Estimation of the future prevalence of diabetes based on data from the Brazilian Study of Cardiovascular Risk Factors in Adolescents (ERICA).

INTRODUCTION

Diabetes is a significant public health issue due to its high prevalence and multifaceted consequences, impacting both the Brazilian Unified Health System and society. The disease adversely affects people's quality of life and elevates healthcare costs. In 2019, approximately 16 million Brazilians were diagnosed with diabetes mellitus. Understanding the future trends of this disease is crucial for planning effective preventive interventions. This paper aims to estimate the future prevalence type 2 diabetes mellitus on individuals from the Study of Cardiovascular Risk Factors in Adolescents (ERICA) sample, based on the progression of their cardiovascular risk factors.

METHOD

A literature review was conducted to identify predictive models for type 2 diabetes mellitus that utilize cardiovascular risk factors assessed during adolescence to forecast diabetes risk in adulthood. A logistic regression model, grounded in the natural history of clinical variables derived from longitudinal studies, was applied to each individual to determine their risk of developing type 2 diabetes mellitus. Additionally, probabilistic and deterministic sensitivity analyses were performed, incorporating the minimum and maximum values of model parameters.

RESULTS

The predictive model estimated that 15.12% of individuals in the ERICA sample are likely to develop type 2 diabetes mellitus in adulthood, with a range of 1.1% to 28% based on sensitivity analyses. The parameters exerting the most significant influence on these results included diastolic blood pressure and triglycerides, followed by LDL cholesterol and systolic blood pressure.

CONCLUSION

The application of this predictive model to the Study of Cardiovascular Risk Factors in Adolescents (ERICA) sample indicates an estimated prevalence of 15.12% for T2DM over a 20.5-year follow-up period. Studies like this one provide valuable insights for designing targeted interventions to mitigate the progression of diabetes and its associated socioeconomic impacts.