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Oral processing in elderly: understanding eating capability to drive future food texture modifications

Published online by Cambridge University Press:  19 December 2018

Anwesha Sarkar*
Affiliation:
Food Colloids and Bioprocessing Group, School of Food Science and Nutrition, University of Leeds, Leeds LS2 9JT, UK
*
Corresponding author: Dr Anwesha Sarkar, email A.Sarkar@leeds.ac.uk
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Abstract

Ageing population suffer from increased risk of malnutrition which is a major determinant of accelerated loss of autonomy, adverse health outcomes and substantial health-care costs. Malnutrition is largely attributed to reduced nutrient intake which may be associated with several endogenous factors, such as decline of muscle mass, oral functions and coordination that can make the eating process difficult. From an exogenous viewpoint, nutritionally dense foods with limited innovations in food texture have been traditionally offered to elderly population that negatively affected pleasure of eating and ultimately, nutrient intake. Recent research has recognised that older adults within the same age group are not homogenous in terms of their preferences, nutritional needs, capabilities and impediments in skill-sets. Hence, a new term eating capability (EC) has been coined to describe various quantifiable endogenous factors in the well-coordinated eating process that may permit characterisation of the capabilities of elderly individuals in food handling and oral processing. This review covers current knowledge on EC focusing on parameters, such as hand and oro-facial muscle forces. Although limited in literature, EC score measured using a comprehensive toolkit has shown promise to predict eating difficulty perception and oral processing behaviour. Further systematic studies are required to explore relationships between individual/multiple constituents of EC and oral comfort. Such knowledge base is needed to underpin the creation of next generation personalised texture-modified foods for elderly population using sophisticated technologies, such as 3D printing to enhance eating pleasure, increase nutrient intake that will ultimately contribute to tackling malnutrition.

Information

Type
Conference on ‘Getting energy balance right’
Copyright
Copyright © The Author 2018 
Figure 0

Fig. 1. (Colour online) Schematic overview of eating capability measurements that provide design inputs to food texture modifications, and may act as enabler to drive output of optimised nutrient intake. Eating capability can be negatively affected by input conditions of chronic diseases and polypharmacy.

Figure 1

Fig. 2. (Colour online) Devices used for measuring eating capability including JAMAR dynamometer for hand gripping force (a), Flexisensor with neoprene disc for finger gripping force (b), Semmes–Weinstein monofilament for touch sensitivity (c), Flexisensor with silicone disc for bite force (d), and Iowa Oral Performance Instrument for tongue and lip sealing pressure measurements (e); Copyright© 2015 Elsevier, Reproduced with permission(8).

Figure 2

Fig. 3. Age dependency of eating capability parameters, showing right-hand gripping force (a), finger force (b), finger tactile sensitivity (c), bite force (d), tongue pressure (e) and lip sealing pressure (f) as a function of age in older adults from the UK (n 103; black bars) and Spain (n 100; white bars); Copyright© 2015 Elsevier, Data used with permission(8).

Figure 3

Fig. 4. (Colour online) Relation of right-hand gripping force with oro-facial muscle forces (maximum bite force (▲), maximum tongue pressure (●) and lip sealing pressure (■) of older adults in the UK (closed symbols)); (a) and Spain (open symbols) (b), respectively. Each data point represents the mean data of forces from participants in each of the age classes (years old), i.e. 65–70, 70–75, 75–80, 80–85, 85–90 and 90+. Black lines show linear-regression best fits to the observed values except for lip sealing pressure relationship in Spain, latter shows a polynomial-fit. Copyright© 2015 Elsevier, Data used with permission(8) for (a) and Copyright© 2015 Cambridge University Press, reproduced with permission(46) for (b).

Figure 4

Fig. 5. Relation among samples, number of chew and maximum force at break during oral processing by older adults (n 30) for model foods (hydrogels) with controlled mechanical properties with visual corresponding images (a) and food products (b). Nomenclatures 1κ and 2κ represent hydrogels containing 1 wt % and 2 wt % κ-carrageenan, respectively, M-κSAl represents mixed hydrogel containing 2 wt % κ-carrageenan + sodium alginate, B-κCAl represents hydrogel with structural inhomogeneity containing 1 wt % κ-Carrageenan + big calcium alginate beads (mean size 1210 µm) and S-κCAl represents hydrogels with structural inhomogeneity containing 1 wt % κ-carrageenan + small calcium alginate beads of mean size 1210 µm. Copyright© 2016 Elsevier. Used with permission(16,47).