Life expectancy at birth is one of the most important and direct measures of a population’s health and well-being. Inequality in life expectancy across societal groups is a key indicator of deeper social and economic inequalities. Information about differences in life expectancy across places is especially useful for policy makers who need to direct health and infrastructure investments toward the people who would benefit most.
Unfortunately, for small areas there is often a lot of coincidental “noise” in the short-term mortality data that we use to calculate life expectancy. For example, one fatal traffic accident with two 25-year-old drivers might raise a small rural county’s estimated death rate at age 25, and thus reduce its estimated life expectancy. In other places there may be lucky events that lead to lower mortality. Such coincidences aren’t likely to be repeated every year, however. That makes life expectancy comparisons across places with small populations potentially unreliable, and therefore much less useful for policy makers.
In a research article published (in English) in the leading German medical journal, Deutsches Ärzteblatt, we used advanced statistical modeling to overcome this problem and produce much more reliable estimates of both male and female life expectancy for 402 small areas in Germany. These areas, roughly equivalent to US counties, have populations as small as 34000 and as large as 3.6 million.
We show (see maps) that there is considerable variation in life expectancy across places in Germany. Male life expectancy ranges from 75.8 to 81.2 years, depending on location. Female life expectancy varies between 81.8 and 85.7. Life expectancy differences of 4-5 years are quite large for a rich country like Germany with good social services.
Somewhat surprisingly, Germany has as a North-South divide in local life expectancies, in addition to the East-West divide that we might expect from post-WWII history. For both men and women, the longest lives are in the South, while the shortest are in the former East Germany and in the industrial “Rust Belt” in the West.
This study combines new statistical methods with the most recent data to produce improved local life expectancy estimates. We hope that the results are useful for better understanding of the social processes that produce inequality, and for better targeting of public resources.
Dr. Roland Rau is Professor of Demography at the University of Rostock, and a researcher at the Max Planck Institute for Demographic Research. He has enjoyed his research stays at FSU and is looking forward to another visit when travel is possible again.
Dr. Carl Schmertmann is the William J. Serow Professor of Economics at FSU, and Director of FSU’s Center for Demography and Population Health.
Source for featured image: https://www.pexels.com/photo/germany-flag-in-front-of-building-109629/