ArticleFrontiers in public health2024
Predicting the prevalence of type 2 diabetes in Brazil: a modeling study.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Palmitoleic acid n7 improves glucose uptake and metabolism and attenuates oxidative stress in human visceral adipocytes.Endocrine · 2026Article
- Differential Expression of Human and Bacterial Proteins Reveals Microbiome-Host Crosstalk in Metabolic Disorders.Proteomics. Clinical applications · 2026Article
- Outcomes of Kidney Transplants From Standard Criteria Donors With Diabetes: A Propensity Score-Matched Study.Kidney medicine · 2026Article
- Gaps Between Guidelines and Practice in Patients with Hypertension and Type 2 Diabetes: A Nationwide Cross-Sectional Study (SNAPSHOT-Brazil Study).Journal of clinical medicine · 2026Article
- Type 2 diabetes mellitus in people with multiple sclerosis: a systematic review and meta-analysis.Acta neurologica Belgica · 2026Review
- Adherence to Insulin Treatment in People With Type 1 or Type 2 Diabetes in Primary Health Care in a Brazilian City: A Cross-Sectional Study.Health science reports · 2026Article
- Enhancing AI-driven forecasting of diabetes burden: a comparative analysis of deep learning and statistical models.Scientific reports · 2025Article
- Association between Self-Care Behaviors and Inadequate Glycemic Control in ELSA-Brasil Participants with Type 2 Diabetes.Arquivos brasileiros de cardiologia · 2025Article
- Individualized selection of recent glucose monitoring devices for self-management based on competitive features.Pakistan journal of medical sciences · 2024Review
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9 authors.
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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.
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