Designing Fuzzy Algorithms to Develop Healthy Dietary Pattern

AUTHORS

Golaleh Asghari 1 , Hanieh-Sadat Ejtahed 1 , Mohammad-Mahdi Sarsharzadeh 1 , Pantea Nazeri 1 , Parvin Mirmiran 2 , *

1 Nutrition and Endocrine Research Center, Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran

2 Department of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, National Nutrition and Food Technology Institute, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran

How to Cite: Asghari G, Ejtahed H, Sarsharzadeh M, Nazeri P, Mirmiran P. Designing Fuzzy Algorithms to Develop Healthy Dietary Pattern, Int J Endocrinol Metab. Online ahead of Print ; 11(3):154-161. doi: 10.5812/ijem.9927.

ARTICLE INFORMATION

International Journal of Endocrinology and Metabolism: 11 (3); 154-161
Published Online: June 30, 2013
Article Type: Original Article
Received: December 22, 2012
Accepted: March 16, 2013
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Abstract

Background: Fuzzy logic, a mathematical approach, defines the percentage of desirability for recommended amount of food groups and describes the range of intakes, from deficiency to excess.

Objectives: The purpose of this research was to find the best fuzzy dietary pattern that constraints energy and nutrients by the iterative algorithm.

Materials and Methods: An index is derived that reflects how closely the diet of an individual meets all the nutrient requirements set by the dietary reference intake. Fuzzy pyramid pattern was applied for the energy levels from 1000 to 4000 Kcal which estimated the range of recommended servings for seven food groups including fruits, vegetables, grains, meats, milk, oils, fat and added sugar.

Results: The optimum (lower attention upper attention) recommended servings per day for fruits, vegetables, grain, meat, dairy, and oils of the 2000 kcal diet were 4.06 (3.75-4.25), 6.69 (6.25-7.00), 5.69 (5.75-6.25), 4.94 (4.5-5.2), 2.75(2.50-3.00), and 2.56 (2.5-2.75), respectively. The fuzzy pattern met most recommended nutrient intake levels except for potassium and vitamin E, which were estimated at 98% and 69% of the dietary reference intake, respectively.

Conclusions: Using fuzzy logic provides an elegant mathematical solution for finding the optimum point of food groups in dietary pattern.

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© 2013, International Journal of Endocrinology and Metabolism. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.
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