A fuzzy set qualitative comparative analysis of 131 countries: which configuration of the structural conditions can explain health better?

Int J Equity Health. 2018 Jan 22;17(1):10. doi: 10.1186/s12939-018-0724-1.

Abstract

Background: According to the recommendations of the World Health Organization Commission On Social Determinants of Health (CSDH) for intersectoral action on health, the well-being of and equity in health within a population are achieved via a complex fusion of policies and actions. In this study, following the CSDH's approach and considering set-theoretic relations, we aimed to unravel this complexity and answer the kinds of questions that are outside the scope of conventional variable-oriented approach.

Methods: A fuzzy-set qualitative comparative analysis of 131 countries was conducted to examine the configurational effects of five macro-level structural conditions on life expectancy at birth. The potential causal conditions were level of country wealth, income inequality, quality of governance, education, and health system. The data collected from different international data sources were recorded during 2004-2015.

Results: The intermediate solution of the truth table analysis indicated a configuration of conditions including high level of governance, education, wealth, and affluent health system to be consistently sufficient for high life expectancy. On the other hand, four configurations, each containing two or three conditions, were consistent with being usually sufficient to cause low life expectancy.

Conclusions: We were able to configurationally explore the cases and specify the combinations of potentially causal conditions which were usually sufficient to explain high or low life expectancy in different countries. As a result, particular cases were identified for further research. In addition, research may provide support for the CSDH's recommendations emphasizing the importance of intersectoral action for health.

Publication types

  • Comparative Study

MeSH terms

  • Delivery of Health Care / organization & administration*
  • Delivery of Health Care / statistics & numerical data*
  • Global Health / statistics & numerical data*
  • Health Services Accessibility / organization & administration*
  • Health Services Accessibility / statistics & numerical data*
  • Humans
  • Social Determinants of Health / statistics & numerical data*
  • Socioeconomic Factors*