The socioeconomic distribution of life expectancy and healthy life expectancy in Chile

BACKGROUND: Life expectancy (LE) has usually been used as a metric to monitor population health. In the last few years, metrics such as Quality-Adjusted-Life-Expectancy (QALE) and Health-Adjusted-Life- Expectancy (HALE) have gained popularity in health research, given their capacity to capture health related quality of life, providing a more comprehensive approach to the health concept. We aimed to estimate the distribution of the LE, QALEs and HALEs across Socioeconomic Status in the Chilean population. METHODS: Based on life tables constructed using Chiang II´s method, we estimated the LE of the population in Chile by age strata. Probabilities of dying were estimated from mortality data obtained from national registries. Then, life tables were stratified into five socioeconomic quintiles, based on age-adjusted years of education (pre-school, early years to year 1, primary level, secondary level, technical or university). Quality weights (utilities) were estimated for age strata and SES, using the National Health Survey (ENS 2017). Utilities were calculated using the EQ-5D data of the ENS 2017 and the validated value set for Chile. We applied Sullivan´s method to adjust years lived and convert them into QALEs and HALEs. RESULTS: LE at birth for Chile was estimated in 80.4 years, which is consistent with demographic national data. QALE and HALE at birth were 69.8 and 62.4 respectively. Men are expected to live 6.1% less than women. However, this trend is reversed when looking at QALEs and HALEs, indicating the concentration of higher morbidity in women compared to men. The distribution of all these metrics across SES showed a clear gradient in favour of a better-off population-based on education quintiles. The absolute and relative gaps between the lowest and highest quintile were 15.24 years and 1.21 for LE; 18.57 HALYs and 1.38 for HALEs; and 21.92 QALYs and 1.41 for QALEs. More pronounced gradients and higher gaps were observed at younger age intervals. CONCLUSION: The distribution of LE, QALE and HALEs in Chile shows a clear gradient favouring better-off populations that decreases over people´s lives. Differences in LE favouring women contrast with differences in HALEs and QALEs which favour men, suggesting the need of implementing gender-focused policies to address the case-mix complexity. The magnitude of inequalities is greater than in other high-income countries and can be explained by structural social inequalities and inequalities in access to healthcare.