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Lookup NU author(s): Dr David XieORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Background: Dysphagia, a widely suffered disease mainly by seniors, causes food swallowing-related issues such as choking, aspiration, aspiration pneumonia, and even death. Designing special diets such as thickened fluids (e.g. water, milk, soups, and juices) is an essential means of managing swallowing problems for people with dysphagia. Scope and approach: This review discusses intrinsic influencing factors (e.g. surface tension, viscosity, yield stress, and the cohesion of fluid food boluses) and external influencing factors (e.g. temperature, fluid volume, saliva secretion, and body posture) that influence the swallowing behaviors (e.g. oropharyngeal flow velocity, residual amount, and aspiration risk) of thickened fluids. Subsequently, computer models assessing the swallowing features of thickened fluids (Newtonian/non-Newtonian) are highlighted, including mesh-based methods (e.g. finite element method (FEM)) and mesh-free methods (e.g. smooth particle hydrodynamics (SPH) and moving particle semi-implicit (MPS)). Also, current challenges and prospects of computer modeling in the development of dysphagia fluid foods are proposed. Key findings and conclusions: The swallowing behaviors of thickened fluids are closely linked to intrinsic and external factors. Increasing the viscosity and cohesiveness can slow the flow of the swallowed fluid bolus and suppress fluid splashing, thus providing more response time for the nerve system and muscles to reduce choking and aspiration risks. Such information is vital for establishing mesh-based and mesh-free computer models used to inspect the swallowing process of thickened fluids. These computer models are potentially useful for developing dysphagia foods, especially thickened fluids, with tailored swallowing performance.
Author(s): Liu S, Qiao D, Cheng Z, Xie F, Zhao S, Zhang B
Publication type: Article
Publication status: Published
Journal: Trends in Food Science & Technology
Print publication date: 01/07/2023
Online publication date: 11/05/2023
Acceptance date: 10/05/2023
Date deposited: 18/05/2023
ISSN (print): 0924-2244
ISSN (electronic): 1879-3053
Publisher: Elsevier Ltd
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