EDUCATIONAL STRATEGIES IN QUILOMBOLA COMMUNITIES: USE OF BAYESIAN NETWORKS FOR HEALTH RISK ASSESSMENT

Abstract

This study reports experiences in health education in two quilombola communities in Rio Grande do Sul, highlighting the use of Bayesian networks (RB) to assess the risks of  type 2 diabetes mellitus (DM2) and systemic arterial hypertension (SAH). It was conducted as a cross-sectional and observational study, using the methodology of problematization, with stages that included observation, definition of key points, theorizing, hypothesis and practical application. The modeling of the quality of life was carried out using the Netica software, with the implementation of Bayesian networks (RBs), allowing the insertion of probabilities of occurrence of the variables through the network nodes. The profile of the 34 participants revealed a predominance of women (79.4%), aged between 30 and 59 years (55.9%) and with a mean body mass index (BMI) of 32.5 kg/m². Among them, 51.5% had a diagnosis of SAH and 23.5% of DM2. Inadequate diet was observed, with high sugar consumption (38.2%) and low use of whole foods (3.0%). The RBs had a sensitivity of 71.42% for DM2 and 76.47% for SAH, and specificity of 77.7% and 88.23%, respectively, demonstrating high precision. The modeling also identified a significant association between the risks of the diseases with factors such as BMI, age, family history and glucose. Educational strategies contributed to preventing complications and promoting quality of life, while MB proved to be promising tools for diagnosis and health education. The study reinforces the importance of inclusive public policies aimed at quilombola communities.

DOI: https://doi.org/10.56238/sevened2024.039-008