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Effect of probiotic supplementation associated with dietary intervention on body composition, intestinal microbiota and inflammatory biomarkers in obese young adults

Grant number: 19/22524-8
Support type:Scholarships in Brazil - Doctorate (Direct)
Effective date (Start): August 01, 2020
Effective date (End): September 30, 2024
Field of knowledge:Health Sciences - Nutrition - Nutrition Biochemistry
Principal Investigator:Ronaldo Vagner Thomatieli dos Santos
Grantee:Camila Guazzelli Marques
Home Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil

Abstract

The worldwide prevalence of Obesity has increased substantially in recent years. Its pathophysiology is complex and multifactorial, and the cause most attributed to its genesis is the imbalance between caloric intake and permanent and prolonged energy expenditure. However, recent evidence adds that intestinal microbiota (MI) is a potentiating factor for the development of Obesity as MI modulates host metabolism affecting not only energy balance but also intestinal barrier function and inflammation. low grade chronic systemic disease. Therefore, proposing strategies capable of promoting its modulation and, consequently, reduction of low-grade chronic systemic inflammation may be relevant in the prevention and/or treatment of Obesity. The aim of the present study will be to evaluate the effect of probiotic supplementation and caloric restriction on intestinal microbiota, systemic inflammation and body composition of obese individuals. It will be a randomized, double-blind, placebo-controlled, two-parallel study in young adults with grade I Obesity. The intervention period will be 12 weeks of probiotic supplementation or placebo associated with calorie restriction. All assessments, including feces, blood, body composition, food intake and physical activity level will be performed at baseline and final time. While in the fourth and eighth week will be performed only the evaluations of body composition, food intake and level of physical activity. Statistical analysis will be performed according to data behavior, using parametric and nonparametric tests when appropriate. Thus, we will use time and group analyzes, correlations, as well as regression models to understand the results, considering pd0.05 and effect size. (AU)