Publication:
Evaluation of Low- and Middle-Income Countries According to Cardiovascular Disease Risk Factors by Using Pythagorean Fuzzy AHP and TOPSIS Methods

dc.authorscopusid58838164700
dc.authorscopusid57205664363
dc.authorwosidAydin, Gizem Zevde/Iyj-2971-2023
dc.authorwosidÖzkan, Barış/Aae-8026-2019
dc.contributor.authorAydin, Gizem Zevde
dc.contributor.authorOzkan, Baris
dc.contributor.authorIDÖzkan, Bariş/0000-0001-7767-4087
dc.contributor.authorIDAydin, Gizem Zevde/0000-0002-8249-6788
dc.date.accessioned2025-12-11T01:14:16Z
dc.date.issued2024
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Aydin, Gizem Zevde] Ondokuz Mayis Univ, Fac Hlth Sci, Dept Healthcare Management, Samsun, Turkiye; [Ozkan, Baris] Ondokuz Mayis Univ, Fac Engn, Dept Ind Engn, Samsun, Turkiyeen_US
dc.descriptionÖzkan, Bariş/0000-0001-7767-4087; Aydin, Gizem Zevde/0000-0002-8249-6788;en_US
dc.description.abstractBackgroundCardiovascular disease risk factors play a crucial role in determining individuals' future health status and significantly affect health. This paper aimed to address cardiovascular disease risk factors in low- and middle-income countries using multi-criteria decision-making methods.MethodsIn line with this objective, 22 evaluation criteria were identified. Due to the unequal importance levels of the criteria, the interval-valued Pythagorean Fuzzy AHP (PF-AHP) method was employed for weighting. The TOPSIS method was utilized to rank the countries.ResultsThe application of interval-valued PF-AHP revealed that metabolic, behavioral, and economic factors are more important in contributing to disease risk. Among adults, tobacco use prevalence was identified as the most significant risk factor. According to the TOPSIS method, Lebanon, Jordan, Solomon Islands, Serbia, and Bulgaria ranked highest, while Timor Leste, Benin, Ghana, Niger, and Ethiopia ranked lowest.ConclusionsIdentifying disease risk factors and preventing or reducing risks are crucial in combating cardiovascular diseases. Therefore, it is recommended that countries ranking higher take remedial actions to reduce disease risk.en_US
dc.description.woscitationindexScience Citation Index Expanded
dc.identifier.doi10.1186/s12911-024-02769-9
dc.identifier.issn1472-6947
dc.identifier.issue1en_US
dc.identifier.pmid39609774
dc.identifier.scopus2-s2.0-85210582139
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1186/s12911-024-02769-9
dc.identifier.urihttps://hdl.handle.net/20.500.12712/42240
dc.identifier.volume24en_US
dc.identifier.wosWOS:001367130400001
dc.identifier.wosqualityQ2
dc.language.isoenen_US
dc.publisherBMCen_US
dc.relation.ispartofBMC Medical Informatics and Decision Makingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectPythagorean Fuzzy Setsen_US
dc.subjectAHPen_US
dc.subjectTOPSISen_US
dc.subjectCardiovascular Diseaseen_US
dc.subjectMultiple Criteria Decision Makingen_US
dc.titleEvaluation of Low- and Middle-Income Countries According to Cardiovascular Disease Risk Factors by Using Pythagorean Fuzzy AHP and TOPSIS Methodsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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