Information for Grant Writers

Description of 24-hour Dietary and Supplement Recall Features of NDSR

A description of the 24-hour dietary and supplement recall features of NDSR for use in grant applications is available below. You can copy and paste the content needed into the appropriate section of your grant.
The 24-hour dietary recalls will be collected using Nutrition Data System for Research (NDSR), a computer-based software application developed at the University of Minnesota Nutrition Coordinating Center (NCC) that facilitates the collection of recalls in a standardized fashion [1]. Dietary intake data gathered by interview is governed by a multiple-pass interview approach [2]. Five distinct passes provide multiple opportunities for the participant to recall food intake. The first pass involves obtaining from the participant a listing of all foods and beverages consumed in the previous 24 hours. This listing is reviewed with the participant for completeness and correctness (second pass). The interviewer then collects detailed information about each reported food and beverage, including the amount consumed and method of preparation (third pass). In the optional fourth pass, the interviewer then probes for commonly forgotten foods. Finally, the detailed information is reviewed for completeness and correctness (fifth pass).
Dietary supplement use will be assessed in conjunction with collection of 24-hour dietary recalls using the Dietary Supplement Assessment Module included in NDSR [3]. Use of all types of dietary supplements and non-prescription antacids are queried in the module.
The NCC Food and Nutrient Database serves as the source of food composition information in NDSR [4]. This database includes about 19,000 foods of which about 8,300 are brand name products. Ingredient choices and preparation methods provide more than 160,000 food variants. Values for 178 nutrient, nutrient ratios and other food components are generated from the database. The USDA Nutrient Data Laboratory is the primary source of nutrient values and nutrient composition. These values are supplemented by food manufacturers’ information and data available in the scientific literature [5]. Standardized, published imputation procedures are applied to minimize missing values [6].

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