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Identificação de alguns factores de risco para a obesidade e visualização da informação
| Name: | Description: | Size: | Format: | |
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| 4.23 MB | Adobe PDF |
Advisor(s)
Abstract(s)
A obesidade tem se apresentado como uma doença de preocupação
mundial e que precisa de medidas preventivas por conta de um crescimento
significativo em termos globais. A patologia obesidade potencializa o
desenvolvimento de doenças futuras como a hipertensão, diabetes, cardiopatias, e
o câncer. Para o estudo da obesidade é pertinente analisar não só as questões
genéticas, mas também as clínicas e as sócios-demográficas.
O objetivo desse trabalho é identificar alguns fatores de riscos a obesidade
e buscar maior visibilidade da informação, apoiando a comunidade médica e
cientifica a buscar tratamentos preventivos, personalizados visando o combate,
proporcionando melhor qualidade de vida a sociedade como um todo.
Nesta dissertação foi investigada o perfil de 714 pacientes relacionados a
variáveis sociais, clínicas e genéticas usando técnicas univariadas, bivariadas e o
modelo de Regressão Logística que foi fundamental para identificação dos fatores
de risco para a obesidade.
A visualização da informação como uma ferramenta de apresentação
também foi de grande importância para traçar o perfil do nosso paciente e dar apoio
para melhores analises e tomada de decisões.
Com o uso do software estatístico (SPSS) e de softwares computacionais na
área da visualização da informação (Tableau Public e Power BI), foi possível
identificar e propor um melhor modelo que melhor demostrasse as características
e o conhecimento sobre a obesidade.
Obesity has presented itself as a disease of global concern and that needs preventive measures due to significant growth in global terms. Obesity pathology enhances the development of future diseases such as hypertension, diabetes, heart disease, and cancer. For the study of obesity, it is pertinent to analyze not only genetic issues, but also clinical and socio-demographic ones. The objective of this work is to identify some risk factors for obesity and seek greater visibility of information, supporting the medical and scientific community to seek preventive treatments, personalized aiming to combat, providing better quality of life to society as a whole. In this dissertation, the profile of 714 patients related to social, clinical and genetic variables was investigated using univariate, bivariate techniques and the Logistic Regression model, which was fundamental for the identification of obesity risk factors. The visualization of information as a presentation tool was also of great importance to outline the profile of our patient and provide support for better analysis and decision making. With the use of statistical software (SPSS) and computer software in the area of information visualization (Tableau Public and Power BI), it was possible to identify and propose a better model that better demonstrated the characteristics and knowledge about obesity.
Obesity has presented itself as a disease of global concern and that needs preventive measures due to significant growth in global terms. Obesity pathology enhances the development of future diseases such as hypertension, diabetes, heart disease, and cancer. For the study of obesity, it is pertinent to analyze not only genetic issues, but also clinical and socio-demographic ones. The objective of this work is to identify some risk factors for obesity and seek greater visibility of information, supporting the medical and scientific community to seek preventive treatments, personalized aiming to combat, providing better quality of life to society as a whole. In this dissertation, the profile of 714 patients related to social, clinical and genetic variables was investigated using univariate, bivariate techniques and the Logistic Regression model, which was fundamental for the identification of obesity risk factors. The visualization of information as a presentation tool was also of great importance to outline the profile of our patient and provide support for better analysis and decision making. With the use of statistical software (SPSS) and computer software in the area of information visualization (Tableau Public and Power BI), it was possible to identify and propose a better model that better demonstrated the characteristics and knowledge about obesity.
Description
Keywords
Regressão logística Visualização de informação Obesidade Logistic regression Information visualization Obesity
Pedagogical Context
Citation
Carvalho, Janaína Maria Trinchão Silva - Identificação de alguns factores de risco para a obesidade e visualização da informação [Em linha]. [S.l.]: [s.n.]: 2022. 164 p.