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Influence of diet and physical activity on the risk of cardiometabolic diseases resulting from depressive disorders

Grant number: 24/17640-7
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Start date: April 01, 2025
End date: March 31, 2028
Field of knowledge:Health Sciences - Collective Health - Epidemiology
Principal Investigator:Carlos Augusto Monteiro
Grantee:André de Oliveira Werneck
Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:22/05636-0 - Program of population studies on the consumption of ultraprocessed foods and health, AP.TEM

Abstract

People with mental disorders present a reduced life expectancy, especially due to a higher incidence of cardiometabolic diseases. Dietary patterns and physical activity are associated with both the risk for depressive disorders as well as cardiometabolic diseases, however, little is known about their effect on the incidence of cardiometabolic diseases resulting from depressive disorders. Therefore, this project aims to investigate the influence of dietary patterns and physical activity on the risk of cardiometabolic diseases resulting from depressive disorders. Data from the NutriNet Brasil cohort will be used. The NutriNet Brasil cohort is the largest cohort targeted in investigating the association between dietary patterns and non-communicable chronic diseases in Brazil. The cohort has about 110,000 adults enrolled so far, with around 40,000 participants having completed the initial questionnaires. Diet will be assessed by the contribution of ultraprocessed foods and will be evaluated through the Nova24h, a 24h food recall created specifically for the identification of food consumption according to the degree of processing. Physical activity will be assessed using the Global Physical Activity Questionnaire. The incidence of depressive disorders will be evaluated using a validated questionnaire (Patient Health Questionnaire-9). The incidence of cardiometabolic diseases (obesity - assessed by weight gain - type 2 diabetes, hypertension, and cardiovascular diseases - acute myocardial infarction, stroke, angina, coronary artery obstruction, and heart failure) will be assessed by self-report. Confounding factors will be defined through Directed Acyclic Graphs specific to each analysis. For the main analyses, multi-stage models will be created, using proportional hazards Markov models.

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