In the field of population studies, health outcomes are often measured and compared using Healthy Life Years (HLY), an indicator of expected number of healthy life years that combines different data on health and mortality. However, population composition may differ cross-nationally when it comes to important factors that influence health, such as education level. If, for example, a greater percentage of the population is highly educated in one country compared to another, this must be considered in comparisons of HLY between the two countries.
In order to account for the role of education in a country’s health outcomes, Markus Sauerberg of the Vienna Institute of Demography (OeAW) compared HLY between 16 European countries by gender and education level, using Eurostat data. To calculate HLY, he looks at lifespan as well as prevalence of limitations in daily activities. He then considers the proportion of individuals at each education level in the country to compute the HLY for the country as a whole. In other words, each country’s HLY is weighted by the education composition of the country’s population. For comparison with the HLY measure, the researcher also calculates a measure of life expectancy at age 30.
Sauerberg’s analysis provides important insights into population health across Europe using the HLY indicator, as well as the role of educational inequalities in shaping health outcomes. Results indicate that life expectancy at age 30 is highest in Italy for both women and men, while Bulgaria has the lowest life expectancy. The HLY measure produced different outcomes: HLY is highest in Sweden (again for both genders), and lowest in Slovakia for women and Estonia for men. Sauerberg then breaks these differences down by education level. Calculating HLY and life expectancy by education level in each country reveals a generally greater effect of education on HLY than on life expectancy. Further, he standardized the HLY indicator by assuming the same population composition by educational attainment for every analyzed country. The so-called education-adjusted HLY estimates reveal that some of the inequalities in HLY between countries can be attributed to differences in educational expansion. Portugal’s comparatively low HLY value, for example, can be partly explained through its low share of highly-educated individuals. Yet Sauerberg warns that these results should be interpreted with caution, as health and mortality data was uncertain and difficult to harmonise.
Overall, by using both indicators of life expectancy and HLY, and by considering the education level of the population, Sauerberg provides intriguing findings for health policy interventions. In Romania, for example, HLY is similar across education levels, indicating that larger structural factors may limit healthy life for all Romanians. Yet educational inequality varies across countries, indicating that policy solutions to improve HLY should vary. While some countries could use educational expansion as a way to promote population health, others need to target structural disadvantages through measures such as establishing a well-functioning healthcare system.