USDA Food Intake Data Converted to Retail Food Commodities in Creme Food®

The 1994-2002 FICRCD data has between 4,000 and 9,000 foods, each converted to their food commodity equivalents (per 100g of food consumed). The database consists of 8 high level food commodity categories, these are:

  • Dairy Products
  • Fats and Oils
  • Fruits; Grains
  • Meat, Poultry
  • Fish and Eggs
  • Nuts
  • Caloric Sweeteners and
  • Vegetables, Dry Beans and Legumes

These are further divided into 65 food commodities.

In Creme Food® the FICRCD database is linked with CSFII 1994 – 1998, NHANES / WWEIA 1999-2000 and NHANES / WWEIA 2001-2002. This allows us to generate food commodity intakes results for each of these survey populations and analysis of commodity intakes for any population sub-groups of interest (e.g. broken down by age, gender and economic status).

FICRCD was developed by USDA’s Agricultural Research and Economic Service with the aim of linking nutrition, agriculture and economics. This information allows us to determine the amount ($) spent on food commodities at an individual consumer or population level. We can achieve this by linking this database with the USDA ERS food expenditure data set.

We can now understand, for example, the minimum cost of obtaining a healthy diet for US consumers. This information can be used to create promotional campaigns on cost effective diets that can provide all essential nutrient requirements for families.

Please contact us for more information on Creme Food® and visit our website here to learn more about our products and services.

References: 

Bowman SA, Martin CL, Friday JE, Moshfegh AJ, Lin B-H, and Wells
HF. 2011. Methodology and User Guide for The Food Intakes Converted to Retail Commodities
Databases: CSFII 1994-1996 and 1998; NHANES 1999-2000; and WWEIA, NHANES 2001-2002.
U.S. Department of Agriculture, Agricultural Research Service, Beltsville, MD, and U.S.
Department of Agriculture, Economic Research Service, Washington, D.C.

Written by Mark Lambe on June 6 2013

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