The United Nations has defined a population in which those aged 65 years or older comprise 7% to 14% of the population as an aging society, 14% to 20% as an aged society, and 20% or higher as a super-aged society¹⁾. In 2019, the percentage of Koreans aged 65 years and older was estimated to be 14.9% of the entire population, categorizing Korea as an aged society²⁾. The elderly population is currently 7.68 million, approximately 2.31 million more compared to a decade ago. Due to this surge in the elderly population, there is a growing interest in the prevention and treatment of geriatric diseases and increasing awareness of the severity of problems associated with dementia, a cognitive impairment.

Dementia is a condition associated with multiple cognitive impairments including aphasia, apraxia, agnosia, and loss of executive function, in addition to the memory impairment due to an acquired brain disease, which seriously interferes with the social and occupational functions³⁾. Dementia is a serious social problem since severe deterioration in the cognitive function undermines independent physical functioning and results in a high dependence on support systems such as family and the community⁴⁾. According to the 2018 Korean statistics of the cause of death, the number of deaths increased significantly compared to the previous year, citing an increase in the elderly population due to aging. Alzheimer’s related deaths increased by 22.5 percent to 12.0 per 100,000 people in 2018.

Previous studies have suggested a variety of factors that are associated with cognitive function^5,6). The demographic characteristics include age, sex, education, and living arrangements; and the health characteristics include the chewing ability, the number of remaining teeth, denture status, nutrition, exercise, and depression. Chewing ability is the ability to grind food to help in swallowing; however, recent studies suggest that chewing ability can affect brain function⁷⁾. A systematic literature review also reported a relationship between chewing ability and cognitive functions such as memory, retention, and attention⁸⁾. Among the various cognitive functions, the chewing ability was found to have a positive effect on attention, especially sustained attention⁹⁾. The review demonstrated that certain areas of the brain were activated during chewing based on the measurement of local cerebral blood flow¹⁰⁾. Moreover, the increased chewing ability was found to increase the blood oxygen concentration in the frontal cortex and hippocampus, which carry out cognitive functions, and influence the organs responsible for learning and memory. Evaluation of the effects of the chewing ability on neural activity in the brain showed that chewing can affect the right hippocampus and thalamus, resulting in arousal and enhanced memory to improve the overall cognitive function. Another systematic review of various cross-sectional and cohort studies conducted in the elderly populations also found an association between decreased chewing ability and cognitive function¹¹⁾.

There is extensive research in the literature reporting the relationship between chewing ability and cognitive function¹²⁾. However, few studies have examined the relationship between oral health, chewing ability, and cognitive function. The present study aimed to evaluate the elderly population in a rural community regarding their denture status, the remaining teeth, the chewing ability by visual inspection and colour-changeable chewing gum, as well as the occlusion patterns, and investigate the relationship with cognitive function.

1. Study participants

This cross-sectional study was conducted in the elderly population aged 65 to 97 years, residing in Village K, located in Ganghwa County of Incheon, Korea, over a duration of 10 days in February 2018. The study population was in the Korean Social Life, Health, and Aging Project (KSHAP) which is a precursor to the National Social Life, Health, and Aging Project (NSHAP) conducted in the United States, designed to understand how social networks relate to a wide variety of health conditions in the elderly^13,14). A trained dentist conducted the oral examination to evaluate the number of remaining teeth, denture status, and occlusion patterns. Trained dental hygienists conducted interviews to obtain information regarding the general characteristics, oral health, and cognitive function measured using Mini-Mental State Examination-Dementia Screening (MMSE-DS). A skilled investigator performed the visual shade-matching of the colour-changeable chewing gum to evaluate the chewing ability and the colour changes were measured using a digital shade analysis system. A total of 162 participants, 53 men and 109 women, who completed the survey questionnaires and the oral health examinations, were included in the data analysis. All participants were informed of the nature of the study and informed consent was obtained. This study was approved by the Institutional Review Board (IRB) of the Kyungpook National University Hospital (KNUH 2015-07-007-001).

2. Assessment of the chewing ability

2.1. Denture status

Regarding the status of the maxillary and mandibular dentures, the participants were classified into three groups: natural teeth, partial/complete denture wearers, and requiring dentures. The criteria for requiring dentures were either the absence of both premolars and molars or the absence of molars in at least one quadrant.

2.2. Number of remaining teeth

An oral examination involved the inspection of all teeth including the third molars. The number of remaining teeth excluded the teeth that allow ≥1 mm horizontal and vertical mobility based on Miller’s¹⁵⁾ classification in consideration of the functional chewing aspects, and implants or teeth with only remaining root. The study participants were classified into four groups depending on the number of remaining teeth as edentulous, 1-9, 10-19, or ≥20¹⁶⁾.

2.3. Evaluation of the chewing ability with colour-changeable gum

The colour-changeable chewing gum (Masticatory Performance Evaluating Gum XYLITOL, Lotte Co., Ltd., Tokyo, Japan) was used to evaluate the chewing ability both subjectively and objectively. The red dye is pH-sensitive and it changes colour under neutral or alkaline conditions. Citric acid maintains a low internal pH in the green-yellowish coloured gum before chewing. As chewing progresses, the gum changes to a pink colour since the yellow and blue dyes seep into the saliva and the pink colour appears due to elution of the citric acid¹⁷⁾. After the gum was chewed naturally by the participants for two minutes, a visual shade matching was performed using a five-point scale: 1=green, 2=yellow, 3=light pink, 4=pink, 5=hot pink. The participants were classified into two levels of chewing ability: 1 to 3 points were classified as poor chewers and 4 to 5 points were classified as good chewers.

2.4. Colourimeter (ShadeEye-NCC) digital shade analysis system

For the objective numerical representation of the colour-changeable chewing gum, measurements were obtained using ShadeEye-NCC (Dental Chroma Meter, SHOFU Inc., Kyoto, Japan), a digital shade analysis system. ShadeEye-NCC employs the CIELAB colour system to offer values of L* (brightness of colour), a* (red-green hue), and b* (yellow-blue hue) for calculation of the ΔE (overall change in colour)¹⁸⁾. To obtain ΔE, five areas of the gum were randomly measured and the measurements were averaged¹⁹⁾.

2.5. Examination of occlusion pattern

The T-scan III^® system (Tekscan, Inc., Boston, MA, USA) is a diagnostic device that provides dynamic occlusal measurement revealing the level and timing of force on individual teeth and the occlusal stability of the overall bite²⁰⁾. The participants were asked to sit in chairs, slightly lift their heads, and clench their teeth in centric occlusion position. Then the dentist measured the occlusal pattern by setting the occlusal sensor’s pointer of the T-scan III^® system between the maxillary central teeth to maintain the correct position. The occlusion recordings were obtained by adjusting the sensitivity until 1-3 red dots appeared, having the participants clench their teeth in the centric occlusion position for two seconds, and repeating the process 2-3 times to determine the colour variations in the occlusion forces on a graph. The measurements were classified into four categories for analysis—unilateral, bilateral, anterior, and posterior²¹⁾.

3. Assessment of the cognitive function

The cognitive function of the participants was assessed using the Korean version of the Mini-Mental State Examination for Dementia Screening (MMSE-DS) developed by Kim et al.²²⁾ for the standardization of dementia screening tools at the Ministry of Health and Welfare. The assessment included 19 items with scores ranging between 0 to maximum 30 points (10 points for orientation, 6 points for verbal memory, 5 points for concentration and calculation, 5 points for language, 3 points for praxis, 1 point for visuospatial construction, and 2 points for judgment and common sense). The total score of each participant was evaluated according to age, gender, education level, and the type of residence based on the test manual²³⁾. An MMSE-DS score ≤23 was considered to indicate cognitive impairment, while a score of >23 was considered as normal cognitive function²⁴⁾.

4. Statistical analysis

Data analysis was performed using IBM SPSS version 23.0 for Windows (SPSS Inc., Chicago, IL, USA) at a 5% significance level. Frequency analysis was used to determine the participants’ general characteristics, while the Chi-square test, t-test, and one-way ANOVA were used to determine the relationship between the general characteristics, chewing ability, and cognitive function. If the results of the one-way ANOVA suggested a mean difference, we further conducted the Scheffe’s post hoc test. We also conducted a multiple regression analysis to evaluate the relationship between chewing ability and cognitive function, adjusting for age, gender, education level, and living arrangements.

The characteristics of the study participants and the chewing ability factors with cognitive function are shown in Table 1. The participants were divided into two groups according to their MMSE-DS scores (cognitive impairment, MMSE-DS score ≤23, n=52 or MMSE-DS score >23, n=110). The mean MMSE-DS score was lower for participants aged 80 years or older (23.84±3.98), women (24.19±3.97), less educated (24.19±3.90) and those living with family other than spouses (22.84±4.67). All the variations were significantly different (P<0.05). The variations in cognitive function according to the chewing ability indicate that more the teeth, higher the mean MMSE-DS score (P<0.05). The cognitive function between the two groups was classified based on the colour change in the chewing gum and the MMSE-DS score was significantly lower (P<0.001) in the group with poor chewing ability indicated by less colour change.

Table 1 . Cognitive function with socio-demographic and chewing ability.

	Cognitive impairment
	N (%)	MMSE-DS score			Yes (≤23)		No (>23)	P-value**
		Mean±SD	P-value*		N=52		N=110
Age			.010					.010**
<80	89 (54.9)	25.36±3.45			21 (40.4)		68 (61.8)
≥80	73 (45.1)	23.84±3.98			31 (59.6)		42 (38.2)
Gender			.019*					.031**
Male	53 (32.7)	25.66±3.12			11 (21.2)		42 (38.2)
Female	109 (67.3)	24.19±3.97			41 (78.8)		68 (61.8)
Education			.001*					.002**
≤Elementary	129 (79.6)	24.19±3.90			49 (94.2)		80 (72.7)
>Elementary	33 (20.4)	26.58±2.40			3 ( 5.8)		30 (27.3)
Living arrangement			.002*					.014**
Alone	42 (25.9)	23.62±3.78			19 (36.5)		23 (20.9)
With spouse	101 (62.3)	25.46±3.36			24 (46.2)		77 (70.0)
With family	9 (11.7)	22.84±4.67			9 (17.3)		10 (9.1)
Denture status			.284					.053
Need denture	29 (17.9)	23.55±4.15			13 (25.0)		16 (14.5)
Denture wearer	69 (42.6)	24.87±3.94			18 (34.6)		51 (46.4)
Natural teeth	64 (39.5)	24.97±3.33			21 (40.4)		43 (39.1)
Number of remaining teeth			.017*					.276
0	17 (10.5)	22.06±4.53			9 (17.3)		8 (7.3)
1-9	25 (15.4)	24.40±4.16			7 (13.5)		18 (16.4)
10-19	35 (21.6)	24.91±3.61			11 (21.1)		24 (21.8)
≥20	85 (52.5)	25.15±3.37			25 (48.1)		60 (54.5)
Color-changeable gum			.001*					.044**
Poor (1-3)	40 (24.7)	23.05±4.95			18 (34.6)		22 (20.0)
Good (4-5)	122 (75.3)	25.20±3.13			34 (65.4)		88 (80.0)
Occlusion balance I			.206					.078
Unilateral	65 (40.1)	24.22±4.10			26 (50.0)		39 (35.4)
Bilateral	97 (59.9)	24.98±3.51			26 (50.0)		71 (64.6)
Occlusion balance II			.284					.053
Anterior	101 (62.3)	24.43±3.59			14 (26.9)		47 (42.7)
Posterior	61 (37.7)	25.08±4.03			38 (73.1)		63 (57.3)

Occlusion balance I: Bilateral balanced occlusion..

Occlusion balance II: Anterior and posterior balanced occlusion..

*P<0.05 by one-way ANOVA or t-test..

**P<0.05 by χ²-test..

The relationship between Shade Eye-NCC measuring the chromaticity of the chewing gum and the cognitive function is shown in Table 2. The overall change in colour (ΔE) was strongly correlated with the denture status (P<0.05), the number of remaining teeth (P<0.05), visual inspection of colour changes in the gum (P<0.05), and bilateral occlusion balance (P<0.05).

Table 2 . Cognitive function and chewing ability according to ShadeEye-NCC L*, a*, b*, ΔE of colour-changeable gum.

	ShadeEye-NCC
	L*	P-value	a*	P-value	b*	P-value	ΔE	P-value
Denture status		.003*		<.001*		.035*		<.001*
Need denture	59.27±3.40		32.05±6.08		16.94±5.26		51.49±7.55
Denture wearer	58.45±2.19		33.89±4.03		14.23±4.27		54.19±5.16
Natural teeth	58.24±2.03		36.12±3.11		11.34±3.58		57.29±3.75
Number of remaining teeth		<.001*		<.001*		.046*		<.001*
0	61.80±4.87		27.48±8.66		21.63±5.71		45.37±10.36
1-9	59.62±2.94		30.80±5.50		18.35±4.86		49.80±6.76
10-19	58.79±2.85		33.26±4.61		15.96±4.32		52.98±5.74
≥20	58.09±2.02		35.90±3.27		11.77±3.51		56.97±3.94
Color-changeable gum		<.001*		<.001*		.018*		<.001*
Poor (1-3)	61.49±3.98		27.02±6.59		21.88±4.11		44.87±7.74
Good (4-5)	58.01±1.90		35.84±2.56		12.38±3.30		56.71±3.10
Occlusion balance I		.183		.002*		.006*		.001*
Unilateral	59.25±3.63		31.84±6.67		15.65±6.34		51.79±8.45
Bilateral	58.61±2.42		34.88±4.12		14.11±4.60		55.12±5.32
Occlusion balance II		.311		.540		.484		.767
Anterior	58.68±2.68		33.10±5.04		15.57±5.04		53.01±6.41
Posterior	59.17±3.39		34.59±6.07		13.32±5.73		55.06±7.58

Occlusion balance I: Bilateral balanced occlusion..

Occlusion balance II: Anterior and posterior balanced occlusion..

*P<0.05 by one-way ANOVA or t-test..

According to the multiple regression analysis results to determine the relationship between chewing ability and the cognitive function is shown in Table 3. The MMSE-DS score was positively correlated with the denture status (β=0.406, P<0.05), the number of remaining teeth (β=0.352, P<0.05), and age (β=- 0.197, P<0.05) in Model III, in which the age, gender, education level, and living arrangements were adjusted. No multicollinearity among the variables was found.

Table 3 . Multiple regression analysis of chewing ability and cognitive function.

	Reference	MMSE-DS score
		Model I (crude)				Model II				Model III
		B	β	P-value		B	β	P-value		B	β	P-value	VIF†
Denture status	Need denture	.128	.420	.000*		.310	.412	.000*		.305	.406	.000*	2.223
Number of remaining teeth	.	.128	.340	.005*		.138	.365	.002*		.133	.352	.003*	2.717
Colour-changeable gum	Poor	.151	.017	.878		.116	.013	.903		.036	.004	.970	4.345
Occlusion balance I	Unilateral	.110	.014	.850		.254	.033	.653		.250	.033	.659	1.115
Occlusion balance II	Anterior	.501	.065	.398		.233	.030	.687		.186	.024	.749	1.152
Total colour change of ShadeEye-NCC (ΔE)	.	.149	.274	.017*		.085	.157	.173		.085	.156	.176	4.495
Age	<80					―.129	―.235	.003*		―.108	―.197	.022*	1.435
Gender	Male					―1.108	―.139	.059		―.770	―.096	.235	1.295
Education	≤Elementary									1.020	.109	.194	1.436
Living arrangement	Alone									―.046	―.007	.920	1.074

*P<0.05 by linear regression..

VIF<10, Variance inflation factors..

Model (crude) I: Unadjusted model..

Model II: Model I+age and gender adjusted model..

Model III: Model II+education, and living arrangement adjusted model..

In this study, we analyzed the effects of chewing ability and cognitive function in 162 elderly people aged 65 or older and residing in a rural area. There were significant differences in the cognitive function according to the age, gender, education level and living arrangements, and in the distribution of cognitive function according to the number of remaining teeth. The multiple linear regression analysis showed a significant association between the MMSE-DS scores with the number of remaining teeth and denture status. These results suggest the possibility of being dynamically related to the number of remaining teeth and cognitive function.

Some studies have evaluated the association between the number of remaining teeth and cognitive functions. According to Van der bilt²⁵⁾, the number of teeth and the anatomical structure were related to the dentition, and the number of teeth as a single factor can have the most effect. Kalaria et al.²⁶⁾ reported that the lower the socioeconomic status such as education and income, the higher the risk of developing dementia. Another study by Zahodne et al.²⁷⁾ also showed that those with lower education levels had a lower cognitive function. Paganini-Hill et al.²⁸⁾ found that chewing with dentures is more likely to cause dementia than chewing with natural teeth. Consequently, the results of this study can be interpreted on this basis.

This study investigated the elderly population in a rural Village K in Ganghwa County of Incheon, which limits the ability to generalize our findings. In particular, the number of study participants was 162, which is a smaller sample size compared to some studies. In addition, the difficulty in gender analysis due to the gender imbalance among the participants, 53 men (32.7%) and 109 women (67.3%), can be another limitation of this study. Moreover, the association between the sociodemographic dimension and cognitive impairment, and the association between chewing ability and cognitive impairment were investigated separately using correlation analyses. However, the sociodemographic dimension was not applied to the study design to analyze the association between the chewing ability and cognitive function in the study design and needs to be addressed in future research.

The use of the T-scan III^® system for determination of the occlusion pattern in the assessment of the chewing ability in this study also has limitations. First of all, as the system was not equipped for absolute assessment of the occlusion patterns due to variations in the sensitivity of its sensors, only the relative occlusal distribution of the participants was examined. Moreover, the study classified the occlusion patterns into unilateral, bilateral, anterior, and posterior patterns by classifying the mouth into four quadrants (anterior, posterior, left and right) and obtaining the relative occlusal distribution of the participants using percentages for the quadrants. However, due to a lack of previous studies reporting the objective criteria for classifying the occlusion, the occlusion patterns used in the present study are relative and arbitrary.

This study reports significant findings including the effects of cognitive impairment measured using MMSE-DS on the chewing ability in elderly participants and verifies the relationship between the decline in cognitive function and low chewing ability. Future studies need to include sociodemographic analysis to examine the relationship between cognitive function and oral health.

The study highlights the importance of association between chewing ability and cognitive function. The finding corroborates that tooth loss may be a predictor of risk factor for cognitive impairment.

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A3A2067165).

*This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A3A2067165).

The authors declare no conflict of interest.