Análise de redes complexas para o estudo da qualidade de vida em saúde bucal

Abstract

Complex network analysis is an approach based on graph theory and computational algorithms, widely used to understand the structure of relationships in complex systems, including oral health. This study aimed to apply complex network analysis to investigate the quality of life in oral health, using secondary data from the São Paulo State oral health survey, with a sample of 17,560 participants. The methodology employed the R software and the "bootnet" package, which allows for statistical network inference using the bootstrap technique. Four main centrality measures were evaluated: Betweenness, Closeness, Strength, and Expected Influence. The results showed that the items QV5 (Stopped practicing sports) and CP3 (Self-perception of happiness) presented the highest betweenness, while QV4 (Stopped social life) and QV5 stood out in terms of closeness and strength. For expected influence, the variable QV3 (Nervousness/irritation) was the most relevant. These findings demonstrate the ability of complex network analysis to reveal hidden relationships and patterns in the perception of quality of life in oral health. It is concluded that the science of complex networks is a promising analytical tool for understanding interactions between variables and developing personalized interventions in oral health.