On the measurement of healthy lifespan inequality

Abstract

Background Current measures to monitor population health include indicators of (i) average length-of-life (life expectancy), (ii) average length-of-life spent in good health (health expectancy), and (iii) variability in length-of-life (lifespan inequality). What is lacking is an indicator measuring the extent to which healthy lifespans are unequally distributed across individuals (the so-called ‘healthy lifespan inequality’ indicators). Methods We combine information on age-specific survival with the prevalence of functional limitation or disability in Spain (2014–2017) by sex and level of education to estimate age-at-disability onset distributions. Age-, sex- and education-specific prevalence rates of adult individuals’ daily activities limitations were based on the GALI index derived from Spanish National Health Surveys held in 2014 and 2017. We measured inequality using the Gini index. Results In contemporary Spain, education differences in health expectancy are substantial and greatly exceed differences in life expectancy. The female advantage in life expectancy disappears when considering health expectancy indicators, both overall and across education groups. The highly educated exhibit lower levels of lifespan inequality, and lifespan inequality is systematically higher among men. Our new healthy lifespan inequality indicators suggest that the variability in the ages at which physical daily activity limitations start are substantially larger than the variability in the ages at which individuals die. Healthy lifespan inequality tends to decrease with increasing educational attainment, both for women and for men. The variability in ages at which physical limitations start is slightly higher for women than for men. Conclusions The suggested indicators uncover new layers of health inequality that are not traceable with currently existing approaches. Low-educated individuals tend to not only die earlier and spend a shorter portion of their lives in good health than their highly educated counterparts, but also face greater variation in the eventual time of death and in the age at which they cease enjoying good health—a multiple burden of inequality that should be taken into consideration when evaluating the performance of public health systems and in the elaboration of realistic working-life extension plans and the design of equitable pension reforms.

Descent, marriage, and residence practices of a 3,800-year-old pastoral community in Central Eurasia

“…This was especially true for females, for whom life expectancy was estimated to be more than 8 y shorter than for males (females: 27.8 y vs. males: 36.2 y, SI Appendix , section 2 ). If longevity is considered to be an indicator for societal health ( 83 ), the life expectancy values reported here, as well as those for other contemporary sites in the area, suggest the possibility of health constraints such as recurring human or livestock diseases.…”

Are Measures of Health Status for the Total Population Good Proxies for the Health of the Older Population in International Comparison Studies?

“…One of the important shortcomings of this indicator is the fact that it does not take into account health status directly, using only mortality as a proxy. Despite this, LE is still used in many analyses, including international comparisons, as mortality data are routinely collected by countries from a variety of sources and interpretation of differences in these indicator values is intuitive [22][23][24][25].…”

Multi-country clustering-based forecasting of healthy life expectancy

“…Regularities have been observed also in HLE (Permanyer et al. 2022a ) with a less optimistic picture obtained looking at life expectancy trends. Therefore, it seems appropriate to identify clusters of countries having common characteristics detected by life expectancy before conducting the forecast by a multi-population model.…”