Associations of Ultra-Processed Food Intake with the Incidence of Cardiometabolic and Mental Health Outcomes Go Beyond Specific Subgroups-The Brazilian Longitudinal Study of Adult Health.

: Avoidance of ultra-processed foods (UPFs) has been recommended to achieve a healthy diet, but whether it applies equally to all UPFs is uncertain. We evaluated individual UPF subgroups in the prediction of cardiometabolic and mental health outcomes. : The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) is an occupational cohort study of 15,105 adults (35-74 years) recruited in 2008-2010.

Ultra-processed food consumption is positively associated with the incidence of depression in Brazilian adults (CUME project).

Objective: To evaluate the association between the consumption of ultra-processed food and the incidence of depression in Brazilian adults.

Methods: This longitudinal study included 2572 participants (M = 936 and F = 1636, mean age of 36.1 years) from the Cohort of Universities of Minas Gerais - CUME Project, Brazil.

Interaction effect between breakfast skipping and sedentary behavior in the dietary inflammatory potential of Brazilian school-age children.

Objectives: Missed nutrients from skipped meals affect diet quality. However, the extent to which breakfast skipping affects the inflammatory potential of a diet, as indicated by Children's Dietary Inflammatory Index (C-DII) score, remains unknown. We aimed to evaluate the association between breakfast skipping and C-DII score, and investigate the presence of interaction with sociodemographic factors and sedentary behavior.

Identifying patterns of diurnal blood pressure variation among ELSA-Brasil participants.

Ambulatory blood pressure monitoring (ABPM) is the gold standard method for the diagnosis of hypertension. ABPM provides a set of repeated measurements for blood pressure (BP), usually over 24 h. Traditional approaches characterize diurnal BP variation by single ABPM parameters such as average and standard deviation, regardless of the temporal nature of the data.