Inequality in Mortality between Black and White Americans by Age, Place, and Cause, and in Comparison to Europe, 1990-2018
Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990-2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in rich and poor U.S. areas and with reference to six European countries.
Inequalities in life expectancy are starker in the U.S. than in Europe. In 1990 White Americans and Europeans in rich areas had similar overall life expectancy, while life expectancy for White Americans in poor areas was lower. But since then even rich White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%.
Black life expectancy increased more than White life expectancy in all U.S. areas, but improvements in poorer areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black mortality reductions included: Cancer, homicide, HIV, and causes originating in the fetal or infant period.
Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990-2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both rich and poor areas.
We would like to thank James Banks, Sonya Krutikova, and Kjell Salvanes for organizing the IFS working group on geographical approaches to measuring inequality in mortality, with financial support from the ESRC Centre for the Microeconomic Analysis of Public Policy at IFS (ES/T014334/1). Claudia Costa received support from the Science and Technology Foundation (FCT), the European Social Fund, and the Centro Operational Programme (SFRH/BD/132218/2017). Paula Santana received support from the Centre of Studies in Geography and Spatial Planning (UIDB/04084/2020), through an FCT fund. Aline Bütikofer, René Karadakic, and Kjell Salvanes received support from the Research Council of Norway through project No. 275800 and through its Centres of Excellence Scheme, FAIR project No. 262675 and by the NORFACE DIAL grant 462-16-050. Peter Redler received support from the Elite Network of Bavaria within the Evidence-Based
Economics programme. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Marlies Bar acknowledges support from the Initiative for Smarter Choices for Better Health funded by Erasmus University.René Karadakic
This project was partially supported by the Research Council of Norway through project No. 275800 and through its Centres of Excellence Scheme, FAIR project No. 262675 and by NORFACE DIAL grant No. 462-16-050.Carlos Riumallo-Herl
Carlos Riumallo Herl received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 840591.Kjell Salvanes
see the note from Aline ButikoferTom Van Ourti
Tom Van Ourti got support from the Initiative for Smarter Choices for Better Health funded by Erasmus University.