Assessment of the influence of chewing pattern on glucose homeostasis through linear regression model.

Chewing profile EMG device Glycemia Glycemic curve Linear regression models Mastication

Journal

Nutrition (Burbank, Los Angeles County, Calif.)
ISSN: 1873-1244
Titre abrégé: Nutrition
Pays: United States
ID NLM: 8802712

Informations de publication

Date de publication:
03 May 2024
Historique:
received: 07 09 2023
revised: 22 03 2024
accepted: 30 04 2024
medline: 2 6 2024
pubmed: 2 6 2024
entrez: 1 6 2024
Statut: aheadofprint

Résumé

Maintaining plasma glucose homeostasis is vital for mammalian survival, but the masticatory function, which influences glucose regulation, has, to our knowledge, been overlooked. In this study, we investigated the relationship between the glycemic response curve and chewing performance in a group of 8 individuals who consumed 80 g of apple. A device called "Chewing" utilizing electromyographic (EMG) technology quantitatively assesses chewing pattern, while glycemic response is analyzed using continuous glucose monitoring. We assessed chewing pattern characterizing chewing time (t t These results emphasize the influence of proper chewing techniques on blood sugar levels. Implementing correct chewing habits could serve as an additional approach to managing the glycemic curve, particularly for individuals with diabetes.

Identifiants

pubmed: 38823253
pii: S0899-9007(24)00131-X
doi: 10.1016/j.nut.2024.112481
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

112481

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Giuseppe Maulucci reports financial support was provided by Regione Lazio PO FSE 2014-2020. “Chewing Performance” was taken from the article by Alessia Riente et al. title “Evaluation of the masticatory pattern through an electromyographic device” by the same co-authors.

Auteurs

Alessia Riente (A)

Metabolic Intelligence Lab, Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy; Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

Alessio Abeltino (A)

Metabolic Intelligence Lab, Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy; Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

Giada Bianchetti (G)

Metabolic Intelligence Lab, Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy; Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

Cassandra Serantoni (C)

Metabolic Intelligence Lab, Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy; Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

Marco De Spirito (M)

Metabolic Intelligence Lab, Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy; Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

Dario Pitocco (D)

Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

Stefano Capezzone (S)

Gruppo Fastal Blu Sistemi, Rome, Italy.

Rosita Esposito (R)

Digital Innovation Hub Roma, Chirale S.r.l., Rome, Italy.

Giuseppe Maulucci (G)

Metabolic Intelligence Lab, Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy; Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy. Electronic address: giuseppe.maulucci@unicatt.it.

Classifications MeSH