Source: AGRICULTURAL RESEARCH SERVICE submitted to
USDA NATIONAL NUTRIENT DATABANK FOR FOOD COMPOSITION
Sponsoring Institution
Agricultural Research Service/USDA
Project Status
TERMINATED
Funding Source
Reporting Frequency
Annual
Accession No.
0426560
Grant No.
(N/A)
Project No.
8040-52000-064-00D
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Feb 20, 2014
Project End Date
Feb 19, 2019
Grant Year
(N/A)
Project Director
VACANT
Recipient Organization
AGRICULTURAL RESEARCH SERVICE
RM 331, BLDG 003, BARC-W
BELTSVILLE,MD 20705-2351
Performing Department
(N/A)
Non Technical Summary
(N/A)
Animal Health Component
(N/A)
Research Effort Categories
Basic
0%
Applied
75%
Developmental
25%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
70150101010100%
Knowledge Area
701 - Nutrient Composition of Food;

Subject Of Investigation
5010 - Food;

Field Of Science
1010 - Nutrition and metabolism;
Goals / Objectives
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.
Project Methods
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.

Progress 02/20/14 to 02/19/19

Outputs
Progress Report 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. 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. This is the final report for 8040-52000-064-00D entitled ⿿USDA National Nutrient Databank for Food Composition⿝. Over the past 5 years, nutrient data have been expanded and updated for ~300 food types and ~500 individual (brand name) foods. This includes 125 popular commercially processed and restaurant foods/components (detailed in Objective 1D), over 100 restaurant foods (fast-food and casual dining), 4 fat levels of cows⿿ milk, raw and cooked retail ground beef from 3 to 30% fat, a diverse number of domestic and wild meats, fowl and organs; the latter are not yet published. Many of these projects were done in collaborations with other agencies e.g., CDC and FDA. An assessment of the current knowledge of nutrient data on human milk composition was completed, and efforts initiated to set up collaboration for its improvement. The USDA Nutrient Data Laboratory (NDL) released 3 updated versions of the USDA National Nutrient Database for Standard Reference (SR 27, SR 28, and SR Legacy). A new database, the USDA Global Branded Food Products Database (BFPD) was released and expanded several times and now contains ~250,000 foods. An iodine study was funded by the Office of Dietary Supplements that examined over 200 foods from NDL⿿s archived samples under the National Food and Nutrient Analysis Program (NFNAP) and also included newly sampled table salt, retail cow⿿s milk (four fat levels), and industrial frozen/dried egg products. These data were merged with FDA⿿s Total Diet Study to provide a Special Interest Database (N~400 foods) for inclusion into FDC. Both data sets are being prepared for release later in 2019. Phase 2 of this study will map the new iodine data to foods which are reported in the What We Eat In America national survey (WWEIA), NHANES. This project is underway and includes analysis of iodine in select dietary supplements; it will be released in manuscript format next year, 2020. In addition, NDL developed an expanded and updated table of cooking yields data for over 175 meat and poultry products (released September 2014). A brief summary of specific research projects: Nutrient composition data for use in What We Eat In America (WWEIA), NHANES: Over the past 5 years, nutrient data were provided for WWEIA, NHANES surveys (2013-2014 and 2015-2016), through a special dataset or releases of SR. These included 66 nutrients for ~3,500 foods. Many new foods in the marketplace were added, including several gluten-free products, milk substitutes, sauces and condiments, Greek yogurt, breakfast cereals, low-sodium meat products, whole grain pastas and baked products, infant and baby foods, beverages, school lunch pizzas and chicken products, fast-food sandwiches, and new beef cuts. Nutrient profiles were updated for several commonly consumed foods and many popular sodium-contributing foods. Sodium monitoring: In FY 2019, sodium values for selected popular commercially processed and restaurant foods (Sentinel Foods) were compared to baseline levels (2010-2013), using labels and laboratory values, providing an assessment of changes in the marketplace. Over the past 5 years, data for sodium, potassium, energy, total fat, saturated fat, total dietary fiber, and total sugar for 125 Sentinel Foods were finalized and released, providing baseline estimates to use in assessing changes as foods are reformulated for sodium reduction. Post-hoc analyses of these data were completed and published/presented, comparing similar restaurant and packaged foods, private-label and national brands, and label and laboratory values for the same products, providing insights into the food environment, improving databases, and helping public health officials strategize efforts needed to monitor sodium changes. Sentinel Foods were tracked for changes in label sodium values in 2015 and 2017 (~300 labels each), and 43 (1,181 samples); Sentinel Foods were resampled and analyzed to assess changes in sodium and related nutrient content. Update Special Interest Databases for bioactive compounds: In FY 2019, data for isoflavones and their metabolites were obtained in egg samples through collaboration with the American Egg Board. The data suggested that isoflavones and their metabolites existed at significant concentrations in processed eggs in the U.S. Considering consumption levels, eggs and egg products could be an important source of isoflavone intake in the U.S. A new high-performance liquid chromatography (HPLC) method to accurately quantify cranberry A-type proanthocyanidins was further improved and validated with additional mass spectrometry characterization. Over the past 5 years, different classes of flavonoid compounds were analyzed in a number of different foods by working with Food Composition and Methods Development Laboratory (FCMDL), outside collaborators or industry partners. The data either filled knowledge gaps or provided more accurate and representative compositional information on these food products. The information was used to add or update information in the three USDA Flavonoid Databases. The influence of specific bioactive compounds, such as epicatechin in tea and fatty acids in royal jelly, were studied using animal and cell culture models in collaborative studies. Inter-laboratory method evaluation for measuring vitamin D and 25(OH)D in animal-based foods and dietary supplements: NDL addressed knowledge gaps for reliable estimation of vitamin D intake [i.e., D2+D3+25(OH)D] and explored how this information impacted decisions about supplementation, fortification or other interventions. Five international and U.S. laboratories participated in the study with the Office of Dietary Supplements, NIH. This pilot provided methods information and data for 6 quality control materials in two separate trials, improving analytical methods. Results were published in the Journal of Agricultural and Food Chemistry, showing that vitamin D and 25(OH)D can be accurately determined in animal-based foods at natural levels and in supplements. The study provided data to the National Institute of Standards and Technology (NIST) for certifying values for vitamin D and 25(OH)D in three of their standard reference materials. This reference materials allow other labs to produce scientifically sound data. Evaluate and process data for glucosinolates (GLS) for manuscript and database: In FY 19, continuous efforts were made to obtain and analyze data on dietary glucosinolates. Additional literature data (until the end of 2018) have been obtained. One hundred sixty four research papers were found containing the original data, of which, 32 were conducted in the U. S. and 132 were carried out in 29 other countries. The current dataset included 17 aliphatic, 4 aromatic and 4 indole GLSs in 20 different foods. The profile and content of glucosinolates were found to be greatly affected by the plant species/cultivars and environmental factors (e.g. soil condition, climate, irrigation, fertilizer, etc.). Over the last 5 years, extensive efforts were made to obtain and analyze the data to develop a new Special Interest Database on dietary glucosinolates; the majority of the data were from peer-reviewed publications. Analytical data on select cruciferous vegetables were also obtained by working with FCMDL. FCMDL-NDL studies compared different sample preparation and analytical procedures to quantify glucosinolates in vegetables, then evaluated the quality and develop inclusive and exclusive criteria of the literature data. Data provide a tool to estimate dietary intake of GLSs in the U.S. and other countries for assessing their possible roles in promoting human health. Analyze the effects of various processing/preparation on the retention of certain bioactive components: In FY2019, manuscript describing the effects of cooking on broccoli flavonoids and proposing different retention factors was published. Over the last five years, retention of bioactive compounds after domestic cooking were assessed in a number of commonly consumed vegetables, including broccoli, collard greens, kale, onion, and red cabbage in collaboration with FCMDL. Different subgroups of flavonoids (e.g. flavonols, anthocyanins) and glucosinolates were analyzed in raw and cooked forms. Apparent retention (AR) and true retention (TR) were compared and TR was proposed to be used in future studies. 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. Provide easy-to-use, web-based mechanisms for data submission: The Global Branded Food Products Database (BFPD) was expanded to ~250,000 food records with submitters (GS1, Label Insight, ILSI NA, JIFSAN, OneWorldSync) using improved formats for import of data with quality control checks for incoming data. Enhance dissemination routines in the National Nutrient Databank System, FoodData Central: FDC was launched, completing the multi-year initiative to update USDA food composition databases, automate functionality and information transparency, and provide an integrated platform for all users. FDC houses the Standard Reference Legacy, FNDDS, new analytical data on Foundation Foods with drill-down capacity and metadata, the BFPD, and links to the NDL⿿s Dietary Supplement Ingredient Database and the Dietary Supplement Label Database. Accomplishments 01 Improving USDA food composition databases. USDA food composition databases are used by a diverse user community to make policy decisions, investigate the impact of diet on health, develop new foods, advise patients on improving their diet, and address the general need for more information on what is in the food we eat. An integrated data system, FoodData Central, was made public. It now provides all USDA food composition databases in a single location, plus expanded nutrient information and links to Special Interest Databases and related agricultural and experimental research data. The USDA databases include SR Legacy, Food and Nutrient Database for Dietary Studies (FNDDS), the Global Branded Food Products Database, and Foundation Foods. Presentations and demos have been conducted to the outside users. A manuscript on the NIH workshop called ⿿Human Milk Composition ⿿ Biological, Environmental, Nutritional, and Methodological Considerations⿝ was published. 02 Sodium monitoring. Too much sodium in the diet can increase blood pressure and the risk of heart disease and stroke. Most Americans consume more sodium than recommended for a healthy diet, and most of the sodium in the diet comes from commercially processed and restaurant foods. ARS researchers at Beltsville, Maryland, collaborated with CDC and FDA to track sodium levels in 125 of these foods. Our results show that majority of the foods have not changed. Only 1/3 of the products tracked show changes, with twice as many reductions as increases in sodium content of the foods. A manuscript assessing changes in the sodium content of selected popular commercially processed and restaurant foods was submitted. 03 Dietary bioactive compounds. Dietary bioactive compounds are of great interest for researchers and consumers due to their health benefits. The USDA Nutrient Data Laboratory (NDL) in Beltsville, Maryland, developed three special interest databases on dietary flavonoids to meet the demands from federal agencies and the research societies. Over the last five years, NDL has acquired analytical data of various subgroups of flavonoids in a number of plant foods through working with FCMDL and outside collaborators. The obtained data were evaluated, processed and were used to update three special interest databases on dietary flavonoids to meet the demands of federal agencies and the research societies. Several research papers were published.

Impacts
(N/A)

Publications

  • Wu, X., Wang, T.T., Prior, R.L., Pehrsson, P.R. 2018. Preventative effects on atherosclerosis by berries - the case of blueberries. Journal of Agricultural and Food Chemistry.
  • Ahuja, J.K., Li, Y., Nickle, M.S., Haytowitz, D.B., Roseland, J., Nguyen, Q., Khan, M., Wu, X., Somanchi, M., Williams, J.R., Pehrsson, P.R., Cogswell, M. 2018. Comparison of label and laboratory sodium values in popular sodium-contributing foods in the United States. Journal of the Academy of Nutrition and Dietetics.
  • Qingshuang, C., Shanming, J., Yue, S., Linsheng, Y., Wu, X., Zhongwen, X. 2018. 10-Hydroxy-trans-2-decenoic acid attenuates angiotensin II-induced inflammatory responses in rat vascular smooth muscle cells. Journal of Functional Foods.


Progress 10/01/17 to 09/30/18

Outputs
Progress Report 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. 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. Objective 1A - Updating and expanding USDA-ARS food composition databases: Analytical studies: Fifty-one foods from fast-food and casual dining restaurants were sampled and analyzed under NFNAP through collaboration with FDA. These included mainly components of menu items such as burger buns, bacon, pizza crust, etc. Analytical studies were completed on the nutrient content of six processed egg product types (American Egg Board collaboration). Analysis of four types of milk (whole, 2%, 1%, and fat- free) with samples from 24 retail locations was completed to evaluate nutrient content and variability (in collaboration with the National Dairy Council). A paper on the nutrient composition of different forms of processed raspberries (frozen, juice concentrate and puree), analyzed in collaboration with National Processed Raspberry Association is under preparation. Human milk: The state of current knowledge, research needs and challenges for obtaining good quality human milk composition data were reviewed and summarized. A webinar and a 1-day NIH workshop called �Human Milk Composition � Biological, Environmental, Nutritional, and Methodological Considerations� was organized jointly with the Office of Disease Prevention and Health Promotion in fall 2017. The objective was to gather information on data needs and methodological challenges, and to develop visions for a research program to develop a human milk composition repository. Efforts are underway to initiate activities for a comprehensive research plan, including prioritizing nutrients, forming working groups, etc. A manuscript on the workshop is under preparation. Iodine research: In this study funded by the Office of Dietary Supplements, approximately 200 foods from NDL�s archived samples under the NFNAP as well as new samples such as table salt, retail milk (all fat levels), and industrial frozen and dried egg products, were analyzed for their iodine contents. These data and data from the FDA�s Total Diet Study are being prepared for inclusion in USDA Food Data Central for researchers� use. In addition, Phase 2 of this study is being planned which will coordinate mapping of new iodine data to foods formerly in SR which are used in the What We Eat In America (WWEIA) national survey (NHANES). This research includes analysis of iodine in select dietary supplements. Objective 1C - Expanding nutrient composition data for Survey: New and updated data from the analytical studies and from sodium monitoring were made available to FSRG as part of SR Legacy database to determine nutrient intakes of survey respondents in WWEIA. Objective 1D - Sodium monitoring: As part of an interagency agreement with the Centers for Disease Control and Prevention (CDC), NDL finalized nutrient content of ~300 highly consumed sodium-contributing foods monitored using nutrient data obtained through websites or labels. Nutrient data from chemical analysis of 40 Sentinel Foods and label reviews were used to assess changes in the content of sodium and other nutrients. In addition, NDL collaborated with FDA to sample and analyze 51 restaurant foods and their components. Objective 2A � Update Special Interest Databases for bioactive compounds: Flavonoid compounds in different cranberry and raspberry products were further processed and verified. The data either filled knowledge gaps or provided more accurate and representative information on these products. Data were added/updated in two Special Interest Databases � Flavonoids and Proanthocyanidin Databases, which were released as new versions on March 2018. Isoflavones and their metabolites were analyzed in selected egg samples through collaboration with the American Egg Board, and data will support a more accurate assessment of isoflavone intake in the U.S. A new HPLC method to accurately quantify A- type proanthocyanidins in cranberries and cranberry products was developed by working with collaborators, and the manuscript is under revision for resubmission. Additional research on the functions of other bioactive compounds, such as fatty acids in royal jelly, was conducted through collaborations. Objective 2B � Evaluate and process data for glucosinolates for manuscript and database: Continuous efforts were made to obtain and analyze data to develop a new Special Interest Database on dietary glucosinolates. Additional literature data (published 2016-2018) have been obtained. All available data were processed and evaluated. The glucosinolate contents in foods collected in the U.S. and other countries, as well as in edible plants vs. inedible plants were analyzed and compared. Database development is in the final stage. One manuscript on the development of the glucosinolates database is under preparation. Objective 2C � Analyze the effects of various processing/preparation on the retention of certain bioactive components: Additional data were obtained to evaluate the cooking effects on flavonoids and glucosinolates to determine retention factors of these compounds. Different ways to calculate retention factors were evaluated. The data will provide more accurate information in calculating dietary intakes of these bioactive compounds, and will help interpret their health benefits from epidemiological studies. One manuscript on the cooking effects on broccoli flavonoids was submitted for approval for publication. Objective 3A - Information technology modernization for web-based data submission: Procedures for submitting brand-name data have been developed at the National Agricultural Library and the Joint Institute for Food Safety and Applied Nutrition, University of Maryland. The USDA Branded Food Products Database (BFPDB) now contains over 250,000 food items and is updated and expanded continuously. This database 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; 5) Label Insight; and 6) the Joint Institute for Food Safety and Applied Nutrition, University of Maryland. Additionally, development of an independent data portal to receive NDL analytical data is largely complete (McWest Corporation contract), automating the formatting and importing of analytical data into the USDA Food Data Central. Work on a portal for handling data from other sources is underway. Objective 3B - Enhanced NDBS data dissemination systems: The existing NDBS will be replaced by the internal �NDL� side of the new USDA Food Data Central portal and processing system, which will update and expand upon the functionality of the current system. This system integrates with a new website for the public-facing USDA Food Data Central, currently under development. The new website allows frequent releases and transparency, interconnectivity among the databases, links to external, related databases, and will improve provider and user functionality. Accomplishments 01 Improving USDA food composition databases. USDA food composition databases are used by a diverse user community to make policy decisions, investigate the impact of diet on health, develop new foods, advise patients on improving their diet, and address the general need for more information on what is in the food we eat. The USDA Branded Food Products Database was expanded several times within the last year and now contains approximately 240,000 foods, improving coverage of the foods we eat. The USDA National Nutrient Database for Standard Reference � Legacy was released in April 2018. This release included data updates generated as part of the sodium monitoring project and excluded food items that duplicated those in the USDA Branded Food Products Database. 02 Sodium monitoring. Too much sodium in the diet can increase blood pressure and the risk of heart disease and stroke. Most Americans consume more sodium than recommended for a healthy diet, and most of the sodium in the diet comes from commercially processed and restaurant foods. ARS researchers at Beltsville, Maryland, collaborated with CDC and FDA to track sodium levels in these foods. The researchers updated the sodium estimates with current nutrient data and reported on changes in sodium content of top sodium-contributing foods from baseline (2010- 2013), at the National Nutrient Databank conference. Furthermore, in a post-hoc analysis, they published a comparison of label and laboratory sodium values in popular sodium-contributing foods in the United States. The majority of the label to laboratory values agreed, although there were some differences by brand type (national, private-label) and source (store, restaurant (fast-food, sit-down). CDC and FDA will use the information to study the appropriateness of their monitoring methods, the impact of current public health efforts, and to plan new strategies to lower the amount of sodium that Americans get from food. 03 Dietary bioactive compounds. Dietary bioactive compounds are of great interest for researchers and consumers due to their health benefits. The USDA Nutrition Data Laboratory in Beltsville, Maryland, developed three special interest databases on dietary flavonoids to meet the demands from federal agencies and the research societies. The databases require constant updating for more complete, accurate and current data. Analytical data of flavonoid compounds (anthocyanins, proanthocyanidins and other flavonoids) in certain berries and berry products were added to two Special Interest Databases, which were released as new versions on March 2018.

Impacts
(N/A)

Publications

  • Phillips, K.M., Tarrago-Trani, M., Rasor, A., Mcginty, R.M., Haytowitz, D. B., Pehrsson, P.R. 2018. Season plays a role in variability in vitamin C content of fresh fruits and vegetables in a local retail market. Journal of the Science of Food and Agriculture.
  • Roseland, J.M., Nguyen, Q.V., Douglass, L.W., Patterson, K.Y., Howe, J.C., Williams, J.R., Thompson, L.D., Brooks, J., Woerner, D.R., Engle, T.E., Savell, J.W., Gehring, K.B., Cifelli, A.M., Mcneill, S.H. 2017. Fatty acid, cholesterol, vitamin, and mineral content of cooked beef cuts from a national study. Journal of Food Composition and Analysis.
  • Ershow, A., Skeaff, Merkel, J., Pehrsson, P.R. 2018. Development of databases with iodine in foods and dietary supplements. Nutrients.
  • Saldanha, L.G., Dwyer, J.T., Andrews, K.W., Brown, L.L., Costello, R.B., Ershow, A.G., Gusev, P.A., Hardy, C.J., Pehrsson, P.R. 2017. Is nutrient content and other label information for prescription prenatal supplements different from nonprescription products? Journal of the Academy of Nutrition and Dietetics.
  • Roseland, J., Phillips, K.M., Patterson, K.Y., Pehrsson, P.R., Taylor, C.L. 2017. Vitamin D in foods: an evolution of knowledge. In: Feldman, D., Pike, J.W., Bouillion, R., Giovannucci, E. Vitamin D (4th Edition). New York, NY: Elsevier. p. 41-77.


Progress 10/01/16 to 09/30/17

Outputs
Progress Report 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. 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. 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. Accomplishments 01 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. 02 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. 03 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. 04 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. 05 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.

Impacts
(N/A)

Publications

  • 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.
  • Haytowitz, D.B., Pehrsson, P.R. 2016. USDA's National Food and Nutrient Analysis Program (NFNAP) produces high-quality data for USDA Food Composition Databases: Two decades of collaboration. Food Chemistry. doi: 10.1016/j.foodchem.2016.11.082.
  • 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. 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:
  • 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. 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.


Progress 10/01/15 to 09/30/16

Outputs
Progress Report 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. 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. Objective 1A, Expanding food composition databases (SR): To focus efforts on the database modernization project, an interim release was made, instead of a full release of SR. The interim release included updated and new data for baby foods and 8 foods re-sampled, as part of the sodium monitoring project. Sixty-eight foods were sampled and analyzed under NFNAP; for each food, up to 3 brand-name items were purchased. These included: rice (wild, basmati and jasmine); new popular juices; infant/toddler foods; sausages/ processed meats; kale and grape tomatoes; coffee beverages (Starbucks, Dunkin Donuts); several Red Lobster menu items; hummus, sunflower seeds and dry-roasted almonds. NDL partnered with the USA Pea & Lentil Council to obtain samples of chickpeas, lentils and dried peas for analysis and with National Frozen Raspberry Association for frozen raspberry products; data will be released in SR 29. Objective 1C, Expanding nutrient composition data for Survey: New and updated data were provided to FSRG to determine nutrient intakes of survey respondents in WWEIA. Objective 1D, Sodium monitoring: As part of the an interagency with the CDC, monitoring plan, 125 popular, sodium contributing commercially processed/restaurant foods (Sentinel Foods) were tracked to assess the changes in the sodium content of the U.S. food supply. Related nutrients (total sugar, potassium, total and saturated fat, total dietary fiber) that may change as food manufacturers reformulate were also monitored. NDL developed a new monitoring database (2013-2015) of label nutrient data for Sentinel Foods for major national and store brands (obtained from manufacturers, restaurant chains, through websites or labels), to be updated yearly. Nine Sentinel Foods were sampled in FY15, as were 27 new sodium-contributing foods. Changes were reviewed and will be presented at the annual American Public Health Conference (October 2016). NDL conducted several post-hoc analysis using data obtained from the sodium monitoring project e.g., comparing sodium, potassium, total and saturated fat, total dietary fiber and total sugar content by brand type (national versus private brands); results showed no systematic differences. This is the first comparisons of nutrient content in the same foods of different brand types in the U.S.; therefore, private-label brand products due to their lower costs, have the potential to favorably influence intakes of nutrients. Results were submitted to the Journal of Academy of Nutrition and Dietetics. NDL also studied differences by census region in total fat, saturated fat, and sodium contents as represented by ~1,000 labels in about 75 foods (Northeast, West, Midwest, and South). No significant differences were observed, suggesting lack of regional variability among labels for similar foods in the US. NDL conducted a comparative analysis of fast-food sandwiches and burgers from major fast-food outlets i.e., Subway, McDonald's, Burger King, Wendy's, and Chick-Fil-A, which were sampled nationwide and analyzed. Large variations in sodium levels by brand and type were found, suggesting the importance of including brand-specific information for these foods for dietary assessment and national nutrition monitoring. A similar review was conducted for selected commercial baby and toddler foods. These analyses provide several insights for the ARS food composition databases, including the need to monitor private-label brands and brand specific information for commercial foods where nutrient differences exist. Results from the latter three studies were presented at the National Nutrient Databank Conference, May 2016. Finally, NDL collaborated with CDC on 2 manuscripts using dietary intake data from the WWEIA, NHANES to: 1) identify major food sources and eating occasions contributing to sodium intake among US school-aged children; and 2) model predicted changes in US daily average sodium intake and the prevalence of excess sodium intake using the New York City�s and Health Canada standards for commercially-processed and prepared foods. The manuscripts were submitted to the Journal of Academy of Nutrition and Dietetics and American Journal of Clinical Nutrition, respectively. Objective 2A, Special Interest Databases for bioactive compounds: Updates were made to the USDA Database for the Flavonoid Content of Selected Foods and the USDA Database for the Isoflavone Content of Selected Foods. These resulted in an update to the USDA's Expanded Flavonoid Database for the Assessment of Dietary Intakes. Five international and U.S. laboratories participated in the NDL-led inter-laboratory method evaluation for measuring vitamin D and 25(OH)D in animal-based foods and dietary supplements. This pilot study provided methods information and data for six materials in two separate trials. Objective 2B, Special Interest Database for sulfur containing compounds: Data for glucosinolates from 170 research articles published in peer- reviewed scientific journals were evaluated for data quality. Pilot studies were conducted by working with FCMDL to compare different sample preparation and analytical procedures to quantify glucosinolates in vegetables. Additional data were obtained by collaborating with FCMDL on selected vegetables. Objective 2C, Effect of processing/preparation on bioactive content: Samples of broccoli, collard greens, kale, onion, and red cabbage were purchased from 3 different supermarket chains. FCMDL prepared (using NDL protocols) and analyzed the samples in raw and cooked forms (boiled, steamed, microwaved) for selected flavonoids and glucosinolates to determine retention factors of these compounds after preparation. Preliminary results for broccoli and red cabbage suggested higher apparent retention of flavonoids in broccoli by microwave cooking than steaming or boiling, while anthocyanidin cyanidins in red cabbage were retained better by steaming than boiling. Glucosinolates are generally well retained after cooking due to deactivation of enzyme myrosinase. Retention factors obtained from these studies would be used to determine the flavonoid contents of cooked multi-ingredient foods through recipe calculations, when analytical values are not available. As many vegetables are consumed as cooked forms, 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. Objective 3A, Information technology modernization for web-based data submission: Food industry data were initially received (2014) through the Public-Private Partnership utilizing an industry-standard format; 244 food products were demonstrated to industry partners. In May 2016, data for 354 foods were publically released after data accuracy issues were addressed as the first installment of the USDA Branded Food Products Database (BFPDB) and incorporated into the SR online search program as a separate, connected database. In summer 2016, data for over 75,000 foods were received from industry partners through a University of Maryland data pipeline (developed in the past year) and are being evaluated for a September 2016 release. These data will include GS1 or Label Insights data, per a USDA-ILSI NA (International Life Sciences Institute North America) contract. Data exchange and ongoing discussions between USDA and ILSI NA have provided information enabling NDL to better design modifications to the NDL�s database management system. Additionally, development of an independent NDL data portal to receive analytical data received through NFNAP and other external sources is underway (McWest Corporation contract). This portal will automate formatting and importing of these data into the ARS FooDS under development, which will then be available to the public through the search program hosted at National Agricultural Library. Initial work has begun on ARS FooDS, the comprehensive food composition database which brings all BHNRC databases (SR, special interest database, FNDDS, chemometric data from FCMDL, etc.) into one master database system. This system will allow interconnectivity among the databases, links to external, related databases, and improved provider and user functionality. Objective 3B, Enhanced NDBS data dissemination systems: NDL implemented NDBS enhancements e.g., software programs to reformat data from external sources (as part of the data portal), data processing bypasses, and an automated linear programming tool/ Formulations Program (FP) for generating complete nutrient profiles for multi-ingredient, commercially processed foods. This tool uses nutrient and ingredient information from food labels to develop nutrient values where data are not available. The McWest Corporation is programming a new FP using industry standard software packages and project management practices. Versions using Agile process were delivered and were tested by NDL. An validation study of FP (in progress) determines how effectively the FP calculates with precision (to analytical value) a calculated nutrient value and then can be used to determine nutritional significance in relationship of foods/diet to health outcomes. The new technology incorporates a high degree of automation and improved user interface, dramatically reducing the need for hands-on processes by eliminating the need for manual data entry. In addition, a thesaurus, and new statistical and data analysis techniques are under development. These efforts are being extended to other components of NDBS (in progress). NDL has acquired 4 major industry databases through collaborations with FDA (Mintel, Label Insights and Labelbase) and ERS (IRI market share data) at no cost. They will improve specificity and currency of commercial products in SR, e.g., by providing market shares of different brands and pro-active mechanisms for monitoring changes in these foods. Accomplishments 01 Maintaining Currency of Food Composition Database (SR). An SR interim release was made available to update data for baby foods (also provided to survey) and on 8 foods re-sampled for the sodium monitoring project. This permits 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. 02 Sodium monitoring. ARS researchers at Beltsville, Maryland, published sodium levels of popular commercially processed and restaurant foods based on nationwide sampling and chemical analyses on their website and in a peer reviewed journal. These foods will serve as indicators for assessing changes in the sodium content over time as food industry reformulates in response to public health efforts to reduce sodium in the US food supply. In addition, they transferred to CDC a new monitoring database (2013-2015) of nutrient data from manufacturers/ restaurant chains, either obtained directly from them or through websites or labels for Sentinel Foods for major national and store brands. 03 Bioactive research. Updates were made to the USDA Database for the Flavonoid Content of Selected Foods and the USDA Database for the Isoflavone Content of Selected Foods to entre data correction and completeness. Additional data are constantly acquired through literature search and working with collaborators or industry partners (e.g. Ocean Spray) for future updates. These resulted in an update to the USDA's Expanded Flavonoid Database for the Assessment of Dietary Intakes, and NDL played an important role to make sure the data were calculated and expressed correctly. These data are used by national and international researchers and as the base for other databases. 04 Iodine research. Iodine research was initiated with the Office of Dietary Supplements and the Food and Drug Administration. Two of 14 manuscripts with Nutrient Data Laboratory (NDL) authors and reflecting 2014 NIH-hosted roundtables are in press for September 2016 release. NDL has outlined the plan to jointly analyze iodine-containing foods in the Food and Drug Administration (FDA) Total Diet Study database and the USDA National Nutrient Database for Standard Reference. Both databases are used widely by researchers and nutrition policy makers. With the increase in commercially packaged foods (containing non iodized salt), the issue of deficiency, especially among women of reproductive age, is being revisited in the United States. 05 New technology. NDL has enhanced National Data Bank System (NDBS) data dissemination systems, automated data processing modules for data import and export, and an automated linear programming tool or Formulations Program (FP) for generating complete nutrient profiles for multi-ingredient, commercially processed foods. This system incorporates a high degree of automation and improved user interface, dramatically reducing the need for hands-on processes by eliminating the need for manual data entry by obtaining ingredient information and label data from external sources, i.e. the manufacturers� data portal, the development of which is also underway at the University of Maryland with USDA. Import of specialty market databases have improved specificity and currency of commercial products in SR, for example, by providing market shares of different brands and pro-active mechanisms for monitoring changes in these foods. Cumulatively, this allows for more current and accurate data for the user and the ability to use the data more efficiently in studies of diet and health outcome.

Impacts
(N/A)

Publications

  • Ahuja, J.K., Wasswa-Kintu, S., Daniel, M., Thomas, R.G., Haytowitz, D.B., Showell, B.A., Nickle, M.S., Roseland, J.M., Pehrsson, P.R., Cogswell, M.E. , Gunn, J. 2015. Sodium content of popular commercially processed and restaurant foods in the United States. Preventive Medicine Reports. 2:962- 967.
  • Maalouf, J., Cogswell, M.E., Yuan, K., Martin, C.L., Gillespie, C., Ahuja, J.K., Pehrsson, P.R. 2015. Sodium content of foods contributing to sodium intake: A comparison between selected foods from the CDC Packaged Food Database and the USDA National Nutrient Database for Standard Reference. Procedia Food Science. 4:114-124.
  • Cogswell, M.E., Yuan, K., Gunn, J.P., Gillespie, C., Sliwa, S., Galuska, D. A., Moshfegh, A.J., Rhodes, D.G., Ahuja, J.K., Pehrsson, P.R., Merritt, R., Bowman, B.A. 2014. Sodium intake among U.S. school-aged children - United States, 2009-2010. Electronic Publication. 63(36):789-797.
  • Quader, Z.S., Gillespie, C., Sliwa, S.A., Mugavero, K., Gunn, J.P., Ahuja, J.K., Pehrsson, P.R., Moshfegh, A.J., Burdg, J.P., Cogswell, M.E. 2016. Sodium intake among U.S. school-age children: National Health and Nutrition Examination Survey, 2011-2012. Journal of the Academy of Nutrition and Dietetics. 64(22):4531-4535.


Progress 10/01/14 to 09/30/15

Outputs
Progress Report 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. 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. Objective 1A, Expanding food composition databases (SR): In Release SR28 of the USDA National Nutrient Database for Standard Reference, over 300 new food items were added. The new items mainly included commercially packaged and restaurant foods, including school foods. Approximately 72 food items were analyzed through NFNAP�most in response to requests from FSRG and as part of the sodium monitoring project (see below). Most food items were sampled nationally, but for a few, less commonly consumed foods, local samples were procured. Data for additional food items were obtained through collaborations with various trade associations and by long-standing relationships with a number of food companies. About 180 foods no longer on the market were deleted from the database, and 10,000 nutrient values were updated as part of this process. Data on the trans fatty acid content of foods were added to SR28 for basic commodities. These data will be used to calculate trans fatty acid values for multi-component foods in subsequent releases of SR with the goal of making trans fat data available for all foods in the FNDDS 2015- 16. Objective 1B, Expanding cooking yield and retention tables: NDL released an updated cooking yields table on-line for >174 meat and poultry items as USDA Cooking Yields for Meat and Poultry Release 2. A manuscript was published focusing on effect of cooking on yields and proximate nutrients among beef cuts from different primals. Objective 1C, Expanding nutrient composition data for Survey: NDL continued its long-standing commitment to provide FSRG with updated nutrient values for a subset of SR foods (survey-SR) containing the complete matrix of 65 components monitored as part of national nutrition monitoring on a biennial basis. The survey-SR subset of over 3,000 foods is used with the NDL nutrient retention factors file as the foundation for FSRG�s Food and Nutrient Database for Dietary Studies (FNDDS), the database used for processing intakes of survey respondents in WWEIA, NHANES. Among the 65 nutrients provided to FSRG are those identified by the 2010 Dietary Guidelines for Americans Report as over-consumed nutrients or components (i.e., sodium, saturated fat), shortfall nutrients (i.e., vitamin D, calcium), and nutrients of concern for selected population groups (i.e., folate, iron, vitamin B12). New and updated data were provided for FSRG to determine nutrient intakes of survey respondents in WWEIA, NHANES 2013-2014. The updated data included: 1) Nutrient profiles expanded for 21 new foods which first appeared in SR 27; 2) ~15,000 changes for ~500 existing foods updated for SR 27 and SR 28; 3) ~ 250 new foods added to SR 28, which were requested by FSRG as foods reported by survey respondents. For about 60 new foods, NFNAP sampling was planned and executed in order to have analytical data available for the survey-SR dataset. Comprehensive quality control checks were conducted on all new and updated data. The subsequent data files provided to FSRG contained the food descriptions and nutrient data for new foods and for changes in existing survey-SR foods. Objective 1D, Sodium monitoring: As part of the inter-agency (USDA-CDC) monitoring plan, 125 highly-popular, sodium contributing, commercially processed and restaurant food items (Sentinel Foods) continued to be tracked as indicators to assess the changes in the sodium content of the food supply. NDL has been monitoring nutrient profiles of these Sentinel Foods through nationwide sampling and laboratory analysis. In addition, nutrient profiles for over 1,100 other commercially processed and restaurant foods (Priority-2 Foods) were monitored using information from manufacturers and market share data. In addition to sodium, related nutrients (total sugar, potassium, total and saturated fat, and total dietary fiber) that may change as food manufacturers reformulate were monitored. As part of the continuous monitoring, we resampled nine Sentinel Foods nationwide after consultation with FSRG and CDC. Over 40 additional sodium-contributing foods were sampled nationwide and analyzed. Nutrient data for many of these items had previously been based on formulations/recipes or old analytical data, and many of these foods were analyzed because of being identified as having big changes in sodium content. Objective 2A, Special Interest Databases (SID) for bioactive compounds: The �USDA Database for the Proanthocyanidin Content of Selected Foods, Release 2� was completed, reviewed by three external reviewers, and released, with proanthocyanidin values for 283 foods. Seventy-eight new food items were added in the updated database. In the NDL-led pilot study on inter-laboratory methods for measuring vitamin D and 25(OH)D in animal-based foods and dietary supplements, 5 international and U.S. laboratories participated and provided methods information and data for six materials in two separate trials. NDL evaluated the data and will prepare a manuscript describing the results with coauthors from USDA and NIH Office of Dietary Supplements. Objective 2B, Special Interest Database (SID) for sulfur containing compounds: Data for glucosinolates from 130 research articles published in peer-reviewed scientific journals were evaluated for data quality and entered into standard SID format. Objective 2C, Effect of processing/preparation on bioactive content: Samples of broccoli, collard greens, kale and red cabbage were purchased from 3 different supermarket chains. Food Composition and Methods Development Laboratory (FCMDL) prepared (using protocols provided by NDL) and analyzed these vegetables in raw and cooked forms (boiled, steamed, microwaved) for selected flavonoids and GLS/ITCs to determine retention factors of these compounds after preparation. Preliminary results for broccoli and red cabbage suggested higher apparent retention of kaempferol in broccoli by microwave cooking than steaming or boiling, while cyanins in red cabbage were retained better by steaming than boiling. Objective 3A, Information technology modernization for web-based data submission: Data from the foods industry were received through the Public-Private Partnership utilizing the industry-standard GS1 format. These data were reformatted for demonstration to five industry partners; 244 products were presented as searchable products using a staging server separate from that used for the USDA National Nutrient Database for Standard Reference. Once industry representatives and partners in ILSI NA develop strategies to resolve remaining data accuracy issues and deliver a corrected database to USDA, it can be released to the public. Data exchange and ongoing discussions within the public private partnership (USDA, Agricultural Technology Information Partnership [ATIP Foundation]), and ILSI NA have provided information enabling NDL to better design modifications to the NDBS in order to handle increased data submissions through the ATIP portal and other sources. Work began at UMD on developing programs for the reformatting of data received from external sources, including the ATIP portal, for import into the NDBS and/ or the search program hosted at NAL. Objective 3B, Enhanced NDBS data dissemination systems: NDL staff members implemented enhancements to the NDBS, including software programs to reformat data from external sources (as part of the data portal), data processing bypasses within the system, and an automated linear programming tool or Formulations Program (FP) for generating complete nutrient profiles for multi-ingredient, commercially processed foods. This tool uses nutrient and ingredient information from food labels to develop nutrient values where data are not available. The McWest Company was awarded a contract for the programming of a new FP using industry standard software packages and project management practices. The first versions of the new FP were delivered and tested by NDL staff. Each week new updates were delivered, providing new features and addressing issues raised during the previous tests. Ultimately, this work will produce a system with a high degree of automation and improved user interface, dramatically reducing the need for hands-on processes by eliminating the need for manual data entry by obtaining ingredient information and label data from external sources, i.e. the ATIP portal. Thesaurus, statistical and data analysis techniques will also be employed to reduce the need for hands-on entry and operation of the FP. This will result in the replacement of outdated software developed as part of the NDBS in 1999. These efforts need to be extended to other components of the NDBS as well. Accomplishments 01 Release of four major databases for human nutrition assessment. ARS scientists in the Beltsville Human Nutrition Research Center, Beltsville, Maryland, a) released new or updated databases including a) USDA National Nutrient Database for Standard Reference (SR28); b) the USDA Database for the Proanthocyanidin Content of Selected Foods; c) Monitoring sodium levels in commercially processed and restaurant foods dataset; and d) dataset of USDA National Nutrient Database for Standard Reference for What We Eat in American, NHANES 2013-2014. Completion of pilot study on inter-laboratory methods for measuring vitamin D and 25(OH)D in animal-based foods and dietary supplements, including results from 5 international and United States laboratories. These will be invaluable references for human nutrition assessment worldwide.

Impacts
(N/A)

Publications

  • Ahuja, J.K., Pehrsson, P.R., Haytowitz, D.B., Wasswa-Kintu, S., Nickle, M. S., Showell, B.A., Thomas, R.G., Roseland, J.M., Williams, J.R., Khan, M., Nguyen, Q., Hoy, K., Martin, C.L., Rhodes, D.G., Moshfegh, A.J., Gillespie, C., Gunn, J., Merritt, R., Cogswell, M. 2015. Monitoring sodium in commercially processed foods from stores and restaurants. American Journal of Clinical Nutrition. 101:622-631.
  • Roseland, J.M., Nguyen, Q.V., Williams, J.R., Douglass, L.W., Patterson, K. Y., Howe, J.C., Brooks, C.J., Thompson, L.D., Woerner, D.R., Engle, T.E., Savel, J.W., Harris, K.B., Cifelli, A., Mcneill, S. 2015. Protein, fat, moisture, and cooking yields from a nationwide study of retail beef cuts.. Journal of Food Composition and Analysis. 43:131�139.
  • Gillespie, C., Malouf, J., Yuan, K., Cogswell, M.E., Gunn, J., Levings, J., Moshfegh, A.J., Ahuja, J.K., Merritt, R. 2014. Sodium content in US packaged foods 2009. American Journal of Clinical Nutrition. 101: 344-353.
  • Bhagwat, S.A., Haytowitz, D.B., Wasswa-Kintu, S., Pehrsson, P.R. 2015. Development of USDA's expanded flavonoid database: A Tool for Epidemiological Research. British Journal of Nutrition. DOI: 10.1017/ S0007114515001580.
  • Roseland, J.M., Nguyen, Q., Williams, J.R., Patterson, K.Y., Woerner, D.R., Douglass, L.W. 2014. USDA Nutrient Data Set for Retail Veal Cuts. World Wide Web. Available:


Progress 10/01/13 to 09/30/14

Outputs
Progress Report 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. 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. SR and survey: SR27 has been released and contains data for over 8,600 food items for up to 150 components. Some of the foods added or updated in SR27 include: Breakfast cereals, fried chicken pieces (breast, thigh, and wing) and skin and breading, fast food biscuit, chicken strips, hash browns, chicken noodle condensed soup, fried shrimp (from restaurant), several pulses (chickpeas, green and red lentils, and green peas), a number of vegetarian items, enhanced and non-enhanced pork loin chops, rotisserie chicken breast, Italian-style meatballs, turkey bacon, popular juice smoothies and fortified juice products, greek yogurt, sorghum grain and flour, green tea, energy drinks, and other beverages. The online search program has been accessed over 2.3 million times in the past year by 1.3 million unique users. NFNAP: 125 foods were selected for sampling and analysis. Most foods were selected for analysis, if they were frequently reported in the national survey, What We Eat In America, NHANES (e.g., flavored chips such as Doritos, mayonnaise-type dressings such as Miracle Whip), had been reformulated based on review of labels (e.g., sour cream, microwave popcorn), or had not been analyzed for the longest periods of time (e.g., butter, margarine). Some foods that have become highly popular in the past few years were also included (e.g., whole grain pasta, turkey bacon, wheat hamburger rolls, flavored Greek yogurt). The foods were picked up nationwide from 12 different locations and shipped to Food Analysis Laboratory Control Center (FALCC), Virginia Tech (Blacksburg,VA), and Texas Tech University's Animal and Food Sciences laboratory. The foods were weighed, cooked, dissected, and homogenized to prepare about 750 composites and 7,000 samples, which were sent for chemical analyses to commercial laboratories and universities, along with quality control materials. Most foods were analyzed to develop a full nutrient profile comprising of macronutrients, minerals, vitamins, fatty acids, and amino acids. The updated food composition data were used to update USDA National Nutrient Database for Standard Reference (SR), the foundation for most food composition databases used in food policy, research, dietary practice, and nutrition monitoring in the U.S. 124 samples (representing 94 foods) were sent to Tufts University under a SCA for Vitamin K analysis. One paper has been submitted to the Journal of Food Composition and Analysis. UNC and choline: 33 Samples were analyzed for choline at University of North Carolina. Cooperator expertise was used to develop food matrix specific methods for handling and analyzing samples. The Cooperator also offered expertise in interpretation of results of the choline components analyses. The choline values obtained will be released in SR, for use by the research community in epidemiological studies and to establish a relationship between choline and betaine intake and the etiology of neural tube defect. Release 1 of USDA�s Expanded Flavonoid Database for the Assessment of Dietary Intakes was made available on NDL�s web site in September 2014. It contains full flavonoid profiles for nearly 3,000 foods reported as consumed in NHANES-WWEIA 2007-08 and will be used to correlate health outcomes with flavonoid intake. Work began on preparing Release 2 of the USDA Database for the Proanthocyanidin Content of Selected Foods. Work also began on new database on sulfur-containing bioactive components. An ARS scientist with experience in analyzing these compounds worked with FCMDL to analyze various foods. Meat research was extensive; NDL ordered samples of food which were delivered to the TTU cooperator for weighing, dissecting for physical components, preparation including cooking, packaging, and shipment to specified analytical laboratories for nutrient analysis. Texas Tech University research specialists processed 3 different types of meat samples. The Cooperator established procedures for the implementation of these steps and for inclusion of control materials or duplicate samples for quality control assurance. In addition, this agreement included consultations with NDL and contract laboratories on issues of methodology, sample analysis, handling and storage. The Cooperator offered expertise in experimental design and interpretation of results of the nutrient analyses. In the NDL- led pilot study on interlaboratory methods for measuring vitamin D and 25(OH)D in animal-based foods and dietary supplements, NDL identified 5 international and U.S. laboratories who agreed to participate. Six suitable materials were identified and sent to the labs for analysis. Analytical data and methods information were obtained from the laboratories. NDL began evaluating the data and will report the results. Sodium Monitoring: The Nutrient Data Laboratory (NDL) in collaboration with the Centers for Disease Control (CDC), the Food and Drug Administration (FDA) and the Agricultural Research Services� (ARS) Food Surveys Research Group (FSRG) has developed a plan to monitor levels of sodium in commercially processed and restaurant foods. As part of the monitoring plan, about 125 selected commercially processed and restaurant food items, termed �Sentinel Foods,� will be tracked as indicators to assess the changes in the sodium content of the food supply. The Sentinel Foods were selected based on the dietary data from the national survey, What We Eat in America (WWEIA), National Health and Nutrition Examination Survey (NHANES) and accounted for about one-third of total sodium intake in WWEIA, NHANES 2007-2008. NDL has been monitoring nutrient profiles of these Sentinel Foods through nationwide sampling and laboratory analysis, using standardized validated procedures under the USDA National Food and Nutrient Analysis Program (NFNAP). In addition, over 1,100 other commercially processed and restaurant foods (Priority-2 Foods) are monitored using information from manufacturers or restaurant chains and their websites or Nutrition Facts Panels. In addition to sodium, related nutrients (total sugar, potassium, total and saturated fat, and total dietary fiber) that may change as food manufacturers reformulate are also being monitored. During FY 2014, the baseline analyses of all 125 Sentinel Foods and re-sampling and analyses of 3 highly popular foods (bread, hot dog rolls and tortilla) were completed. In addition, over 40 additional sodium-contributing foods were analyzed. Nutrient data for many of these items were based on formulations/recipes or old analytical data, and many of these foods were identified as having big changes in their sodium content. Inclusion of these foods will improve food composition data in SR and assessment of sodium intakes in WWEIA, NHANES. In addition, it will provide CDC an early and essential indication of how sodium and related nutrients are changing in the U.S. food supply, and will focus further investigations and assessment. A manuscript on the sodium monitoring methodology is under review by the American Journal of Clinical Nutrition. Several studies were conducted using the new analytical data on Sentinel Foods. A study comparing the analytical data with label data found significant differences (p<0.05) for quarter of the 77 Sentinel Foods studied. The differences between analytical and label values were not significant by brand (national vs. store). The percent differences between analytical values and label values were lower for restaurants than stores. These data will be further reviewed in FY 2015 for all Sentinel Foods, to help validate the methodology for sodium monitoring, i.e. combination of laboratory analysis and use of data on labels or manufacturer and restaurant websites. A study on Chinese dishes shows the high variability in sodium content (13% in General Tso to 56% in lemon chicken) of these dishes. Studies done by NDL meat scientists show that sodium values for enhanced forms of meats - pork, turkey, chicken breast, and dark meat chicken were significantly higher than the non-enhanced forms (p<0.001). The sodium values in these products ranged from 154 mg - 231 mg/100g for enhanced compared to 45 mg -113 mg/100g for non-enhanced. A study comparing four pairs of similar foods such as chicken nuggets from store and restaurant did not find any consistent differences between the two sources. These studies improve our understanding of the food environment, and help focus public health efforts. Significant Activities that Support Special Target Populations: Continued tracking of foods consumed by ethnic groups (i.e., Asian Americans) consistent with oversampling in the National Health and Nutrition Examination Survey,What We Eat in America. Accomplishments 01 Nutrient data for foods and other dietary components are critical to the assessment of dietary intake and support the investigation of hypotheses concerning the relationship of dietary intake to health status. During 2014, the Nutrient Data Laboratory developed and released the annual update of the USDA National Nutrient Database for Standard Reference (SR27) Nutrient profiles for over 300 foods were added to SR27 (www.ars.usda.gov/nutrientdata). Of these, 121 were added or updated using NFNAP data; the remainder was obtained from food industry sources. 02 Release of Ground Beef Calculator, Version 2. The Ground Beef Calculator Version 2, released in 2014, computes nutrient profiles for raw and prepared ground beef products at lean/fat levels between 97/3 and 70/30. Analytical data were used in mixed model regression analysis to obtain a regression equation for each nutrient at fat levels ranging from 3% to 30%. This user-friendly on-line tool provides nutrient values for ground beef for five preparation methods: raw, broiled patties, pan-broiled patties, pan-browned crumbles, and baked loaf. The Ground Version 2 is an update of the original ground beef calculator released in 2006 with lean/fat levels between 95/5 and 70/30.

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