Cargando…

A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome

Background: Metabolic syndrome (MS) is closely linked to obesity; however, not all individuals with obesity will develop obesity-related complications and a metabolically healthy obesity (MHO) group is also described. Objective: To perform a multivariate analysis (MVA) of the anthropometric and bioc...

Descripción completa

Detalles Bibliográficos
Autores principales: Calcaterra, Valeria, Biganzoli, Giacomo, Ferraro, Simona, Verduci, Elvira, Rossi, Virginia, Vizzuso, Sara, Bosetti, Alessandra, Borsani, Barbara, Biganzoli, Elia, Zuccotti, Gianvincenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999358/
https://www.ncbi.nlm.nih.gov/pubmed/35407464
http://dx.doi.org/10.3390/jcm11071856
_version_ 1784685167200174080
author Calcaterra, Valeria
Biganzoli, Giacomo
Ferraro, Simona
Verduci, Elvira
Rossi, Virginia
Vizzuso, Sara
Bosetti, Alessandra
Borsani, Barbara
Biganzoli, Elia
Zuccotti, Gianvincenzo
author_facet Calcaterra, Valeria
Biganzoli, Giacomo
Ferraro, Simona
Verduci, Elvira
Rossi, Virginia
Vizzuso, Sara
Bosetti, Alessandra
Borsani, Barbara
Biganzoli, Elia
Zuccotti, Gianvincenzo
author_sort Calcaterra, Valeria
collection PubMed
description Background: Metabolic syndrome (MS) is closely linked to obesity; however, not all individuals with obesity will develop obesity-related complications and a metabolically healthy obesity (MHO) group is also described. Objective: To perform a multivariate analysis (MVA) of the anthropometric and biochemical data in pediatric patients with obesity to reveal a “phenotype” predictive for MS. Methods: We analyzed 528 children with obesity (OB) and 119 normal-weight pediatric patients (NW). Adiposity indices were recorded, and MS was detected. MVA was performed. Results: Analysis of the structure of correlation of the variables showed that the variables of waist circumference (WC), body mass index (BMI), and estimated fat mass (eFM) were positively correlated with each other as a whole. In addition, the variables of the triglycerides (TG), triglyceride–glucose (TyG) index, and visceral adiposity index were positively correlated with each other as a whole, although none were correlated with the variables of BMI z-score, waist-to-height ratio, WC, eFM, or weight. The variables that related to insulin resistance (IR) and dyslipidemia were crucial for the early stratification of patients at risk of MS. Conclusions: Independently of body weight, IR, dyslipidemia, hypertriglyceridemia, and fat distribution seem to be the strongest MS risk factors. The early detection of and intervention in these modifiable risk factors are useful to protect children’s health.
format Online
Article
Text
id pubmed-8999358
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-89993582022-04-12 A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome Calcaterra, Valeria Biganzoli, Giacomo Ferraro, Simona Verduci, Elvira Rossi, Virginia Vizzuso, Sara Bosetti, Alessandra Borsani, Barbara Biganzoli, Elia Zuccotti, Gianvincenzo J Clin Med Article Background: Metabolic syndrome (MS) is closely linked to obesity; however, not all individuals with obesity will develop obesity-related complications and a metabolically healthy obesity (MHO) group is also described. Objective: To perform a multivariate analysis (MVA) of the anthropometric and biochemical data in pediatric patients with obesity to reveal a “phenotype” predictive for MS. Methods: We analyzed 528 children with obesity (OB) and 119 normal-weight pediatric patients (NW). Adiposity indices were recorded, and MS was detected. MVA was performed. Results: Analysis of the structure of correlation of the variables showed that the variables of waist circumference (WC), body mass index (BMI), and estimated fat mass (eFM) were positively correlated with each other as a whole. In addition, the variables of the triglycerides (TG), triglyceride–glucose (TyG) index, and visceral adiposity index were positively correlated with each other as a whole, although none were correlated with the variables of BMI z-score, waist-to-height ratio, WC, eFM, or weight. The variables that related to insulin resistance (IR) and dyslipidemia were crucial for the early stratification of patients at risk of MS. Conclusions: Independently of body weight, IR, dyslipidemia, hypertriglyceridemia, and fat distribution seem to be the strongest MS risk factors. The early detection of and intervention in these modifiable risk factors are useful to protect children’s health. MDPI 2022-03-27 /pmc/articles/PMC8999358/ /pubmed/35407464 http://dx.doi.org/10.3390/jcm11071856 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Calcaterra, Valeria
Biganzoli, Giacomo
Ferraro, Simona
Verduci, Elvira
Rossi, Virginia
Vizzuso, Sara
Bosetti, Alessandra
Borsani, Barbara
Biganzoli, Elia
Zuccotti, Gianvincenzo
A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome
title A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome
title_full A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome
title_fullStr A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome
title_full_unstemmed A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome
title_short A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome
title_sort multivariate analysis of “metabolic phenotype” patterns in children and adolescents with obesity for the early stratification of patients at risk of metabolic syndrome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999358/
https://www.ncbi.nlm.nih.gov/pubmed/35407464
http://dx.doi.org/10.3390/jcm11071856
work_keys_str_mv AT calcaterravaleria amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT biganzoligiacomo amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT ferrarosimona amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT verducielvira amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT rossivirginia amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT vizzusosara amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT bosettialessandra amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT borsanibarbara amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT biganzolielia amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT zuccottigianvincenzo amultivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT calcaterravaleria multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT biganzoligiacomo multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT ferrarosimona multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT verducielvira multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT rossivirginia multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT vizzusosara multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT bosettialessandra multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT borsanibarbara multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT biganzolielia multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome
AT zuccottigianvincenzo multivariateanalysisofmetabolicphenotypepatternsinchildrenandadolescentswithobesityfortheearlystratificationofpatientsatriskofmetabolicsyndrome