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Current Nutrition & Food Science

Editor-in-Chief

ISSN (Print): 1573-4013
ISSN (Online): 2212-3881

Research Article

Development of Decision Support System Platform for Daily Dietary Plan

Author(s): Suwimon Kooptiwoot and Bagher Javadi*

Volume 18, Issue 7, 2022

Published on: 26 April, 2022

Page: [670 - 676] Pages: 7

DOI: 10.2174/1573401318666220318102124

Price: $65

Abstract

Background: Solving health issues needs accurate and significant information regarding food consumption. Recently, data analysis and communication have provided outstanding and robust approaches to fulfill the necessity of scientific information and help in decisionmaking in many fields. Many evidence has reported that with little information, better decisions could be achieved.

Objective: This research aimed to develop the Decision Support System (DSS) for the daily dietary plan to practically help users in food consumption and health care.

Materails and Methods: The system consists of 1,940 cuisine items, including Thai and English menus. In this system, the user can set the daily dietary plan by selecting menu items with foodspecific and total calories. Overall calories of selected menu items would be calculated automatically. The user can see the normal range of calories required based on gender with the help of the baseline (normal office person).

Results: This system can help users to become familiar with a better daily dietary plan, food calories, and health care easily. Furthermore, experts (doctors) can improve their learning experiences by formulating and adjusting the Decision Support System (DSS) for patients in special need. The easiness and usefulness of this system are evaluated by 119 users using a Likert scale (1=least, 5=most). The result, on average, is noted to be 4.58.

Conclusion: The Decision Support System (DSS) is developed for the daily dietary plan. The accessibility to the system is via personal computer (PC), smartphone, and tablet with an internet connection. For future work, this DSS can improve by connecting the platform with health care providers via sharing the data for more online support.

Keywords: Decision Support System, daily dietary plan, food calories, Thai and English menu items, computational daily dietary plan, food-DSS for special needs.

Graphical Abstract

[1]
Omotosho A, Ayegba P. Medication adherence: A review and lessons for developing countries. Int J Online Biomed 2019; 15(11): 104-23.
[http://dx.doi.org/10.3991/ijoe.v15i11.10647]
[2]
Flegal KM, Kruszon-Moran D, Carroll MD, Fryar CD, Ogden CL. Trends in obesity among adults in the United States, 2005 to 2014. JAMA 2016; 315(21): 2284-91.
[http://dx.doi.org/10.1001/jama.2016.6458] [PMID: 27272580]
[3]
Sattigere VD, Ramesh Kumar P, Prakash V. Science-based regulatory approach for safe nutraceuticals. J Sci Food Agric 2020; 100(14): 5079-82.
[http://dx.doi.org/10.1002/jsfa.9381] [PMID: 30264462]
[4]
Mariapun J, Ng C-W, Hairi NN. The gradual shift of overweight, obesity, and abdominal obesity towards the poor in a multi-ethnic developing country: Findings from the Malaysian National Health and Morbidity Surveys. J Epidemiol 2018; 28(6): 279-86.
[http://dx.doi.org/10.2188/jea.JE20170001] [PMID: 29657257]
[5]
Ng M, Fleming T, Robinson M, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 384(9945): 766-81.
[http://dx.doi.org/10.1016/S0140-6736(14)60460-8] [PMID: 24880830]
[6]
Bales CW, Ritchie CS. Handbook of clinical nutrition and aging. Totowa, NJ: Springer 2009.
[http://dx.doi.org/10.1007/978-1-60327-385-5]
[7]
Rousham EK, Pradeilles R, Akparibo R, et al. Dietary behaviours in the context of nutrition transition: A systematic review and meta-analyses in two African countries. Public Health Nutr 2020; 23(11): 1948-64.
[http://dx.doi.org/10.1017/S1368980019004014] [PMID: 32157986]
[8]
Aucoin M, LaChance L, Clouthier SN, Cooley K. Dietary modification in the treatment of schizophrenia spectrum disorders: A systematic review. World J Psychiatry 2020; 10(8): 187-201.
[http://dx.doi.org/10.5498/wjp.v10.i8.187] [PMID: 32874956]
[9]
Picard K, Mager D, Richard C. How food processing impacts hyperkalemia and hyperphosphatemia management in chronic kidney disease. Can J Diet Pract Res 2020; 81(3): 132-6.
[http://dx.doi.org/10.3148/cjdpr-2020-003] [PMID: 32072822]
[10]
Frankenfield DC. Bias and accuracy of resting metabolic rate equations in non-obese and obese adults. Clin Nutr 2013; 32(6): 976-82.
[http://dx.doi.org/10.1016/j.clnu.2013.03.022] [PMID: 23631843]
[11]
Pell C, Allotey P, Evans N, et al. Coming of age, becoming obese: A cross-sectional analysis of obesity among adolescents and young adults in Malaysia. BMC Public Health 2016; 16(1): 1082.
[http://dx.doi.org/10.1186/s12889-016-3746-x] [PMID: 27737680]
[12]
Mitsea E, Drigas A. A journey into the metacognitive learning strategies. Int J Online Biomed 2019; 15(14): 4-20.
[http://dx.doi.org/10.3991/ijoe.v15i14.11379]
[13]
Berthoud H-R. Mind versus metabolism in the control of food intake and energy balance. Physiol Behav 2004; 81(5): 781-93.
[http://dx.doi.org/10.1016/j.physbeh.2004.04.034] [PMID: 15234184]
[14]
Chesani F, Cota G, Gavanelli M, Lamma E, Mello P, Riguzzi F. Declarative and mathematical programming approaches to decision support systems for food recycling. Eng Appl Artif Intell 2020; 95: 103861.
[http://dx.doi.org/10.1016/j.engappai.2020.103861]
[15]
Gand M, Mattheus W, Roosens N, et al. A genoserotyping system for a fast and objective identification of Salmonella serotypes commonly isolated from poultry and pork food sectors in Belgium. Food Microbiol 2020; 91: 103534.
[http://dx.doi.org/10.1016/j.fm.2020.103534] [PMID: 32539977]
[16]
Alvelos H, Teixeira L, Ramos ALFA, Xambre AR. SysSensory: A web based decision support system for sensory analysis. J Inf Technol Res 2020; 13(2): 60-74.
[http://dx.doi.org/10.4018/JITR.2020040104]
[17]
Malard JJ, Adamowski JF, Díaz MR, et al. Agroecological food web modelling to evaluate and design organic and conventional agricultural systems. Ecol Modell 2020; 421: 108961.
[http://dx.doi.org/10.1016/j.ecolmodel.2020.108961]
[18]
Greenhawt M. Shared decision-making in the care of a patient with food allergy. Ann Allergy Asthma Immunol 2020; 125(3): 262-7.
[http://dx.doi.org/10.1016/j.anai.2020.05.031] [PMID: 32504666]
[19]
Arivazghan N, Kottilingam K. Remote diagnosis decision support system for breast cancer screen. Int J Adv Trends Comput Sci 2020; 9(5): 7785-8.
[http://dx.doi.org/10.30534/ijatcse/2020/124952020]
[20]
Abd-Elmabod SK, Muñoz-Rojas M, Jordán A, et al. Climate change impacts on agricultural suitability and yield reduction in a Mediterranean region. Geoderma 2020; 374: 114453.
[http://dx.doi.org/10.1016/j.geoderma.2020.114453]
[21]
Hermanuadi D, Brilliantina A, Novitasari E. Decision support system for selecting strategy of agroindustry development based on “Tape”. IOP Conf Ser Earth Environ Sci 2020; 411: 012016.
[22]
Holzapfel E, Lillo-Saavedra M, Rivera D, et al. A satellite-based ex post analysis of water management in a blueberry orchard. Comput Electron Agric 2020; 176: 105635.
[http://dx.doi.org/10.1016/j.compag.2020.105635]
[23]
Massaro A, Savino N, Galiano A. Agri-photonics in precision agriculture. 2020 22nd International Conference on Transparent Optical Networks (ICTON). 2020. Jul 19-23; Bari, Italy.
[24]
Birtane S, Canayaz E, Altikardes ZA, Korkmaz H. Development of decision support system using Mamdani type fuzzy logic clusters for metabolic syndrome risk assesment. In: 2017 Medical Technologies National Congress (TIPTEKNO) 2017 Oct 12-14 Trabzon, Turkey.
[http://dx.doi.org/10.1109/TIPTEKNO.2017.8238035]
[25]
Lakhno VA, Kartbayev TS, Turginbayeva AA, Alimseitova ZK, Beketova GS. Analysis of existing and development prospects of decision support systems for evaluating investment projects in the field of enterprise digitalization. Int J Adv Trends Comput Sci 2020; 9(5): 8533-9.
[http://dx.doi.org/10.30534/ijatcse/2020/233952020]
[26]
Vital-Soto A, Azab A, Baki MF. Mathematical modeling and a hybridized bacterial foraging optimization algorithm for the flexible job-shop scheduling problem with sequencing flexibility. J Manuf Syst 2020; 54: 74-93.
[http://dx.doi.org/10.1016/j.jmsy.2019.11.010]
[27]
Knapczyk A, Francik S, Wróbel M, Jewiarz M, Mudryk K. Decision support systems for scheduling tasks in biosystems engineering. E3S Web Conf 2019. 132: 01008.
[http://dx.doi.org/10.1051/e3sconf/201913201008]
[28]
Simeoni P, Nardin G, Ciotti GJE. Planning and design of sustainable smart multi energy systems. The case of a food industrial district in Italy. Energy 2018; 163: 443-56.
[29]
Udias A, Pastori M, Dondeynaz C, et al. A decision support tool to enhance agricultural growth in the Mékrou river basin (West Africa). Comput Electron Agric 2018; 154: 467-81.
[30]
Reca J, Trillo C, Sánchez J, Martínez J, Valera D. Optimization model for on-farm irrigation management of Mediterranean greenhouse crops using desalinated and saline water from different sources. Agric Syst 2018; 166: 173-83.
[31]
Nie Y, Wu Y, Zhao J, et al. Is the finer the better for municipal solid waste (MSW) classification in view of recyclable constituents? A comprehensive social, economic and environmental analysis. Waste Manag 2018; 79: 472-80.
[http://dx.doi.org/10.1016/j.wasman.2018.08.016] [PMID: 30343777]
[32]
Pusic M, Ansermino M. Clinical decision support systems. B C Med J 2004; 46(5): 236-9.
[33]
Farshidi S, Jansen S, de Jong R, Brinkkemper S. A decision support system for software technology selection. J Decis Syst 2018; 27(sup1): 98-110.
[34]
Zhang Z, Li Q. An open urban emergency decision support system. Int Arch Photogramm Remote Sens Spat Inf Sci 2008; 1123-8.
[35]
Ngwenya B. Application of decision support systems and its impact on human resources output: A study of selected universities in Zimbabwe. Int J Comput Sci 2013; 1(3): 46-54.
[http://dx.doi.org/10.12691/jcsa-1-3-4]
[36]
Velmurugan MS, Narayanasamy K. Application of decision support system in e-commerce. Commun IBIMA 2008; 5: 156-69.
[37]
Wright D, Dey P, Brammer J, Hunt P. Bioenergy decision support systems: Worth the effort? In: World Renewable Energy Congress 2011 May 8-13 Sweden Linköping.
[http://dx.doi.org/10.3384/ecp110579]
[38]
Rybnytska O, Burstein F, Rybin AV, Zaslavsky A. Decision support for optimizing waste management. J Decis Syst 2018; 27(sup1): 68-78.
[39]
Kašpar J, Bettinger P, Vacik H, Marušák R, Garcia-Gonzalo J. Decision support approaches in adaptive forest management. Forests 2018; 9(4): 215.
[40]
Baggio R, Caporarello L. Decision support systems in a tourism destination: Literature survey and model building. In: Proceedings ItAIS-2nd Conference of the Italian chapter of AIS (Association for Information Systems). 2005 Dec 1-2; Verona, Italy.
[41]
Korovin IS, Kalyaev IA. Modern decision support systems in oil industry: Types, approaches and applications. In: Proceedings of the 2015 International Conference on Test, Measurement and Computational Methods. 2015. Nov; Atlantis Press. 141-4.
[http://dx.doi.org/10.2991/tmcm-15.2015.35]
[42]
Chan JH, Limsuwan T. Web-based decision support system for school meal planning. Int J Inf Syst Soc Change 2012; 3(1): 10-2.
[http://dx.doi.org/10.4018/jissc.2012010102]
[43]
Kashima T, Matsumoto S, Ishii H. Decision support system for menu recommendation using rough sets. Int J Innov Comput, Inf Control 2011; 7(5): 2799-808.
[44]
Jung H, Chung K. Knowledge-based dietary nutrition recommendation for obese management. Inf Technol Manage 2016; 17(1): 29-42.
[http://dx.doi.org/10.1007/s10799-015-0218-4]
[45]
Smethers AD, Rolls BJ. Dietary management of obesity: Cornerstones of healthy eating patterns. Med Clin North Am 2018; 102(1): 107-24.
[http://dx.doi.org/10.1016/j.mcna.2017.08.009] [PMID: 29156179]
[46]
Bray GA, Siri-Tarino PW. The role of macronutrient content in the diet for weight management. Endocrinol Metab Clin 2016; 45(3): 581-604.
[http://dx.doi.org/10.1016/j.ecl.2016.04.009] [PMID: 27519132]
[47]
Makris A, Foster GD. Dietary approaches to the treatment of obesity. Psychiatr Clin North Am 2011; 34(4): 813-27.
[http://dx.doi.org/10.1016/j.psc.2011.08.004] [PMID: 22098806]
[48]
Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: A randomized trial. JAMA 2005; 293(1): 43-53.
[http://dx.doi.org/10.1001/jama.293.1.43] [PMID: 15632335]
[49]
Al-Dhuhli BA, Al-Gadidi BS, Al-Alawi HH, Al-Busaidi KA. Developing a nutrition and diet expert system prototype. In: 21st International Business Information Management Association Conference. 2013 Jun 27-28; Vienna, Australia. 1368-75.
[50]
Hong S-M, Cho J-Y, Lee J-H, Kim G, Kim M-C. NutriSonic web expert system for meal management and nutrition counseling with nutrient time-series analysis, e-food exchange and easy data transition. Nutr Res Pract 2008; 2(2): 121-9.
[http://dx.doi.org/10.4162/nrp.2008.2.2.121] [PMID: 20126376]
[51]
Kovasznai G. Developing an expert system for diet recommendation. In: 2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI). 2011 May 19-21; Timisoara, Romania.

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