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  | Title = Assessment of subjective and objective masticatory function among elderly individuals with mild cognitive impairment

Assessment of subjective and objective masticatory function among elderly individuals with mild cognitive impairment

Nan-Ju Lee, Hyo-Jung Kim, Yiseul Choi, Taek-Bin Kim & Bock-Young Jung  

Metrics details

Masticatory function is known to be related to cognitive ability; therefore, factors for improving masticatory function should be identified.

Aims

This study aimed to identify factors influencing masticatory function associated with mild cognitive impairment (MCI) in elderly individuals.

A total of 123 elderly participants [mean age: 76.5 ± 6.5 years; 82 females (66.7%), 41 males (33.3%)] were included. Cognitive function was evaluated by the Korean version of the Mini-Mental State Examination (KMMSE). Questionnaires for subjective evaluation were administered, and dynamic objective masticatory function evaluations, including chewing tests and bite force measurements, were performed. Intergroup differences were evaluated by the Wilcoxon rank-sum and chi-square test, and correlations between cognitive ability and masticatory function were evaluated by multilinear logistic regression.

The number of teeth, number of posterior teeth, bite force, masticatory ability index (MAI) and posterior support status showed significant differences between the normal (KMMSE > 23) and MCI (KMMSE ≤ 23) groups. However, only the MAI, representing dynamic masticatory performance, was significantly associated with MCI regardless of age, sex and removable prostheses. The number of teeth and posterior teeth, bite force, subjective masticatory ability and posterior occlusal support showed no significant association with MCI.

These results suggested the importance of chewing function for preventing the progression of cognitive impairment.

Considering that only the MAI was significantly associated with MCI, it is more important to improve chewing efficiency by harmonizing therapeutic prosthetics with the surrounding masticatory system than simply increasing the number of teeth to prevent or delay cognitive impairment in elderly individuals.

As the aging population is growing rapidly worldwide, aging-related health problems such as cognitive impairment and dementia have begun to stand out as social issues in terms of welfare.

Clinically, the identification of factors associated with MCI progression to dementia and MCI reversion to normal cognitive function has important implications. There have been many studies on the association between oral health and cognitive status, but most of these studies have examined single-element relationships and have shown conflicting results. Variations in methodology, especially diversity in research populations, are considered the main reason for the lack of causality and inconsistent outcomes. Additionally, there are no standard data regarding oral function from a normal healthy population comprising various age groups to enable a quantitative comparison. This study aimed to identify the significantly influential variables among various factors of subjective and objective masticatory function that are potentially associated with MCI and to suggest an oral rehabilitation guide for the reversion of MCI in elderly individuals.

This cross-sectional study was performed according to the guidelines of the Declaration of Helsinki and was approved by the institutional review board committee of the Yonsei University College of Dentistry (No. 2-2019-0009). Among the patients over 65 years of age who visited the Department of Advanced General Dentistry of the Yonsei University Dental Hospital from March 2019 to February 2020, 123 participants who met the following criteria were included: (1) able to communicate, answer the questions and fill out the questionnaires on their own; and (2) had completed prosthetic treatment at least 4 weeks prior and had no chewing problems.

To avoid bias from factors not related to masticatory function, the exclusion criteria were as follows: (1) history of a congenital or acquired disease, such as cerebral infarction, or psychiatric illness, including depression and dementia, that could make it difficult for the participant to communicate with researchers; (2) difficulty in performing dynamic masticatory function tests with maximal effort due to health problems, such as cardiovascular disease, general weakness after surgery and Parkinson disease [24]; and (3) temporomandibular joint pain and tooth mobility of grade 2–3. Written consent was received directly from each participant. The sample size was calculated using G*power 3.1 software (Kiel University, Kiel, Germany) with α set to 0.05, the power set to 0.99 and the effect size set to 1.68.

All participants underwent cognitive and masticatory function assessments. Cognitive function was assessed by 1 trained researcher using the KMMSE. For the masticatory function evaluation, both subjective and objective assessments were performed. The subjective masticatory ability assessment was conducted using a simple questionnaire, the Key Food Intake Ability (KFIA) questionnaire, to determine the participant’s own masticatory ability. A chewing test and bite force measurement were performed to assess the dynamic objective masticatory function, and the number of remaining teeth, number of posterior teeth, posterior occlusal contact and presence or absence of RPs were recorded for the static objective masticatory assessment.

The KMMSE consisted of 30 questions in the following 6 domains: registration; attention and calculation; recall; language; ability to follow simple commands; and orientation. Each question was rated as 0 or 1 point, and the KMMSE score was recorded as the total number of points, ranging from 0 to 30, with lower scores indicating greater cognitive impairment. The MCI group included participants with a cutoff score of 23 based on a previous study [27]. Those who belonged to the MCI group in this study were recommended to visit a neurologist for further evaluation.

The number of remaining teeth was determined by counting the teeth that were natural or restored teeth except for third molars and root rests. Posterior occlusal supports were recorded using the Eichner index based on the condition of posterior occlusal contact between the maxilla and the mandible, with the following 3 classifications: Eichner A, occluding pairs in four bilateral posterior supports; Eichner B, one to three occluding pairs or occluding contacts in the anterior region; and Eicher C, no occluding pairs [28].

The mixing ability test developed by Sato et al. [29] was used to measure chewing ability and dynamic masticatory performance. The mixing ability index (MAI) was calculated by analyzing the degree of color mixing and the shape and width of a chewed wax specimen, a two-color wax cube (12*12*12 mm3) (Fig. 1). Each participant was instructed to chew the wax specimen ten times with a normal chewing pattern using one’s own habitual masticatory side with the head upright in an unsupported natural position. This chewing test was repeated twice, and the chewed wax specimens were kept in a refrigerator and analyzed within three days to avoid any deformation. Images of both the front and back sides of the chewed wax specimen without shadows were captured using a digital single-lens reflex camera (D80, Nikon Co., Tokyo, Japan) and saved as JPEG files [30]. Both monochrome images and color images of each specimen were obtained using a digital image analyzer (Image-Pro Plus® version 6.0, Media Cybernetics, Inc., Bethesda, MD, USA) (Fig. 2). Areas without color mixing, i.e., green or red areas, were selected in color images using an eyedropper tool built in the analyzer and calculated by a single independent examiner to eliminate measurement error. The MAI was calculated using a scale of 0–100 points, and the average of two specimens was obtained. The MAI assessment is a relative comparison, with a higher MAI indicating better masticatory performance [30].

Participants were instructed to bite with their own maximum force several times at the maximal intercuspal position for 3 s while seated in a comfortable position with the head upright, keeping Frankfort’s horizontal plane parallel to the ground. An adequately sized pressure-sensitive film (Dental Prescale 50H, GC, Japan) was positioned in the mouth, and the bite force was measured and analyzed using a bite force analyzer (OCCLUSER 709, GC, Japan) [31].

Subjective masticatory ability was assessed using the self-assessed questionnaire asking if the participant had any difficulties chewing five key foods, including peanuts, carrots, caramel, dried squid, and diced radish Kimchi [32], and the KFIA score was recorded using a five-point Likert scale depending on the degree of discomfort. The average score for the five key foods was recorded as the KFIA score, with a higher score indicating better subjective masticatory function (Table 1).

All statistical analyses were carried out using SAS 9.4 software (SAS Institute, Inc., Cary, NC, USA) with a significance level of 0.05. The Wilcoxon rank-sum test was used to determine differences between the groups in terms of continuous dependent variables, and the chi-square test was used for categorical variables. To determine the statistical correlation between cognitive ability and masticatory function, multiple generalized linear and logistic regression analyses were performed. The dependent variables were age, the KFIA score, number of teeth, number of posterior teeth, bite force, MAI and Eichner index, and the independent variable was the KMMSE score.

The participants consisted of 82 women (66.7%) and 41 men (33.3%), with a mean age of 76.5 ± 6.5 years; 31 out of 123 participants were in the MCI group, and the remainder were in the normal group.

Those in the MCI group had significantly fewer remaining teeth and posterior teeth than those in the normal group (P = 0.030, < 0.010). Among the objective measures of masticatory function, the bite force in the MCI group was significantly lower than that in the normal group (P = 0.048). Regarding the MAI, representing dynamic chewing ability, the MAI was significantly lower in the MCI group than in the normal group (P < 0.0001). The Eichner A proportion was higher in the normal group, and the Eichner B + C proportion was significantly higher in the MCI group (P = 0.004). The percentage of overall participants wearing RPs was 36.6%, which was more than one-third, and the difference in the percentage of participants wearing RPs between the normal and MCI groups was significant (P = 0.015).

Table 3 shows a comparison of the results of the subjective and objective masticatory function evaluations according to the presence of RPs. In the non-RP group, there was a significant difference in age and the MAI between the normal and MCI groups (P < 0.05). In the RP group, there was a significant difference in the MAI between the MCI and normal groups. That is, the MAI showed a significant difference between the MCI and normal groups regardless of the presence of RPs.

Table 4 shows the results of simple and multiple linear regression analyses of the association of MCI with the factors of the subjective and objective assessments.

Model 2 is a multiple generalized linear model adjusted for age, sex and the presence of RPs, and the results showed that the KFIA score, number of remaining teeth, number of posterior teeth and bite force were not significantly different between the MCI and normal groups. However, a significant difference was shown in the MAI in the MCI group (P < 0.0001). The odds of incomplete posterior occlusal support were 3.12 times higher in the MCI group than in the normal group, with no statistical significance (P = 0.112) in Model 2*.

The influence of the presence of RPs was investigated to determine whether it had any association with cognitive impairment.

Table 5 shows that the KFIA score, number of remaining teeth, number of posterior teeth and bite force had no statistically significant association with MCI regardless of RP use. However, the MAI was significantly lower in the MCI group than in the normal group regardless of the presence of RPs (P < 0.0001). Regarding the Eichner index, the likelihood of having incomplete posterior occlusal support was higher in both the non-RP MCI (OR: 4.03, CI 0.81, 20.18) and RP MCI (OR: 1.36, CI 0.10, 18.85) groups, without a significant difference.

Most clinical studies on masticatory function have performed both objective and subjective assessments because while subjective methods show other aspects of mastication, such as adoptive and psychological factors, they have not been used to examine the relationship between MCI and oral function due to the unreliability of data obtained from participants with cognitive decline [7, 12, 16, 23, 33]. However, in this study, both subjective and objective methods were applied because the participants were physically healthy and independent in their daily lives, and chewing ability measured by a subjective masticatory function assessment could have a significantly positive association with cognitive impairment [6]. Therefore, to some extent, it was expected that the results of the subjective and objective masticatory assessments might not necessarily agree completely [34] but that there might be a degree of agreement between them. However, the difference in the KFIA score, reflecting subjective masticatory function, between the normal and MCI groups in this study was not significant (P = 0.076), even though there was a significant difference in the MAI, reflecting objective masticatory function. This finding is supported by those previous studies reporting that older people tend to overestimate their physical function without an awareness of latent declines [34]. Additionally, the disagreement rate has been reported to range from 22.4% to 39% [10], and this phenomenon can be explained as ‘anosognosia’, which is a major symptom of MCI originating from the reduced neuronal response in the frontal and parietal cortical midline structures [24, 35].

The power of this analysis was greater than 0.8, and the significance level was sufficiently high; thus, our results can be considered reliable. However, for more precise verification, a sufficient number of participants should be included in the MCI and normal groups with a uniform sex distribution. In addition, care must be taken to select participants with various oral conditions, such as various degrees of posterior occlusal support and types of prostheses, to avoid possible bias in the results.

Based on data from participants with approximately 20 remaining teeth and no difficulty chewing, the MAI, among other masticatory factors, was significantly associated with MCI in elderly patients.

     Petersen RC, Morris JC (2003) Clinical features. In: Petersen RC (ed) Mild cognitive impairment: aging to Alzheimer’s disease. Oxford University Press, New York, pp 15–40