Evidence map›Paper›PMID 36497509›Full record

ArticleInternational journal of environmental research and public health2022

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, Raed Alsaqour

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
4.8field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 6 institutions in 4 countries.

Mahmood SafaeiSchool of Computing & Engineering, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK.ORCID 0000-0002-3924-6927
Elankovan A SundararajanCentre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia.ORCID 0000-0003-2711-0659
Shahla AsadiSchool of Computing & Engineering, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK.
Mehrbakhsh NilashiUCSI Graduate Business School, UCSI University, Cheras 56000, Kuala Lumpur, Malaysia.ORCID 0000-0003-0099-8299
Mohd Juzaiddin Ab AzizCentre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia.
M S SaravananDepartment of Artificial Intelligence, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, Tamil Nadu, India.
Maha AbdelhaqDepartment of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Raed AlsaqourDepartment of Information Technology, College of Computing and Informatics, Saudi Electronic University, Riyadh 93499, Saudi Arabia.ORCID 0000-0001-8227-9110
National University of Malaysia · MYUniversity of Gloucestershire · GBPrincess Nourah bint Abdulrahman University · SASaudi Electronic University · SASaveetha University · INUCSI University · MY

Funding

Princess Nourah bint Abdulrahman University Researchers Supporting PNURSP2022R97Universiti Kebangsaan Malaysia, 459 under High Impact Research Grant DIP-2018-041
6 · The paper itself

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.

Indexed as

Diabetes Mellitus, Type 2ObesityAdultFuzzy LogicHumansOverweightRisk FactorsDEMATELfuzzy rule-basedobesityrisk factors

Identifiers

PMID36497509
PMCPMC9740807
OpenAlexW4309587971

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.