Max Planck Institute for Demographic Research

A study analyzes the complex the relationship between personality and parenthood

A study confirms this trend, while also showing major differences between men and women, eastern and western Germany, and low and high-skilled workers

Women with very young children need more support

Data bias can skew results of social media studies
 

A new Max Planck Center in Rostock and Helsinki

More than one-third of the world’s population uses Facebook at least once a month. In the process, Facebook collects a lot of data from its users, which represents a valuable but barely tapped source for scientific research. Emilio Zagheni and his team at the Max Planck Institute for Demographic Research in Rostock are using social media data in an attempt to track and predict international migration.

It’s easy to overlook the marginalized. Social exclusion can have very different causes and consequences – also in the context of migration. Six Max Planck Institutes have now joined forces for a cross-institute project focusing on the topic. The project examines, among other things, the question of why immigrants often lose their good health. It explores what prompts Somalis to move from Europe to Kenya, and what consequences the deal between the EU and Turkey might have for the rights of asylum seekers in Greece. Their common aim is to uncover exclusion and develop fair rules to regulate migration.

Eternal life lasts a very long time. Nevertheless, Ralf Schaible from the Max Planck Institute for Demographic Research in Rostock can already affirm that the freshwater polyp Hydra comes quite close to this ideal. In a long-term experiment initiated by the institute’s Director James W. Vaupel, he and his colleagues investigate why, under certain circumstances, Hydra doesn’t age.

Demographers are astounded at the way human mortality continues to drop. This trend started well over a hundred years ago. What used to be a statistical investigation of death rates has now developed into the science of longevity. This is what Jutta Gampe focuses on at the Max Planck Institute for Demographic Research in Rostock.

Online genealogy data are beset by a number of biases that affect their representativity. Diego Alburez-Gutierrez from the Max Planck Institute for Demographic Research and his colleague Robert Stelter show this with the example of a user-generated dataset from the FamiLinx project. They calculate the remaining life expectancy of men aged 30 who lived in the German Empire between 1500 and 1910 and the Netherlands between 1600 and 1909. Their work highlights the need to develop bias-correction methods to analyze historical population trends derived from crowdsourced digital data.

A team including researchers from the Max Planck Institute for Demographic Research is collecting mortality data in a new database. These data allow to follow the course of the Covid-19 pandemic only a few weeks later. An analysis for 37 high-income countries based on the data has shown that life expectancy decreased in 31 of the countries in 2020. A total of about 28 million more years of life were lost than expected. And the years of life lost associated with the Covid-19 pandemic were more than five times higher than those associated with the seasonal influenza epidemic in 2015. 

Life expectancy in the United States is lagging behind other industrialized nations. Recently, US life expectancy has even decreased. A new study by the Max Planck Institute for Demographic Research now shows: Mortality from cardiovascular diseases was a more decisive factor for this development than the often-mentioned opioid crisis.

It is impossible to provide timely estimates of human migration flows after natural disasters by only using traditional data from statistical authorities. Facebook offers new opportunities as a complementary source of information. Emilio Zagheni and his collaborators traced relocation after Hurricane Maria 2017 from Puerto Rico to the US mainland and found return migration, too.

Lifespan variation is a metric of mortality difference in age at death between individuals. With empirical examples from Germany, the USA, and Finland, we show how this variation is overlooked by monitoring metrics of average mortality levels, such as life expectancy. The latter captures the magnitude of survival gains; lifespan variation captures the equality in survival improvement. To gain a full picture of population health, we need to monitor both.