At a Glance Projects Publications Team

Project

Understanding Mortality Dynamics

Roland Rau, Marcus Ebeling, Torsten Sauer, James W. Vaupel; in Collaboration with Anders Ahlbom, Karin Modig (both: Karolinska Institutet, Stockholm, Sweden), Christina Bohk-Ewald (University of Helsinki, Finland), Eva Kibele (The Statistical Office of the Free Hanseatic City of Bremen, Germany), Sebastian Klüsener (Federal Institute for Population Research, Wiesbaden, Germany), Magdalena Muszyńska (Vienna, Austria)

Detailed Description

The team has developed a novel forecasting mortality model. Two features distinguish it from many other models: (i)It models rates of mortality improvement instead of death rates and (ii)) it allows for the inclusion of trends from other populations when the development in the current population appears to be unlikely to continue as is. The group has also shown that lifespan disparity can be a useful tool to evaluate the plausibility of mortality forecasts. Alternatively, it can be used as a constraint or as a prior in the development of new mortality forecasting models.

Future mortality also depends on the question of what the main drivers for mortality change are: period or cohort effects? We have published a monograph that focuses on the visualization of various aspects of mortality dynamics for many high-income countries and for causes of death, seasonality of death, and progress against cancer in the United States.

In the medium and long term, continued progress in survival and life expectancy will depend on mortality decline among centenarians. Using Swedish register data, the group investigated whether mortality among the extremely old is declining or not. We have not found any convincing indications that mortality among Swedish centenarians declined during the past 30 years.

Finally, we looked at the following question: How will the global trend towards urbanization affect mortality among the elderly in the future? We have shown in a spatial analysis that in Germany and in the UK, urban regions face higher mortality at ages around 60 and 70 but lower mortality at ages 80 and above.

Publications

Modig, K.; Lambe, M.; Ahlbom, A.; Ebeling, M.:

Excess mortality for men and women above age 70 according to level of care during the first wave of COVID-19 pandemic in Sweden: a population-based study

The Lancet Regional Health - Europe 4:100072, 1–7. (2021)    

Ebeling, M.; Meyer, A. C.; Modig, K.:

The rise in the number of long-term survivors from different diseases can slow the increase in life expectancy of the total population

BMC Public Health 20:1523, 1–8. (2020)    

Rau, R.; Bohk-Ewald, C.; Muszynska, M. M.; Vaupel, J. W.:

Visualizing mortality dynamics in the Lexis diagram

Cham: Springer International Publishing, The Springer series on demographic methods and population analysis 44. (2018)    

Bohk-Ewald, C.; Ebeling, M.; Rau, R.:

Lifespan disparity as an additional indicator for evaluating mortality forecasts

Demography 54:4, 1559–1577. (2017)    

Bohk-Ewald, C.; Rau, R.:

Probabilistic mortality forecasting with varying age-specific survival improvements

Genus 73:1, 1–37. (2017)    

Modig, K.; Andersson, T.; Vaupel, J. W.; Rau, R.; Ahlbom, A.:

How long do centenarians survive? Life expectancy and maximum lifespan

Journal of Internal Medicine 282:2, 156–163. (2017)