Description

Introduction

Various research studies and epidemiological surveillance systems have shown a sustained increase in the incidence and prevalence of Type 1 Diabetes (T1D) worldwide. However, the International Diabetes Federation warns that significant information gaps, outdated data, and high levels of underreporting persist, limiting a true understanding of the disease’s magnitude and behavior.

Global Diabetes Trends

In Colombia, available epidemiological evidence is even more limited. In this context, the metropolitan area of the Valle de Aburrá, which has experienced profound demographic, environmental, and social changes in recent years, represents an ideal setting to study the evolution of T1D. Generating robust evidence in this region is essential to strengthen epidemiological surveillance, improve health planning, and contribute to global diabetes control goals.

Valle de Aburrá Map

Project Objective

To analyze the temporal and geographical trends of the epidemiological profile of T1D in the metropolitan area of the Valle de Aburrá (Colombia) in recent years.

Methodology

An observational, descriptive, cross-sectional study will be conducted using retrospective data for the analyzed period.

Multiple secondary information sources will be integrated, including healthcare providers, patient associations, and vital statistics.

The population will consist of individuals clinically diagnosed with T1D residing in the Valle de Aburrá.

To estimate incidence and prevalence, the capture-recapture method will be applied using different data sources.

Mortality rates will be based on official records with cause of death corresponding to code E10 (ICD-10).

Spatial epidemiology and temporal trend analyses will identify patterns and generate future projections.

Expected Impact

This project will generate a comprehensive epidemiological profile of T1D. These tools will guide evidence-based public health policies to improve clinical outcomes, resource management, and disease awareness. Furthermore, it creates a replicable model for continuous monitoring in Latin America, aligning with Sustainable Development Goals to reduce non-communicable diseases.