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  • Author or Editor: Christina Ciecierski x
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This chapter compares risk factors for lung cancer and their significance for 27 countries in the European Union (EU). Drawing on data from a variety of sources, this study uses K-mean cluster analysis to investigate potentially modifiable risk factors for cancer including tobacco use, alcohol consumption, air pollution, socioeconomic status, and public expenditures on health care and their effects on lung cancer outcomes. Findings from this study show that the EU is not homogenous in terms of the effect of risk factors for lung cancer. Study results yielded four country groups, each representing different patterns in risk factors for lung cancer. The lowest rates of lung cancer mortality occur among southern European countries that includes: Italy, Spain, Portugal, Malta, and Romania. These countries present with a pattern of risk factors that include: relatively low alcohol consumption and low rates of smoking coupled with moderate population exposure to air pollutants. By contrast, another cluster of countries with the highest relative lung cancer rates includes Bulgaria, Cyprus, Greece, Croatia, Hungary and Poland. Here, rates of smoking and exposure to air pollutants are highest from among all the population groups analyzed, potentially lending a signal that these risk factors for lung cancer are most significant for this country group. Surprisingly, EU countries with the highest development levels and the highest ratio of health care spending relative to GDP, also present with a relatively high indicator of lung cancer mortality despite their relatively low rates of smoking and exposure to air pollutants. The heterogeneity among EU Member states regarding significant risk factors for lung cancer implies that cancer prevention policy needs to be tailored to individual patterns in risk factors for cancer.

Open Access
In: Economics and Mathematical Modeling in Health-Related Research
In: Economics and Mathematical Modeling in Health-Related Research
In: Economics and Mathematical Modeling in Health-Related Research
The definition of a healthcare system evolves continuously, becoming broader and more complex with each rendering. Healthcare systems can consist of many different elements, including but not limited to: access to comprehensive medical care, health promotion, disease prevention, institutional framework, financing schemes, government responsibility over health, etc. In light of its broad classification of healthcare, this book focuses on a wide spectrum of health-related issues ranging from risk factors for disease to medical treatment and possible frameworks for healthcare systems. Aging populations, increasing costs of healthcare, advancing technology, and challenges created by the COVID-19 pandemic require an innovative conceptual and methodological framework. By combining the experience and effort of researchers from a variety of fields including mathematics, medicine and economics, this book offers an interdisciplinary approach to studying health-related issues. It contributes to the existing literature by integrating the perspective of treatment with the economic determinants of health care outcomes, such as population density, access to financial resources and institutional frameworks. It also provides new evidence regarding the pharmaceutical industry including innovation, international trade and company performance.

Contributors are: Sayansk Da Silva, Joe Feinglass, Scott W. Hegerty, Joseph E. Hibdon, Jr, Arkadiusz Michał Kowalski, Małgorzata Stefania Lewandowska, Dawid Majcherek, Ewelina Nojszewska, Izabela Pruchnicka-Grabias, Agata Sielska and Julian Smółka.