Modelling Remission from Overweight Type 2 Diabetes Reveals How Altering Advice May Counter Relapse

Date
2024-03-20
Authors
Hassell Sweatman, Catherine
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract

The development or remission of diet-induced overweight type 2 diabetes involves many biological changes which occur over very different timescales. Remission, defined by, or fasting plasma glucose concentration mg/dl, may be achieved rapidly by following weight loss guidelines. However, remission is often short-term, followed by relapse. Mathematical modelling provides a way of investigating a typical situation, in which patients are advised to lose weight and then maintain fat mass, a slow variable. Remission followed by relapse, in a modelling sense, is equivalent to changing from a remission trajectory with steady state mg/dl, to a relapse trajectory with steady state mg/dl. Modelling predicts that a trajectory which maintains weight will be a relapse trajectory, if the fat mass chosen is too high, the threshold being dependent on the lipid to carbohydrate ratio of the diet. Modelling takes into account the effects of hepatic and pancreatic lipid on hepatic insulin sensitivity and -cell function, respectively. This study leads to the suggestion that type 2 diabetes remission guidelines be given in terms of model parameters, not variables; that is, the patient should adhere to a given nutrition and exercise plan, rather than achieve a certain subset of variable values. The model predicts that calorie restriction, not weight loss, initiates remission from type 2 diabetes; and that advice of the form ‘adhere to the diet and exercise plan’ rather than ‘achieve a certain weight loss’ may help counter relapse.

Description
Keywords
01 Mathematical Sciences , 06 Biological Sciences , Bioinformatics , 31 Biological sciences , 49 Mathematical sciences
Source
Mathematical Biosciences, ISSN: 0025-5564 (Print); 0025-5564 (Online), Elsevier, 371. doi: 10.1016/j.mbs.2024.109180
Rights statement
© 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by/nc-nd/4.0/).