Over time, diabetes can lead to vascular disorders and nerve damage in the extremities. Late or inadequate treatment for conditions such as diabetic foot syndrome can necessitate amputation of the lower limb. This indicator is also part of the biennial Health at a Glance report from the Organisation for Economic Co-operation and Development (OECD) (OECD, 2017).
- The rate of diabetes-related amputations per 100,000 residents is decreasing from 2015 to 2020.
- In contrast to men, rates for women show a steady decline.
- The rate of diabetes-related amputations is significantly increased in federal states with a higher diabetes prevalence and regions with strong socioeconomic deprivation.
By regional socioeconomical deprivation
Between 2015 and 2020, major amputation rates for diabetes per 100,000 residents show a decrease from 11.3 to 10.6. Women show stronger decreasing rates from 7.1 to 5.9 in the considered period. Compared to women, rates for men are three times higher. After decreasing to 15.4 per 100,000 residents in 2019, the rate of aputations has been rising again slightly to 15.5 in 2020. The federal states of Thuringia, Mecklenburg-Western Pomerania, or Saxony-Anhalt show significantly higher diabetes amputation rates per 100,000 residents in 2019, with values of 11.5, 14.8, and 11.9 for women and 28.6, 37.2, and 35.0 for men, respectively, compared with federal states such as Baden-Württemberg (women: 4.7; men: 12.7), Hesse (women: 4.2; men: 11.6), or Hamburg (women: 3.1; men: 8.2). For both men and women, the highest rates of diabetes-related amputations are shown in regions with the highest socioeconomic deprivation.
The decrease in major amputations continues in 2020 for women. For men, the rate remains constant compared to the two previous years. Standardized to the age distribution of Germany as of December 31, 2020, however, a continuation of the decline in amputations over time is also evident for men. Regional differences can be observed for both sexes, which correspond to the distribution of diabetes prevalence by federal state (fact sheet “Prevalence of documented diabetes”). The same applies to regions with high socioeconomic deprivation, as diabetes prevalence is also higher here than in regions with lower socioeconomic deprivation (Grundmann et al. 2014).
Show more information on methodology and data sources
The indicator Diabetes-related amputations is defined as the number of amputations of the lower limb above the ankle (major amputations, OPS Codes: 5‑864/5‑865.0) per 100,000 residents (in patients aged 15 years and over with a main or secondary diagnosis of diabetes, E10.-/E11.-E13.-/E14.) per year.
All hospital cases that are billed in accordance with the DRG remuneration system.
Diagnosis-related groups statistics (DRG statistics) that include all approximately 19 million inpatient cases per year in Germany.
- Observed relative values: The number of amputations per 100,000 residents.
- Observed absolute values: Number of lower extremity amputation cases above the ankle (OPS codes: 5-864/5-865.0) in persons (over 15 years) with principal or secondary diagnosis (E10.-/E11.-E13.-/E14.).
- Age standardisation: Direct age standardisation used five-year age groups for the ages 15 to 19 until 80 to 84, and a separate group for the ages 85 and over. The resident population of Germany as of 31 December 2020 was used as the reference population.
- Stratification: The stratification by federal state is based on place of residence. Stratification by regional socioeconomic deprivation is based on the German Index of Socioeconomic Deprivation (GISD, Revision 2020) (Kroll et al. 2017). The index provides information on all rural and urban districts and divides them into quintiles ranging from lowest to highest socioeconomic deprivation. The amputation rate was calculated stratified for each quintile after linkage of the GISD with diabetes-related amputations at the district level (ecological correlation).
Diagnosis-related Groups (DRG) statistics contain information on all hospitalisations in Germany. They include main and secondary diagnoses, operations and other procedures, as well as information on patients’ age, sex and place of residence. The data are documented on a case by case basis, which means that a person hospitalised more than once will be classified as several cases. Data quality depends on coding practices and other aspects of documentation.