Corruption and health outcomes within an economic and cultural framework

Eur J Health Econ. 2020 Mar;21(2):195-207. doi: 10.1007/s10198-019-01120-8. Epub 2019 Oct 5.


The purpose of this paper is to investigate the relationship between corruption and population health. Our cross-sectional sample covers 185 countries (54 high-income and 131 low-income countries) and the period of the analysis is 2005-2017. This research provides clear evidence that the level of corruption significantly affects physical health (expressed as life expectancy and Mortality rate) and mental health (expressed by happiness), under the moderating role of economic development and cultural framework. Moreover, we validate a powerful and positive correlation between the income level and both physical and mental health. Culture also has an important role in the corruption-health nexus, because we find evidence supporting four out of the six dimensions of culture (individualism versus collectivism, indulgence versus restraint, uncertainty avoidance and masculinity vs femininity) as having influence upon the physical and mental health of individuals. When we estimate the results on subsamples of countries (high-income and low-income countries), we validate a crisscross effect of corruption. Thus, a high level of corruption more deeply affects the physical health of population in low-income countries than in high-income countries. On the other hand, mental health is more pronouncedly affected by corruption in high-income countries than in low-income countries. This study may have important implications for national or international policy makers who need to acknowledge that anti-corruption policies play an important role in increasing population health, but they also need to adopt them according to the economic and cultural context of each nation.

Keywords: Corruption; Culture; Mental health; Physical health; Wealth.

MeSH terms

  • Cross-Sectional Studies
  • Culture
  • Developing Countries
  • Economic Development*
  • Humans
  • Income
  • Life Expectancy*
  • Mental Health*
  • Outcome Assessment, Health Care
  • Population Health*