P-408: Incidence by sex of type 1 diabetes in the metropolitan area of the Aburrá Valley, Colombia, 2015–2024: analysis of the step-T1D study
J P Perez Bedoya, C A Pérez Aguirre, N C Barengo, J R Lacalle Remigio, P A Diaz ValenciaAbstract
Introduction
The global incidence of type 1 diabetes (T1D) has increased over recent decades; however, epidemiological data from Colombia remain scarce
Objectives
To estimate sex-specific incidence rates of T1D in the Metropolitan Area of the Aburrá Valley (MAAV) between 2015 and 2024
Methods
We conducted a retrospective observational study using electronic health records from five major healthcare institutions in the Metropolitan Area of the Aburrá Valley (MAAV). From these institutions, three analytical data sources were constructed: private, public, and mixed healthcare providers. We included individuals aged ≤35 years with a diagnosis of T1D residing in the MAAV. Incidence was estimated using capture–recapture methods across two five-year periods (2015–2019 and 2020–2024). Population projections from the National Department of Statistics were used as denominators. Analyses were performed in R using the dga package with Bayesian model averaging. Results reflect the status of the project database as of April 2026
Results
A total of 413 T1D patients were identified (51.6% female). The estimated overall cumulative incidence was 15.4 (CrI: 11.5–24.3) for 2015–2019 and 14.8 (CrI: 8.5–43.4) for 2020–2024 per 100,000 persons. Among females, 195 incident cases (95% CrI: 136–381) were estimated for 2015–2019 and 92 (95% CrI: 77–185) for 2020–2024, corresponding to cumulative incidences of 18.4 (95% CrI: 12.8–35.9) and 8.6 (95% CrI: 7.2–17.2) per 100,000 persons, respectively. Among males, 125 incident cases (95% CrI: 101–245) were estimated for 2015–2019 and 268 (95% CrI: 99–1420) for 2020–2024, with corresponding cumulative incidences of 12.4 (95% CrI: 10.0–24.3) and 26.2 (95% CrI: 9.7–138.7) per 100,000 persons, respectively
Conclusions
This study provides the first population-based estimates of T1D incidence in the MAAV and highlights the value of capture–recapture methods; the inclusion of additional data sources in the project is expected to improve the precision of the estimates