Location: Nutrient Data Laboratory2017 Annual Report
1a. Objectives (from AD-416):
The mission of the Nutrient Data Laboratory is "To develop authoritative food composition databases and state of the art methods to acquire, evaluate, compile, and disseminate composition data on foods and dietary supplements available in the United States." The following three objectives and nine sub-objectives provide the infrastructure for completing planned research over the next five years and the guiding principles for accomplishing the research with a clear, scientific focus. Objective 1. Develop and expand the USDA-ARS food composition databases to represent the dynamics of the U.S. food supply, including increased use of commercially packaged foods, restaurant foods, school foods, and ethnic foods. Sub-Objective 1.A. Update the USDA National Nutrient Database for Standard Reference (SR) to represent the dynamics of the current U.S. food supply, including increased availability and variety of commercially packaged, restaurant, school, and ethnic foods. Sub-Objective 1.B. Expand and update existing food yield and nutrient retention factor tables to reflect current food preparation methods and food products. Sub-Objective 1.C. Provide nutrient composition data for use in the national survey, What We Eat In America (WWEIA), NHANES. Sub-Objective 1.D. Monitor sodium and related nutrients in commercially processed and restaurant foods in the U.S. food supply. Objective 2. Develop authoritative food composition databases for non-nutritive components that may promote health; examples include isothiocyanates and other sulfur-containing compounds. Expand existing databases, including flavonoids, to include more foods, variability estimates, and other information (cultivar, weather, growing conditions, etc.), which impact the nutrient values. Sub-Objective 2.A. Expand and update accurate representative values for a number of bioactive compounds in raw, processed, and prepared foods in different Special Interest Databases (SID). Sub-Objective 2.B. Develop a new Special Interest Database (SID) on the content of sulfur-containing bioactive compounds in selected foods, with special emphasis on variability and factors, e.g., cultivar, location, and growing conditions, which potentially could influence variability. Sub-Objective 2.C. Determine the effect of various preparation methods on the content of various bioactive compounds in selected foods. Objective 3. Identify, evaluate, and develop new methods for the acquisition, evaluation, compilation, and dissemination of food composition data from diverse sources through modernization of existing and development of new, robust information technology. Sub-Objective 3.A. Provide easy-to-use, web-based mechanisms for data submission. Sub-Objective 3.B. Enhance dissemination routines in the National Nutrient Databank System (NDBS) via automated methods to expand the types of data formats available on NDL’s web site.
1b. Approach (from AD-416):
Multiple methods for obtaining data will be used (e.g., nationwide product sampling and analysis, collaborations [food manufacturers, agricultural scientists], and publicly available information). The National Food and Nutrient Analysis Program (NFNAP) generates high-quality, analytical data for U.S. foods and includes a rigorous scientific process to develop nationally representative estimates of means and variability, under USDA analytical oversight. The 5 aims are: a) identify/prioritize foods/nutrients for analysis; b) devise/implement nationally based sampling plan(s); c) analyze food samples; and d) review, compile, and disseminate data. Beef data will be evaluated by nutrient and cut and compared across primals (chuck, brisket, etc.) and cooking methods. New meat data processed through the National Data Bank System (NDBS) will support calculations of cooking yield and retention factors (means, variances, and associated 90% or 95% confidence intervals). NDL will identify SR foods to be added or updated; this list will be provided to FSRG to prioritize foods needed in WWEIA (e.g., commercially processed and restaurant foods to replace home recipes), ensuring WWEIA adequately represents respondent reports. For important new foods, NFNAP sampling may include analytical data available for the next survey-SR dataset; standardized NDBS imputation procedures will be used to calculate missing values. NDL analyzed each Sentinel Food (SF; 2010-2013) for all nutrients; they will be reanalyzed every 4-8 years depending on budget and priority using the Principal Axis Factoring (Factor Analysis): consumption frequency in WWEIA, NHANES, 2009-10; potential for reduction (New York City’s National Salt Reduction Initiative targets); and history of change in the market. NDL will obtain and disseminate data for sulfur-containing bioactive compounds, detailing other factors (cultivars, location, weather, growing conditions) which impact concentration and focusing on genus Brassica, Allium; samples will be obtained through NFNAP and analyzed by ARS-Food Composition and Methods Development Laboratory (FCMDL) and sources and magnitudes of variability studied. Food selected for analysis for non-nutritive components will be based on flavonoid content, lack of analytical data, and potential for developing retention factors for related foods. The proanthcyanidin database will be expanded using formulations (linear regression techniques) developed for SR, to provide values to FSRG for foods reported in WWEIA-NHANES. Standardized, user-friendly databases will be released; collaboration with ILSI North America/Agricultural Technology Innovation Partnership (ATIP) Foundation and the food industry will be explored to expand the number of brand name foods. ATIP will develop/manage a new portal to facilitate submission of food manufacturers’ brand name nutrient data, strengthening NDL database for policy makers, researchers and the public. In parallel, NDL will work with other partners to identify infrastructure improvements to the NDBS.
3. Progress Report:
Objective 1A - Updating and expanding USDA-ARS food composition databases. Analytical studies: Thirty-seven Sentinel Foods (primary sodium contributors) were sampled and analyzed under NFNAP and 55 foods from fast-food and casual dining restaurants were sampled under a collaboration with FDA. Analytical studies were also initiated or completed on the nutrient content of processed eggs (American Egg Board collaboration), beef offal and other variety items (collaboration with Colorado State University and National Cattlemen’s Beef Association), dried fruits (collaborations with California Dried Plum Board and California Raisin Board), grass fed and grain fed retail lamb cuts (collaboration with Colorado State University and American Lamb Board), and beef cuts were evaluated and compared across primals and cooking methods (collaboration with Texas A&M, Texas Tech, and Colorado State University). This research supports on-pack nutrient labeling. In addition a study was conducted to determine the quantitative effect of different preparation parameters on the sodium content of cooked dry pasta, in collaboration with Virginia Tech. A manuscript is under preparation. Human milk: To replace dated nutrient composition in SR of human breast milk, an extensive literature review to evaluate the data quality and to identify knowledge gaps was completed. 28 papers (1980-2016) were found to contain original data on nutrients of human breast milk in the US and Canada. The results showed that there were no comprehensive studies focusing on nutrients in human milk; and current data do not provide sufficient information to update most nutrients of human milk. A manuscript is under-preparation and planned for FY2017 as well as an update to FooDS. Iodine research: The study funded by the Office of Dietary Supplements, underway, includes analyses of samples archived under the NFNAP as well as new samples. A pilot study showed iodine is stable under the storage conditions used for archive samples. A pilot study of pasta cooked in water with either iodized salt or no salt were analyzed to see if the iodine is picked up by the pasta from the water showed iodine is clearly absorbed by the pasta during cooking. These data and data from the FDA’s Total Diet Study are being prepared for inclusion in USDA FooDS for researchers. Gluten-free foods: A study evaluating 12 different types of gluten-free foods and comparing them to their gluten-containing counterparts was completed and presented at Experimental Biology. Added Sugar: NDL identified 29 top sugar contributing foods, which represent over one-third of the total sugar consumed in the U.S. Current sugar levels in commercially processed foods in the U.S are high and comprised mainly of mono and disaccharides. This study provides baseline values of total and individual sugars in commercially processed foods which are top sugar contributors, for use in assessing changes as manufacturers reformulate foods in the future in support of efforts to monitor sugar content and consumption. Objective 1C - Expanding nutrient composition data for Survey. New and updated data from the analytical studies listed above will be made available to FSRG as part of FooDS to determine nutrient intakes of survey respondents in WWEIA. Objective 1D - Sodium monitoring. As part of an interagency agreement with the CDC, 125 highly consumed Sentinel Foods were tracked by labels and 31 Sentinel Foods were chemically analyzed to assess changes in the content of sodium and other nutrients. In addition, NDL collaborated with FDA to sample and analyze 55 restaurant foods and their components. NDL updated the Sentinel Food Label Monitoring database with 2016 label nutrient data for Sentinel Foods for major national and store brands (obtained from manufacturers, restaurant chains, through websites or labels). Also completed was a post-hoc analysis using data obtained from the sodium monitoring project, comparing the label nutrients of Sentinel Foods to analytical values for total and saturated fat, sugar and sodium (recommended for reduced consumption in the 2015-2020 Dietary Guidelines for Americans due to their role in chronic, non-communicable diseases). The results showed that while the majority of foods are compliant with labeling regulations, inaccuracy is not uncommon and substantial variability exists in the discrepancy between label and laboratory values. NDL also has initiated collaboration with Food and Nutrition Services, USDA and CDC to improve the analytical basis of foods consumed by children at schools as part of the school breakfast and lunch program. Objective 2A – Update Special Interest Databases for bioactive compounds. Different classes of flavonoid compounds were analyzed in cranberry and raspberry products. The information was used to add or update information in the USDA Flavonoid Databases. One manuscript is under writing with the collaborators. Additional data are being acquired on an ongoing basis through literature search and working with collaborators or industry partners (e.g. trade groups of different berries) for future updates. Objective 2B – Evaluate and process data for glucosinolates for manuscript and database. Extensive efforts were made to obtain and analyze the data to develop a new Special Interest Database on dietary glucosinolates. The data analyses suggested though only cruciferous vegetables contain glucosinolates, the number of compounds and their concentrations varied considerably between different vegetables and within the same vegetables, probably due to the different sample preparation and quantification methods. One manuscript on the development of glucosinolates database is under preparation. Objective 2C – Analyze the effects of various processing/preparation on the retention of certain bioactive components. Samples were prepared and analyzed in raw and cooked forms using standardized protocols for selected flavonoids and glucosinolates to determine retention factors of these compounds after preparation. The data will provide more accurate information in calculating dietary intake of these bioactive compounds, and to help interpreting their health benefits from epidemiological studies. The data have been processed and the manuscript is under preparation. Objective 3A - Information technology modernization for web-based data submission: The USDA Branded Food Products Database (BFPDB) containing approximately 68,000 food items was launched in September 2016 at the Global Open Data for Agriculture and Nutrition Summit. This release is the result of a Public-Private Partnership between 1) Agricultural Research Service (ARS), USDA; 2) International Life Sciences Institute (ILSI) North America; 3) GS1 US; 4) 1WorldSync; and 5) Label Insight. Additionally, development of an independent data portal to receive NDL analytical data and other data is in progress (McWest Corporation contract), automating the formatting and importing of these data into the USDA FooDS, the comprehensive food composition database which brings all BHNRC food composition databases into one master database system. Hosted at the National Agricultural Library, USDA FooDS is being designed to allow interconnectivity among the databases, links to external, related databases, frequent releases and transparency, and will improve provider and user functionality. Objective 3B - Enhanced NDBS data dissemination systems. The existing NDBS will be replaced by the new USDA FooDS portal and processing system, which will update and expand upon the functionality of the current system.
1. Improving USDA food composition databases. 170 new foods and about 7,200 nutrients were added or updated, based on data from analytical studies, labels and other sources. New and updated data were included for almonds, baby foods, breakfast cereals, Greek yogurts, grass-fed and grain-fed lamb, ground pork, olives, plantains, processed raspberry products, margarine, selected fruit juices, pulses and fishes, almonds, sunflower seeds and vegetable smoothies. These new foods and other updates will be made available as part of the ARS FooDS, expected in fall 2017. The USDA Branded Food Products Database was expanded in January 2017 and again in June 2017—for a total of over 205,000 foods. Future updates will happen more frequently. This permits USDA databases to represent the dynamics of the current U.S. food supply, especially increased availability and variety of commercially packaged foods. Furthermore, a retail lamb nutrient dataset to support retailers with on-pack nutrient labeling was disseminated on the NDL website.
2. Sodium monitoring. ARS researchers at Beltsville, Maryland, compared concentrations of sodium and related nutrients (potassium, total dietary fiber, total and saturated fat, and total sugar) in popular sodium-contributing, commercially packaged foods by brand type (national or private-label brand). Concentrations of these nutrients did not differ systematically between private-label and national brands, suggesting that brand type is not a consideration for nutritional quality of foods in the United States. The study data provide public health officials with baseline nutrient content by brand type to help focus US sodium-reduction efforts. In addition, ARS transferred to the Center for Disease Control (CDC) an updated label monitoring database (2013-2016) of nutrient data from manufacturers/restaurant chains. Furthermore, a paper on sodium intakes and sources in school age children was published in the Journal of Academy of Nutrition and Dietetics.
3. Gluten-free foods. These foods are highly popular in the U.S. and are promoted as healthful choices. ARS researchers evaluated 12 different types of gluten-free foods and compared them to their gluten-containing counterparts. They found that only whole grain pasta met the Food and Drug Administration (FDA) criteria for ‘healthy’. Additionally, they found gluten-free foods to be consistently lower in mean calcium, folate, iron, niacin and protein concentrations per 100 grams than their wheat-containing counterparts. The results suggest that while gluten-free products serve as grain-based alternatives for the gluten-intolerant sub-population, they may not be a ‘healthy’ choice as per FDA guidelines and may not be superior to similar gluten-containing foods for specific nutrients.
4. Glucosinolates. Glucosinolates are a group of important sulfur-containing compounds found in cruciferous vegetables, that may have chemo-protective effect. ARS researchers at Beltsville, Maryland, investigated the 3 key challenges of developing a valid database of glucosinolates – sample preparation procedures, analytical methods and what to measure and present in a database. The authors discussed these unique challenges in a paper published in the Journal of Food Composition and Analysis.
5. Vitamin K. Vitamin K exists in various forms. Vitamin K2 form (menquinones) has not been well characterized in foods. ARS researchers, in collaboration with Tufts University researchers, quantified the 2 forms of vitamin K in several dairy products and mixed dishes. They found that dairy products contain substantial amounts of vitamin K2, that is proportional to the fat content of the products. In addition, they characterized vitamin K per serving of various mixed dishes consumed in the U.S. and found that mixed dishes, even those that do not contain vitamin-K rich vegetables, can contain substantial amounts of vitamin K from plant oils and animal products.
Ahuja, J., Pehrsson, P., Cogswell, M.E. 2017. A Comparison of concentrations of sodium and related nutrients (potassium, total dietary fiber, total and saturated fat, and total sugar) in private-label and national brands of popular, sodium-contributing, commercially pack. Journal of the Academy of Nutrition and Dietetics. 117(5):770–777.e17.
Maalouf, J., Pehrsson, P.R., Cogswell, M.E., Bates, M., Yuan, K., Scanlon, K.S., Gunn, J.P., Merritt, R.K. 2017. Sodium, sugar and fat content of complimentary infant and toddler foods sold in the United States, 2015. American Journal of Clinical Nutrition. doi:10.3945/ajcn.116.142653.
Cogswell, M.E., Patel, S.M., Yuan, K., Gillespie, C., Juan, W., Curtis, C.J., Vigneault, M., Clapp, J., Roach, P., Moshfegh, A., Ahuja, J.K., Pehrsson, P.R., Brookmire, L., Merritt, R. 2017. Modeled changes in U.S. sodium intake from reducing sodium concentrations of commercially processed and prepared foods to meet voluntary standards established in North America: NHANES. American Journal of Clinical Nutrition. doi:10.3945/ajcn.116.145623.
Wu, X., Sun, J., Haytowitz, D.B., Harnly, J.M., Chen, P., Pehrsson, P.R. 2017. Challenges of developing a valid Dietary Glucosinolate database. Journal of Food Composition and Analysis. HTTPS://DOI: 10.1016/j.jfca.2017.07.014.
Pehrsson, P.R., Haytowitz, D.B., Mckillop, K.A., Moore, G.G., Finley, J.W., Fukagawa, N.K., Wu, X. 2017. USDA Branded Food Products Database, Release 2. USDA National Nutrient Database for Standard Reference. Available: https://ndb.nal.usda.gov/ndb/.
Fu, X., Harshman, S.G., Shen, X., Haytowitz, D.B., Karl, P.J., Wolfe, S.L., Booth, S.L. 2017. Multiple Vitamin K forms exist in dairy foods. Current Developments in Nutrition. doi:10.3945/cdn.117.000638.
Tidball, M.M., Exler, J., Somanchi, M., Williams, J.R., Kraft, C., Curtis, P., Tidball, K.G. 2017. Toward increasing the visibility of wild-caught foods in the US: Brook Trout Nutritional Analysis for Inclusion into the USDA National Nutrient Database for Standard Reference. Journal of Food Composition and Analysis. doi: 10/1016/j.jfca.2017.03.004
Finnan, E.G., Harshman, S.G., Haytowitz, D.B., Booth, S.L. 2017. Mixed dishes are an unexpected source of dietary vitamin K. Journal of Food Composition and Analysis. 64:127-131. https://doi.org/10.1016/j.jfca.2017.04.002.
Hui, C., Xu, N., Zhao, W., Su, J., Liang, M., Xie, Z., Wu, X., Li, Q. 2017. (-) Epicatechin regulates blood lipids and attenuates hepatic steatosis in rats fed high fat diet. Molecular Nutrition and Food Research. doi: 10.1002/mnfr.201700303.
Harshman, S.G., Finnan, E.G., Bargar, K.J., Bailey, R.L., Haytowitz, D.B., Gilhooly, C.H., Booth, S.L. 2017. Mixed dishes are a top contributor to phylloquinone intake in U.S. adults: Data from the 2011-2012 NHANES. Journal of Nutrition. doi: 10.3945/jn.117.248179.