South Korea is entering the age of super-aging society. The 2015 Census of Older People estimates that proportion of those who aged 65 and over in South Korea is 13.2%, and forecasts that the proportion will continue to rise and reach 20.0% in 2025, entering the super-aging society [1,2]. In the era of super-aging society, the importance of maintaining general health of elderly is steadily increasing, and one of the crucial factors in general healthcare of elderly is managing oral health. Neglecting oral health management can lead to several oral diseases such as dental caries and periodontal disease, which can affect systemic health [3]. Especially, oral infectious diseases are definitive causal factors for systemic diseases, as oral microbial toxins and inflammations can spread to systemic conditions through metastatic inflammation, transient bacteremia, or aspiration pneumonia [4,5]. Risk for this oral health-related systemic disease is especially higher in elderly. Several characteristics of elderly such as decreased function of immune system, xerostomia, medication can make oral health management difficult, and increase the possibility that spread of oral infection would not be well controlled in elderly [6].

Thus, oral infectious disease is particularly important in elderly. For proper management of oral infectious disease, the understand of common oral infectious diseases as well as factors that can make elderly vulnerable to infection is important, which include dental caries, periodontitis, as well as xerostomia, halitosis, oral candidiasis, and systemic diseases. Xerostomia is very common oral condition, featuring with subjective sense of oral dryness [7]. Prevalence of xerostomia is 9.3% to 64.8% depending on studies, and it tends to increase in elderly [8-10]. Main causes of xerostomia include dysfunction of salivary gland, radiation therapy, chemotherapy, medication, and systemic diseases [11,12]. Symptoms of xerostomia include dryness, speech disturbances, and difficulty in chewing and swallowing food, which can impair the oral self-cleansing mechanism and thereby increase the risk and spread of oral infections [13].

Halitosis is also one of the common oral diseases among the elderly. Oral health problems account for more than 90% of the causes of halitosis, and the most common cause was tongue coating, and others were including periodontal disease, xerostomia, dental plaque, and faulty prostheses [14-16]. These oral health problems and halitosis share the common denominator, the oral infection from oral microbiome. Imbalanced oral microbiota caused by poor oral hygiene can cause several oral health problems, and produce volatile sulfur compounds (VSCs), which is the direct cause of halitosis [14]. Halitosis can significantly impact both oral and systemic health, as hydrogen sulfide (H₂S), one of the major components of VSCs, plays a crucial role in regulating cellular activities such as inflammation, apoptosis, and cell differentiation [17]. Notably, in the elderly, the distribution of the oral microbiome undergoes significant changes, characterized by a shift in dominant species, decreased diversity, and an increase in enteropathogens. These changes elevate the risk of both oral and systemic diseases [18,19], highlighting the critical importance of oral health management in the elderly.

Although needs to understand oral health condition and related oral and systemic disease are getting more important, previous studies about xerostomia, halitosis, and oral health of elderly are still insufficient, and their correlation with age is not fully investigated. This study aims to assess the level of halitosis and salivary parameters across different age groups and to investigate the association between age, halitosis, and salivary characteristics. In addition, this study aims to investigate the status of oral health and medication according to age, and their correlation with salivary flow rate and salivary buffer capacity. Main hypothesis of this study is that elderly will show decreased salivary flow rate and salivary buffer capacity, and have higher prevalence of halitosis, systemic disease, and poor oral health than younger counterparts. Additional hypothesis is that xerostomia, halitosis, oral health condition, systemic disease, and medication will interact have correlation with each other.

1. Research Subjects and Groups

This study targeted patients aged between teens to 80s who visited the Department of Orofacial Pain and Oral Medicine at Kyung Hee University Dental Hospital from August 2020 to May 2023, complaining xerostomia or halitosis. For sample size calculation, we used G*Power software (ver. 3.1.9.7, Heinrich-Heine-Universität Düsseldorf), found that 220 participants were suitable for statistical analysis (α level=0.05, the power=0.90, and the effect size=0.5). After screening, 303 patients were selected, and 29 patients were excluded due to the insufficient medical records. A total 274 patients (66 males, 208 females, mean age 59.39±16.10 years) were enrolled in this study. Patients were then divided into eight age groups according to 10-year increments: teens into age group 1, 20s into age group 2, and so on until age group 8.

2. Evaluation of Saliva and Halitosis

Evaluation of salivary parameters was performed at the patients’ initial visit, using GC Saliva Check Buffer kits (GC Company). Evaluated salivary parameters were salivary flow rate, salivary pH, and salivary buffer capacity, using the spitting method. First, patients were ordered to spit their saliva for 10 minutes in resting state. The amount of collected saliva was recorded as unstimulated flow rate (UFR). After measuring UFR, a salivary pH test strip was inserted into the unstimulated whole saliva, and salivary pH was recorded according to the color change of test strip (Fig. 1A). Next, patients were instructed to chew paraffin wax gum for 2 minutes, and spit their saliva for 5 minutes. This amount of collected saliva was recorded as stimulated flow rate (SFR). After measuring SFR, stimulated whole saliva was dropped onto the buffer test strip using a pipette, and salivary buffer capacity was recorded according to the color change of buffer test strip with the salivary buffer indicator (Fig. 1B). In terms of diagnosis criteria, normal UFR is 0.3-0.4 mL/min, and normal SFR is 1.5-2.0 mL, while hyposalivation is diagnosed when UFR is under 0.1 mL/min or SFR is under 0.7 mL/min [20]. Normal salivary pH is between 6.7-7.3, and abnormal salivary pH is under 6.3 [21]. Additionally, since there are several measuring methods for salivary buffer capacity, this study followed the guideline of manufacturer of salivary test kit, GC company, where score between 10-12 is normal salivary buffer capacity, 6-9 is low, and 0-5 is very low. All of the salivary evaluation procedures were performed by skilled dentists and dental hygienists, trained in standardized examination protocol.

3. Evaluation of Halitosis

The level of halitosis was assessed during the patients’ initial visit. Halitosis was evaluated using the Oral Chroma Twin Breasor II (iSenLab), which separates and measures H₂S and methyl mercaptan (CH₃SH) in parts per billion (ppb). For gas collection, a syringe was carefully inserted deep into the patients’ oral cavity, avoiding contact with the tongue or saliva, while the mouth remained closed. The collected gas was then introduced into the device for analysis, and the results were recorded (Fig. 1C). The VSC level was calculated as the sum of H₂S and CH₃SH concentrations. An abnormal VSC level was diagnosed when H₂S exceeded 112 ppb or CH₃SH exceeded 26 ppb [22].

4. Evaluation of Oral Health Condition

Before the oral health examination, patients were asked for the reason of visit, and it was classified into five categories: stomatitis, glossodynia, xerostomia, halitosis, and taste disorder. Then oral health condition was evaluated and recorded by examination of skilled dentists. Patients rated their oral discomfort using a visual analog scale, with scores recorded on a scale from 0 to 10. Sticky saliva was checked when frosty or viscous saliva is observed with the naked eye. Oral hygiene was recorded with three grades of good, acceptable, and poor, according to the subjective judgment of clinician. Calculus deposition was evaluated in three levels according to the subjective judgment of clinician: none, where no visible calculus was observed; moderate, where visible calculus was observed in some teeth; and severe, where visible calculus was observed in almost all teeth. Tongue coating was checked if patients had white or yellowish tongue coating on the posterior 2/3 of tongue. Ulcer was checked if patients had any visible ulcer in oral mucosa. Oral candidiasis was evaluated by two categories: clinical impression of candidiasis and oral candidiasis. Clinical impression of candidiasis was checked if patients had any typical clinical symptoms of oral candidiasis, including tongue coating, tongue atrophy, or angular cheilitis. Oral candidiasis was checked if patients were proven to have oral fungus by swab culture, which was performed by collecting oral specimen with sterile transport swab (Transystem, COPAN), culturing in the medium, and evaluating the observed specimen. All of the culture procedure were following the criteria of the Department of Laboratory Medicine of Kyung Hee University Medical Center.

5. Evaluation of Systemic Disease and Medication

Systemic diseases and medication of patients were collected from the questionnaire at the patients’ initial visit. Systemic diseases were categorized into hypertension, diabetes, osteoporosis, and heart disease, which are the four most prevalent systemic diseases. Patients with overlapping conditions among these categories were included in each relevant group. Medications prescribed to patients were also recorded and classified into four categories: Amlodipine tab (amlodipine), for hypertension; Metformin tab (metformin), for diabetes; Alend tab (alendronate), for osteoporosis; and Lasix tab (furosemide), for heart and cardiovascular diseases.

6. Statistical Analysis

The data were analyzed using the IBM SPSS for Windows (version 26.0, IBM Corp.). Descriptive statistics were used to calculate means and standard deviations. To analyze the distribution of discontinuous data, we used the χ² and Bonferroni tests for the equality of proportions. Analysis of variance and Tukey’s post-hoc test were used to compare the values of parameters among the age groups. Spearman’s correlation analysis was used to determine factors associated with ageing and the other oral and systemic parameters. The correlation coefficients (r) indicate the strength of the correlation and range between −1 and 1; the closer the absolute value of r is to 1, the stronger is the relationship. For all analyses, the statistical significance was set at a two-tailed p-value<0.05.

7. Ethics Approval and Consent to Participate

The procedures for human subjects in this study were conducted according to the ethical standards of the Committee on Human Experimentation of our institution and the 1975 Declaration of Helsinki. This study was approved by the appropriate ethics review board of the Kyung Hee University Dental Hospital (IRB No. KH-DT23022). Informed consent was obtained from all participants in this study.

1. Sex and Age Distribution of Patients

A total of 274 participants were included in this study. Of these, 66 (22.8%) were male, and 208 (71.7%) were female. The distribution of participants across age groups was as follows: 9 individuals (3.3%) in their teens (age group 1), 10 (3.6%) in their 20s (age group 2), 11 (4.0%) in their 30s (age group 3), 30 (10.9%) in their 40s (age group 4), 63 (23.0%) in their 50s (age group 5), 66 (24.1%) in their 60s (age group 6), 67 (24.5%) in their 70s (age group 7), and 18 (6.6%) in their 80s (age group 8). The mean age of the participants was 59.39±16.10 years.

2. Salivary Parameters by Age Group

The salivary parameters across different age groups are presented in Fig. 2. Across the age groups, there was no significant difference in the UFR (p=0.229), SFR (p=0.971), salivary pH (p=0.606), and salivary buffer capacity (p=0.344). For UFR, age group 2 had the lowest mean value (0.28±0.18 mL/min) and age group 8 had the highest mean value (0.60±0.36 mL/min). For SFR, age group 1 had the lowest mean value (1.27±0.39 mL/min) and age group 8 had the highest mean value (1.51±0.64 mL/min). All of the age groups were in the normal range of salivary flow rate. For salivary pH, age group 2 had abnormal salivary pH (6.18±0.62), which was the lowest mean value among the age groups. Additionally, most age groups exhibited slightly lower salivary pH than the normal range, except for age group 8, which had a mean value of 6.77±0.63. For salivary buffer capacity, only age group 1 (10.67±1.22) and age group 3 (10.82±1.25) had normal salivary buffer capacity. Other age groups had lower salivary buffer capacity than normal range, and age group 2 had the lowest mean value (9.00±2.67).

3. Volatile Sulfur Compound Levels by Age Group

The VSC levels across different age groups are shown in Fig. 3. Age group 2 showed significantly higher mean level of CH₃SH (152.00±214.96 ppb) than the other age groups (p=0.049). For H₂S, age group 2 had the highest mean value (410.00±579.82 ppb) followed by age group 3 (318.50±635.00 ppb). However, relationship between H₂S and age groups was not statistically significant (p=0.393). For VSC, age group 2 had the highest mean value (112.40±355.44 ppb), but it was not statistically significant difference with the other age groups (p=0.051).

4. Distribution of Representative Systemic Diseases by Age Group

The distribution of the four representative systemic diseases is shown in Fig. 4. There was a significant difference in the prevalence of hypertension across the age groups (p=0.001), with a significantly higher incidence observed in the older age groups (age groups 7 and 8) compared to the other age groups. Similarly, the prevalence of diabetes also differed significantly across the age groups (p=0.010), with a higher incidence in age groups 7 and 8. In contrast, the differences in the prevalence of osteoporosis (p=0.099) and heart disease (p=0.235) across the age groups were not statistically significant.

5. Correlation between Age, Halitosis, and Salivary Flow Rate

Table 1 displays the result of correlation analysis between age, halitosis, salivary flow rate, and oral candidiasis. VSC and complaint of halitosis were strongly correlated (r=0.621, p<0.001). UFR and SFR also showed a statistically strong correlation (r=0.513, p<0.001).

6. Correlations of Age, Salivary Flow Rate, Medications, Halitosis, and Oral Health Conditions

This study examined the correlations between, medications, oral conditions, halitosis and salivary flow rate. The results of correlation analysis are presented in Table 2. Age was significantly related with amlodipine (r=0.249, p=0.001) and tongue coating (r=0.205, p=0.001). Among the medications, amlodipine was a significant factor in multiple medications and oral status. Amlodipine usage was significantly associated with age (r=0.249, p<0.001), metformin usage (r=0.243, p<0.001), alendronate usage (r=0.232, p<0.001), oral hygiene (r=0.208, p=0.001), sticky saliva (r=0.180, p=0.003), calculus deposition (r=0.169, p=0.005), tongue coating (r=0.134, p=0.027), and SFR (r=0.131, p=0.030). Additionally, metformin usage was significantly related with calculus deposition (r=0.135, p=0.025), and alendronate usage had a significant relationship was sticky saliva (r=0.140, p=0.021). Furthermore, sticky saliva was significantly correlated with VSC levels (r=0.183, p=0.002).

7. Salivary Flow Rate and Buffer Capacity according to Oral Diseases

Five oral diseases, which were the reason of visit, were examined and categorized: Group 1 was categorized as stomatitis, Group 2 as glossodynia, Group 3 as xerostomia, Group 4 as halitosis, and Group 5 as taste disorder. Correlation with saliva for each group was analyzed, and the results are displayed in Table 3. Salivary pH was significantly higher in Group 5 (7.50±0.58) than other groups (p=0.023). The mean value of UFR was highest in Group 5 (0.50±0.58 mL/min) and lowest in Group 4 (0.15±0.38 mL/min), but the difference was not significant (p=0.528). SFR was highest in Group 5 (2.25±0.50 mL/min) and lowest in Group 3 (1.27±0.84 mL/min), but the difference was not significant (p=0.051). Salivary buffer capacity was highest in Group 5 (11.25±1.50 mL/min) and lowest in Group 4 (8.85±2.44 mL/min), but the difference was not significant (p=0.501).

In this study, we aimed to investigate the changes in salivary parameters, halitosis, systemic diseases, and oral health conditions with increasing age, as well as to examine the correlations among these factors. The results showed that amlodipine usage and tongue coating were closely associated with increasing age, whereas salivary parameters and halitosis did not exhibit significant relationships with age. Regarding to age groups, CH₃SH level was significantly higher in age group 2, and prevalence of hypertension and diabetes was significantly higher in age group 7 and 8. In contrast, H₂S, VSC, all of the salivary parameters, prevalence of osteoporosis and heart disease were not significantly related with age groups. In addition, patients taking amlodipine were more likely to have sticky saliva, heavy calculus deposition, more tongue coating, poor oral hygiene, and lower SFR. Patients with taste disorder had significantly higher salivary pH.

In this study, CH₃SH level was significantly higher in the 20s group compared to other age groups, which is contrary to the result of previous studies suggesting that halitosis is not clearly associated with age, or halitosis is more prevalent in elderly [23,24]. Among the oral microbiome, Firmicutes were strongly related with production of CH₃SH, followed by Bacteroidetes [23]. The relative abundance of Firmicutes tends to increase, while that of Bacteroidetes decrease from childhood to elderly, and this increased ratio of Firmicutes could explain the increased prevalence of halitosis in elderly [25,26]. However, combined proportion of Firmicutes and Bacteroidetes in oral microbiome does not change drastically as age increases, and proportion of Firmicutes could increase in youngers with systemic disease or poor oral hygiene [18,27]. Hence, it’s not unusual that increased CH₃SH level is observed in younger patients, and the results of this study can be possible. Further studies would be needed with more and broader participants to accurately verify this result.

Contrary to the main hypothesis, salivary flow rate and salivary buffer capacity were not significantly different across the age groups. This result contrasts with previous studies suggesting that whole salivary flow rate tends to decrease in the elderly [12,28]. While several studies consistently report that the UFR is significantly lower in the elderly, there is ongoing debate regarding whether the SFR also decreases with age [29,30]. SFR is mainly composed of saliva from parotid gland, whose function is not significantly decreased with increasing age, and thus it is possible that SFR is not significantly different with increasing age [29,31]. Also, regarding to UFR, a study reported that UFR is closely related with oral condition while SFR is not [31]. Since this study included only patients with oral discomfort, UFR of younger participants might be influenced to decrease by their poor oral condition, leading to the insignificant difference with elderly. Further studies would be needed to re-evaluate this result, with design of case-control study including healthy participants.

Regarding to the systemic disease, hypertension and diabetes were closely related with increasing age, which is corresponding to the previous studies [32,33]. Also amlodipine, which is antihypertensive drug, showed a significant relationship with several factors including sticky saliva, oral hygiene, calculus, tongue coating, and SFR in this study. This results are strongly emphasizing the importance of evaluating systemic disease and medication during oral health management in elderly. It is already well proven that systemic diseases as well as related medications and the oral health condition are strongly related [6,34]. Hypertension can cause angioedema, xerostomia or lichenoid reaction in oral mucosa, and patients with periodontal disease had increased risk for hypertension. And patients using antihypertensive drugs had higher risk of xerostomia, which was more severe in elderly [35]. Also, diabetes can cause xerostomia and imbalance of microorganisms in mouth, which can lead to taste disorder, increased risk of oral candidiasis, and periodontal disease. Since the prevalence of hypertension and diabetes in South Korea is steadily increasing [36,37], clinicians should even more carefully consider systemic disease during oral healthcare, especially in elderly.

Correlation analysis revealed the correlation of age with tongue coating. Tongue coating is comprised of several components including residual food, bacterial by-product, leukocytes, and keratinized products of degeneration, and thus tongue coating is closely related to the oral health and ability to manage oral condition [38]. Tongue coating is a significant contributing factor to certain oral diseases, including halitosis and taste disorders [39]. Tongue coating can also interact with systemic health, since microbiota in tongue coating can spread into respiratory or digestive system, affecting several metabolic pathways and causing disturbance of nitric oxide homeostasis, taste receptor dysfunction, and mucosal barrier destruction [40]. Thus, tongue coating can significantly impact both oral and systemic health; however, its exact etiology remains unidentified. Previous studies have suggested various potential contributing factors to tongue coating formation, including age, sex, oral hygiene, smoking, xerostomia, and systemic diseases. Nevertheless, the findings across studies remain controversial and require further validation [41]. Nevertheless, elderly patients had more tongue coating in this study, and this results would suggest the importance of oral health management in elderly.

In the analysis between oral disease groups and salivary function, salivary pH was significantly higher in taste disorder group. Alkaline state of saliva can be due to the interaction between oral bacteria and food debris, which can lead to plaque formation. However, excessive alkalinity of saliva can bring similar anaerobic conditions as academia, and their impact on oral conditions is almost same [21]. In previous studies, some reported that taste disorder is not closely related with salivary pH, while other reported that dysgeusia for certain taste is related with low pH [42,43]. Due to this controversial results, further studies should be needed to investigate relationship between taste disorder and salivary pH.

Despite the findings of this study, several limitations should be acknowledged. Primarily, evaluation of oral health was depending on the subjective judgement of examiners, and there might be lack of consistency. Additionally, adjustments for false discoveries were not applied during multiple correlation analyses, necessitating caution in interpreting the results. Nonetheless, this study provides valuable insights into correlations between age, salivary parameters, halitosis, oral health, and systemic disease.

In conclusion, this study comprehensively examined changes and correlations among salivary parameters, halitosis, oral health, and major systemic diseases across different age groups. While the correlation between aging, salivary parameters, and halitosis was less significant than anticipated, the study successfully identified relationships between aging, oral health, medication use, and systemic diseases. These findings highlight the importance of considering a broad range of factors in managing oral health, particularly in the context of an aging population. By raising local awareness and integrating these insights into treatment plans for xerostomia and halitosis, this study underscores the potential to enhance treatment efficiency, improve the quality of life, and support a stable lifestyle for the elderly.

No potential conflict of interest relevant to this article was reported.

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

None.

Conceptualization: YHL, SS. Data curation: SS, TSK, YHL. Formal analysis: SS, TSK, YHL. Methodology: YHL, SS. Project administration: YHL, SS. Visualization: SS, TSK, YHL. Writing - original draft: SS, TSK, YHL. Writing - review & editing: SS, TSK, YHL.