Association between total functional tooth unit score and hemoglobin A1c levels in Japanese community-dwelling individuals: the Nagasaki Islands study
Periodontitis is highly prevalent among older populations and also occasionally occurs in young individuals . Severe periodontitis is accompanied by the destruction of periodontal tissue , causing tooth mobility and loss  and thus negatively affecting masticatory performance . The main cause of periodontitis is bacterial biofilm (dental plaque) formation . More than 700 bacterial species have been identified in the oral cavity , among which Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans are closely associated with periodontitis . The level of P. gingivalis in periodontal pockets is positively correlated with probing pocket depth (PPD) . Aggregatibacter actinomycetemcomitans is frequently detected in lesions in young patients with periodontitis . Diabetes mellitus (DM) is one of the most common chronic diseases in the world . In 2019, 110.1 million people aged ≥ 70 years were living with DM, with a global prevalence of 23.7% . The main causes of DM are impaired insulin secretion (insulin maintains blood sugar levels within a certain range and is secreted by β-cells in the pancreatic islets), resistance to insulin, or both . Numerous epidemiological studies have demonstrated a bidirectional association between periodontal disease and DM . Diabetics have an approximately three-fold increased risk of periodontal disease compared to nondiabetics . Severe periodontitis increases the incidence of type 2 DM by 53% . Treatment of periodontitis in diabetic patients reduces hemoglobin A1c (HbA1c) levels by 0.3–0.4%, resulting in improved glycemic control . To date, at least three mechanisms have been proposed to explain the adverse effects of periodontal disease on glycemic control. First, periodontal inflammation increases the levels of systemic proinflammatory mediators such as interleukin (IL)-1β, IL-6, and tumor necrosis factor α, and chronic low-grade systemic inflammation exacerbates insulin resistance . Increased insulin resistance impairs glucose tolerance and elevates blood glucose levels . Second, P. gingivalis and its proteases (gingipains) migrate into the pancreas via the bloodstream, causing marked changes in islet structure and β-cell apoptosis . Dipeptidyl peptidases produced by P. gingivalis , particularly dipeptidyl peptidase 4, interact with and degrade incretin hormones, which are essential for the upregulation of insulin and modulation of blood glucose levels . Finally, the decline in masticatory function due to severe periodontal disease and tooth loss has been associated with changes in diet , and the intake of certain nutrients has been reported to be associated with glycemic control . Although the relationship between periodontal disease and glycemic control is well established, and the underlying mechanisms described above have been proposed, it remains controversial which periodontal disease-related factors are strongly associated with glycemic control. In this study, therefore, we aimed to examine the relationship between glycemic control and periodontal status, salivary periodontopathic bacterial levels, and masticatory function. 

Recruitment of the study population In 2017, 737 community-dwelling adults residing in the Goto Islands in Nagasaki underwent medical examinations. Under the guidance of Japan’s Ministry of Health, Labor, and Welfare, the municipal government of Goto City promotes medical examinations for community-dwelling adults for the screening and treatment of noncommunicable diseases. We also conducted a dental examination and collected saliva samples from the participants to measure their levels of periodontopathic bacteria . Individuals who refused to undergo a saliva test or periodontal examination were excluded (Fig. ). We also excluded those who did not respond to the questionnaire and edentulous individuals for whom periodontal examinations could not be performed. The final study population comprised 671 participants aged 29–92 years (mean 65.3 years, median 67.0 years), 236 males and 435 females. This cross-sectional study was conducted in accordance with the tenets of the Declaration of Helsinki 2013 and the protocol was approved by the Nagasaki University Ethics Committee (#14051404-13). All the participants received verbal and written information prior to their participation and provided written informed consent. 

In 2017, 737 community-dwelling adults residing in the Goto Islands in Nagasaki underwent medical examinations. Under the guidance of Japan’s Ministry of Health, Labor, and Welfare, the municipal government of Goto City promotes medical examinations for community-dwelling adults for the screening and treatment of noncommunicable diseases. We also conducted a dental examination and collected saliva samples from the participants to measure their levels of periodontopathic bacteria . Individuals who refused to undergo a saliva test or periodontal examination were excluded (Fig. ). We also excluded those who did not respond to the questionnaire and edentulous individuals for whom periodontal examinations could not be performed. The final study population comprised 671 participants aged 29–92 years (mean 65.3 years, median 67.0 years), 236 males and 435 females. This cross-sectional study was conducted in accordance with the tenets of the Declaration of Helsinki 2013 and the protocol was approved by the Nagasaki University Ethics Committee (#14051404-13). All the participants received verbal and written information prior to their participation and provided written informed consent. 

The participants underwent a routine medical examination. Body weight and height were measured while they wore lightweight clothing and no shoes (InBody470; InBody, Tokyo, Japan), and body mass index (BMI) was calculated. A venous blood sample was obtained and blood tests were performed, including the HbA1c test: HbA1c levels were measured using high-performance liquid chromatography (HLC-723G7; Tosoh, Tokyo, Japan). Information on the participants’ demographics (age, sex), exercise habit (at least 30 min per week), alcohol consumption, late-night eating (within 2 h of bedtime), diabetes treatment, and smoking status (currently smoking or not) were collected using a self-administered questionnaire . 

Trained dentists examined the participants’ full-mouth dental status, including number of teeth, caries status, type of prosthetic restorations, PPD, clinical attachment level (CAL), and bleeding on probing (BOP), using a dental mirror and periodontal probe under lighting. Dental caries was diagnosed according to the criteria recommended by the World Health Organization . PPD and CAL were measured at four sites per tooth (mesio-buccal, mid-buccal, disto-buccal, and lingual) in all teeth excluding the third molars, and the intraclass correlation coefficients for the three examiners and one gold standard examiner involved were 0.78–0.90. Occlusal support areas were evaluated using functional tooth units (FTUs), defined as pairs of occluding posterior teeth. One pair of occluding premolars was defined as one FTU, and one pair of occluding molars was defined as two FTUs. Thus, one individual with complete dentition had 12 FTUs (excluding the third molars). The FTU count was divided into three categories: (1) number of FTUs comprising natural teeth (n-FTU); (2) sum of natural teeth and artificial teeth on implant-supported and fixed prostheses (nif-FTU); and (3) sum of natural teeth and artificial teeth on implant-supported, fixed, and removable prostheses (total FTU) . Carious teeth with extensive coronal destruction were regarded as nonfunctional. 

All saliva samples were collected between 09:00 and 11:00. The participants were required to abstain from eating, drinking, and brushing their teeth for two hours prior to saliva collection. Masticatory stimulated saliva was collected from each participant using an OMNIgene OM-501 (DNA Genotek, Ottawa, Canada). Bacterial DNA was extracted from 200 µL of saliva using a QIAamp MinElute Viruses Spin kit (Qiagen, Hilden, Germany) and quantified using an Mx3000P (Agilent, Santa Clara, CA, USA) quantitative polymerase chain reaction system. The sequences of the specific primers for P. gingivalis , A. actinomycetemcomitans , and total bacteria have been described previously . Standard curves for each organism were plotted for each primer set using threshold cycle values obtained by the amplification of 10-fold serial dilutions (1–10 7 colony-forming units [CFU]) of previously quantified bacterial DNA. Bacterial DNA standards and sample DNA were run in duplicate, and their means were used to calculate bacterial levels. The CFU value, equivalent to the bacterial DNA in each sample, was converted to a logarithm. Statistical analysis All statistical analyses were performed using the JMP15.0.0 software (SAS Institute, Cary, NC, USA). Continuous variables are described using means and standard deviations (SDs), while categorical variables are described using numbers. Pearson’s correlation analysis was performed to determine the correlation between HbA1c levels and the continuous variables. For categorical variables, the Student’s t -test or Welch’s t -test was used to evaluate the differences between two groups, depending on within-group variance. Multivariable linear regression analyses were performed with HbA1c level as the dependent variable. First, the relationship between HbA1c levels and the following independent variables was explored: age, BMI, sex, exercise habit, regular dental checkups, alcohol consumption, late-night eating, diabetes treatment, BOP, PPD, CAL, salivary P. gingivalis level, salivary A. actinomycetemcomitans level, salivary total bacterial level, number of teeth, n-FTU, nif-FTU and total FTU. Variables associated with HbA1c levels in the bivariate analysis were included in the multivariable linear regression analyses as independent variables. As the three FTUs are similar variables representing the occlusal support area, we created three models with n-FTU, nif-FTU, and total FTU as independent variables to examine their associations with HbA1c levels. Two-tailed p -values < 0.05 were taken to indicate statistically significant differences. 

All statistical analyses were performed using the JMP15.0.0 software (SAS Institute, Cary, NC, USA). Continuous variables are described using means and standard deviations (SDs), while categorical variables are described using numbers. Pearson’s correlation analysis was performed to determine the correlation between HbA1c levels and the continuous variables. For categorical variables, the Student’s t -test or Welch’s t -test was used to evaluate the differences between two groups, depending on within-group variance. Multivariable linear regression analyses were performed with HbA1c level as the dependent variable. First, the relationship between HbA1c levels and the following independent variables was explored: age, BMI, sex, exercise habit, regular dental checkups, alcohol consumption, late-night eating, diabetes treatment, BOP, PPD, CAL, salivary P. gingivalis level, salivary A. actinomycetemcomitans level, salivary total bacterial level, number of teeth, n-FTU, nif-FTU and total FTU. Variables associated with HbA1c levels in the bivariate analysis were included in the multivariable linear regression analyses as independent variables. As the three FTUs are similar variables representing the occlusal support area, we created three models with n-FTU, nif-FTU, and total FTU as independent variables to examine their associations with HbA1c levels. Two-tailed p -values < 0.05 were taken to indicate statistically significant differences. 

General characteristics of the study population The study population comprised 671 participants with a mean age of 65.3 years and a mean HbA1c level of 5.7% (Table ). The highest age was 92 years and the lowest was 29. Forty-one participants had an HbA1c level ≥ 6.5, which is the reference value for DM as defined by the American Diabetes Association, and 39 participants were receiving DM treatment. 

The study population comprised 671 participants with a mean age of 65.3 years and a mean HbA1c level of 5.7% (Table ). The highest age was 92 years and the lowest was 29. Forty-one participants had an HbA1c level ≥ 6.5, which is the reference value for DM as defined by the American Diabetes Association, and 39 participants were receiving DM treatment. 

Age and BMI were positively correlated with HbA1c levels (Table ) ( r = 0.264 and r = 0.207, respectively; p < 0.001 in both cases). With regard to periodontal status, only CAL was positively correlated with HbA1c level ( r = 0.080, p = 0.039). For bacterial levels, only salivary P. gingivalis levels were positively correlated with HbA1c levels ( r = 0.139, p = 0.002). All masticatory function variables (i.e., number of teeth, n-FTU, nif-FTU, and total FTU) were negatively correlated with HbA1c levels ( r = − 0.134, r = − 0.153, r = − 0.144, and r = − 0.112, respectively; p < 0.001 for the first three and p = 0.004 for total FTU). The HbA1c levels of the male participants were significantly higher than those of the female participants ( p = 0.006; Table ). Those of participants with an exercise habit were significantly higher than those of participants with no exercise habit ( p = 0.013), and those of participants taking diabetes medications were significantly higher than those not doing so ( p < 0.001). Multivariable linear regression analysis to determine factors associated with HbA1c levels As the three FTUs are similar variables representing occlusal support area, we created three models with n-FTU, nif-FTU, and total FTU as independent variables to examine their association with HbA1c levels (Table ). In Models 1 and 2, none of the variables related to periodontal and dentitional status or salivary bacterial levels were significantly associated with HbA1c levels. In Model 3, total FTU, but not the number of teeth, was significantly associated with HbA1c levels ( B = − 0.12, p = 0.008). 

As the three FTUs are similar variables representing occlusal support area, we created three models with n-FTU, nif-FTU, and total FTU as independent variables to examine their association with HbA1c levels (Table ). In Models 1 and 2, none of the variables related to periodontal and dentitional status or salivary bacterial levels were significantly associated with HbA1c levels. In Model 3, total FTU, but not the number of teeth, was significantly associated with HbA1c levels ( B = − 0.12, p = 0.008). 

In our multivariable analysis, none of the variables related to periodontal status or periodontopathic bacteria were associated with HbA1c levels. Of the variables that were related to masticatory function, total FTU score was significantly associated with HbA1c levels, whereas the number of teeth and the n- and nif-FTU scores were not. This suggests that among the factors that are related to periodontal disease, only a decrease in total FTU score, which is an indicator of occlusal support that includes dentures, was associated with HbA1c levels. Variables related to periodontal status were not associated with HbA1c levels, even though HbA1c levels were significantly correlated with the severity of periodontitis/periodontal diseases in previous cross-sectional and longitudinal studies . This discrepancy may be attributable to the low severity of periodontitis in our study population. As shown in Table , the mean PPD and CAL were 1.9 and 2.5 mm, respectively. Furthermore, periodontopathic bacteria levels in the saliva were not associated with HbA1c levels, although in a previous study, P. gingivalis was detected more frequently in patients with type 2 DM with elevated HbA1c levels than in those with depressed HbA1c levels . This discrepancy could be due to differences in sampling methods: while the previous study analyzed the bacterial flora in the subgingival area, we did it in the saliva. Differences in the bacterial flora can be more clearly detected in the subgingival area than in the saliva. Masticatory function has been reported to be associated with glycemic control. The degree of mastication affects the glycemic index (a qualitative indicator of the ability of carbohydrates to increase blood glucose levels) . Implant-supported prosthesis delivery to partially or completely edentulous diabetic individuals improves their HbA1c balance . Since FTU score is one of the key determinants of masticatory performance , these reports support the fact that the present study shows an association between total FTU score and glycemic control. Of the three categories of FTU scores, only total FTU was associated with HbA1c levels. A low Eichner classification score has been reported to be associated with increased HbA1c levels in patients with type 2 DM . Since the Eichner classification is based on the occlusal contact of naturally existing teeth in the premolar and molar regions, this contradicts our finding that there was no association between n-FTU and HbA1c, since n-FTU is an indicator of occlusal support areas in natural teeth. It should be noted that the mean n-, nif-, and total FTU scores in the study population were 5.8, 6.6, and 9.5, respectively. The proportion of participants wearing dentures was relatively high, probably due to their advanced age. It is possible that total FTU score better reflects the actual masticatory function in older adults than other FTU and Eichner scores, and this may have contributed to the association with HbA1c levels we observed. In a previous study, total FTU score in diabetic participants did not differ significantly from that in nondiabetic participants, although it was somewhat lower . The discrepancy between the results of that study and this one may be due to differences in the study population classification methods used. In the previous study, participants were classified as diabetic or nondiabetic, but we did not do that in this study. This is the first study to show that total FTU score is associated with glycemic control. This study has several limitations. Although total FTU score was found to be associated with HbA1c levels, this was a cross-sectional study, so we could not establish a cause-and-effect relationship. Future longitudinal studies may reveal the causal relationships between the variables investigated in this study. It is unclear whether bacteria other than those examined are associated with glycemic control. In the future, measuring salivary levels of other bacteria may clarify their relationship with HbA1c levels. The mean HbA1c level of all participants in the present study was 5.7%, indicating that a relatively small proportion of the participants had impaired glucose tolerance. For assessment of glucose metabolism in populations with modestly impaired glucose tolerance, glycated albumin and 1,5-anhydroglucitol are superior to HbA1c . We used PPD, CAL, and BOP as indices of periodontal status. However, the periodontal inflamed surface area (PISA), which quantifies the inflammatory burden posed by periodontitis, is more suitable for representing inflammation of the entire mouth . Since this was a community-based examination targeting many participants, it was difficult to perform periodontal examination at six sites on every tooth, as required for the calculation of PISA. The questionnaire did not include a recent antibiotic history, which could have affected the bacteria levels in the saliva. This lack of information may have affected our analysis of the relationship between salivary bacteria and HbA1c levels. 

In this study, glycemic control was significantly associated with total FTU score. Within the limitations of this cross-sectional study, our findings suggest that the occlusal support area supplemented with removable dentures may affect glycemic control in populations of advanced age. Future longitudinal studies in the same cohort may reveal causal relationships between these factors. 

