Research Article
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Comparison of countries in European region according to risk factors of noncommunicable diseases by APLOCO method

Year 2024, Volume: 10 Issue: 3, 257 - 267, 31.12.2024
https://doi.org/10.30569/adiyamansaglik.1537592

Abstract

Aim: The aim of the study was to compare countries in the WHO European Region according to key risk factors of NCDs.
Materials and Methods: Target population of study consists of 37 European Region countries. Weights of key risk factors were determined by Shannon Entropy and NMV weighting methods. APLOCO, one of the MCDM methods, was used to evaluate countries according to decision criteria.
Results: There is a significant and very strong positive monotonic relationship between score rankings obtained from NMV-based APLOCO and Shannon Entropy-based APLOCO methods. According to both the NMV-based and Shannon Entropy-based APLOCO methods, 14 European countries have above-average while 23 have below-average scores.
Conclusion: NCD risk factors are more prevalent in countries of the European Region with below-average NCD prevalence. NCDs may increase in countries of this region due to high risk factor prevalence.

Ethical Statement

As the data used for the study has been publicly published by WHO, there is no need for ethics committee approval.

Supporting Institution

The author received no financial support for the study.

References

  • WHO Regional Office for Europe. Reducing noncommunicable diseases: a signature roadmap for the WHO European Region. Copenhagen: WHO Regional Office for Europe; 2022.
  • WHO Regional Office for Europe. The European Health Report 2021: Taking stock of the health-related Sustainable Development Goals in the COVID-19 era with a focus on leaving no one behind, 2022.
  • Institute for Health Metrics and Evaluation (IHME). GBD compare, 2019. https://vizhub.healthdata.org/gbd-compare/
  • Nugent R, Bertram MY, Jan S, Niessen LW, Sassi F, Jamison DT et al. Investing in non-communicable disease prevention and management to advance the Sustainable Development Goals. Lancet. 2018;391(10134):2029–35. https://doi.org/10.1016/S0140-6736(18)30667-6.
  • WHO Regional Office for Europe. Commercial determinants of noncommunicable diseases in the WHO European Region, 2024. https://iris.who.int/handle/10665/376957
  • World Health Organization (WHO). Noncommunicable Diseases Data Portal. 2024.
  • R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2024.
  • Bulut T. A New Multi Criteria Decision Making Method: Approach of Logarithmic Concept (APLOCO).International Journal of Artificial Intelligence and Applications (IJAIA). 2018;(9):1. https://doi.org/10.5121/ijaia.2018.9102.
  • Özkaynak, E. Development of Node Weighted Link Prediction Methods In Complex Networks. PhD Thesis. Karabuk Univeresity, 2020.
  • Fındık, O., Özkaynak, E. Link prediction based on node weighting in complex networks. Soft Computing. 2021;25:2467-2482. https://doi.org/10.1007/s00500-020-05314-8.
  • Mishra AK, Joshi N, Mathur I. A fuzzy based integrated model for identification of vital node in terrorist network using logarithmic concept. Journal of Intelligent & Fuzzy Systems. 2020;39(3):3617-3631. https://doi.org/10.3233/JIFS-191899.
  • Bulut T and Genç B. (2022). R’da Çok Kriterli Karar Verme Yöntemi Olarak APLOCO’nun Fonksiyonu ve Grafiği. https://tevfikbulut.net/cok-kriterli-karar-verme-yontemi-olarak-aploconun-fonksiyonu-ve-grafigi/.
  • Taylor, JMG. Kendall’s and Spearman’s Correlation Coefficients in the Presence of a Blocking Variable. Biometrics. 1987;43(2):409-416. https://doi.org/10.2307/2531822.
  • Lee HC and Chang CT. Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and Sustainable Energy Reviews. 2018;92:883-896. https://doi.org/10.1016/j.rser.2018.05.007.
  • Huang SW, Liou JJH, Chuang HH and Tzeng GH. Using a Modified VIKOR Technique for Evaluating and Improving the National Healthcare System Quality. Mathematics. 2021;9(1349):1-21.https://doi.org/10.3390/math9121349.
  • Pramanik PKD, Biswas S, Pal S, Marinković D, Choudhury P. A Comparative Analysis of Multi-Criteria Decision-Making Methods for Resource Selection in Mobile Crowd Computing. Symmetry. 2021;13:1713. https://doi.org/10.3390/sym13091713.
  • Shekhovtsov A. How Strongly Do Rank Similarity Coefficients Differ Used in Decision Making Problems?. Procedia Computer Science. 2021;192:4570-4577. https://doi.org/10.1016/j.procs.2021.09.235.
  • Bulut T. (2017). Çok Kriterli Karar Verme (ÇKKV) Modellerinde Kriterlerin Ağırlıklandırılmasına Yönelik Bir Model Önerisi: Normalize Edilmiş Maksimum Değerler [NMD] Metodu (Normalized Maximum Values [NMV] Method). https://tevfikbulutcom.wordpress.com/2017/06/21/coklu-karar-verme-modellerinde-kriterlerin-agirliklandirilmasina-yonelik-model-onerisi/.
  • Bulut T. (2022). Normalize Edilmiş Maksimum Değerler [NMD] Metodunun Teorik Çerçevesi. https://tevfikbulut.net/normalize-edilmis-maksimum-degerler-nmd-metodu/.
  • Shannon CE. A mathematical theory of communication. The Bell System Technical Journal. 1948;27(3):379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x.
  • Wang T and Lee H. Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications. 2009;36:8980-8985. https://doi.org/10.1016/j.eswa.2008.11.035.
  • Shemshadi A, Shirazi H, Toreihi M and Tarokh MJ. A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Systems with Applications. 2011;38:12160-12167. https://doi.org/10.1016/j.eswa.2011.03.027.
  • Song M, Zhu Q, Peng J, Santibanez Gonzalez EDR. Improving the evaluation of cross efficiencies: A method based on Shannon entropy weight. Computers & Industrial Engineering. 2017;112:99-106. https://doi.org/10.1016/j.cie.2017.07.023.
  • Ezzati M, Pearson-Stuttard J, Bennett JE & Mathers, CD. Acting on non-communicable diseases in low- and middle-income tropical countries. Nature. 2018;559:507-516.
  • Tolonen H, Reinikainen J, Zhou Z, Härkänen T, Männistö S, Jousilahti P et al. Development of non-communicable disease risk factors in Finland: projections up to 2040. Scandinavian Journal of Public Health. 2023;51(8):1231-1238. https://doi.org/10.1177/14034948221110025.
  • World Health Organization (WHO). World health statistics 2023: monitoring health for the SDGs, Sustainable Development Goals. 2023.
  • World Health Organization (WHO).Global status report on noncommunicable diseases 2010. 2010. https://iris.who.int/bitstream/handle/10665/44579/9789240686458_eng.pdf
  • Habtemichael M, Molla M & Tassew B. Catastrophic out-of-pocket payments related to non-communicable disease multimorbidity and associated factors, evidence from a public referral hospital in Addis Ababa Ethiopia. BMC Health Serv Res. 2024;24:896. https://doi.org/10.1186/s12913-024-11392-3.
  • Bahadır O, Türkmençalıkoğlu H, & Bonyah E. Evaluation of The Significance Grades of The Problems Experienced by Mathematics Teachers in Distance Education in The Covid-19 Pandemic by The Entropy Method. Indonesian Journal of Science and Mathematics Education. 2022;5(3):250-260. https://doi.org/10.24042/ijsme.v5i3.10599.

Avrupa bölgesindeki ülkelerin APLOCO yöntemiyle bulaşıcı olmayan hastalıkların risk faktörlerine göre karşılaştırılması

Year 2024, Volume: 10 Issue: 3, 257 - 267, 31.12.2024
https://doi.org/10.30569/adiyamansaglik.1537592

Abstract

Amaç: Çalışmanın amacı, DSÖ Avrupa Bölgesi'ndeki ülkeleri bulaşıcı olmayan hastalıkların temel risk faktörlerine göre karşılaştırmaktır.
Gereç ve Yöntemler: Çalışmanın hedef popülasyonunu Avrupa Bölgesi’ndeki 37 ülke oluşturmaktadır. Karar kriteri olarak kullanılan temel risk faktörlerinin ağırlıkları Shannon Entropi ve NMD objektif ağırlıklandırma yöntemleri ile belirlenmiştir. Ülkeleri karar kriterlerine göre değerlendirmek için ÇKKV yöntemlerinden biri olan APLOCO kullanılmıştır.
Bulgular: NMD tabanlı APLOCO ve Shannon Entropi tabanlı APLOCO yöntemlerinden elde edilen puan sıralamaları arasında anlamlı ve çok güçlü pozitif monoton bir ilişki vardır. NMD tabanlı APLOCO ve Shannon Entropi tabanlı APLOCO yöntemlerine göre Avrupa Bölgesi'nde ortalamanın üzerinde puana sahip ülke sayısı 14, ortalamanın altında puana sahip ülke sayısı ise 23'tür.
Sonuç: Bulaşıcı olmayan hastalık risk faktörlerinin prevelansı, ortalamanın altındaki Avrupa Bölgesi ülkelerinde daha yüksektir. Bulaşıcı olmayan hastalık risk faktörlerinin yüksek prevalansı, bu bölgedeki bulaşıcı olmayan hastalıkların prevalansını artırabilir.

Ethical Statement

As the data used for the study has been publicly published by WHO, there is no need for ethics committee approval.

Supporting Institution

The author received no financial support for the study.

References

  • WHO Regional Office for Europe. Reducing noncommunicable diseases: a signature roadmap for the WHO European Region. Copenhagen: WHO Regional Office for Europe; 2022.
  • WHO Regional Office for Europe. The European Health Report 2021: Taking stock of the health-related Sustainable Development Goals in the COVID-19 era with a focus on leaving no one behind, 2022.
  • Institute for Health Metrics and Evaluation (IHME). GBD compare, 2019. https://vizhub.healthdata.org/gbd-compare/
  • Nugent R, Bertram MY, Jan S, Niessen LW, Sassi F, Jamison DT et al. Investing in non-communicable disease prevention and management to advance the Sustainable Development Goals. Lancet. 2018;391(10134):2029–35. https://doi.org/10.1016/S0140-6736(18)30667-6.
  • WHO Regional Office for Europe. Commercial determinants of noncommunicable diseases in the WHO European Region, 2024. https://iris.who.int/handle/10665/376957
  • World Health Organization (WHO). Noncommunicable Diseases Data Portal. 2024.
  • R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2024.
  • Bulut T. A New Multi Criteria Decision Making Method: Approach of Logarithmic Concept (APLOCO).International Journal of Artificial Intelligence and Applications (IJAIA). 2018;(9):1. https://doi.org/10.5121/ijaia.2018.9102.
  • Özkaynak, E. Development of Node Weighted Link Prediction Methods In Complex Networks. PhD Thesis. Karabuk Univeresity, 2020.
  • Fındık, O., Özkaynak, E. Link prediction based on node weighting in complex networks. Soft Computing. 2021;25:2467-2482. https://doi.org/10.1007/s00500-020-05314-8.
  • Mishra AK, Joshi N, Mathur I. A fuzzy based integrated model for identification of vital node in terrorist network using logarithmic concept. Journal of Intelligent & Fuzzy Systems. 2020;39(3):3617-3631. https://doi.org/10.3233/JIFS-191899.
  • Bulut T and Genç B. (2022). R’da Çok Kriterli Karar Verme Yöntemi Olarak APLOCO’nun Fonksiyonu ve Grafiği. https://tevfikbulut.net/cok-kriterli-karar-verme-yontemi-olarak-aploconun-fonksiyonu-ve-grafigi/.
  • Taylor, JMG. Kendall’s and Spearman’s Correlation Coefficients in the Presence of a Blocking Variable. Biometrics. 1987;43(2):409-416. https://doi.org/10.2307/2531822.
  • Lee HC and Chang CT. Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and Sustainable Energy Reviews. 2018;92:883-896. https://doi.org/10.1016/j.rser.2018.05.007.
  • Huang SW, Liou JJH, Chuang HH and Tzeng GH. Using a Modified VIKOR Technique for Evaluating and Improving the National Healthcare System Quality. Mathematics. 2021;9(1349):1-21.https://doi.org/10.3390/math9121349.
  • Pramanik PKD, Biswas S, Pal S, Marinković D, Choudhury P. A Comparative Analysis of Multi-Criteria Decision-Making Methods for Resource Selection in Mobile Crowd Computing. Symmetry. 2021;13:1713. https://doi.org/10.3390/sym13091713.
  • Shekhovtsov A. How Strongly Do Rank Similarity Coefficients Differ Used in Decision Making Problems?. Procedia Computer Science. 2021;192:4570-4577. https://doi.org/10.1016/j.procs.2021.09.235.
  • Bulut T. (2017). Çok Kriterli Karar Verme (ÇKKV) Modellerinde Kriterlerin Ağırlıklandırılmasına Yönelik Bir Model Önerisi: Normalize Edilmiş Maksimum Değerler [NMD] Metodu (Normalized Maximum Values [NMV] Method). https://tevfikbulutcom.wordpress.com/2017/06/21/coklu-karar-verme-modellerinde-kriterlerin-agirliklandirilmasina-yonelik-model-onerisi/.
  • Bulut T. (2022). Normalize Edilmiş Maksimum Değerler [NMD] Metodunun Teorik Çerçevesi. https://tevfikbulut.net/normalize-edilmis-maksimum-degerler-nmd-metodu/.
  • Shannon CE. A mathematical theory of communication. The Bell System Technical Journal. 1948;27(3):379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x.
  • Wang T and Lee H. Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications. 2009;36:8980-8985. https://doi.org/10.1016/j.eswa.2008.11.035.
  • Shemshadi A, Shirazi H, Toreihi M and Tarokh MJ. A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Systems with Applications. 2011;38:12160-12167. https://doi.org/10.1016/j.eswa.2011.03.027.
  • Song M, Zhu Q, Peng J, Santibanez Gonzalez EDR. Improving the evaluation of cross efficiencies: A method based on Shannon entropy weight. Computers & Industrial Engineering. 2017;112:99-106. https://doi.org/10.1016/j.cie.2017.07.023.
  • Ezzati M, Pearson-Stuttard J, Bennett JE & Mathers, CD. Acting on non-communicable diseases in low- and middle-income tropical countries. Nature. 2018;559:507-516.
  • Tolonen H, Reinikainen J, Zhou Z, Härkänen T, Männistö S, Jousilahti P et al. Development of non-communicable disease risk factors in Finland: projections up to 2040. Scandinavian Journal of Public Health. 2023;51(8):1231-1238. https://doi.org/10.1177/14034948221110025.
  • World Health Organization (WHO). World health statistics 2023: monitoring health for the SDGs, Sustainable Development Goals. 2023.
  • World Health Organization (WHO).Global status report on noncommunicable diseases 2010. 2010. https://iris.who.int/bitstream/handle/10665/44579/9789240686458_eng.pdf
  • Habtemichael M, Molla M & Tassew B. Catastrophic out-of-pocket payments related to non-communicable disease multimorbidity and associated factors, evidence from a public referral hospital in Addis Ababa Ethiopia. BMC Health Serv Res. 2024;24:896. https://doi.org/10.1186/s12913-024-11392-3.
  • Bahadır O, Türkmençalıkoğlu H, & Bonyah E. Evaluation of The Significance Grades of The Problems Experienced by Mathematics Teachers in Distance Education in The Covid-19 Pandemic by The Entropy Method. Indonesian Journal of Science and Mathematics Education. 2022;5(3):250-260. https://doi.org/10.24042/ijsme.v5i3.10599.
There are 29 citations in total.

Details

Primary Language English
Subjects Preventative Health Care, Health Promotion, Social Determinants of Health
Journal Section Research Article
Authors

Tevfik Bulut 0000-0002-3668-7436

Early Pub Date December 24, 2024
Publication Date December 31, 2024
Submission Date August 23, 2024
Acceptance Date October 8, 2024
Published in Issue Year 2024 Volume: 10 Issue: 3

Cite

AMA Bulut T. Comparison of countries in European region according to risk factors of noncommunicable diseases by APLOCO method. ADYÜ Sağlık Bilimleri Derg. December 2024;10(3):257-267. doi:10.30569/adiyamansaglik.1537592