Journal of Clinical & Experimental Nephrology

Keywords

Periodontal disease; Liver disease; Kidney disease; Rafsanjan Cohort Study (RCS); Prospective Epidemiological Research Studies in IRAN (PERSIAN)

Introduction

Periodontal disease, characterized by the loss of bone and inflammation around the teeth, is a prevalent oral disease that often leads to tooth loss in older individuals. The clinical diagnosis of periodontal disease involves identifying signs and symptoms such as bleeding during probing, pocket depth and clinical attachment loss. This condition can be prevented by practicing good dental hygiene, reducing risk factors, making lifestyle modifications, undergoing regular periodontal check ups, and controlling dental plaque [1].

Currently, the treatment of periodontitis aims to alleviate adverse clinical manifestations.

Chronic periodontitis, the most common form of the disease, can range in severity from mild to severe. The severe form affects approximately 11 percent of the global population, with its prevalence increasing with age until around 50-60 years old. Various factors, including age, socioeconomic status, education level, smoking, stress, and systemic diseases, influence the development and progression of this slowly advancing condition [2].

Periodontal diseases have been linked to several significant acute and chronic systemic diseases.

Numerous studies, both in animals and humans, have established a connection between periodontitis and non alcoholic fatty liver disease. Liver diseases, such as non-alcoholic fatty liver disease, liver cirrhosis, liver cancer, and other forms of liver damage, are substantial health concerns worldwide. Non Alcoholic Fatty Liver Disease (NAFLD) is presently the most prevalent liver disease globally, affecting about 25.2 percent of adults aged 18 or above. The prevalence of NAFLD is rising globally, in parallel with increasing rates of obesity, metabolic syndrome, and diabetes, making it a significant global health issue. Additionally, NAFLD increases the risk of liver cirrhosis, end stage liver disease, hepatocellular carcinoma, and mortality. The release of toxins and pro-inflammatory cytokines during periodontal inflammation can easily enter the bloodstream, reach the liver tissue, and contribute to lipid peroxidation, oxidative stress, and the progression of liver disease.

Chronic kidney disease and chronic periodontitis are both common conditions that are disproportionately associated with each other. It has been reported that the progression of one disease can impact the other. Furthermore, these conditions share risk factors and have a common source of systemic inflammation. Chronic Kidney Disease (CKD) is a significant global health issue with a high prevalence, significantly affecting the overall health and quality of life of patients. CKD is defined as kidney damage, such as proteinuria, hematuria, or decreased kidney function (Glomerular Filtration Rate (eGFR) <60 mL/min/ 1.73 m² for >3 months). In the active stages of periodontitis, the production of inflammatory cytokines can increase the levels of C-reactive proteins, which contribute to the development of CKD [3].

Investigating the acccosiation between liver and kidney disease and periodontal disease is essential given the possible relationship of liver and kidney disease and periodontal health. Within the adult population of the Oral Health Branch of Rafsanjan Cohort Study (OHBRCS), we want to examine the relationship between liver and kidney diseases and periodontal disease in this paper.

Materials and Methods

Study design

In order to investigate the potential relationship liver and kidney disease and periodontal diseases in people aged 35 to 70 who were registered at the Oral Health Branch of the Rafsanjan Cohort Study (OHBRCS), this study was authorized by the ethics committee of Rafsanjan University of Medical Sciences (Ethical codes: ID: IR.RUMS.REC.1402.060). OHBRCS is a component of the Rafsanjan Cohort Study (RCS). RCS, which is a component of Prospective Epidemiological Research Studies in Iran (Persian), began operations in Rafsanjan in 2015 [4].

8682 people took part in OHBRCS. The participants were interviewed using a validated, organized, and complete questionnaire that included questions on socioeconomic status, personal habits, medical history, and demographic and anthropometric data.

The criteria for entering this study include the following:

• Age 35 to 70 years.
• All people must have been included in the Rafsanjan cohort study.
• To live only in the designated area.
• Be Iranian (have a national card or birth certificate).
• Be a resident of this city for at least nine months a year.
• The presence of at least 2 teeth.

The study excluded people who were pregnant and those who were using dietary supplements. 6545 persons made up the study's final population after the inclusion and exclusion criteria were applied.

Liver and kidney health assessment

Fasting blood samples and urine samples were collected from all research participants and biochemical parameters were checked using a Biotecnica autoanalyzer (BT 1500, Italy) in the central laboratory of the cohort. In this study, liver enzymes including Alanine Transaminase (ALT), Aspartate Transaminase Glutamyltransferase (GGT) were investigated. Hematuria, proteinuria and Glomerular Filtration (GFR) were used to check kidney health parameters

Hematuria: The presence of ≤ 3 RBC in urine

GFR reduction: GFR<60 mL/min/1.73 m²

Elevated ALT: ≥ 35 U/L in women and ≥ 40 U/L in men

Elevated AST: ≥ 35 U/L in women and ≥ 40 U/L in men

Elevated ALP: ≥ 306 U/L in both sexes

Increased GGT: ≥ 37 U/L in women and ≥ 54 in men

Periodontal health assessment

Indicators of gingival health, such as BOP, Clinical Attachment Loss (CAL), Periodontal Probing Depth (PPD), and dental calculus, were assessed in all patients. A qualified dentist examined the patients on a dental unit while utilizing a disposable dental mirror and a Williams probe (Michigan "o" probe williams coded, Hu-Friedy, USA) to record the gingival indices. Each tooth had four spots that were gently probed in order to calculate the BOP index. After 30 to 60 seconds, the presence or absence of bleeding was noted. The ratio of bleeding points to all points is known as the BOP index for each individual.

To measure CAL, the area around the teeth was thoroughly probed, and the distance between the CEJ and the depth of the pocket was noted. This analysis determined only plaque-induced CAL. The probe was moved parallel to the axis of the teeth along the gingival margin to measure the pocket depth, which is the vertical distance from the free gingival margin to which a probe penetrates into a pocket. The deepest entrance points of the probe in six sides (mesial, middle, and distal of buccal and lingual surfaces) were recorded. In this investigation, only real pockets were counted. Dental calculus was evaluated using the CSI (Calculus Surfce Index) index; in this manner, the four surfaces of buccal, lingual, mesial and distal of the four front teeth of the mandible were assessed by observation or touch with a probe [5].

Other variables assessment

The Wealth Score Index (WSI) was used to check the state of well-being. Multiple Correspondence Analysis (MCA) was used to calculate the Wealth Score Index (WSI), which was then used to evaluate the socioeconomic standing of the individuals. The WSI for each participant was determined by factoring in their possession of a variety of durable items (such as a dishwasher, car, and TV), the condition of their home (such as the number of rooms and kind of ownership), and their level of education [6].

The amount of physical activity was evaluated using the Metabolic Equivalent of Task (MET). Through the completion of a questionnaire, the individuals' daily activities were recorded for the study. For this, the Metabolic Equivalent of Task (MET) criteria was employed. The quantity of energy spent by each person in relation to their weight is represented by a MET. As anillustration, one MET is equal to 3.5 mL of oxygen used per kilogram of body weight per minute by each person at rest, whereas four METs is equal to 16 ml of oxygen used per kilogram of body weight per minute. We evaluated each participant's activity levels using MET.

Dyslipidemia is defined as having either LDL levels greater than or equal to 130 mg/dL, total cholesterol levels greater than or equal to 200 mg/dL, HDL levels less than or equal to 40 mg/dL in males and 50 mg/dL in females, or triglyceride levels greater than or equal to 150 mg/dL. Additionally, if someone has taken medication to lower their lipid levels within the past two weeks, they are also considered to have dyslipidemia [7].

Statistics analysis

Following collection, data were processed in a STATA 14 environment, and the findings were shown through the use of tables and descriptive statistical techniques. With the use of the chi-square test (2) for categorical variables and the t-test for quantitative variables, the basic characteristics of the analyzed groups were compared. For categorical data, number and percentage (%) were used, and for quantitative variables, mean (SD: Standard Deviation). To reduce the impact of confounding factors, the analysis was conducted in two stages using a univariate and multivariate logistic regression model. The factors that emerged as significant in the univariate phase of the multivariate analysis were included to the multivariable logistic regression model, and the odds ratio was determined as a result. Age (continuous variable), gender (male/female), education (continuous variable), wealth status index (continuous variable), smoking (yes/no), opium use (yes/no), body mass index (yes/no), activity level (yes/no), hypertension (yes/no), diabetes (yes/no), history of CVD (yes/no), and brushing (yes/no) were adjusted in the model. The thresholds for significance was set at values lower than 0.05 [8].

Results

This study involved 6545 participants with an average age of 47.61 years and a standard deviation of 8.74 years. Of these participants, 44.20% were men and 55.80% were women. The prevalence of BOP (Bleeding on Probing), calculus, pocket depth and Clinical Attachment Loss (CAL) was found to be 73.51%, 81.56%, 13.72%, and 59.67%, respectively, among this population. Also, the prevalence of ALT, AST, ALP, and GGT enzymes were 9.72%, 2.78%, 8.16%, and 9.16%, respectively. The prevalence of decreased GFR, hematuria and proteinuria were 12.79%, 17.97% and 4.29%, respectively [9].

Table 1 shows sociodemographic characteristics, personal habits and medical history of the study population by ALT and AST. The frequency of ALT elevate was significantly higher in men (P-value<0.001) and people who consumpted alcohol (P value<0.001) and had a history of diabetes (P-value 0.012) and dyslipidemia (P-value<0.001). Individuals with elevated ALT had significantly higher mean of education (P-value 0.003), age (P value<0.001) and BMI (P-value<0.001), and also had less tooth brushing frequency (P-value<0.001) [10].

People with elevated AST had significantly more frequency of hypertension (P-value 0.002), diabetes (P-value 0.010) and dyslipidemia (P-value<0.001). Individuals with elevated AST had significantly lower mean physical activity (P-value 0.007) and higher BMI (P-value<0.001) [11].

Table 1: Sociodemographic characteristics, personal habits and medical history of the study population by ALT and AST (n=6545).

Table 2 shows sociodemographic characteristics, personal habits and medical history of the study population by ALP and GGT. The frequency of ALP elevate was significantly higher in people who smoked cigarettes (P-value 0.015), consumed opium (P-value 0.004), and had a history of hypertension (P value<0.001), diabetes (P-value<0.001), and dyslipidemia (P value<0.001). Individuals with elevated ALP had significantly higher average age (P-value<0.001) and BMI (P-value 0.020), education level (P-value<0.001), physical activity (P-value 0.039), wealth score index (P-value<0.001), and the frequency of tooth brushing (P-value<0.001). The frequency of elevated GGT in people with a history of hypertension (P-value<0.001), diabetes (P-value<0.001), dyslipidemia (P-value<0.001) and CVD (P-value 0.024) was significantly higher. Individuals with elevated ALP had significantly higher average age (P-value 0.001) and BMI (P value<0.001), education level (P-value 0.023), physical activity (P-value 0.007), wealth score index (P-value 0.026), and the frequency of tooth brushing (P-value 0.049) [12].

Table 2: Sociodemographic characteristics, personal habits and medical history of the study population by ALP and GGT (n=6544).

Table 3 shows sociodemographic characteristics, personal habits and medical history of the study population by hematuria and proteinoria. The frequency of hematuria in women (P value<0.001) and proteinuria in men (P-value<0.001) was significantly higher. The frequency of hematuria was higher in people with opium consumption (P-value 0.002) and significantly lower in people with a history of diabetes (P-value<0.001). People with hematuria had a significantly lower average BMI (P value 0.015) and wealth score index (P-value<0.001), and a lower level of education (P-value 0.001).

The frequencyof proteinuria was significantly higher in people who smoked cigarettes (P-value 0.040), consumpted opium (P value 0.023), and had a history of hypertension (P-value<0.001), diabetes (P-value<0.001), dyslipidemia (P-value<0.001), and CVD (P-Value<0.001). People with proteinuria had a significantly higher mean age (P-value<0.001) and BMI (P-value 0.001), education level (P-value<0.001), and wealth score index (P-value 0.002). And the frequency of tooth brushing was less (P-value 0.002) [13].

Table 3: Sociodemographic characteristics, personal habits and medical history of the study population byhematuria and proteinoria (n=6511)

Table 4 shows the Sociodemographic characteristics, personal habits and medical history of the study population by GFR. The frequency of GFR decrease was lower in people who consumpted alcohol (P-value<0.001), opium (P-value<0.001) and smoked cigarettes (P-value<0.001), and it was significantly higher in women (P-value<0.001) and people with a history of hypertension (P-value<0.001), diabetes (P-value<0.001), dyslipidemia (P value<0.001), and CVD (P-value<0.001). Individuals with decreased GFR had significantly higher mean age (P-value<0.001) and BMI (P-value<0.001), and lower levels of education (P value<0.001) and physical activity (P-value<0.001)[14].

Table 4: Sociodemographic characteristics, personal habits and medical history of the study population by GFR (n=6545).

Table 5 shows periodontal characteristics of the study population by ALT and AST. There was a significant difference between the elevated ALT and BOP. The frequency of ALT elevate was significantly higher in people who had BOP (P-value 0.042) [15].

Table 5: Periodontal characteristics of the study population by ALT and AST (n=6545).

Table 6 shows periodontal characteristics of the study population by ALP and GGT. There was a significant difference between the elevated ALP and CAL. The frequency of ALP elevate was significantly higher in people who had CAL (P-value 0.007) [16].

Table 6: Periodontal characteristics of the study population by ALP and GGT (n=6545).

Table 7 shows periodontal characteristics of the study population by hematuria and proteinoria. There was a significant difference between the presence of hematuria and proteinuria with CAL. In people who had CAL, the frequency of hematuria was significantly lower (P-value 0.041) and the frequency of proteinuria was higher (P-value 0.023) [17].

Table 7: Periodontal characteristics of the study population by hematuria and proteinoria (n=6545).

Table 8 shows periodontal characteristics of the study population by GFR. There was a significant difference between GFR decrease with pocket and CAL. The frequency of GFR decrease was significantly higher in people with CAL (P- value<0.001). But the frequency of GFR decrease was significantly lower in people who had pockets (P-value 0.043) [18].

Table 8: Periodontal characteristics of the study population by GFR (n=6545).

Table 9 shows the associations between the elevated liver enzymes (ALT, AST, ALP, GGT) and periodontal health indexes among study participants using the crude and adjusted models. In people with BOP, the chance of ALT elevate was 22% higher (p<0.05). But after removing the confounding factors, this effect was not seen (p>0.05). In people with CAL, the chance of elevating ALP was 29% higher, but this effect was not seen after removing the confounding factors. There was no significant relationship between other periodontal health indexes and elevated liver enzymes (ALT, AST, ALP, GGT) [19].

Table 9: The associations between the elevated liver enzymes (ALT, AST, ALP, GGT) and periodontal health indexes among study participants using the crude and adjusted models.

Table 10 shows the associations between the kidney health indexes (hematuria, proteinoria, GFR) and periodontal health indexes among study participants using the crude and adjusted models. In people with CAL, the chance of GFR decreasing was 31% higher (p<0.05). But after removing the confounding factors, this effect was not seen (p>0.05). There was no significant relationship between other periodontal health indexes and kidney health indexes (hematuria, proteinuria, GFR) [20].

Table 10: The associations between the kidney health indexes (hematuria, proteinoria, GFR) and periodontal health indexes among study participants using the crude and adjusted models.

Discussion

The objective of this study was to investigate the relationship between liver and kidney disease with periodontal disease.

We found that there was no significant relationship between periodontal health indexes and the elevate of liver enzymes (ALT, AST, ALP, GGT). Contrary to our study, in a study conducted by Widita, et al., in 2018, which aimed to investigate the relationship between clinical periodontal parameters and changes in liver enzymes levels over an 8-year period in the Japanese elderly population with an average age of 72 years, they concluded that the increase in ALT levels It is significantly related to CAL and probing depth, but no significant relationship was found between AST level and periodontal clinical indexes. This difference can be due to the difference in sample size and racial and age differences.

In line with the result of our study, in a study conducted by Kuroki, et al., in 2018 with the aim of investigating the relationship between the level of liver enzymes and alveolar bone loss, they concluded that there is a significant relationship between the measured level of liver enzymes and the highest amount of alveolar bone loss.

Contrary to our study, in a study conducted by Furuta, et al., in 2010 with the aim of investigating the relationship between periodontitis and liver disorders in 18 and 19-year-old Japanese students, they concluded that in men, having periodontitis was significantly associated with increased ALT levels, but there was no significant relationship between periodontitis and ALT in female students. This difference can be due to the difference in the average age of the studied community and the difference in race.

We found that there was no significant relationship between periodontal health indexes and kidney health indexes (hematuria, proteinuria, GFR). Contrary to the results of our study, in a study conducted by Han et al., in 2013 with the aim of investigating the relationship between chronic kidney disease and periodontitis in Korean adults, they concluded that there is a positive relationship between hematuria and decreased GFR with periodontitis, but there is a relationship between Proteinuria and periodontitis were not found. This difference can be due to the racial difference and the difference in the way periodontitis is diagnosed and defined.

In line with the results of our study, in a study done by Brotto, et al., in 2013 with the aim of investigating the relationship between periodontitis and kidney disorders by measuring kidney health indicators in two groups of people with periodontitis and the group without periodontitis, they concluded that severe periodontitis is not associated with changes in kidney function.

Contrary to the results of our study, in a study by Vanezuela, et al., In 2021, they concluded that periodontal disease may be associated with the development of chronic kidney disease. This difference can be due to the difference in the size of the study sample, racial differences, and differences in the measurement and type of periodontal and kidney health indicators

Strengths of the study

The current study has several strengths, including the population-oriented nature of the study, the large statistical population and the control of confounding factors. Also, the information collected for this study was collected with high accuracy by trained dentists and users. However, there were also some limitations to the research. For example, due to the cross sectional design, we cannot investigate the cause-effect relationship between liver and kidney disease and periodontal disease. Also, all the participants in our study were from the same Iranian population, so the results cannot be generalized to other races and populations.

Conclusion

Overall, this study suggests that there was no significant relationship between liver health indexes (ALT, AST, ALP, GGT) and kidney health indexes (hematuria, proteinuria, GFR) and periodontal health indexes. However, in order to prove these results, it is necessary to confirm the results of cohort studies of other populations and longitudinal and prospective studies.

Ethical Approval and Consent to Participate

This study was authorized by the ethics committee of Rafsanjan university of medical sciences (Ethical codes: ID: IR.RUMS.REC.1402.060). Written informed consent was obtained from the participants. The participants’ data were kept confidential and were only accessible to the study investigators. All methods were performed in accordance with the relevant guidelines and regulations.

Data Availability

The persian adult cohort study Center at Rafsanjan university of medical sciences in Iran hosts the datasets used in the current investigation. The information is not publicly accessible. However, the corresponding authors can provide the data on reasonable request.

Consent for Publication

Not applicable.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

There are no conflicts of interest, according to the authors.

Authors’ Contributions

Raziyehsadat Rezvaninejad designed the study and supervised the project. Mohammad Hossein Rokn Rabei collected the data and prepared Tables. Parvin Khalili and Zahra Jamali performed the statistical analysis. Raziyehsadat Rezvaninejad and Mohammad Hossein Rokn Rabei wrote and revised the initial manuscript. All the authors read and approved the final manuscript.

Acknowledgments

The authors thank the study participants, the study-site personnel, and members of Rafsanjan cohort center in Rafsanjan, Iran. This study was supported by the Vice chancellery for research and technology of Rafsanjan university of medical sciences.