Behind The Data

ERS Food Availability Data Under Revision

The ERS per capita food availability data are a historical series that measure the national food supply of several hundred foods. It is the only source of time series data on food availability in the country.

The per capita food availability data are most commonly used to:

• Estimate the average level of food consumption in the country,

• Show year-to-year changes in the estimated consumption of major foods,

• Establish long-term consumption trends, and

• Assess changes in food consumption relative to major nutrition or policy initiatives.

The food availability data measure food use of basic commodities, such as wheat, beef, and eggs, as measured at the farm level or at an early stage of processing. They do not measure food use of highly processed foods, such as bakery products, frozen dinners, and soups, in their finished product form. Their ingredients, however, are included as components of less processed foods, such as sugar, flour, vegetables for processing, and fresh meat.

Constructing the Data

The food availability series is based on records of annual commodity flows, from production to end uses. This involves developing supply and use “balance sheets” for each major commodity from which human foods are produced. In general, the total annual available supply of each commodity consists of the sum of production, imports, and beginning stocks. The amount of food available for human consumption is usually calculated as the difference between available commodity supplies and nonfood use. For most commodity categories, measurable nonfood uses are farm inputs (feed and seed), exports, ending stocks, and industrial uses. The components of the balance sheets are either directly measured or estimated by government agencies using survey sampling and statistical methods.

As an example of these calculations, ERS has published potato supply and use data starting in 1960 for fresh and processing potatoes (i.e., freezing, canning, chipping, and dehydrating potatoes). (Sweet potatoes are estimated separately.) ERS bases its estimates of the availability of potatoes for consumption entirely on production and net trade because data on beginning and ending stocks are not available, except for frozen potatoes. USDA’s National Agricultural Statistics Service provides survey data on production and frozen stocks, and the Census Bureau provides the trade data. Per capita use of potatoes is calculated as total domestic availability divided by total U.S. population (including armed forces overseas) on July 1, as reported by the Census Bureau.

The food availability data are a commonly used proxy for food intake because there are no comprehensive time series data on human food use for the hundreds of commodities covered by this database. The food availability data are not affected by the problems implicit in consumer survey data, such as bias from inaccurate self-reporting of food intake by consumers. In short, the food availability data provide an independent basis for examining changes in food consumption patterns if waste and other losses in the system are relatively constant over time. Additionally, trends in per capita food availability can be used to test the hypotheses that government and general sources of diet and health information influence consumers' food choices.

Conversion Factors Under Revision

One source of error in the food availability data lies with the retail conversion factors used to estimate per capita consumption. The conversion factors used in this data series are rough approximations of weight loss of a commodity from the farm to the retail level. For example, the conversion factor used to convert the weight of fresh potatoes at the farm level to the eventual weight of fresh potatoes sold at retail is estimated at 96 percent. Whereas the retail conversion factor for canned potatoes is around 64 percent. Much of this difference is due to the peeling, cutting, and trimming required to produce various canned potato products.

In general, precise information to estimate and update conversion factors is lacking. The way foods are produced, marketed, and sold has changed over time. For example, some vegetables, like fresh asparagus, are now harvested and bagged on the farm, which means less waste in processing and a higher conversion factor from farm to retail. ERS, in collaboration with The Food Industry Center at the University of Minnesota, has undertaken a high-priority effort to systematically update conversion factors at the retail level. Using input from various members of the food industry—processors, packers, wholesalers, and retailers—will yield more accurate conversion factors and thus a more thorough understanding of how commodities are transformed into consumer products.