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United States Department of Agriculture

Agricultural Research Service

Title: Evaluation of nutrient variability in highly consumed "fast foods" under the National Food and Nutrient Analysis Program

Authors
item Pehrsson, Pamela
item Haytowitz, David
item Perry, Charles - NASS
item Nickle, Melissa
item Cutrufelli, Rena
item Holden, Joanne

Submitted to: Experimental Biology
Publication Type: Abstract Only
Publication Acceptance Date: November 21, 2006
Publication Date: April 25, 2007
Citation: Pehrsson, P.R., Haytowitz, D.B., Perry, C., Cutrufelli, R.L., Holden, J.M. 2007. Evaluation of nutrient variability in highly consumed "fast foods" under the National Food and Nutrient Analysis Program. Experimental Biology, April 25, 2007, Washington, D.C.

Technical Abstract: USDA's National Food and Nutrient Analysis Program generates means and standard errors (S.E.) of nutrients in foods from nationally representative sample sets used in dietary assessment and consumer education. However, genetic makeup, growing/shipping/storage conditions, preparation techniques, and differences among brands, locations, analytical methods, and laboratories affect nutrient variability. Hamburgers, French fries, and chicken tenders, highly consumed fast foods, were double-sampled from 12 nationally representative locations and three top chains. AOAC methods were used for analysis of 27 nutrients. ANOVA comparisons of nutrient variability for select nutrients were made between regional/random composites and individually analyzed samples. For some nutrients, most of the difference in variability between individual and composites analyses was explained by the grouping effect (e.g., sodium in hamburgers, 77%, p<.006); 11 nutrients showed a significant grouping effect (p<.10). Using regression modeling, composite variability was a reasonable predictor of serving-to-serving variability for some nutrients (3.5 x composite S.E.). Understanding the variability in nutrient databases is important when estimating intakes for use with reference values, nutrient intolerances, sample size determination, and cost-effective modeling. Funded by: USDA & NIH Y1CN5010.

Last Modified: 8/29/2014
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