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Association between the prevalence of Depressive and anxious disorders and metabolic Syndrome: a cross-sectional analysis on ELSA- Brasil (The Brazilian Longitudinal Study of Adult Health)

Grant number: 20/06887-0
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): September 01, 2020
Effective date (End): August 31, 2021
Field of knowledge:Health Sciences - Medicine - Medical Clinics
Principal Investigator:Andre Russowsky Brunoni
Grantee:Laura Fernandes Berto
Host Institution: Faculdade de Medicina (FM). Universidade de São Paulo (USP). São Paulo , SP, Brazil


Depression and anxiety are among the most prevalent common mental disorders in the world, being major contributors to the global burden of disease. Several studies have indicated the association between mental disorders and clinical diseases, lifestyle, and pro-inflammatory conditions, revealing a complex and multifactorial association. To study this association, we propose to investigate the relationship between mental disorders and Metabolic Syndrome (MetS), a condition that affects almost a quarter of the world's population. Patients with mental disorders and MetS present similar risk factors, such as sedentary lifestyle, smoking, overweight/obesity, and stress. In this context, we propose to conduct a cross-sectional study to investigate the association between the prevalence of depression and anxiety disorders and MetS in an LMIC (Low-to-Middle-Income Country) population, as it was studied almost exclusively in high-income countries. The study will be based on the first wave (2008-2010) of the Longitudinal Study of Adult Health (ELSA-Brasil), a multicenter cohort applied in 15,105 public Brazilian employees. Mental disorders in ELSA-Brasil were classified according to CIS-R and ICD-10. On the other hand, MetS were determined according to its definition by NCEP-ATP III. For statistical analysis, different models (multiple logistic regressions) will be created, with mental disorders (depressive episodes, anxiety disorders, or common mental disorder) as dependent variables, and the Mets as the independent variable. The models will be adjusted by a series of confounding variables, such as sociodemographic and lifestyle aspects. As a benefit, our study may assist in the management of mental disorders in clinical settings, particularly in populations of LMICs. (AU)

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