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Purchase to Plate - Documentation

Purchase to Plate National Average Prices dataset for WWEIA/NHANES

Overview

The Purchase to Plate National Average Prices (PP-NAP) data set provides estimated prices for individual food and beverage items reported consumed by participants in What We Eat in America (WWEIA), the dietary component of the National Health and Nutrition Examination Survey (NHANES). The prices are derived using the Purchase to Plate Crosswalk (PPC), a restricted access element of the Purchase to Plate Suite, that links retail grocery scanner data from Circana (formerly Information Resources, Inc. (IRI)) with the USDA, Food and Nutrient Database for Dietary Studies (FNDDS).  

The PP-NAP can be used to estimate the cost of food for the WWEIA/NHANES study participants’ reported food intake and was used by the USDA in the 2021 reevaluation of the Thrifty Food Plan (TFP). The TFP is used as the basis for Supplemental Nutrition Assistance Program (SNAP) benefits. This data product is part of the USDA, Economic Research Service’s (ERS) Consumer Food Data System.

Data availability: The PP-NAP follows the cycles of WWEIA/NHANES. Through 2018, these data were released in 2-year cycles: 2011–12; 2013–14; 2015–16; 2017–18.

Scheduled next release: Data collection for WWEIA/NHANES was interrupted by the Coronavirus (COVID-19) pandemic in March 2020. These data were combined with earlier data and released as the WWEIA/NHANES 2018–March pre-pandemic data. Data collection began again in August 2021 and was released as WWEIA/NHANES 2021–23. ERS anticipates providing price data for the WWEIA/NHANES 2021—23 no earlier than fall 2025.

Scope/Coverage of Data 

The 2017–18 and 2015–16 PP-NAP provide food prices that are the average of 2-years of price data collected from grocery stores, while the 2013–14 and 2011–12 PP-NAP provide this data using 1 year. Food prices are for foods that NHANES respondents report eating and are based on 100 grams of the food as eaten. That is, the food items are fully cooked, and the weight of the food only includes the edible portion. The weight does not include bones, skins, peels, seeds or shells.  

Foods in WWEIA, and thus the PP-NAP, are more general than grocery items (e.g. apple versus large Honeycrisp apple sold in a 5-pound bag) and can include multiple items sold in a grocery store (e.g. stir-fried broccoli with peanut sauce contains broccoli, oil, peanuts, and either a purchased peanut sauce or ingredients to make the sauce). 

Prices are included for foods reported at least 10 times in each cycle of WWEIA/NHANES.

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Methods Used to Produce Data

The datasets (described below) used to build PP-NAP are USDA’s What We Eat in America (WWEIA), the dietary component of the National Health and Nutrition Examination Survey (NHANES), the USDA Food and Nutrient Database for Dietary Studies (FNDDS), the Circana retail grocery scanner data (OmniMarket Core Outlets (formerly InfoScan)), and the Purchase to Plate Crosswalk (PPC). The generalized process for construction of the national average prices is as follows:

  1. Select USDA food codes representing foods or beverages that were reported 10 or more times in the WWEIA cycle or are needed for the Thrifty Food Plan (TFP) market basket update.
  2. Review recipes in the FNDDS of the selected foods to determine whether recipe modifications are needed to accommodate convenience foods and include standard substitutions in the recipe.
  3. Calculate the total purchase weight sold and expenditure for each item (at the Universal Product Codes (UPCs) (barcodes) level) in the Circana grocery scanner data.
  4. Link scanner data UPCs to food codes in the FNDDS using the PPC.
  5. Convert purchase weight to edible weight for each UPC using the PPC conversion factors.
  6. Sum the total expenditure and edible weight across UPCs for each ingredient in the recipe.
  7. Calculate the average price per 100 grams of the ingredients by dividing expenditure by edible weight.
  8. Apply average unit prices for the ingredients to the recipes identified in step two and calculate the unit price of the FNDDS foods selected in step one.

The resulting prices are nationally representative of foods that are reported eaten by WWEIA/NHANES participants. The resulting price for any particular food may be derived from multiple brands and private labels, package sizes, flavors, and types. The Circana grocery scanner data represent individual products that are purchased in a grocery store. The WWEIA/NHANES codes and supporting recipes in the FNDDS are more general (e.g., BBQ sauce versus a brand-specific BBQ sauce). More information on each of these datasets, including links to the data, is included in the Additional Literature section.

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Sources of Data (Public)

What We Eat in America/National Health and Nutrition Examination Survey (WWEIA/NHANES) – NHANES is a biennial program of surveys aimed at assessing the health and nutrition of non-institutionalized adults and children living in the United States. Of particular interest is the WWEIA component that includes one or two 24-hour dietary recall interviews for each respondent. The USDA then calculates the nutritional content for the foods reported—including the vitamin and mineral content, and the food pattern equivalents (food group quantities). Respondents describe the quantity of the food or beverage, and this information is uniformly converted to grams of food or beverage. Note that the grams of food are only the edible portion—after the skin, peels, seeds, bones, and shells are removed and the food is cooked.

Food and Nutrient Database for Dietary Studies (FNDDS) – The FNDDS provides the nutrient content for the foods in the WWEIA survey. USDA determines the average nutrient content of these foods by developing recipes. Some recipes are a single ingredient (e.g., an apple, milk, orange juice, cooked chicken with no salt added), while others include multiple ingredients, and some incorporate standardized ingredient recipes. For example, cooked chicken might be used in several recipes so there is one recipe for cooked chicken used in all recipes. The recipes are used in the PP-NAP to estimate the cost of the food, but revisions are needed to incorporate convenience foods, include commonly used substitutions, and include all forms of ingredient items (e.g., fresh, frozen, dried, shelf-stable, cooked, raw, and purchased with or without refuse (skins, peels, seeds, bones, shells)).

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Sources of Data (Proprietary)

Circana OmniMarket Core Outlets – The Circana (formerly Information Resources, Inc. (IRI)) OmniMarket Core Outlets (formerly InfoScan) dataset is a record of retail food store sales from across the country at the UPC level. Participating stores include standard grocery stores, mass merchandisers or super centers, convenience stores, drug stores, and dollar stores. The Circana Product Dictionary (PD) offers additional information at the Universal Product Code (UPC) level—including weight, flavor, and nutrients from the nutrition facts label. This nutrient information, however, is lacking in comparison to USDA nutrition databases. The weight is the purchase weight, so items like fresh fruits and vegetables may contain refuse (e.g., peels, seeds, skins), while other items (such as raw meat, pasta, and raw rice) would gain or lose weight when the consumer cooks the food. More information about the data, including the statistical properties of these data are available.

Sources of Error

There are three known sources of error in the PP-NAP: the quality of the matches, the choice of recipe used to price the food in NHANES, and representativeness of the scanner data.

  1. Matching—Although matches between the scanner data and the USDA data are done using computer-assisted methods, each match is reviewed by trained nutritionists. For consistency, a sample of each nutritionist’s review is reviewed by a senior nutritionist. The stated error rate for the matches is less than 5 percent, but the true error rate is likely lower. Remaining errors in the matches are most likely due to errors in the product dictionary.
  2. Recipe choice—The FNDDS recipes developed for WWEIA/NHANES were used as a starting point. However, most of these recipes had to be modified and, in some cases, a prepared product was used. When comparing prices of two closely related products (e.g., hot coffee made from coffee grounds versus a mocha-latte purchased ready-to-drink), the price differences are not considered errors.
  3. Retail scanner data:
    1. Missing stores—Compared to Economic Census data (U.S. Department of Commerce, Bureau of the Census), InfoScan (now known as OmniMarket Core Outlets) data ERS receives represent half of all grocery sales but only represent 15 percent of stores. This coverage varies by parts of the country. Additional information on how representative the data are can be found in the ERS report, Examining Food Store Scanner Data: A Comparison of the IRI InfoScan Data with Other Data Sets, 2008–2012.
    2. Stores may not be representative of the national composition of stores—Future updates will include ERS developed store weights to account for some of these shortcomings.
    3. Private label products may be underrepresented—Some chains do not share their private label (store brand) data with ERS at a sufficient level of detail to include in the PP-NAP estimation.
    4. Errors in the product dictionary—In rare cases, the product information is incomplete, or the product is categorized incorrectly.

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Strengths and Limitations

PP-NAP limitations

  • The unit prices are national averages and do not represent the prices that WWEIA/NHANES participants (or any other consumers) face in a given locality, at a certain time, or for a specific food item.
  • Unit prices are based on the retail cost of food purchased at grocery stores and other stores that sell groceries. The unit prices do not include adjustment for the labor, rent, and utilities associated with restaurant food. The prices also do not include sales tax or account for any edible food loss.
  • Individual price changes between cycles of PP-NAP can reflect new product introduction to the market, removal of older products, and consumers changing their preferences for package sizes. In addition, changes to the FNDDS impact both how product prices are calculated and the individual products that are calculated. As a result of these changes, ERS does not advise using the PP-NAP to examine trends in price changes between cycles.

PP-NAP strengths

The PP-NAP allows researchers to add relative food price data to the vast array of medical and dietary data available in NHANEs. Using reported dietary intake, the PP-NAP allows researchers to estimate a distribution of food expenditures over all or a sub-set of individuals. Since each food has the same price per 100 grams no matter which individual reports eating it, differences in estimated expenditures reflect differences in food choices alone.

  • These data are used in reevaluation of the Thrifty Food Plan.
  • The prices can be used independent of NHANES to compare the relative cost of healthy and less healthy foods, estimate the national average cost of preparing a set of recipes, or in combination with other data linked to the FNDDS.

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Resources

Restricted Access PP-Suite Products

The following products are restricted access because they include Circana’s proprietary data. Information on accessing the Circana data and these value-added products is available on the Using Proprietary Data page.

The Purchase to Plate Crosswalk (PPC) allows researchers to measure how well consumer purchases or store sales adhere to Federal nutrition guidance by calculating Healthy Eating Index (HEI) scores. The PPC does this by linking retail foods in the Circana household and store scanner data with foods found in the FNDDS. The PPC provides a crosswalk between about 350,000 retail foods reported in Circana grocery and household scanner data in a given year to about 3,200 foods included in the FNDDS in the closest matching year(s). The retail foods in Circana data are typical grocery items and are ready-to-eat, ready-to-heat, or ingredients used to prepare meals and snacks. The foods in the FNDDS are “prepared” foods (e.g., cooked, peeled, etc.), ready-to-eat, reported “as consumed”—or in some cases raw but without the inedible bones, seeds, shells, or skins included. To allow users to align purchase quantities with the nutrients in the USDA data, the PPC provides conversion factors associated with each grocery item that converts the item’s purchased weight to the edible (“as consumed”) weight.

The Purchase to Plate Price Tool (PPPT) estimates food prices for the foods WWEIA/NHANES participants report consuming. PPPT includes the program and data that produces the PP-NAP, following the steps described in Methods Used to Produce Data. The tool allows researchers to estimate food prices for a subset of the IRI grocery scanner data.

The Purchase to Plate Ingredient Tool (PPIT) produces data that indicate how much of each item in the recipe should be purchased to prepare 100 grams of the food. Estimated price information for the ingredients is also included.

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Additional Literature

Price Construction

These publications provide background on how National Average Prices are constructed:

IRI InfoScan and Consumer Network

Please see ERS’s Using Proprietary Data page for more information on the Cirana databases—including how to gain access to the Circana data and considerations when using the data and comparisons of  Circana OmniMarket Core Outlets and Consumer Network database to other databases.

USDA Nutrition Database

The PP-NAP uses the recipes in the Food and Nutrient Database for Dietary Studies (FNDDS) to create prices.

USDA Purchase to Plate Crosswalk (PPC)

The following report includes information on linking the IRI grocery scanner data to the USDA FNDDS, including matching methodology and conversion factors:

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How the PP-NAP differs from other ERS Data Products

The Fruit and Vegetable Prices data product looks at the average prices for more than 150 commonly consumed fresh and processed fruits and vegetables, including the retail price per pound and the price per edible cup equivalent. The prices in this data product are also constructed from the Circana grocery scanner data, however the scanner data foods used are fewer and more focused than the PP-NAP. For example, organic fruits and vegetables are not included and package sizes are limited. The PP-NAP includes all package sizes and organic foods. In addition, the PP-NAP food costs are tied to codes in the FNDDS while the Fruit and Vegetable Prices are not. Finally, the PP-NAP covers a more diverse set of foods than the 150 most frequently consumed fruits and vegetables.

The Food Expenditure Series is a comprehensive data set that measures the U.S. food system—quantifying the value of food acquired in the United States by type of product, outlet, and purchaser. The data series measures the value of food acquired—including food and beverage sales (as well as taxes and tips), and the value of food produced at home, donated, and furnished to employees and institutionalized persons. Food expenditure data are estimated at the national and State levels. National-level food expenditures are allocated annually between four types of products from various outlets and three types of purchasers and users. In addition to the annual estimates, monthly sales of food at home (FAH) and food away from home (FAFH) are available, benchmarked to the annual estimates, with each annual revision. State-level expenditures are allocated annually for FAH and FAFH, benchmarked to the national-level estimates. The annual average consumer FAH expenditure data are used to validate the PP-NAP. The PP-NAP allows users to develop a distribution of total food costs based on the 2 days of dietary recall data in NHANES.

The Food Price Outlook uses the U.S. Bureau of Labor Statistics Consumer Price Index (CPI) and Producer Price Index (PPI) and other information to forecast the price changes of major categories of food. The PP-NAP provides food costs for specific foods for past years.

The Food-at-Home Monthly Area Prices (F-MAP) data product provides monthly food price data over time, across food groupings, and across geographic areas. F-MAP includes monthly prices for 90 food-at-home (FAH) categories across 15 geographic areas of the United States. The F-MAP contains two types of price measures for each food group, geographic area, and month combination: (1) a mean unit value price and (2) a price index. The PP-NAP provides more detailed item-level price data, but at the national level and over two years instead of every month.

The National Household Food Acquisition and Purchase Survey (FoodAPS) is a comprehensive survey of all food acquisitions made by participating households over a 1-week period. The data also contain links between UPCs and the FNDDS. The PP-NAP provides average prices for items in the FNDDS, while FoodAPS records the price paid by the household for a specific grocery or FAFH item.

The Food Consumption, Nutrient Intakes, and Diet Quality data product reports the average daily ingested amounts of selected nutrients and food groups, as well as added sugars and discretionary fats and oils. These data are reported for total intake as well as amounts per 1,000 calories (density). Along with overall population estimates, estimates are provided by sex, age group, race/ethnicity, education, and income levels. For all groupings, data are provided for individuals’ total food consumption as well as subdivided for FAH and FAFH. Data were obtained from Federal food consumption surveys from 1977 to 2018. Since 2003, those data have been obtained from the WWEIA/NHANES survey. The PP-NAP provides national average prices for foods in the WWEIA/NHANES survey, so that researchers can use additional data in WWEIA/NHANES for their research questions.

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Recommended Citation

Recommended Citation: U. S. Department of Agriculture, Economic Research Service. (2023). Purchase to Plate National Average Prices from the Purchase to Plate Suite [data product].

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User’s Guide

The PP-NAP can be linked to WWEIA/NHANES data by joining the food_code variable with the corresponding WWEIA/NHANES variable. The PP-NAP also contains the price per 100 edible grams (price_100gm), other columns that cover the method used to calculate the price (method, method_description), and whether the food can be found in NHANES or only FNDDS. WWEIA/NHANES food quantity data are reported in edible grams.

As noted in the “Methods Used to Produce Data”, the PP-NAP does not include all foods reported in WWEIA/NHANES. At a minimum, foods are included if they are reported at least 10 times by survey participants. Additional food prices are included as described below.

The following variables are available for each 2-year data period:

  • Year—Indicates the data period of NHANES where the food_code is found
  • food_code—Code assigned for the food in the FNDDS, which is the same code used in WWEIA/NHANES
  • mod_code—Code assigned to a modification of a food_code. Use food_code and mod_code when linking to WWEIA/NHANES (PP-NAP 2011/2012 only)
  • food_description—Description of the food associated with food_code
  • method – Number of the method used to calculate the price
  • method_description—Name of the method used to calculate the price (the publications under “Price Construction” in the Additional Literature section provide additional details)
  • NHANES—Indicates why the food_code is included in the PP-NAP (not in PP-NAP 2011/2012):
    • Base—Food identified at the beginning of the price creation process
    • Top 90—Participants in WWEIA/NHANES, reported eating this food or beverage at least 10 times (PP-NAP 2013/2014 only)
    • Extras—Has a direct link to Circana grocery scanner data and exists in the FNDDS only or the food was added later in the process to facilitate the next revision of the USDA Food Plan market baskets
    • Alcohol—Alcoholic beverage (PP-NAP 2013/2014 only)
  • price_100gm—The price per 100 edible grams of the food in nominal dollars for the years of the IRI data used to estimate the price

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