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EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS

Yıl 2025, Cilt: 28 Sayı: 1, 65 - 80, 26.03.2025
https://doi.org/10.61859/hacettepesid.1581132

Öz

The objective of this study is to apply cluster analysis to OECD countries in order to identify country groups with similar Human Development Index (HDI), mortality and health expenditure profiles. In order to achieve the aforementioned aim, the research employed a correlation analysis and K-means clustering method to analyse a number of variables for 38 OECD Countries with 2020 data. These included the HDI, maternal, infant and under-five child mortality rates, the share of total health expenditure and the share of public health expenditure. The results demonstrated a significant and positive correlation between HDI and total health expenditure, as well as public health expenditure. Additionally, a negative and strong relationship was observed between HDI and maternal, infant and child mortality rates. The cluster analysis yielded the following results: 13 countries were assigned to cluster 1, 3 to cluster 2, and 13 to cluster 3. Furthermore, it was observed that Colombia, Mexico and Turkey, which are situated within the same cluster, exhibited the lowest HDI and the lowest proportion allocated to health expenditures with the highest maternal, infant and under-five child mortality rates. The results of this study demonstrate that health expenditure is a crucial factor in the progression of the HDI. It is thought that countries with a low HDI can enhance health outcomes by reducing mortality rates and increasing health expenditure.

Kaynakça

  • Akın, P., & Koc, T. (2021). Prediction of human development index with health indicators using tree-based regression models. Adıyaman University Journal of Science, 11(2), 410-420.
  • Alijanzadeh, M., Asefzadeh, S., & Moosaniaye, Z. S. A. (2016). Correlation between human development index and infant mortality rateworldwide. Biotech Health Sciences, 3(1), e35330.
  • Alpar, R. (2013). Çok değişkenli istatistiksel yöntemler (4. Bs.). Detay Yayıncılık, Ankara.
  • Altaş, D., & Arikan, G. (2017). The analysis of human development index with cluster analysis techniques. Social Sciences Research Journal, 6(3), 126-138.
  • Anand, S., & Sen, A. (2000). The income component of the human development index. Journal of Human Development, 1(1), 83-106.
  • Arntzen, A., Samuelsen, S. O., Bakketeig, L. S., & Stoltenberg, C. (2004). Socioeconomic status and risk of infant death. A population-based study of trends in Norway, 1967–1998. International Journal of Epidemiology, 33(2), 279-288.
  • Babiarz, P., Grabiński, T., Migała-Warchoł, A., & Szczygieł, E. (2018). The application of customized human development index to the analysis of socio-economic development of the European Union member states. Economics & Sociology, 11(4), 332.
  • Chu, K. C., Miller, B. A., & Springfield, S. A. (2007). Measures of racial/ethnic health disparities in cancer mortality rates and the influence of socioeconomic status. Journal of the National Medical Association, 99(10), 1092.
  • Coşar, K. (2020). OECD sağlık verilerinin veri madenciliği yöntemleri ile analizi. Yüksek Lisans Tezi, Marmara Üniversitesi, İstanbul.
  • Crémieux, P. Y., Ouellette, P., & Pilon, C. (1999). Health care spending as determinants of health outcomes. Health Economics, 8(7), 627-639.
  • Dobesova, Z. (2024). Evaluation of Orange data mining software and examples for lecturing machine learning tasks in geoinformatics. Computer Applications in Engineering Education, e22735.
  • Doorslaer, E. V., & Koolman, X. (2004). Explaining the differences in income‐related health inequalities across European countries. Health Economics, 13(7), 609-628.
  • Fahmiyah, I., & Ningrum, R. A. (2023). Human development clustering in Indonesia: Using K-means method and based on Human Development Index categories. Journal of Advanced Technology and Multidiscipline, 2(1), 27-33.
  • Ferreira, L., & Hitchcock, D. B. (2009). A comparison of hierarchical methods for clustering functional data. Communications in Statistics-Simulation and Computation, 38(9), 1925-1949.
  • Güloğlu, H., Güloğlu, B., & Güven, M. (2018). K means clustering analysis of the determinants of Human Development Index for the member states of the Organization for Islamic Cooperation. Eurasian Academy of Sciences Eurasian Econometrics, Statistics & Emprical Economics Journal, 11, 67- 77.
  • Hakobyan, M., Mkrtchyan, A., & Yepiskoposyan, L. (2006). Infant mortality in Armenia, 1992–2003. Economics & Human Biology, 4(3), 351-358.
  • Hands, S., & Everitt, B. (1987). A Monte Carlo study of the recovery of cluster structure in binary data by hierarchical clustering techniques. Multivariate Behavioral Research, 22(2), 235-243.
  • Khosravi, A., & Rahbar, M. R. (2009). Health profile indicators in the Islamic Republic of Iran. Ministry of Health & Medical Education Deputy for Health, Iran.
  • Krylovas, A., Kosareva, N., & Dadelo, S. (2020). European countries ranking and clustering solution by children’s physical activity and human development index using entropy-based methods. Mathematics, 8(10), 1705.
  • Mirahsani, Z. (2016). The relationship between health expenditures and human development index. Journal of Research & Health, 6(3), 373- 377.
  • Miranda‐Lescano, R., Muinelo‐Gallo, L., & Roca‐Sagalés, O. (2023). Human development and decentralization: The importance of public health expenditure. Annals of Public and Cooperative Economics, 94(1), 191-219.
  • Morse, S. (2014). Stirring the pot. Influence of changes in methodology of the Human Development Index on reporting by the press. Ecological Indicators, 45, 245-254.
  • Mylevaganam, S. (2017). The analysis of Human Development Index (HDI) for categorizing the member states of the United Nations (UN). Open Journal of Applied Sciences, 7(12), 661-690.
  • Nixon, J., & Ulmann, P. (2006). The relationship between health care expenditure and health outcomes: Evidence and caveats for a causal link. The European Journal of Health Economics, 7, 7-18.
  • Nuhu, K. M., McDaniel, J. T., Alorbi, G. A., & Ruiz, J. I. (2018). Effect of healthcare spending on the relationship between the Human Development Index and maternal and neonatal mortality. International Health, 10(1), 33-39.
  • OECD (2024). Retrieved from https://www.oecd.org/ (Accessed 06.10.2024).
  • Orange, 2024. Retrieved from http://orange.biolab.si/. (Accessed 01.10.2024).
  • Peters, D. H., Garg, A., Bloom, G., Walker, D. G., Brieger, W. R., & Hafizur Rahman, M. (2008). Poverty and access to health care in developing countries. Annals of the New York Academy of Sciences, 1136(1), 161-171.
  • Polat, E. (2021). The classification of countries’ Human Development Index level under economic inequality by using data mining classification algorithms. Romanian Statistical Review, 4, 27-44.
  • Prados De La Escosura, L. (2015). World human development: 1870–2007. Review of Income and Wealth, 61(2), 220-247.
  • Reidpath, D. D., & Allotey, P. (2003). Infant mortality rate as an indicator of population health. Journal of Epidemiology & Community Health, 57(5), 344-346.
  • Repiská, R., Grisáková, N., & Štetka, P. (2022). Hierarchical clustering based on international sustainability indices of EU countries. Ekonomické rozhľady–Economic Review, 51(2), 149-170.
  • Reyes, G. E., & Useche, A. J. (2019). Competitiveness, economic growth and human development in Latin American and Caribbean countries 2006-2015: A performance and correlation analysis. Competitiveness Review: An International Business Journal, 29(2), 139-159.
  • Rohani, H. S., Ahmadvand, A., & Garmaroudi, G. (2018). The relationship between important reproductive health indices and human development index in Iran. Medical Journal of the Islamic Republic of Iran, 32, 54.
  • Stanton, E. A. (2007). The Human Development Index: A history, Working Papers wp127, Political Economy Research Institute, University of Massachusetts at Amherst.
  • Sulkowski, A., & White, D. S. (2016). A happiness Kuznets curve? Using model-based cluster analysis to group countries based on happiness, development, income, and carbon emissions. Environment, Development and Sustainability, 18, 1095-1111.
  • Tebala, D., & Marino, D. (2023). Companies and artificial intelligence: an example of clustering with orange. In Innovations and Economic and Social Changes due to Artificial Intelligence: The State of the Art (pp. 1-12). Cham: Springer Nature Switzerland.
  • Tekin, B. (2018). Ward, k-ortalamalar ve iki adimli kümeleme analizi yöntemleri ile finansal göstergeler temelinde hisse senedi tercihi. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 21(40), 401-436.
  • Tekin, B., & Gümüş, F. B. (2017). The classification of stocks with basic financial indicators: An application of cluster analysis on the BIST 100 index. International Journal of Academic Research in Business and Social Sciences, 7(5), 1-32.
  • United Nations, (2007). The millennium development goals report. NewYork
  • United Nations Children’s Fund, (2017). Monitoring the situation of children and women. Retrieved from https://data.unicef.org/topic/education/literacy/ (Accessed 14.02.2025).
  • United Nations Development Program (2001). Human Development Report 2001. Making New Technologies Work for Human Development. Oxford University Press. New York.
  • United Nations Development Program, (2014). UNDP, Human Development Report. New York.
  • World Health Organization, (2020). Children: Reducing mortality fact sheet. Retrieved from http://www.who.int/mediacentre/factsheets/fs178/en/ (Accessed 14.02.2025).
  • World Health Organization, (2021). Maternal mortality fact sheet. Retrieved from https://www.who.int/europe/news-room/fact-sheets/item/maternal-mortality (Accessed 14.02.2025).
  • World Health Organization-Global Health Observatory, (2024). – processed by Our World in Data. Retrieved from https://ourworldindata.org/financing-healthcare (Accessed 01.10.2024).
  • Yakut, E., Gunduz, M., & Demirci, A. (2015). Comparison of classification success of human development index by using ordered logistic regression analysis and artificial neural network methods. Journal of Applied Quantitative Methods, 10(3), 15-34.
  • Yalçın, A. Z., & Çakmak, F. (2016). Türkiye'de kamu sağlık harcamalarının insani gelişim üzerindeki etkisi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 30(4), 705-724.

OECD ÜLKELERİNİN İNSANİ GELİŞME ENDEKSİ, ÖLÜM ORANLARI VE SAĞLIK HARCAMALARI AÇISINDAN KÜMELEME ANALİZİ İLE DEĞERLENDİRİLMESİ

Yıl 2025, Cilt: 28 Sayı: 1, 65 - 80, 26.03.2025
https://doi.org/10.61859/hacettepesid.1581132

Öz

Bu çalışmanın amacı, OECD ülkelerine kümeleme analizi uygulayarak İnsani Gelişme Endeksi (HDI), ölüm oranı ve sağlık harcamaları profilleri benzer olan ülke gruplarını belirlemektir. Araştırma kapsamında 38 OECD ülkesi için 2020 yılına ait verilerle HDI, anne, bebek ve beş yaş altı çocuk ölüm oranları, toplam sağlık harcaması payı ve kamu sağlık harcaması payı değişkenleri korelasyon analizi ve K-ortalamalar kümeleme yöntemi kullanılarak analiz edilmiştir. HDI ile toplam sağlık harcamaları ve kamu sağlık harcamaları arasında anlamlı ve pozitif ilişki; HDI ile anne, bebek ve çocuk ölüm oranları arasında ise negatif ve güçlü ilişki olduğu belirlenmiştir. Kümeleme analizi sonucunda küme 1'de 13 ülke, küme 2'de 3 ülke ve küme 3'te 13 ülke olduğu belirlenmiştir. Aynı kümede yer alan Kolombiya, Meksika ve Türkiye'nin en düşük HDI ve sağlık harcaması ile en yüksek anne, bebek ve beş yaş altı çocuk ölüm oranlarına sahip olduğu görülmüştür. Çalışma sonuçları sağlık harcamalarının HDI gelişimine önemli bir katkısı olduğunu göstermiştir. HDI skoru düşük olan ülkelerin sağlık harcamalarını artırarak ve ölüm oranlarını azaltarak sağlık sonuçlarını iyileştirebileceği düşünülmektedir.

Kaynakça

  • Akın, P., & Koc, T. (2021). Prediction of human development index with health indicators using tree-based regression models. Adıyaman University Journal of Science, 11(2), 410-420.
  • Alijanzadeh, M., Asefzadeh, S., & Moosaniaye, Z. S. A. (2016). Correlation between human development index and infant mortality rateworldwide. Biotech Health Sciences, 3(1), e35330.
  • Alpar, R. (2013). Çok değişkenli istatistiksel yöntemler (4. Bs.). Detay Yayıncılık, Ankara.
  • Altaş, D., & Arikan, G. (2017). The analysis of human development index with cluster analysis techniques. Social Sciences Research Journal, 6(3), 126-138.
  • Anand, S., & Sen, A. (2000). The income component of the human development index. Journal of Human Development, 1(1), 83-106.
  • Arntzen, A., Samuelsen, S. O., Bakketeig, L. S., & Stoltenberg, C. (2004). Socioeconomic status and risk of infant death. A population-based study of trends in Norway, 1967–1998. International Journal of Epidemiology, 33(2), 279-288.
  • Babiarz, P., Grabiński, T., Migała-Warchoł, A., & Szczygieł, E. (2018). The application of customized human development index to the analysis of socio-economic development of the European Union member states. Economics & Sociology, 11(4), 332.
  • Chu, K. C., Miller, B. A., & Springfield, S. A. (2007). Measures of racial/ethnic health disparities in cancer mortality rates and the influence of socioeconomic status. Journal of the National Medical Association, 99(10), 1092.
  • Coşar, K. (2020). OECD sağlık verilerinin veri madenciliği yöntemleri ile analizi. Yüksek Lisans Tezi, Marmara Üniversitesi, İstanbul.
  • Crémieux, P. Y., Ouellette, P., & Pilon, C. (1999). Health care spending as determinants of health outcomes. Health Economics, 8(7), 627-639.
  • Dobesova, Z. (2024). Evaluation of Orange data mining software and examples for lecturing machine learning tasks in geoinformatics. Computer Applications in Engineering Education, e22735.
  • Doorslaer, E. V., & Koolman, X. (2004). Explaining the differences in income‐related health inequalities across European countries. Health Economics, 13(7), 609-628.
  • Fahmiyah, I., & Ningrum, R. A. (2023). Human development clustering in Indonesia: Using K-means method and based on Human Development Index categories. Journal of Advanced Technology and Multidiscipline, 2(1), 27-33.
  • Ferreira, L., & Hitchcock, D. B. (2009). A comparison of hierarchical methods for clustering functional data. Communications in Statistics-Simulation and Computation, 38(9), 1925-1949.
  • Güloğlu, H., Güloğlu, B., & Güven, M. (2018). K means clustering analysis of the determinants of Human Development Index for the member states of the Organization for Islamic Cooperation. Eurasian Academy of Sciences Eurasian Econometrics, Statistics & Emprical Economics Journal, 11, 67- 77.
  • Hakobyan, M., Mkrtchyan, A., & Yepiskoposyan, L. (2006). Infant mortality in Armenia, 1992–2003. Economics & Human Biology, 4(3), 351-358.
  • Hands, S., & Everitt, B. (1987). A Monte Carlo study of the recovery of cluster structure in binary data by hierarchical clustering techniques. Multivariate Behavioral Research, 22(2), 235-243.
  • Khosravi, A., & Rahbar, M. R. (2009). Health profile indicators in the Islamic Republic of Iran. Ministry of Health & Medical Education Deputy for Health, Iran.
  • Krylovas, A., Kosareva, N., & Dadelo, S. (2020). European countries ranking and clustering solution by children’s physical activity and human development index using entropy-based methods. Mathematics, 8(10), 1705.
  • Mirahsani, Z. (2016). The relationship between health expenditures and human development index. Journal of Research & Health, 6(3), 373- 377.
  • Miranda‐Lescano, R., Muinelo‐Gallo, L., & Roca‐Sagalés, O. (2023). Human development and decentralization: The importance of public health expenditure. Annals of Public and Cooperative Economics, 94(1), 191-219.
  • Morse, S. (2014). Stirring the pot. Influence of changes in methodology of the Human Development Index on reporting by the press. Ecological Indicators, 45, 245-254.
  • Mylevaganam, S. (2017). The analysis of Human Development Index (HDI) for categorizing the member states of the United Nations (UN). Open Journal of Applied Sciences, 7(12), 661-690.
  • Nixon, J., & Ulmann, P. (2006). The relationship between health care expenditure and health outcomes: Evidence and caveats for a causal link. The European Journal of Health Economics, 7, 7-18.
  • Nuhu, K. M., McDaniel, J. T., Alorbi, G. A., & Ruiz, J. I. (2018). Effect of healthcare spending on the relationship between the Human Development Index and maternal and neonatal mortality. International Health, 10(1), 33-39.
  • OECD (2024). Retrieved from https://www.oecd.org/ (Accessed 06.10.2024).
  • Orange, 2024. Retrieved from http://orange.biolab.si/. (Accessed 01.10.2024).
  • Peters, D. H., Garg, A., Bloom, G., Walker, D. G., Brieger, W. R., & Hafizur Rahman, M. (2008). Poverty and access to health care in developing countries. Annals of the New York Academy of Sciences, 1136(1), 161-171.
  • Polat, E. (2021). The classification of countries’ Human Development Index level under economic inequality by using data mining classification algorithms. Romanian Statistical Review, 4, 27-44.
  • Prados De La Escosura, L. (2015). World human development: 1870–2007. Review of Income and Wealth, 61(2), 220-247.
  • Reidpath, D. D., & Allotey, P. (2003). Infant mortality rate as an indicator of population health. Journal of Epidemiology & Community Health, 57(5), 344-346.
  • Repiská, R., Grisáková, N., & Štetka, P. (2022). Hierarchical clustering based on international sustainability indices of EU countries. Ekonomické rozhľady–Economic Review, 51(2), 149-170.
  • Reyes, G. E., & Useche, A. J. (2019). Competitiveness, economic growth and human development in Latin American and Caribbean countries 2006-2015: A performance and correlation analysis. Competitiveness Review: An International Business Journal, 29(2), 139-159.
  • Rohani, H. S., Ahmadvand, A., & Garmaroudi, G. (2018). The relationship between important reproductive health indices and human development index in Iran. Medical Journal of the Islamic Republic of Iran, 32, 54.
  • Stanton, E. A. (2007). The Human Development Index: A history, Working Papers wp127, Political Economy Research Institute, University of Massachusetts at Amherst.
  • Sulkowski, A., & White, D. S. (2016). A happiness Kuznets curve? Using model-based cluster analysis to group countries based on happiness, development, income, and carbon emissions. Environment, Development and Sustainability, 18, 1095-1111.
  • Tebala, D., & Marino, D. (2023). Companies and artificial intelligence: an example of clustering with orange. In Innovations and Economic and Social Changes due to Artificial Intelligence: The State of the Art (pp. 1-12). Cham: Springer Nature Switzerland.
  • Tekin, B. (2018). Ward, k-ortalamalar ve iki adimli kümeleme analizi yöntemleri ile finansal göstergeler temelinde hisse senedi tercihi. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 21(40), 401-436.
  • Tekin, B., & Gümüş, F. B. (2017). The classification of stocks with basic financial indicators: An application of cluster analysis on the BIST 100 index. International Journal of Academic Research in Business and Social Sciences, 7(5), 1-32.
  • United Nations, (2007). The millennium development goals report. NewYork
  • United Nations Children’s Fund, (2017). Monitoring the situation of children and women. Retrieved from https://data.unicef.org/topic/education/literacy/ (Accessed 14.02.2025).
  • United Nations Development Program (2001). Human Development Report 2001. Making New Technologies Work for Human Development. Oxford University Press. New York.
  • United Nations Development Program, (2014). UNDP, Human Development Report. New York.
  • World Health Organization, (2020). Children: Reducing mortality fact sheet. Retrieved from http://www.who.int/mediacentre/factsheets/fs178/en/ (Accessed 14.02.2025).
  • World Health Organization, (2021). Maternal mortality fact sheet. Retrieved from https://www.who.int/europe/news-room/fact-sheets/item/maternal-mortality (Accessed 14.02.2025).
  • World Health Organization-Global Health Observatory, (2024). – processed by Our World in Data. Retrieved from https://ourworldindata.org/financing-healthcare (Accessed 01.10.2024).
  • Yakut, E., Gunduz, M., & Demirci, A. (2015). Comparison of classification success of human development index by using ordered logistic regression analysis and artificial neural network methods. Journal of Applied Quantitative Methods, 10(3), 15-34.
  • Yalçın, A. Z., & Çakmak, F. (2016). Türkiye'de kamu sağlık harcamalarının insani gelişim üzerindeki etkisi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 30(4), 705-724.
Toplam 48 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Sağlık Politikası
Bölüm Makaleler
Yazarlar

Nazan Kartal 0000-0002-5416-7952

Yayımlanma Tarihi 26 Mart 2025
Gönderilme Tarihi 7 Kasım 2024
Kabul Tarihi 1 Mart 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 28 Sayı: 1

Kaynak Göster

APA Kartal, N. (2025). EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS. Hacettepe Sağlık İdaresi Dergisi, 28(1), 65-80. https://doi.org/10.61859/hacettepesid.1581132
AMA Kartal N. EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS. HSİD. Mart 2025;28(1):65-80. doi:10.61859/hacettepesid.1581132
Chicago Kartal, Nazan. “EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS”. Hacettepe Sağlık İdaresi Dergisi 28, sy. 1 (Mart 2025): 65-80. https://doi.org/10.61859/hacettepesid.1581132.
EndNote Kartal N (01 Mart 2025) EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS. Hacettepe Sağlık İdaresi Dergisi 28 1 65–80.
IEEE N. Kartal, “EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS”, HSİD, c. 28, sy. 1, ss. 65–80, 2025, doi: 10.61859/hacettepesid.1581132.
ISNAD Kartal, Nazan. “EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS”. Hacettepe Sağlık İdaresi Dergisi 28/1 (Mart 2025), 65-80. https://doi.org/10.61859/hacettepesid.1581132.
JAMA Kartal N. EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS. HSİD. 2025;28:65–80.
MLA Kartal, Nazan. “EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS”. Hacettepe Sağlık İdaresi Dergisi, c. 28, sy. 1, 2025, ss. 65-80, doi:10.61859/hacettepesid.1581132.
Vancouver Kartal N. EVALUATION OF OECD COUNTRIES IN TERMS OF HUMAN DEVELOPMENT INDEX, MORTALITY RATES AND HEALTH EXPENDITURES WITH CLUSTER ANALYSIS. HSİD. 2025;28(1):65-80.