
The prevalence of chronic degenerative diseases has been increasing due to changes in lifestyle and dietary habits associated with socioeconomic development1). Among chronic conditions, metabolic syndrome was characterized by the coexistence of risk factors such as hypertension, abdominal obesity, dyslipidemia, and impaired fasting glucose, and primarily occurred due to unhealthy dietary and lifestyle habits2). Metabolic syndrome posed a significant public health threat, increased the prevalence of diabetes and cardiovascular diseases, and adversely affected quality of life.
Oral health was critical for digestion and nutrition, and its deterioration led to reduced masticatory function and difficulties in consuming a balanced diet, thereby negatively impacting systemic health. As the prevalence of metabolic syndrome rose, its detrimental effects on oral health became more evident, making oral health management an essential indicator of overall health3). Metabolic syndrome promotes a chronic inflammatory state, increasing the risk of periodontitis, and the severity of periodontitis is associated with a higher prevalence of metabolic syndrome4). This can serve as a significant cause of tooth loss5).
Previous studies demonstrated associations between tooth loss and systemic conditions such as metabolic syndrome6,7), dementia8), obesity9), kidney disease10), cardiovascular disease11), diabetes11), and certain types of cancer12).
Tooth loss was regarded as an indicator of systemic health status and was closely linked to chronic inflammatory diseases. Oral health extended beyond localized issues in the oral cavity and was intricately connected to overall systemic health. Specifically, tooth loss not only represented the ultimate consequence of oral diseases but also negatively affected individuals’ quality of life and social interactions. Previous studies have reported some associations between metabolic syndrome and tooth loss; however, many of these studies focused on limited samples, resulting in low generalizability, or emphasized specific variables. This study aims to differentiate itself by utilizing large-scale population-based data and analyzing the effects of individual components of metabolic syndrome, thereby providing more comprehensive and distinctive findings.
This study aimed to evaluate the association between metabolic syndrome and tooth loss among Korean adults using data from the 4th to 7th cycles of the Korea National Health and Nutrition Examination Survey (KNHANES).
This study included 49,468 adults aged 19 years or older who participated in the 4th to 7th KNHANES and had available data on metabolic syndrome and oral examinations. General characteristics included sex, age, education level, income, occupation, and residential area. Occupations were classified based on the latest version of the Korean Standard Classification of Occupations (KSCO) applicable to each survey period, and regions were categorized into urban (dong) and rural (eup/myeon) areas according to residential location.
Metabolic syndrome was defined based on the criteria established by the U.S. National Cholesterol Education Program13) and the Korean Society for the Study of Obesity14). Participants were classified as having metabolic syndrome if they met three or more of the following criteria:
Abdominal obesity: Waist circumference ≥90 cm in male, ≥85 cm in female.
Hypertension: Systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg.
Fasting glucose: ≥100 mg/dl.
Hypertriglyceridemia: Triglycerides ≥150 mg/dl.
Low high-density lipoprotein cholesterol (HDL cholesterol) cholesterol: HDL cholesterol <40 mg/dl in male, <50 mg/dl in female.
In this study, out of a total of 49,468 participants, 12,362 (25.0%) were identified as having metabolic syndrome, while 37,106 (75.0%) were classified as not having the condition.
Tooth loss was assessed using oral examination data, specifically by converting records of teeth lost due to dental caries and teeth lost without caries experience into a binary variable indicating the presence or absence of tooth loss.
In this study, out of a total of 49,468 participants, 27,968 (56.5%) were found to have tooth loss, while 21,500 (43.5%) were found to have no tooth loss.
Because the KNHANES employed a complex sampling design, analyses were conducted using complex sample analysis methods. Differences in tooth loss according to general characteristics and the presence of metabolic syndrome were examined using complex sample chi-square tests. Complex sample logistic regression analysis was performed to investigate factors associated with tooth loss. All statistical analyses were conducted using SPSS Statistics for Windows, version 17.0 (SPSS Inc., Chicago, IL, USA). Statistical significance was set at p<0.05.
Tooth loss showed significant differences based on sociodemographic characteristics, including sex (p=0.004), age (p<0.001), education level (p<0.001), income (p<0.001), occupation (p<0.001), and residential area (p<0.001) (Table 1).
Tooth Loss according to Sociodemographic Characteristics
Variable | Classification | Tooth loss | Total (n=49,468) | p-value | |
---|---|---|---|---|---|
Yes (n=27,968) | No (n=21,500) | ||||
Sex | Male | 12,173 (57.3) | 9,062 (42.7) | 21,235 (100) | 0.004 |
Female | 15,795 (55.9) | 12,438 (44.1) | 28,233 (100) | ||
Age (y) | ≤39 | 4,071 (26.9) | 11,084 (73.1) | 15,155 (100) | <0.001 |
40s | 4,322 (44.3) | 5,430 (55.7) | 9,752 (100) | ||
50s | 6,404 (66.7) | 3,196 (33.3) | 9,600 (100) | ||
60s | 7,049 (83.7) | 1,373 (16.3) | 8,422 (100) | ||
70s | 5,173 (92.9) | 397 (7.1) | 5,570 (100) | ||
≥80 | 949 (97.9) | 20 (2.1) | 969 (100) | ||
Education level | ≤Elementary school | 9,950 (86.9) | 1,505 (13.1) | 11,455 (100) | <0.001 |
Middle school | 3,948 (74.4) | 1,355 (25.6) | 5,303 (100) | ||
High school | 8,133 (48.8) | 8,522 (51.2) | 16,655 (100) | ||
College or higher | 5,937 (37.0) | 10,118 (63.0) | 16,055 (100) | ||
Income | Low | 7,205 (79.6) | 1,846 (20.4) | 9,051 (100) | <0.001 |
Lower-middle | 7,451 (60.1) | 4,939 (39.9) | 12,390 (100) | ||
Upper-middle | 6,758 (49.1) | 7,013 (50.9) | 13,771 (100) | ||
High | 6,554 (46.0) | 7,702 (54.0) | 14,256 (100) | ||
Occupation | Manager/professional | 2,446 (37.1) | 4,141 (62.9) | 6,587 (100) | <0.001 |
Clerical | 1,663 (36.7) | 2,873 (63.3) | 4,536 (100) | ||
Service/sales | 3,251 (51.1) | 3,116 (48.9) | 6,367 (100) | ||
Agriculture/fishery | 2,869 (84.3) | 533 (15.7) | 3,402 (100) | ||
Manufacturing/labor | 2,755 (56.0) | 2,162 (44.0) | 4,917 (100) | ||
Simple labor | 2,994 (69.5) | 1,313 (30.5) | 4,307 (100) | ||
Unemployed | 11,990 (62.0) | 7,362 (38.0) | 19,352 (100) | ||
Region | Urban | 20,747 (53.0) | 18,384 (47.0) | 39,131 (100) | <0.001 |
Rural | 7,221 (69.9) | 3,116 (30.1) | 10,337 (100) |
Values are presented as n (%).
p-value by χ2-test.
The prevalence of tooth loss showed a statistically significant difference based on the presence of metabolic syndrome (p<0.001). Significant differences in tooth loss prevalence were also observed according to abdominal obesity, elevated triglycerides, low HDL cholesterol, elevated blood glucose, and hypertension (p<0.001) (Table 2).
Tooth Loss according to Metabolic Syndrome
Variable | Classification | Tooth loss | Total (n=49,468) | p-value | |
---|---|---|---|---|---|
Yes (n=27,968) | No (n=21,500) | ||||
Metabolic syndrome | Yes | 8,724 (70.6) | 3,638 (29.4) | 12,362 (100) | <0.001 |
No | 19,244 (51.9) | 17,862 (48.1) | 37,106 (100) | ||
Abdominal obesity | Yes | 8,824 (65.8) | 4,582 (34.2) | 13,406 (100) | <0.001 |
No | 19,144 (53.1) | 16,918 (46.9) | 36,062 (100) | ||
High triglycerides | Yes | 8,952 (62.6) | 5,353 (37.4) | 14,305 (100) | <0.001 |
No | 19,016 (54.1) | 16,147 (45.9) | 35,163 (100) | ||
Low HDL cholesterol | Yes | 12,083 (62.6) | 7,228 (37.4) | 19,311 (100) | <0.001 |
No | 15,885 (52.7) | 14,272 (47.3) | 30,157 (100) | ||
Fasting blood glucose | Yes | 10,599 (69.7) | 4,604 (30.3) | 15,203 (100) | <0.001 |
No | 17,369 (50.7) | 16,896 (49.3) | 34,265 (100) | ||
Blood pressure | Yes | 10,633 (69.6) | 4,641 (30.4) | 15,274 (100) | <0.001 |
No | 17,335 (50.7) | 16,859 (49.3) | 34,194 (100) |
Values are presented as n (%).
p-value by χ2-test.
HDL: high-density lipoprotein.
Complex sample logistic regression analysis was performed to identify factors influencing tooth loss (Table 3). Independent variables included those that showed statistically significant results in the complex sample chi-square test, while the dependent variable was the presence or absence of tooth loss.
Factors Influencing Tooth Loss
Tooth loss | Variable | Classification | OR | 95% CI | p-value | |
---|---|---|---|---|---|---|
LLCI | ULCI | |||||
Yes (ref=No) | Sex | Male | 0.819 | 0.759 | 0.884 | <0.001 |
Female | 1.000 | |||||
Age (y) | ≤39 | 0.019 | 0.011 | 0.034 | <0.001 | |
40s | 0.038 | 0.021 | 0.067 | <0.001 | ||
50s | 0.074 | 0.042 | 0.130 | <0.001 | ||
60s | 0.149 | 0.086 | 0.260 | <0.001 | ||
70s | 0.301 | 0.168 | 0.539 | <0.001 | ||
≥80 | 1.000 | |||||
Education level | ≤Elementary school | 1.652 | 1.481 | 1.843 | <0.001 | |
Middle school | 1.522 | 1.370 | 1.691 | <0.001 | ||
High school | 1.179 | 1.107 | 1.256 | <0.001 | ||
College or higher | 1.000 | |||||
Income | Low | 1.155 | 1.050 | 1.271 | 0.003 | |
Lower-middle | 1.110 | 1.032 | 1.195 | 0.005 | ||
Upper-middle | 0.992 | 0.930 | 1.059 | 0.815 | ||
High | 1.000 | |||||
Occupation |
Manager/professional | 1.015 | 0.934 | 1.103 | 0.720 | |
Clerical | 1.010 | 0.923 | 1.106 | 0.824 | ||
Service/sales | 1.056 | 0.974 | 1.145 | 0.188 | ||
Agriculture/fishery | 1.410 | 1.210 | 1.644 | <0.001 | ||
Manufacturing/labor | 1.172 | 1.067 | 1.287 | 0.001 | ||
Simple labor | 1.205 | 1.088 | 1.336 | <0.001 | ||
Unemployed | 1.000 | |||||
Region | Urban | 0.813 | 0.752 | 0.879 | <0.001 | |
Rural | 1.000 | |||||
Metabolic syndrome | Yes | 1.186 | 1.107 | 1.271 | <0.001 | |
No | 1.000 |
p-value by complex sample logistic regression analysis.
OR: odds ratio, CI: confidence interval, LLCI: lower limit confidence interval, ULCI: upper limit confidence interval.
Tooth loss was considered a multifaceted indicator of oral health, contributing to nutritional deficiencies and overall physical deterioration. It also influenced metabolic syndrome, which often arose from poor dietary habits15). The interconnectedness between oral health and systemic health provided sufficient justification for the need for preventive and comprehensive care to promote a healthy life16). Therefore, this study was conducted to examine the association between metabolic syndrome and tooth loss among Korean adults.
In this study, differences in tooth loss according to general characteristics showed statistically significant associations with sex (p=0.004), age (p<0.001), education level (p<0.001), income (p<0.001), occupation (p<0.001), and residential area (p<0.001). The number of missing teeth was relatively higher in female compared to male. It also increased with age, decreased educational levels, lower income levels, employment in agriculture, forestry, or fishery sectors, and residence in rural areas. Previous studies analyzing the association between sociodemographic characteristics and tooth loss among Korean adults were lacking, making it difficult to compare the findings of this study. However, the results were similar to those of a study conducted by Kim et al.10), which reported that among elderly Koreans with chronic kidney disease, the number of missing teeth increased with older age, lower income levels, and lower educational attainment. Additionally, the findings of this study were similar to those of a study by Ju17), which examined patients with diabetes and reported that the number of missing teeth was higher among individuals with older age, lower income levels, and those residing in rural areas. In this study, the proportion of missing teeth was higher in female compared to male. This may be attributed to the physiological changes female undergo after menopause. Without proper health management during this period, health issues may arise more easily. Specifically, one of the most significant physical changes during menopause is the reduction of estrogen hormone levels, which can lead to periodontal inflammation and alveolar bone loss18), potentially influencing tooth loss. The increase in tooth loss with age was thought to result from aging, which led to decreased salivation and reduced immunity, thereby increasing the risk of tooth loss. Additionally, the accumulation of periodontal disease and dental caries over time further exacerbated this risk. Lower levels of education and income might limit access to and understanding of oral health information, leading to inadequate preventive care behaviors. Additionally, lower income could have restricted regular dental visits and access to appropriate treatments. The higher rate of tooth loss among agricultural and fishery workers and rural residents could be due to a lack of healthcare facilities and limited accessibility, which might have delayed preventive care and timely treatments, thereby increasing the risk of tooth loss.
Metabolic syndrome became increasingly severe as overall socioeconomic levels improved and nutritional intake increased, while physical activity decreased relatively19). As the prevalence of metabolic syndrome increased, its adverse effects on oral health also grew.
In this study, the prevalence of tooth loss was relatively higher among individuals with metabolic syndrome. Additionally, those with abdominal obesity, elevated triglycerides, low HDL cholesterol, elevated blood glucose, or high blood pressure exhibited a relatively higher prevalence of tooth loss (p<0.001). This finding was similar to the results of Kang16), which demonstrated that the number of missing teeth increased as the number of metabolic syndrome components increased. It also aligned with the findings of Hwang and Lee20), who reported that higher blood pressure was associated with an increased risk of tooth loss in a study on the relationship between tooth loss and systemic health. Additionally, it was consistent with the results of Kang16), who observed a tendency for individuals with elevated triglycerides to have a greater number of missing teeth. Abdominal obesity was found to increase systemic inflammation levels, which promoted inflammatory responses in periodontal tissues and heightened the risk of periodontal disease21,22). As periodontal disease progressed, the supporting structures of the teeth were destroyed, potentially leading to tooth loss. Elevated triglycerides and low HDL cholesterol negatively impacted vascular health, potentially reducing blood flow to the periodontal tissues. This reduction in blood flow could induce hypoxia in the periodontal tissues, weaken resistance to bacterial infections, and accelerate the progression of periodontal disease, ultimately resulting in tooth loss. Diabetic patients have weakened immunity, making them more vulnerable to oral infections, and untreated periodontitis can lead to an increased risk of tooth loss23).
To identify factors influencing tooth loss, variables that showed statistically significant results in the complex sample chi-square test were included as independent variables, while the dependent variable was the presence of tooth loss. The results showed that men were relatively less likely to have missing teeth compared to female (odds ratio [OR]=0.819, p<0.001), and younger age was associated with a lower likelihood of having missing teeth. Individuals with lower education levels were more likely to have missing teeth, and compared to those with high income, those with middle-low income (OR=1.110, p=0.005) and low income (OR=1.155, p=0.003) were more likely to have missing teeth. In terms of occupation, individuals in machinery/assembly (OR=1.172, p=0.001), simple labor (OR=1.205, p<0.001), and agriculture/forestry/fisheries (OR=1.410, p<0.001) were more likely to have missing teeth compared to the unemployed. Regarding residential area, individuals in urban areas were less likely to have missing teeth compared to those in rural areas (OR=0.813, p<0.001). It has been reported that the severity of periodontal disease and the extent of alveolar bone loss increase in individuals aged 30 years and older24). As age increases, the likelihood of exposure to various risk factors also rises, which is believed to influence the rate of tooth loss. The analysis of the association between education level and tooth loss in adults revealed that the prevalence of tooth loss was higher among individuals with lower education levels. This finding was consistent with the results reported by Cheon et al.25). Additionally, in the study by Choi et al.26), age, residential area, household income, education level, and household type were reported to be associated with severe tooth loss. Individuals with metabolic syndrome exhibited an OR of 1.19 (95% confidence interval: 1.11∼1.27) for tooth loss. A previous study reported that individuals with metabolic syndrome had a 1.4 times higher risk of periodontal disease22), suggesting that metabolic syndrome and its components increase the risk of periodontal disease and tooth loss.
The findings of this study demonstrated that sociodemographic characteristics and metabolic syndrome among Korean adults were associated with tooth loss. These results indicated that the components of metabolic syndrome might have served as risk factors for tooth loss.
The limitation of this study was that, although factors influencing metabolic syndrome and tooth loss were analyzed using data from the KNHANES, the study was conducted with a cross-sectional design, which did not allow for the determination of precise causal relationships. Therefore, future research should include follow-up studies to observe and investigate the causal factors and temporal changes in the development of metabolic syndrome and tooth loss. Additionally, health behaviors such as smoking, alcohol consumption, and exercise, as well as oral health behaviors including tooth brushing frequency and the use of oral hygiene products, may influence tooth loss. Therefore, future research should incorporate these factors into an expanded analysis.
Despite these limitations, the study successfully identified the factors associated with tooth loss and the risk factors for tooth loss according to sociodemographic characteristics and metabolic syndrome by utilizing the nationally representative KNHANES data.
The results of this study confirmed that sociodemographic characteristics and metabolic syndrome influenced tooth loss among Korean adults. These results suggested that sociodemographic factors and each component of metabolic syndrome could serve as risk factors for tooth loss in Korean adults. To validate these results, longitudinal follow-up studies are needed. Additionally, efforts should be made to develop oral health education programs and integrate systemic health management strategies to improve oral health among adults with metabolic syndrome.
None.
Conflict of interest
No potential conflict of interest relevant to this article was reported.
Ethical approval
This research received review exemption from Gangneung-Wonju National University Institutional Review Board (IRB No. GWNUIRB-R2019-11).
Authors contributions
Conceptualization: Jung-Hui Son and Soo-Myoung Bae. Formal analysis: Jung-Hui Son and Soo-Myoung Bae. Supervision: Jung-Hui Son and Soo-Myoung Bae. Writing-original draft: Jung-Hui Son and Soo-Myoung Bae. Writing-review & editing: Jung-Hui Son and Soo-Myoung Bae.
Funding
None.
Data availability
Data supporting the results of this study are available from the corresponding author or the Korean Society of Dental Hygiene Science upon reasonable request.
![]() |
![]() |