Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Oct;16(10):1973-1991.
doi: 10.1007/s13300-025-01781-0. Epub 2025 Sep 3.

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

Guy Fagherazzi  1 , Pierre Serusclat  2 , Barbara Roux  3 , Oriane Bretin  3 , Emilie Casarotto  3 , Pascaline Rabiéga  3 , Yolaine Rabat  3 , Cécile Berteau  4 , Antoine Pouyet  5 , Michael Joubert  6
Affiliations

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

Guy Fagherazzi et al. Diabetes Ther. 2025 Oct.

Abstract

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.

Keywords: Epidemiology; France; Health outcomes; Machine learning algorithm; Type 1 diabetes; Type 2 diabetes.

PubMed Disclaimer

Conflict of interest statement

Declarations. Conflicts of Interest: Guy Fagherazzi has provided advisory/speaking services and/or has received research grants and/or speaker honoraria from MSD, MSDAvenir, Eli Lilly, Roche Diabetes Care, Sanofi, AstraZeneca, Danone Research, Diabeloop, Bristol Myers Squibb, L'Oréal R&D, Abbvie Pharmaceutical, Pfizer, Vitalaire and Akuity Care. Michael Joubert declares consultant and/or speaker fees and/or research support from Abbott, Air Liquide Santé International, Amgen, Asdia, AstraZeneca, Bayer, BMS, Boehringer-Ingelheim, Dexcom, Dinno Santé, Glooko, Insulet, Lifescan, Lilly, LVL médical, Medtronic, MSD, Nestle HomeCare, Novonordisk, Organon, Orkyn, Roche Diabetes, Sanofi, Tandem, Vitalaire, Voluntis, Ypsomed. Michael Joubert is an Editorial Board Member of Diabetes Therapy. Michael Joubert was not involved in the selection of peer reviewers for the manuscript nor any of the subsequent editorial decisions. Pierre Serusclat has provided advisory/speaking services and/or research support from Roche Diabetes Care as an expert on the scientific committee of the present study. Cécile Berteau and Antoine Pouyet are employees of Roche Diagnostics France and Timkl France, respectively. Oriane Bretin, Emilie Casarotto, Yolaine Rabat, Pascaline Rabiéga and Barbara Roux are employees of IQVIA RWS France. Ethical Approval: The study was approved by the French Data Protection Supervisory Authority “Commission Nationale Informatique et Libertés” (CNIL) (authorization no. 919119). As this study was a retrospective analysis of data from the SNDS, no informed consent was required and therefore not obtained. Retrospective analysis of pseudonymized data and therefore consent for publication is not required.

Figures

Fig. 1
Fig. 1
Cohort flowchart diagram. T1D type 1 diabetes, T2D type 2 diabetes
Fig. 2
Fig. 2
Outpatient consultations in individuals with T1D and T2D (overall, insulin-treated (T2Di) and non-insulin-treated (T2Dni)), in 2019. T1D type 1 diabetes, T2D type 2 diabetes (treated with insulins or other antidiabetic treatments than insulins and untreated individuals), T2Di type 2 diabetes treated with insulins, T2Dni type 2 diabetes treated with other antidiabetic treatments than insulins
Fig. 3
Fig. 3
Annual prevalence of T1D and T2D (overall, insulin-treated (T2Di) and non-insulin-treated (T2Dni)), by calendar year, France. T1D type 1 diabetes, T2D type 2 diabetes (treated with insulins or other antidiabetic treatments than insulins and untreated individuals), T2Di type 2 diabetes treated with insulins, T2Dni type 2 diabetes treated with other antidiabetic treatments than insulins. Annual prevalence for each subgroup of interest was calculated among the total French population (≥ 18 years) in a given year (INSEE data)
See this image and copyright information in PMC

References

    1. Magliano DJ, Chen L, Islam RM, et al. Trends in the incidence of diagnosed diabetes: a multicountry analysis of aggregate data from 22 million diagnoses in high-income and middle-income settings. Lancet Diabetes Endocrinol. 2021;9(4):203–11. - PMC - PubMed
    1. IDF Diabetes Atlas. https://diabetesatlas.org/. Accessed March 22, 2024.
    1. Europe diabetes report 2000–2045. https://diabetesatlas.org/data-by-indicator/. Accessed March 22, 2024.
    1. Papatheodorou K, Banach M, Bekiari E, Rizzo M, Edmonds M. Complications of diabetes 2017. J Diabetes Res. 2018;2018:3086167. - PMC - PubMed
    1. Tomic D, Shaw JE, Magliano DJ. The burden and risks of emerging complications of diabetes mellitus. Nat Rev Endocrinol. 2022;18(9):525–39. - PMC - PubMed

LinkOut - more resources