Loss of Functional Dentition is Associated with Cognitive Impairment

Abstract

Background:

Although tooth loss is known to increase the risk of cognitive impairment and dementia, few studies have investigated the association between functional teeth including rehabilitated lost teeth and cognitive function

Objective:

We investigated the associations of the numbers of functional teeth and functional occlusal units with cognitive impairment and cognitive function in late life.

Methods:

The current study was conducted as a part of the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD), a community-based elderly cohort study. We analyzed 411 participants who have agreed with the additional dental exam. Geriatric psychiatrists and neuropsychologists administered the Consortium to Establish a Registry for Alzheimer’s disease Assessment Packet Clinical and Neuropsychological Assessment Battery to all participants, and dentists examined their dental status.

Results:

Higher number of functional teeth (OR = 0.955, 95% CI = 0.914–0.997, p = 0.037) and higher number of functional occlusal units (OR = 0.900, 95% CI = 0.813–0.996, p = 0.042) were associated with lower odds of cognitive impairment. When we analyzed these relationships separated by the location of teeth, only the numbers of functional teeth (OR = 0.566, 95% CI = 0.373–0.857, p = 0.007) and functional occlusal units (OR = 0.399, 95% CI = 0.213–0.748, p = 0.004) in the premolar area were associated with lower odds of cognitive impairment.

Conclusion:

Loss of functional teeth and functional occlusal units (especially in the premolar region) were associated with increased cognitive impairment.

Keywords

Cognitive impairment dental prosthesis occlusal unit tooth

INTRODUCTION

Systematic reviews and meta-analyses suggest that a lower number of residual teeth is associated with higher risk of cognitive impairment or dementia in late life [1 –3]. One possible explanation for the adverse effects of tooth loss on late-life cognition could be a decrease in masticatory activity, although a causal relationship has not been conclusively demonstrated [4 –6]. Animal studies have shown that reduced masticatory activity in older animals resulted by consumption of soft food led to a loss of spatial memory, reduced learning capacity, neuroendocrine changes, and hippocampal degeneration [6, 7]. Importantly, the frontal cortex was shown to be activated during mastication, particularly in older individuals [8, 9].

If masticatory activity is indeed a key factor, the number of residual functional teeth or functional occlusal units may reflect more accurately the true extent of masticatory stimulation and should be more strongly associated with risk of cognitive impairment than the number of residual natural teeth. Some studies reported that masticatory function may be more closely related to cognitive impairment than the number of natural teeth in humans [7 , 11].

Masticatory function was found to be improved by dental rehabilitation procedures such as implants and fixed prostheses, which have become increasingly common in recent years [12]. However, the associations between cognitive function and the numbers of functional teeth or functional occlusal units have not been subject to intense study, compared to the associations with the number of residual natural teeth.

It would be important to determine whether the number of functional teeth and the number of functional occlusal units are associated with cognitive impairment as functional dentition is a modifiable factor in one’s health.

Two recent studies reported that the number of functional masticatory units was associated with the scores of brief cognitive tests. [13, 14]. However, their association with cognitive impairment has never been investigated. In this study, we investigate the association between the numbers of functional teeth and functional occlusal units and cognition in a randomly sampled community-dwelling elderly population.

MATERIALS AND METHODS

Participants

The current study was conducted as a part of the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD) [15]. The KLOSCAD is an ongoing nationwide, prospective, community-based elderly cohort study evaluating cognitive aging and dementia in 6,818 community-dwelling elderly Koreans aged 60 years or older randomly sampled from 30 villages and towns across South Korea using residential rosters. A total of 696 participants enrolled from Jukjeon district, Yongin, were invited to undergo dental examinations between 2012 and 2013, with 433 (62.2%) completing dental assessments. Final analysis included 411 participants: 11 participants were excluded due to a diagnosis of a major psychiatric disorder listed in the Axis I of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders–Text Revision (DSM-IV-TR) [16] at baseline assessment and 11 participants refused to undergo apolipoprotein (APOE) genotyping. Compared to the overall cohort (KLOSCAD), this subcohort, sample from a large urban area near the Metropolitan Seoul, was younger, more educated, had higher socioeconomic status (SES), and less depressive symptoms but with more medical comorbidities (Supplementary Table 1). All participants provided written informed consent. Study protocol was approved by the institutional review board of Seoul National University Bundang Hospital (SNUBH) (B-0912-089-010).

Assessment of dental status

Trained dentists from the Department of Periodontology at SNUBH assessed the dental status of each participant, including the numbers of natural teeth, fixed prostheses, and implants, as well as the use of dentures. All healthy, carious, or treated (including crowns or inlays) teeth were considered as natural teeth. Natural or prosthetic teeth, including implants and fixed prostheses, were considered as functional teeth. A functional occlusal unit was defined as a pair of natural teeth, fixed or removable prostheses or implants except where both sides of a pair were removable prostheses. We classified the teeth and functional occlusal units by their location into three groups: anterior (incisors and canines), premolar (1st and 2nd premolar), and molar (1st and 2nd molar). We excluded 3rd molar teeth and retained roots from current analysis as they have little contribution to mastication.

Assessment of cognitive function

Geriatric psychiatrists administered a standardized diagnostic interview, a physical and neurological examination, and laboratory tests to each participant, including a complete blood cell count, chemistry profile, a serologic test for syphilis, and apolipoprotein E (APOE) genotyping. Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease Assessment Packet Clinical Assessment Battery (CERAD-K-C) [17] and the Korean version of Mini International Neuropsychiatric Interview were used in the assessments [18]. Additionally, neuropsychologists or trained nurses administered the Frontal Assessment Battery (FAB) [19], Digit Span Test [20], and CERAD-K Neuropsychological Assessment Battery (CERAD-K-N), [17, 21] which consists of Verbal Fluency Test, 15-item Boston Naming Test, MMSE, Word List Memory Test, Word List Recall Test, Word List Recognition Test, Constructional Praxis Test, Constructional Recall Test, and Trail Making Test A. More detailed information on the study protocol and procedures can be found elsewhere [22].

Dementia was diagnosed according to DSM-IV-TR criteria, while mild cognitive impairment (MCI) was diagnosed on the basis of the criteria of the International Working Group on MCI [23]. Diagnosis of dementia or MCI was determined for each participant in a consensus diagnostic conference attended by four geriatric research psychiatrists. Cognitive impairment was defined as a diagnosis of MCI or dementia.

Assessment of other confounding variables

Low SES was defined as monthly family income of 1,000,000 KRW or less. We assessed lifetime smoking habits and alcohol use as packs per years and standard units, respectively. Additionally, we evaluated the following potential confounding factors: body mass index (BMI), hypertension, diabetes mellitus, a history of stroke, Cumulative Illness Rating Scale (CIRS) total score [24], Geriatric Depression Scale (GDS) score, and presence of the APOE ɛ4 allele. CIRS quantifies the overall burden of comorbid illnesses based on 5-point scales for thirteen independent body systems, with higher scores indicating greater disease burden.

Statistical analysis

We compared demographic and clinical characteristics between participants with and without cognitive impairment using Student’s t test for continuous variables and chi-square test for categorical variables. We examined the association between dental status and MMSE score using partial correlation tests incorporating age, sex, education, SES, BMI, smoking, alcohol use, hypertension, diabetes mellitus, stoke, GDS score, CIRS score, and APOE genotype as covariates. We examined the association between dental status and cognitive impairment using binary logistic regression analyses that adjusted for age, sex, years of education, SES, smoking, alcohol consumption, BMI, hypertension, diabetes mellitus, a history of stroke, CIRS score, GDS score and APOE ɛ4 allele as covariates. All statistical analyses were performed using SPSS software (SPSS version 20.0, IBM Corp., Armonk, NY, USA), with two-sided p values below 0.05 considered significant.

RESULTS

The cognitive impairment (CI) group included 53 patients diagnosed with MCI (mean MMSE, 25.51±3.46) and 3 patients diagnosed with dementia. The CI group were older, less educated, exhibited more depressive symptoms, and had more medical comorbidities (as indicated by higher CIRS scores) compared to the normal cognition (NC) group. The CI group had less remaining natural teeth, functional teeth, and functional occlusal units, but were more likely to use dentures compared to the NC group (Table 1 and Fig. 1).

Table 1

Demographic and clinical characteristics of participants

Variable	Normal cognition	Cognitive impairment ^†	p ^‡
	N = 355 (86.4%)	N = 56 (13.6%)
Age (y, mean±SD)	68.2±5.1	71.0±6.7	<0.001
Sex (female, %)	57.5	67.9	0.142
Education (y, mean±SD)	12.9±4.2	10.4±5.1	0.001
Socioeconomic status (low, %)	8.7	14.3	0.188
BMI (kg/m², mean±SD)	23.9±2.6	24.3±2.9	0.297
Smoking (packs per years, mean±SD)	8.8±16.5	8.4±14.1	0.878
Alcohol (units in lifetime, mean±SD)	1.1×10⁴ ± 2.6× 10⁴	1.4×10⁴ ±4.4× 10⁴	0.477
Hypertension (%)	47.9	55.4	0.299
Diabetes mellitus (%)	17.2	26.8	0.085
History of stroke (%)	5.4	10.7	0.131
CIRS (points, mean±SD)	5.4±2.8	6.2±3.1	0.045
GDS (points, mean±SD)	8.6±5.9	11.1±5.7	0.004
APOEɛ4 carriers (%)	20.6	12.5	0.157
Natural teeth (number, mean±SD)	23.3±6.0	20.6±9.1	0.037
Functional teeth (number, mean±SD)	25.7±5.2	22.4±9.3	0.012
Anterior	11.5±2.0	10.3±3.8	0.022
Premolar	7.5±1.5	6.4±2.9	0.007
Molar	6.7±2.0	5.7±2.9	0.014
Functional occlusal unit (number, mean±SD)	13.0±2.2	11.6±4.4	0.024
Anterior	5.9±0.8	5.4±1.8	0.061
Premolar	3.8±0.7	3.3±1.4	0.012
Molar	3.3±1.1	2.9±1.5	0.058
Complete edentulism(%)	1.4	8.9	0.001
Denture use (%)	13.0	30.4	0.001

CIRS, Cumulative Illness Rating Scale; GDS, Geriatric Depression Scale. ^†dementia or mild cognitive impairment. ^‡Student’s t-test for continuous variables and chi-square test for categorical variables.

Fig.1

Distribution of remaining functional teeth.

Table 2 shows negative associations between functional dentition and cognitive impairment. The probability of having cognitive impairment was 4% decreased when the number of total functional teeth was increased, and 10% decreased when the number of total functional occlusal units was increased. However, there was not a significant association between the number of natural teeth with cognitive impairment. When we analyzed the association of the number of functional teeth and the number of functional occlusal units with the odds of cognitive impairment separated by the location of teeth, only the numbers of premolar functional dentition were inversely associated with cognitive impairment. For each 1 increment in premolar functional teeth and each 1 unit increment in premolar functional unit there were 43% and 60% decrease in the odds of cognitive impairment, respectively.

Table 2

Association of the numbers of functional teeth and functional occlusal units with cognitive impairment

Variables	OR (95% CI)	p
Functional teeth
Model 1
Total number of functional teeth	0.955 (0.914–0.997)	0.037
Model 2
Number of anterior functional teeth	1.135 (0.905–1.424)	0.272
Number of premolar functional teeth	0.566 (0.373–0.857)	0.007
Number of molar functional teeth	1.263 (0.956–1.666)	0.101
Functional occlusal units
Model 1
Total number of functional occlusal units	0.900 (0.813–0.996)	0.042
Model 2
Number of anterior functional occlusal units	1.187 (0.810–1.739)	0.380
Number of premolar functional occlusal units	0.399 (0.213–0.748)	0.004
Number of molar functional occlusal units	1.396 (0.934–2.085)	0.104

In all binary logistic regression models, age, sex, years of education, socioeconomic status, amount of smoking, alcohol consumption, body mass index, presence of hypertension, diabetes mellitus, a history of strokes, Cumulative Illness Rating Scale score, Geriatric Depression Scale score, and presence of APOE ɛ4 allele were adjusted as covariates.

The numbers of total functional teeth and functional occlusal units were also found to correlate with MMSE score (r = 0.190, p < 0.001 for functional teeth; r = 0.137, p = 0.006 for functional occlusal units). When the location of teeth and occlusal units were taken into consideration, the correlation remained significant in all locations for the number of functional teeth, but only in anterior and premolar locations for the number of functional occlusal units (Table 3).

Table 3

Correlation of the numbers of functional teeth and functional occlusal units with Mini Mental State Examination score

Variables	r	p
Functional teeth
Total number of functional teeth	0.190	<0.001
Number of anterior functional teeth	0.182	<0.001
Number of premolar functional teeth	0.180	<0.001
Number of molar functional teeth	0.159	0.001
Functional occlusal units
Total number of functional occlusal units	0.137	00.006
Number of anterior functional occlusal units	0.125	0.013
Number of premolar functional occlusal units	0.153	0.002
Number of molar functional occlusal units	0.085	0.092

In all Pearson correlation tests, age, sex, years of education, socioeconomic status, smoking, alcohol consumption, body mass index, presence of hypertension, diabetes mellitus, a history of strokes, Cumulative Illness Rating Scale score, Geriatric Depression Scale score, and presence of APOE ɛ4 allele were included as covariates.

DISCUSSION

In the current study, we found that loss of functional teeth and functional occlusal units (especially in the premolar region) were associated with increased cognitive impairment.

The number of remaining natural teeth was associated with the risk of cognitive impairment [25, 26] or dementia [27 –29]. Although these associate ions may be multifactorial and reciprocal, a decrease in masticatory activity has been proposed as one of the key underlying mechanisms. In animal models, poor mastication induced by molar extraction [30, 31] or prolonged soft diet [32, 33] resulted in cognitive impairment. In humans, several studies reported that lower bite force (as an indication of reduced masticatory function) was related to cognitive impairment [34, 35]. A recent study showed that tooth loss is associated with lower total brain volume and gray-matter volume using MRI [36]. Functional MRI studies in humans have shown that masticatory movement increases cerebral blood flow and blood oxygen supply, and activates various brain areas, such as supplementary motor area, insula, thalamus, and cerebellum. Furthermore, cognitive impairment was reversed when damaged molar teeth were restored by artificial crowns [37], and implant-supported fixed prostheses were shown to modify brain activation [38]. Shin et al. reported that non-rehabilitated tooth loss was associated with increased cognitive impairment while there was no significant association with tooth loss itself [39]. Thus, we suggest that maintaining as many functional teeth by implants, fixed prostheses, or dentures may help in the prevention of cognitive impairment via restoring masticatory stimulation. However, these cross-sectional associations need to be explored in future prospective studies in order to investigate causal direction.

In previous studies on the association between tooth loss and cognition, only the loss of teeth in the posterior region was significantly associated with cognitive impairment [13, 39]. However, in the present study, only the loss of functional teeth or functional occlusal units in the premolar region was associated with the odds of cognitive Impairment. We assume that the number of missing premolars may reflect non-rehabilitated posterior functional teeth. In many cases, loss of the molar teeth does not result in functional teeth loss due to proper restoration, but loss of premolars tends to remain untreated. Although the role may not be as large as molars, premolar teeth may also play a significant role in maintain masticatory function. From the shortened dental arch (SDA) concept, well-preserved premolar teeth are known to ensure sufficient masticatory ability in cooperation with the anterior teeth even in the absence of molars [40, 41].

Recently, Feng et al. reported that a single premolar occlusion elicits a similar pattern of regional brain activation to the areas activated by masticatory movements, including the precentral gyrus, postcentral gyrus, cerebellum, thalamus, insula, supplementary motor area, superior frontal gyrus, inferior frontal gyrus, hippocampus, parahippocampal gyrus, supramarginal gyrus, and cingulate gyrus [42]. We postulate that premolar occlusion, despite playing a minor role in chewing, may be important in regional brain activation and maintenance of cognitive function in humans.

Although the odds for cognitive impairment were higher than 1 in association with the number of molar units, estimates were not statistically significant. Global cognition (as assessed by MMSE) could be normal in MCI patients although one or more specific domains of cognition is mildly impaired. Therefore, the molar units that are associated with the risk of MCI may not be associated with MMSE score which indicates the level of global cognition. In addition, a majority of MCI is amnestic type but MMSE is relatively lack of delayed recall items (10% of the total MMSE score).

Our current study has a number of unique strengths. First, our sample population was a randomly sampled community-dwelling elderly cohort, which makes the results highly representative of the general older population. Second, we applied comprehensive neurocognitive function tests spanning all cognitive domains, with the clinical diagnoses made by geriatric research psychiatrists. Therefore, our study has obtained highly reliable data on each participant’s cognitive status, as compared to other studies which used simple cognitive test such as the MMSE. Third, oral examination was conducted by trained dentists, ensuring that dental parameters were measured appropriately. Fourth, we collected extensive information on possible confounding factors, including the APOE genotype. This study also has several limitations. First, the design of our investigation is cross-sectional, which limits attributions about the direction of causality between the number of functional teeth and cognitive impairment. A reversed causality cannot be excluded, meaning that cognitive impairment may have caused the loss of functional teeth due to poorer oral hygiene. Second, this analysis did not include data on markers of periodontal diseases or systemic inflammations, which have been suggested as potential factors in the pathophysiology of Alzheimer’s disease. Third, we did not directly measure masticatory force or perform functional brain imaging as part of this study. Fourth, the correlation coefficients of the numbers of functional teeth and functional occlusal units with MMSE score were very small even in the univariate analyses. Multivariate analyses on the effects of functional teeth and occlusal units on cognitive function by their location warrant further well-powered studies with a larger sample.

In conclusion, loss of functional teeth and functional occlusal units (especially in the premolar region) were associated with increased cognitive impairment. Future studies with prospective design are needed to explore the causal relationship between functional teeth and cognitive impairment.

Footnotes

ACKNOWLEDGMENTS

This work was funded by a grant from the Korean Health Technology Research and Development Project of the Ministry of Health, Welfare, and Family Affairs, Republic of Korea (Grant No. A092077), and from Research of Korea Centers for Disease Control and Prevention (2019-ER6201-00).

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

References

, Fillenbaum

, Plassman

, Guo

(2016) Association between oral health and cognitive status: A systematic review. J Am Geriatr Soc 64, 739–751.

, Han

D-H

, Han

K-T

, Liu

, Ukken

, Chang

, Dounis

, Yoo

(2018) Association between residual teeth number in later life and incidence of dementia: A systematic review and meta-analysis. BMC Geriatr 18, 48.

Cerutti-Kopplin

, Feine

, Padilha

, De Souza

, Ahmadi

, Rompré

, Booij

, Emami

(2016) Tooth loss increases the risk of diminished cognitive function: A systematic review and meta-analysis. JDR Clin Trans Res 1, 10–19.

Miyamoto

, Yoshida

, Tsuboi

, Iizuka

(2005) Rehabilitation with dental prosthesis can increase cerebral regional blood volume. Clin Oral Implants Res 16, 723–727.

Narita

, Kamiya

, Yamamura

, Kawasaki

, Matsumoto

, Tanaka

(2009) Chewing-related prefrontal cortex activation while wearing partial denture prosthesis: Pilot study. J Prosthodont Res 53, 126–135.

Weijenberg

RAF

, Delwel

, Ho

, van der Maarel-Wierink

, Lobbezoo

(2019) Mind your teeth-The relationship between mastication and cognition. Gerodontology 36, 2–7.

Weijenberg

, Scherder

, Lobbezoo

(2011) Mastication for the mind—the relationship between mastication and cognition in ageing and dementia. Neurosci Biobehav Rev 35, 483–497.

Hirano

, Obata

, Kashikura

, Nonaka

, Tachibana

, Ikehira

, Onozuka

(2008) Effects of chewing in working memory processing. Neurosci Lett 436, 189–192.

Onozuka

, Fujita

, Watanabe

, Hirano

, Niwa

, Nishiyama

, Saito

(2003) Age-related changes in brain regional activity during chewing: A functional magnetic resonance imaging study. J Dent Res 82, 657–660.

10.

Lexomboon

, Trulsson

, Wardh

, Parker

(2012) Chewing ability and tooth loss: Association with cognitive impairment in an elderly population study. J Am Geriatr Soc 60, 1951–1956.

11.

Elsig

, Schimmel

, Duvernay

, Giannelli

, Graf

, Carlier

, Herrmann

, Michel

, Gold

, Zekry

, Muller

(2015) Tooth loss, chewing efficiency and cognitive impairment in geriatric patients. Gerodontology 32, 149–156.

12.

Kang

, Lee

, Kwon

, Kim

(2015) Short-term improvement of masticatory function after implant restoration. J Periodontal Implant Sci 45, 205–209.

13.

Takeuchi

, Izumi

, Furuta

, Takeshita

, Shibata

, Kageyama

, Ganaha

, Yamashita

(2015) Posterior teeth occlusion associated with cognitive function in nursing home older residents: A cross-sectional observational study. PloS One 10, e0141737.

14.

Cardoso

, Diniz-Freitas

, Vázquez

, Cerqueiro

, Diz

, Limeres

(2019) Relationship between functional masticatory units and cognitive impairment in elderly persons. J Oral Rehabil 46, 417–423.

15.

Kim

, Park

, Lee

, Jhoo

, Kim

B-J

, Kim

J-L

, Kim

, Youn

, Ryu

S-H

, Lee

(2013) Overview of the Korean longitudinal study on cognitive aging and dementia. Alzheimers Dement 9, P626–P627.

16.

American Psychiatric Association (2000) Task Force on DSM-IV. Diagnostic and statistical manual of mental disorders: DSM-IV-TR. American Psychiatric Association, Washington, DC.

17.

Lee

, Lee

, Kim

, Jhoo

, Kim

, Lee

, Kim

, Han

, Woo

(2002) Development of the Korean Version of the Consortium to Establish a Registry for Alzheimer’s Disease Assessment Packet (CERAD-K) clinical and neuropsychological assessment batteries. J Gerontol B Psychol Sci Soc Sci 57, P47–P53.

18.

Yoo

S-W

, Kim

Y-S

, Noh

J-S

, Oh

K-S

, Kim

C-H

, NamKoong

, Chae

J-H

, Lee

G-C

, Jeon

S-I

, Min

K-J

(2006) Validity of Korean version of the mini-international neuropsychiatric interview. Anxiety Mood 2, 50–55.

19.

Kim

, Huh

, Choe

, Jeong

, Park

, Lee

, Jhoo

, Lee

, Woo

(2010) Korean version of frontal assessment battery: Psychometric properties and normative data. Dement Geriatr Cogn Disord 29, 363–370.

20.

Wechsler

(1987) WMS-R: Wechsler memory scale-revised, Psychological Corporation.

21.

Lee

, Lee

, Kim

, Jhoo

, Kim

, Yoon

, Woo

, Ha

, Woo

(2004) A normative study of the CERAD neuropsychological assessment battery in the Korean elderly. J Int Neuropsychol Soc 10, 72–81.

22.

Han

, Kim

, Kwak

, Kim

, Moon

, Park

(2018) Overview of the Korean longitudinal study on cognitive aging and dementia. Psychiatry Investig 15, 767.

23.

Winblad

, Palmer

, Kivipelto

, Jelic

, Fratiglioni

, Wahlund

, Nordberg

, Bäckman

, Albert

, Almkvist

(2004) Mild cognitive impairment–beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment. J Intern Med 256, 240–246.

24.

Miller

, Paradis

, Houck

, Mazumdar

, Stack

, Rifai

, Mulsant

, Reynolds

(1992) Rating chronic medical illness burden in geropsychiatric practice and research: Application of the Cumulative Illness Rating Scale. Psychiatr Res 41, 237–248.

25.

Okamoto

, Morikawa

, Okamoto

, Habu

, Iwamoto

, Tomioka

, Saeki

, Yanagi

, Amano

, Kurumatani

(2010) Relationship of tooth loss to mild memory impairment and cognitive impairment: Findings from the fujiwara-kyo study. Behav Brain Funct 6, 77.

26.

Kaye

, Valencia

, Baba

, Spiro

, Dietrich

, Garcia

(2010) Tooth loss and periodontal disease predict poor cognitive function in older men. J Am Geriatr Soc 58, 713–718.

27.

Kim

, Stewart

, Prince

, Kim

, Yang

, Shin

, Yoon

(2007) Dental health, nutritional status and recent-onset dementia in a Korean community population. Int J Geriatr Psychiatry 22, 850–855.

28.

Paganini-Hill

, White

, Atchison

(2012) Dentition, dental health habits, and dementia: The Leisure World Cohort Study. J Am Geriatr Soc 60, 1556–1563.

29.

Stein

, Desrosiers

, Donegan

, Yepes

, Kryscio

(2007) Tooth loss, dementia and neuropathology in the Nun study. J Am Dent Assoc 138, 1314–1322.

30.

Onozuka

, Watanabe

, Mirbod

, Ozono

, Nishiyama

, Karasawa

, Nagatsu

(1999) Reduced mastication stimulates impairment of spatial memory and degeneration of hippocampal neurons in aged SAMP8 mice. Brain Res 826, 148–153.

31.

Kato

, Usami

, Noda

, Hasegawa

, Ueda

, Nabeshima

(1997) The effect of the loss of molar teeth on spatial memory and acetylcholine release from the parietal cortex in aged rats. Behav Brain Res 83, 239–242.

32.

Yamamoto

, Hirayama

(2001) Effects of soft-diet feeding on synaptic density in the hippocampus and parietal cortex of senescence-accelerated mice. Brain Res 902, 255–263.

33.

Kushida

, Kimoto

, Hori

, Toyoda

, Karasawa

, Yamamoto

, Kojo

, Onozuka

(2008) Soft-diet feeding decreases dopamine release and impairs aversion learning in Alzheimer model rats. Neurosci Lett 439, 208–211.

34.

Miura

, Yamasaki

, Kariyasu

, Miura

, Sumi

(2003) Relationship between cognitive function and mastication in elderly females. J Oral Rehabil 30, 808–811.

35.

Scherder

, Posthuma

, Bakker

, Vuijk

, Lobbezoo

(2008) Functional status of masticatory system, executive function and episodic memory in older persons. J Oral Rehabil 35, 324–336.

36.

Dintica

, Rizzuto

, Marseglia

, Kalpouzos

, Welmer

A-K

, Wårdh

, Bäckman

, Xu

(2018) Tooth loss is associated with accelerated cognitive decline and volumetric brain differences: A population-based study. Neurobiol Aging 67, 23–30.

37.

Watanabe

, Ozono

, Nishiyama

, Saito

, Tonosaki

, Fujita

, Onozuka

(2002) The molarless condition in aged SAMP8 mice attenuates hippocampal Fos induction linked to water maze performance. Behav Brain Res 128, 19–25.

38.

Yan

, Ye

, Zhen

, Ke

, Gang

(2008) Neuroplasticity of edentulous patients with implant-supported full dentures. Eur J Oral Sci 116, 387–393.

39.

Shin

, Shin

, Karna

, Kim

(2019) Rehabilitation of lost-teeth related to maintenance of cognitive function. Oral Dis 25, 290–299.

40.

Käyser

(1981) Shortened dental arches and oral function. J Oral Rehabil 8, 457–462.

41.

Witter

, Van Elteren

, Käyser

, Van Rossum

(1990) Oral comfort in shortened dental arches. J Oral Rehabil 17, 137–143.

42.

Feng

C-Z

, Li

J-F

, Hu

, Jiang

, Wang

Y-Y

, Liu

H-C

(2019) Brain activation patterns during unilateral premolar occlusion. Cranio 37, 53–59.