Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methods
Abstract Background Cardiovascular 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 metho...
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| Format: | Article |
| Language: | English |
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BMC
2024-11-01
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| Series: | BMC Medical Informatics and Decision Making |
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| Online Access: | https://doi.org/10.1186/s12911-024-02769-9 |
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| author | Gizem Zevde Aydın Barış Özkan |
| author_facet | Gizem Zevde Aydın Barış Özkan |
| author_sort | Gizem Zevde Aydın |
| collection | DOAJ |
| description | Abstract Background Cardiovascular 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. Methods In 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. Results The 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. Conclusions Identifying 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. |
| format | Article |
| id | doaj-art-1d96d28b00c94f2aa831e93f867f9ba2 |
| institution | DOAJ |
| issn | 1472-6947 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj-art-1d96d28b00c94f2aa831e93f867f9ba22025-08-20T02:51:15ZengBMCBMC Medical Informatics and Decision Making1472-69472024-11-0124112010.1186/s12911-024-02769-9Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methodsGizem Zevde Aydın0Barış Özkan1Department of Healthcare Management, Faculty of Health Sciences, Ondokuz Mayıs UniversityDepartment of Industrial Engineering, Faculty of Engineering, Ondokuz Mayıs UniversityAbstract Background Cardiovascular 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. Methods In 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. Results The 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. Conclusions Identifying 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.https://doi.org/10.1186/s12911-024-02769-9Pythagorean fuzzy setsAHPTOPSISCardiovascular diseaseMultiple criteria decision making |
| spellingShingle | Gizem Zevde Aydın Barış Özkan Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methods BMC Medical Informatics and Decision Making Pythagorean fuzzy sets AHP TOPSIS Cardiovascular disease Multiple criteria decision making |
| title | Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methods |
| title_full | Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methods |
| title_fullStr | Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methods |
| title_full_unstemmed | Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methods |
| title_short | Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methods |
| title_sort | evaluation of low and middle income countries according to cardiovascular disease risk factors by using pythagorean fuzzy ahp and topsis methods |
| topic | Pythagorean fuzzy sets AHP TOPSIS Cardiovascular disease Multiple criteria decision making |
| url | https://doi.org/10.1186/s12911-024-02769-9 |
| work_keys_str_mv | AT gizemzevdeaydın evaluationoflowandmiddleincomecountriesaccordingtocardiovasculardiseaseriskfactorsbyusingpythagoreanfuzzyahpandtopsismethods AT barısozkan evaluationoflowandmiddleincomecountriesaccordingtocardiovasculardiseaseriskfactorsbyusingpythagoreanfuzzyahpandtopsismethods |