Introduction: The connection between periodontitis and mild cognitive impairment (MCI) continues to receive attention. However, whether periodontitis is a risk factor for MCI remains still uncertain. This study aims to systematically analyze the available literature regarding the relationship between periodontitis and the risk of developing MCI and whether the periodontal health of MCI patients is poorer. Methods: A literature search of PubMed, Scopus, Embase, and Web of Science databases was conducted to include all studies on the relationship between periodontitis and MCI from inception to April 2023. The studies were independently screened by 2 researchers, and those meeting the inclusion criteria were extracted and cross-checked. Pooled odds ratio (OR) or mean difference (MD) with 95% confidence intervals (CI) was calculated using either a fixed-effects or random-effects model. Results: Seven studies with a total of 3,973 participants were included. Meta-analysis results showed a statistically significant higher incidence of MCI in patients with periodontitis (OR, 1.70 (95% CI: 1.24–2.32, p < 0.001) compared to healthy participants. A subgroup meta-analysis showed that the pooled OR for the risk of MCI in patients with severe periodontitis was 2.09 (95% CI: 1.49–2.92, p < 0.001). In addition, attachment loss (MD = 0.44, 95% CI: 0.12–0.75, p < 0.001) and plaque index (MD = 0.72, 95% CI: 0.50–0.93, p < 0.001) were higher in MCI patients compared with the control group, but the pocket probing depth (MD = 0.21, 95% CI: −0.08 to 0.49, p = 0.15) was not significantly different between the two groups. Conclusions: Patients with periodontitis are at a higher risk of developing MCI, and the periodontal health of MCI patients is generally compromised. However, further well-designed studies should be conducted to confirm this relationship between MCI and periodontitis.

Mild cognitive impairment (MCI) can be defined as a progressive decline in memory or other cognitive functions that does not interfere with the ability to perform daily living activities and does not meet the diagnostic criteria for dementia, and it is widely regarded as an intermediate state of cognitive function between normal aging and dementia [1]. MCI is at risk of conversion to dementia, especially Alzheimer’s disease (AD) [2]. A systematic review found that 19% of patients with MCI would convert to AD within 1 year [3]. Undoubtedly, the burden on the health care system and the global financial cost would be increased due to the growing number of people suffering from dementia. To date, the specific pathogenesis of MCI is unknown, and specific treatments for this disease are lacking [4]. Therefore, more interventions are needed to stop its progression towards dementia by enhancing the identification of risk factors for MCI. Risk factors with strong evidence include age, gender, smoking, dietary habits, diabetes, severe cardiovascular disease, and so on [5, 6]. In addition, recent studies have shown that chronic inflammatory states play an important role in the development of MCI [7], and as a result, the relevance of various chronic inflammatory diseases such as periodontitis to MCI is of increasing interest.

Periodontitis is a chronic infectious disease that manifests as the progressive destruction of the supporting tissues of the teeth [8]. Advanced periodontitis will lead to loosening and loss of teeth, and it causes a significant reduction in quality of life [9]. In addition to being closely related to systemic health conditions, periodontitis is a risk factor for many systemic diseases such as diabetes and cardiovascular disease [10, 11]. A correlation between periodontitis and AD has been reported [12]. Several studies in recent years have suggested that there is an association between periodontitis and MCI [13, 14], while periodontitis may affect the development of cognitive impairment through various mechanisms. A meta-analysis in 2021 that included 20 observational studies showed an odds ratio (OR) of 1.77 (95% confidence interval [CI]: 1.31–2.38) for periodontitis and cognitive impairment, suggesting a correlation between periodontitis and cognitive impairment [15]. However, it has also been suggested that the link between periodontitis and MCI may not be strong enough [16]. An interesting thing about MCI is that in some early studies, it was found that people with MCI had some chance of returning to a normal cognitive state [17‒19]. Fortunately, periodontitis may be avoided with proper brushing, and if it has already started, there are efficient therapies for managing it [20]. Considering the treatability of periodontitis and the reversibility of MCI, it is necessary to conduct a correlation analysis between periodontitis and MCI. This study aimed to investigate the relationship between periodontitis and MCI based on a systematic review and meta-analysis following the PRISMA statement [21].

Protocol and Registration

This systematic review was registered in the PROSPERO (https://www.crd.york.ac.uk/PROSPERO/), under registration number CRD42023395297.

Search Strategy

Studies were conducted in April 2023 using PubMed, Scopus, Embase, and Web of Science databases, with no date or language restrictions. All studies identified were independently screened by two investigators, and conflicts were adjudicated by a third investigator. For each database, the search terms included periodontitis, periodontal diseases, periodontal infection, tooth loss, oral health, mild cognitive impairment, cognitive decline, cognitive dysfunction, poor cognitive function, cognitive defect, and mild memory impairment. The MeSH terms, keywords, and detailed search strategies were appropriately adapted for each database using the Boolean operators to combine the searches. The search string of each database is shown in online supplementary Table 1 (for all online suppl. material, see https://doi.org/10.1159/000535776). In addition, references to relevant articles were also manually searched to increase the number of included studies. No gray literature was retrieved in our study.

Inclusion and Exclusion Criteria

Studies were selected based on the following PECO outline: population (P): adults; exposure (E): periodontitis diagnosis based on widely used criteria or clinical periodontal parameters, including pocket probing depth (PPD), clinical attachment loss (CAL), plaque index (PI), community periodontal index, bleeding on probing, and so on; comparison (C): an individual without periodontitis; outcome (O): MCI diagnosis based on widely used criteria or reliable cognitive tests (no distinction between exposure and outcome in cross-sectional studies); study (S): observational studies.

Exclusion criteria were as follows: (i) studies written in a language other than English; (ii) studies involving duplication of data or providing incomplete data; (iii) study subjects having received systematic treatment for periodontitis or MCI within 6 months; (iv) no clear diagnosis of periodontitis or MCI; (v) review articles, case reports, animal studies, basic experimental studies, and articles that do not include the results of interest.

Quality Assessment

The quality and bias risk of included studies were independently evaluated by two investigators. Cohort and case-control studies were conducted with the “Newcastle-Ottawa Scale” (NOS) [22], and studies with NOS scores of 1–3, 4–6, and 7–9 were judged to be of low, moderate, and high quality, respectively. Cross-sectional studies were conducted with the “cross-sectional study evaluation standard of the American Agency for Healthcare Research and Quality” (AHRQ), which defines the studies with scores of 0–3, 4–7, and 8–11 as low, medium, and high quality, respectively. Any disagreement during the quality evaluation will be resolved by a third investigator.

Data Extraction and Collection

After selection, the following data were extracted from the included articles: (i) basic characteristics of the included studies, including the first author’s name, title, published year, country, and study design; (ii) sample size, age of participants; (iii) diagnostic criteria for diseases and the basis for grouping; (iv) required observed indicators, measurement outcome data, and effect values.

Statistical Analysis

Statistical analysis was performed using RevMan 5.4 software. The heterogeneity test was performed first, and in the case of small heterogeneity (p > 0.1 and I2 ≤50%), a fixed-effects model was used [23]. The random-effects model was used in the case of large heterogeneity (p ≤ 0.1 or I2 >50%). Based on the extracted information, the effect values and their 95% CI were collated. The combined effect values and 95% CI were calculated using ORs for dichotomous variables and means and standard deviations for continuous variables, and forest plots were drawn. A funnel plot would be used to assess publication bias when there were more than 10 studies in this meta-analysis [24]. Sensitivity analysis would be performed by serially removing one study at a time to investigate the influence of a single study on the whole results.

Search Results

After extensively searching Pubmed, Scopus, Embase, and Web of Science databases and retrieving the references of relevant articles, we found 4,247 studies, of which 1,268 were duplicates and were excluded. In addition, 2,812 articles were excluded because they were irrelevant to the research theme. The remaining 167 articles were read in full text, of which 160 articles were excluded for various reasons. Finally, seven articles were included in this study (Fig. 1).

Fig. 1.

Flow diagram for search and selection of the included studies.

Fig. 1.

Flow diagram for search and selection of the included studies.

Close modal

General Characteristics of the Included Studies

As shown in Table 1, four case-control studies [13, 16, 25, 26] and three cross-sectional studies [27‒29] were included in this study. Two were from Sweden, two from China, and one each from Brazil, Japan, and the USA. Two of them were evaluated as high quality, and the rest were of moderate quality. Detailed assessments for the risk of bias are shown in the online supplementary Tables 2 and 3. Fewer than 10 studies were included, so it is difficult to quantify the publication bias.

Table 1.

General characteristics of the included studies

Author (year, country)Study designParticipants/controlFemale% /controlMean age /controlDiagnostic criteria for periodontitisDiagnostic criteria for MCIAdjustment factorsNOS/AHRQ score
Holmer et al. [13] (2018, Sweden) Case-control study 50/76 49.0/56.6 70/67 BOP, PPD, and MABL The Winblad criteria Age, gender, marital status, education, smoking, body mass index, and diabetes mellitus 
Yang et al. [27] (2021, China) Cross-sectional study 36/35 38.9/37.1 75.42±7.77/74.11±6.25 The fifth edition of the World Health Organization “Oral Health Surveys Basic Methods” NINCDS-ADRDA Matched: age, body mass index, sex, and education 
Jockusch et al. [28] (2021, Sweden) Cross-sectional study 29/26 62.1/50 80/75 PSI and BOP MMSE 
Gil-Montoya et al. [25] (2015, Spain) Case-control study 21/229 67.2/55.9 77.0±7.8/78.5±7.9 PPD, CAL, PI, and BOP The Spanish criteria Age, sex, oral hygiene habits, and educational level 
Cestari et al. [16] (2016, Brazil) Case-control study 19/21 68.4/66.7 73.11±6.79/75.33±5.75 PPD and CAL NINCDS-ADRDA Matched: educational status, age, gender, and the prevalence of hypertension and diabetes 
Okamoto et al. [29] (2010, Japan) Cross-sectional study 93/3,208 31.4/51.7 74.0/71.0 CPI MMSE Depressive symptoms, sex, age, length of education, and other variables 
Zhu [26] (2019, China) Case-control study 48/82 PPD, CAL, and PI MoCA 
Author (year, country)Study designParticipants/controlFemale% /controlMean age /controlDiagnostic criteria for periodontitisDiagnostic criteria for MCIAdjustment factorsNOS/AHRQ score
Holmer et al. [13] (2018, Sweden) Case-control study 50/76 49.0/56.6 70/67 BOP, PPD, and MABL The Winblad criteria Age, gender, marital status, education, smoking, body mass index, and diabetes mellitus 
Yang et al. [27] (2021, China) Cross-sectional study 36/35 38.9/37.1 75.42±7.77/74.11±6.25 The fifth edition of the World Health Organization “Oral Health Surveys Basic Methods” NINCDS-ADRDA Matched: age, body mass index, sex, and education 
Jockusch et al. [28] (2021, Sweden) Cross-sectional study 29/26 62.1/50 80/75 PSI and BOP MMSE 
Gil-Montoya et al. [25] (2015, Spain) Case-control study 21/229 67.2/55.9 77.0±7.8/78.5±7.9 PPD, CAL, PI, and BOP The Spanish criteria Age, sex, oral hygiene habits, and educational level 
Cestari et al. [16] (2016, Brazil) Case-control study 19/21 68.4/66.7 73.11±6.79/75.33±5.75 PPD and CAL NINCDS-ADRDA Matched: educational status, age, gender, and the prevalence of hypertension and diabetes 
Okamoto et al. [29] (2010, Japan) Cross-sectional study 93/3,208 31.4/51.7 74.0/71.0 CPI MMSE Depressive symptoms, sex, age, length of education, and other variables 
Zhu [26] (2019, China) Case-control study 48/82 PPD, CAL, and PI MoCA 

AHRQ, American Agency for Healthcare Research and Quality; BOP, bleeding on probing; CAL, clinical attachment loss; CPI, community periodontal index; DSM-IV, Diagnostic and Statistical Manual, Fourth Edition; MMSE, Mini-Mental State Examination; MABL, marginal alveolar bone loss; MCI, mild cognitive impairment; MoCA, Montreal Cognitive Assessment; NINCDS-ADRDA, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association; NOS, Newcastle-Ottawa Scale; PI, plaque index; PPD, probing pocket depth; PSI, periodontal screening index; RABL, radiographic alveolar bone loss.

Meta-Analysis Results

Association between the Risk of MCI in Patients with Periodontitis

A test of heterogeneity was performed on the seven included studies, resulting in p = 0.45, I2 = 0%, low heterogeneity, and a fixed-effects model was used for meta-analysis. The results of the meta-analysis showed a statistically significant difference in the correlation between periodontitis and MCI (OR = 1.70 > 1, 95% CI: 1.24–2.32, fixed-effects model, p < 0.001) (Fig. 2).

Fig. 2.

Forest plot of the association between MCI and periodontitis.

Fig. 2.

Forest plot of the association between MCI and periodontitis.

Close modal

Although heterogeneity is low, we still perform sensitivity analysis to test the robustness of this meta-analysis’s results. Each study was removed one by one to test the sensitivity and the results are shown in the online supplementary Table 4. None of the studies were excluded with a change in overall results; we therefore consider this result to be robust.

Association between the Risk of MCI in Patients with Severe Periodontitis

Among the seven studies included in the meta-analysis, four reported severe periodontitis. Heterogeneity testing of these seven studies showed low heterogeneity (p = 0.16, I2 = 42%); therefore, a fixed-effects model was used in this meta-analysis. The meta-analysis results of the fixed-effects model showed a statistically significant difference in the association between severe periodontitis and MCI (OR = 2.09 > 1, 95% CI: 1.49–2.92, p < 0.001) (Fig. 3), which indicates that MCI among patients with severe periodontitis was increased by 109% compared to those without severe periodontitis.

Fig. 3.

Forest plot of the association between MCI and severe periodontitis.

Fig. 3.

Forest plot of the association between MCI and severe periodontitis.

Close modal

PPD/CAL/PI in the MCI Patient Group versus the Control Group

Among the seven studies included in the quantitative analysis, 2 studies compared the PPD in MCI patients with that of controls. The heterogenicity test showed low heterogeneity (p = 0.79, I2 = 0%), therefore, a fixed-effects model was used for meta-analysis. Meta-analysis showed that the correlation between MCI and PPD was not statistically significant (mean difference [MD] = 0.21, 95% CI: −0.08 to 0.49, p = 0.15 > 0.05) (Fig. 4a). Based on this result it is difficult to predict the effect of MCI on PPD.

Fig. 4.

Forest plot of periodontal status in MCI patients: PPD (a), CAL (b), and PI (c).

Fig. 4.

Forest plot of periodontal status in MCI patients: PPD (a), CAL (b), and PI (c).

Close modal

Among the seven studies included in the quantitative analysis, 3 studies compared the CAL in MCI patients with controls. The test for heterogeneity showed low heterogeneity (p = 0.20, I2 = 38%); therefore, the meta-analysis was performed using a fixed-effects model. Meta-analysis results showed that periodontal attachment loss was greater in the group of MCI patients compared to the cognitively normal group (MD = 0.44, 95% CI: 0.12–0.75, p < 0.001) (Fig. 4b).

Among seven studies included in the quantitative analysis, 2 studies compared the PI of MCI patients with controls. The test for heterogeneity showed low heterogeneity (p = 0.91, I2 = 0%); therefore, a fixed-effects model was used for meta-analysis. Meta-analysis showed that the PI was higher in the MCI group compared to the cognitively normal group (MD = 0.72, 95% CI: 0.50–0.93, p < 0.001) (Fig. 4c).

Main Finding

Seven observational studies were included in this study, and the meta-analysis showed a correlation between periodontitis and MCI, which suggested that periodontitis may be a risk factor for the development of MCI and that patients with severe periodontitis are at higher risk of developing MCI. This is the same as the results of some studies. For example, a 5-year prospective cohort study showed that periodontitis exposure is significantly associated with an increased risk of MCI with an OR of 2.61 (95% CI, 1.08–6.29) [30], which is consistent with the findings of Shin et al. [31]. It was also demonstrated by a large cohort study that periodontitis was moderately associated with MCI events [32]. Furthermore, the relationship between MCI and periodontitis was stable during the sensitivity analysis in our study. Therefore, we conclude in this meta-analysis that periodontitis is associated with MCI, and the risk of developing MCI in patients with periodontitis was significantly higher than in those with relatively healthy periodontal status.

At the same time, this meta-analysis also shows that periodontal conditions are generally worse in MCI patients compared to those with normal cognitive function, and MCI patients have higher clinical attachment loss and PI than those with normal cognitive function, which is consistent with the findings of Lin et al. [14], suggesting that MCI may be one of the risk factors for poor periodontal health. It is difficult to conclude the relationship of MCI with higher PPD due to only a few pieces of literature being available on this topic, which warrants more future research. Based on our results, the prevention of MCI could improve periodontal health.

Possible Pathogenesis between MCI and Periodontitis

Periodontitis is a chronic infectious disease of periodontium-supporting tissues with a prevalence rate of 11% [33]. Although studies have been conducted to support the association of periodontitis with MCI, the pathogenesis by which periodontitis increases the risk of developing MCI has not been fully elucidated. Existing studies suggest that inflammation plays a key role in the physiopathology of cognitive impairment, with periodontitis-induced peripheral inflammation being one of the possible causes [34]. Research on animals has shown that Porphyromonas gingivalis, the primary cause of periodontitis, can generate neuroinflammation, which may be a significant factor in cognitive impairment [35]. Supportively, a study among U.S. adults showed that higher levels of antibodies to P. gingivalis were associated with poorer cognitive performance [36]. It has been well documented that the inflammatory response is an important mechanism for the development of cognitive and memory impairment in AD and that abnormal deposition of β-amyloid (Aβ) may be a stimulus for the inflammatory response [37]. As an early stage of AD, MCI may have deposition of Aβ before the onset of typical clinical manifestations of AD. The finding that Aβ production is higher in patients with severe periodontal disease would seem to indicate that periodontitis is an influencing regulatory variable [38].

In addition, patients with periodontitis are a constant source of bacteria, viruses, bacterial lipopolysaccharides (LPS), and inflammatory factors, as well as C-reactive protein. All of these can enter the bloodstream through periodontal pockets and, in some cases, cross the blood-brain barrier, activating IL-1β produced by microglia [39, 40]. They can also accelerate the proliferation and activation of microglia through the autocrine pathway, and the activated microglia produce large amounts of inflammatory factors, causing neuronal degeneration and necrosis [41, 42]. At the same time, microglia interact with activated astrocytes to promote the deposition of Aβ, thus forming a positive feedback loop. Patients with severe periodontitis are at higher risk of developing MCI. The main reason for it is the prevalence of deep periodontal pockets in patients with severe periodontitis [43], where it is known that the deeper the pocket, the more inflammatory cytokines and periodontal pathogens are present, as well as the greater the likelihood of cognitive impairment. Despite innovative knowledge of the pathogenesis of cognitive impairment, there is currently no promised curative treatment [44]. Early diagnosis and therapy of MCI could prevent or delay the disease progression.

Numerous studies have indicated that patients with dementia and cognitive impairment had worse periodontal health than cognitively normal persons [36, 45, 46], and our study found the same in patients with MCI. A plausible rationale is that the pathological byproducts of MCI and dementia may cause pro-inflammatory cytokines to be overexpressed, diminishing the body’s defenses and raising the risk of periodontitis. Further carefully planned experimental research is required to confirm if dementia or MCI contributes to the development of periodontitis. Essentially, regardless of whether MCI is the cause of periodontitis, inadequate oral hygiene among MCI patients may be a significant risk factor for the disease, which also explains why people with dementia and cognitive impairment have worsening periodontal conditions [47]. It is not unexpected that individuals with dementia and cognitive impairment may have an irreversible decrease in their knowledge of oral hygiene activities. Due to reduced cognitive function, older persons may neglect their dental hygiene regimens or gradually become less able to take care of their mouths [48, 49]. Furthermore, as periodontitis and MCI are two conditions that are very common in middle-aged and older persons, the significance of advancing age in both conditions cannot be overlooked, as evidenced by all of the studies that were included in this meta-analysis.

Possible Therapy between MCI and Periodontitis

A study has found that increased frequency of toothbrush use by MCI patients significantly reduces mean PPD, PI, and bleeding on probing [50]. Yang et al. [51] found that adequate tooth brushing may indirectly prevent cognitive decline by improving periodontal health only among older adults without cognitive impairment in their study. Unlike AD, MCI can be effectively prevented from developing into AD or other types of dementia if identified and intervened in the early stages. Although the chances of recovering normal cognition are extremely low, the evidence suggests that cognitive function improves over time in about 20% of MCI patients [52], which would make early intervention in MCI more effective than in AD. Therefore, there is a need to improve the oral hygiene routine of MCI patients to improve periodontal health, especially to stop the conversion of people with poor periodontal health to severe periodontitis, thereby inhibiting the exacerbation of MCI or even improving it.

Limitations

Although a large number of searches were conducted, strict inclusion criteria were established, and the data collection and statistical analysis were as consistent as possible, there are still certain limitations in this study:

  • 1.

    Only seven studies were included in this meta-analysis, and the types of studies were limited to case-control studies and cross-sectional studies, where no cohort studies were included. The lack of cohort studies prevents us from further determining the causal relationship between MCI and periodontitis.

  • 2.

    Although the values of I2 of the meta-analyses in this paper were all less than 50%, there was still some clinical heterogeneity between the studies.

  • 3.

    Due to differences in grouping and outcome indicators among the included studies, they were not able to combine, resulting in a smaller sample size and fewer studies included for each outcome indicator.

  • 4.

    The diagnostic criteria for MCI and periodontitis varied among the included studies, and not all studies performed the diagnosis with grading and staging of periodontitis according to the 2018 new classification guidelines for periodontal disease [8].

  • 5.

    The correction factors varied among the studies and were not accessible in two of them.

  • 6.

    The included studies were from different countries, and there were some ethnic differences.

In this meta-analysis, we can conclude that patients with periodontitis may be at higher risk of developing MCI and that periodontal conditions are generally poorer in MCI patients than in healthy subjects. However, further well-designed studies, particularly cohort studies and experimental studies, should be conducted to confirm the relationship between periodontitis and MCI to better combat MCI.

An ethics statement is not applicable because this study is based exclusively on published literature.

The authors have no conflicts of interest to declare.

No funding was received in our study.

Y. Zeng, J. Lin, and J. Chen contributed to the study’s conception and design. J. Lin, J. Chen, Z. Li, and J. Xia performed data collection and analysis. J. Lin wrote the first draft of the manuscript. J.L. Pathak, M.A. Mashrah, Y. Liang, Y. Shen, and X. Zhong commented on and critically revised the previous versions of the manuscript. J. Lin, J.L. Pathak, and Y. Zeng read and approved the final manuscript.

All data generated or analyzed during this meta-analysis are included in this article and its online supplementary material. Further inquiries can be directed to the corresponding author.

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