GSB 7.1 Standardlösung

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Mortality

One of the St. Vincent declaration goals is to align the lifespans of people with diabetes with those of people without diabetes (WHO & IDF, 1990). Until now, estimates of excess mortality have either been based on a selective set of data or their low case numbers have prevented stratification by age and sex (Heidemann & Scheidt-Nave, 2017).

Key messages

  • The age-standardized mortality rate per 1,000 persons aged 30 years and older is more than half higher for persons with diabetes than for persons without diabetes.
  • Women and men with diabetes in Germany show a comparably increased mortality rate compared to women and men without diabetes.
  • With increasing age, mortality rates equalized between the groups with and without diabetes.

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By state

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  • By gender

    Indikatoren_ScreenreaderHinweis_Datentabelle

  • By age

    Indikatoren_ScreenreaderHinweis_Datentabelle

  • By education group

    Indikatoren_ScreenreaderHinweis_Datentabelle

Results

Relative to 1,000 persons, the mortality rate in 2014 was 20.0 for women aged 30 years and older with diabetes and 21.9 for men aged 30 years and older
with diabetes. Thus, the mortality rates per 1,000 persons are each significantly above the values for women aged 30 years and older (12.2) and men aged 30 years and older (12.8). With increasing age, there is a clear convergence of mortality rates between persons with and without diabetes.
In the 30- to 39-year-old age group, the death rate per 1,000 persons is 3.1 in the group with diabetes and 0.55 in the group without diabetes, which is more than 5 times higher in the group with diabetes.
The relative gap of mortality rates reduces in the age group of 50-59 years, it is 10.9 in the group with diabetes and 3.9 in the group without diabetes, being still 2.8 times higher in the group with diabetes.
Finally, the mortality rate per 1,000 persons in the age group 80 years and older is 112.0 in persons with diabetes and 86.3 in persons without diabetes, thus reducing the relative gap in mortality rates between the two groups to a 1.3-fold increase in mortality.

Conclusion

In 2014, the mortality rate for people with diabetes aged 30 and older is higher by more than half than for those without diabetes. These results are consistent with findings from population-based analyses for Germany (Röckl et al., 2017, Paprott et al., 2015). These previous analyses and international studies (Tancredi et al., 2015) are also consistent in showing that the mortality rates of people with and without diabetes converge at an advanced age when most deaths occur. This confirmation of DaTraV data results opens up the prospect of using this data basis for regionalised analyses and for observing the development of excess mortality over time.

Show more information on methodology and data sources

Definition

The indicator mortality is defined as the mortality rate for people with documented diabetes and people without documented diabetes, respectively, as the quotient of the number of deaths in relation to the number of people in the respective population group at risk in one year.

Reference population

Adults aged 30 years and over with and without documented diabetes (in accordance with the definition of the indicator Prevalence of documented diabetes) who have statutory health insurance are included in the analysis

Data source

Claims data from approximately all of the 70 million people with statutory health insurance collected in accordance with the Data Transparency Ordinance (DaTraV data). Around 47 million are at least 30 years old, approximately 6.5 million had documented diabetes in 2013 and around 770,000 died in 2014.

Calculation

  • Observed relative values: The quotient of the number of deaths in relation to 1,000 people with statutory health insurance.
  • Observed absolute values: Number of persons covered by statutory health insurance with documented diabetes and aged 30 years or over who deceased in 2014.

Data quality

DaTraV data are claims data on all people covered by SHI. DaTraV data include documented outpatient and inpatient diagnoses as well as information on prescribed medications. The quality of claims data from SHI depends on conduct of documentation. DaTraV data do not cover people insured by private health insurance and do not provide information on inpatient or outpatient care.