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The ERS Loss-Adjusted Food Availability Data are derived from ERS per capita food availability data adjusted for food spoilage, plate waste, and other losses to more closely approximate actual per capita intake. This data series is recommended for estimates of the per capita number of:
- calories consumed daily, and
- MyPyramid equivalents consumed daily of the five major food groups plus the amounts of discretionary added sugar and sweeteners and added fats and oils. These estimates were previously called servings and the data series was previously known as the Food Guide Pyramid Servings data.
This data series is considered to be a preliminary series
because ERS has a set of initiatives underway to update
and document the underlying loss assumptions. Data can
be accessed through Excel
spreadsheets which provide all of the current loss
assumptions and the structure for the data series.
Coverage of the Data
Per capita calorie consumption and MyPyramid equivalents are estimated for more than 250 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 MyPyramid equivalents for the U.S. population.
History Behind the Data
In the mid-1990s, ERS conducted a major effort to expand the usefulness of the Food Availability Data System for diet and nutrition monitoring by converting annual food availability data into daily individual intake data and by adjusting the data for estimated spoilage and losses in the home and marketing system. The release of the Food Guide Pyramid in 1992 provided researchers with a new framework for assessing U.S. dietary status—one that went beyond a traditional approach (adequacy of individual nutrients) to a food-based approach linking diet and chronic disease risk.
Adjusting the food availability data for spoilage and
waste is key to the integrity of the Loss-Adjusted Food
Availability Data series, but data to make such adjustments
are unreliable. Unknown errors could be introduced into
the series by adjusting for losses. Previous studies have
limited documentation of food loss estimates at different
marketing levels such as retail and consumer levels or
for individual food commodity groups (for example, peaches,
corn, or beef).
ERS first attempted to estimate losses from data on food available for consumption in three selected sectors of the marketing system—retail stores, foodservice institutions, and the home. ERS gathered existing food loss coefficients from published reports and discussions with commodity experts and then applied these coefficients to the Food Availability Data System for 1995. See “Estimating and Addressing America's Food Losses,” in the January-April 1997 edition of FoodReview magazine. 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.
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.” 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, 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 sweeteners and added fats and oils.
Another major effort to revise, refine, and restructure the data system was completed in 2005, and the new system was launched on the ERS website on February 1, 2005. For the first time, this new data system included spreadsheets for each of the hundreds of commodities in the Loss-Adjusted Food Availability Data, and the spreadsheets presented all of ERS's food loss assumptions. Additionally, each fruit and vegetable 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 provided data users with access to the core spreadsheets in this data series to increase transparency of the loss assumptions, with a footnote on each spreadsheet stating that these assumptions were first estimates intended to serve as a starting point for additional research and discussion.
By 2005, the level of documentation of ERS's food loss assumptions ranged from little to none for estimates at the retail and customer levels to substantial for estimates at the farm level and for the nonedible share for each food. 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, including innovations in processing technology and unprecedented growth in the foodservice sector. Despite these limitations, the food loss estimates were the best available and continued to be used in assumptions in ERS's Loss-Adjusted Food Availability Data System. For these and other reasons, ERS recognized the need to update and improve all loss assumptions for each commodity for 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, megastores like Walmart, and other retail outlets, including convenience stores and mom-and-pop grocery stores. Losses in restaurants and other foodservice outlets are not included.
- 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).
- Cooking loss and uneaten food, such as plate waste from the edible share.
Initiatives To Update the ERS Loss-Adjusted Food Availability Data
ERS's longrun goal for the Loss-Adjusted Food Availability
Data series is to review, update, and document each loss
estimate for each covered commodity for the most recent
year of data possible, 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 because of
the diverse nature of the three types of loss assumptions—farm
to retail, retail, and consumer levels—and because
of resource limitations. ERS has three
multipart initiatives underway to update the three
types of loss assumptions for the several hundred commodities.
Although some of the initiatives have been completed and
the resulting updated loss estimates are now used in the
Loss-Adjusted Food Availability Data series, other initiatives
and subcomponents are still underway and still other initiatives
may be necessary to fill in remaining data gaps. Hence,
the data series is considered to be preliminary.
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Losses at the primary
level—farm to retail weight |
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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. The final report from this second cooperative agreement is forthcoming. Once these new estimates are reviewed and approved by ERS, they will be available for use by ERS commodity analysts and for updates to the loss assumptions in the Food Availability Data System. |
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| 2. |
Losses at the retail level |
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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 the 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 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 and 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, juice). |
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| 3. |
Losses at the consumer level |
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Under a grant with ERS, the Research Triangle Institute
(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 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, concludes that
there have been few published research studies
on consumer-level food loss in the United
States, and much of the published material
was released by ERS. In the second stage of
this grant, RTI used a numerical estimation
method to calculate consumer-level food loss
estimates using Nielsen Homescan data and
National Health and Nutrition Examination
Survey (NHANES) 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, Consumer-Level
Food Loss Estimates and Their Use in the ERS
Loss-Adjusted Food Availability Data was published
in January 2011. |
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In addition to these initiatives, ERS welcomes suggestions to expand and improve its loss estimates. Once the 2010 Dietary Guidelines for Americans are released, the Loss-Adjusted Food Availability Data series will be updated to incorporate Federal recommendations and other information from this report.
Constructing the Data
The current ERS per capita food availability data were converted into daily per capita MyPyramid equivalents comparable to those identified in USDA’s MyPyramid Food Guidance System 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 discretionary added fats, oils, and added sweeteners. The data were adjusted for spoilage and other losses by subtracting estimated losses from the consumption weight reported in the food availability data. Loss was estimated at several different stages in the marketing system (farm to retail, retail, and consumer). Nonedible portions of all foods—seeds, pits, and inedible peels—were also subtracted from the data. The data were converted from pounds per capita per year to grams (or ounces) per capita per day to be comparable to MyPyramid equivalents.
For each food supply commodity, a MyPyramid equivalent was defined, with size based on USDA’s MyPyramid Food Guidance System and weight based on USDA's Nutrient Database for Standard Reference (NDB). For example, the MyPyramid Food Guidance System defines 1 cup of sliced, raw apple as a 1-cup equivalent of fruit and the NDB indicates that 1-cup of sliced apple with skin weighs 109 grams.
After defining MyPyramid equivalent weights for each commodity, daily per capita consumption—adjusted for loss and nonedible parts—was converted into grams and divided by the assigned MyPyramid equivalent. MyPyramid equivalent weights for individual commodities were aggregated to total daily amounts for the five major MyPyramid food groups, plus the discretionary amounts for added sugar and sweeteners and for added fats and oils. Aggregated amounts for each food group plus the discretionary groups were then compared with the amount recommended in USDA’s Food Guide in Appendix A-2 of the 2005 Dietary Guidelines for Americans. 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.
Limitations of the Data
As with the basic food availability data, the Loss-Adjusted Food Availability Data series does not measure actual consumption or the quantities ingested. This is because neither series is based on direct observations of individual intake (see Food Availability documentation). Therefore, data are not available by socioeconomic, demographic, and geographic (State, regional, or city) breakdowns, and it is not known if such data exist.
The limited ability of researchers to measure food loss accurately suggests 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, particularly at the consumer level, is by nature difficult to measure accurately. 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 product discard. 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 categories.
Food loss for individual commodities, in particular, may vary over time, yet the ERS data currently do not capture these changes. Some of the apparent increase in food loss probably stems from increased waste and more trimming of food. Processed foods, such as frozen dinners, are generally more trimmed 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. Additionally, 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.
Usefulness of the Data
Even with some limitations, both the per capita food availability data and the per capita loss-adjusted food availability data are useful for economic analyses because they serve as indirect measures of trends in food use. In other words, both data series provide an indication of whether Americans, on average, are consuming more or less of various foods over time.
By converting food availability data into daily individual food servings comparable to MyPyramid recommendations, ERS has contributed to existing dietary assessment research. For example, the 2008 report “Dietary Assessment of Major Trends in U.S. Food Consumption, 1970-2005” examined major trends in the amount of food available for consumption in the United States between 1970 and 2005 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.
Because the loss-adjusted data were derived from data for raw and semi-processed agricultural commodities rather than for final food products, MyPyramid equivalents can be readily converted back to farm-level data. This eases the translation of dietary recommendations into production and supply goals for farmers and the food industry. This time series can be used as a baseline to project future trends in food demand and to compare these trends with recommendations for MyPyramid equivalents. For example, a 2006 ERS report “Possible Implications for U.S. Agriculture from Adoption of Select Dietary Guidelines” 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.
The data are also useful for helping researchers better understand the differences and similarities between the food supply data and USDA's Continuing Survey of Food Intakes by Individuals (CSFII), which measures food products actually eaten by individuals. In essence, the serving estimates allow researchers to compare the amount and types of food available in the food supply with information on actual food intakes by Americans.
 For more information, see Estimating
and Addressing America's Food Losses , A Dietary Assessment
of the U.S. Food Supply: Comparing
Per Capita Food Consumption with Food Guide Pyramid Serving Recommendations, and the Food
Availability documentation. See also Glossary, Questions & Answers, and Related
Resources.
View or download Excel spreadsheets of Loss-Adjusted
Food Availability Data.
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