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The development of a decision support system for the infant food chain

In a time where the awareness of food safety and quality increases among the general population, it is vital that consumers are enabled to make informed decisions on risks involving the safety of their food. The SAFFI (Safe Food for Infants in EU and China) project aims to build an integrated decision support system (DSS) for the infant food chain that will enable stakeholders at all levels to make informed decisions regarding infant food. The infant food chain was selected due to its strict regulatory requirements, its vulnerabilities as highlighted by different food safety crises, the economic importance of the infant food sector in the EU and China and the focus on this particular food chain by food safety authorities.

The SAFFI project will incorporate data and models from work packages dealing with hazard identification (HI), hazard detection (HD), hazard control (HC) and risk ranking (RR). The models will be integrated into a user-friendly and upgradeable cloud-based decision support system application. A multi-actor cost-benefit analysis of the project will be carried out, enabling the stakeholders in the project to assess the relevance of implementing the project technologies by integrating food safety, regulatory and economic criteria.

The decision support system will be validated on four specific case studies, and tested on end-users, with the aim of extending this approach to other food chains.

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Forster H, Walsh MC, O’Donovan CB, Woolhead C, McGirr C, Daly E, O’Riordan R, Celis-Morales C, Fallaize R, Macready AL, Marsaux CFM, Navas-Carretero S, San-Cristobal R, Kolossa S, Hartwig K, Mavrogianni C, Tsirigoti L, Lambrinou CP, Godlewska M, Surwiłło A, Gjelstad IMF, Drevon CA, Manios Y, Traczyk I, Martinez JA, Saris WHM, Daniel H, Lovegrove JA, Mathers JC, Gibney MJ, Gibney ER, Brennan L
J Med Internet Res 2016;18(6):e150
30/06/2016

A Dietary Feedback System for the Delivery of Consistent Personalized Dietary Advice in the Web-Based Multicenter Food4Me Study

Background:

Despite numerous healthy eating campaigns, the prevalence of diets high in saturated fatty acids, sugar, and salt and low in fiber, fruit, and vegetables remains high. With more people than ever accessing the Internet, Web-based dietary assessment instruments have the potential to promote healthier dietary behaviors via personalized dietary advice.

Objective:

The objectives of this study were to develop a dietary feedback system for the delivery of consistent personalized dietary advice in a multicenter study and to examine the impact of automating the advice system.

Methods:

The development of the dietary feedback system included 4 components: (1) designing a system for categorizing nutritional intakes; (2) creating a method for prioritizing 3 nutrient-related goals for subsequent targeted dietary advice; (3) constructing decision tree algorithms linking data on nutritional intake to feedback messages; and (4) developing personal feedback reports. The system was used manually by researchers to provide personalized nutrition advice based on dietary assessment to 369 participants during the Food4Me randomized controlled trial, with an automated version developed on completion of the study.

Results:

Saturated fatty acid, salt, and dietary fiber were most frequently selected as nutrient-related goals across the 7 centers. Average agreement between the manual and automated systems, in selecting 3 nutrient-related goals for personalized dietary advice across the centers, was highest for nutrient-related goals 1 and 2 and lower for goal 3, averaging at 92%, 87%, and 63%, respectively. Complete agreement between the 2 systems for feedback advice message selection averaged at 87% across the centers.

Conclusions:

The dietary feedback system was used to deliver personalized dietary advice within a multi-country study. Overall, there was good agreement between the manual and automated feedback systems, giving promise to the use of automated systems for personalizing dietary advice.

Trial Registration:

Clinicaltrials.gov NCT01530139; https://clinicaltrials.gov/ct2/show/NCT01530139 (Archived by WebCite at http://www.webcitation.org/6ht5Dgj8I)

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