The dietary modelling tool: Using online constraint optimisation techniques to streamline food-based dietary prescriptions

Probst, Yasmine; Sullivan, Eilise; Morrison, Evan; Dam, Hoa Khanh

doi:10.1016/j.jnim.2015.12.203

Cited by 1 publication

(5 citation statements)

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“…As outlined earlier, the DMT was developed with 2 interfaces for users: a study interface, for defining default constraints for a study, and a user interface for modeling individual participant diets within the selected trial. Screenshots of these user screens are provided in Multimedia Appendix 1 [ 17 ]. This approach to development allows multiple users to model diets in different studies simultaneously.…”

Section: Resultsmentioning

confidence: 99%

“…This approach to development allows multiple users to model diets in different studies simultaneously. The forms were hosted online [ 17 ] also allowing multi-user access from varied locations.…”

Section: Resultsmentioning

confidence: 99%

“…Developed online, the DMT [ 17 ] relies on 2 data sources that are not seen by the user to populate the nutrient data (eg, macronutrients) for each of the food groups (eg, vegetables, fruits, and so on):…”

Section: Methodsmentioning

confidence: 99%

“…An overview of the process is shown in Figure 1 . In summary, to use the tool, users (likely dietitians) access a website [ 17 ]. Initially, the user provides as input to the tool the following data related to the trial:…”

Section: Methodsmentioning

confidence: 99%

“…By applying constraint optimization techniques to this process, it can be automated, saving both time and resources and streamlining the overall approach used. The development of the Dietary Modeling Tool (DMT) [ 17 ] has the potential to provide an automated method for dietary prescription, tailored to individual characteristics within the food and/or nutrient-based constraints of a clinical trial. The objectives of the DMT were that it would take on a simple, Web-based (widely accessible), and user-friendly format and target the individual energy requirements of participants.…”

Section: Introductionmentioning

confidence: 99%

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First-Stage Development and Validation of a Web-Based Automated Dietary Modeling Tool: Using Constraint Optimization Techniques to Streamline Food Group and Macronutrient Focused Dietary Prescriptions for Clinical Trials

Probst

Morrison²,

Sullivan³

et al. 2016

J Med Internet Res

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BackgroundStandardizing the background diet of participants during a dietary randomized controlled trial is vital to trial outcomes. For this process, dietary modeling based on food groups and their target servings is employed via a dietary prescription before an intervention, often using a manual process. Partial automation has employed the use of linear programming. Validity of the modeling approach is critical to allow trial outcomes to be translated to practice.ObjectiveThis paper describes the first-stage development of a tool to automatically perform dietary modeling using food group and macronutrient requirements as a test case. The Dietary Modeling Tool (DMT) was then compared with existing approaches to dietary modeling (manual and partially automated), which were previously available to dietitians working within a dietary intervention trial.MethodsConstraint optimization techniques were implemented to determine whether nonlinear constraints are best suited to the development of the automated dietary modeling tool using food composition and food consumption data. Dietary models were produced and compared with a manual Microsoft Excel calculator, a partially automated Excel Solver approach, and the automated DMT that was developed.ResultsThe web-based DMT was produced using nonlinear constraint optimization, incorporating estimated energy requirement calculations, nutrition guidance systems, and the flexibility to amend food group targets for individuals. Percentage differences between modeling tools revealed similar results for the macronutrients. Polyunsaturated fatty acids and monounsaturated fatty acids showed greater variation between tools (practically equating to a 2-teaspoon difference), although it was not considered clinically significant when the whole diet, as opposed to targeted nutrients or energy requirements, were being addressed.ConclusionsAutomated modeling tools can streamline the modeling process for dietary intervention trials ensuring consistency of the background diets, although appropriate constraints must be used in their development to achieve desired results. The DMT was found to be a valid automated tool producing similar results to tools with less automation. The results of this study suggest interchangeability of the modeling approaches used, although implementation should reflect the requirements of the dietary intervention trial in which it is used.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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