Nationwide Trends in Type 1 and Type 2 Diabetes in France (2010–2019): A Population-Based Study Using a Machine Learning Classification Algorithm

Introduction Diabetes represents an increasing public health challenge in France, yet national data distinguishing type 1 from type 2 diabetes and insulin use remain limited. This study aimed to describe trends in the epidemiology, care pathways and health outcomes of adult individuals living with t...

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Vydáno v:Diabetes therapy Ročník 16; číslo 10; s. 1973 - 1991
Hlavní autoři: Fagherazzi, Guy, Serusclat, Pierre, Roux, Barbara, Bretin, Oriane, Casarotto, Emilie, Rabiéga, Pascaline, Rabat, Yolaine, Berteau, Cécile, Pouyet, Antoine, Joubert, Michael
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cheshire Springer Healthcare 01.10.2025
Springer
Springer Nature B.V
Témata:
Adults
Algorithms
Antidiabetics
Cardiology
Chronic illnesses
Classification
Diabetes
Disease
Endocrinology
Epidemiology
Forecasts and trends
Gestational diabetes
Health aspects
Insulin
Internal Medicine
Machine learning
Medicine
Medicine & Public Health
Mortality
Original Research
Population-based studies
Public health
Trends
Type 1 diabetes
Type 2 diabetes
France
Health outcomes
France
Epidemiology
Type 2 diabetes
Machine learning algorithm
Type 1 diabetes
ISSN:1869-6953, 1869-6961
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Shrnutí:Introduction Diabetes represents an increasing public health challenge in France, yet national data distinguishing type 1 from type 2 diabetes and insulin use remain limited. This study aimed to describe trends in the epidemiology, care pathways and health outcomes of adult individuals living with type 1 or type 2 diabetes in France from 2010 to 2019. It focused on individuals treated or not with insulin and applied a predictive classification algorithm to accurately distinguish between diabetes types using real-world data. Methods A 10-year retrospective population-based cohort study was conducted from a representative one-tenth sample of the French national healthcare database (i.e. SNDS, Système National des données de Santé), covering nearly the entire French population. Adults (≥ 18 years) affiliated with the general insurance scheme were included. A machine learning algorithm, trained on clinical data from general practitioners, was applied to classify diabetes type. Annual trends in prevalence, incidence, comorbidities, treatments, outpatient care, complications and mortality were assessed. Results Among an extrapolated 5.5 million individuals with diabetes in 2019, 3.5% had type 1 diabetes and 96.5% had type 2 diabetes. The prevalence of type 2 diabetes increased from 6.2% in 2010 to 8.0% in 2019, while type 1 diabetes remained stable. Comorbidity rates were high and increasing in insulin-treated individuals with type 2 diabetes. In 2019, 15.3% of insulin-treated individuals with type 2 diabetes had at least one complication-related hospitalisation. Specialist consultations were underused, especially in type 2 diabetes. The mortality rate in individuals with type 1 diabetes declined from 2.6% to 1.5%, with an increase in mean age at death. Conclusion This national study provides updated insights into diabetes in France and highlights the need to improve access to specialised care and reinforce long-term surveillance strategies.
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ISSN:1869-6953
1869-6961
DOI:10.1007/s13300-025-01781-0