A Hybrid MCDM Approach Based on Fuzzy-Logic and DEMATEL to Evaluate Adult Obesity

Safaei, Mahmood ORCID: 0000-0002-3924-6927, Sundararajan, Elankovan, Asadi, Shahla ORCID: 0000-0002-8199-2122, Nilashi, Mehrbakhsh, Aziz, Mohd Juzaiddin Ab, Saravanan, M. S., Abdelhaq, Maha and Alsaqour, Raed (2022) A Hybrid MCDM Approach Based on Fuzzy-Logic and DEMATEL to Evaluate Adult Obesity. International Journal of Environmental Research and Public Health, 19 (23). Art 15432. doi:10.3390/ijerph192315432

Preview

Text (Peer Reviewed Version) 12091 Safaei et al (2022) A_Hybrid_MCDM_Approach_Based_on_Fuzy_Logic_and_DEMATEL_to_Evaluate_Adult_Obesity.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (1MB) | Preview

Abstract

Obesity and its complications is one of the main issues in today’s world and is increasing rapidly. A wide range of non-contagious diseases, for instance, diabetes type 2, cardiovascular, high blood pressure and stroke, numerous types of cancer, and mental health issues are formed following obesity. According to the WHO, Malaysia is the sixth Asian country with an adult population suffering from obesity. Therefore, identifying risk factors associated with obesity among Malaysian adults is necessary. For this purpose, this study strives to investigate and assess the risk factors related to obesity and overweight in this country. A quantitative approach was employed by surveying 26 healthcare professionals by questionnaire. Collected data were analyzed with the DEMATEL and Fuzzy Rule-Based methods. We found that lack of physical activity, insufficient sleep, unhealthy diet, genetics, and perceived stress were the most significant risk factors for obesity.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Obesity; Fuzzy Rule-Based; Dematal; Risk Factors
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine > RA645.O23 Body mass. Adult obesity
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas:	Applied Business & Technology
Depositing User:	Kate Greenaway
Date Deposited:	16 Dec 2022 16:41
Last Modified:	31 Oct 2023 12:06
URI:	https://eprints.glos.ac.uk/id/eprint/12091

University Staff: Request a correction | Repository Editors: Update this record