3.1.2.1 Assessment of the Cutting Ability

The cutting ability of mastication can be evaluated by the size of food particles being chewed. One of the widely used methods for assessing particle size is the sieve method (Van Der Bilt et al. 1993). Subjects are asked to chew a fixed amount (e.g. 3 g) of natural food (e.g. peanuts) or materials (e.g. gummy jelly [Nokubi et al. 2010]) for a fixed number of cycles (e.g. 15 strokes) (Figure 3.1). The chewed particles are expectorated and collected for the sieving procedure to evaluate the distribution of the size of particles. Sieving is performed using a single sieve or a stack of multiple sieves with different pore sizes (Figure 3.1a). When a single sieve is used (e.g. the US Standard No. 5 sieve with a pore size of 4000 μm) (Cusson et al. 2015), masticatory performance (i.e. the cutting ability) is indexed by the percentage of the weight of the chewing food that passes through the sieve. A higher percentage of food particles through the sieve means better cutting performance (Figure 3.1a). For the measurement with multiple sieves, masticatory performance can be indexed by the median particle size, which denotes the size (in the diameter of sieve pore) of a theoretical sieve through which 50% (in weight) of the particles can pass (Woda et al. 2010) (Figure 3.1a). For example, a stack of sieves may consist of a sieve with a larger pore size (4000 μm) and a sieve with a smaller pore size (2000 μm). If 60% of the particles pass through the 4000 μm sieve and 30% of them pass through the 2000 μm sieve, the median particle size would be somewhere between 2000 and 4000 μm. If a single sieve is used instead of multiple sieves, the diameter of the single sieve should be close to the median particle size of chewed food. Otherwise, the single sieve method would be less reliable compared to the multiple sieve method (Van Der Bilt and Fontijn‐Tekamp 2004).

3.1.2.2 Assessment of the Mixing Ability: The Two‐colour Chewing‐gum Test

The concept of assessing the mixing ability is straightforward: if different portions of food are well mixed, then mixed particles will form a more homogenous group compared to the original portions. The two‐colour chewing‐gum test (TCGT) aims to quantify the degree of homogeneity of mixing by assessing the colour of different food portions. According to Schimmel et al. (2007), this can be performed by assessing the colour of a bolus mixed from two pieces of chewing gums of different colours (Figure 3.2). The method offers a convenient and time‐saving way for assessing masticatory performance because chewing gum can easily be obtained, and at the chairside, the degree of mixing (i.e. the homogeneity of colour features) can be judged by visual inspection with good reliability (Silva et al. 2018). More precisely, the chewed bolus can be digitalized by photographing or scanning, and the image of the bolus can be proceeded by imaging analysis. There have been various methods developed for quantifying the degree of mixing according to different aspects of the colour features, such as the standard deviation of colours, the change in colour hue and the pattern that colour portions are clustered (Lo et al. 2020; Halazonetis et al. 2013; Schimmel et al. 2007). One of the widely used methods is to analyze the variance of the hue of the image (Halazonetis et al. 2013). The smaller standard deviation of hue (SDHue) represents an increased homogeneity of colour mixing, i.e. a better mixing ability. For example, the average value of SDHue decreased from 0.144 to 0.023 when the chewing cycles increased (i.e. a better masticatory effect) from 20 to 50 cycles (Halazonetis et al. 2013).

3.1.2.3 Assessment of the Mixing Ability: The Colour‐changeable Chewing‐gum Test

The TCGT directly quantifies the change in colour features induced by chewing, while the colour‐changeable chewing‐gum test (CCGT) quantifies the degree of mixing indirectly via the chemical reaction of the colour‐changeable gum (Hama et al. 2014; Hayakawa et al. 1998). The colour‐changeable gum consists of two critical components: a pH‐sensitivity dye that develops red colour in alkaline conditions and citric acid that lowers the pH condition (i.e. less alkaline). Before chewing, the pH value of the gum is lowered by citric acid, and therefore the dye will not develop into a reddish colour. During chewing, the citric acid will be released and washed out. It increases the pH condition (i.e. more alkaline) and leads to the development of red colour (Tarkowska et al. 2017). The mixing performance is then quantified by the degree of colour change before vs. after chewing.

3.1.3.1 The Number of Chewing Cycles

The number of chewing cycles can be assessed from two aspects. Firstly, the number of chewing cycles within a fixed period is defined as the chewing rate. The central pattern generator of the brainstem plays a pivotal role in rhythmic jaw movement (Moore et al. 2014). Therefore, the central nervous system (CNS) mechanisms are critical for maintaining a constant rate of chewing. Additionally, the chewing rate of chewing a piece of gum is also associated with the number of functional teeth. In a study with 268 healthy older people (aged between 65 and 88 years), the mean chewing rate was 203.7 (cycle/3 minutes) and 170.3, respectively, for older people with Eichner class A~B3 and Eichner class B4~C (Kikutani et al. 2009). A higher chewing rate was also associated with a better mixing ability (Kikutani et al. 2009). Secondly, the number of chewing just before swallowing is a critical index for assessing behavioural adaptation in feeding (Peyron et al. 2004a). With a similar chewing rate, older people would chew longer than younger people so that the total number of chewing cycles (before swallowing) is greater in older people. To increase the number of chewing cycles would be an adaptative behaviour for improving the feeding experience (Peyron et al. 2004a).

3.1.3.2 Maximal Biting Force

The biting force has been conceived as a major factor related to masticatory performance. The MBF can be evaluated either by clenching with the whole dental arch (i.e. ‘full arch’) (Ikebe et al. 2012) or clenching on a single pair of molars (i.e. ‘single pair’) (Ogura et al. 2012; Palinkas et al. 2010). Pressure films and dynamometers are commonly used for the full‐arch and single‐pair assessment, respectively. Notably, the MBF is closely associated with personal factors, including age and gender. For example, the right‐molar single‐pair MBF reduced from 339 to 324 N in male subjects and from 221 to 203 N in female subjects, in the younger (21–40 y/o) vs. the older (41–60 y/o) subjects (Palinkas et al. 2010). In general, a lower occlusal force is associated with a lower cutting ability (Ikebe et al. 2012). However, it should be noted that both factors are closely related to the number of functional teeth. In a study with large‐sampled elderly people (aged ≱ 60 years), the mean full‐arch MBF reduced from 530 N (for Eichner class A) to 220 N (for Eichner class C), and the cutting ability reduced from 2659 mm² (Eichner class A) to 1316 mm² (Eichner class C) (Ikebe et al. 2012). Additionally, using magnetic resonance imaging (MRI), researchers have identified a great individual difference in the size of the masseter, the major jaw‐closing muscles associated with mastication. The masseter muscle volume (MMV) showed a weak‐to‐moderate and statistically significant correlation with the mixing ability (Lin et al. 2017a). Biting force is also associated with the processing of sensory feedback (Trulsson et al. 2012). Differences in the MBF can be found between the individuals with natural teeth and those who with dental implants (Trulsson et al. 2012). Because periodontal mechanoreceptors are removed during extraction, normal sensory feedback (via the periodontium) is compromised in an implant‐supported prosthesis. Therefore, in the patients, changes in the MBF may be associated with altered sensory processing. It is also noteworthy that during eating, the biting force may interact with the types of food. For example, the reduction of the maximal contraction of the masticatory muscles was noted in older people, compared to younger people, only when they chewed a harder food (Galo et al. 2007).

3.1.3.3 Oral Stereognosis

Oral stereognosis refers to the ability to recognize and discriminate an intraoral object (Jacobs et al. 1998). Clinically, assessments of oral stereognosis can be conducted by asking subjects to evaluate the size or shape of a standardized object intraorally. For example, in one study, subjects needed to evaluate the size of steel spheres with the diameter varying between 4 and 9 mm (Engelen et al. 2004). In the other studies, they were asked to discriminate the size (12 × 12 × 3 mm³ vs. 8 × 8 × 2 mm³) and the shape (circles, ellipses, semicircles, squares, rectangles and triangles) of testing objects (Hirano et al. 2004; Kawagishi et al. 2009; Ikebe et al. 2007b). The performance can be quantified according to the accuracy of evaluation and the response duration (Hirano et al. 2004). Older dentate subjects showed a worse performance in the assessment of oral stereognosis compared to younger subjects (Ikebe et al. 2007a). In older edentulous patients wearing a complete denture, a better performance of the oral stereognosis assessment was associated with better masticatory performance (Ikebe et al. 2007b). In healthy adults, the ability to perceive the size of intraoral objects was associated with the cutting ability (Engelen et al. 2004). The role of perceptual processing in oral stereognosis is also evidenced by an earlier functional magnetic resonance imaging (fMRI) study, which revealed that oral stereognosis was associated with functional brain features (Fujii et al. 2011). The findings suggest that the individual difference in oral stereognosis may be associated with not only peripheral but also central factors.

3.1.4.1 Water Swallowing Test

The water swallowing test (WST) is one of the most widely used chairside methods for assessing the ability to swallow. It is a simple task that requires the subject to swallow 3 ml of water, and the assessor identifies whether any choke occurs during swallowing (Brodsky et al. 2016). The test is mainly used for screening potential patients with functional dysphagia. A recent meta‐analysis based on 22 studies revealed that the WST offers sufficient screening for aspiration (Brodsky et al. 2016). Notably, the sensitivity and specificity for screening aspiration may be associated with the methodological variations of the WST, including the volume to sip and the way of sipping (i.e. consecutive vs. single sips) (Brodsky et al. 2016). Another recent meta‐analysis on patients with stroke also reported that WST is a useful screening tool for evaluating the aspiration of stroke patients (Chen et al. 2016).

3.1.4.2 Repetitive Saliva Swallowing Test

The repetitive saliva swallowing test (RSST) is a simple chairside test developed and popularized in Japan (Oguchi et al. 2000a,b). The test requires a subject to perform voluntary swallows repeatedly in 30 seconds. The score of the RSST is indexed by the number of swallows that the subject can complete during 30 seconds, which can be identified using the palpation of laryngeal elevation (Oguchi et al. 2000a,b). The subjects are instructed to swallow as many times as possible (Lin et al. 2019; Persson et al. 2019). During the procedure, the subject cannot drink or eat anything but swallows his/her own saliva. The RSST score revealed a significant age‐related difference, reducing from 7.4 ± 1.7 (mean ± standard deviation) in younger adults to 5.9 ± 2.3 in older adults (mean age 68.1 years) (Oguchi et al. 2000b). For its clinical validity, safety and simplicity, the RSST is suggested for evaluating functional dysphagia (Oguchi et al. 2000a). However, it should be noted that the RSST score also reflects the ability of voluntary swallowing, which is regulated by the CNS (Ertekin 2011). Therefore, the test score may reflect not only the function of the oropharyngeal system but also the CNS mechanisms of swallowing. As shown in a recent study, the RSST score was associated with individual variability in structural brain features (Lin et al. 2019). The individual difference in the RSST score may be associated with both peripheral and central factors.

3.1.5.1 Masticatory Experience

The design of self‐report assessment for masticatory experience can be simple and straightforward, such as a single yes/no question that assesses if subjects are satisfied with their chewing activity or not (Miura et al. 1998). The assessment may be a more complicated questionnaire that assesses different aspects of the eating experience. The experience to be assessed may include one’s sensory, motor and emotional experience regarding mastication and behavioural changes associated with the difficulty of mastication. For example, Tsuga et al. (1998) used a customized questionnaire to assess the masticatory ability of 160 elderly participants (aged ≱ 80 years). The questionnaire assessed both sensory experiences, such as pain during chewing and dryness of mouth, and behavioural changes related to mastication, such as taking a long time to finish a meal and avoid eating with others (Tsuga et al. 1998). The result showed that a higher score of masticatory experience (i.e. more problems during chewing) was significantly correlated with a lower number of teeth and a lower MBF (Tsuga et al. 1998). Notably, individual eating experience may vary greatly due to individual differences in diet habits. There exists a great regional/cultural difference in diet habits. Therefore, research findings cross‐referred between different countries or regions should be carefully interpreted. To better evaluate the association between masticatory experience and diet, the types of food to eat are specified in some assessments, and eating experience is assessed for each type of food. For example, the food questionnaire by Koshino et al. (2008) requires subjects to rate the eating experience of 25 food items based on Japanese cuisine. Subjects’ difficulty of chewing the selected group of food is indexed as a masticatory score, which showed a significant correlation with their cutting ability, as assessed using the sieve method. In a similar vein, Hsu et al. (2012) designed a questionnaire consisting of 23 food items based on Taiwanese cuisine. Their findings suggested that lesser masticatory difficulty of the food was associated with better preservation of teeth, i.e. more than 20 existing natural teeth and at least eight functional teeth units (Hsu et al. 2012). Since diet habit is closely related to regional and cultural factors, the studies of masticatory experience should adopt a culturally valid tool to better reflect the real eating experience of subjects.

It is noteworthy that at present most of the questionnaires have focused on the experience of the difficulty of chewing. In other words, the questionnaires are mainly used for evaluating the disturbances (e.g. pain) associated with chewing. A limitation of these assessments of ‘masticatory difficulty’ is to neglect the fact that individuals will develop some adaptive strategies to cope with these challenges during chewing (Bourdiol et al. 2020; Woda et al. 2010). For example, older people with tooth loss or a newly installed denture may adapt to their oral condition via some behavioural strategies, such as chewing with more cycles or chewing with a different side. Until now, the experience of adaptation of oral conditions has been rarely investigated (Al‐Sahan et al. 2020). A recent study reported that older people (aged ≱ 65 years) with tooth loss would adopt different strategies to cope with their conditions (Zelig et al. 2019). Some adaptive chewing strategies were used for a better eating experience, such as ‘I’ve got to make sure that I have chewed it real good’ or ‘sometimes I eat here on the gum’ (Zelig et al. 2019). These findings suggested that older people require more attention and cognitive control when eating in a challenging condition. On the contrary, when adaptation failed, maladaptive behaviour such as avoidance of some types of food may occur (Zelig et al. 2019).

3.1.5.2 Swallowing Experience

Several questionnaires have been developed for screening older people with a risk of dysphagia. The Eating Assessment Tool (EAT‐10) is a self‐rating questionnaire consisting of 10 items, which assesses individual experience during swallowing (Belafsky et al. 2008). As a tool for evaluating the risk of dysphagia, the questionnaire focuses on the individual experience of swallowing difficulty, including the occurrence of pain and cough during swallowing. Moreover, it differentiates the swallowing of different types of food, such as liquids, solids and pills, because different physical properties of the food may influence one’s swallowing experience. The EAT‐10 showed good internal consistency and test–re‐test reliability and a good clinical validity in discriminating patients with and without dysphagia (Belafsky et al. 2008). An EAT‐10 score of 3 or higher can be abnormal in swallowing function based on the normative data from 482 patients (Belafsky et al. 2008). Another assessment designed for assessing swallowing difficulty is the swallowing disturbance questionnaire (SDQ), which consists of 15 yes/no questions about swallowing disturbances. The total SDQ score was associated with the score from fibreoptic endoscopic evaluation of swallowing (FEES) (Manor et al. 2007). The Swallowing Quality of Life questionnaire (SWAL‐QOL) is a longer questionnaire consisting of 44 items (McHorney et al. 2002). The questionnaire assesses the experience of swallowing difficulty from multiple dimensions, including its effect on social interaction, sleep and fatigue, thus focusing on the various aspects of quality of life. The validity of the SWAL‐QOL is supported by clinical evidence, which shows that the older patients with Parkinson’s disease (who may be co‐morbid with dysphagia) showed a worse condition in almost all the SWAL‐QOL items (except for sleep) than the healthy older subjects (Leow et al. 2010). The findings revealed that the questionnaires for assessing swallowing experience can be an important tool for screening the risk of dysphagia. The self‐rating scores may contribute to the medical decision whether instrumental assessment (e.g. FEES) is required for further diagnosis.

3.1.5.3 Consistency Between Functional and Questionnaire Assessments

The functional and questionnaire assessments are designed for different purposes for evaluating oral functions. The former focuses on quantifying the individual performance of oral functions, while the latter focuses on investigating one’s eating experience. Based on 708 older people (mean age 66 years), Ikebe et al. (2007c) found that the cutting ability was not significantly associated with the self‐reported dissatisfaction of masticatory function when the variables posterior occlusal contacts and food acceptance were controlled. In another research with a large sample of elderly adults (n = 1789), Cusson et al. (2015) reported no significant correlation between the perceived masticatory ability (assessed using a questionnaire) and the cutting ability assessed using the sieve method. The inconsistency of the results between objective and subjective assessments can be partly explained by the methodological difference between the two approaches. For the assessment of masticatory performance, subjects need to chew a standardized food during a limited period (or a fixed number of strokes). Such a standardized testing condition, though providing a fair basis for the comparison of performance between individuals, may not reflect the real eating experience as assessed using the questionnaire methods.

3.1.6.1 Evaluation of Treatment Outcomes

Firstly, from the point of clinical management, the effect size of treatment (i.e. improvement in oral functions) should be carefully estimated for evaluating treatment outcomes. For example, by assessing the cutting ability, researchers were able to identify the effect of occlusal support (i.e. wearing a partial/complete removable denture or not) on masticatory performance (Yamashita et al. 2000). In a randomized controlled study of the elderly people aged ≥75 years, the researchers found a significantly higher MBF but an insignificant difference in the mixing ability (based on the TCGT), in the patients with an implant‐supported overdenture, compared to the patients who received reline of a complete denture (Müller et al. 2013). The findings suggest that better occlusal support may contribute to better masticatory performance in cutting (Yamashita et al. 2000). However, the effect of better occlusal support on improving masticatory performance in mixing is less clear‐cut (Müller et al. 2013). Consistently, a systematic review showed that the patients with shortened dental arches revealed a 30–40% reduction in their masticatory performance, while a distal extension of the removable dental prosthesis could partially compensate 50% of this reduction (Liang et al. 2015). Together, the findings suggest that via assessment one can better clarify the association between clinical interventions and improvement of oral functions brought by the interventions.

The use of assessment also contributes to tracing the change of oral functions over a long period. For example, the longitudinal fMRI study by Luraschi et al. (2013) revealed that the mixing ability and MBF significantly increased when the patients adapted to a new denture during a three‐month follow‐up. In contrast, some research did not show a significant change in the cutting ability over one year of treatment (Aras et al. 2009). It should be noted that at present most studies of functional assessments have focused on their validity, which can be demonstrated by a correlation with other clinical symptoms and signs (e.g. the more the missing teeth, the lower the masticatory performance) (Woda et al. 2010; Tarkowska et al. 2017). There exists less evidence regarding the temporal stability, i.e. the test vs. re‐test reliability, of the assessments because most research was conducted with a cross‐sectional design. Good temporal stability for either functional or questionnaire assessments would be essential for evaluating the change of oral functions over a long period.

3.1.6.2 Evaluation of the Association Between Oral and Systemic Factors

Secondly, through the assessments, it becomes feasible to investigate the association between oral functions and the systemic factors related to general physical/mental conditions. In terms of physical conditions, a recent study with a large sample size (n = 5104) of elderly people (aged ≱ 65 years) showed that the status of physical frailty, including non‐frail, pre‐frail and frail, was associated with the full‐arch biting force (Watanabe et al. 2017). In terms of cognitive impairment, patients with cognitive impairment showed a worse masticatory mixing and cutting performance (Campos et al. 2017; Kim et al. 2017). In addition, the assessment of oral functions helps to clarify the association between oral functions and the factors related to diet, including the selection and processing of food. For example, the sieve method can be used for quantifying the particle size distribution of food boluses (Peyron et al. 2004b). Based on a test of six natural foods, Peyron et al. (2004b) found that upon the completion of mastication, the sizes of the chewed particles were similar among the nuts and among vegetables, and only little inter‐individual variability was found for the chewed particle size. The findings echoed the importance of maintaining an optimal size of food particles for swallowing. Upon swallowing, one needs to chew the food until it is broken down into small particles with sufficient lubrication, and the detection of particle size with oral mucosa may play a key role (Prinz and Lucas 1995). With the results from a functional assessment of mastication, one can quantify the association between individual masticatory performance and the properties of food.