Inequalities in life expectancy

Large inequalities in life expectancy exist not only by gender, but also by socio-economic status, no matter how they are measured – by education level, income or occupational group. This section focuses on inequalities by education level since this is the socio-economic indicator with the most widely available data, although the data coverage still remains limited to only about half of EU countries.

Inequalities in life expectancy by education level are generally larger among men than among women, and are particularly large in Central and Eastern Europe. On average across 14 EU countries for which data are available, 30-year-old men with less than an upper secondary education can expect to live about seven years less than those with a tertiary education (a university degree or the equivalent) in 2017 (Figure 3.3). In the Slovak Republic, Poland and Hungary, 30-year-old men with a low level of education can expect to live more than 10 years less than those with a high level of education.

The education gap among women is smaller, at about three years on average across the 14 EU countries. In the Slovak Republic and Estonia, 30-year-old women with a low level of education can expect to live over five years less than those with a high level of education.

This education gap in life expectancy is due to higher mortality rates among the least educated at different ages. The gap in mortality rate between low-educated and high-educated prime-age men (the 25-64 year-olds) is particularly large. This gap is due to much higher mortality rates from all the main causes of death among low-educated prime-age men. Half of the gap in mortality rate among men in this age group is due to higher death rates from circulatory diseases and cancer, and another 20% is due to external causes of death (e.g. accidents and suicide). An important gap in mortality rates by education level also exists among older men and women, also driven mainly by higher death rates from circulatory diseases and cancer (Murtin et al., 2017).

Many factors contribute to the education gap in mortality and life expectancy. These include lower income and standard of living for people with lower educational attainment, higher smoking rates and obesity rates, and less healthy nutritional habits (see indicators in Chapter 4 for more information on disparities in risk factors by socio-economic group). If the prevalence of smoking among the least educated was identical to that of the most educated, life expectancy between ages 35 to 80 could increase by one year among men and six months among women on average across 12 EU countries (Figure 3.4). Similarly, reducing the prevalence of high bodyweight among the least educated could contribute to a four-month increase of life expectancy between ages 35 to 80 among men and women. Wider determinants of health matter too, notably income. Reducing the share of the least educated people living on low incomes could also further increase life expectancy, especially among men in Central and Eastern European countries (Mackenbach et al., 2019).

Reducing socio-economic inequalities in life expectancy requires inter-sectoral actions involving not only health ministries but also other ministries responsible for education, employment, social protection, housing and environment (James et al., 2017).


INSEE (2018), “L’espérance de vie par niveau de vie” [Life expectancy by living standards], Insee Première, No. 1687, February 2018.

James, C. et al. (2017), “Inclusive growth and health”, OECD Health Working Papers, No. 103, OECD Publishing, Paris,

Mackenbach, J. et al. (2019), “Determinants of inequalities in life expectancy: an international comparative study of eight risk factors”, The Lancet Public Health, Vol. 4/10, pp. e529-e537,

Murtin, F. et al. (2017). “Inequalities in longevity by education in OECD countries: Insights from new OECD estimates”, OECD Statistics Working Papers, 2017/02, OECD Publishing, Paris,

Metadata, Legal and Rights

This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. Extracts from publications may be subject to additional disclaimers, which are set out in the complete version of the publication, available at the link provided.

© OECD/European Union 2020

The use of this work, whether digital or print, is governed by the Terms and Conditions to be found at