Background: The aim is to estimate age- and sex-specific direct medical costs related to diagnosed type 1 and type 2 diabetes in Germany between 2010 and 2040.
Methods: Based on nationwide representative epidemiological routine data from 2010 from the statutory health insurance in Germany (almost 80% of the population's insurance) we projected age- and sex-specific healthcare expenses for type 1 and 2 diabetes considering future demographic, disease-specific and cost trends. We combine per capita healthcare cost data (obtained from aggregated claims data from an almost 7% random sample of all German people with statutory health insurance) together with the demographic structure of the German population (obtained from the Federal Statictical Office), diabetes prevalence, incidence and mortality. Direct per capita costs, total annual costs, cost ratios for people with versus without diabetes and attributable costs were estimated. The source code for running the analysis is publicly available in the open-access repository Zenodo.
Results: In 2010, total healthcare costs amounted to more than €1 billion for type 1 and €28 billion for type 2 diabetes. Depending on the scenario, total annual expenses were projected to rise remarkably until 2040 compared to 2010, by 1-281% for type 1 (€1 to €4 billion) and by 8-364% for type 2 diabetes (€30 to €131 billion). In a relatively probable scenario total costs amount to about €2 and €79 billion for type 1 and type 2 diabetes in 2040, respectively. Depending on annual cost growth (1% p.a. as realistic scenario vs. 5% p.a. as very extreme setting), we estimated annual per capita costs of €6,581 to €12,057 for type 1 and €5,245 to €8,999 for type 2 diabetes in 2040.
Conclusions: Diabetes imposes a large economic burden on Germany which is projected to increase substantially until 2040. Temporal trends in the incidence and cost growth are main drivers of this increase. This highlight the need for urgent action to prepare for the potential development and mitigate its consequences.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11264726 | PMC |
http://dx.doi.org/10.1186/s12963-024-00337-x | DOI Listing |
Sci Rep
January 2025
School of Sports and Health, Nanjing Sport Institute, Nanjing, China.
Mitochondrial function is crucial for hepatic lipid metabolism. Current research identifies two types of mitochondria based on their contact with lipid droplets: peridroplet mitochondria (PDM) and cytoplasmic mitochondria (CM). This work aimed to investigate the alterations of CM and PDM in metabolic dysfunction-associated steatotic liver disease (MASLD) induced by spontaneous type-2 diabetes mellitus (T2DM) in db/db mice.
View Article and Find Full Text PDFNat Methods
January 2025
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
A key challenge of the modern genomics era is developing empirical data-driven representations of gene function. Here we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-wide genotype-phenotype maps comprising CRISPR-Cas9-based knockouts of >20,000 genes in >30 million cells. Our optical pooled cell profiling platform (PERISCOPE) combines a destainable high-dimensional phenotyping panel (based on Cell Painting) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries.
View Article and Find Full Text PDFNat Med
January 2025
Food Is Medicine Institute, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.
Sci Rep
January 2025
Department of Endocrinology and Metabolism, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
With the rapid advancement of proteomics, numerous scholars have investigated the intricate relationships between plasma proteins and various diseases. Therefore, this study aims to elucidate the relationship between BDH1 and type 2 diabetes using Mendelian randomization (MR) and to identify novel targets for the prevention and treatment of type 2 diabetes through proteomics. This study primarily employed the Mendelian Randomization (MR) method, leveraging genetic data from numerous large-scale, publicly accessible genome-wide association studies (GWAS).
View Article and Find Full Text PDFIntroduction: The most frequent form of diabetes in pediatric patients is polygenic autoimmune diabetes (T1D), but single-gene variants responsible for autoimmune diabetes have also been described. Both disorders share clinical features, which can lead to monogenic forms being misdiagnosed as T1D. However, correct diagnosis is crucial for therapeutic choice, prognosis and genetic counseling.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!