This edition contains the following articles on:
NDSR 2017: Gluten to be included
NDSR 2017: Option to include Customizable Data Fields in the Header Tab
Can intake of FODMAPs be estimated from data available in NDSR Output Files?
Creative Use of NDSR – Assessing the Nutritional Quality of Food Purchases
Beware of Consumer-Oriented Diet Assessment Apps
New Foods
NDSR 2017: Gluten to be included
There has been growing interest in studying gluten, a protein found in wheat, rye, and barley. Consequently, gluten is being added to the NCC Food and Nutrient Database and will be included in NDSR 2017. You will find it in the reports and output files that provide values for other nutrients in NDSR.
Like other nutrients added to new versions of NDSR, gluten values may be generated for recalls, records, menus, etc. entered in past versions of NDSR by restoring the back-up files in NDSR 2017. If you’ve ever wondered why we say the NDSR back up files are gold, now you know one of the reasons they should be considered a treasure to save.
There is a caveat with the gluten values to be included in NDSR that we want you to be aware of. Foods with “zero” values are not necessarily gluten-free because of the process used to determine the nutrient composition for brand name food products in the database. When creating formulations (recipes) for brand name food products, NCC relies on information available on the product ingredient statement as available from the product manufacturer. Consequently, shortcomings with respect to the completeness and accuracy of the product ingredient statement may result in inaccuracies in gluten estimates. Concerns include the following:
- In some cases the product ingredient statement lacks specificity with respect to the type of starch or modified starch included in the product. Thus, the formulations created for products that lack detail on the type of starch or modified starch in the product may not include the correct type of starch or modified starch.
- Product ingredients that are listed in the ingredient statement as less than 2% of product weight may not be included in formulations created by NCC. Thus, the potential contribution of these ingredients to the gluten content of a food product may not be ascertained.
- Gluten that might be present in a food product due to cross contamination will not be ascertained in the approach used to estimate the gluten content of foods, since only ingredients in the ingredient statement are used to create the product formulations on which gluten values are to be estimated.
The aforementioned limitation should be considered when using gluten values from NDSR. For example, the gluten values from NDSR may not be appropriate for use in determining whether a food or diet is gluten-free. However, the gluten values may be useful in determining whether a diet or food is low or high in gluten.
NDSR 2017: Option to include Customizable Data Fields in the Header Tab
Some have asked if we could add fields in the header tab for entering height, weight, and other information about study participants. To address this need, NDSR 2017 has a new feature that will allow you to include up to five customizable data fields (labeled ‘data fields’) in the header tab for records in a project. The number of data fields you wish to include may be selected in the Method Preferences tab. In addition to choosing the number of data fields you would like to include, you have the option to include a description of the information to be collected for each field (e.g. ‘height, in centimeters’, ‘weight, in kilograms’). These descriptions will appear in the header tab next to the data field for the question. Data entered using these customizable data fields will be included in NDSR Output Files 04, 05, and 06; the Record Properties Report, and the Records QA Report.
This new feature will be available for the following record types: Recall, Record, Record-Assisted Recall, User Recipe and Menu. It will not be available for the DSAM User Product.
Can intake of FODMAPs be estimated from data available in NDSR Output Files?
Several researchers have asked if intake of FODMAPs* can be estimated from data available in NDSR output files. The answer is that some food components considered to be FODMAPS are available in NDSR.
What is available? monosaccharides (fructose, glucose, galactose, tagatose) and disaccharides (sucrose, lactose, maltose) are available in NDSR output files and reports. In addition, the major polyols found in food (erythritol, inositol, isomalt, lactitol, maltitol, mannitol, pinitol, sorbitol, xylitol) are available.
What is missing? Oligosaccharides such as fructo-oligosaccharides, galacto-oligosaccharides are not available in NDSR.
*FODMAPs is an acronym referring to Fermentable Oligosaccharides, Disaccharides, Monosaccharides and Polyols.
Creative Use of NDSR – Assessing the Nutritional Quality of Food Purchases
Dr. Melissa Laska, an Associate Professor in the Division of Epidemiology and Community Health at the University of Minnesota, is using NDSR in a creative way. She is carrying out a study to evaluate the impact of a local policy change (the Minneapolis Staple Foods Ordinance) that establishes minimum stocking criteria for a wide array of healthy foods as a requirement of grocery/food store licensing. One of the outcomes being evaluated is whether the nutritional quality of foods purchased by store customers improves as a result of this policy. To measure this outcome she is carrying out intercept surveys of shoppers as they exit stores. An inventory of all food and beverages purchased at the store is carried out as part of the intercept survey.
Where does NDSR fit into the picture? Dr. Laska’s team is entering each participant’s purchases into NDSR so that the nutrient composition of foods purchased before and after implementation of the policy may be compared. Dr. Lisa Harnack (NCC Director) assisted in developing the NDSR data entry procedures used for the study, and she was pleasantly surprised to discover that NDSR worked well for this purpose. Some unique data entry rules are required when using NDSR for analyzing food purchases. Dr. Harnack (harna001@umn.edu) would be happy to discuss the procedures with anyone considering using NDSR for this purpose.
If you are using NDSR in a creative way let us know at nccnews@umn.edu so we can share your creativity with others.
Beware of Consumer-Oriented Diet Assessment Apps
There are currently thousands of apps available to consumers for use in diet tracking and other purposes (e.g. menu planning, looking up nutrient content of foods, etc.). Some of these apps are being touted as useful for nutrition research. Thus, we carried out an informal review of some of the available apps. In this review we noticed some issues you may want to consider if you are thinking about using a consumer-oriented app for your research. Factors include:
- Are output files available to facilitate analysis of study data? Some apps provide reports in formats not amendable to data analysis for research.
- Does the app provide feedback/educational messages to study participants? If so, measurement reactivity may be a concern depending on your study design. As an example, if food and nutrient intake is being assessed as a baseline measure in a cohort study, it would be problematic if the app used to assess diet at baseline provided feedback/nutrition education that could lead to change in participants’ eating habits.
- Does the app include the nutrients and food groups of interest in your study? Many consumer apps include only the nutrients found on the Nutrition Facts label. Also, food serving count information (e.g. servings of whole grains, fruit, etc.) are generally not available.
- How complete are the nutrient values for foods in the app? Some apps have high levels of incomplete data for some nutrients (e.g. vitamin D values missing for 80% of foods in the app). Missing values may lead to underestimation of nutrient intake.
- Are reliable sources of nutrient composition data used? Some apps use crowdsourcing as a source of nutrient composition data for some foods (e.g. app users are allowed to add foods and their nutrient composition information to the app for use by all app users). Data entry errors are a potentially serious concern with crowdsourced nutrient information for foods.
- How often is the food and nutrient database updated to reflect marketplace changes (e.g. product reformulations, addition of new products in the marketplace, etc.)? Food and nutrient data may be out of date if regular updates are not carried out.
- What is the quality of the user interface? In some apps, it is difficult to locate foods consumed (search function operates poorly). Some apps allow for limited options in entering food amounts (e.g. candy bar must be entered as a fraction of a regular sized bar because other food specific unit options such as ‘miniature’, ‘fun size’, and ‘king size’ are not available). These types of user interface shortcomings may lead to inaccurate reporting by study participants and incomplete data (participant does not complete entry due to confusion/fatigue/frustration).
- How valid are food and nutrient intake estimates? The validity of an app may be affected by factors such as usability, the quality of the food and nutrient database, and the accuracy of the program code for carrying out nutrient calculations. Thus, data available regarding the validity of an app should be among the factors considered.
New Foods
The following foods are included in the NCC News Spring 2017 New Foods Backup File, available for download on our website under New Food Backup Files, “Spring 2017.”
- Jennie-O Reduced Sodium Turkey Frank
- Annie’s Grape Pea B & J Pockets
- Daiya Foods Cheese Lovers Gluten Free Pizza
- Enjoy Life Foods Cocoa Loco Bar
- Yoplait Greek 100 Protein Yogurt – Vanilla Flavor
- Plum Organic Mighty Veggie Pouch – Zucchini, Apple, Watermelon & Barley
- Starbucks Bacon, Gouda & Egg Breakfast Sandwich
- Herbalife Formula 1 Healthy Meal Powder – Vanilla
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