DEVELOPMENT OF ACCURATE AND REPRESENTATIVE FOOD COMPOSITION DATA FOR THE U.S. FOOD SUPPLY
Location: Nutrient Data
Title: UNDERSTANDING NUTRIENT VARIABILITY: IMPACT ON PUBLIC HEALTH
Submitted to: National Nutrient Databank Conference
Publication Type: Abstract Only
Publication Acceptance Date: May 11, 2006
Publication Date: September 18, 2006
Citation: Holden, J.M., Pehrsson, P.R., Perry, C., Patterson, K.K., Haytowitz, D.B. 2006. Understanding nutrient variability: impact on public health. National Nutrient Databank Conference, September 18-20, 2006, Hawaii.
Objective: Information on the sources and magnitude of nutrient variability in U.S. foods is often lacking and may include differences due to cultivars, brands, growing or processing conditions, cooking practices, fortification, nutrient stability, and analytical methods. Accurate analytical determination of variability (with minimal errors in measurement) is especially important for critical nutrients and application of food composition data in dietary guidance programs. Methods: The National Food and Nutrient Analysis Program (NFNAP) generates high quality estimates of food components, expanding and improving the quality of data in United States Department of Agriculture (USDA) food composition databases. Nationally representative sampling plans, adequate sample size, and rigorous sample handling and analytical protocols ensure quality data for estimating nutrient variability. Variability is examined among: 1) brand-specific composites; 2) individual samples; 3) production/growing locations (e.g., agricultural commodities); 4) harvest seasons/locations (e.g., fresh produce); and 5) analytical methods and labs. Results: An ANOVA in select foods showed wide variability for nutrients due to brand and location (e.g., 46-89% of the variability in proximates in frozen cheese pizza). Fluoride in drinking water ranged from <20 ug (wells) to 100-110 ug (municipal) per 100 g across 144 national locations. A region effect was detected for over 10 nutrients in fast food hamburgers across chains. Vitamin D variability data in milk will also be presented. Conclusion: These techniques for assessing nutrient variability allow improved monitoring of estimates of the composition of foods, including fortified foods, and nutrient intakes, product development, and information for planning future studies and assessing adequacy of analytical programs. Funding: USDA and National Institute of Health (NIH), Agreement No. Y1CN5010.