Gastrointestinal distress as a potential mediator between stress and periodontal inflammation

Abstract

Objectives:

Periodontal disease is multifactorial in its aetiology, which encompasses biopsychosocial contributors, including psychological stress. Gastrointestinal distress and dysbiosis have been associated with several chronic inflammatory diseases yet have rarely been investigated with respect to oral inflammation. Given the implications of gastrointestinal distress on extraintestinal inflammation, this study aimed to evaluate the potential role of such distress as a mediator between psychological stress and periodontal disease.

Methods:

Utilizing a cross-sectional, nationwide sample of 828 adults in the USA generated via Amazon Mechanical Turk, we evaluated data collected from a series of validated self-report psychosocial questionnaires on stress, gut-specific anxiety around current gastrointestinal distress, and periodontal disease, including periodontal disease subscales targeted at physiological and functional factors. structural equation modelling was used to determine total, direct and indirect effects, while controlling for covariates.

Results:

Psychological stress was associated with gastrointestinal distress (ß = .34) and self-reported periodontal disease (ß = .43). Gastrointestinal distress also was associated with self-reported periodontal disease (ß = .10). Gastrointestinal distress likewise mediated the relation between psychological stress and periodontal disease (ß = .03, p = .015). Given the multifactorial nature of periodontal disease(s), similar results were demonstrated using the subscales of the periodontal self-report measure.

Conclusions:

Associations exist between psychological stress and overall reports of periodontal disease as well as more specific physiological and functional components. Additionally, this study provided preliminary data supporting the potential mechanistic role that gastrointestinal distress plays in connecting the gut-brain and the gut-gum pathways.

Introduction

Periodontal disease is a highly prevalent oral condition, affecting nearly half of all adults aged 30 years and older in the USA (Eke et al., 2015) and is a leading cause of tooth loss (Eke et al., 2021; Tonetti et al., 2018). Extensive work has identified oral bacteria (e.g., Porphyromonas gingivalis) and poor oral hygiene behaviors (i.e., lack of regular tooth brushing and flossing) as major risk factors for periodontal inflammation and associated attachment loss (Tonetti et al., 2018; Wright et al., 2019). An abundance of P. gingivalis (or other bacteria) present in the oral cavity, however, combined with poor oral hygiene habits, does not guarantee the development of periodontal disease, indicating that there may be other important host or environmental factors that play a mechanistic role in both periodontal disease onset and progression (Tonneti et al., 2018).

Psychosocial factors, in particular psychological stress, are among the contributors that may predispose, precipitate or perpetuate periodontal inflammation and disease severity (Aleksejuniené et al., 2002; Dumitrescu, 2006; Genco & Borgnakke, 2013; Genco et al., 1999; Hildebrand et al., 2000; Ng & Keung Leung, 2006; Warren et al., 2014; Wright et al., 2019). Although prior research has demonstrated associations and potential mechanisms between psychological stress and periodontal conditions, the direct and/or indirect mechanisms have not been fully elucidated (Genco et al., 1998; Goyal et al., 2013). The gastrointestinal system has increasingly been shown to play an important role in inflammatory processes throughout the body, including the oral cavity (Albuquerque-Souza & Sahingur, 2022; Bajaj et al., 2018; Byrd & Gulati, 2021). Given its role in both inflammation and stress, the purpose of this study was to explore the role of gastrointestinal distress as a potential novel mechanism in understanding the relation between psychological stress and periodontal disease.

The gastrointestinal tract—and the digestive system more broadly—facilitates immune functions and responses, particularly through barrier functioning. Its primary role is to allow the “good” (e.g., nutrients) in and keep the “bad” (e.g., toxins) out. In this context, the consequences of gastrointestinal processes have been examined for many systems and other areas of the body (Fasano & Flaherty, 2021; Moloney et al., 2015). For example, celiac disease is a condition for which alterations in the microbiota, in combination with genetic predisposition and exposure to the trigger gluten, interact to precipitate an autoimmune host response (Leonard et al., 2021). Increased intestinal permeability elicited, in part, by zonulin (a modulator of epithelial tight junction permeability), plays a crucial role in celiac disease pathogenesis (Sturgeon & Fasano, 2016). Tissue permeability and gut dysbiosis have been associated with several other inflammatory conditions as well, including type 1 diabetes, multiple sclerosis and others (Sturgeon & Fasano, 2016). Other emerging literature has identified the potential role of gut dysbiosis in periodontal disease (Albuquerque-Souza & Sahingur, 2022; Bajaj et al., 2018). Additional evidence is needed, however, to identify potential mechanisms by which gastrointestinal distress (due to dysbiosis or other disease processes) could be contributing to periodontal disease.

The intersection between the gut and periodontal conditions has been described as the “gut-gum axis” (Byrd & Gulati, 2021) or, in other literature, the “oral-gut-liver axis” (Albuquerque-Souza & Sahingur, 2022). As mentioned, gastrointestinal distress has previously been implicated in other inflammatory diseases (Sturgeon & Fasano, 2016), and it could be that inflammatory processes started in the gut affect the oral cavity, though little work in this area exists. While the gut may influence the risk of periodontal disease (i.e., in a “bottom-up” directionality), the oral microbiome also has been shown to influence the gastrointestinal microbiome (i.e., “top-down” directionality) in ways that may impact disease (Albuquerque-Souza & Sahingur, 2022; Bajaj et al., 2018; Byrd & Gulati, 2021).

As the entry point to the digestive system, the oral cavity is not only relevant to, but integrated with, both the immune and the digestive processes via masticatory function and saliva production (National Cancer Institute, 2021). Like the gastrointestinal tract, inflammation in the oral cavity can lead to deleterious disruptions in digestive functions. For example, inflammation of the periodontium can lead to the breakdown of surrounding tissues, disrupted ability to chew foods and tooth loss. These parallels and potential bidirectional connections between the gastrointestinal tract/digestive system and the oral cavity provide a novel perspective by which to examine the aetiology, maintenance, and treatment of periodontal disease. Based on existing literature, a bidirectional relation between gut distress and the oral cavity likely exists, though this project was an exploratory study of the potential mechanisms leading to periodontal disease as an outcome.

As an analytical approach to examining complex relations among variables, structural equation modelling (SEM) is a latent variable approach that combines factor analysis and regression/path model analysis (Wang & Wang, 2012). SEM allows for examining complex relations between several biopsychosocial variables, while also accounting for measurement error inherent in variables derived from self-report assessments (Keith, 2014). By utilizing SEM, a priori causal inferences are made, which allow for the estimation of both indirect and direct effects.

While both psychological stress and gastrointestinal distress have been associated with periodontal inflammation or disease, no known study has examined the mechanistic relation(s) between the two. The present study aimed to use SEM to explore the complex and potential role of gastrointestinal distress as a mediator in the relation between stress and periodontal disease. It was hypothesized that psychological stress would be positively correlated with periodontal disease. Secondarily, it was hypothesized that increased gut distress would predict increased periodontal disease. Thirdly, it also was hypothesized that gut distress would act as a mediator in the relation between stress and periodontal disease such that gut distress would partially explain some of the effect of stress on periodontal disease.

Method

Data for this study were obtained as part of a larger project designed to examine psychosocial correlates of oral health and disease (Wright & McNeil, 2021). The cross-sectional data collection was conducted online via Qualtrics (Qualtrics, Provo, UT) and utilized Amazon’s Mechanical Turk (MTurk) for recruitment of a convenience sample of participants. Inclusion criteria for the parent study consisted of adults at least 18 years of age living in the United States who reported that they could read and speak English. MTurk uses “hits” or a targeted number of advertisements to recruit individuals. A single iteration (i.e., hit) can be used to enrol only nine participants at one time. Once a “hit” is fulfilled, a new hit with more participant slots is posted until the total target number of participants is reached. Recruitment was targeted to ensure an overall normal age distribution of adults in the United States by increasing the requested age in the MTurk advertisement for the study with each iteration. Participants were consented and asked to respond to several self-report questionnaires including four validation items (e.g., “What color are teeth?”) to reduce response biases and issues that commonly exist in similar online data collection strategies. All procedures were conducted in accordance with West Virginia University’s Institutional Review Board (Protocol #1708705017) requirements and procedures and complied with STROBE protocols for cross-sectional studies. Participants were provided written and electronic informed consent via Qualtrics.

Measures

The questionnaires administered online included assessments of demographic information including gender, age in years, household income (treated continuously), and race/ethnicity, as well as the following measures:

Periodontal Disease Self-Report (PDSR; Wright, Heaton, & McNeil, 2021).

As part of a larger project, the creation and initial validation of a multi-item self-report periodontal disease measure was conducted (Wright et al., 2021). The questionnaire items (totalling 17) were loosely based on previous periodontal disease self-report measures (see Blicher et al., 2005) and adapted to reflect sound psychometric theory and best practice. Responses were assessed using a scale with three anchors evaluating the extent to which participants agreed with statements such as “I have gum problems” or “I have difficulty chewing because of my teeth.” The PDSR also has two subscales which can provide a more nuanced perspective to periodontal disease symptomology. The Physiological Symptoms subscale includes items more associated with things like bleeding and “puffy” gums. The Functional Symptoms subscale deals more with self-reported difficulty with masticatory ability (i.e., chewing), wiggly teeth, etc. The PDSR has demonstrated evidence for adequate factor validity and fit (Wright et al., 2021). The PDSR Total score and the subscale scores were calculated by summing each of the items and were treated as continuous variables.

Perceived Stress Scale-10 (PSS; Cohen et al., 1983).

The PSS is a commonly used and well-validated measure of overall stress with 10 Likert-type items such as, “In the last month, how often have you felt that you were unable to control the important things in your life?” or “In the last month, how often have you found that you could not cope with all the things that you had to do?” The PSS has been shown to be internally consistent (i.e., reliable) and others have provided evidence for concurrent and overall construct validity (Cohen et al., 1983). The PSS scores are also calculated by summing its items and were treated as a continuous variable.

Visceral Sensitivity Index (VSI; Labus et al., 2004).

The VSI was used as a surrogate estimation of gastrointestinal distress. The VSI (Labus et al., 2004; Labus et al., 2007) is a valid and reliable measure of gut-specific anxiety. The measure has 15 Likert-type items such as, “I have a difficult time enjoying myself because I cannot get my mind off of discomfort in my belly” or “In stressful situations, my belly bothers me a lot.” Thus, it has participants rate items that are also consistent with symptoms frequently encountered by individuals with gastrointestinal maladies. Similarly, the VSI item scores were summed to create a continuous variable to be used in the analyses.

Analytical Approach

To understand the assumed directional relations between psychological stress, gut distress, and periodontal inflammation, an SEM approach was utilized. Given the analytic approach, the assumptions of linearity, independence of data, normality, equality of variance and extreme multicollinearity (Keith, 2014) among included variables were implied. During online data collection, validation items were included to prevent a participant from response bias (e.g., choosing random answers) and otherwise protect the integrity of the data. Participants who did not correctly answer all four of the validity items were not included in the final sample. The final number of participants after excluding those (n = 205) with incorrect responses to validity items was 828. There was no missing data in the included variables after exclusion of participants with validity concerns.

Both the total score for the PDSR as well as the more nuanced subscales were used to examine our initial hypotheses using two SEM models using MPlus software. With a variance adjusted weighted least squares estimator (WLSMV), each of the items of the PSS, the VSI, and the PDSR total score were loaded onto a latent total score for each measure. The primary dependent variable for the first model was the latent PDSR total score and the independent variable was the latent PSS total score. PDSR scores were regressed on both VSI and PSS scores. Likewise, VSI scores were regressed on PSS scores. Total, direct, and indirect effects for this first model then were estimated.

Next, the second model was conducted using the PDSR Physiological symptoms subscale and PDSR Functional symptoms subscale as outcomes. Participant demographic characteristics, including gender, age, education (in years), and household income were included in both SEM models. In each case, model fit was determined using root mean square error of approximation (RMSEA), confirmatory factor index (CFI), Tucker-Lewis index (TLI), and standardized root mean square residual (SRMR; Hu & Bentler, 1998; Hu & Bentler 1999). Guidelines for determining adequate fit included an RMSEA of equal to or less than 0.08, CFI and TLI of 0.90 or higher, and an SRMR of equal to or less than 0.06 (Hu & Bentler, 1998; Hu & Bentler 1999). Figures 1 and 2 display diagrams of the models tested.

Figure 1.

Structural equation model displaying relations between psychological stress (St), gastrointestinal distress (GI), and self-reported periodontal disease (Pd) total score while accounting for subscales of Physiological factors (Ph) and Functional Factors (Fc). Numbers depict individual items making up latent variables (circles). Covariates of gender (G), age (A), education (E), and household income (I) were manifest variables depicted with rectangles. Solid lines depict significant associations whereas dashed lines were non-significant associations.

** = p < 0.001 * = p < 0.05

Figure 2.

Structural equation model displaying relations between psychological stress (St), gastrointestinal distress (GI), and self-reported periodontal disease subscales of Physiological factors (Ph) and Functional Factors (Fc). Numbers depict individual items making up latent variables (circles). Covariates of gender (G), age (A), education (E), and household income (I) were manifest variables depicted with rectangles. Solid lines depict significant associations whereas dashed lines were non-significant associations.

** = p < 0.001 * = p < 0.05

Results

Participants’ mean age was 48.0 years old (SD = 12.7, Range = 18–82) and included 488 women (58.9%) and 340 (41.1%) men. The mean PSS score was 15.3 (SD = 8.1, Range = 0–39) and the mean VSI score (reversed) was 38.9 (SD = 21.4, Range = 15–90). The PDSR mean total score was 8.0 (SD = 8.0, Range = 0–34); the PDSR Physiological symptoms subscale and Functional subscale score means were 5.4 (SD = 5.8, Range = 0–22) and 2.6 (SD = 2.8, Range = 0–12), respectively. Additional demographic information and characteristics are displayed in Table 1.

Table 1.

Sample demographics.

		Mean/#	SD/%
Age		48.0	12.7
Gender	Female	488	58.9%
	Male	340	41.1%
Income	Less than $10,000	34	4.1%
	$10,000 to $14,999	35	4.2%
	$15,000 to $24,999	95	11.5%
	$25,000 to $34,999	117	14.1%
	$35,000 to $49,999	130	15.7%
	$50,000 to $74,999	201	24.3%
	$75,000 to $99,999	117	14.1%
	$100,000 to $149,999	66	8.0%
	$150,000 to $199,999	23	2.8%
	$200,000 or more	10	1.2%
Education (years)	Range = 0 – 26 years	15.4	2.6
Race/ Ethnicity	White	671	81.0%
	Black/African American	75	9.1%
	Hispanic	38	4.6%
	Asian	46	5.6%
	Native American	16	1.9%
	Other	8	1.0%

Note: Participants (n = 828) could select more than one race/ethnicity, thus allowing for total percentage to be greater than 100%.

The SEM model with the PDSR total score as the outcome resulted in overall adequate model fit (RMSEA = .04; CLI = .90; TLI = .90; SRMR = .06), while accounting for the covariates of gender, age, income, and education. Regression results were such that increased individual levels of perceived stress were associated with increased PDSR scores (ß = .43, p < .001). Likewise, perceived stress scores were positively associated with VSI scores (ß = .34, p < .001). Elevated VSI scores also were associated with higher levels of self-reported periodontal disease (ß = .10, p = .013). The total effect of PSS on PDSR scores also was significant (ß = .46, p < .001) and there was a significant indirect effect of PSS on PDSR through VSI scores (ß = .03, p = .015).

In terms of covariates, gender was associated with self-reported periodontal disease such that men reported higher symptomology and women lower (ß = .09, p = .023). Higher income was associated with less stress (ß = −.16, p < .001). Greater age also was associated with less stress (ß = −.22, p < .001) and less gastrointestinal distress (ß = −.10, p = .005). Gender and income were not significantly associated with gastrointestinal distress. Figure 1 displays the model results.

The second model with the PDSR subscale scores resulted in similar fit (RMSEA = .04; CLI = .90; TLI = .89; SRMR = .06). The crude regression results in this second model were such that increased perceived stress was associated with increases in self-reported scores on the Physiological Symptoms subscale (ß = .37, p < .001) and the Functional Symptoms subscale (ß = .39, p < .001) of the PDSR. Greater stress also was associated with greater gastrointestinal malady (ß = .34, p < .001). Greater gastrointestinal distress was related to greater Physiological Symptoms (ß = .08, p = .033) as well as Functional Symptoms (ß = .10, p =.007) on the PDSR. In terms of mediations, the total effect of perceived stress on self-reported Physiological Symptoms was significant (ß = .40, p < .001) and the indirect effect was significant (ß = .03, p = .036). The total effect of perceived stress on self-reported Functional Symptoms was significant (ß = .43, p < .001) with an indirect effect also significant (ß = .04, p = .009).

Men were more likely to endorse higher symptoms on the functional symptoms subscale of the PDSR and women less (ß = .11, p = .004), though no significant association was found for the physiological symptoms subscale (p = .084). Higher household income was again associated with less stress (ß = −.16, p < .001), as was increased age associated with less reported stress (ß = −.22, p < .001). In addition, higher household income was associated with a decrease in functional symptoms subscale scores on the PDSR (ß = −.10, p = .008). Also, there was a significant association between higher levels of education with fewer functional symptoms on the PDSR (ß = −.09, p = .015). Higher age was associated with less reported gastrointestinal distress as well (ß = −.10, p = .005). Like the first model, gender and income were not significantly associated with gastrointestinal distress. Full results are displayed in Figure 2.

Discussion

The primary purpose of this study was to explore the possible relations between self-reported psychological stress, gastrointestinal distress, and periodontal disease. We found evidence of an association between stress and overall reports of periodontal disease as well as more specific physiological and functional components. Moreover, gastrointestinal distress played a mediating role in the relation between stress and self-reported periodontal disease. This study extends prior work on the “gum-gut axis” (Byrd & Gulati, 2021). Demonstrating an association between self-report gastrointestinal distress and periodontal disease provides preliminary data for follow-up in future studies. Additionally, given the associations between psychological stress and periodontal disease, together with the known associations between stress and the immune system (Segerstrom & Miller, 2004), these findings also suggest the potential existence of a “gum-gut-brain axis.” Much more work is needed in this space, but this study suggests a novel avenue for research in the ongoing efforts to explicate the aetiology and systemic effects of periodontal inflammation.

While prior work has identified the association between psychological stress and periodontal disease, this study is the first to present evidence that gut-related distress is a potential mediator in that relation. Several hypotheses could be derived from these findings. For example, robust evidence has implicated psychological stress in inflammatory processes (Segerstrom & Miller, 2004) and could therefore be affecting both the gastrointestinal and periodontal tissues. Perhaps stress precipitates an increase in biological processes that are reflected in biomarkers such as cytokines that are pro-inflammatory for periodontal tissues as well (e.g., interleukin-6; Vanuytsel et al., 2014; Yoshikawa et al., 2017). Additional research, though, based on biomarkers or clinical data should be conducted in this area to further examine these relations.

Using an a priori assumption of directionality, gut distress appeared to mediate the relation between stress and periodontal disease and had a significant direct presumed effect on periodontal disease. While limited due to the cross-sectional nature of the data, the results here provide at least some evidence around the association between the gut and the mouth. That is, it could be that inflammatory processes cultivated by gastrointestinal distress (e.g., because of dysbiosis) could be travelling elsewhere in the body, potentially settling in and leading to inflammation in the oral cavity as well. This certainly could be the case given the oral cavity often is seen as the beginning of the digestive system. Additional work should be done to broaden the scope of oral health science to include digestive disease processes. Likewise, additional work should be done to broaden digestive disease science to include the oral cavity and researchers in that area (e.g., dentists, oral microbiologists, periodontists). Other work by some of the authors have demonstrated the association of tissue permeability, gut dysbiosis, resultant malady and the implications for other bodily systems such as metabolic processes, insulin resistance, autoimmunity and more (Leonard et al., 2021; Sturgeon & Fasano, 2016).

Limitations

The data for this study were collected online from a convenience sample, thus limiting the generalizability of our findings. We also used only self-report data. Given that, the results, interpretation and implication of this study must be seen as exploratory. Such work, however, is important in determining where resources might be allocated in additional attempts to explicate the etiologies and mechanisms that lead to periodontal disease. Furthermore, it will be important to validate our self-report periodontal disease measure using clinical examination data.

While several common covariates in periodontal disease were included in our analyses, other important covariates, such as smoking status and diabetes status were not. The covariates included and their associations with the primary predicting and outcome variables, however, were in large part consistent with prior literature. One exception was age, which did not significantly predict periodontal disease in either model. This could be due to the particular demographic of our convenience sample – individuals who typically use MTurk or other online data collection platforms – though additional work could help to understand the associations between age and the PDSR measure.

Finally, SEM as a method is not without its limits. The use of latent variable approaches helps in accounting for error that ordinary least squares regression may not, but also assumes the existence of underlying variables. Prior work, however, has demonstrated the potential viability and utility of a latent approach for measuring periodontal disease (Wright et al., 2021). Also, there are limitations to the assumed directionality, which cannot be confirmed due to the cross-sectional nature of the data. Future work that is experimental or prospective in nature will aid in better explicating the potential bidirectional relation between the mouth and the gut.

Conclusion

Periodontal disease is a complex multifactorial condition that is known to be microbiologic in nature but mediated by various host factors. This study provided evidence for another potential mechanism that could help to explain aetiological factors contributing to its development and maintenance. That is, this study points to gastrointestinal dysfunction leading to distress as a viable target for future work in periodontology, particularly as a factor to be studied in relation to psychological stress and periodontal disease.

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.