New study on life expectancy in Germany

Armut can affect health and therefore also health Life expectancy impact. In itself, this is not a new finding. Nevertheless, a study now shows what this means. In Germany, they conducted Roland Rau, professor of demography at the University of Rostock and Max Planck Fellow at the Max Planck Institute for Demographic Research, and Carl Schmertmann, professor of economics at Florida State University.

Using a new statistical method that largely rules out random fluctuations in areas with a low population density, the two have examined life expectancy in individual counties. Because, as they write in their study, which appeared in the “Ärzteblatt”, small-scale estimates are crucial to “identify marginalized regions”. On the one hand, the results are surprising, but on the other hand, they are not. Because in the wealthier south of Germany, people live longer on average. For women, the range between life expectancies across Germany is just under four years, for men just over five. Women in the Starnberg district south of Munich are the oldest at an average of 85.7 years. Women in the Salzland district in Saxony-Anhalt have the lowest life expectancy with an average of 81.8 years. Men have the highest life expectancy at 81.2 years in the Munich district, the lowest at 75.8 years in Bremerhaven.

Infographic
People live longer in the south – Estimated life expectancy in Germany

Roland Rau finds it surprising that some factors, which could be assumed to have an impact on life expectancy, did not play a major role. Population density, average income and the number of doctors per 100,000 population did not correlate very well with life expectancy. So whether people lived in the country or in the city did not necessarily affect their life expectancy. Those who live in the countryside in eastern Germany have an on average lower life expectancy than eastern German townspeople, says Rau. But that’s not the case in the West. Here it is more like cities like Essen, Duisburg or Gelsenkirchen that have a lower life expectancy.

Disadvantage has an impact

The researchers saw a stronger correlation between lower life expectancy and extremely disadvantaged sections of the population. There is a greater correlation between a lower life expectancy and the fact that people receive Hartz IV or there is more child poverty. But that doesn’t mean that there must be a causal connection between the two things: “We collected the data at the district level. And you can’t deduce circles from individuals, ”says Rau.

The scientist finds the results “disillusioning”. Because studies have shown time and again that socio-economic differences in life expectancy play a role not only in countries like Great Britain or the United States, but also in those that are known for their social policies: in Denmark or Sweden. The study by the scientists now suggests that this also applies to Germany. Even affluent states like Bavaria are not homogeneous, says Rau, there are differences here as well: Life expectancy is also comparatively low in circles in the northeast of Bavaria.

In order to work out these regional differences precisely, Rau and Schmertmann worked on their statistical model for two years. A problem is often that coincidences are more important in areas with low population density. “It’s like throwing a coin: if it falls on one side of ten times twice, then you shouldn’t conclude that the probabilities are distributed that way. The more you throw the coin, the more accurate it becomes, ”says Rau. Figures from a district like Berlin are therefore much more precise than those from a rural area. In order to compensate for this, known data was included in the assessment: “We know that women are older than men. If this is not the case in a circle, we can assume that this is probably a coincidence, ”says Rau. The more data you have, the lower the weight of previous knowledge and vice versa.

The study had two goals, says Rau. On the one hand, the researchers wanted to apply their model. They also wanted to find out whether a correlation between socio-economic factors and life expectancy can be determined at the district level. From the results, he can now conclude no specific instructions, says Rau. Nevertheless, the scientists write: “Our results indicate that measures that improve living standards for poorer sections of the population are most likely to reduce the existing differences in life expectancy.”

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