ood consumption according to the degree of industrial food processing in Brazilian graduates (CUME Project): A hierarchical analysis of associated factors

• Autor(a) principal: Moreira, Michelle Andrade
• Data de Publicação: 2024
• Outros Autores: Moreira, Ana Paula Boroni, Hermsdorff, Helen Hermana Miranda, Pimenta, Adriano Marçal, Bressan, Josefina, Cândido, Ana Paula Carlos
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista de Nutrição
• Texto Completo: https://periodicos.puc-campinas.edu.br/nutricao/article/view/12757
• topic: Eating; Nutrition policy; Regression analysis; Social determinants of health; Ingestão de alimentos; Política nutricional; Análise de regressão; Determinantes sociais da saúde

Objective Evaluate the food consumption of the participants of the Cohort of Universities of Minas Gerais, according to the degree of processing, and its relationship with socioeconomic, behavioral, and individual factors. Methods A total of 4,124 individuals from the baseline of the Cohort of Universities of Minas Gerais (2016 and 2018) participated in this study. Food consumption was self-reported by completing an online Food Frequency Questionnaire. The foods were divided into 3 groups: Group 1, in natura, minimally processed foods, culinary ingredients and culinary preparations; Group 2, processed foods; Group 3, ultra-processed foods. A hierarchical multiple linear regression model was used to verify the associated factors. Results Regarding the factors associated with food consumption, it is noteworthy that Group 1 was positively associated with the practice of physical activity, female gender, age, “non-white” skin color, and the presence of diabetes Mellitus; and negatively with “not married/without stable union” marital status, alcohol abuse, tobacco use, obesity, and depression. Considering Group 2, it was positively associated with alcohol abuse, tobacco use, and age; and negatively with physical activity, female gender, and “non-white” skin color. As for Group 3 it was positively associated with a marital status of “not married/without stable union”, obesity, and depression; and negatively with physical activity, age, “non-white” skin color, and presence of diabetes Mellitus. Conclusion The factors that are in at least one of the final hierarchical linear regression models stand out: marital status, physical activity, alcohol abuse, tobacco use, sex, age, skin color, obesity, diabetes mellitus, and depression.