poultry, and Seafood and Their Use in the ERS Loss-Adjusted Food Availability Data
PG did not have appropriate data to update the retail-level loss assumptions for specific grains, dairy, and added fats & oils in the ERS Loss-Adjusted Food Availability Data Series, and for fruits and vegetables other than in their fresh form (such as canned, frozen, and juice).
In 2014, ERS commissioned PG to collect 2011-12 shrink data for fresh fruits, vegetables, meat, poultry, and seafood for use as retail-level food-loss assumptions in the LAFA data series. The sample included 1 large national and 4 regional supermarket retailers from Nielson’s proprietary database—a database that provided data from roughly 2,900 stores in 45 States and the District of Columbia. The sample did not include convenience stores, megastores, club stores, and mom-and-pop grocery stores. To identify a shrink percentage for each retailer, fresh commodity, and study year (2011 and 2012), the total supplier shipment data were paired with the corresponding total point-of-sale data (aggregated across all stores for each retailer in the sample). Because the newer food loss assumptions were generally close to the earlier ones, the new shrink estimates had relatively little impact on average food-loss rates for the fruit and vegetable groups in the LAFA data series or on total per capita estimates of the quantity of these food groups available for consumption at the retail level. The updated loss estimates are documented in the 2016 report:Updated Supermarket Shrink Estimates for Fresh Foods and Their Implications for ERS Loss-Adjusted Food Availability Data
3. Losses at the consumer level
Under a grant with ERS, RTI International calculated updated consumer-level loss estimates for cooking loss and food loss from the edible share of food. In the first stage of this grant, RTI International reviewed studies on food loss at the consumer level and completed a small sample of restaurant interviews. The report from this effort, Exploratory Research on Estimation of Consumer-Level Food Loss Conversion Factors, concluded that there have been few published research studies on consumer-level food loss in the United States, and most of the published material was released by ERS (see Muth, M. K., Kosa, K. M., Nielsen, S. J., & Karns, S. A. Exploratory research on estimation of consumer-level food loss conversion factors, Agreement No. 58-4000-6-0121, Final Report (Report No. RTI Project Number 0210449.000.001). Research Triangle Park, North Carolina: RTI International, 2007).
In the second stage of this grant, RTI International used a numerical estimation method to calculate consumer-level food loss estimates using Nielsen Homescan data (food purchase data) and the dietary intake component of the National Health and Nutrition Examination Survey (NHANES) (food consumption data). ERS then analyzed how the loss-adjusted food availability per capita data would change if the proposed RTI estimates of consumer-level food loss were incorporated into the data series. The full report, which was published in January 2011, is linked below:Consumer-Level Food Loss Estimates and Their Use in the ERS Loss-Adjusted Food Availability Data
In August 2012, ERS incorporated RTI International's "best estimate" of consumer-level food loss conversion factors into the Loss-Adjusted Food Availability Data Series. When RTI International's best estimates were unavailable, the previous ERS estimate was used. ERS did not adopt the RTI estimate for fresh grapefruit because the estimate did not seem reasonable. Additionally, RTI International's best estimates for cane and beet sugar were used for high fructose corn syrup (HFCS), glucose, and dextrose.
As part of the Launch of the U.S. Food Waste Challenge, ERS has initiatives underway to:
- Update the estimates of food loss at the retail level in the United States provided in Supermarket Loss Estimates for Fresh Fruit, Vegetables, Meat, Poultry, and Seafood and Their Use in the ERS Loss-Adjusted Food Availability Data
- Develop a consistent and globally applicable conceptual model for estimating postharvest food losses
Initiatives to improve ERS's food loss assumptions underlying the LAFA per capita availability estimates
The Loss-Adjusted Food Availability data series is considered preliminary since the underlying assumptions require further improvement. ERS's second long-run goal is to systematically improve and modify the assumptions underlying the LAFA per capita availability and food loss estimates. In 2017, ERS contracted with RTI International to convene a panel of academic experts to review seven critical technical issues and seven data gaps. In the forthcoming report, Expert Panel on Technical Questions and Data Gaps for the ERS Loss-Adjusted Food Availability (LAFA) Data Series, the panel provided recommended approaches and the methods to implement them. The 2018 update to the data series addresses the following issues:
1. Incorporating new measures of supermarket shrink into the data series
In 2016, ERS published the report, Updated Supermarket Shrink Estimates for Fresh Foods and Their Implications for ERS Loss-Adjusted Food Availability Data, on 2011-12 shrink factors for fresh fruits, vegetables, meat, poultry, and seafood to update the retail-level food-loss assumptions in the LAFA data series. Based on the report, the panel had to determine if ERS should incorporate the shrink factors and how the factors should be incorporated. The panel recommended that the updated loss estimates for fresh fruit and vegetables should be incorporated in their entirety from 2011 to the most recent year available. In addition, the panel recommended that the loss factors between 2005-06 and 2011-12 (for the years 2007 to 2010) should be updated using linear interpolation; this, in turn, would document the subsequent change in the loss-adjusted availability estimates. ERS incorporated the updated 2011-12 fresh fruit and vegetable loss factors from 2011 to the current year and used linear interpolation for the years 2007 to 2010.
2. Structuring the balance sheets with regard to the inedible portion
For certain commodities in the balance sheets (such as fresh fruit), nonedible parts (for example, stems, cores, and peels) are removed at the consumer level; on the other hand, nonedible parts for other commodities (such as beef) are removed earlier in the balance sheets. The panel had to determine where the inedible portion should be incorporated into the balance sheet based on three factors: (1) aggregation, (2) transparency, and (3) sequencing. The panel recommended that the balance sheets:
- Account for inedible shares at the consumer level rather than at the primary-to-retail level for six commodities—beef, pork, lamb, veal, chicken, and turkey;
- Add a separate “edible weight” column at the consumer level for all commodities.
ERS added a separate "edible weight" column at the consumer level for all commodities. The addition of the new "edible weight" estimate will improve the transparency of the LAFA data series by providing users with a consumption estimate after the non-edible share has been removed.
The loss-adjusted food availability data were converted into daily per capita food intake, which is presented in two forms: the number of calories consumed daily (per capita) and food pattern equivalents. The data are commonly used to provide estimates of the average daily intake of U.S. food in terms of food pattern equivalents and calories, show year-to-year changes in consumption of major foods, provide insight about consumption trends since 1970, and permit statistical analyses of effects of prices and income on food consumption.
The current ERS per capita food availability data were converted into daily per capita food pattern equivalents, comparable to those identified in USDA's Food Pattern Equivalents Database (FPED), using a multi-stage process. Each commodity was assigned to one of five major food groups (fruits, vegetables, meat, dairy, and grains), or to one of two additional groups for added fats & oils and added sugars & sweeteners. The data were adjusted for spoilage and other losses by subtracting estimated losses from the consumption weight reported in the food availability data. For each commodity, loss was estimated at up to three different stages in the marketing system—farm to retail, retail, and consumer. Nonedible portions of all foods—seeds, pits, bones, and inedible peels—were also subtracted from the data. The data were converted from pounds per capita per year to grams per capita per day to be comparable to food pattern equivalents.
For each food supply commodity, a food pattern equivalent was defined, with size based on USDA's FPED and weight based on USDA's National Nutrient Database for Standard Reference (NDB). For example, FPED defines 1 cup of sliced, raw apple—1/2 of a large apple (3.25-inch diameter) or 1 small apple (2.5-inch diameter)—as a 1-cup equivalent of fruit, and the NDB indicates that 1 cup of sliced apple with skin weighs 110 grams.
After defining food pattern equivalent weights for each commodity, daily per capita consumption—adjusted for loss and nonedible parts—was converted into grams and divided by the assigned food pattern equivalent. Food pattern equivalent weights for individual commodities were aggregated to total daily amounts for the five major USDA food groups, plus the amounts for added sugars & sweeteners and added fats & oils. Aggregated amounts for each food group were then compared with the amount recommended in USDA's Food Patterns of the Dietary Guidelines for Americans and published in a 2017 report, U.S. Trends in Food Availability and a Dietary Assessment of Loss-Adjusted Food Availability, 1970-2014 (see link below). These recommendations are broken into 12 calorie levels, ranging from 1,000 to 3,200 calories per day. Because data are not available on the distribution of Americans among each of the 12 calorie levels in the Dietary Guidelines, ERS used the 2,000-calorie-per-day reference level in the analysis to be consistent with the level used throughout the examples in the Dietary Guidelines and on the Nutrition Facts labels found on most packaged foods.U.S. Trends in Food Availability and a Dietary Assessment of Loss-Adjusted Food Availability, 1970-2014
As with the basic food availability data, the Loss-Adjusted Food Availability Data Series does not measure actual consumption or quantities ingested because neither series is based on direct observations of individual intake (see Food Availability Documentation). Therefore, this data series does not provide breakdowns by socioeconomic, demographic, and geographic (State, regional, or city) characteristics; however, ERS has made a separate calculation for this information which can be found in the Commodity Consumption by Population Characteristics data product.
Limitations on accurately measuring food loss suggest that actual loss rates may differ from the assumptions used in this data series. Estimates of farm to retail, retail, and consumer-level food losses may be understated or overstated due to limitations in the underlying published studies. Food loss is difficult to measure accurately at the consumer level. Participants in household surveys on food waste tend to be highly "reactive"—changing their behavior during the survey period instead of acknowledging how much food they typically discard or misstating their true levels of discarded food products.
Studies that observe food loss by inspecting landfill garbage are also prone to errors. Such studies are not nationally representative and may not account for food fed to pets and other animals, put in garbage disposals, or composted at home. Plate waste studies, such as for schoolchildren at lunchtime, often target only a slice of the total U.S. population, and the findings cannot be extrapolated to other demographic groups.
Food loss for individual commodities, in particular, may vary over time, yet the ERS data currently do not capture most of these changes. For example, trimming fat from some foods, such as red meats, has increased. Processed foods, such as frozen dinners, are generally trimmed more than if the raw ingredients were prepared at home. Smaller households, with increased away-from-home eating, may also have more waste. On the other hand, new food technologies and food production and processing practices, such as improvement in the preservation of bread, may reduce food losses over time.
Although ERS has relatively well-documented data for the loss assumptions for the nonedible share, the Loss-Adjusted Food Availability Data Series is not designed to identify where in the food production, marketing, and consumption chain the nonedible share was removed from food commodities. Rather, the structure of the original data series is such that the nonedible share is removed at the consumer level for fresh fruits, vegetables, and eggs (see "Estimating and Addressing America's Food Losses" by Linda Kantor). Alternatively, meat, poultry, fish, and seafood are transformed into boneless weight earlier in the series; that is, the primary (carcass) weight of the commodity is converted to the retail (boneless) weight.
Both the per capita food availability data and the per capita loss-adjusted food availability data, despite some limitations, are useful for economic analyses because they serve as indirect measures of trends in food use. Both data series provide an indication of whether Americans, on average, are consuming more or less of various foods over time.
Using this data, ERS has contributed to dietary assessment research. For example, the 2017 report, U.S. Trends in Food Availability and a Dietary Assessment of Loss-Adjusted Food Availability, 1970-2014 (see link below), examined major trends in the amount of food available for consumption in the United States between 1970 and 2014 and estimated whether Americans are meeting Federal dietary recommendations for each of the major food groups. Researchers and policymakers can use the Loss-Adjusted Food Availability Data Series to measure changes in food consumption behavior over time relative to major nutrition education or policy initiatives.U.S. Trends in Food Availability and a Dietary Assessment of Loss-Adjusted Food Availability, 1970-2014
Because the loss-adjusted data were derived from data for raw and semi-processed agricultural commodities rather than from final food products, food pattern equivalents can be readily converted back to either the fresh-equivalent (or raw-equivalent) weight at the farm level (for example, for fruits, vegetables, eggs, meat, and poultry) or at the retail level (for example, for dairy, fish, oils, milled grains, and shell nuts). This eases the translation of dietary recommendations into information on production and supply that may be of interest to researchers and the food industry. For example, this time series can be used as a baseline to estimate potential future trends in food demand based on fully meeting Federal dietary recommendations for different food groups.
A 2006 ERS report, Possible Implications for U.S. Agriculture from Adoption of Select Dietary Guidelines (November 2006, see link below), provides one view of the potential implications for U.S. agriculture if Americans fully met the recommendations in the 2005 Dietary Guidelines for Americans and MyPyramid Plan for fruit, vegetables, milk, and whole grains. A straightforward extrapolation using ERS loss-adjusted food availability data for these food groups suggests that the potential long-term impact on food demand and production in the United States could be substantial.Possible Implications for U.S. Agriculture From Adoption of Select Dietary Guidelines
The data are also useful for helping researchers to better understand the differences and similarities between the food supply data and the National Health and Nutrition Examination Survey (NHANES), which measures foods actually consumed by individuals. The food pattern equivalent estimates allow researchers to compare the amount and types of food available in the food supply with information from NHANES on actual food intakes by Americans.
In addition to providing estimates of per capita intake, the loss assumptions embedded in the Loss-Adjusted Food Availability Data Series have been used by ERS over time to estimate food loss at the retail and consumer levels in the United States. Food loss represents the edible amount of food, postharvest, that is available for human consumption but is not consumed for any reason; it includes cooking loss and natural shrinkage (such as moisture loss); loss from mold, pests, or inadequate climate control; and food waste. Summary tabulations for losses on-farm and between the farm and retailer cannot be estimated due to data limitations for some of the food groups. Two articles on food loss (also cited in Background and history of food loss estimates) form the foundation of ERS's estimates in the Loss-Adjusted Food Availability Data Series:
- "Estimating and Addressing America's Food Losses" (1997), and
- A Dietary Assessment of the U.S. Food Supply: Comparing Per Capita Food Consumption with Food Guide Pyramid Serving Recommendations (1998).
Fulfilling a request by the House of Representatives, Committee on Appropriations (H.R. 106-619), ERS published the report (2002). The report reviewed the literature on plate waste in school nutrition programs, particularly the National School Lunch Program (NSLP), to determine the level of plate waste in these programs, factors that contribute to plate waste, and strategies that may reduce waste. (Also see a related article, "Several Strategies May Lower Plate Waste in School Feeding Programs"(2002).
Recently, ERS has disseminated its research and data on food loss in the following three journal articles:
- Postharvest losses and waste in developed and less developed countries: opportunities to improve resource use (2011). In this article, R. J. Hodges, J. C. Buzby, and B. Bennett compared postharvest losses and waste in developed and less developed countries and discussed the opportunities to improve resource use.
- The Value of Retail- and Consumer-Level Fruit and Vegetable Losses in the United States (2011). In this article, J.C. Buzby, J. Hyman, H. Stewart, and H.F. Wells valued losses based on food purchased at retail prices.
- Total and per capita value of food loss in the United States (2012). In this article, J.C. Buzby and J. Hyman expanded the valuation of food loss beyond fruits and vegetables to all other commodities covered in the Loss-Adjusted Food Availability Data Series. The article also discusses strategies to reduce food loss in developed countries.
Additional updated estimates of food loss at the retail and consumer levels in the United States in 2010 are provided in the following table.
|Commodity||Food supply (billion lbs)||Losses - Retail (billion lbs)||Losses - Retail (percent)||Losses - Consumer (billion lbs)||Losses - Consumer (percent)||Losses - Total (billion lbs)||Losses - Total (percent)|
|Other dairy products||29.1||2.8||10||5.7||19||8.5||29|
|Meat, poultry, and fish||58.4||2.7||5||12.7||22||15.3||26|
|Fish and seafood||4.8||0.4||8||1.5||31||1.9||39|
|Tree nuts and peanuts||3.5||0.2||6||0.3||9||0.5||15|
|Added sugar and sweeteners||40.8||4.5||11||12.3||30||16.7||41|
|Added fats and oils||26.0||5.4||21||4.5||17||9.9||38|
Notes: Food supply is at the retail level, which is the foundation for the retail- and consumer-level loss stages in the Loss-Adjusted Food Availability Data Series.
Totals for losses from the food supply may not add up exactly due to rounding.
Per capita losses at the retail and consumer levels for each commodity (not shown in the table) were estimated by multiplying the quantity of that commodity available for consumption by the appropriate loss assumption. Individual loss estimates were then multiplied by the U.S. population and summed to their respective food groups and retail or consumer levels.
Source: USDA, Economic Research Service. Calculated by using food loss assumptions in ERS's Loss-Adjusted Food Availability Data Series for 2010 as of September 17, 2012 (see Food Availability (Per Capita) Data System) and the U.S. population on July 1, 2010 (309.75 million). This table updates the estimates in Estimating and Addressing America's Food Losses.
Total losses at both the retail and consumer levels amounted to 31 percent of the available food supply and weighed almost 133 billion pounds. These estimates would have been even greater if losses at the farm level and between the farm and retail levels had been included. For each of the over 200 commodities in the Loss-Adjusted Food Availability Data Series, the amount of food loss at both the retail and consumer levels was estimated by multiplying the quantity of that commodity available for consumption by the appropriate loss assumption. Individual loss estimates were then multiplied by the U.S. population and summed to their respective food groups and retail or consumer levels. All food loss data for the individual commodities are available on the ERS website in the Food Availability (Per Capita) Data System.
In 2010, the estimated total value of food loss at the retail and consumer levels in the United States was $161.6 billion. This estimate is based on the prices consumers would have paid in 2010, on average, for those foods if bought at retail. ERS derived its food loss estimates by:
- Obtaining national average retail prices in 2010 from Nielsen Homescan data for each of over 200 individual commodities in the Loss-Adjusted Food Availability Data Series,
- Applying these prices to the amount of food loss for each commodity at the retail and consumer levels, and
- Aggregating these values to estimate the total value of food loss at the retail and consumer levels in the United States in 2010.
It is important to note that these estimates are for one point in time and would change as retail prices change in response to changes in the supply and demand for food.
A 2014 report provides ERS's first estimates of the amount of food loss in terms of calories. This report also provides greater detail on the amount and value of food loss in 2010; 133 billion pounds (31 percent of the available food supply at the retail and consumer levels) went uneaten in 2010, and the estimated value of this food loss was $161.6 billion using retail prices. See link below:The Estimated Amount, Value, and Calories of Postharvest Food Losses at the Retail and Consumer Levels in the United States
More information on how the value estimates are calculated is available in four recent articles:
- Estimated Fresh Produce Shrink and Food Loss in U.S. Supermarkets (2015).
- Postharvest losses and waste in developed and less developed countries: opportunities to improve resource use (2011),
- The Value of Retail- and Consumer-Level Fruit and Vegetable Losses in the United States (2011), and
- Total and per capita value of food loss in the United States (2012).
Potential future issues to explore include obtaining better estimates of food loss on the farm and between the farm and retail levels; updating the loss assumptions at the retail level to account for new advances in inventory tracking, packaging, and other technologies; and providing updated retail-level loss assumptions for those commodities not covered in Supermarket Loss Estimates for Fresh Fruit, Vegetables, Meat, Poultry, and Seafood and Their Use in the ERS Loss-Adjusted Food Availability Data (March 2009, see below), but included in the Loss-Adjusted Food Availability Data.Supermarket Loss Estimates for Fresh Fruit, Vegetables, Meat, Poultry, and Seafood and Their Use in the ERS Loss-Adjusted Food Availability Data
A full listing of all ERS publications on food loss is available (see Readings).