Measuring Inequality in Longevity: the AUM Index
In recent decades, the issue of inequality in longevity has become increasingly central to the public health debate. This is particularly evident when looking at differences between and within countries, where disparities in life expectancy and quality of life significantly affect a population’s perception of health. For example, during the COVID-19 pandemic, it was clear that social inequalities amplified the negative effects of the virus, with much higher mortality rates among the poorer segments of the population. Data on life expectancy also show significant variations: in Italy, for example, there is a marked difference between northern and southern regions.
One of the most recent and innovative measures to study these phenomena is the Average Uneven Mortality (AUM) index, developed by Marco Bonetti, director of the Dondena Centre for Research on Social Dynamics and Public Policy at Bocconi University, along with co-authors Ugofilippo Basellini of the Max Planck Institute for Demographic Research and Andrea Nigri of the University of Foggia. The AUM index is based on the correlation between time to death and its cumulative risk function, allowing inequalities in mortality to be analyzed more precisely and comparably across different populations and time periods.
According to Bonetti, “The AUM index provides a new tool to better understand mortality patterns and inequality in longevity. This normalized measure allows for meaningful comparisons across countries and over time, facilitating the identification of trends in population health.”
In the paper titled “The Average Uneven Mortality index: Building on the ‘e-dagger’ measure of lifespan inequality“ published in Demographic Research, Bonetti and his co-authors present the AUM index as an innovative indicator for the study of mortality and inequality in longevity. The AUM, which is a number between 0 and 1, equals 1 if and only if the mortality rate is constant with age, representing a useful tool for identifying variations in mortality within populations.
One of the most interesting aspects of the application of the AUM index is its ability to show how inequality in longevity has changed over time. Using data from the Human Mortality Database, the authors observed that the AUM index at birth decreased until the 1950s, then reversed the trend and increased in the following years. This change reflects significant improvements in infant survival and elderly mortality rates during this period.
Normalization of the AUM index allows more accurate comparisons than other measures of inequality in longevity, facilitating analysis of global and local trends in population health. This ability to compare is essential for understanding demographic dynamics and their policy and social implications.
