A simple framework for analysing the impact of economic growth on non-communicable diseases

Abstract

Non-communicable diseases (NCDs) are currently the leading cause of death worldwide. In this paper, we examine the channels through which economic growth affects NCDs’ epidemiology. Following a production function approach, we develop a basic technique to break up the impact of economic growth on NCDs into three fundamental components: (1) a resource effect; (2) a behaviour effect; and (3) a knowledge effect. We demonstrate that each of these effects can be measured as the product of two elasticities, the output and income elasticity of the three leading factors influencing the frequency of NCDs in any population: health care, health-related behaviours and lifestyle, and medical knowledge.

Keywords:

• economic growth
• Engel’s functions
• health production function
• non-communicable diseases
• social determinants of health

JEL classifications:

• I1
• I15

Public Interest Statement

This paper provides a simple but coherent framework to describe and measure the impact of economic growth on mortality due to chronic non-communicable diseases (NCDs). NCDs, once considered diseases of affluence, are currently a major public health problem and the cause of about two-thirds of global deaths. The burden of NCDs is remarkable in all the world regions and is projected to increase during the next years (even in low- and middle-income countries). This global epidemic is acknowledged as a major threat to health systems and economic growth. The research to date has tended to focus on the economic burden of NCDs on individuals and countries. In this paper, we reverse the perspective by examining the main channels through which economic growth affects NCDs’ epidemiology. The study identifies three fundamental forces: (1) a resource effect; (2) a behaviour effect; and (3) a knowledge effect.

Acknowledgements

We would like to thank two anonymous reviewers for their very helpful comments and suggestions. All remaining errors are, of course, our own.

Notes

1. A variety of measures are commonly used to characterize the overall health of populations. The dependent variable in the health production function can be a measure of disease frequencies (such as the incidence or prevalence rate), of health outcome (such as the mortality or morbidity rate and life expectancy), or even of the duration of life combined with some notion of its quality (such as the quality-adjusted life years (QALYs) or disability-adjusted life years [DALYs]). We focus on the mortality rate only to keep the model as simple as possible (Breyer, Kifmann, & Zweifel, 2009).

2. In a narrow sense, an Engel’s function shows the relationship between the quantity demanded of a single good (or the expenditure on a set of goods) and income, holding prices constant (Engel, 1895; Lewbel, 2006).

Additional information

Funding

Funding. The authors received no direct funding for this research.

Notes on contributors

Ivan K. Cohen

Ivan K. Cohen is an associate professor in finance and economics at Richmond—The American International University in London. His current research interests include financial economics and the economics of pension funds.

Fabrizio Ferretti

Fabrizio Ferretti is an assistant professor in economics at the University of Modena and Reggio Emilia. His current research interests include Keynesian economics and health economics.

Bryan McIntosh

Bryan McIntosh is a senior lecturer in health management at the University of Bradford. His current research interests include health economics, management and organizational behaviour.