Designing and Evaluating a Nutrition Recommender System for Improving Food Security in a Developing Country

Shahabeddin Abhari; Kamran B Lankarani; Leila Azadbakht; Sharareh R Niakan Kalhori; Reza Safdari; Sara Emamgholipour Sefiddashti; Ali Garavand; Saeed Barzegari; Sahand Moradi

doi:10.34172/aim.2023.93

Designing and Evaluating a Nutrition Recommender System for Improving Food Security in a Developing Country

Arch Iran Med. 2023 Nov 1;26(11):629-641. doi: 10.34172/aim.2023.93.

Authors

Affiliations

¹ Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
² Ubiquitous Health Technology Lab, School of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, ON, CAnada.
³ Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
⁴ Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran.
⁵ Scie Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig, Institute of Technology and Hannover Medical School, Braunschweig, Germany.
⁶ Department of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
⁷ Department of Health Information Technology, School of Allied Medical Sciences, Lorestan University of Medical Sciences, Khorramabad, Iran.
⁸ Department of Paramedicine, Amol School of Paramedical Sciences, Mazandaran University of Medical Sciences, Sari, Iran.
⁹ The York Management School, University of York, York, UK.

Abstract

Background: Due to the increased price of foods in recent years and the diminished food security in Iran, nutrition recommender systems can suggest the most suitable and affordable foods and diets to users based on their health status and food preferences. Objective: The present study aimed to design and evaluate a recommender system to suggest healthy and affordable meals and provide a tele-nutrition consulting service.

Methods: This applied three-phase study was conducted in 2020. In the first stage, the food items' daily prices were extracted from credible sources, and accordingly, meals were placed in three price categories. After conducting a systematic review of similar systems, the requirements and data elements were specified and confirmed by 10 nutritionists and 10 health information management and medical informatics experts. In the second phase, the software was designed and developed based on the findings. In the third phase, system usability was evaluated by four experts based on Nielsen's heuristic evaluation.

Results: Initially, 72 meals complying with nutritional principles were placed in three price categories. Following a literature review and expert survey, 31 data elements were specified for the system, and the experts confirmed system requirements. Based on the information collected in the previous stage, the Web-based software TanSa in the Persian language was designed, developed, and presented on a unique domain. During the evaluation, the mean severity of the problems associated with Nielsen's 10 principles was 1.2, which is regarded as minor.

Conclusion: To promote food security, the designed system recommends healthy, nutritional, and affordable meals to individuals and households based on user characteristics.

Keywords: Food security; Health informatics; Meal; Nutrition; Recommender systems.

© 2023 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Publication types

Systematic Review

MeSH terms

Developing Countries*
Diet
Food Security
Humans
Nutritional Status
Software*