Health Expectancy: Increasingly Used, but Not Well Understood

Abstract

Good health is central to human happiness and well-being. It contributes substantially to economic progress, as healthy populations live longer and are more productive. The corresponding public health policies are typically assessed based on a structural indicator for “Health Expectancy” (HE) such as the EU’s “Healthy Life Years” (HLY) or the WHO’s “Health-Adjusted Life Expectancy” (HALE). Unfortunately, HE estimates are extremely sensitive to methodological choices, an issue that is widely overlooked. First, the common practice of measuring population health by the distribution of responses to specific survey questions is ambiguous and not straightforward. Consequently, levels and trends of HE vary significantly depending on the underlying data and health indicators. Moreover, HE estimates are also highly sensitive to technical features, such as the age range and partitioning selected for analysis, as well as the technique chosen to add the health dimension to the life table; an issue that has gone remarkably unrecognized. With the aim of filling this important research gap, the European Research Council (ERC) funded a Consolidator Grant project entitled “Levels and trends of health expectancy: understanding its measurement and estimation sensitivity” (LETHE). This special issue of Comparative Population Studies (CPoS) marks the completion of this project. It contains five articles, each dealing with a specific aspect of HE computation or a concrete empirical application based on HE indicators. This editorial summarizes the insights gained during the LETHE project and aims to make users of HE aware of its methodological sensitivities through illustrative empirical examples. A better understanding of these issues is essential to ensure the indicators’ appropriate usage in research as well as in advising policy makers and public health officials.

* This is the Editorial on the Special Issue "Levels and Trends of Health Expectancy: Understanding its Measurement and Estimation Sensitivity".