Socioeconomic differences in mortality among 27 million economically active Germans: a cross-sectional analysis of the German Pension Fund data
ObjectivesTo assess disparities in mortality by socioeconomic status in Germany.Design and participantsWe analyse a large administrative dataset of the German Pension Fund (DRV), including 27 million person-years of exposure and 42 000 deaths in 2013. The data cover the economically active populatio...
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Veröffentlicht in: | BMJ open 2019-10, Vol.9 (10), p.e028001-e028001 |
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Zusammenfassung: | ObjectivesTo assess disparities in mortality by socioeconomic status in Germany.Design and participantsWe analyse a large administrative dataset of the German Pension Fund (DRV), including 27 million person-years of exposure and 42 000 deaths in 2013. The data cover the economically active population, stratified by sex and by East and West.Outcome measuresAge-standardised mortality rates and Poisson regression mortality rate ratios (MRRs).ResultsThe risk of dying increases with decreasing income: the MRRs of the lowest to the highest income quintile are 4.66 (95% CI 4.48 to 4.85) among men and 3.06 (95% CI 2.90 to 3.23) among women. The impact of income attenuates after controlling for education and other explanatory variables, especially for females. In the fully controlled model for females, individual income is a weaker predictor of mortality, but there is a clear educational mortality gradient. In the fully controlled model, the MRRs of the unemployed to the employed are 2.09 (95% CI 2.03 to 2.15) among men and 2.01 (95% CI 1.92 to 2.10) among women. The risk of dying is around half as high among foreigners as among German citizens. The socioeconomic disparities are greater among East than West German men.ConclusionsLow socioeconomic status is a major determinant of excess adult mortality in Germany. The persisting East-West differences in male adult mortality can be explained by the higher socioeconomic status of men living in the West, rather than by contextual differences between East and West. These differences can be further monitored using DRV data. |
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ISSN: | 2044-6055 2044-6055 |
DOI: | 10.1136/bmjopen-2018-028001 |