PERIODONTITIS AND DEMENTIA A SYSTEMATIC REVIEW · Periodontitis is the 6th most common chronic disease affecting about one third of world’s population. It is mostly prevalent in

PERIODONTITIS AND DEMENTIA – A SYSTEMATIC REVIEW

Sam Asher

Master thesis

Public Health

School of Medicine

Faculty of Health Sciences

University of Eastern Finland

December 2018

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UNIVERSITY OF EASTERN FINLAND, Faculty of Health Sciences,

Institute of Public Health and Clinical Nutrition, Public Health.

ASHER S.: Periodontitis and Dementia - a systemic review.

Master's thesis, 96 Pages.

Instructors: Professor Tomi-Pekka Tuomainen, Adjunct Professor Alina Solomon and Ruth

Stephen.

December 2018.

Keywords: Dementia, Alzheimer’s disease, cognitive impairment, memory impairment, cognitive

deterioration, periodontitis, tooth loss.

ABSTRACT

Several studies indicate a possible association between periodontitis and dementia. Additionally, the

available scientific literature also suggests that periodontitis may be related to cognitive impairment.

This review aimed to systematically assess and evaluate the scientific literature on the impact of

periodontitis on the risk of dementia and cognitive impairment.

The online scientific databases (PubMed and Scopus) were searched for original English language,

longitudinal studies that assessed the role of periodontitis in determining the risk of dementia and

cognitive impairment. In total 10 studies complied with the inclusion criteria, with 5 concerning

dementia as the outcome and 5 cognitive impairment. The studies included in this review were also

assessed for the quality of evidence in four major and one minor domain.

Four studies reported association between periodontitis and dementia. Evidence supporting the possible

role of periodontitis in elevating the risk of dementia was of low to moderate quality. In the case of

cognitive impairment, although there seemed to be higher likelihood of cognitive impairment with poor

periodontal status, results were less straightforward. All five studies with cognitive impairment as the

outcome were of low quality.

This review suggests that periodontitis is likely to increase the risk of dementia. However, the amount

and quality of evidence currently available is insufficient and of moderate to low quality to draw any

firm conclusions. Further studies with better study designs, longer study duration and more

comprehensive assessment of periodontitis and cognitive status are needed to elucidate the association

of periodontal health with cognition and dementia.

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ABBREVIATIONS

Aβ: Amyloid beta

ABL: Alveolar bone loss/loss of alveolar bone

AD: Alzheimer’s disease

APOE: Apolipoprotein E

APP: Amyloid precursor protein

ARIC: The atherosclerosis risk in communities study

BBB: Blood brain barrier

BOP: Bleeding on probing

CAL: Clinical attachment loss/loss of clinical attachment

CPI: Community periodontal index

CPITN: Community periodontal index for treatment needs

CRP: Serum C-reactive protein

CSF: Cerebrospinal fluid

CVDs: Cardiovascular diseases

DLB: Dementia with Lewy bodies

DMFT: Decayed, missing, and filled teeth index

DSM: Diagnostic and statistical manual of mental disorders

DSS: Digit symbol substitution

DWR: Delayed word recall

FINGER: Finnish geriatric intervention study to prevent cognitive impairment and disability

GBI: Gingival bleeding index

GCF: Gingival crevicular fluid

GDS: Geriatric depression scale

HEPESE: Hispanic established populations for epidemiologic studies of the elderly

ICD: International statistical classification of diseases and related health problems

IL-6: Interleukin-6

LHID: Longitudinal health insurance database

LPS: Lipopolysaccharide

MAPT: Multi-domain Alzheimer preventive trial

MCI: Mild cognitive impairment or Cognitive impairment

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MMI: Mild memory impairment

MMSE: Mini mental state examination

MRI: Magnetic resonance imaging

NHI: National health insurance - Taiwan

NHIRD: National health insurance research database of Taiwan

NSAIDs: Non-steroidal anti-inflammatory drugs

PAQUIDENT: Paquid dental study - France

PCI: Plaque control index

PDI: Periodontal disease index

PPDs: Periodontal pocket depths

PreDIVA: Prevention of dementia by intensive vascular care

PSP: Progressive supra-nuclear palsy

ROS: Reactive oxygen species

TBI: Traumatic brain injury

TNF- α: Tumor necrosis factor alpha

VaD: Vascular dementia

VCI: Vascular cognitive impairment

WF: Word fluency test.

WHO: World health organization

WMS-R: Wechsler memory scale – revised

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TABLE OF CONTENTS

1. INTRODUCTION ................................................................................................................................ 8

2. LITERATURE REVIEW ..................................................................................................................... 9

2.1 PERIODONTITIS ............................................................................................................................... 9

2.1.1 Definition ...................................................................................................................................... 9

2.1.2 Prevalence ................................................................................................................................... 10

2.1.3 Types of Periodontitis ................................................................................................................. 10

2.1.4 Pathophysiology of Periodontitis ................................................................................................ 11

2.1.5 Diagnosis of Periodontitis ........................................................................................................... 16

2.1.6 Treatment of Periodontitis .......................................................................................................... 17

2.1.7 Risk factors for Periodontitis ...................................................................................................... 18

2.2 DEMENTIA AND COGNITIVE IMPAIRMENT ........................................................................... 22

2.2.1 Dementia ..................................................................................................................................... 22

2.2.2 Cognitive impairment ................................................................................................................. 27

2.2.3 Diagnostic criteria for Dementia and Cognitive impairment ...................................................... 28

2.2.4 Risk factors for Dementia and Cognitive impairment ................................................................ 31

2.2.5 Possible prevention strategies for Dementia and Cognitive impairment .................................... 39

3 AIMS AND METHODS ...................................................................................................................... 41

3.1 AIMS ................................................................................................................................................. 41

3.1.1 General Objective ....................................................................................................................... 41

3.1.2 Specific Objectives ..................................................................................................................... 42

3.1.3 Novelty compared to previous reviews ....................................................................................... 42

3.2 METHODOLOY .............................................................................................................................. 42

3.2.1 Inclusion criteria ......................................................................................................................... 43

3.2.2 Exclusion criteria ........................................................................................................................ 43

3.3.3 Quality assessment ...................................................................................................................... 44

4 RESULTS ............................................................................................................................................ 47

4.1 STUDIES WITH DEMENTIA AS THE OUTCOME ..................................................................... 49

4.1.1 Designs and settings .................................................................................................................... 49

4.1.2 Study population and duration .................................................................................................... 49

4.1.3 Periodontitis assessment ............................................................................................................. 50

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4.1.4 Dementia assessment .................................................................................................................. 50

4.1.5 Periodontitis-Dementia association............................................................................................. 50

4.1.6 Quality assessment of studies assessing Dementia ..................................................................... 56

4.2 STUDIES WITH COGNITIVE IMPAIRMENT AS THE OUTCOME ......................................... 59

4.2.1 Design and settings ..................................................................................................................... 59

4.2.2 Study population and study duration .......................................................................................... 59

4.2.3 Periodontitis assessment ............................................................................................................. 60

4.2.4 Cognitive impairment assessment ............................................................................................... 60

4.2.5 Periodontitis-Cognitive impairment association ......................................................................... 61

4.2.6 Quality assessment of studies assessing Cognitive impairment ................................................. 68

5 DISCUSSION ..................................................................................................................................... 71

5.1 STUDIES ON PERIODONTITIS AND DEMENTIA ..................................................................... 71

5.1.1 Overall findings........................................................................................................................... 71

5.1.2 Measures of Periodontitis............................................................................................................ 71

5.1.3 Association between Periodontitis and Dementia based on periodontal pocket depths ............. 72

5.1.4 Association between Periodontitis and Dementia based on tooth loss ....................................... 72

5.1.5 Comparison between results based on different measures of Periodontal health ....................... 72

5.1.6 Severity of Periodontitis.............................................................................................................. 73

5.2 STUDIES ON PERIODONTITIS AND COGNITIVE IMPAIRMENT .......................................... 74

5.2.1 Overall findings........................................................................................................................... 74

5.2.2 Measures of Periodontitis............................................................................................................ 74

5.2.3 Association between Periodontitis and Cognitive impairment based on periodontal pocket

depths .............................................................................................................................................. 75

5.2.4 Association between Periodontitis and Cognitive impairment based on tooth loss ................... 75

5.2.5 Variability in Cognitive assessment ............................................................................................ 76

5.3 MECHANISMS ................................................................................................................................ 76

5.4 STRENGTHS AND LIMITATIONS .............................................................................................. 79

5.5 CONCLUSION AND FUTURE DIRECTIONS .............................................................................. 80

6. REFERENCES.................................................................................................................................... 82

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LIST OF FIGURES AND TABLES

Figure 1: Search Results (Prisma flow diagram) ................................................................................... 48

Table 1: Community periodontal index (WHO 2005) ............................................................................ 17

Table 3: Risk and protective factors for Dementia and Cognitive impairment ...................................... 38

Table 4: MEDLINE search strategy PubMed July 2017 (run on date 18.07.2017) ................................ 43

Table 5: Studies assessing the association between Periodontitis and Dementia ................................... 52

Table 6: Quality assessment of the studies assessing Dementia ............................................................. 57

Table 7: Studies assessing the association between Periodontitis and Cognitive impairment ............... 63

Table 8: Quality assessment of studies assessing cognitive impairment ................................................ 69

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1 INTRODUCTION

Periodontitis is the inflammation of tooth supporting tissues. In severe cases, deterioration of

periodontal tissues culminates into tooth loss (Silva et al. 2017). Chronic periodontitis is the most

common form of periodontitis affecting about one third of world population (Branco et al. 2015). It

arises as an inflammatory response mounted against sub-gingival plaque bacteria. Although it is

primarily an infectious pathology, dysregulated or hyperactive immune response plays a crucial role in

its development and progression (Suresh et al. 2017). The impact of periodontitis spreads beyond oral

health and is proposed to affect systemic health. It is regarded as an important determinant for systemic

conditions like diabetes, cardiovascular diseases and adverse pregnancy outcomes (Pitiphat et al. 2008,

Macedo Paizan & Vilela-Martin 2014, Lönn J et al. 2018).

Dementia is a syndrome characterized by progressive deterioration of cognitive function and functional

incapacitation. It is mainly prevalent in elderly individuals, with 5-7% of 60 years or older individuals

affected by it worldwide (LoGiudice & Watson 2014). Age and genetic predisposition are the major

risk factors for dementia (Kalantarian et al 2013). Furthermore, number of lifestyle and environmental

factors are proposed to be important determinants of dementia (Ylilauri et al. 2017). Dementia is

caused by a number of pathologies, with Alzheimer’s disease (AD) being the most common cause,

followed by vascular cognitive impairment (VCI) and dementia with Lewy bodies (DLB) (Tzeng et al.

2016).

Dementia pathology (mainly AD) may occur years before the first symptoms appear. Studies have

highlighted the role of periodontitis in the progression of dementia and cognitive deterioration (Dintica

et al. 2018, Gusman et al. 2018). However, more research is needed to establish its role as a risk factor

for dementia. A few studies have indicated that periodontitis increases the risk of dementia and

cognitive decline (Oh et al. 2018). Multiple mechanisms have been proposed, such as the inflammatory

model (Gallart-Palau et al. 2017). Tooth loss, a direct consequence of periodontitis, also independently

increases the risk of dementia and cognitive impairment (Nilsson et al. 2013).

With a significant rise in elderly population, prevalence of dementia alone is projected to surpass 100

million by 2050 (Koch & Jensen 2016). It is hence important to identify risk factors which can

contribute towards understanding the multifactorial etiology of the disease. In view of these notions,

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the role of periodontitis as a modifiable risk factor for dementia and cognitive impairment needs to be

investigated.

2 LITERATURE REVIEW

2.1 PERIODONTITIS

2.1.1 Definition

Periodontitis is the inflammation of tooth supporting tissues that results in deterioration of periodontal

ligament and resorption of alveolar bone. It is characterized by gingival inflammation, formation of

periodontal pockets, clinical attachment loss and resorption of alveolar bone. Periodontal pockets form

as the widening of gingival sulcus due to gingival inflammation. Whereas clinical attachment loss

(CAL) is the term describing the apical migration of junctional epithelium, that forms the base of the

healthy gingival sulcus. As the inflammation spreads to the alveolar bone it causes its resorption that

may eventually culminate into tooth loss (Newnan et al. 2012).

Chronic periodontitis is the most common form of periodontitis that arises in response to sub gingival

plaque bacteria (Armitage 1999). Several plaque bacteria, predominantly gram-negative species such as

Porphyromonas gingivalis are associated with periodontitis (Hajishengallis 2012). Although

periodontitis is triggered by plaque bacteria, host immune response prompted against bacterial stimulus

plays a predominant role in determining the extent and severity of periodontal tissue breakdown

(Kinane & Marshall 2001).

Several factors such as poor oral hygiene, diabetes, medication and smoking significantly increases the

risk of periodontitis. Periodontitis is a slowly progressing chronic pathology, however, in the presence

of multiple predisposing factors, periodontal tissue breakdown undergoes frequent acute exacerbations

(Genco & Borgnakke 2013).

The clinical consequences of periodontitis spreads beyond its effects on oral cavity. In addition to

causing difficulty in mastication and speech, periodontitis adversely affects psychosocial wellbeing and

overall quality of life. Furthermore, it is suggested to be a risk factor for multiple systemic diseases

https://www.ncbi.nlm.nih.gov/pubmed/?term=Hajishengallis%20G%5BAuthor%5D&cauthor=true&cauthor_uid=22941505

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such as diabetes, cardiovascular diseases and adverse pregnancy outcomes (Gross et al. 2017). Chronic

periodontitis serves as a constant trigger for the expression of inflammatory mediators and is proposed

to increase the risk of many systemic diseases such as cardiovascular diseases (CVDs) and diabetes.

Furthermore, increasing evidence also suggest that periodontitis facilitate in the development of

neurodegenerative disorders such as dementia (Kamer et al. 2012, Kamer et al. 2015, Nilsson et al.

2017).

2.1.2 Prevalence

Periodontitis is the 6th most common chronic disease affecting about one third of world’s population. It

is mostly prevalent in adults (35 years or older) but is also observed in younger individuals (Silva et al.

2017). The prevalence of periodontitis has been reported to lie between 20-50% worldwide, however

most estimates are believed to underestimate the absolute numbers, with prevalence among the middle-

aged individuals (35-44 years old) alone estimated to be between 15-20% globally (WHO 2012). About

10-15% of world’s population is affected by severe periodontitis that often culminates into tooth loss if

left untreated (Ballini et al. 2015).

The prevalence of periodontitis increases with age. Severe periodontitis, in particular, is relatively more

prevalent among elderly individuals. Age-related factors such as increased prevalence of systemic

diseases, decreased effectiveness and frequency of oral health practices and propensity to have general

systemic inflammatory state is suggested to contribute to increased susceptibility of periodontitis

among the elderly. The prevalence of periodontitis has been on a rise, attributed to increase in

population and increased proportion of elderly. Furthermore, people are retaining more teeth well into

their old age that could explain for high prevalence of periodontitis (Kassebaum et al. 2017).

2.1.3 Types of Periodontitis

2.1.3.1 General classification of Periodontitis

Periodontitis is mainly classified into aggressive and chronic types, with each type further stratified

into localized and generalized subtypes. In addition to aggressive and chronic periodontitis other less

common types of periodontal diseases include periodontitis as a manifestation of systemic diseases,

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necrotizing periodontal diseases, periodontitis associated with endodontic lesions and periodontal

disease as part of developmental or acquired deformity diseases (Armitage 1999).

Chronic periodontitis initiates as the inflammation of gingiva triggered by plaque bacteria, giving rise

to gingivitis. If left untreated or uncontained by the immune response mounted to deal with the

bacterial challenge, gingival inflammation spreads to periodontal ligament and alveolar bone resulting

in progression of gingivitis into periodontitis (Armitage 1999).

2.1.3.2 Classification of Chronic Periodontitis

Chronic periodontitis is divided into localized and generalized types which demonstrates the extent of

dentition affected by periodontal disease. This classification of chronic periodontitis is based on the

percentage of sites or teeth that exhibits clinical attachment loss and resorption of alveolar bone.

Diagnosis of localized periodontitis is assigned when less than 30% of teeth or sites displays clinical

attachment loss and alveolar bone resorption. Whereas general periodontitis indicates the involvement

of more than 30% of teeth or sites (Wiebe & Putnins 2000).

2.1.3.3 Mild, Moderate and Severe Periodontitis

Furthermore, periodontitis is also categorized as “mild periodontitis”, “moderate periodontitis”

and “severe or advanced periodontitis”, depicting severity of periodontitis. The severity of periodontitis

is ascertained by measuring amount of clinical attachment loss. Mild periodontitis presents with 1-2

mm of clinical attachment loss, while moderate periodontitis infers 3-4 mm of attachment loss. Clinical

attachment loss of 5 mm or beyond is referred to as severe periodontitis (Wiebe & Putnins 2000).

2.1.4 Pathophysiology of Periodontitis

2.1.4.1 Characteristics of Periodontitis

The classical features of periodontitis comprise of gingival inflammation, periodontal pocket

formation, clinical attachment loss and resorption of alveolar bone. Relatively less frequently

encountered features include gingival recession and tooth mobility, observed in severe periodontitis.

Gingival inflammation incurs a number of changes in the healthy gingiva including gingival swelling,

loss of gingival stippling and changes in color and contour of gingiva (Loesche & Grossman 2001).

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On the spread of gingival inflammation, gingival sulcus increases in depth, eventually leading to

striping away of gingiva from the tooth surface. This marks the formation of periodontal pockets and

transition of gingivitis into periodontitis. Degree of periodontal pocket depth may be indicative of

severity of periodontal disease. However, such should be implied with caution as it underestimates the

disease in case of gingival recession where periodontal pockets remain shallow and overestimates in

cases where gingiva is extensively swollen (Loesche & Grossman 2001).

Clinical attachment loss assesses position of junctional epithelium against the tooth and is a measure of

extent of apical migration of junctional epithelium. It is a superior indicator of periodontal tissue

destruction in comparison to periodontal pocket depth and accounts for gingival changes such as

gingival recession or gingival overgrowth (Armitage & Cullinan 2010). Alveolar bone resorption is

another classical feature of periodontitis, which in severe cases is clinically manifested as loosening of

teeth. It may be clinically assessed during periodontal probing, however in majority of instances

radiographic assessment is undertaken for adequately determining the extent and pattern of bone loss

(Cochran 2008).

2.1.4.2 Etiology of Periodontitis

Dental Plaque

Periodontitis is an infectious disease caused by pathogenic bacteria in mature dental plaque. The

microbial biofilm called ‘dental plaque’ is the tenacious admixture of oral bacteria in a complex

extracellular matrix that forms on tooth surface. Hundreds of bacteria have been isolated from dental

plaque, majority of which are commensal in nature, having no pathological significance (Paster et al.

2001). However, multiple bacterial species predominantly the gram-negative types such as

Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola and Prevotella intermedia are

implicated as periodontal pathogens responsible for triggering the host immune response leading to the

development and establishment of periodontitis (Socransky et al. 1998). The extracellular component

of plaque is mainly derived from saliva and comprises of various organic and inorganic salivary

components (Peterson et al. 2014).

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Dental plaque is classified as supra-gingival and sub-gingival plaque according to its position relative

to gingival margin. Supra-gingival plaque is part of dental plaque lying above the gingival margin

whereas part of dental plaque sheltered within gingival sulcus is referred to as sub-gingival plaque. It is

the sub-gingival plaque that holds key importance in pathogenesis of periodontitis. The overall

composition and pattern of sub-gingival plaque vary little from supra-gingival plaque. However, it is

more resolute, achieves maturation at a relatively faster pace and harbors more potent and greater

proportion of periodontal pathogens such as spirochetes. The formation and maturation of plaque is

driven by inter-microbial interaction, facilitated by presence of local and systemic factors. Furthermore,

host immune system is also suggested to play a significant part in establishing and sustaining the

dysbiosis that triggers the pathological process leading to periodontitis (Loesche & Grossman 2001).

Formation of plaque starts with the development of a layer of organic matrix called acquired pellicle

upon which successively various bacterial species colonize. The aerobic non-pathogenic bacteria are

the first to populate followed by virulent gram-negative anaerobic types (Darveau et al. 1997). The host

inflammatory response triggered by sub-gingival plaque clinically manifests as gingival inflammation.

The gingival inflammation leads to increase in size of gingival sulcus that allows further accumulation

of sub-gingival plaque. This subsequently produces an immune response of even larger magnitude

leading to progression of gingivitis towards periodontitis (Cekici at al. 2014).

Host immune response

The immune response in periodontitis is complex and involves both the innate and acquired segments

of immune system. However, there is no clear delineation between the effects of innate and acquired

immune system with both working in cooperation and overlapping the effects of each other. Although

periodontitis is triggered by plaque bacteria and can essentially be categorized as an infectious disease,

it is the host immune response that plays the chief role in the pathological process leading to

destruction of periodontal tissues (Wilensky et al. 2015).

This is supported by the finding that poor oral hygiene which is indicative of extensive accumulation of

plaque dominated by gram negative bacteria, does not always coincides with the development of

periodontitis (Meyle & Chapple 2015). On the other hand, susceptible individuals can develop severe

periodontitis even in the presence of plaque scarcely populated by periodontal pathogens, although the

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classical periodontal pathogens are demonstrated in such individuals as well. Another important finding

advocating the more significant part of host immune system in periodontitis is the fact that although

several periodontal pathogens have been linked with periodontitis in general or with specific types of

periodontitis. No single pathogen has yet been found to be the sufficient cause of periodontitis

(Hajishengallis 2015).

It is proposed that in susceptible individuals, the host immune system is dysregulated that leads to a

hyperactive immune response against plaque bacteria. This hyperactive immune response leads to

extensive periodontal tissue breakdown, even if the microbial challenge is minimal (Khan et al. 2015).

The hallmark features of periodontitis, namely, periodontal pocket formation, clinical attachment loss

and resorption of alveolar bone are brought about by cytokines released by immune cells to counteract

microbial challenge (Shah et al. 2017). Furthermore, established risk factors for periodontitis such as

systemic comorbidities increase the risk of periodontitis by contributing to dysregulation of host

immune response (Zhu & Nikolajczyk 2014).

The inflammatory response in periodontitis is initially mounted as a physiological response to contain

the bacterial stimulus, which converts into a pathological chronic inflammation if the inflammation

fails to clear the constant stream of bacterial stimulation. After the recognition of bacteria or bacterial

products by innate immune system, chemokines and cytokines are expressed to recruit phagocytes.

Furthermore, the complement system is also triggered to contain the bacterial challenge (Cekici et al.

2014).

As the innate immune system is overwhelmed by the bacterial challenge it causes the activation of

acquired segment of immune system, bringing in other types of immune cells to counteract the

periodontal infection. The acquired immune system works side by side along with the already

functional innate immune system. In majority of the cases, there establishes an equilibrium between

constant bacterial stimulus and continuous counteractive immune response leading to establishment of

mild or moderate chronic periodontitis. However, in susceptible subjects the immune response is

dysregulated that leads to extensive destruction of periodontal tissues, which clinically manifests as

severe periodontitis (Cekici et al. 2014).

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2.1.4.3 Development and Progression of Periodontitis

Periodontitis develops in a stepwise manner, progressing in severity as the host inflammatory response

becomes more potent. Initially only the gingiva is involved, clinically apparent as gingivitis. But as the

inflammation spreads it involves periodontal ligament and alveolar bone in pathological process,

resulting in eventual loss of clinical attachment and resorption of alveolar bone thus producing

periodontitis (Robinson 1995).

The initial lesion of periodontitis develops within 2 to 4 days of plaque accumulation, which is

clinically indistinguishable from healthy gingiva. The only discernible changes are at the histological

level, brought about by resident leukocytes and endothelial cells. There is migration of neutrophils to

the site of inflammation in response to cytokines released by junctional epithelium, accompanied with

increased flow of gingival crevicular fluid (GCF). On progression of initial lesion to early lesion,

gingival inflammation becomes clinically evident and is accompanied by further increase in GCF flow.

Histologically, there is increased proportion of neutrophils at the affected site, along with migration of

other types of leukocytes such as macrophages (Cekici et al. 2014).

If the microbial challenge is not cleared and further exacerbation of inflammatory response occurs,

early lesion progresses into established lesion, which presents clinically as chronic gingivitis of

moderate to severe intensity. At this stage gingival inflammation is well pronounced, with proliferation

of epithelium into underlying connective tissue. The cell infiltrate is now predominantly populated by

lymphocytes and plasma cells, with junctional epithelium beginning to detach from tooth surface at this

point (Cekici et al. 2014).

Any further damage to periodontium marks the formation of advanced lesion and transition of

gingivitis into periodontitis. The inflammatory response reaches its peak and leads to apical migration

of junctional epithelium clinically manifested as clinical attachment loss. Furthermore, the

inflammatory process involves tooth supporting alveolar bone leading to its resorption. The GFC is

predominantly concentrated by neutrophils, while underlying connective tissues are populated by

plasma cells (Cekici et al. 2014).

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2.1.5 Diagnosis of Periodontitis

Diagnosis of periodontitis is based on clinical findings which includes periodontal pocket formation

(with or without gingival recession), bleeding on probing (BOP), clinical attachment loss and alveolar

bone loss. These clinical findings are calibrated to determine the extent of periodontal damage and are

usually supplemented with radiographic assessment which is valuable in determining the extent and

severity of periodontitis, as well as in delineating the pattern and extent of alveolar bone loss (Highfield

2009). These measures form the basis of diagnostic criteria highlighted in standard diagnostic manuals

such as International Statistical Classification of Diseases and Related Health Problems (ICD) (WHO

2016).

Clinical features are enough to ascertain the presence of periodontitis, but to conclusively highlight a

certain case, as of chronic periodontitis, clinical findings are assessed in context of age, presence of

sub-gingival plaque, local risk factors and pace of disease progression, along with medical and dental

history (Highfield 2009).

A number of indices of periodontal health such as Community Periodontal Index for Treatment Needs

(CPITN), Periodontal Disease Index (PDI) and Community Periodontal Index (CPI) among others are

used for screening and diagnosing periodontitis both at the clinical and epidemiological level (Beltrán-

Aguilar et al. 2012). Although different periodontal indices assess periodontal health based on above

mentioned measures of periodontitis. Not all measures are employed by each index and there exists

variation in the number and combination of measures used (Buenco et al. 2015). Most of these indices

do not only provide estimation of periodontal health but also provide an approximate estimate of

treatment that is needed to be administered (Dhingra & Vandana 2011).

One of the most commonly used periodontal index is community periodontal index (CPI) which is a

modified version of community periodontal index of treatment needs. CPI assesses the periodontal

status through periodontal probing, clinical attachment loss, gingival bleeding and presence of calculus

(Table 1). Instead of screening the entire dentition CPI assesses only a limited number of teeth that are

found to be representative of entire dentition, thereby delivering a comprehensive assessment of

periodontal health in an efficient manner (Dhingra & Vandana 2011).

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The severity of periodontitis is defined as per the measurements of PPDs, CAL or alveolar bone loss

(ABL). However, none of these measures are accurate indicators and needed to be used in concordance.

For instance, PPDs however commonly used, under or overestimates periodontal deterioration based on

the state of gingiva (Highfield 2009). Although CAL is considered as the standard measure of

periodontal disease, it is more relevant in depicting the history of disease and less reliable in

ascertaining the present status of periodontal tissues (Buenco et al. 2015).

The clinical assessment of periodontal tissues is undertaken by means of periodontal probing in which

a periodontal probe such as CPITN probe, is inserted into periodontal pockets to measure PPDs and

CAL. Although a rough estimate of ABL can also be obtained by periodontal probing, radiographic

assessment is almost always obtained. The probe is inserted parallel to vertical axis of tooth under

slight force and ran circumferentially to identify points of deepest penetration for each tooth. PPDs are

measured as the distance from the floor or bottom of the periodontal pocket to gingival margin, while

CAL is measured as the distance from the bottom of the pocket to cemento-enamel junction (Hefti

1997).

Table 1: Community periodontal index (WHO 2005)

Category/code Description

0

1

2

3

4

Healthy periodontium

Gingival bleeding on probing

Calculus detected and bleeding on probing

Periodontal pockets lying between 4 - 5 mm / shallow periodontal pockets

Periodontal pockets being 6 mm or more / deep periodontal pockets

2.1.6 Treatment of Periodontitis

Management of periodontitis is based on the principal of establishing plaque control and preventing

further deterioration of periodontal tissues (Teughels et al. 2014). The treatment modalities employed

to do so are divided into non-surgical and surgical types, which may be supplemented with

antimicrobials where needed. In line with the principles of conservative and noninvasive management

of diseases, nonsurgical treatment options such as professional debridement of plaque through

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techniques such as scaling are first undertaken (Newman et al. 2012). Surgical treatment such as

gingivectomy is reserved for severe cases or undertaken in cases where extent of periodontal damage is

extensive or non-surgical measures have failed (Drisko 2014).

Any active manipulation of periodontium, whether surgical or non-surgical are delivered to remove

plaque and increase the effectiveness of oral hygiene practices undertaken thereafter (Gao et al. 2014).

Regardless of the treatment modality opted for, instituting oral hygiene measures and controlling for

risk factors forms an integral part of treatment plan (Genco & Borgnakke 2013).

2.1.7 Risk factors for Periodontitis

Multiple local, systemic and lifestyle factors increase the risk of periodontitis. Several mechanisms

have been proposed by which various factors individually or synergistically impart elevated risk of

periodontitis. The main pathway by which most of the established risk factors predisposes to

periodontitis is dysregulation of immune response (Jain & Mulay 2014, Hong M et al. 2016).

Furthermore, multiple factors also assist in the development of periodontitis by facilitating maturation n

of plaque and establishment of dysbiosis (Loesche & Grossman 2001, Albandar 2002).

Majority of the risk factors for periodontitis are modifiable in nature that render periodontitis to

preventive regimens. Furthermore, non-modifiable factors such as age and gender are also suggested to

increase the risk of periodontitis through indirect pathways that can also be explored as targets for

preventive strategies (Genco & Borgnakke 2013, Persson 2017).

2.1.7.1 Non-modifiable factor

Age

The prevalence and severity of periodontitis increases with age. The prevalence of severe periodontitis

is 15% higher among the elderly individuals as compared to general population (Khocht et al. 2010).

This is evident by the association between CAL and increasing age, with increase in CAL being

consistent with advancing age. Apart of this increase in CAL is down to gingival recession which itself

is an indicative of progressing periodontal deterioration (Billings et al. 2018).

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The exact mechanism by which advancing age predisposes to periodontitis is not known. However,

ageing is not considered to be a direct contributor to the development of periodontitis. This is supported

by lack of association between age-related changes in periodontium, such as higher fibrotic content or

decrease vascularity of periodontium, and risk of periodontitis. Ageing is proposed to elevate the risk

of periodontitis through age-related factors such as presence of systemic diseases, malnutrition,

decreased dexterity and decreased frequency of regular dental visits (Persson 2017).

Gender

Men are 50% more likely to have periodontitis as compared to women. Moreover, risk of severe

periodontitis among men is three times to that for women. The exact mechanism by which men are

more prone to periodontitis is still poorly understood. It is proposed that higher prevalence of lifestyle

and behavioral risk factors such as poor oral hygiene and smoking among men is mainly responsible

for the difference in risk of periodontitis between genders (Genco & Borgnakke 2013).

2.1.7.2 Modifiable factors

Systemic factors

Systemic risk factors such as diabetes, obesity and use of medication for systemic diseases increase the

risk of periodontitis. The exact mechanism by which individual systemic diseases contribute to the

development of periodontitis is still poorly understood. However, it is suggested that systemic risk

factors facilitate in the development of periodontitis by impairing metabolic control and causing

dysregulation of immune response (Casanova et al 2014). The alterations caused by systemic factors in

the immune system varies from mounting a deficient immune response against bacterial stimulus to the

development of hyperactive inflammatory response (Silva et al. 2015).

Diabetes

Most widely accepted systemic risk factor for periodontitis is diabetes. The prevalence of periodontitis

among individuals with diabetes is three times to that of general population. Moreover, individuals with

diabetes are also more likely to develop severe periodontitis and undergo rampant destruction of

periodontium (Preshaw et al. 2012). The impact of diabetes on periodontium is so pronounced that it is

regarded as one of the complications of diabetes. Diabetes is proposed to establish a general

20

inflammatory state that contributes in the dysregulation of immune response mounted against plaque

bacteria (Chapple et al. 2013).

Obesity and metabolic syndrome

Several studies indicate increased risk of periodontitis as a function of obesity and metabolic syndrome.

Increasing evidence indicates that obesity do not only increase susceptibility to developing

periodontitis, but obese individuals also demonstrate greater loss of clinical attachment as compared to

controls. The mechanism by which obesity facilitates in the development of periodontitis is still under

study. However, it is suggested that obesity predisposes to periodontitis partly by modulating the

immune response and facilitating in the establishment of dysbiosis (Genco & Borgnakke 2013).

Metabolic syndrome is also proposed to be an independent risk factor for periodontitis. Indeed,

individual metabolic changes such as hypertension, dyslipidemia and insulin resistance are all found to

increase the risk of periodontitis. These metabolic disturbances are suggested to facilitate in the

development of periodontitis by impairment of immune response and contributing to systemic

inflammation (Reynolds 2014).

Osteoporosis, low dietary calcium and vitamin D deficiency

Osteoporosis is another systemic factor that has been shown to increase the risk of periodontitis. Many

studies have demonstrated that systemic osteoporosis also effects the jaw bones and thereby contributes

to tooth loss. Furthermore, it is suggested that osteoporosis facilitates tooth loss indirectly by increasing

the likelihood of developing periodontitis. However, the exact nature and magnitude of the effect of

osteoporosis on periodontitis remains unclear (Martínez-Maestre et al. 2010).

In addition to osteoporosis, low dietary intake of calcium and vitamin D deficiency have also been

found to increase the risk of periodontitis and tooth loss. Calcium deficiency is also found to impact the

severity of periodontitis. The exact mechanism by which either of these deficient states contribute to

periodontitis are still poorly understood. However, impairment of bone metabolism is cited as one of

the possible pathways by which calcium and vitamin D deficiency adversely impacts periodontal health

(Nishida et al. 2000).

21

Medication

Different classes of medicines such as antihypertensive drugs, narcotic analgesics and antihistamines

are associated with increased risk of periodontitis. Multiple mechanisms have been proposed by which

different medicine impart increased risk of periodontitis. Among the most commonly observed oral

effect of systemic medicines is decreased salivary flow (Al-Jehani 2014). Saliva is the primary

defensive mechanism by which host resist and maintain the bacterial stimulus from dental plaque to a

minimum. Decrease in the composition or volume of saliva significantly impairs plaque control and

increases the risk of periodontitis (Mariotti & Hefti 2015). Another important class of drugs that

increase the risk of periodontitis is calcium channel blockers. Calcium channel blockers are associated

with gingival overgrowth which hinders plaque control by sheltering plaque in resultant pseudo

periodontal pockets. This allows for the maturation of plaque that subsequently increase the risk of

periodontitis (Scully 2003).

Life style factors

Poor oral hygiene

Lack of adequate oral hygiene measures facilitates deposition and maturation of plaque that triggers

chronic inflammatory pathology of periodontitis (Albandar 2002). Local retentive factors such as mal-

aligned teeth and ill-fitting restorations further contribute to increased risk of periodontitis by

facilitating plaque retention and making oral hygiene measures ineffective (Loesche &Grossman 2001).

Smoking

Smoking is regarded as the single most important preventable risk factor for periodontitis. The

prevalence of periodontitis among smokers is almost twice to that of non-smokers. Smoking do not

only contribute to the development and progression of periodontitis but is also a strong determinant of

severity of periodontitis (Nociti et al. 2015). The exact mechanism by which smoking increases the risk

of periodontitis is still not clearly understood. However, smoking is suggested to cause changes in

immune system such as decreased production of immunoglobulins and increased expression of reactive

oxygen species (ROS), that increases periodontal tissue destruction (Johannsen et al. 2014).

22

Alcohol intake

Many studies indicate negative effect of alcohol intake on periodontal health. However, effect of

alcohol intake varies between genders and amount of alcohol consumed. Alcohol intake have been

found to cause more detrimental effects on periodontal health in men as compared to women. Moderate

alcohol intake has been found to cause little to no adverse effect on periodontal health, however,

excessive consumption of alcohol significantly increases risk of periodontitis (Kongstad et al. 2008).

Alcohol intake is proposed to impact periodontal health by alteration of plaque composition towards a

more pathogenic type and increased expression of pro-inflammatory cytokines (Suwama et al 2018).

Psychological Stress and Depression

In addition to its negative effects on general health, stress is a significant determinant of periodontal

health. It has been found to incur a number of physiological changes that may directly or indirectly

contribute to increased risk of periodontitis. One such change is decreased salivary flow that aids in

dysbiosis and subsequent development of periodontitis (Reners & Brecx 2007). Furthermore, stress has

also been found to reduce the effectiveness of periodontal treatment (Bakri et al. 2013).

Another important factor that increases the susceptibility of developing periodontitis is depression. The

exact mechanism by which depression contributes to the development of periodontitis is yet poorly

understood. However, evidence suggests that depression significantly impairs immune response and

adversely effects wound healing that can directly contribute to the development of periodontitis.

Furthermore, depression is also likely to negatively affect lifestyle habits thereby indirectly

predisposing to periodontitis (Reynolds 2014).

2.2 DEMENTIA AND COGNITIVE IMPAIRMENT

2.2.1 Dementia

2.2.1.1 Definition and prevalence

Dementia is a syndrome characterized by progressive deterioration of cognitive function. Extent of

cognitive deterioration observed in dementia is well beyond age-related cognitive decline and is

essentially accompanied by functional incapacitation or functional dependence which leaves

23

individuals dependent on caregivers for carrying out day to day activities. It is highly prevalent among

the elderly, with 5-7% of 60 years old or older individuals affected by it worldwide. Old age is the most

significant predisposing factor for dementia, with prevalence of dementia reported between 20-50%

among 85 years or older individuals (Slavin et al. 2013, WHO 2017).

The effects of dementia extend beyond the affected individual, with significant social and

psychological burden experienced by caregivers and family members. Several factors such as chronic

systemic diseases including CVDs, are implicated as risk factors of dementia. Many extensively

studied risk factors are non-modifiable in nature, however increasingly greater number of studies are

now being carried out with focus on modifiable risk factors (LoGiudice & Watson 2014).

Cognition is the mental ability or function to acquire, process, utilize and implement information or

knowledge. Cognition is not a single process but is a constellation of multiple domains such as

memory, thinking, orientation, language and judgement among others. All or several of these are

usually involved at the same time in the processing of each piece of information (Woodford & George

2007).

Dementia affects multiple cognitive domains, although the pattern, number of cognitive domains

affected, and the extent of deterioration depends on underlying pathology (LoGiudice & Watson 2014).

For instance, memory is most commonly and extensively affected cognitive domain in Alzheimer’s

disease (Aggarwal et al 2015), while executive function is most commonly compromised in vascular

dementia (Ying et al. 2016). In addition to functional dependence, cognitive deterioration is often

accompanied with or preceded by behavioral and psychiatric symptoms such as agitation, anxiety,

depression, delusions, hallucinations, sleep and appetite disturbances (Cerejeira et al. 2012).

Around 50 million people are affected by dementia worldwide, with around 8-10 million new cases

encountered on yearly basis. These numbers are projected to increase significantly in the next few

decades owing to the increase in the number of elderly individuals worldwide. According to one

estimate, prevalence of dementia is projected to surpass 150 million by 2050 (WHO 2017). Owing to

the personal, societal and socioeconomic cost, dementia stands out among the foremost healthcare

challenges of present time. Additionally, lack of availability of effective treatment, strongly advocates

24

studies into determining the modifiable risk factors and subsequent development of preventive

strategies (Koch & Jensen 2016).

2.2.1.2 Types of Dementia

A number of pathologies are implicated in the development of dementia. Most of these underlying

pathologies either belong to the neurodegenerative or cerebrovascular class of diseases. However, other

conditions such as HIV infection, thyroid diseases and normal pressure hydrocephalus are implicated as

the etiological factor leading to the development of dementia (WHO 2012).

The underlying disease that contributes to the development of dementia forms the basis of classification

of dementia into its subtypes. In many cases a single underlying disease is clearly delineated. However,

in others more than one disease occurs simultaneously. Even in cases where a single underlying cause

is identifiable, there may lie significant variability in its presentation. Furthermore, signs and symptoms

between different types often overlap (LoGiudice & Watson 2014).

Alzheimer’s disease is the most prevalent type of dementia, with 60-70% of individuals having AD.

AD is followed by vascular dementia (VaD) and dementia with Lewy bodies with each contributing

between 10-20% of dementia cases (Tripathi et al. 2014). Other less common types of dementia include

frontotemporal dementia, dementia due to Parkinson's disease, Creutzfeldt-Jakob disease and

Huntington’s disease (Reith & Mühl-Benninghaus 2015) (Table 2).

Alzheimer’s disease

Alzheimer's disease is clinically characterized by deterioration of multiple cognitive domains, of which

memory is most extensively compromised. Pathological findings include intracellular accumulation of

tau protein in the form of neurofibrillary tangles and extracellular deposits of amyloid protein (Shanthi

et al. 2015). The exact mechanism that leads to its development is still not clearly understood.

However, neuroinflammation and oxidative stress are suggested to be important pathological processes

in regard to the development of AD (Gurav 2014).

Vascular dementia

25

Vascular dementia is characterized by the presence of cerebrovascular lesions. It is further stratified

into subtypes such as multi-infarct dementia, single infarct dementia and subcortical dementia among

others (Benisty 2013, Lam et al. 2014). VaD often develops in individuals with a history of ischemic

stroke, which is proposed to cause progressive cognitive deterioration if experienced repeatedly.

Executive dysfunction and psychomotor slowing are usually the most pronounced cognitive changes in

VaD (Iadecola 2013).

Dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is characterized by the presence of abnormal protein inclusions of

α-synuclein within neurons. Other neuropathological changes seen in DLB includes deterioration of

tegmental dopamine cell population and basal forebrain cholinergic population. Along with general

deficit in cognitive domains, DLB presents with hallucinations, impairment of executive function and

visuospatial dysfunction (Gomperts 2016).

Mixed dementia

Mixed dementia is a term reserved for cases of dementia where more than one underlying pathology is

suspected to be present. In cases of mixed dementia, a dominant type of pathology can be identified.

However, there can also be extensive overlapping of clinical characteristics, making the exact

determination of contributory pathological processes difficult. Most commonly observed combinations

in mixed dementia are of AD and VaD or AD with DLB (Bhogal et al. 2013).

26

Table 2: Main types of Dementia and associated neuropathological features

Types of dementia Neuropathological hallmarks

Alzheimer’s disease

Vascular dementia

Dementia with Lewy bodies

Frontotemporal dementia

Mixed dementia

Parkinson’s disease dementia

Creutzfeldt-Jakob disease

Normal pressure

hydrocephalus

Intercellular accumulation of beta amyloid and intracellular

accumulation of tau protein

Cerebrovascular changes such as vessel blockage, hemorrhagic

stroke and cerebral infarcts.

Intracellular accumulation of alpha synuclein called Lewy bodies.

Heterogeneous group of disorders characterized by protein

accumulation in the frontal and temporal lobes (for example tau

proteins or TDP-43 protein).

Overlapping of features pertaining to different types of dementia,

for instance in mixed dementia with AD and VaD, protein

accumulation is accompanied with cerebrovascular changes.

Accumulation of alpha-synuclein primarily in substantia nigra as

opposed to DLB. Neuropathological presentation can be variable,

with some cases demonstrating accumulation of both alpha-

synuclein and beta amyloid. Protein accumulation is accompanied

by motor impairment.

Spongiform changes in the grey matter. Caused by misfolded

proteins (prions) that lead to misfolding and malfunctioning of

other proteins throughout the brain matter.

Enlargement of ventricles owing to accumulation of cerebrospinal

fluid (CSF) with little or no shrinkage of brain matter in initial

27

stages, enabling it to be distinguished from other types of

dementia.

2.2.2 Cognitive impairment

2.2.2.1 Definition and prevalence

Mild Cognitive Impairment (MCI) is defined as a pathological deterioration of cognitive function that

does not meet the criteria for dementia or is not severe enough to be categorized as dementia. As per

the definition, MCI has long been labelled as the prodromal phase of dementia or the intermediate state

between healthy cognition and dementia. One of the significant differences between MCI and dementia

is that functional capacity or functional independence is essentially preserved in MCI. There is a

significantly greater risk of developing dementia among the individuals with MCI. The broad definition

of MCI highlights the incomplete understanding of this pathology, which make its diagnosis and

management difficult and prone to subjectivity (Langa & Levine 2014).

It is estimated that the prevalence of MCI is four times to that of dementia with prevalence values

ranging between 3-42%. In general, rough estimates put the overall prevalence of MCI between 16-

20% among the 65 years or older individuals which increases dramatically in subsequent decades

(Roberts & Knopman 2013). Multiple factors such as systemic diseases and sedentary life style

increase the risk of developing MCI (Eshkoor et al. 2015). The underlying etiology of MCI and the

exact mechanisms that leads to its development are still poorly understood. Neurodegenerative diseases

are proposed to be a primary cause of MCI (Aggarwal 2007). The diagnosis of MCI is based on clinical

finding of cognitive impairment in one or more cognitive domains based on cognitive tests such as

Mini mental scale examination (MMSE) or other standardized tests (Knopman et al. 2009).

Individuals with MCI carry a significantly higher risk of developing dementia, with 1 out of every 5

individuals with MCI developing dementia. Conversion rate of specific types of MCI differ

significantly and there appears a pattern of higher conversion risk of certain types of MCI into specific

forms of dementia, such as conversion of amnestic MCI into AD (Knopman & Petersen 2014). The

exact mechanism and the risk factors that leads to the conversion of MCI into dementia is yet not

28

delineated. Despite significantly higher risk of developing dementia, some cases of MCI revert to

normal cognitive state, while others may stabilize with limited or no discernible progression (Roberts et

al. 2012). The factors that causes a specific group of individuals with MCI to develop dementia, while

others are preserved are still under investigation (Trzepacz et al. 2014).

MCI not only increases the risk of dementia, but it also significantly impairs general quality of life

(Knopman & Petersen 2014). This in addition to increased proportion of ageing population, personal

and socioeconomic cost of its management makes it a major healthcare challenge (Eshkoor et al 2014).

2.2.2.2 Types of Mild cognitive impairment (MCI)

MCI is broadly classified into two types, amnestic and non-amnestic. This categorization is based on

the cognitive domains most prominently affected by the neurodegenerative process. Amnestic MCI is

the cognitive impairment in which memory is greatly impaired, while other cognitive domains are

either subtly involved or are persevered. Non-amnestic MCI refers to cognitive impairment involving

deterioration of non-amnestic cognitive domains such as executive functioning, language and so forth.

The two basic types are further classified into single and multiple domain subtypes. In single domain

subtypes only one cognitive domain is affected, while cases of multiple domain subtypes involve more

than one cognitive domain (Petersen 2011).

The prevalence of amnestic MCI is almost twice to that of non-amnestic types. Amnestic MCI carries a

higher risk of conversion into AD as compared to any other type of dementia. Similarly, individuals

with non-amnestic types of MCI are at greater risk of developing types of dementia other than AD.

There is also increasing evidence suggesting that multi-domain MCI subtypes are more likely to

progress into dementia as compared to single domain MCI subtypes (Petersen RC et al. 2010). Another

important difference between the amnestic and non-amnestic MCI, is higher prevalence of behavioral

changes in non-amnestic MCI (Mortimer et al. 2013).

2.2.3 Diagnostic criteria for Dementia and Mild Cognitive Impairment

The diagnosis of dementia and MCI is complex and based primarily on the clinical findings of

cognitive impairment and its effects on functional independence. These two attributes form the core of

the diagnostic criteria defined in standard diagnostic manuals such as Diagnostic and Statistical Manual

https://en.wikipedia.org/wiki/Diagnostic_and_Statistical_Manual_of_Mental_Disorders

29

of Mental Disorders (DSM) and International Statistical Classification of Diseases and Related Health

Problems (ICD) among others (American Psychiatric Association 2013). The general criteria for

dementia and cognitive impairment in either DSM or ICD are similar. However, subtle differences

pertaining to behavioral changes and involved cognitive domains that delineate between subtypes do

impact the prevalence values and breakdown of different types (Wancata et al. 2007).

Findings from medical examination are supplemented with neuropsychological assessment, which

provides a measure of the type and extent of the impairment. The neuropsychological assessment uses a

battery of cognitive tests such as Mini-Mental State Examination (MMSE) or other more complex tests.

Neuroimaging is also used which is helpful in identifying and quantifying pathological changes in the

brain (Echavarri et al. 2012). More recent diagnostic criteria for research also take into account

cerebrospinal fluid (CSF) biomarkers such as tau and β-amyloid proteins.

The diagnostic criteria for neurodegenerative disorders have evolved over time and are likely to

undergo further refinement as the mechanisms leading to their development become clearer. There

have been significant differences in the diagnostic criteria of dementia and MCI in DSM-5 as compared

to previous versions. The term “dementia” was removed from DSM-5, and the heading of Delirium,

Dementia, and Amnestic and Other Cognitive Disorders was replaced with Neurocognitive Disorders.

The category of Major Neurocognitive Disorder was introduced, corresponding to the previous

Dementia category as given in older versions of DSM (American Psychiatric Association 2013).

Furthermore, a new category of Mild Neurocognitive Disorder was introduced that corresponds with

the definition and presentation of MCI. No specific criteria for MCI had been listed in previous DSM

versions.

The diagnostic criteria for Major Neurocognitive Disorder are based on 2 major clinical findings.

Firstly, the subject should demonstrate cognitive deterioration of pathological nature in any cognitive

domain, and secondly, cognitive deterioration needs to be severe enough to impair individual’s ability

to carry out day to day tasks (Sachdev et al. 2014). The updated criteria in DSM-5 for dementia are

different from earlier versions where deterioration of memory held key importance and required

demonstration of deterioration of multiple cognitive domains for a formal diagnosis of dementia to be

made. Although classical features of cognitive impairment and functional incapacitation are

https://en.wikipedia.org/wiki/Diagnostic_and_Statistical_Manual_of_Mental_Disorders

https://en.wikipedia.org/wiki/International_Statistical_Classification_of_Diseases_and_Related_Health_Problems

https://en.wikipedia.org/wiki/International_Statistical_Classification_of_Diseases_and_Related_Health_Problems

30

demonstrated by all forms of dementia to varying degree, specific types of dementia are delineated on

the basis of neuropathological findings inherent to each type (Hugo & Ganguli 2014).

The introduction in DSM-5 of more specific criteria for Mild Neurocognitive Disorder acknowledges

the fact that more and more old individuals with cognitive decline seek medical care early, before they

develop dementia. One important purpose of emphasizing MCI as a separate diagnosis has been to

facilitate early diagnosis and treatment of the underlying disease, before it progresses to the more

severe stage of dementia. In addition, it also acknowledges the fact that MCI may not always be

progressive in nature. The diagnostic principle is similar to Major Neurocognitive Disorder or dementia

except that in MCI, cognitive impairment is not severe enough to affect individual’s ability to carry out

day to day task (Sachdev et al. 2015).

In addition to subjective assessment of cognition, neuropsychological assessment using standardized

tests is recommended in DSM-5. The battery of cognitive tests not only aids in screening the

individuals with cognitive deficits but also enables to calibrate degree of cognitive deficit that in turn

facilitates in differentiating between MCI and dementia. Although DSM-5 does not specify exactly

which battery of cognitive tests should be used, it provides some guidelines regarding the degree of

cognitive deterioration likely to be experienced in major and mild neurocognitive disorders.

Neuropsychological assessment falling between 1 to 2 standard deviation of normative mean is

suggested to indicate mild neurocognitive disorder, while for major neurocognitive disorder the value

lies 2 or more standard deviation below normative mean (Sachdev et al. 2015).

In general, for evaluation of cognitive function and assessing orientation, immediate memory,

language, calculation, short-term recall and attention, MMSE is the most widely used test. Score ranges

from 0 to 30, with a score of 24 or below suggesting dementia, although a threshold for MCI has not

been universally established (Tombaugh & McIntyre 1992, Lancu and Olmer 2006). Additionally,

other than MMSE, a range of more detailed and sensitive neuropsychological test batteries are

available. Majority of these tests assess multiple cognitive domains; however, a number of cognitive

tests also evaluate specific cognitive domains that help in distinguishing between different types of

cognitive impairment. For instance, Wechsler memory scale –Revised (WMS-R) is used for assessment

31

of memory, whereas Boston naming test is employed for assessing language and executive function can

be specifically assessed through digit symbol substitution test (Stokin et al. 2015).

2.2.4 Risk factors for Dementia and Mild cognitive impairment

Dementia and MCI are regarded as multifactorial conditions. Many demographic, systemic and life

style factors are implicated for contributing to the overall risk of dementia and MCI. Many of these

factors often occur and interact across the entire life span and are through various pathways proposed to

result in cognitive deterioration. While some of these risk factors such as age and family history are

non-modifiable, many modifiable risk factors such as diabetes, CVDs and various lifestyle factors have

been identified (Table 3). Owing to the debilitating nature of these pathologies and lack of availability

of effective treatment, modifiable factors are a subject of several epidemiological studies looking into

the preventive strategies for dementia and MCI (Sindi et al. 2015).

2.2.4.1 Non-modifiable risk factors

Demographic factors

Demographic factors such as age and gender significantly increase the risk of dementia and cognitive

impairment.

Age

Age is regarded as the strongest risk factor for either condition with majority of the cases occurring in

6th decade of life or thereafter (Kalantarian et al 2013). The incidence of dementia increases

dramatically with age, doubling in less than 6 years. Indeed 70% of all dementia cases occur in 75

years or older individuals (Fratiglioni et al. 2000). The incidence of dementia is found to increase from

just 3.1 cases per 1000 among the 60-64 years old age group to 175.0 cases per 1000 among the 95

years or older age group (WHO 2012). The same pattern seems to be followed by MCI. Although the

incidence values for MCI varies from 5.1 to 168 per 1000 persons, as in the case of dementia, incidence

of MCI tends to increase with advancing age (Roberts & Knopman 2013).

Gender

32

Gender is also found to independently influence the risk of dementia and MCI. Women are found to be

at a greater risk of dementia, with factors such as higher life expectancy and hormonal changes after

menopause being suggested as possible explanations (Rocca et al. 2014). Contrary to dementia several

studies have reported greater risk of MCI in men, with men being twice more likely to have MCI than

women. Higher prevalence of systemic diseases and relatively less healthy life style such as increased

alcohol consumption and smoking among men as compared to women have been suggested as potential

causes of increased risk of MCI among men (Roberts et al 2012). However, more studies are needed to

conclusively determine the role of gender differences in the risk of cognitive impairment.

Genetic factors

Genetic factors such as familial aggregation and different individual genes are found to increase the

risk of dementia and MCI. Studies have reported 25 to 50% increase in risk of dementia among

individuals with family history of dementia (Milne et al. 2008), while the risk of cognitive impairment

also substantially increases in individuals with family history (Locke et al. 2009). Furthermore, the

degree of cognitive deterioration may be more pronounced in cases with familial aggregation

(Scarabino et al. 2016).

Several different genes are implicated in increasing the risk of developing dementia. This is particularly

true for AD, in which presence of ε4 allele of Apolipoprotein E (ApoE ε4) is regarded as an established

risk factor, with at least 15-20% of all cases of dementia attributed to it. Moreover, ApoE ε4 is found to

decrease the age of dementia onset and also adversely affect its responsiveness to interventions (Teruel

et al. 2011).

2.2.4.2 Modifiable risk factors

Cardiovascular and metabolic risk factors

Systemic factors such as cardiovascular and metabolic diseases, significantly add to the risk of

dementia and MCI. Although multiple mechanisms have been postulated to explain for the effect of

systemic diseases on cognition, the exact mechanisms by which systemic diseases contribute to the

development of cognitive deterioration are not fully clarified. Regardless of the systemic risk factor

33

involved, increasing evidence suggests that significant reduction in the risk of cognitive deterioration

may be possible through the management of systemic diseases (Baumgart et al. 2015).

Cardiovascular diseases

A wide range of cardiovascular pathologies such as atrial fibrillation, thrombotic events, heart failure

and hypertension increase the risk of dementia and cognitive impairment (Da la Torre 2012, Wand et

al. 2015). A number of possible mechanisms such as cerebral hypo-perfusion and cerebral infarction

among others are cited as leading to subsequent cognitive deterioration (Etgen et al. 2011).

Additionally, the time frame during which cardiovascular risk factors develop, appears to be important

for the risk of late-life cognitive deterioration. Risk factors such as hypertension in midlife seem to be

consistently associated with increased risk of dementia and cognitive impairment later on. Studies on

hypertension at older ages have reported conflicting results. However, further studies are required to

conclusively determine the magnitude and time span of effects of CVDs on cognition (Corrada et al.

2017).

Diabetes

Diabetes is another important condition that independently elevates the risk of dementia and MCI. This

is particularly true for vascular dementia with studies reporting up to 60% increased risk of vascular

dementia in people with diabetes. Furthermore, diabetes is also found to increase the risk of

progression of MCI to dementia (Chatterjee et al. 2016). It is suggested that cerebrovascular

disturbances produced by diabetes explain the increased risk of cognitive decline and dementia.

Additionally, impairment of metabolic control is also suggested to contribute towards the adverse

effects of diabetes on cognition (Hardigan et al. 2016).

Diabetes also demonstrates an association with AD. Individuals with diabetes carry significantly

greater risk of developing AD, with studies indicating a link between diabetes and accumulation of

amyloid (Chung et al. 2018). Multiple mechanisms such as impairment of insulin signaling, oxidative

stress and mitochondrial dysfunction are attributed to the impact of diabetes on elevating the risk of

AD. However, further studies are required to clearly elucidate the exact mechanisms (Yang & Song

2013).

34

Obesity and metabolic syndrome

Obesity and metabolic syndrome have been reported as significant risk factors for dementia and

cognitive impairment (Miller & Spencer 2014, Rizzi et al. 2014, Tynkkyen et al. 2016, Ylilauri et al.

2017). The effect of obesity on the risk of dementia appears to be age-dependent. Obesity in midlife

significantly elevates the risk of cognitive deterioration, but like hypertension its contribution to the

development of cognitive deterioration is less clear at older ages (Singh-Manoux et al. 2018).

A decline in body mass index has been reported to occur over time in people who develop dementia

later on. This may explain why some studies have reported contradictory findings, indicating that

higher body mass index at older ages may be protective against dementia (Qizilbash et al. 2015).

Further studies are still needed to determine the exact nature and magnitude of the effect that obesity

has on cognitive deterioration.

Metabolic syndrome is also suggested to elevate the risk of cognitive deterioration. Indeed, different

constituent pathological disturbances seen in metabolic syndrome, such as dyslipidemia, are found to

be risk factors for cognitive deterioration (Liu et al. 2015, Salameh et al. 2016).

The biological mechanisms behind the impact of obesity and metabolic syndrome on dementia risk are

still poorly understood. They are suggested to increase the risk of cognitive deterioration through their

effects on general health. Obesity and subsequent increased adiposity increase the risk of developing

other systemic pathologies, that are in turn are established risk factors for cognitive deterioration

(Gustafson 2006). Furthermore, obesity is also found to be associated with brain atrophy (Ho e al.

2010).

Lifestyle, psychological and other risk factors

Early life adversities

Factors indicative of early life adversities such as low education and poor socioeconomic status and

related factors significantly increase the risk of dementia and cognitive impairment. Both poor

socioeconomic status and low education can affect lifestyle, access to health care services and

awareness regarding diseases and corresponding adoption of preventive measures, thereby contributing

to an individual’s risk of multiple pathologies including dementia (McDowell et al. 2007).

35

The exact pathological mechanisms by which early life adversities contribute to the development of

cognitive deterioration are not fully known. However, they are believed to affect brain development

and compromise attainment of cognitive reserve that in turn decreases the resistance against

neuropathological changes leading to the development of cognitive deterioration (Russ et al. 2014).

Moreover, they are also proposed to increase the risk of dementia and cognitive impairment by

increasing the likelihood of developing systemic diseases that in turn independently increase the risk of

cognitive deterioration (Xu et al. 2014).

Smoking

Smoking is one of the most commonly implicated life style factors in cognitive deterioration. Current

smokers carry significantly higher risk of dementia and MCI as compared to non-smokers and former

smokers. The mechanisms by which smoking imparts adverse effects on cognition are not fully clear,

although the impact of smoking on cardiovascular health may at least partly explain the effects.

However, the effects are suggested to be of reversible nature, evident by reduction of dementia risk

upon smoking cessation. The reduction in dementia risk on smoking cessation is significant, with

formers smokers carrying almost same risk of dementia as non-smokers (Zhong et al. 2015).

Alcohol intake

Alcohol intake is another important lifestyle factor with significant bearing on cognition.

Current evidence indicates that alcohol exerts a range of effects on cognition which depends on the

quantity of alcohol consumed. Both heavy alcohol intake and complete abstinence from alcohol have

been reported to increase the risk of cognitive decline, while mild to moderate alcohol intake suggested

to impart a certain degree of protection against cognitive impairment (Kim et al 2016, Sabia et al.

2018).

Depression of central nervous system, neurotoxicity and impairment of cerebrovascular function are

implicated as possible pathways by which heavy alcohol intake leads to detrimental effects on

cognition (Wilhelm et al. 2015). However, the mechanism by which abstinence from alcohol increases

the risk of cognitive deterioration and the pathway by which mild to moderate alcohol consumption

provides a protective effect are still not known (Wood et al. 2016, Sabia et al. 2018).

36

Depression

Several studies have indicated that the risk of cognitive deterioration is significantly higher in

individuals with depression. Furthermore, there is also evidence that indicates increase in severity of

depression increases the severity of cognitive deterioration (Gutzmann & Qazi 2015).

The exact part that depression plays in cognitive deterioration is not clear, although, studies have

observed some similarities in brain changes in people with depression and those with dementia,

indicating a likely link between the pathological entities (Bennett & Thomas 2014). However,

depression may also be a consequence of the neurodegenerative disease process, and one of the first

symptoms to accompany the development of cognitive impairment (Zulkifly et al. 2016).

Head injury

History of head injury is another factor linked with increased risk of dementia. The risk is found to be

particularly significant in cases where head injury was accompanied with loss of consciousness.

Repeated minor head injuries such as concussion have been found to produce structural changes in the

brain. These structural changes compounded over time are believed to elevate the risk of developing

dementia (Hugo & Ganguli 2014).

37

38

Table 2: Risk and protective factors for Dementia and Cognitive impairment

Risk factors Protective factors

Non-modifiable:

Demographic factors:

Age

Gender

Genetic factors:

Different genes particularly ApoE ε4

Family history

Non-modifiable:

Genetic factors:

Different genes such as ApoE ε2

Modifiable:

Systemic factors:

Cardiovascular diseases

Stroke

Diabetes

Hypertension

Obesity

Lifestyle factors:

Sedentary lifestyle

Smoking

Heavy alcohol intake

Unhealthy dietary habits such as diets rich in

saturated fats

Others:

Depression

Psychological stress

Traumatic head injury

Modifiable:

Socioeconomic factors:

High education

High income

Lifestyle factors:

Physical activity

Participation in cognitively stimulating activities

Participation in social activities

Mild to moderate alcohol intake

Healthy diet such as Mediterranean diet or diet

rich in omega 3 and antioxidants

Pharmacological agents:

Antihypertensives

Statins

NSAIDs

39

2.2.5 Possible prevention strategies for Dementia and Mild cognitive impairment

Many modifiable factors have been proposed to significantly reduce the risk of dementia and cognitive

impairment (Savica and Petersen 2011). Among these factors, physical activity and higher education

are found to be most impactful (Schlosser Covell et al. 2015, Mirza et al. 2016). Moreover, healthy

dietary practices such as diets rich in omega 3 and antioxidants, bilingualism and participation in social

and cognitively stimulating activities also render some protective effect against cognitive deterioration

(Hu et al 2013, Ramakrishnan et al. 2017, Zhou et al. 2018).

The exact mechanism by which these factors provide protection against cognitive deterioration are still

poorly understood. Healthy lifestyle practices such as physical activity and Mediterranean diet are

believed to prevent metabolic disturbances and systemic inflammation that are in turn regarded as

independent risk factors for dementia and cognitive impairment (Petersson and Philippou 2016).

Whereas, social and cognitively stimulating factors such as higher education, bilingualism, continuous

learning and social activities are suggested to render protective effect against cognitive deterioration by

means of 'cognitive reserve' (Paillard-Borg et al. 2009). Cognitive reserve is a term referring to the

individual’s ability to tolerate or cope with the pathological changes by means of the way in which

cognitive tasks are processed and performed (Russ et al. 2013).

In addition to lifestyle factors, evidence suggests that a number of pharmacological agents such as

antihypertensive dugs, statins and anti-inflammatory agents like non-steroidal anti-inflammatory drugs

(NSAIDs) may provide protective effect against dementia and cognitive impairment (Pan et al. 2018,

Tan et al. 2018, Xue ta al. 2018). The underlying principle in the proposed effect of these agents is to

reduce the risk of systemic diseases that in turn are risk factors for cognitive deterioration. However,

the evidence regarding rigorous use of any of these agents in preventive regimens is not enough.

Indeed, some studies have also produced contradictory results, especially in case of NSAIDs, where

use of suggested pharmacological agents in old age may predispose to a greater risk of cognitive

deterioration. Furthermore, the dosage, duration of use and time span during which they may render

protective effect are still under investigation (DeLoach & Beall 2018).

40

Several clinical trials involving different lifestyle changes or pharmacological agents have been

conducted. Although some positive effects have been observed, the magnitude of the effect has not

been of much practical significance (Sindi et al. 2015). There are 3 main reasons cited for this limited

success. Firstly, most of the trials were focused on determining the effect of targeting a single risk

factor, which does not consider the multifactorial nature of dementia. Secondly, dementia is a chronic

pathology that results from the interplay of several risk factors over a life span. Thereby, preventive

measures are also needed to be applied with a life course perspective, rather than administering them in

old age when the underlying pathology may already have been in development for years (Mangialasche

et al. 2012).

Thirdly, several risk factors such as hypertension and obesity seem to have age- or time-dependent

effects, suggesting that there may be an optimal time window when preventive interventions need to be

administered to achieve maximum benefit (Richard et al. 2009, Corrada et al. 2017, Singh-Manoux et

al. 2018). Moreover, methodological limitations such as small sample size and short duration of the

study are reasoned for the inconclusive effects (Mangialasche et al. 2012).

2.2.5.1 Multi-domain trials in Dementia prevention

Several recent clinical trials have attempted to prevent dementia and MCI by applying multidomain

preventive interventions that aim to target multiple risk factors simultaneously. Examples of such major

trials include Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability

(FINGER), Multidomain Alzheimer Preventive Trial (MAPT) and the Prevention of Dementia by

Intensive Vascular Care (PreDIVA). These trials are based on controlling for systemic and vascular

factors in conjunction with introduction of lifestyle changes. Lifestyle changes comprise physical

activity, healthy nutrition, social and cognitively stimulating activities that have been suggested to

increase resilience against cognitive deterioration (Andrieu et al. 2011).

FINGER is a multidomain, multicenter interventional study conducted on 1260 individuals. It is the

first large 2-year trial that has shown significant positive effects on cognition for a multidomain

lifestyle intervention. The intervention comprised of vascular risk factors management, nutritional

guidance, physical activity and engagement in social and cognitively stimulating activities (Ngandu et

al. 2015). MAPT is a French multidomain, multicenter interventional study conducted on 1680

41

individuals. It also tested the efficacy of multidomain intervention including omega 3 supplementation

in reducing the risk of dementia (Tabue-Teguo et al. 2018).

PreDIVA was another interventional study conducted on 3534 individuals that adopted multidomain

strategy against dementia prevention. It analyzed the difference in risk of dementia between individuals

receiving standard care for cardiovascular factors and individuals that received intensive vascular care.

Intensive care regimen adopted in PreDIVA managed cardiovascular factors through multidomain

strategy including medication, nutritional and lifestyle alterations (Moll van Charante et al. 2017). The

MAPT and PreDIVA trials have several differences from FINGER, for example different target

population and intensity of the multidomain intervention. These 2 trials did not show a significant

impact on the main cognitive outcome (specific cognitive tests in MAPT, and dementia in PreDIVA).

3 AIMS AND METHODS

3.1 AIMS

3.1.1 General Objective

The general objective was to conduct a systematic review of original research articles that assessed the

association between periodontitis and dementia. This review also aimed to study the role of

periodontitis in the development of cognitive impairment. Due to the limited number of studies that

were published at the time when the search strategy for this review was undertaken, all the studies

evaluating periodontitis against cognitive decline, mild cognitive impairment, memory impairment and

cognitive dysfunction were included in this review.

All the studies, pertaining to various endpoints of cognition were addressed under the main outcome of

cognitive impairment, to assess the effect of periodontitis on cognitive impairment or on cognition in

general. The assessment of the effect of periodontitis on cognition was carried out to assess

contribution of periodontitis in the development of mild cognitive impairment which in turn increases

risk of dementia (Petersen et al. 2001). This might render more insight into the impact of periodontitis

on the overall continuum extending from healthy cognition right up to dementia.

42

3.1.2 Specific Objectives

This systematic review has following specific objectives:

1. To study whether periodontitis is a risk factor for dementia.

2. To study whether periodontitis is a risk factor for cognitive impairment.

3. To assess quality of evidence of studies evaluating the association between periodontitis and

dementia

4. To assess quality of evidence of studies evaluating the association between periodontitis and

cognitive impairment?

3.1.3 Novelty compared to previous reviews

Although in the past few years, few reviews addressing the association of periodontitis and dementia

have been conducted (Shen et al. 2016), most of them evaluated the role of periodontitis on the

progression of dementia. Furthermore, as to our knowledge none of the reviews solely focused on

longitudinal studies and included only a handful of studies with different study designs. This review

focuses on longitudinal studies and includes more recent studies compared to previous reviews.

Additionally, this review also focuses on studies assessing association between periodontal health and

cognitive impairment. Furthermore, quality assessment of the included studies was also carried out to

evaluate the overall quality of evidence that is currently available in regard to the role of periodontitis

on cognition.

3.2 METHODOLOGY

This systematic review was limited to observational longitudinal studies. Studies that directly assessed

association between periodontitis and dementia were searched on PubMed and Scopus. The search was

restricted to English language publications and was conducted by using keywords

“PERIODONTITIS”, “GINGIVITIS”, “TOOTH LOSS”, “DEMENTIA”, “PROSPECTIVE”,

“RETROSPECTIVE”, “COHORT”, “FOLLOW UP” and “LONGITUDINAL”.

The same search strategy was further expanded with search terms like “MEMORY IMPAIRMENT”,

“COGNITIVE IMPAIRMENT” and “COGNITIVE DETERIORATION” to retrieve studies that were

primarily studying the role of periodontitis in the development of cognitive impairment. Detail of the

search strategy is given in Table 4. Qualitative assessment of included studies was also conducted as

43

part of the review. The included studies were evaluated on four major domains and one minor domain

to determine overall quality of each study and risk of bias in each study. A cumulative grading was

assigned to each study based on grades attained in individual domains.

3.2.1 Inclusion criteria

Following is the inclusion criteria that was defined for this review:

• Longitudinal observational studies.

• Studies that recruited individuals without dementia at baseline. Studies with a mix of

cognitively healthy individuals and individuals with cognitive impairment at baseline were also

included if they conducted a separate analysis for incident dementia and incident cognitive

impairment.

• Studies having periodontitis as the exposure (either assessed directly or evaluated through

specifically justified proxy measures such as tooth loss).

• Dementia as the outcome of interest (for part of the review assessing periodontitis as a risk

factor for dementia) and cognitive impairment as the outcome (for part of the review assessing

periodontitis as a risk factor for impairment).

• Studies having a well-defined criterion for diagnosis of exposure and outcome.

3.2.2 Exclusion criteria

Cross sectional studies and studies that recruited individuals with dementia at baseline were excluded.

Table 3: MEDLINE search strategy PubMed July 2017 (run on date 18.07.2017)

((periodontitis) OR gingivitis) OR tooth loss

(((cognitive impairment) OR dementia) OR memory) OR cognitive deterioration

(#1 AND #2)

((((periodontitis) OR gingivitis) OR tooth loss)) AND ((((cognitive impairment) OR dementia) OR

memory impairment) OR cognitive deterioration)

((((cohort) OR prospective) OR longitudinal) OR follow up) OR retrospective

(#3 AND #4)

44

3.3.3 Quality assessment

Due to lack of availability of standardized validated tools for quality assessment of longitudinal studies,

method employed by Shamliyan et al (2011) was modified to meet the specific requirements of this

review. The quality assessment was undertaken in four major domains and one minor. Grades in

individual domains were combined to produce overall grading for each study.

Following are the domains in which each study was assessed:

1. Population representativeness: based on subdomains of age, subject selection and sample size.

2. Assessment of Exposure (Periodontitis): based on diagnostic method(s) and criteria used for

evaluation of periodontitis.

3. Length of follow up period/study duration.

4. Assessment of Outcome (Dementia and Cognitive impairment): based on diagnostic method(s)

and criteria used for the evaluation of outcome.

5. The minor domain is drop out or attrition of study participants.

3.3.3.1 Systematic evaluation of studies

Population representativeness

The representativeness of study population was based on 3 subdomains, age, random or non-random

selection and sample size. The subdomain of age was dichotomized into 2 groups, less than 65 years

old and 65 years or older. We categorized it as such, due to better probability of assessing longer-term

risk pertaining to chronic diseases such as dementia in younger individuals (less than 65 years old).

Secondly, older individuals are also likely to present with multiple comorbidities that may confound

association in question and offer significantly less time for follow up.

Furthermore, older individuals are also likely to have asymptomatic or preclinical disease (outcome) in

question as prevalence of both dementia and cognitive impairment increases significantly after 65 years

of age, making risk assessment in that age group less reliable and non-representative for majority of

general population (Kalantarian et al 2013).

45

The cut-off point of 65 years, although commonly mentioned in the literature, is somewhat arbitrary

and should be interpreted as such. Considering that chronic diseases such as dementia take decades to

develop, individuals may remain clinically asymptomatic for a long time. This may also apply to

individuals younger than 65 years.

The subdomain of random or non-random selection was stratified as such, due to inherent limitations of

non-randomized subject selection such as reduced validity and limitations encountered in

generalization of findings. Lastly, adequate cut-off for sample size was established at 1000, as cohort

studies require larger sample size as compared to case-control studies to convey same degree of

reliability that a case-control study would render with a smaller sample. Secondly, cohort studies

evaluate rate of outcome rather than prevalence of outcome, which is much smaller than prevalence and

thereby larger sample size is required in cohort studies to yield reliable findings (Tanaka et al. 2015).

Each study was graded as either “GOOD”, “MODERATE” or “LOW” depending on the following

criteria:

• Age ≤65 years AND random selection AND sample size>1000 = Good (G)

• At least two out of: Age ≤65 years, random selection, sample size >1000 = Moderate (M)

• At least two out of: Age >65 years, non-random selection, sample size<1000 = Low (L)

Exposure assessment (Periodontitis)

The grading of this domain was based on method(s) or criteria used for the assessment of periodontitis.

Each study was graded as “GOOD”, “MODERATE” or “LOW” for this domain.

a. GOOD: Studies with clinically-diagnosed periodontitis using standardized method of

periodontal examination such as measurement of periodontal pocket depths (PPDs) and/or

Clinical attachment loss (CAL) and/or alveolar bone loss (ABL) or as per the criteria

highlighted in ICD.

b. MODERATE: Studies with clinically-diagnosed periodontitis using other non-specific objective

measures of periodontal health like Gingival bleeding index (GBI), Plaque control index (PCI)

and number of missing teeth recorded by dentist or other dental medicine professional.

c. LOW: Studies that assessed periodontal status based on self- reported data such as tooth count

or presence of gingival bleeding.

46

Assessment of the Outcome (Dementia and Cognitive impairment)

Studies with dementia as the outcome were grouped separately from those studies that assessed

periodontitis and cognitive impairment. The domain of outcome assessment was graded as either

“GOOD” or “LOW”.

a. GOOD: Studies that used standard diagnostic criteria as underlined in DSM or ICD to infer

diagnosis of dementia. In case of cognitive impairment validated diagnostic criteria signified

use of standardized cognitive tests, such as MMSE, to determine the presence and degree of

cognitive impairment.

b. LOW: Studies that did not diagnose outcome(s) of interest by employing standard diagnostic

criteria or used poorly defined diagnostic criteria.

Length of follow-up period / Study duration

Although there is no standard study duration for optimal assessment of dementia risk factors, in general

studies with longer study duration in the range of decades provide more reliable scientific evidence as

compared to studies of shorter duration (Vincent et al. 2012). The following assessment was used for

study duration:

a. GOOD: Studies that had a follow up period of 20 or more years.

b. MODERATE: Studies with a follow-up period of 10-19 years.

c. LOW: Studies with less than 10 years of follow-up period.

Loss of follow-up/ Drop out

Attrition is another important aspect that defines the quality of a longitudinal study. Higher degree of

participant drop-out yields lower degree of reliability to the findings. Subsequently, a study may fail to

add intended knowledge to the body of evidence and answer the question of interest (Hill et al. 2016).

Significant loss to follow up could indicate differences between participants, and thus lead to

overestimation of the effect of exposure onto the outcome (Howe et al. 2013).

Considering the outcomes under study and mean age of participants, each study was graded as

“GOOD”, “MODERATE” or “LOW” as per the following criteria:

a. GOOD: Studies with dropout of 20% or less.

47

b. MODERATE: Studies with drop-out of 20-40%.

c. LOW: Studies with more than 40% drop-out.

Overall quality of evidence

Cumulative grading for overall quality of a study was derived by summation of grades in individual

domains for respective studies. Each study was graded as either “GOOD”, “MODERATE” or “LOW”

for overall quality. The overall grading for each study was derived as follows:

a. GOOD: “GOOD” in all major domains and “GOOD” or “MODERATE” in minor domain.

b. MODERATE: “GOOD” or “MODERATE” in all major domains but does not meet the criteria

for good quality of evidence.

c. LOW: “LOW” in at least one major domain.

4 RESULTS

The specific search strategy produced 46 articles. After reviewing through the abstracts of each article

31 studies were identified. After going through the full text, 10 articles fulfilled the inclusion criteria

(Figure 1). Five of these studies had dementia as the outcome (Stein et al. 2007, Arrive et al. 2012,

Tzeng et al. 2016, Lee YL et al 2017, Lee YT et al. 2017), while five studies assessed association

between periodontitis and cognitive impairment (Kaye et al. 2010, Reyes-Ortiz et al. 2013, Okamoto et

al. 2015, Naorungroj et al. 2015, Okamoto et al. 2017). The reference list of each study was hand-

searched in order to capture any potential study that may have been missed by the adopted search

strategy.

48

Figure 1: Search Results (Prisma flow diagram)

Records identified through database

searching

(n = 46)

Sc

reen

ing

In

clu

ded

Elig

ibili

ty

Iden

tifi

cati

on

Additional records identified through

other sources

(n = 0)

Records after duplicates removed

(n = 46)

Records screened

(n = 46)

Records excluded

(n = 15)

Full-text articles assessed for

eligibility

(n =31)

Full-text articles excluded,

with reasons

(n = 21)

Studies included in

qualitative synthesis

(n = 10)

49

4.1 STUDIES WITH DEMENTIA AS THE OUTCOME

The studies assessing the association between periodontitis and dementia are given in Table 5.

4.1.1 Designs and settings

All five studies were population based, longitudinal studies (Stein et al. 2007, Arrive et al. 2012, Tzeng

et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017). Two studies were prospective cohorts (Arrive et

al. 2012, Lee YT et al. 2017) and three were retrospective studies (Stein et al. 2007, Tzeng et al. 2016,

Lee YL et al. 2017). Three studies were from Taiwan (Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et

al. 2017), one from France (Arrive et al. 2012) and one from US (Stein et al. 2007). Four studies had

both male and female participants (Arrive et al. 2012, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et

al. 2017), whereas one study had female participants only (Stein et al. 2007).

All three studies from Taiwan based their investigation on data from National health insurance research

database (NHIRD) of Taiwan (Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017). The study

from France recruited participants from Paquid dental study (Arrive et al. 2012), and study from US

was based on participants from NUN study (Stein et al. 2007).

4.1.2 Study population and duration

Three studies were conducted on participants who were 65 years or older (Stein et al. 2007, Arrive et

al. 2012, Lee YT et al. 2017), while two studies adopted more diverse age criterion (Tzeng et al. 2016,

Lee YL et al. 2017), with one cohort comprising of 45 years or older participants (Lee YL et al. 2017),

while one had participants aged 20 years or more (Tzeng et al 2016).

Two studies had a sample size of less than 500 participants (Stein et al. 2007, Arrive et al. 2012), while

sample size of two studies lied between 5000 and 10,000 participants (Tzeng et al. 2016, Lee YT et al.

2017). One study had a sample size of more than 180,000 participants (Lee YL et al. 2017).

Three studies had a follow-up period of 10 years (Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al.

2017), whereas one study had a follow-up period of 12 years (Stein et al. 2007) and one 15 years

(Arrive et al 2012).

50

4.1.3 Periodontitis assessment

All five studies defined periodontitis as deterioration of tooth supporting tissues (Stein et al. 2007,

Arrive et al. 2012, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017). In general, multiple

measures such as tooth loss and PPDs were used to assess periodontal health. Three studies assessed

periodontitis according to ICD criteria based on PPDs and other objective measures (Tzeng et al. 2016,

Lee YL et al. 2017, Lee YT et al. 2017), while two studies used multiple oral health measures (Stein et

al. 2007, Arrive et al. 2012). One study also used a questionnaire to supplement findings of objective

measures (Arrive et al. 2012).

4.1.4 Dementia assessment

Two studies used DSM criteria for the assessment of dementia (Arrive et al. 2012, Tzeng et al. 2016).

One of these two studies diagnosed dementia according to DSM-IV R criteria (Tzeng et al 2016), while

one used DSM- III R (Arrive et al 2012). Two studies diagnosed dementia using ICD-9 codes (Lee YL

et al. 2017, Lee YT et al 2017), while one study-based assessment of dementia on the diagnostic

criteria adopted in NUN study. NUN study based their diagnosis of dementia on cognitive test results

(MMSE, DWR, etc.) and clinical finding of memory impairment. Furthermore, diagnostic criteria of

NUN study included impairment in at least one non-memory cognitive domain and inability to perform

day to day activities (Stein et al. 2007).

In all five studies participants were thoroughly examined by specialists to reach a conclusive diagnosis

(Stein et al. 2007, Arrive et al. 2012, Tzeng et al. 2016, Lee TL et al. 2017, Lee YT et al. 2017).

Clinical findings were supplemented with neuropathological evidence where available (Stein et al.

2007).

4.1.5 Periodontitis-Dementia association

Four studies reported higher risk of dementia for individuals with poor periodontal health (Stein et al

2007, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017). One study found inverse association

between tooth loss and dementia onset, however this association only applied to subjects with lower

education (Arrive et al. 2012).

51

Three studies that used ICD criteria for periodontal assessment found that individuals with periodontitis

were significantly more likely to develop dementia as compared to those without periodontitis (Tzeng

et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017). One of these studies concluded that severity of

periodontitis may be important in determining the risk of dementia pertaining to periodontitis (Lee YL

et al. 2017). Although the study conducted by Stein et al (2007) showed a positive association between

fewer teeth and dementia, it found no association between alveolar bone loss and dementia.

52

Table 4: Studies assessing the association between Periodontitis and Dementia

Study Design and

setting

Study population Follow-

up

(years)

Periodontitis

assessment

Dementia

assessment

Results

Lee YL

et al. 2017

Lee YT et al.

2017

Retrospective

population

based,

Longitudinal

health insurance

database (LHID

2000), National

health insurance

(NHI) Taiwan.

Prospective

population

based,

182,747 participants

(97,802 participants with

dental prophylaxis,

19,674 participants with no

treatment,

59,898 with tooth

extraction,

5,373 participants with

intensive periodontal

treatment),

45 years or older

6056 participants

(3028 cases, 3028 controls),

10

10

ICD-9-CM

523.0–523.5

ICD-9-CM

codes 523.3–5

ICD-9-CM

codes (290.X,

331.0).

ICD-9-CM

codes 290.0–

290.4, 294.1,

Participants with severe

periodontitis and those without

treatment were at greater risk of

developing dementia

Reference group: participants

with dental prophylaxis.

HR: 1.14 (CI: 1.04 – 1.24) for

participants with no treatment

HR: 1.10 (CI: 1.04 – 1.16) for

participants with tooth

extraction.

HR: 1.18 (CI: 0.97 – 1.43) for

participants with intensive

periodontal treatment.

Periodontitis increased the risk

of dementia.

HR: 1.16 (CI: 1.01–1.32)

53

Tzeng et al. 2016

Arrive et al. 2012

Longitudinal

health insurance

database (LHID

2000), National

health insurance

(NHI), Taiwan

Retrospective

population

based,

Longitudinal

health insurance

database (LHID

2000), National

health insurance

(NHI), Taiwan

Prospective

population

based, Paquid

Dental study

65 years or older (median

age 74,42 years)

2,207 participants with

periodontitis and 6,621

controls,

20 years or older

405 participants (348

participants with PPDs

measurements)

66-80 years (mean age 70)

10

15

(median

10

years)

ICD-9-CM

codes: 523.4

and 523.1

Number of

teeth, and

temporo-

mandibular

joint function,

and 331.0–

331.2.

DSM-IV R

DSM-III R

Participants with periodontitis

were more likely to develop

dementia as compared to

controls.

HR: 2.54 (CI: 1.297 - 3.352), p

= 0.002

No significant associations in

participants with higher

education. However, for

participants with lower

education tooth loss seemed to

54

Stein et al. 2007

(PAQUIDENT).

France

Retrospective

analysis

of prospective

101 participants,

75 - 98 years old (mean age

84 years)

12

DMFT

(decayed,

missing, and

filled teeth

index) and

questionnaire

regarding

dental health.

For 348

dentate

participants

bleeding on

probing, PPDs

using

Community

Periodontal

Index criteria

were noted.

MMSE,

Delayed Word

Recall, Boston

have a protective effect against

dementia.

HR: 1.07 (CI: 0.57–2.02) for

participants with 11 or more

missing teeth and higher

education

HR: 0.30 (CI: 0.11–0.79) for

participants 11 or more missing

teeth and lower education

HR:) 0.42 (CI: 0.15–1.15) for

PPDs for individuals with

higher education,

HR: 0.97 (CI: 0.29–3.19) for

PPDs for participants with

lower education.

Tooth loss was associated with

increased risk of dementia.

55

study, subset of

NUN study,

convenience

sample - United

States

Naming Test,

verbal fluency

test,

Constructional

praxis test.

The diagnosis

of dementia

was based on

the criteria

used in

NUN study.

HR: 2.20 (CI: 1.1 - 4.5) for

tooth loss

HR: 2.40 (CI: 0.86-6.6) for

alveolar bone loss

OR: odds ratio, HR: hazard ratio, ICD: International Statistical Classification of Diseases and Related Health Problems, DSM: Diagnostic

and Statistical Manual of Mental Disorder

56

4.1.6 Quality assessment of studies assessing Dementia

The quality assessment of the studies assessing association between periodontitis and dementia is given

in Table 6. According to the derived criteria of quality assessment, two studies received “moderate”

grading (Arrive et al. 2012, Lee YT et al. 2017), while three studies were assigned “low” grading (Stein

et al. 2007, Tzeng et al. 2016, Lee YL et al. 2017). Two studies had moderate grading in population

representativeness (Arrive et al. 2012, Lee YT et al. 2017) while three received low grading (Stein et

al. 2007, Tzeng et al. 2016, Lee YL et al. 2017). Population representativeness turned out to be the

main difference between the five studies, as all other domains produced same grading for all five

studies.

All five studies had moderate grading in study duration, with follow up period lying between 10 and 19

years (Stein et al. 2007, Arrive et al. 2012, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017).

All five studies received good grading in domains of exposure and outcome assessment (Stein et al.

2007, Arrive et al. 2012, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017). All five studies

used standard assessment measures like PPDs to assess periodontal health, thereby they were assigned

good grading for exposure assessment (Stein et al. 2007, Arrive et al. 2012, Tzeng et al. 2016, Lee YL

et al. 2017, Lee YT et al. 2017).

Four studies assessed cognitive health and made subsequent diagnosis of dementia using the clinical

criteria in ICD or DSM, yielding good grading to each of them for outcome assessment (Arrive et al.

2012, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017). Even though one study used

cognitive tests rather than ICD or DSM criteria for outcome assessment, it also yielded good grading

for outcome assessment, as their derived criteria were similar with standardized criteria highlighted in

diagnostic manuals. Furthermore, their clinical assessment of dementia was confirmed with neuro-

pathological findings (Stein et al. 2007). None of the five studies had subject attrition or dropout of

more than 20%, thereby all five studies were graded good for minor domain (Stein et al. 2007, Arrive

et al. 2012, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017).

57

Table 5: Quality assessment of the studies assessing Dementia

Study Population

representativeness

Study

duration

Exposure

assessment

Outcome

assessment

Dropout Overall

quality of

evidence

Lee YL

et al.

2017

Lee YT

et al.

2017

Tzeng et

al. 2016

Arrive et

al. 2012

Arrive et

al. 2012

L

M

M

L

L

M

M

M

M

M

G

G

G

G

G

G

G

G

G

G

G

G

G

G

G

L

M

M

L

L

Major domains of quality assessment

1) Population Representativeness




2) Exposure Assessment

• Objective standard measurement using one or more of the following: CAL and/or PPDs,

CPITN, radiographs or using the criteria highlighted in ICD= Good (G)

• Objective measurement using non-specific oral health indexes (GBI, PCI and number of

missing teeth) = Moderate (M)

• Self-report = Low (L)

3) Length of follow up

• ≥20 years = Good (G)

• 10-19 years = Moderate (M)

• <9 years = Low (L)

58

4) Outcome Assessment

Valid if standard validated diagnostic criteria are used. If validated criteria are used it is taken

equivalent to Good (G) and if non-validated criteria are used it is taken as low (L).

Minor Domain of quality assessment

5) Drop-out

• <20% = Good (G)

• 20% to 40% = Moderate (M)

• >40% = Low (L)


• Good (G) = “Good” in all major domains, AND “good” or “moderate” in the minor domain

• Moderate (M) = “Good” or “moderate” in all major domains OR does not meet the

abovementioned requirements for good quality of evidence

• Low (L) = “Low” in at least one major domain.

59

4.2 STUDIES WITH COGNITIVE IMPAIRMENT AS THE OUTCOME

The studies assessing the association between periodontitis and cognitive impairment are given in

Table 7.

4.2.1 Design and settings

All five studies were population-based, prospective studies (Kaye et al. 2010, Reyes-Ortiz et al. 2013,

Naorungroj et al. 2015, Okamoto et al. 2015, Okamoto et al. 2017). Three studies were from US (Kaye

et al. 2010, Reyes-Ortiz et al. 2013, Naorungroj et al. 2015) and two were from Japan (Okamoto et al.

2015, Okamoto et al. 2017). Four studies had both male and female participants (Reyes-Ortiz et al.

2013, Naorungroj et al. 2015, Okamoto et al. 2015, Okamoto et al. 2017), while one study had male

participants only (Kaye et al. 2010).

The two studies from Japan used data from Fujiwara-kyo cohort (Okamoto et al. 2015, Okamoto et al.

2017), while one study from US was conducted on participants of Veterans Affairs Dental Longitudinal

Study (Kaye et al. 2010), One study had participants from a subset of ARIC study (The Atherosclerosis

Risk in Communities Study) (Naorungroj et al 2015), whereas one study was based on Mexican

American participants from the Hispanic Established Populations for Epidemiologic Studies of the

Elderly (Reyes-Ortiz et al 2013).

4.2.2 Study population and study duration

Four studies had a relatively narrow age range for participants, mainly focusing on elderly population

(Reyes-Ortiz et al. 2013, Naorungroj et al 2015, Okamoto et al. 2015, Okamoto et al. 2017). Three

studies recruited participants who were 65 years or older (Reyes-Ortiz et al. 2013, Okamoto et al. 2015,

Okamoto et al. 2017) whereas participants in one study were between 52 to 75 years at baseline

(Naorungroj et al 2015). Study from Kaye et al. (2010) adopted a wider inclusion criterion and

recruited both middle aged and young adults, with the lowest age bound of 28 years at baseline.

60

Three studies had a sample size of less than 1000 participants (Kaye et al. 2010, Naorungroj et al. 2015,

Okamoto et al. 2017), while sample size of two studies ranged between 2000 and 3500 (Reyes-Ortiz et

al. 2013, Okamoto et al. 2015). Out of the five studies, three studies had a follow-up of 5 years (Reyes-

Ortiz et al. 2013, Okamoto et al. 2015, Okamoto et al. 2017), whereas one study had a follow up of 8

years (Naorungroj et al. 2015) and one of 32 years (Kaye et al 2010).

4.2.3 Periodontitis assessment

All five studies defined periodontitis as deterioration of tooth supporting tissues (Kaye et al. 2010,

Reyes-Ortiz et al. 2013, Naorungroj et al 2015, Okamoto et al. 2015, Okamoto et al. 2017). All five

studies used tooth count for periodontal assessment (Kaye et al. 2010, Reyes-Ortiz et al. 2013,

Naorungroj et al 2015, Okamoto et al. 2015, Okamoto et al. 2017), four of which supplemented tooth

count with other measures (Kaye et al. 2010, Naorungroj et al 2015, Okamoto et al. 2015, Okamoto et

al. 2017), while study by Reyes et al (2013) had no other measure to assess periodontal health.

Four studies assessed periodontal health objectively (Kaye et al. 2010, Naorungroj et al 2015, Okamoto

et al. 2015, Okamoto et al. 2017), while one study used subjective data (Reyes-Ortiz et al. 2013). In

addition to tooth count, four studies used PPDs (Kaye et al. 2010, Naorungroj et al 2015, Okamoto et

al. 2015, Okamoto et al. 2017), while one study also had measurements on alveolar bone loss (Kaye et

al. 2010). Kaye et al (2010) also used a questionnaire to supplement findings of PPDs, ABL and tooth

count. Whereas Naorungroj et al (2015) conducted an interview as part of exposure assessment in

addition to objective measures of PPDs and tooth count.

4.2.4 Cognitive impairment assessment

In three studies cognitive decline was the outcome. Cognitive decline was defined as change in

cognition over time and was measured as the difference between baseline and final cognitive test scores

(Kaye et al. 2010, Reyes-Ortiz et al. 2013, Naorungroj et al. 2015). Two studies defined outcome as

mild memory impairment (MMI). In these studies, MMI referred to decline or impairment of memory

while other cognitive domains remain intact. Furthermore, it was treated as a milder form of cognitive

deterioration as compared to MCI (Okamoto et al. 2015, Okamoto et al. 2017). One of these studies

analyzed MMI as the only outcome measure (Okamoto et al. 2017), while the other study also included

cases of MCI in secondary analysis (Okamoto et al. 2015).

61

All five studies assessed cognitive status objectively by means of standardized cognitive tests (Kaye et

al. 2010, Reyes-Ortiz et al. 2013, Naorungroj et al 2015, Okamoto et al. 2015, Okamoto et al. 2017).

Four studies used more than one cognitive test (Kaye et al. 2010, Naorungroj et al 2015, Okamoto et al.

2015, Okamoto et al. 2017), while one study employed only one cognitive test for outcome assessment

(Reyes-Ortiz et al. 2013). MMSE was the most commonly used cognitive test, employed by four of the

five studies (Kaye et al. 2010, Reyes-Ortiz et al. 2013, Okamoto et al. 2015, Okamoto et al. 2017),

whereas three studies used recall test (Okamoto et al. 2015, Naorungroj et al. 2015, Okamoto et al.

2017).

4.2.5 Periodontitis-Cognitive impairment association

Overall results were conflicting on the association of periodontitis and cognitive impairment. The

overall quality of evidence was low. Four studies did indicate positive association between low tooth

count and cognitive impairment (Kaye et al. 2010, Reyes-Ortiz et al. 2013, Okamoto et al. 2015,

Okamoto et al. 2017). One of these studies reported positive association only in the subjects with

positive status for ApoE ε4 (Kaye et al. 2010), while one reported positive association between rate of

tooth loss and cognitive decline (Okamoto et al. 2017).

Two studies reported positive association between low tooth count and cognitive decline (Kaye et al.

2010, Reyes-Ortiz et al. 2013). One study reported positive association between low tooth count and

MMI (Okamoto et al. 2017), while one study reported positive association between low tooth count and

MMI and MCI (Okamoto et al. 2015). The study conducted by Naorungroj et al (2015) reported higher

risk of cognitive decline in individuals with complete tooth loss.

Four studies analyzed association between PPDs and cognitive impairment (Kaye et al. 2010,

Naorungroj et al. 2015, Okamoto et al. 2015, Okamoto et al. 2017). Three of these studies showed no

association between PPDs and cognitive impairment either with cognitive decline (Naorungroj et al.

2015) or with MMI (Okamoto et al. 2017) or MMI and MCI (Okamoto et al. 2015). However, study

conducted by Kaye et al (2010) observed positive association between PPDs and cognitive decline.

62

Furthermore, it also reported higher risk of cognitive decline as a function of alveolar bone loss (Kaye

et al. 2010)

63

Table 6: Studies assessing the association between Periodontitis and Cognitive impairment

Study Design and

setting

Study

population

Follow-up

(years)

Periodontitis

assessment

Cognitive

impairment

assessment

Results

Okamoto

et al. 2017

Prospective

population based,

Fujiwara-kyo

study, Japan

537

participants

(179 cases,

358

controls),

65 years or

above.

5

Tooth count and

PPDs using

Community

Periodontal Index

criteria.

Mild memory

impairment

(MMI) -

(MMI was

defined as no

impairment of

ADL, normal

general cognitive

function: MMSE

score ≥24,

presence of

objective memory

impairment

Recall test, score

≤ 1, and absence

of depression)

MMSE and

Recall test.

No association between PPDs and MMI.

Reference group: PPDs: CPI codes (0-3)

and absence of ApoE ε4.

OR: 0.96 (CI: 0.37–2.45) for code 4 and

presence of ApoE ε4

OR: 0.73 (CI: 0.43–1.25) for code 4 and

absence of ApoE ε4

OR: 1.01 (CI: 0.56–1.83) for code (0-3)

and absence of ApoE ε4

No significant association between tooth

loss and MMI, although presence of ApoE

ε4 modulated the effect of tooth loss on

MMI

Reference group: 9 or more teeth

remaining and absence of ApoE ε4.

OR: 0.99 (CI: 0.58–1.68) for 9 or less teeth

remaining and presence of ApoE ε4.

64

Okamoto

et al. 2015

Prospective

population based,

Fujiwara-kyo

study, Japan

2158

participants.

(2335 total,

177

edentulous),

65 years or

older.

5

Tooth count and

PPDs using

Community

Periodontal Index

criteria.

Mild memory

impairment

(MMI)

MMI: normal

cognitive

function, no

functional

incapacitation but

deterioration of

memory as

assessed by the 3-

word delayed

recall test in

MMSE - “MMI

status,” MMSE

score of 24 or

more, plus Recall


remaining and presence of ApoE ε4


remaining and absence of ApoE ε4.

Significant association between having

17–24 remaining teeth and MMI, and total

tooth loss (edentulism) and MMI. No

association between PPDs and MMI.

OR: 1.04 (0.74–1.47) for PPDs

Reference group: 25 or more teeth

remaining.

OR: 1.58 (1.12–2.25) for 17-24 teeth

present

OR: 1.17 (0.73–1.88) for 9-16 teeth

present

OR: 1.08 (0.64–1.80) for 1-8 teeth present

65

Naorungroj

et al. 2015

Prospective

population based,

Subset of ARIC

study, United

States

785

participants,

558 with

PPDs

assessment.

52–75 years

8

Self-reported tooth

count, PPDs,

bleeding on

probing, interview,

collection of

gingival crevicular

fluid and dental

plaque

Periodontal disease

was classified

according to

Biofilm gingival

interface index

score of or 1, and

GDS (Geriatric

Depression Scale

) score of 5 or

lower.

MMSE and

Recall test. DSM

R3rd edition.

Cognitive decline.

Delayed Word

Recall (DWR),

Digit Symbol

Substitution

(DSS) and Word

Fluency (WF)

test.

Tooth loss and periodontal disease did not

predict greater cognitive decline.

The exposure-outcome association was

presented as a change in cognitive test

scores against oral health measures

Beta estimate for PPDs (severe

periodontitis) with corresponding standard

error and p values:

DWR: −0.16 (SE: 0.21), p = 0.6040

DSS: −0.28 (SE: 1.56), p = 0.5165

WF: −0.50 (SE: 1.79), p = 0.6225

66

Reyes-

Ortiz et al.

2013

Prospective

population based,

Mexican

Americans

participants,

Hispanic

Established

Populations for

Epidemiologic

Studies of the

Elderly (Hispanic

EPESE), United

States.

3032

participants

(1967

participants

in the final

wave)

65 years or

older

5

classification that

comprises of PPDs

and bleeding on

probing to

conclude presence

and extent of

periodontitis.

Self-reported tooth

count

Cognitive decline.

MMSE.

Beta estimate for PPDs (severe

periodontitis) with corresponding standard

error and p values as a function of time:

DWR: 0.45 (SE: 0.27), p = 0.5655

DSS:0.55 (SE: 1.14), p = 0.7636

WF: −0.96 (SE: 1.17), p = 0.2173

Fewer teeth was associated with greater

cognitive decline over time as assessed

through drop in MMSE score.

Estimate change in MMSE over five year

follow up period, negative sign indicates

decline.

Estimate= -0.12, (SE ± 0.05, p <0.01) for

overall drop in MMSE score.

67

Kaye et al.

2010

Prospective

population based,

Veterans Affairs

Dental

Longitudinal

Study.

(convenience

sample, men only

study), United

States

597

participants,

28–70 years

32 PPDs, radiographic

alveolar bone

height, tooth count,

new caries and

restorations.

Additionally, a

questionnaire

regarding oral

hygiene practices

was also

administered.

Cognitive decline

– fall of cognitive

scores below the

cut-off value (25

points or less than

90% of age and

education specific

scores on MMSE

or less than 10

points on SCT).

MMSE and

Spatial Copying

Task (SCT).

Rate of tooth loss and periodontal disease

progression indicated increased risk of


Oral health measures against MMSE,

SCT:

HR: 1.03 (C:1.00 – 1.07), 1.03 (CI: 1.01,

1.06) - per additional tooth with alveolar

bone loss progression/decade (tooth loss)

HR: 1.04 (1.01, 1.09), 1.04 (1.01, 1.06) -

per additional tooth with pocket depth

progression/decade (PPDs)

HR: 1.09 (1.01, 1.18), 1.12 (1.05, 1.18) -

per additional tooth lost/decade (Alveolar

bone loss)

HR: 1.02 (0.97, 1.08), 1.05 (1.01, 1.08) -

per additional tooth with new caries and/or

restorations/decade.

OR: odds ratio, HR: hazards ratio

68

4.2.6 Quality assessment of studies assessing Cognitive impairment

The quality assessment of the studies assessing association between periodontitis and cognitive

impairment is given in Table 8. All five studies received “low” grading (Kaye et al. 2010, Reyes Ortiz

et al. 2013, Okamoto et al. 2015, Naorungroj et al. 2015, Okamoto et al. 2017). Unlike studies with

dementia, studies concerning cognitive impairment were quite dissimilar in individual domains. Two

studies received moderate grading for population representativeness (Reyes-Ortiz et al. 2013, Okamoto

et al. 2015), while three were assigned low grading (Kaye et al. 2010, Naorungroj et al. 2015, Okamoto

et al. 2017). Four studies were given low grade for study duration as each of these four studies followed

participants for less than 10 years (Reyes-Ortiz et al. 2013, Okamoto et al. 2015, Naorungroj et al.

2015, Okamoto et al. 2017) while one study received good grade for study duration, as it followed the

participants for up to 32 years (Kaye et al. 2010).

Four studies were assigned good grading for exposure assessment as they used standard measures such

as PPDs for assessment of periodontitis (Kaye et al. 2010, Okamoto et al. 2015, Naorungroj et al. 2015,

Okamoto et al. 2017), While study conducted by Reyes-Ortiz et al (2013) assessed periodontal status

subjectively and received low grade for exposure assessment. All five studies received good grading

for assessment of cognitive status. The cognitive health and subsequent diagnosis of cognitive

impairment either as cognitive impairment (MMI or MCI) or cognitive decline was made using

cognitive tests (Kaye et al. 2010, Reyes-Ortiz et al. 2013, Okamoto et al. 2015, Naorungroj et al. 2015,

Okamoto et al. 2017).

Three studies had subject attrition or dropout of less than 20% that yielded good grading for minor

domain (Kaye et al. 2010, Naorungroj et al. 2015, Okamoto et al. 2017). Whereas two studies had 20%

- 40% of subject attrition and were thus assigned moderate grading (Reyes-Ortiz et al. 2012, Okamoto

et al. 2015).

69

Table 7: Quality assessment of studies assessing cognitive impairment

Study Population

representativeness

Study

duration

Exposure

assessment

Outcome

assessment

Drop

out

Overall

quality of

evidence

Okamoto et al.

2017

Naorungroj et

al. 2015

Okamoto et al.

2015

Reyes-Ortiz et

al. 2013

Kaye et al.

2010

L

L

M

M

L

L

L

L

L

G

G

G

G

L

G

G

G

G

G

G

G

G

M

M

G

L

L

L

L

L

Major domains of quality assessment

1) Population Representativeness




2) Exposure Assessment

• Objective standard measurement using one or more of the following: CAL and/or PPDs,

CPITN, radiographs = Good (G)

• Objective measurement using non-specific oral health indexes (GBI, PCI and number of

missing teeth) = Moderate (M)

• Self-report = Low (L)

3) Length of follow up

• ≥20 years = Good (G)

• 10-19 years = Moderate (M)

• <10years = Low (L)

4) Outcome Assessment

Valid if standard validated diagnostic criteria are used.

Minor Domain of quality assessment

5) Drop-out:

• <20% = Good (G)

• 20% to 40% = Moderate (M)

70

• >40% = Low (L)


• Good (G) = “Good” in all major domains, AND “good” or “moderate” in the minor domain

• Moderate (M) = “Good” or “moderate” in all major domains OR does not meet the

abovementioned requirements for good quality of evidence

• Low (L) = “Low” in at least one major domain.

71

5 DISCUSSION

In general, periodontitis appeared to contribute to the overall risk of dementia, whereas concerning

cognitive impairment the results were less conclusive. However, lack of uniformity in the definition

and assessment criteria of periodontitis and variability in study populations hindered cumulative

assessment of studies and a more exact estimation of the effect size of periodontitis on the risk of

dementia and cognitive impairment.

Furthermore, the lack of consensus in the definition and assessment of cognitive impairment made

it difficult to assess in more detail the interplay between periodontal health and cognitive

impairment. Multiple co-factors such as age (Stein et al. 2007, Kaye et al. 2010, Reyes-Ortiz et al.

2013, Naorungroj et al. 2015, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017), systemic

diseases (Okamoto et al. 2015, Tzeng et al. 2016, Lee YL et al. 2017, Lee YT et al. 2017, Okamoto

et al. 2017) and low socioeconomic status (Arrive et al. 2012, Tzeng et al. 2016, Lee YL et al.

2017) were observed to be significant modulators of the effect of periodontitis on dementia and


5.1 STUDIES ON PERIODONTITIS AND DEMENTIA

5.1.1 Overall findings

Currently available evidence suggests a positive association between periodontitis and dementia,

with overall low to moderate quality of evidence. Four studies analyzed periodontitis in relation to

incident dementia (Stein et al. 2007, Arrive et al. 2012, Tzeng et al. 2016, Lee YT et al. 2017),

while one study assessed the possible effect of periodontitis severity on dementia risk (Lee YL et al.

2007). Though periodontitis appears to add to the overall risk of dementia, findings need to be

interpreted with caution, give the limitations of the included studies and subsequently limited

quality of evidence.

5.1.2 Measures of Periodontitis

Different measures, either individually or in combination, were used to assess periodontitis,

including periodontal pocket depth, tooth loss and alveolar bone loss. PPDs indicated a positive

association between periodontitis and dementia, whereas tooth loss provided conflicting results.

While ABL had no significant effect on risk of dementia, only one study assessed periodontal health

through alveolar bone loss (Stein et al. 2007).

72

5.1.3 Association between Periodontitis and Dementia based on periodontal pocket depths

Three studies, assessing difference in incident dementia between individuals with periodontitis and

those without, used periodontal pocket depths (PPDs) to assess periodontal status (Arrive et al.

2012, Tzeng et al. 2016, Lee YT et al. 2017). Two of these studies were of moderate quality and

both showed significant association between periodontitis and dementia (Tzeng et al. 2015, Lee YT

et al. 2017), while the remaining study rendered low quality of evidence and observed no significant

effect of PPDs on dementia (Arrive et al. 2012). Both studies that reported significantly greater risk

of dementia proposed inflammation as a possible mechanism behind the impact of poor periodontal

health on risk of dementia (Tzeng et al. 2015, Lee YT et al. 2017).

5.1.4 Association between Periodontitis and Dementia based on tooth loss

Two studies assessed periodontal status through tooth loss, with both studies providing low quality

of evidence (Stein et al. 2007, Arrive et al. 2012). One of them showed significant association

between tooth loss and dementia (Stein et al. 2007), while the other one observed no significant

effect of tooth loss on risk of dementia (Arrive et al. 2012).

Indeed, the study conducted by Arrive et al (2012) observed a protective effect of tooth loss against

dementia in individuals with lower education as compared to those with higher education. A

possible explanation for this peculiar finding was provided, i.e. the tendency among the individuals

with lower education to lose teeth earlier in life. Losing teeth earlier in life may subsequently

decrease the inflammatory burden associated with periodontitis in the long run, thereby, somewhat

decreasing the risk of dementia (Arrive et al. 2012). However, this finding should be interpreted

with caution, given that low education is a strong risk factor for dementia (Beydoun et al. 2014).

Although tooth loss is a relevant proxy measure of periodontitis, tooth loss can have other causes

such as dental caries or traumatic incidents. Therefore, conclusions regarding associations between

periodontitis and incident dementia based on tooth loss alone should be carefully drawn.

5.1.5 Comparison between results based on different measures of Periodontal health

Although only one study of low quality of evidence indicated a positive association between tooth

loss and dementia, 2 studies of moderate quality positively linking PPDs with dementia. The effect

size of tooth loss on dementia risk was of higher magnitude (Stein et al. 2007), than that observed

with PPDs (Tzeng et al. 2015, Lee YT et al. 2017).

73

Since tooth loss resulting from periodontitis is an indicator of periodontitis severity, this finding

may suggest that more severe periodontitis is associated with higher risk of dementia. A possible

mechanism could be the likelihood of increased inflammatory load due to increase in severity of

periodontitis. While edentulism (complete tooth loss), by the same principle, may significantly

lower the inflammatory burden contributed by periodontal tissue, other related factors such as

decreased masticatory stimulation and nutritional deficits may contribute to higher dementia risk. It

is also possible that the inflammatory burden produced by severe periodontitis prior to complete

tooth loss may have already triggered pathological changes leading to cognitive decline and

dementia.

However, severity of periodontitis is an important topic that should be further investigated in future

studies on risk factors for dementia and cognitive impairment. Several methodological

improvements will be needed to investigate the exact effects of tooth loss and edentulism as

indicators for severity of periodontitis. For example, comprehensive recording of the cause of tooth

loss should be undertaken, in addition to addressing the limitations of small sample size and

inadequate study design. Both cause and time-period of tooth loss should be considered and

accounted for, as the timeline of tooth loss would assist in estimating the past, present and

cumulative life-long burden of periodontal disease and their significance in determining the risk of

dementia and cognitive impairment. Another factor that should be considered is progression in

PPDs or CAL, which are more objective indicators of severity of periodontitis.

5.1.6 Severity of Periodontitis

The possible role of periodontitis in dementia as a function of its severity, and the impact of

periodontal treatment, are suggested by the study conducted by Lee YL et al (2017). They based

their evaluation on the periodontal treatment delivered to participants at the baseline, which was

representative of the severity of periodontal disease. This study observed that administration of no

periodontal treatment or dental extraction (tooth loss) at baseline was related to higher risk of

dementia as compared to dental prophylaxis or comprehensive periodontal treatment.

Individuals who required dental extraction at baseline were diagnosed with severe periodontitis.

Although the periodontal status at the end of the study was not known, such individuals may have

been more likely to develop severe periodontitis later on as well, which may explain their increased

risk of dementia. On the other hand, individuals who received no dental treatment carried a slightly

higher risk of dementia. The reasons why no or only limited dental treatment was administered are

74

not fully clear. If these individuals were diagnosed with mild periodontitis, their periodontal status

may have worsened over time due to lack of treatment, thereby leading to a greater chronic

inflammatory load. Whereas inflammatory burden may have been at least partly reduced in

individuals with dental extraction, provided that their periodontal health remained stable thereafter.

Although conclusions regarding exact mechanisms cannot be drawn from this study, it seems that

both presence of periodontitis and its severity have a role in determining overall risk of dementia.

The importance of early and adequate treatment of periodontitis is also emphasized. Differences in

the risk of dementia pertaining to past, present and cumulative life-long burden of periodontitis, as

well as quality of treatment, should be further investigated.

5.2 STUDIES ON PERIODONTITIS AND COGNITIVE IMPAIRMENT

5.2.1 Overall findings

While a few of the findings suggested that poorer periodontal health may be related to cognitive

impairment, non-significant results were reported as well (Kaye et al. 2010, Reyes-Ortiz et al. 2013,

Naorungroj et al. 2015, Okamoto et al. 2015, Okamoto et al. 2017). Three of the five studies

assessed periodontal status against cognitive decline (Kaye et al. 2010, Reyes-Ortiz et al. 2013,

Naorungroj et al. 2015), while two studies evaluated periodontal status against risk of cognitive or

memory impairment (Okamoto et al. 2015, Okamoto et al. 2017). Neither risk of cognitive decline

nor memory impairment were significantly related to poor periodontal health (Kaye et al. 2010,

Reyes-Ortiz et al. 2013, Naorungroj et al. 2015, Okamoto et al. 2015, Okamoto et al. 2017).

5.2.2 Measures of Periodontitis

Similar to the studies with dementia as the outcome, different measures including periodontal

pocket depth, tooth loss and alveolar bone loss were used to assess periodontitis either individually

or in combination. Assessment of periodontal status through PPDs against cognitive status showed

no association between periodontitis and dementia (Kaye et al. 2010, Naorungroj et al. 2015,

Okamoto et al. 2015, Okamoto et al. 2017), whereas tooth loss provided conflicting results (Kaye et

al. 2010, Reyes-Ortiz et al. 2013, Naorungroj et al. 2015, Okamoto et al. 2015, Okamoto et al.

2017). The study conducted by Kaye et al (2010) observed a positive association between rate of

alveolar bone loss and cognitive impairment. However, since this is the only study that assessed

periodontal health through alveolar bone loss, findings need to be verified in further research.

75

5.2.3 Association between Periodontitis and Cognitive impairment based on periodontal

pocket depths

Four of the five studies evaluated association between periodontitis and cognitive impairment based

on periodontal pocket depths (Kaye et al. 2010, Naorungroj et al. 2015, Okamoto et al. 2015,

Okamoto et al. 2017). Three of these studies found no correlation between PPDs and cognitive

impairment (Naorungroj et al. 2015, Okamoto et al. 2015, Okamoto et al. 2017), while one study

indicated increased risk of cognitive impairment as a function of increased rate of periodontal

pocket formation. Increased rate of periodontal pocket formation may infer presence of severe

periodontitis and/or progression in severity at a faster pace, which may lead to a greater

inflammatory burden and subsequently greater risk of dementia (Kaye et al. 2010).

5.2.4 Association between Periodontitis and Cognitive impairment based on tooth loss

All five studies assessed periodontitis through tooth loss (Kaye et al. 2010, Reyes-Ortiz et al. 2013,

Naorungroj et al. 2015, Okamoto et al. 2015, Okamoto et al. 2017), with three studies indicating

positive association between tooth loss and cognitive impairment (Kaye et al. 2010, Reyes-Ortiz et

al. 2013, Okamoto et al. 2015), while two studies observed no association (Naorungroj et al. 2015,

Okamoto et al. 2017).

Among the three studies with positive correlation between periodontitis and cognitive impairment,

one observed increased risk of cognitive impairment with higher rate of tooth loss. This may confer

significance to severity of periodontitis in affecting the risk of cognitive impairment (Kaye et al.

2010). Another study reported significantly greater risk of cognitive impairment in individuals

having 17-24 teeth in comparison to individuals with 25 or more teeth. But the effect was not

significant with extensive tooth loss (16 or less teeth present), except for complete tooth loss

(edentulism). A possible reason for this disparity in the association between extent of tooth loss and

cognitive impairment may have been the mechanisms connecting periodontal health and cognitive

impairment. And possible proportion of contribution made by each pathological mechanism relative

to time and severity of periodontitis (Okamoto et al. 2015).

One study observed significant effect of tooth loss on cognitive impairment in individuals with

ApoE ε4. The combined effect of tooth loss and ApoE ε4 was greater than the effect of either factor

alone. ApoE ε4 is an established risk factor for AD and is proposed to increase amyloid induced

inflammatory response and adversely affect the integrity of the blood-brain barrier (BBB). BBB

provides a route for systemic inflammation to directly impact the brain that may increase the

76

likelihood of developing dementia. Tooth loss, as a consequence of severe periodontitis, has been

suggested to contribute to the overall inflammatory burden (significantly added to by ApoE ε4) and

subsequent risk of cognitive deterioration.

5.2.5 Variability in Cognitive assessment

When considering cognitive impairment, multiple factors may affect the assessment of its presence,

progression and severity. Firstly, there was a lack of uniformity in definition of cognitive

impairment in the included studies, which used either mild memory impairment, mild cognitive

impairment or cognitive decline as outcomes. This lack of uniformity made comparisons of findings

between different studies difficult.

Secondly, there are no universally accepted criteria for defining cognitive impairment, with

differences between the procedures and tests employed in both research and clinical practice. This

leads to significant variability in results of studies using cognitive impairment as the outcome.

Thirdly, results from cognitive tests may be prone to misclassification (Wood et al. 2006).

Cognitive tests are sensitive to factors such as age and educational level, which increase the

difficulty of accurately assessing cognitive status and degree of cognitive impairment (Dellasega &

Morris 1993).

Given that cognition is composed of multiple domains, it cannot be properly assessed by means of a

single cognitive test (Synder et al. 2011). To better evaluate cognitive status, test batteries

comprising multiple cognitive tests need to be applied. Also, cognitive test batteries need to include

domain specific tests as well, to comprehensively assess specific cognitive domains in addition to

global cognitive status (Lancu & Olmer 2006).

5.3 MECHANISMS

Dementia is a multifactorial pathology and it is likely that multiple different causal pathways

concomitantly and/or synergistically contribute to its development. Periodontitis and dementia share

several common risk factors such as various systemic diseases, old age and smoking. This indicates

a complex interplay between multiple factors and mechanisms in determining the impact of

periodontitis on cognition. Moreover, this also underlines the possibility of common pathways

being part of the pathogenesis of periodontitis, cognitive impairment and dementia, and an interplay

between theses pathologies (Cerajewska et al. 2015).

77

Several mechanisms have been proposed to explain the contribution of periodontitis to the

development of dementia and cognitive impairment. Periodontitis may increase the risk of

neurodegeneration by contributing to the development and/or maintenance of systemic

inflammation. Systemic inflammation is an independent determinant of risk of cognitive

deterioration and has been suggested to facilitate the development of neuroinflammation.

Neuroinflammation is considered to be one of the central events in the pathogenesis and progression

of cognitive deterioration (Gallart-Palau et al. 2017).

Periodontal pathogens are a source of constant low-grade bacteremia and subsequent trigger for the

expression of proinflammatory cytokines. This low-grade focal inflammation constantly trickles

into systemic circulation adding to the systemic inflammatory load produced by other chronic

diseases such as CVDs and diabetes (Hajishengallis 2015). Periodontitis is independently associated

with increasing systemic concentration of pro-inflammatory cytokines, evident by increased

expression of systemic inflammatory markers such as C reactive protein (CRP) and tumor necrosis

factor alpha (TNF-α) (Nilsson et al. 2017).

Systemic cytokines are known to cross the blood brain barrier (BBB) and elicit inflammatory

response from glial cells. These systemic cytokines are suggested to either stimulate the glial cells

to produce neuroinflammation by the release of local inflammatory mediators or add to the already

existing inflammation elicited by other risk factors (Hasturk & Kantarci 2014). Inflammatory

cytokines were also proposed to trigger production of β-amyloid protein and promote

phosphorylation of tau protein, linking inflammation to protein accumulation and subsequent

neurodegeneration (Cai et al. 2014).

Moreover, cytokines were suggested to facilitate neurodegenerative processes by multiple other

mechanisms, such as, by causing direct neuronal damage and by increasing the permeability of

BBB. The weakening of BBB has been suggested to provide direct access to periodontal pathogens

and their products to the brain. Periodontal pathogens were proposed to be directly detrimental to

brain, by starting a cascade of pathological changes leading to neuroinflammation and potentially

neurodegeneration (Cai et al. 2014).

Other significant pathological changes brought about by the inflammatory process that may

contribute to the development of cognitive impairment include decrease in the concentration of

acetylcholine and increased expression of reactive oxygen species (ROS). Inflammatory cytokines

78

were found to significantly decrease the concentration of acetylcholine, both by inhibiting its

production and by facilitating its breakdown. Increased expression of ROS was associated with

deterioration of neuronal function, while reduction in the concentration of acetylcholine was

suggested to produce atrophic changes in the brain (Cunningham 2013).

Tooth loss, a direct consequence of severe periodontitis, also independently increases the risk of

dementia and cognitive impairment (Nilsson et al. 2014). Tooth loss may result in chronic

nutritional deficits such as deficiency of Vitamin B, Vitamin E and antioxidants that adversely

affect cognition, and, in the long run increase the risk of dementia. Furthermore, tooth loss was

suggested to be directly detrimental to cognitive health by facilitating the development of atrophic

changes in the brain. These atrophic changes are believed to result because of reduction in sensory

input from masticatory apparatus (Kobayashi et al. 2018).

This is consistent with animal studies showing development of learning and memory deficits as a

function of decreased masticatory stimulus due to tooth loss. Reduced brain stimulation has also

been found to decrease the number of pyramidal cells in the brain leading to reduced acetylcholine

levels in hippocampus and subsequently to memory deficit (Minn et al. 2013). Tooth loss was also

associated with decreased cerebral blood flow and was found to affect oxygen concentration in the

blood. Such changes in the cerebral circulation are also suggestive of adverse effects of tooth loss

on brain (Tonsekar et al. 2017).

Another pathway through which periodontitis may contribute to cognitive deterioration is through

the direct involvement of periodontal pathogens. Periodontal pathogens and their products may

directly transmigrate through the blood brain barrier and invoke neuroinflammation. Periodontal

pathogens are also believed to reach the brain through nerve plexus in the head region such as

through the trigeminal nerve (Shoemark & Allen 2015). However, an infectious etiology of

cognitive impairment and dementia seems to be a rather distant possibility particularly through

periodontal pathogens, considering their relatively limited virulence, and the scarce amount of

evidence supporting this hypothesis (Shaik et al. 2014).

However, the continuous presence of periodontal pathogens throughout life and subsequent constant

presence of low-grade inflammation in periodontal tissues lends a certain degree of support to the

possible role of periodontal pathogens in the overall risk of dementia. Periodontal pathogens have

also been suggested to directly stimulate the innate immune system and glial cells to mount an

79

inflammatory response. Glial cells have an important role in the induction and maintenance of

neuroinflammation. The glial cells in the elderly have been found to be hypersensitive and liable to

produce an exaggerated inflammatory response, which is a common pathological trait for both

periodontitis and dementia (Harding et al. 2017).

Studies have also observed increased expression of neurofibrillary tangles in mice, owing to

lipopolysaccharide (LPS) induced chronic inflammation. LPS is a component of bacterial cell wall

and its ability to effect protein metabolism in the brain supports a possible contribution of bacterial

infection in the overall risk of neurodegeneration (Gurav 2014). Other possible pathways through

which periodontal pathogens were proposed to increase the risk of dementia include increased

expression of reactive oxygen species. Moreover, initial studies also suggest that periodontal

pathogens might modulate the risk of dementia and cognitive impairment through their effects on

adaptive immune system and host gene expression (Olsen et al. 2016, Carter et al. 2017). However,

further studies are needed to clearly understand the role of periodontal pathogens in

neurodegeneration and the exact mechanism by which periodontal health impact cognition.

5.4 STRENGTHS AND LIMITATIONS

To the best of our knowledge, this is the first review to assess the association between periodontitis

and dementia based specifically on longitudinal studies. Secondly, this review also evaluates quality

of evidence based on the risk of bias in each study. Another strength of this review is the

assessment of association between periodontitis and cognitive impairment. The inclusion of

cognitive impairment enables a clearer assessment of the possible impact of poor periodontal health

on the continuum of cognition.

However, the limited number of available studies, variability in the definition and assessment of

exposure and outcome and inconclusiveness of available evidence strongly supports the need for

further studies to understand the links between periodontitis, cognition and dementia.

There is a possibility that some studies may not have been captured by the adopted search strategy,

due to two main reasons. Firstly, the search strategy was limited to PubMed and Scopus, and

secondly, search strategy was applicable to English language publications only. Furthermore, due to

lack of validated assessment tools for quality assessment of longitudinal studies, assessment criteria

were tailored for this review. This is inherently prone to limitations, such as limited consideration of

measures relating to internal validity of studies.

80

Moreover, meta-analysis of the included studies was not conducted which may have been more

informative in highlighting the effect of poor periodontal status on the continuum of cognition. The

conductance of meta-analysis was deterred in part due to the variability in the assessment methods

used to evaluate periodontal health as well as cognitive impairment. Furthermore, studies with

cognitive impairment also lacked uniformity in terms of definition of the outcome of interest

making statistical comparison difficult. Additionally, because of limited number of studies and

heterogeneity in study populations meta-analysis was not undertaken.

5.5 CONCLUSION AND FUTURE DIRECTIONS

Due to limitations pertaining to each included study and the overall quality of evidence, the role of

periodontitis in the development of dementia and cognitive impairment needs to be further

explored. Nevertheless, it seems likely that periodontitis contributes to the overall risk of dementia

and may even elevate the risk of cognitive impairment. Therefore, further well-designed

longitudinal studies of adequate size and duration should be conducted to explore in more detail the

magnitude of the effects and the underlying mechanisms. Comprehensive assessment of

periodontitis, such as through use of multiple assessment measures including CAL, should be

included in future studies.

Future studies should also consider various aspects of periodontitis such as its severity and past,

present, and the cumulative burden of poor periodontal health, as possible factors affecting

cognitive health. If possible, recording of both extent and cause of tooth loss should be carried out

to better determine the extent of periodontal disease, and separately evaluate the effects of tooth loss

as a consequence of periodontal disease and as an independent determinant of cognitive health. Any

teeth replacement such as dentures and implants need to be noted, and their effects evaluated.

Concerning cognitive impairment as outcome, comprehensive assessment of cognition should be

carried out through test batteries instead of single tests. Cognitive outcomes will need to be well

defined according to standardized criteria to allow for comparisons to be made. Specific cognitive

domains should be assessed in addition to global cognition, in order to determine potential effects of

periodontitis on various cognitive domains. Such analyses may also facilitate in distinguishing the

effects of periodontitis on various types of dementia.

81

It is likely that multiple pathological pathways are involved in conferring increased risk of dementia

and cognitive impairment due to periodontitis. Among the most probable of these pathways is

progression of localized periodontal inflammation into systemic inflammation. Systemic

inflammation, together with other comorbidities, may elicit or add to neuroinflammation that

eventually may lead to dementia. For example, increased concentration of inflammatory markers

such as C reactive protein and interleukin-6 (IL-6) have been associated with both periodontitis and

dementia.

However, well-designed longitudinal studies evaluating changes in inflammation markers in

relation to periodontitis and cognition have not been conducted. Therefore, thorough evaluation of

inflammation markers at multiple time points during the course of the study, should be undertaken

in future studies to clarify the mechanisms by which periodontitis contributes to neurodegeneration.

Furthermore, nutritional deficits as a function of tooth loss should be considered in relation to

cognitive deterioration, as well as the impact of teeth replacement.

Additionally, the impact of periodontitis on risk of progression of cognitive impairment to dementia

should be analyzed. This may facilitate in outlining the timeline, interplay of various confounders

and magnitude of impact that periodontitis has on the overall risk and development of dementia.

Both dementia and cognitive impairment are projected to increase significantly in the next few

decades. Periodontitis is now widely accepted to be more than a passive determinant of general

health, and this review adds to previous literature indicating a possible contribution of periodontitis

to the overall risk of dementia and cognitive impairment. Since periodontitis is a preventable

disease, preventive strategies for cognitive deterioration incorporating prevention and management

of periodontitis could be effectively designed to reduce the risk of cognitive impairment and

dementia.

Since periodontitis shares multiple risk factors with dementia, its prevention may have broader

effects on the risk of dementia by reducing other common risk factors. More studies investigating

various dimensions of the periodontitis-cognition association, such as severity of periodontitis,

direct role of periodontal pathogens and possible interplay between different pathological pathways

must be carried out to conclusively determine the nature and extent of association between

periodontitis and cognitive deterioration.

82

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