Document Type : Systematic Review


1 PhD Candidate, Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran

2 PhD, Professor, Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran

3 MD, Professor, Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran

4 PhD, Professor, Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran

5 PhD, Associate Professor, Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran

6 MD, Associate Professor, Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran

7 PhD Candidate, Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran\

8 PhD student, Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran


Background: Nutrition informatics has become a novel approach for registered dietitians to practice in this field and make a profit for health care. Recommendation systems considered as an effective technology into aid users to adjust their eating behavior and achieve the goal of healthier food and diet. The purpose of this study is to review nutrition recommendation systems (NRS) and their characteristics for the first time.
Material and Methods: The systematic review was conducted using a comprehensive selection of scientific databases as reference sources, allowing access to diverse publications in the field. The process of articles selection was based on the PRISMA strategy. We identified keywords from our initial research, MeSH database and expert’s opinion. Databases of PubMed, Web of Sciences, Scopus, Embase, and IEEE were searched. After evaluating, they obtained records from databases by two independent reviewers and inclusion and exclusion criteria were applied to each retrieved work to select those of interest. Finally, 25 studies were included.
Results: Hybrid recommender systems and knowledge-based recommender systems with 40% and 32%, respectively, were the mostly recommender types used in NRS. In NRS, rule-based and ontology techniques were used frequently. The frequented platform that applied in NRS was a mobile application with 28%.
Conclusion: If NRS was properly designed, implemented and finally evaluated, it could be used as an effective tool to improve nutrition and promote a healthy lifestyle. This study can help to inform specialists in the nutrition informatics domain, which was necessary to design and develop NRS.


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