Submitted to: National Nutrient Databank Conference
Publication Type: Abstract Only
Publication Acceptance Date: 4/11/2008
Publication Date: 5/12/2008
Citation: Lemar, L.E. 2008. Fatty acid data in the USDA National Nutrient Databank: Data handling and currency issues. 32nd National Nutrient Databank Conference, May 12-14, 2008, Ottawa, Ontario, Canada. Interpretive Summary:
Technical Abstract: Modifications in the USDA National Nutrient Databank System have facilitated the Nutrient Data Laboratory (NDL) in upgrading fatty acid handling. High priority was given to enabling fatty acid data to be entered in units as received (e.g. percent methyl esters, percent fatty acid of total fat) and then converted to g fatty acid per 100 g food for dissemination in the USDA National Nutrient Database for Standard Reference (SR). Other enhancements have included the ability to disseminate data on additional fatty acid isomers, including trans-fatty acids, and to perform a variety of normalization procedures on fatty acid data. These normalizations are essential to allow fatty acids from one source to be adjusted to total fat values and/or fatty acid class data from other sources. In the past 10 years a variety of foods, including margarines and spreads, snack foods, and industrial oils and shortenings, have been sampled and analyzed for a variety of nutrients including fatty acids. NDL nutritionists review food label ingredient listings and Nutrition Facts panels regularly to ensure that SR fatty acid data are current with respect to oil source (e.g. soybean, canola, palm), treatment (e.g., hydrogenation), and form (e.g., pourable oil or solid). As formulations change, fatty acid data are replaced with current data from USDA contract analyses, industry-provided data, or, in some cases, with data calculated by a formulation estimation process. These updates not only are critical to maintaining currency of the SR database, they are critical to food intake assessments which use data from the Food and Nutrient Database for Dietary Studies (FNDDS). The underlying food composition data in the FNDDS come from a subset of foods and ingredients in SR.