Severe Periodontitis Is Associated with Insulin ...

ORIGINAL

ARTICLE

Severe Periodontitis Is Associated with Insulin Resistance in Non-abdominal Obese Adults In-Seok Song, Kyungdo Han, Yong-Moon Park, Suk Ji, Sang Ho Jun, Jae-Jun Ryu,* and Jun-Beom Park* Department of Oral and Maxillofacial Surgery (I.-S.S., S.H.J.), Korea University Anam Hospital, Seoul 02841, Republic of Korea; Department of Biostatistics, College of Medicine (K.H.), The Catholic University of Korea, Seoul 06591, Republic of Korea; Epidemiology Branch (Y.-M.P.), National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709; Department of Periodontology (S.J.), Ajou University Hospital, Suwon 16499, Republic of Korea; Department of Prosthodontics (J.-J.R.), Korea University Anam Hospital, Seoul 02841, Republic of Korea; and Department of Periodontics, College of Medicine (J.-B.P.), The Catholic University of Korea, Seoul 06591, Republic of Korea

Context: We hypothesized that insulin resistance, even with normal body weight (body mass index or waist circumference), can aggravate periodontitis severity. Objective: We investigated the associations between diabetes, insulin resistance, and severe periodontitis. Design: Among 29 235 total participants, 5690 subjects aged ⱖ 30 y who had periodontal disease with community periodontal index (CPI) of 3 or 4 were selected for this study. Participants: Data were derived from the 2008 –2010 Korea National Health and Nutrition Examination Survey. Results: Patients diagnosed with type 2 diabetes were more likely to have severe periodontitis (CPI 4) compared with patients with normal glucose tolerance or impaired fasting glucose (P ⬍ .001). Subjects with severe periodontitis had significantly higher prevalence of abdominal obesity, serum triglycerides, and insulin resistance (P values of .012, ⬍.001, and .003, respectively). The odds ratios (ORs) for prevalence of severe periodontitis were significantly increased from normal glucose tolerance and impaired fasting glucose (OR ⫽ 1.32; 95% confidence interval, 1.06 –1.64) to type 2 diabetes (OR ⫽ 1.5; 95% CI, 1.11–2.02), after adjusting for potential confounders (P for trend ⫽ .003). The prevalence of severe periodontitis increased significantly with increasing insulin resistance (P for trend ⫽ .04) in nondiabetic individuals. Furthermore, insulin-resistant individuals with normal waist circumference showed significantly higher odds of severe periodontitis (OR ⫽ 1.47; 95% CI, 1.16 –1.87) than did insulinsensitive individuals with normal waist circumference. Conclusions: Non-abdominally obese subjects with insulin resistance were more likely to have severe periodontitis. Insulin resistance can be considered an independent risk factor of periodontal disease in normal weight population defined by abdominal obesity. (J Clin Endocrinol Metab 101: 4251– 4259, 2016)

ISSN Print 0021-972X ISSN Online 1945-7197 Printed in USA Copyright © 2016 by the Endocrine Society Received May 8, 2016. Accepted August 30, 2016. First Published Online September 6, 2016

doi: 10.1210/jc.2016-2061

* J.-J.R. and J.-B.P. contributed equally to the study. Abbreviations:BMI, body mass index; BP, blood pressure; CPI, community periodontal index; CVD, cardiovascular disease; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostatic model assessment of insulin resistance; KNHANES, Korea National Health and Nutrition Examination Survey; MHNW, metabolically healthy normal weight; MONW, metabolically obese normal weight; T2D, type 2 diabetes; WC, waist circumference.

J Clin Endocrinol Metab, November 2016, 101(11):4251– 4259

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Periodontitis and Insulin Resistance

eriodontitis is defined as dysfunctional periodontal immune-inflammatory reaction caused by bacterial pathogens, leading to periodontal breakdown and tooth loss (1). An estimated 50% of the global adult population and more than 60% of adults older than 60 years are reported to have periodontitis. Among adults with periodontitis, 10 –15% have severe periodontitis (1). Among the South Korean population, the overall prevalence of subjects with periodontal disease is 29.2% (2). Periodontitis is a well-known cause of several systemic diseases. Moderate-to-severe periodontitis was revealed to be closely associated with cardiovascular disease (CVD) (3). Bacteria and bacteria-driven lipopolysaccharide can damage the endothelium, causing monocyte adhesion to an injured site and an inflammatory response mediated by proinflammatory cytokines release (3). These pathogens accelerate the formation of atherosclerosis and increase the severity of CVD (4). Moreover, secondary-releasing circulating cytokines, including C-reactive protein, TNF-␣, and IL-6, and pathogens promote atherosclerosis, inflammation, and increased CVD mortality (3). Other diseases related to periodontal disease include diabetes, aspiration pneumonia, preterm birth/low birth-weight infants, renal disease, and neoplasm (3). Type 2 diabetes (T2D) is a chronic metabolic disorder characterized by elevated blood glucose, insulin resistance, and loss of serum insulin (5). The disease is characterized by the failure of pancreatic ␤-cell response responsible for compensating for insulin resistance, which results in hyperglycemia and consequently T2D (6). Much of the population worldwide suffers from diabetes—346 million people—which will increase to 439 million by 2030 (1). T2D is also linked to macrovascular atherogenesis and microvascular complications such as retinal, renal, and neural pathogenesis (6). T2D is also known as a modifying factor of periodontitis (3). Prolonged and impaired serum glucose control provokes macrophage or neutrophil dysfunction (7), giving rise to accumulation of advanced glycation end-products and causing periodontal vasculature breakdown and delayed wound healing (8). Insulin resistance is defined as a lack of bodily response to insulin despite insulin secretion (9). One large samplebased cohort study reported that insulin resistance is responsible for metabolic syndrome (MS), hypertension, obesity, hypercholesterolemia, CVD, neurovascular disease, and mortality, as well as increased cancer risk (10). Insulin resistance is related to low-grade systemic inflammation, can deteriorate body functions through pancreatic ␤-cell dysfunction and impaired fasting glucose, and eventually increase the risk of T2D (11). There are emerging evidences that insulin resistance is a cause of periodontal disease progression among Korean adult populations

P


(12) as well as other citizens including American (13), French (14), Finnish (15), and British (16). In this study, we investigated the associations between T2D, insulin resistance, and severe periodontitis. We hypothesized that insulin resistance aggravates the severity of periodontitis. Moreover, the associations between severe periodontitis and insulin resistance in non-obese adults with normal body mass index (BMI) or waist circumference (WC) were evaluated using representative national data.

Subjects and Methods Overview of the survey and participants The data from this study were derived from the 2008 –2010 Korea National Health and Nutrition Examination Survey (KNHANES), a nationwide cross-sectional survey conducted by the South Korean Ministry of Health and Welfare. Specially trained investigators examined the representative population of South Koreans with well-designed questionnaires that included physical inspections, health interviews, and nutritional examination. In the present study, 29 235 total participants were initially screened. The 10 367 subjects age less than 30 years were excluded, and the 2049 subjects who did not receive a dental examination were removed from the study. Among the remaining 16 819 patients, 6160 subjects who had periodontitis with a community periodontal index (CPI) of 3 or 4 were selected. After removing 470 subjects who had missing parameters, 5690 total subjects were included. All participants provided written informed consent. This study was approved by the Institutional Review Board of the Korean Center for Disease Control and Prevention (2008-04EXP-01-C, 2009-01CON-03-2C, and 2010-02CON-21-C) and conducted according to the Helsinki Declaration– based Ethical Principles for Medical Research Involving Human Subjects.

Sociodemographic and lifestyle variables Sociodemographic and lifestyle variables of participants were evaluated with a self-administered questionnaire regarding education level, household income, smoking, alcohol intake, physical exercise, place of residence (urban), and occupation. Education level was categorized as either finished high school (ⱖ13 y) or not. Household income was divided into quartiles by number of included family members. The lowest quartile of household income was less than $1,092.40 per month. Smokers were classified as nonsmokers, ex-smokers, or current smokers. Nonsmokers were those who had never smoked or had smoked less than 100 cigarettes during their lifetime, whereas ex-smokers were those who had smoked more than 100 cigarettes in their entire life but were not smoking at the time of the study. Alcohol consumption was categorized as nondrinkers, mild-to-moderate drinkers (1–30 g/d), and heavy drinkers (⬎30 g/d). Physical activity was measured based on the International Physical Activity Questionnaire. Subjects who exercised on a regular basis regardless of indoor or outdoor exercise were defined as regular exercisers as follows; moderate exercisers were those who do moderate exercise including swimming slow, volleyball, badminton,


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table tennis, carrying light stuffs for more than 30 minutes per session or at least five times per week. Severe exercisers were those who exercised actively such as running, climbing, cycling fast, swimming fast, football, basketball, carrying heavy stuffs for more than 20 minutes per session or at least three times per week. The participants were divided into two by the criteria, whether they had occupations or not.

Anthropometric measurements Trained inspectors obtained the anthropometric data. Body weight was recorded using a digital scale to the nearest 0.1 kg with bare feet and light clothing, and height was measured to the nearest 0.1 cm. WC was measured to the nearest 0.1 cm at the narrowest midpoint between the iliac crest and the costal margin, with loose-fitting clothing at the end of a normal expiration. BMI was calculated by dividing body weight (kg) by the square of height (m2). These measurements were performed according to World Health Organization recommendations (17).

Biochemical measurements Trained staff members collected biochemical samples from the participants. A standard mercury sphygmomanometer (Baumanometer, W. A. Baum Co.) was used to measure blood pressure (BP). Systolic and diastolic BP were measured three times at 5-minute intervals, and average values were calculated for the analysis. Blood samples were collected from the antecubital vein of each participant following at least 8 hours of fasting. Samples were stored at a low temperature immediately and transported to the central testing institute (NeoDin Medical Institute). Serum levels of fasting blood glucose, total cholesterol, triglycerides, and high-density (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were measured enzymatically with an automatic chemistry analyzer (Hitachi 7600; Hitachi, Ltd.). Serum insulin was analyzed using INS-IRMA kits (BioSource Europe S.A.) by immunoradiometric assay (IRMA). Serum levels of 25-hydroxyvitamin D3 were measured by the RIA method with a 1470 WIZARD gamma counter (PerkinElmer). White blood cell counts were calculated by laser-flow cytometry using a Sysmex XE-2100D (Sysmex).

Descriptions of glucose tolerance status and MS Data regarding glucose tolerance status were collected from each participant based on self-reported questionnaires. Subjects with fasting blood glucose level less than 100 mg/dL were defined as having normal glucose tolerance, and subjects with 100 –125 mg/dL fasting blood glucose were classified as having impaired fasting glucose. Those with a fasting blood glucose at least 126 mg/dL or those previously diagnosed with T2D were defined as subjects with T2D (5). The scientific statement criteria of the American Heart Association/National Heart, Lung, and Blood Institute were used to define MS in Asians (18). According to the criteria, subjects with three or more of the following five medical conditions were considered to have MS: WC at least 90 cm for men and at least 80 cm for women, BP at least 130/85 mm Hg or use of an antihypertensive drug, fasting blood glucose at least 100 mg/dL or current use of an antidiabetic drug, fasting triglycerides at least 150 mg/dL or use of an antidyslipidemic drug, and HDL-C less than 40 mg/dL in men and less than 50 mg/dL in women or use of an antidyslipidemic drug.


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Definition of metabolic health status Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) is used to measure the quantity of insulin resistance through following formula: fasting insulin (␮U/mL) ⫻ fasting glucose (mg/dL)/405 (19). A HOMA-IR score being in the highest quartile (cut-off values were 2.21 for men and 2.33 for women), or previously diagnosed as having T2D was defined as insulin resistance or metabolically obese, and below these cutoff values were defined as noninsulin resistance or metabolically healthy in this study. The participants were classified as normal if they had BMI less than 25 kg/m2, whereas as obese if they had BMI at least 25 kg/m2. Similarly, subjects were categorized as normal if WC less than 90 cm for men or WC less than 80 cm for women, whereas as abdominal obese if WC at least 90 cm for men or WC at least 80 cm for women. Subjects with a normal weight (BMI ⬍ 25 kg/m2) but below the highest HOMA-IR quartile were called metabolically healthy normal weight (MHNW), whereas an individual with BMI less than 25 kg/m2 but in the highest HOMA-IR quartile was designated as metabolically obese normal weight (MONW). Likewise, participants with WC less than 90 cm for men and less than 80 cm for women, and those who had a HOMA-IR below the highest quartile were named as MHNW, whereas those with WC less than 90 cm for men and less than 80 cm for women, and in the highest HOMA-IR quartile were designated as MONW.

Oral health behaviors and periodontal treatment needs Subjects reported the times of day when they brushed their teeth from the choices before bedtime, after snacks, and before or after breakfast, lunch, and dinner. This study also determined whether secondary oral products such as dental gargle, dental floss, interdental brushes, and electric toothbrushes were used. The frequency of daily toothbrushing was defined as total number of toothbrushings per day. The number of dental visits within 1 year and self-reported oral health status were also determined. Periodontal treatment needs were assessed using the Community Periodontal Index (CPI), which the World Health Organization/Federation Dentaire Internationale has defined as an epidemiological screening procedure for rough depiction of periodontal status and treatment needs by trained dental practitioners (20). All teeth of each subject were divided into sextants. A specially designed periodontal probe (PWHO, Osung MND) with a ball end 0.5 mm in diameter was used. Ten specific index teeth (17, 16, 11, 26, 27, 36, 37, 31, 46, and 47) were examined to evaluate each sextant’s score. A sextant was only scanned if two or more teeth were present. If index teeth were absent from a sextant, all of the remaining teeth were examined to produce the score, and the highest score was recorded as the score for the sextant. The probe was applied with light probing force (20 –25 g) with a walking-around motion to the sulcus/periodontal pockets in each sextant. The CPI score represented periodontitis status as follows: 0, normal; 1, gingival bleeding; 2, calculus; 3, a shallow pocket with depth of 3.5–5.5 mm or moderate periodontitis; and 4, a deep pocket depth at least 5.5 mm or severe periodontitis (11).

Statistical analyses The data are presented as mean ⫾ SE for continuous variables and percentage (SE) for categorical variables. Student t tests for continuous variables and the Rao-Scott ␹2 tests for categorical


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variables were used to compare the difference between moderate periodontitis (CPI 3) and severe periodontitis (CPI 4) according to metabolic health status, including normal glucose tolerance, impaired fasting glucose, and T2D. The ORs for severe periodontitis (CPI 4) were calculated according to diabetic status (normal glucose tolerance, impaired fasting glucose, or T2D). Model 1 was adjusted for age and sex. Model 2 was adjusted for the components of Model 1 and BMI, smoking, drinking, and physical activity. Model 3 was adjusted for the components of model 2 plus MS, place of residence, occupation, frequency of daily toothbrushing, use of secondary oral products, number of annual dental visits, and dental prosthetic status. In addition, we explored whether the association between metabolic health status and severe periodontitis would differ by general and abdominal obesity, defined by BMI and waist circumference, respectively, with adjustments for age, sex, smoking, drinking, and physical activity. The interaction between general obesity and insulin resistance, abdominal obesity, and insulin resistance was evaluated, respectively. The SAS statistical software package version 9.3 (SAS Institute) was used for the analysis. All the data were considered to be statistically significant when the P ⬍ .05.

Results Table 1 displays the characteristics of the study participants. Male participants had a higher prevalence of severe periodontitis (CPI 4) (P ⬍ .001). Elderly subjects, current smokers, and heavy alcohol drinkers were more likely to have severe periodontitis (P values of .03, ⬍.001, and .017, respectively). However, people who lived in urban areas and employed subjects were less likely to have severe periodontitis (P values of .027 and .015, respectively). Patients who were diagnosed with T2D were more likely to have severe periodontitis compared with the groups with normal glucose tolerance or impaired fasting glucose (P ⬍ .001). Subjects with severe periodontitis showed significantly higher prevalence of abdominal obesity, high systolic BP, high serum glucose, high serum triglycerides, and high white blood cell count (P values of .012, .029, ⬍.001, .023, and ⬍.001, respectively). Participants with severe periodontitis presented significantly higher values of insulin resistance (P ⫽ .003). Figure 1 shows the overall numbers of male and female participants with severe periodontitis. The participants overall and the male subjects indicated the highest prevalence of severe periodontitis in their 50s (all P values ⬍.001). Women also showed the highest prevalence of severe periodontitis in their 50s (P ⫽ .004); however, the pattern of prevalence did not decrease as rapidly compared with the overall group or to male subjects. We also found that patients with T2D had a significantly higher proportion of severe periodontitis than did patients with impaired fasting glucose or normal glucose tolerance


(P for trend ⱕ.001) (Supplemental Figure 1). The proportion of severe periodontitis among participants with wellcontrolled T2D was lower, although it was not statistically significant (P ⫽ .568) (Supplemental Figure 2). Table 2 shows that the ORs of prevalence of severe periodontitis (CPI 4) were significantly different among groups after adjusting for covariates (P for trend ⫽ .003). The prevalence of severe periodontitis was OR ⫽ 1.5; 95% CI, 1.11–2.02 in the T2D group and OR ⫽ 1.32; 95% CI, 1.06 –1.64 in the impaired fasting glucose group after adjusting the covariates, compared with the healthy group with normal glucose tolerance. Figure 2 displays the incidence of severe periodontitis (CPI 4) according to general (BMI) or abdominal (WC) obesity, and insulin resistance (highest-quartile HOMAIR). With regard to general obesity, MONW subjects showed a higher odds of severe periodontitis than did MHNW subjects, although the difference was not statistically significant (P ⫽ 0.154). However, with respect to abdominal obesity, the odds of severe periodontitis was significantly higher in MONW individuals than in MHNW individuals (OR, 1.47; 95% CI, 1.16 –1.87). The interaction between abdominal obesity and insulin resistance was statistically significant (P ⫽ .012), indicating that the association between insulin resistance and severe periodontitis differed by the presence of abdominal obesity.

Discussion In the present study, we found that participants with T2D had a higher prevalence of severe periodontitis. The prevalence of subjects with severe periodontitis increased significantly with increasing insulin resistance in nondiabetic individuals. When we further investigated the association between metabolic health status and periodontitis stratified by general or abdominal obesity, metabolically unhealthy individuals were more likely to have severe periodontitis than metabolically healthy individuals among normal-weight population defined by WC. In this study, the incidence of periodontal disease increased up to age 59 years and decreased thereafter. This pattern was similar in both men and women, although women showed a slower decreasing slope. The results were similar in both sexes over the age of 60 years, according to the South Korean nationwide survey in 2014. The decreasing pattern of severe periodontitis was slower in elderly women than in elderly men (2). A cross-sectional study in Italy also reported a similar result that the incidence of periodontitis increased with age but significantly


doi: 10.1210/jc.2016-2061

Table 1. and 4)


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General Characteristics and Differences between Subjects with Moderate and Severe Periodontitis (CPI 3 Periodontitis

Characteristic

Moderate Periodontitis (CPI 3)

Severe Periodontitis (CPI 4)

Unweighted n Age, y Sex, male BMI, kg/m2 WC, cm White blood cells, ⫻109/Lb,c HOMA-IRb,c Glucose, mg/dL Insulin, ␮IU/mLc Serum 25-hydroxyvitamin D, ng/mL Total cholesterol, mg/dL LDL cholesterol, mg/dL HDL cholesterol, mg/dL Triglycerides, mg/dLc Smoking status Non-smoker Ex-smoker Current smoker Drinking status Non-drinker Mild-to-moderate drinker Heavy drinker Exercise, yes Income, the lowest quartile Education, high-school graduate or higher Residence, urban Occupation, yes Systolic BP, mm Hg Diastolic BP, mm Hg Hypertension Normotension Pre-hypertension Hypertension Diabetes Normal glucose tolerance Impaired fasting glucose Diabetes Frequency of tooth brushing/d ⱕ1 2 ⱖ3 Use of secondary oral products, yes Dental checkup within 1 y, yes

4488 52.9 ⫾ 0.3 57.4 (0.8) 24.2 ⫾ 0.1 83.7 ⫾ 0.2 6.12 (6.06 – 6.18) 2.18 (2.14 –2.22) 101.3 ⫾ 0.5 8.9 (8.7–9) 19.2 ⫾ 0.2 192.5 ⫾ 0.6 117.4 ⫾ 0.6 46.5 ⫾ 0.2 125.4 (122.8 –128.1)

1202 54 ⫾ 0.5 66.7 (1.3) 24.3 ⫾ 0.1 84.6 ⫾ 0.4 6.43 (6.31– 6.54) 2.33 (2.24 –2.43) 107.1 ⫾ 1.4 9.1 (8.8 –9.4) 19.7 ⫾ 0.3 191.3 ⫾ 1.1 115.8 ⫾ 1 45.8 ⫾ 0.4 132.5 (126.9 –138.2)

46.8 (0.9) 22.1 (0.7) 31.1 (0.8)

38.8 (1.4) 26.1 (1.5) 35.1 (1.7)

27.1 (0.8) 61.4 (1) 11.6 (0.6) 26.5 (0.9) 20.1 (0.9) 54.8 (1.1) 77.4 (1.9) 66.2 (0.8) 122.7 ⫾ 0.4 79.6 ⫾ 0.2

24.6 (1.5) 60.2 (1.8) 15.2 (1.3) 27.5 (1.6) 19.7 (1.5) 52.6 (2.3) 71.5 (3.5) 70.4 (1.7) 124.4 ⫾ 0.7 80.3 ⫾ 0.4

33.5 (1) 26.7 (0.8) 39.8 (1)

29.1 (1.7) 28.6 (1.5) 42.3 (1.7)

62.5 (0.9) 24 (0.8) 13.5 (0.7)

54.8 (1.8) 26.9 (1.5) 18.3 (1.4)

15.2 (0.7) 47.7 (0.9) 37.1 (0.9) 32.3 (1.1) 25.8 (1)

18.5 (1.8) 45.9 (1.7) 35.6 (2) 34 (2) 24.4 (1.6)

P Valuea .03 ⬍.0001 .1777 .0118 ⬍.0001 .0028 .0001 .1794 .1172 .3379 .1421 .0772 .0233 ⬍.0001

.0168

.5657 .8336 .3456 .0266 .0149 .0285 .0794 .0545

.0001

.113

.4276 .4052

When at least one of the sextants was CPI 4, the grade was designated as CPI 4. The data are presented as mean ⫾ SE or percentage (SE). a

P values were obtained by independent t test for continuous variables and Rao-Scott ␹2 test for categorical variables.

b

Logarithmic transformation was used to analyze variables with skewed distributions.

c

Geometric mean (95% CI).

decreased in groups older than 50 years (21). Similarly, a nationwide cross-sectional study on the prevalence of periodontitis revealed that severe periodontitis peaked in the sixth decade of life but decreased thereafter (22). The reason for decreased prevalence of periodontitis in people older than 50 years could be explained in part by increased tooth loss at this age (21), owing to the development of

periodontal attachment loss and subsequent tooth loss with aging. Obesity is a well-known cause of both T2D and periodontal disease. Adipocyte-releasing adipokines cause chronic low-grade inflammation through inflammatory cytokines (23). Increased reactive oxygen species, C-reactive protein, and mitochondrial dysfunction result in pan-


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also reported increased visceral fat rate and total fat quantity in MONW subjects compared with metabolically healthy subjects (29). In addition, metabolically healthy obese individuals who showed lower risk of diabetes and CVD than risky obese subjects were distinguished by relatively little visceral fat and early-onset obesity compared with risky obese individuals (30). This study clearly showed that individuals with insulin resistance were more likely to have severe periodontitis, even among participants with normal WC. Obesity might not be directly linked to severe periodonFigure 1. Prevalence trends of severe periodontitis (CPI 4) in men and women according to age. titis, as other studies have shown, and the role of insulin resistance creatic ␤-cell dysfunction, insulin resistance, and , T2D might be a clue. A cross-sectional study in a middle-age (6). Meanwhile, periodontitis provokes hyperlipidemia, French population have supported the association beabnormal fat metabolism, and subsequent inflammatory tween insulin resistance and periodontal disease (14). changes in adipose tissue, which can increase serum proThe severity of periodontal attachment loss and tooth inflammatory cytokines and adipokines, worsening periloss significantly increased in a group of patients in the odontal inflammation (24). highest insulin-resistance quartile (13). Similarly, anIn contrast with the aforementioned close association other cross-sectional study reported that subjects with among periodontitis, obesity, and diabetes, our results severe periodontitis had a higher OR of insulin resisshowed a higher OR of severe periodontitis, even without tance based on the presence of clinical attachment loss general or abdominal obesity. This unexpected result could be explained by the notion of MONW phenotpye or pocket depth in the affected interproximal areas (14). (25). Some participants with normal BMI but unexpected Therefore, insulin resistance would be the moderatmetabolic disturbance were designated as MONW indi- ing factor among severe periodontitis, diabetes, and viduals. They showed increased insulin resistance, adipos- obesity (13). Some evidence supports a bidirectional interaction beity, and higher risks of T2D, CVD, and mortality (26). tween periodontitis and diabetes (14, 31–33). One clinical Individuals with MONW had high triglycerides, high serum insulin, high diastolic and systolic BP, and low trial on the effects of nonsurgical periodontal treatment in HDL-C at relatively young ages (27). A Japanese study has obese and healthy patients showed a decrease in levels of previously demonstrated that elevated visceral fat and se- proinflammatory cytokines, such as IL-6, TNF-␣, and rum triglycerides were responsible for insulin resistance in HOMA-IR score in subjects with obesity (31). Several MONW subjects (28). Another study on young women studies have also demonstrated that periodontal treatment Table 2. ORs and 95% CIs of Severe Periodontitis (CPI 4) According to Diabetic Status (Normal Glucose Tolerance, Impaired Fasting Glucose, or T2D)

Normal glucose tolerance Impaired fasting glucose T2D P value P for trend

Model 1

Model 2

Model 3

1 1.207 (1.012, 1.439) 1.432 (1.13, 1.815) .004 .001

1 1.173 (0.98, 1.404) 1.372 (1.074, 1.752) .021 .006

1 1.311 (1.053, 1.633) 1.511 (1.12, 2.039) .003 ⬍.0001

Model 1: Adjusted for age and sex. Model 2: Model 1 plus adjustments for BMI, smoking, drinking, and physical activity. Model 3: Model 2 plus MS, place of residence, occupation, frequency of daily toothbrushing, use of secondary oral products, number of annual dental visits, and dental prosthetic status.


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abetes, chronic periodontitis, and insulin resistance could not be clearly established because this was a crosssectional study. Second, CPI does not provide an exact diagnosis of periodontal status (37). Full-mouth periodontal examinations to measure probing depth and clinical attachment levels are more accurate for periodontal examinations than is CPI (1). Several studies have divided the severity of periodontitis based on prevalence values from the Centers for Disease Control and Prevention/ American Academy of Periodontology (38), which emphasize measurFigure 2. The ORs of severe periodontitis (CPI 4) according to obesity (BMI and waist ing both pocket depth and clinical circumference) and insulin resistance, after adjusting for age and sex. Error bars represent 95% attachment loss for accuracy of preCIs. General obesity was defined as BMI ⱖ 25 kg/m2, and abdominal obesity was defined as vious and current pathologic status. WC ⱖ 90 cm in men and ⱖ 80 cm in women. Insulin resistance was defined as the highest Third, insulin resistance was meaquartile of the HOMA-IR. sured using HOMA-IR instead of other methods such as the quantitadiminishes glycated hemoglobin (HbA1c level) (33). Pretive insulin sensitivity check index or hyperinsulinemic vious results suggested an association between periodoneuglycemic clamp studies (39). The latter is regarded as a titis and insulin resistance, with chronic periodontal inmore accurate method of measuring insulin resistance flammation and secretion of cytokines contributing to (26, 40). insulin resistance and eventually, T2D (32). In conclusion, nonabdominal obese subjects with inLow physical activity was reported to be linked to sulin resistance were more likely to have severe perioMONW, T2D, and CVD (34). Physical activity and endontitis. Insulin resistance without abdominal obesity ergy expenditures were significantly lower in subjects with can be considered an independent risk indicator of periMONW (29). This was associated with body fat composition, including total and percentage fat mass. Therefore, odontal disease. Dental practitioners and physicians body fat composition was carefully marked as an impor- should be aware that metabolically obese individuals tant risk factor in MONW individuals (25). High visceral with normal weight need lifestyle modifications to refat area is the characteristics in MONW individuals, and duce their risk of T2D and chronic periodontitis. Physmight be associated with insulin resistance (28) as well as ical activity and toothbrushing instruction might be reincreased risks of diabetes and CVD (35), and all causes of quired to reduce the aggravating interaction between mortality (36). Intra-abdominal fat deposition could in- these diseases. Additional research is required to specify crease serum triglyceride level and consequently increase the role of insulin resistance in the progression of severe nonphysiologic fat deposits, including those in the liver periodontitis. Randomized clinical trials or cohorts and muscles (26). Elevated liver fat is associated with in- with longitudinal large-sample data are required to clarsulin resistance, which was supported by a study present- ify the exact causal relationship among T2D, unhealthy ing higher liver fat accumulation in nonobese men with metabolic status, and severe periodontitis. high serum insulin and triglycerides and lower serum HDL-C. There are several advantages of this study. First, this Acknowledgments study was performed with a representative sample of South Korean adults using a nationwide survey. Second, to We thank the Korean Center for Disease Control and Prevention, which performed the KNHANES. We also thank the subjects the best of our knowledge, this study is the first report to who participated in the KNHANES. demonstrate a significant relationship between insulin resistance and severe periodontitis in individuals with norAddress all correspondence and requests for reprints to: mal weight or normal WC. However, this study has some Jun-Beom Park, DDS, MSD, PhD, Department of Periodontics, limitations. First, a definite causal relationship among di- Seoul St. Mary’s Hospital, College of Medicine, The Catholic


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University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. E-mail: [email protected]. JaeJun Ryu, DDS, MSD, PhD, Department of Prosthodontics, Korea University Anam Hospital, Seoul, Republic of Korea, 73, Inchon-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea. E-mail: [email protected]. We declare that there is no official support or endorsement by the National Institues of Health, National Institute of Environmental Health to this study. Author contributions: I.-S.S. started, participated in the organization of, and coordinated the study and wrote the article. K.H. contributed to the execution of the study, organized the database, accomplished the statistical analyses, contributed to the drafting of the article, and is the statistician for the study. Y.-M.P, S.J., and S.H.J. participated in study discussions. J.-J.R. contributed to the design of the study, researched data, and wrote the article. J.-B.P. participated in the design of the study, researched data, and wrote the article. All the authors read and agreed the final version of the manuscript. J.-B.P. is the guarantor of the present work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the precision of the data analysis. The authors received no funding related to the present study. Disclosure Summary: The authors have nothing to disclose.


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