Cluster analysis of health systems in Europe according to life expectancy at birth

The aim of this study was to group European countries according to life expectancy at birth and to determine the impact of economic growth and financial indicators on European country groups.

This study planned and conducted by using life expectancy at birth time series, economic growth and financial development indicators data for the period of 1980 to 2015. European countries are classified in terms of life expectancy (LE) at birth time series data from 1980 to 2015 by using hierarchical clustering analysis method. Random Forest and Classification and Regression Tree (CART) algorithm was used to examine predictors of European country groups in terms of long-term LE time series data by using economic growth and financial development indicators.

The results of this study show that Eastern and Western countries are mostly in two different clusters in terms of long-term LE time series. This study sheds light on the difference between Eurosceptic countries and other European countries. This study revealed that inflation in consumer prices, which is an indicator of economic growth, outperforms financial development indicators to predict country groups in terms of long-term life expectancy at birth data.

Countries in the same cluster may have similar problems and solutions in their health care systems. Priority should be given to health problems that adversely affect the life expectancy of the countries in the same cluster in order to raise the quality of life and extend life expectancy in the European continent.