China 
Africa 
Explore chapters and articles related to this topic
The Concept of Nutritional Status and Its Measurement
Published in James M. Rippe, Lifestyle Medicine, 2019
Johanna T. Dwyer, Regan L. Bailey
All self-reported dietary data are also limited by the accuracy and currency of the databases that are employed to estimate energy and nutrient intakes from foods and beverages reported. The U.S. Department of Agriculture’s (USDA) National Nutrient Database for Standard Reference is the basis for USDA Food and Nutrient Database for Dietary Studies (FNDDS) values that are used in analyzing NHANES data.35 It is critical that the values for the nutrient content of foods used be kept up-to-date. The National Food and Nutrient Analysis Program (NFNAP) is a federally funded research program that provides funds for analyses of new and reformulated foods to enhance the analytical estimates of the nutrient content of foods and dietary supplements.
Strengths and Limitations of Food Composition Databases
Published in Dale A. Schoeller, Margriet S. Westerterp-Plantenga, Advances in the Assessment of Dietary Intake, 2017
Development of Key Food lists requires food intake data and information about the nutrient content of those foods, which are readily available for the U.S. population in general, as outlined above. However, for subpopulations and small ethnic groups, national surveys and databases may inadequately represent dietary habits and nutrient levels of respective foods. A Key Foods list developed for African Americans, who at the time represented ~12% of the U.S. population, had similar foods in the first quartile as the list for the U.S. population, but with minor ranking changes (Haytowitz 2000). However, when a Key Foods list was prepared for American Indians, using national databases, traditional foods commonly consumed by this group were not identified, thus suggesting that other methods were required to adequately track dietary habits and foods of small minority groups (Haytowitz 2000). Dietitians and other professionals familiar with dietary habits of two minority groups in the United States, Alaska Natives, and American Indians, were recruited to identify important traditional foods that may impact on the health of individuals in these subpopulations. Employing these unique techniques, nearly two hundred foods have been sampled, analyzed, and the resulting data incorporated into the current USDA National Nutrient Database for Standard Reference (SR28) (Amy and Pehrsson 2003; Pehrsson et al. 2005; Phillips et al. 2014). These observations indicate that when surveying small, minority populations it is essential to have intimate knowledge of dietary habits, so that appropriate foods can be assessed for nutrient levels in support of diet–health research and education.
Risk Factors for Constipation in Adults: A Cross-Sectional Study
Published in Journal of the American College of Nutrition, 2020
Gamze Yurtdaş, Nilüfer Acar-Tek, Gamze Akbulut, Özge Cemali, Neslihan Arslan, Ayfer Beyaz Coşkun, Fatmanur Humeyra Zengin
Participants were asked how frequently and how much they consumed items from certain food groups (whole-grain foods, bread, pasta/rice, potatoes, fruit, vegetables, legumes, tea, coffee, ayran (yogurt-water), kefir (fermented milk), milk, non-carbonated beverage and alcoholic beverages) over the previous month. The study coordinator explained to the participants how to complete the FFQ. A “Food and Nutrition Photo Catalogue” was used to help participants correctly remember measurements and amounts of food and beverages consumed. Constipation and food consumption frequencies during the previous month were assessed, reflecting the previous month’s dietary habits. The US Department of Agriculture (USDA) (National Nutrient Database for Standard Reference, Release 25 Software v.1.2.2) database was used for evaluating fiber intake (16). Fiber, water and fluid intake were assessed by quartiles.
Inflammatory Potential of Diet and Odds of Lung Cancer: A Case-Control Study
Published in Nutrition and Cancer, 2022
Alireza Sadeghi, Karim Parastouei, Sharareh Seifi, Adnan Khosravi, Babak Salimi, Hoda Zahedi, Omid Sadeghi, Hamid Rasekhi, Maryam Amini
We collected dietary data using a 142-item Willett-format dish-based semi-quantitative food frequency questionnaire (DS-FFQ) which was designed and validated specifically for Iranian adults. Details about the design and validity of this FFQ were published previously (25, 26). This questionnaire included 84 food items and 58 mixed dishes. This questionnaire was completed by trained researchers through interviews with the participants. The FFQ was filled out for participants based on their dietary intakes over the past 12 mo,. To assess the intake of each food item (from the 142 items), researchers asked two questions from the participants. The first question was about the frequency of consumption and the second one was about the amount of consumption at any time. The amount of consumption was determined using portion size. Finally, based on the consumption frequency and the amount of consumption at each time, the daily intake of each food item was computed as grams per day. Also, nutrient intakes of each participant were calculated based on the US Department of Agriculture (USDA) national nutrient database and Iran’s Food Composition Table (IFCT) (27, 28). Since IFCT provides nutrient data for a limited number of food items, nutrient data required for >90% of food items in our FFQ were obtained from the USDA database. It should be kept in mind that all of the food items in our FFQ, except mixed dishes and those that had nutrient data in the IFCT, were completely matched with the related items in the USDA database. To estimate the nutrient composition of mixed dishes such as Olivieh and Kabab, we used nutrient data of food items used for the preparation of those mixed dishes. For instance, Olivieh contains some food items such as potato, mayonnaise, chicken meat, and egg. By considering the amount of each component in one serving of Olivieh and the nutrient content of each component based on the USDA database, we could estimate the nutrient content of Olivieh per one serving.
Relationship between Furocoumarin Intake and Melanoma History among US Adults in the National Health and Nutrition Examination Survey 2003-2012
Published in Nutrition and Cancer, 2020
Melissa M. Melough, Kijoon Kim, Eunyoung Cho, Ock K. Chun
The USDA Food and Nutrient Database for Dietary Studies (FNDDS) is the resource used to calculate nutrients in NHANES, and the FNDDS is based on nutrient values in the USDA National Nutrient Database for Standard Reference (SR). NHANES data files contain information regarding the link between FNDDS foods and SR items so that nutrient intakes can be calculated. Therefore, to determine individuals’ furocoumarin consumption using dietary data from NHANES, the following procedure was applied. First, to find all food codes containing any of the foods in our previously created furocoumarin database (29), the SR descriptions were searched for the name of that food, such as “grapefruit.” SR items that were composed entirely of that food, such as “grapefruit, raw, pink and red and white, all areas” were assigned the furocoumarin values of the database item. SR descriptions that included the database item and that contained a mixture of foods were examined further to determine the percentage of the database item in the combination food. The Nutrition Data System for Research (NDSR) software was used for this process in addition to searches on popular recipe websites to determine typical ingredient content for these mixed items. For example, the database item “cooked carrot” was applied to the SR code for “beef stew with potatoes and vegetables (including carrots, broccoli, and/or dark-green leafy), tomato-based sauce” using the assumption that this stew contains 5.0% cooked carrot by weight based on default recipes used in NDSR for beef stews. Similar procedures were performed for each distinct SR code containing any of the database items in their name. Next, FNDDS food files were searched for foods containing the SR codes designated as containing furocoumarin ingredients. Using the percentage of the applicable furocoumarin database item in each identified SR code and the percentage of the SR code present in the food, the furocoumarin content by weight in each food was calculated. Finally, individuals’ furocoumarin consumption was calculated by summing the furocoumarin content contributed by each food recorded in the dietary recall. Furocoumarin intake across two days of dietary recalls was averaged for each participant.