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

Mahmood Safaei (), Elankovan A. Sundararajan (), Shahla Asadi, Mehrbakhsh Nilashi, Mohd Juzaiddin Ab Aziz, M. S. Saravanan, Maha Abdelhaq and Raed Alsaqour
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Mahmood Safaei: School of Computing & Engineering, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK
Elankovan A. Sundararajan: Centre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Shahla Asadi: School of Computing & Engineering, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK
Mehrbakhsh Nilashi: UCSI Graduate Business School, UCSI University, Cheras 56000, Kuala Lumpur, Malaysia
Mohd Juzaiddin Ab Aziz: Centre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
M. S. Saravanan: Department of Artificial Intelligence, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, Tamil Nadu, India
Maha Abdelhaq: Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
Raed Alsaqour: Department of Information Technology, College of Computing and Informatics, Saudi Electronic University, Riyadh 93499, Saudi Arabia

IJERPH, 2022, vol. 19, issue 23, 1-21

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.

Keywords: obesity; fuzzy rule-based; DEMATEL; risk factors (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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