Predicting the prevalence of type 2 diabetes in Brazil: a modeling study

Front Public Health. 2024 May 2:12:1275167. doi: 10.3389/fpubh.2024.1275167. eCollection 2024.

Abstract

Aims: We adopted a modeling approach to predict the likely future prevalence of type 2 diabetes, taking into account demographic changes and trends in obesity and smoking in Brazil. We then used the model to estimate the likely future impact of different policy scenarios, such as policies to reduce obesity.

Methods: The IMPACT TYPE 2 DIABETES model uses a Markov approach to integrate population, obesity, and smoking trends to estimate future type 2 diabetes prevalence. We developed a model for the Brazilian population from 2006 to 2036. Data on the Brazilian population in relation to sex and age were collected from the Brazilian Institute of Geography and Statistics, and data on the prevalence of type 2 diabetes, obesity, and smoking were collected from the Surveillance of Risk and Protection Factors for Chronic Diseases by Telephone Survey (VIGITEL).

Results: The observed prevalence of type 2 diabetes among Brazilians aged over 25 years was 10.8% (5.2-14.3%) in 2006, increasing to 13.7% (6.9-18.4%) in 2020. Between 2006 and 2020, the observed prevalence in men increased from 11.0 to 19.1% and women from 10.6 to 21.3%. The model forecasts a dramatic rise in prevalence by 2036 (27.0% overall, 17.1% in men and 35.9% in women). However, if obesity prevalence declines by 1% per year from 2020 to 2036 (Scenario 1), the prevalence of diabetes decreases from 26.3 to 23.7, which represents approximately a 10.0% drop in 16 years. If obesity declined by 5% per year in 16 years as an optimistic target (Scenario 2), the prevalence of diabetes decreased from 26.3 to 21.2, representing a 19.4% drop in diabetes prevalence.

Conclusion: The model predicts an increase in the prevalence of type 2 diabetes in Brazil. Even with ambitious targets to reduce obesity prevalence, type 2 diabetes in Brazil will continue to have a large impact on Brazilian public health.

Keywords: demographic changes; modeling; obesity trends; projection; target strategies; type 2 diabetes prevalence.

MeSH terms

  • Adult
  • Aged
  • Brazil / epidemiology
  • Diabetes Mellitus, Type 2* / epidemiology
  • Female
  • Forecasting
  • Humans
  • Male
  • Markov Chains
  • Middle Aged
  • Obesity* / epidemiology
  • Prevalence
  • Risk Factors
  • Smoking / epidemiology

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. The National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq) supported all the funding received during this study; Grant number 442891/2019-9. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.