USDA's National Food and Nutrient Analysis Program: Food Sampling |
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| Affiliation: | 1. Food and Nutrition Department, National Institute of Health (INSA), Portugal;2. Institute of Food Research (IFR), UK;3. Statni zdravotni ustav (SZU), Czech Republic;4. Agence nationale de Securite sanitaire de l''alimentation de l''environnement et du travail (ANSES), France;5. Matís Ltd, Icelandic Food and Biotech R&D, Reykjavik, Iceland;6. Bundesinstitut fuer risikobewertung (BFR), Germany;7. Finnish Food Safety Authority (EVIRA), Finland;1. University of Zagreb, Faculty of Food Technology and Biotechnology, Pierottijeva 6, Zagreb, Croatia;2. Clinical Hospital Dubrava, Avenija Gojka Šuška 6, Zagreb, Croatia;1. Department of Diabetology, Metabolic and Nutrition Disease, University Hospital of Toulouse, Toulouse, France;2. University of Toulouse, Institut National Polytechnique de Toulouse–Ecole Nationale Supérieure d’Électrotechnique, d’Électronique, d’Informatique, d’Hydraulique, et des Télécommunications, Toulouse, France;3. Department of Epidemiology and Analyses in Public Health: Risks, Chronic Diseases, Handicaps, University Hospital of Toulouse, Toulouse, France;4. Department of Paediatrics, Endocrinology, Genetics, and Medical Gynaecology, University Hospital of Toulouse, Hôpital des Enfants, Toulouse, France |
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| Abstract: | The National Food and Nutrient Analysis Program (NFNAP) is designed to develop robust estimates of the mean nutrient content of important foods in the food supply and significantly improve the quality of food composition data in the US Department of Agriculture's (USDA) National Nutrient Databank. The program objectives are: (1) evaluation of existing data; (2) identification of Key Foods and nutrients for analysis; (3) development of nationally based sampling plans; (4) analysis of samples; and (5) compilation and calculation of representative food composition data. This paper describes our efforts in development of the sampling plan (objective 3) and presents limited preliminary results. The sampling plan was based on a self-weighting stratified design. First, the U.S. was divided into four regions, then each region was further divided into three implicit strata from which generalized Consolidated Metropolitan Statistical Areas (gCMSAs) were selected. Rural and urban locations were selected within gCMSAs. Commercial supermarket lists were used to select 24 outlets for food pickups; specific brands were selected based on current market share data (pounds consumed). This population-based approach can be applied in the development of other sampling programs for specific ethnic and regional foods. Sampling plans have been developed for margarine, folate-fortified foods (e.g. flours, bread, and pasta), and a number of highly consumed mixed dishes (e.g. pizza and lasagna). |
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