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Corruption and population health outcomes: an analysis of data from 133 countries using structural equation modeling

  • Original Article
  • Published:
International Journal of Public Health

Abstract

Objectives

The current study aims to develop a theoretical framework for understanding the antecedents of corruption and the effects of corruption on various health indicators.

Methods

Using structural equation models, we analyzed a multinational dataset of 133 countries that included three main groups of variables—antecedents of corruption, corruption measures, and health indicators.

Results

Controlling for various factors, our results suggest that corruption rises as GDP per capita falls and as the regime becomes more autocratic. Higher corruption is associated with lower levels of health expenditure as a percentage of GDP per capita, and with poorer health outcomes. Countries with higher GDP per capita and better education for women have better health outcomes regardless of health expenditures and regime type.

Conclusions

Our results suggest that there is no direct relationship between health expenditures and health outcomes after controlling for the other factors in the model. Our study enhances our understanding of the conceptual and theoretical links between corruption and health outcomes in a population, including factors that may mediate how corruption can affect health outcomes.

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Acknowledgments

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2012S1A3A2033416) to Dr. Minah Kang.

Conflict of interest

No conflicts of interest.

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Authors and Affiliations

  1. Faculty of Law, Institute of Criminology, The Hebrew University of Jerusalem, Mt. Scopus, 91905, Jerusalem, Israel

    Roni Factor

  2. Department of Public Administration, Ewha Womans University, 314 Posco-Bd, 11-1, Daehyun-dong, Seodaemu-gu, Seoul, 120-750, Korea

    Minah Kang

Authors
  1. Roni Factor
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  2. Minah Kang
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Correspondence to Minah Kang.

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Factor, R., Kang, M. Corruption and population health outcomes: an analysis of data from 133 countries using structural equation modeling. Int J Public Health 60, 633–641 (2015). https://doi.org/10.1007/s00038-015-0687-6

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  • DOI: https://doi.org/10.1007/s00038-015-0687-6

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