Modelagem da obesidade adulta nas nações: uma análise via modelos de regressão beta e quantílica

• Autor(a) principal: Souza, Saul de Azevêdo
• Data de Publicação: 2017
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFPB
• Texto Completo: https://repositorio.ufpb.br/jspui/handle/tede/9065
• topic: Obesidade; Regressão beta; Regressão quantílica; Obesity; Beta regression; Quantile regression; CIENCIAS DA SAUDE::SAUDE COLETIVA

In this dissertation the beta regression models with variable dispersion and quantile regression are discussed. Therefore, an introduction was made with the objective of motivating its discussion in epidemiological studies, emphasizing the problematization around obesity. The application of these methods considered a real data set, obtained from public information sources, referring to adult obesity in the nations in the year 2014. After the descriptive analysis of the data it was verified that 50% of the nations present values of the proportion of obese adults greater than 0.20. In addition, viewing the obesity map by nation showed that the highest concentration of countries with the lowest obesity values is found in the continents of Asia and Africa. On the other hand, the highest concentrations of obese are found in the continents of America and Europe. Also, from the graphical analysis of the box-plot a possible difference in the proportions of obese adults between the continents of America and Europe with those of Africa and Asia was observed. After adjusting the beta and quantile regression models it was verified that the covariates average alcohol consumption in liters per person, percentage of insufficient physical activity and percentage of the population living in urban areas have a positive effect on the response variable. That is, individually such covariables tend to increase obesity values in the countries when the other covariables remain constant. In addition, the life expectancy variable in years presented a positive effect and was significant only for the variable regression beta regression model. Finally, analyzing the measures of prediction errors, it was verified that the estimates from the beta regression are more accurate when the mean square error and the total percentage error were evaluated. Therefore, for questions of predicting values for adult obesity in the nations in 2014, the beta regression model with variable dispersion was more suitable for this purpose.