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Towards designing dysphagia foods: Recent advances in influencing factors and computer modeling for the swallowing of thickened fluids

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.

Publication metadata

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

Year: 2023

Volume: 137

Pages: 17-30

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


DOI: 10.1016/j.tifs.2023.05.008


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