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Thus, the expansion and/or update of such FCDs though the aggregation of branded food data (BFCDs) could prove as a cost-efficient methodology. However, a framew<,/span>, …
A Methodological Framework for Aggregating Branded Food Composition Data in mHealth Nutrition Databases: A Case Presentation. Background/Objectives : Up-to-date, relevant and detailed food composition databases (FCDs) are a central component of mHealth apps.
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Thus, the expansion and/or update of such FCDs though the aggregation of branded food data (BFCDs) could prove as a cost-efficient methodology. However, a framework for data aggregation from BFCDs has yet to be documented. Methods : Products ( n = 3988) available in the HelTH BFCD were grouped following a three-step process. Firstly, foods were grouped based on their name, and then the aggregated nutritional composition was tested for heterogeneity using a coefficient of variation cut-off of 20% followed by a search of the ingredient list and other product characteristics to identify descriptors that reduced heterogeneity. Results : Following a three-step process, n = 347 new generic food names were proposed, each derived from at least three branded products, of which n = 235 were populated with aggregated nutritional content values. We found that 95.3%, 88.6%, 86% and 82.6% of aggregated energy, protein, carbohydrate and sodium values, respectively, had a coefficient of variation Conclusions : BFCDs can be used as a resource to expand existing databases with relatively homogeneous and up-to-date nutritional composition data. The application of this framework on larger datasets could improve the generic food name yield and homogeneity and support mHealth apps and other uses. Keywords: branded food data, data aggregation, digital applications, generic food data, mHealth, nutritional composition. Conflict of interest statement. The authors declare no conflicts of interest. Figures. Three-step product aggregation process using… Three-step product aggregation process using the long name, statistically measured homogeneity (via the… Figure 1. Three-step product aggregation process using the long name, statistically measured homogeneity (via the coefficient of variation) and elements found in ingredient lists and on-pack claims. Percentage of products per food… Percentage of products per food category that were aggregated under the same generic… Figure 2. Percentage of products per food category that were aggregated under the same generic name in groups of ≥3 products. Percentage of aggregated values calculated… Percentage of aggregated values calculated for energy, protein, carbohydrates, total sugars, total fat,… Figure 3. Percentage of aggregated values calculated for energy, protein, carbohydrates, total sugars, total fat, saturated fatty acids (SFAs) and sodium per coefficient of variation (CV) grade. Distribution of aggregated content values… Distribution of aggregated content values with CV > 40% for protein, carbohydrates, total… Figure 4. Distribution of aggregated content values with CV > 40% for protein, carbohydrates, total fat and sodium among the food categories.
nutritional composition of dates
dates nutrient composition