Evidence map›Paper›PMID 33087229›Full record

ArticleDeutsches Arzteblatt international2020

District-Level Life Expectancy in Germany.

Roland Rau, Carl P Schmertmann

Abstract read
In one paragraph

Article in Deutsches Arzteblatt international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

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  7. [Regional differences and trends in healthy life expectancy in Germany].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024
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  8. Article
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  12. The underwhelming German life expectancy.European journal of epidemiology · 2023
    Article
  13. Article
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  17. Social Determinants of Remaining Life Expectancy at Age 60: A District-Level Analysis in Germany.International journal of environmental research and public health · 2022
    Article
  18. Article
  19. Redistributing ill-defined causes of death - a case study from the BURDEN 2020-project in Germany.Archives of public health = Archives belges de sante publique · 2021
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  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Roland RauDepartment of Sociology and Demography, University of Rostock; Max Planck Institute forDemographic Research, Rostock.
Carl P SchmertmannCenter for Demography and Population Health, Florida State University, Tallahassee, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdentifying regions with low life expectancy is important to policy makers, in particular for allocating resources in the health system. Life expectancy estimates for small regions are, however, often unreliable and lead to statistical uncertainties when the underlying populations are relatively small.

methodsWe combine the most recent German data available (2015-2017) with a Bayesian model that includes several methodological advances. This allows us to estimate male and female life expectancy with good precision for all 402 German districts and to quantify the uncertainty of those estimates.

resultsAcross districts, life expectancy varies between 75.8 and 81.2 years for men and from 81.8 to 85.7 years for women. The spatial pattern is similar for women and men. Rural districts in eastern Germany and some districts of the Ruhr region have relatively low life expectancy. Districts with relatively high life expectancies cluster in Baden-Wuerttemberg and southern Bavaria. Exploratory analysis shows that average income, population density, and number of physicians per 100 000 inhabitants are not strongly correlated with life expectancy at district level. In contrast, indicators that point to particularly disadvantaged segments of the population (unemployment rate, welfare benefits) are better predictors of life expectancy.

conclusionsWe do not find a consistent urban-rural gap in life expectancy. Our results suggest that policies that improve living standards for poorer segment of the population are the most likely to reduce the existing differences in life expectancy.

Indexed as

IncomeLife ExpectancyAgedAged, 80 and overBayes TheoremFemaleGermanyHumansMaleSocioeconomic Factors

Identifiers

PMID33087229
PMCPMC7588608

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.