Association between the indicators of insulin resistance and periodontitis: A study using data from the National Health and Nutrition Examination Survey 2009–2014

doi:10.21203/rs.3.rs-5155026/v1

Background

The prevalence of obesity-associated insulin resistance (IR) is increasing along with greater obesity rates. To identify the best replacement index of IR, this study aimed to investigate the possible association between IR, which was assessed using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), and the triglyceride–glucose (TyG) index and its derived indexes and periodontitis.

Methods

The association between the indicators of IR and periodontitis was assessed via multivariate-adjusted logistic regression analyses using data from the National Health and Nutrition Examination Survey (NHANES) 2009–2014. In addition, subgroup analyses and receiver operating characteristic curve analyses were conducted to explore possible influencing factors.

Results

Our study encompassed 1,588 participants, and 41.0% were diagnosed with periodontitis. Based on themultivariate logistic regression analysis, a higher TyG-waist-to-height ratio (WHtR)(odds ratio [OR] = 1.00, 95% confidence interval [CI]: 1.08–1.67, P = 0.0075) and HOMA-IR score (OR = 1.00, 95% CI: 1.00–1.00, P = 0.0130) were associated with an increased risk of periodontitis. Conversely, the TyG index, TyG-adjusted for body mass index, and TyG-adjusted for waist circumference (WC) were not associated with periodontitis. According to further subgroup analyses and interaction result analyses, sex affected the association between the TyG index, TyG-WC, and TyG-WHtR and periodontitis (P < 0.05 for interaction). Moreover, the influence of age regulated the association between periodontitis and both TyG and HOMA-IR score. In terms of diagnostic accuracy, the area under the receiver operating characteristic curve analysis revealed that HOMA-IR score and TyG-WHtR slightly outperformed the TyG index, TyG-body mass index, and TyG-WC. Thus, they can be robust markers for assessing IR-related periodontitis risk.

Conclusion

A consistent and positive association was found between HOMA-IR score and TyG-WHtR and the odds of periodontitis prevalence. Hence, HOMA-IR score and TyG-WHtR can be valid predictors for evaluating the association between periodontitis development and IR.

Health sciences/Biomarkers

Health sciences/Medical research

TyG-related indicators

Periodontitis

NHANES

Relationship

A cross-sectional study

Periodontal diseases are among the most prevalent chronic inflammatory conditions affecting the oral cavity worldwide (Eke et al., 2020)^,(Richards, 2014). According to the Global Burden of Disease 2015 study, the prevalence rate of severe periodontitis is approximately 7.4%. The prevalence of milder types of periodontitis can be as high as 50% (Sanz, Herrera, et al., 2020). Periodontitis can lead to tooth loss, pronunciation disorders, and aesthetic issues (Meusel et al., 2015) and can significantly affect a person’s quality of life (Janakiram & Dye, 2020). Therefore, early periodontitis diagnosis and treatment are essential.

As far as the current research is concerned, patients and physicians only notice periodontitis until after symptoms such as loose teeth and tooth loss have occurred. Further, there is still a lack of biomarkers for the early diagnosis of periodontitis, which is best predicted using simpler methods. Blood tests and body mass index measurement are part of routine medical examinations. Diabetes has been established as a risk factor for the development of periodontitis (Mealey & Oates, 2006). Insulin resistance (IR), a precursor to diabetes, contributes to periodontitis by increasing pro-inflammatory cytokines such as interleukin-6 and tumor necrosis factor-alpha (Song et al., 2016; Zeze et al., 2023). IR, which is characterized by decreased sensitivity and responsiveness to insulin, is a hallmark of type 2 diabetes, and it even precedes disease onset (Defronzo, 2009)(Batista et al., 2021). In addition, there is strong evidence linking severe periodontitis to cardiovascular disease (Sanz, Marco Del Castillo, et al., 2020). The hyperinsulinemic–euglycemic clamp is the gold standard for evaluating IR (Tam et al., 2012). However, it is complex and time-consuming. In recent years, a series of novel indicators such as the TyG index and HOMA-IR score have been proposed to be simpler, more cost-effective methods for assessing IR (Muniyappa et al., 2008). Several studies have shown that the accuracy of the TyG index in assessing IR is comparable to that of the hyperinsulinemic–euglycemic clamp (Guerrero-Romero et al., 2010; Li et al., 2021).

Obesity is prevalent worldwide and is strongly associated with various health risks. Previous studies have reported that the combined use of TyG index and obesity-related measures can improve IR detection (Dang et al., 2024; Er et al., 2016). In addition, several studies have shown that combined TyG index and obesity indices for assessing coronary artery calcification is superior to the TyG index alone (Malek et al., 2021). By integrating fasting triglyceride levels and glucose concentrations, the TyG index can be a surrogate marker of IR. Moreover, to offer a more comprehensive assessment of an individual’s metabolic status, it can be used along with obesity indicators such as body mass index and waist circumference (WC).

To facilitate early periodontitis detection by enhancing the management and control of IR indicators, a cross-sectional study was conducted using data from NHANES 2009–2014. The current study aimed to identify optimal markers for assessing the close association between IR and periodontitis among adult populations in the United States.

The cross-sectional data were obtained from NHANES, which is a survey conducted by the National Center for Health Statistics to evaluate nutrition and health in the United States. All details regarding the study designs and data of NHANES are publicly available at www.cdc.gov/nchs/nhanes/.

Participants

As the Figure 1 showed, this study utilized data from NHANES 2009–2014, with 30,468 participants completing the demographic survey, laboratory examination, and health condition questionnaire. The exclusion criteria were as follows:

Individuals with missing data on periodontitis (n = 19,804)
Individuals with missing data on fasting triglyceride (n = 4,951), fasting glucose (n = 4,045), and insulin (n = 26) levels
Individuals with missing data on weight (n = 3) and WC (n = 40)
Individuals with missing data on diabetes (n = 4), hypertension (n = 16), fasting glucose levels (n =10), and alcohol intake (n = 2)
Pregnant women (n = 9)

Finally, 1,588 participants were enrolled in this research.

Definitions of the TyG index, TyG-WC, TyG-WHtR, TyG-BMI, and HOMA-IR score

The indices used in the current study were defined as follows (Dang et al., 2024)^,(Khamseh et al., 2021):

WHtR = WC/height
TyG index = Ln (fasting triglyceride level [mg/dL] × fasting glucose level [mg/dL] / 2).
TyG-BMI = TyG × BMI
TyG-WHtR = TyG × WHtR
TyG-WC = TyG × WC
HOMA-IR = fasting insulin level (μU/mL) x fasting glucose level (mmol/L) / 22.5

Definitions of Periodontal Disease

Periodontitis data were obtained from Oral Health-Periodontal in Examination Data of NHANES 2009–2014. To define periodontitis, the researchers adopted the Disease Control and Prevention and the American Academy of Periodontology classification (Caton et al., 2018; Eke et al., 2012). Based on attachment loss (AL) and pocket depth (PD) measurements at four interproximal sites per tooth, the conditions were defined as follows: mild periodontitis, ≥2 sites with AL ≥ 3 mm and ≥2 sites (nonadjacent) with PD ≥ 4 mm or 1 site with PD ≥ 5 mm; moderate, ≥ 2 sites (nonadjacent) with AL ≥ 4 mm or ≥2 sites (nonadjacent) with PD ≥ 5 mm; and severe, ≥2 sites (nonadjacent) with AL ≥ 6 mm and ≥1 site with PD ≥ 5 mm. In this study, the periodontitis category encompasses mild, moderate, and severe cases.

Covariates

Covariates including age, sex, race/ethnicity, alcohol use, diabetes, and hypertension were selected based on the relevant literature (Borgnakke et al., 2018; Gay et al., 2018). Alcohol use was defined as the consumption of at least 12 alcoholic drinks per year. Diabetes and hypertension were based on self-reported diagnosis by a physician.

Statistical analysis

EmpowerStats version 2.0 (http://www.empowerstats.net/analysis) was used to analyze data from the NHANES 2009–2014 database. Periodontitis was classified as a dichotomous variable, with or without periodontitis. TyG indicators were expressed as a continuous variable divided into three categories. Continuous variables among covariates were presented as mean ± standard deviation and categorical variables as percentages. The chi-square test or the Student’s t-test was used to evaluate the P value of the distribution. Multivariate linear regression models were used. One-way and multifactorial logistic regression analyses were performed to assess the odds ratio (OR) and 95% confidence intervals (95% CIs) for the association between HOMA-IR score, TyG index, TyG-WHtR, TyG-WC, and TyG-BMI and periodontitis. Model I was not adjusted for any covariates. Model II was adjusted for age, sex, and race/ethnicity. Model III was adjusted for all factors in Model II, alcohol status, diabetes, and hypertension. Finally, the receiver operating characteristic (ROC) curves were obtained to assess the diagnostic accuracy of the association between the indicators of IR and the risk of developing periodontitis.

3.1 Baseline Characteristics of the Participants

The current study included 1,588 participants. Approximately 49.62% were men, and 50.38% were women. Further, 56.30% presented with periodontitis, and the average age of the patients was 51.9 years. The participants were categorized based on periodontitis status. Notably, patients with periodontitis had higher TyG indexes and fasting glucose levels and a higher likelihood of cigarette smoking than those without periodontitis (Table 1).

Table 1. Baseline characteristics of the study population according to periodontitis status

Variables	Patients with NPD (n = 936)	Patients with PD (n = 652)	Total	P value
Age (years, mean ± sd)	49.83 ± 13.80	55.02 ± 13.78	51.96 ± 14.02	<0.001
Sex, n (%)				<0.001
Male	414 (44.23%)	374 (57.36%)	788 (49.62%)
Female	522 (55.77%)	278 (42.64%)	800 (50.38%)
Weight (kg, mean ± sd)	82.59 ± 21.57	82.93 ± 22.23	82.73 ± 21.84	0.903
Height (cm, mean ± sd)	167.91 ± 9.99	167.50 ± 10.01	167.74 ± 9.99	0.468
BMI (kg/m², mean ± sd）	29.20 ± 7.00	29.47 ± 7.15	29.31 ± 7.06	0.456
RACE, n (%)				<0.001
Mexican American	96 (10.26%)	112 (17.18%)	208 (13.10%)
Other Hispanics	73 (7.80%)	62 (9.51%)	135 (8.50%)
NonHispanic White	494 (52.78%)	226 (34.66%)	720 (45.34%)
NonHispanic Black	128 (13.68%)	169 (25.92%)	297 (18.70%)
Other race including multiracial	145 (15.49%)	83 (12.73%)	228 (14.36%)
Diabetes, n (%)				<0.001
Yes	74 (7.91%)	107 (16.41%)	181 (11.40%)
No	832 (88.89%)	519 (79.60%)	1,351 (85.08%)
Borderline	30 (3.21%)	26 (3.99%)	56 (3.53%)
Alcohol use, n (%)				0.968
Yes	660 (73.66%)	450 (73.65%)	1,110 (73.66%)
No	234 (26.12%)	160 (26.19%)	394 (26.14%)
Hypertension, n (%)				0.001
Yes	326 (34.83%)	280 (42.94%)	606 (38.16%)
No	610 (65.17%)	372 (57.06%)	982 (61.84%)
Smoking status, n (%)				<0.001
Current	96 (27.83%)	155 (43.79%)	251 (35.91%)
Sometimes	18 (5.22%)	27 (7.63%)	45 (6.44%)
Never	231 (66.96%)	172 (48.59%)	403 (57.65%)
TyG-BMI, mean ± sd	250.85 ± 67.26	256.07 ± 71.07	252.99 ± 68.88	0.137
TyG-WC, mean ± sd	854.20 ± 170.98	876.49 ± 181.58	863.35 ± 175.70	0.013
TyG-WHtR, mean ± SD	5.09 ± 1.00	5.24 ± 1.09	5.15 ± 1.04	0.005
Where, mean ± sd	0.59 ± 0.10	0.60 ± 0.10	0.60 ± 0.10	0.031
Ty index, mean ± SD	8.56 ± 0.68	8.64 ± 0.74	8.59 ± 0.71	0.016
WC, mean ± SD	99.45 ± 16.03	100.95 ± 16.24	100.07 ± 16.13	0.069
mean ± sd	5.78 ± 1.44	6.38 ± 2.35	6.03 ± 1.89	<0.001

3.2. Associations between the Indicators of Insulin Resistance and Periodontitis

Our study assessed the association between the five indicators of IR and the risk of developing periodontitis (Table 2). Results revealed a significant association between HOMA-IR score and TyG-WHtR and periodontitis development. In particular, higher HOMA-IR scores and TyG-WHtR were associated with the odds of periodontitis prevalence. This association persisted across the crude (model I), minimally adjusted (model II), and fully adjusted models. In the fully adjusted models (III), TyG-WHtR exhibited the strongest association with periodontitis (OR = 1.35, 95% CI: 1.08–1.67, P = 0.0075), indicating a 35% increased risk per unit increase. Further, HOMA-IR score (OR = 1.00, 95% CI: 1.00–1.00, P = 0.0130) was positively correlated with the risk of developing periodontitis. Meanwhile, the association between TyG (OR = 1.09, 95% CI: 0.92–1.30, P = 0.3330), TyG-BMI (OR = 1.00, 95% CI: 1.00–1.01, P = 0.3949), and TyG-WC (OR = 1.00, 95% CI: 1.00–1.00, P = 0.4281) and periodontitis was not statistically significant.

Table 2. Association between the Indicators of Insulin Resistance and Periodontitis

Exposure	Model 1 β (95% CI), P value	Model 2 β (95% CI), P value	Model 3 β (95% CI), P value
HOMA-IR score	1.00 (1.00–1.00), 0.0001	1.00 (1.00–1.00), 0.0004	1.00 (1.00–1.00), 0.0130
TyG index	1.19 (1.03–1.37), 0.0162	1.18 (1.01–1.38), 0.0328	1.09 (0.92–1.30), 0.3330
TyG-WHtR	1.15 (1.04–1.26), 0.0047	1.16 (1.04–1.29), 0.0057	1.35 (1.08–1.67), 0.0075
TyG-BMI	1.00 (1.00–1.00), 0.1376	1.00 (1.00–1.00), 0.0635	1.00 (1.00–1.01), 0.3949
TyG-WC	1.00 (1.00–1.00), 0.0131	1.00 (1.00–1.00), 0.0589	1.00 (1.00–1.00), 0.4281

Model 1: no covariates were adjusted

Model 2: adjusted for sex, age, and race

Model 3: adjusted for sex, age, race, hypertension, diabetes, and alcohol use

3.3 Diagnostic Value of the Indicators of Insulin Resistance in Periodontitis

The ROC curves were used to assess the diagnostic utility of several IR indicators in relation to periodontitis (Figure 2). Results showed that the area under the curves (AUCs) for HOMA-IR score and TyG-WHtR were 0.551 and 0.539, respectively. Hence, they slightly surpassed the AUCs of TyG (AUC = 0.528) and TyG indexes combined with different anthropometric measures (TyG-WC, AUC = 0.532; TyG-BMI, AUC = 0.517).

3.4 Subgroup Analysis

To assess the consistency of the association between periodontitis and the various indicators of IR in the overall population and to identify potentially different population characteristics, subgroup analyses and interaction tests stratified by age, sex, drinking status, diabetes status, and hypertension status were performed. As shown in Table 3, sex affected the association between periodontitis and TyG, TyG-WC, and TyG-WHtR (p values <0.05 for the interactions). Age emerged as another important factor that regulates the associations between periodontitis and both TyG and HOMA-IR score. In contrast, the influence of alcohol consumption, diabetes status, and hypertension status on these associations was not statistically significant.

Table 3. Subgroup analysis of the association between periodontitis and TyG-related indices

	TyG			TyG-WC			TyG-BMI
Subgroup	OR (95% Cl)	P value	P interaction	OR (95% Cl)	P value	P interaction	OR (95% Cl)	P value	P interaction
Sex			0.0075			0.0130			0.0788
Male	0.81 (0.65–1.01)	0.0557		1.00 (1.00–1.00)	0.1016		1.00 (1.00–1.00)	0.4742
Female	1.26 (0.99–1.61)	0.0626		1.00 (1.00–1.00)	0.0618		1.00 (1.00–1.00)	0.0581
Age (years)			0.0331			0.2303			0.5023
≤60	1.10 (0.92–1.33)	0.2903		1.00(1.00–1.00)	0.4926		1.00(1.00–1.00)	0.3626
60	0.73 (0.53–1.02)	0.0666		1.00(1.00–1.00)	0.3293		1.00(1.00–1.00)	0.7970
Drinking			0.0697			0.6320			0.4816
Yes	0.92 (0.76–1.11)	0.3807		1.00 (1.00–1.00)	0.9056		1.00 (1.00–1.00)	0.4926
No	1.29 (0.94–1.78)	0.1151		1.00(1.00–1.00)	0.5250		1.00 (1.00–1.01)	0.2062
Diabetes			0.2543			0.0962			0.0996
Yes	1.27 (0.85–1.90)	0.2514		1.00(1.00–1.00)	0.1042		1.00 (1.00–1.01)	0.0448
No	0.96 (0.80–1.16)	0.6620		1.00(1.00–1.00)	0.8882		1.00 (1.00–1.01)	0.5837
Borderline	0.67 (0.32–1.38)	0.2761		1.00 (0.99–1.00)	0.1758		1.00 (0.99–1.00)	0.3074
Hypertension			0.8461			0.6767			0.5384
Yes	0.99 (0.77–1.28)	0.9651		1.00(1.00–1.00)	0.4941		1.00 (1.00–1.00)	0.1832
No	1.03 (0.83, 1.27)	0.8008		1.00(1.00,1.00)	0.8788		1.00 (1.00, 1.00)	0.5692

	HOMA-IR			TyG-WHtR
Subgroup	OR (95% Cl)	P value	P interaction	OR (95% Cl)	P value	P interaction
Sex			0.4181			0.0393
Male	1.00 (1.00–1.00)	0.1428		0.94 (0.79–1.12)	0.4847
Female	1.00 (1.00–1.00)	0.0341		1.19 (1.03–1.39)	0.0202
Age (years)			0.0082			0.2289
≤60	1.00 (1.00–1.00)	0.0016		1.12 (0.99–1.27)	0.0747
>60	1.00 (1.00–1.00)	0.8799		0.96 (0.77–1.20)	0.7245
Drinking			0.9976			0.7504
Yes	1.00 (1.00–1.00)	0.0397		1.08 (0.95–1.23)	0.2503
No	1.00 (1.00–1.00)	0.1404		1.12 (0.91–1.39)	0.2779
Diabetes			0.9882			0.1064
Yes	1.00 (1.00–1.00)	0.1140		1.30 (0.96–1.75)	0.0063
No	1.00 (1.00–1.00)	0.1399		1.07 (0.95–1.22)	0.0002
Borderline	1.00 (1.00–1.01)	0.5932		0.65 (0.36–1.19)	0.9368
Hypertension			0.9334			0.9502
Yes	1.00 (1.00–1.00)	0.0591		1.10 (0.92–1.30)	0.3013
No	1.00 (1.00–1.00)	0.1541		1.10 (0.95–1.28)	0.1854

This cross-sectional study investigated the predictive value of TyG, TyG-WHtR, TyG-BMI, TyG-WC, and HOMA-IR score as alternative IR indices for periodontitis in the general population. According to the results of our study (n = 1,588), HOMA-IR score and TyG-WHtR were positively associated with the risk of periodontitis, and TyG-WHtR exhibited the strongest association (OR = 1.35, 95% CI: 1.08–1.67, P = 0.0075), indicating a 35% increased risk per unit increase. HOMA-IR score (OR = 1.00, 95% CI: 1.00–1.00, P = 0.0130) was positively associated with the risk of developing periodontitis. Conversely, there was no statistically significant association between TyG (OR = 1.09, 95% CI: 0.92–1.30, P = 0.3330), TyG-WC (OR = 1.00, 95% CI: 1.00–1.00, P = 0.4281), and TyG-BMI (OR = 1.00, 95% CI: 1.00–1.01, P = 0.3949) and periodontitis. The AUC of HOMA-IR (0.551) and TyG-WHtR (0.539) was slightly higher than that of TyG-WC (0.532), TyG (0.528), and TyG-BMI (0.517). As the AUCs for HOMA-IR and TyG-WHtR were slightly higher, then they can be promising markers for periodontitis.

Periodontitis and diabetes have a two-way association, and these two diseases affect each other. Our study revealed a positive association between periodontitis and IR. Both diseases have several causes. However, both are affected by inflammation, and they require early diagnosis and treatment (Blasco-Baque et al., 2017; Cutler et al., 1999; Darby, 2022). High triglyceride levels are a manifestation of hyperlipidemia, and serum lipid metabolism can be adversely affected by the upregulation of proinflammatory factors induced by periodontitis (Fentoğlu et al., 2011). Periodontal bacteria may promote ROS overproduction by downregulating enzymatic antioxidant defense systems, leading to oxidative stress. The interaction between inflammation and oxidative stress disrupts insulin signaling pathways and promotes IR (Thouvenot et al., 2022).

In addition, some studies have revealed a causal association between periodontitis and obesity (Gorman et al., 2012; Saxlin et al., 2009). A previous epidemiological study assessed the effect of obesity on the onset and progression of periodontitis. Results showed that elevated body mass index, WC, percentage of subcutaneous fat, and blood lipid levels are associated with an increased risk of developing periodontitis (Arboleda et al., 2019). In terms of the underlying biological mechanism for this association, adipose tissue-derived cytokines, such as tumor necrosis factor-alpha and interleukin-6, can affect systemic metabolism and contribute to the development of low-grade systemic inflammation (Jepsen et al., 2020). However, the currently available evidence varies, and it is inconclusive (Keller et al., 2015). Therefore, the combined use of TyG index and obesity-related data is clinically important for assessing the association between IR and periodontitis.

Compared with the previous use of HEMC as a method for evaluating IR, TyG is more convenient and easier to obtain and calculate (Tao et al., 2022). A previous study used different screening metrics to predict the association between metabolic-associated fatty liver disease and nonalcoholic fatty liver disease (NAFLD). In women, TyG-WHtR had the best performance in identifying MAFLD/NAFLD. In men, TyG-WC had the best performance in identifying MAFLD/NAFLD (Peng et al., 2023). A recent study showed that TyG-BMI is more effective in predicting prediabetes (Jiang et al., 2021). Further, TyG-related indicators have a practical value in clinical practice. Our study results were comparable to those of prior investigations conducted by Lee et al. (Lee et al., 2023), which explored the association between modified triglyceride index and periodontitis among Korean adults. This study emphasized that the TyG-WHtR index emerged as a superior predictor of the association between periodontitis and IR. However, different results were obtained for the association between TyG-BMI and TyG-WC and periodontitis, which can be possibly attributed to the various characteristics of the populations. BMI, WC, and WHtR are three common anthropometric measures. BMI is the most widely used method for assessing adiposity. Nevertheless, it cannot differentiate the other components of body weight, such as bones, muscles, and internal organs and does not reflect fat distribution. Further, it is affected by region and disease (Kleine et al., 2018). WC is an indicator of abdominal obesity. Nevertheless, height affects accuracy (Browning et al., 2010). In contrast, WHtR, which is another indicator of abdominal obesity, has earned support from systematic evaluations and meta-analyses due to its efficacy in predicting cardiovascular and metabolic risks (Ashwell et al., 2012). Further, the analysis was extended by conducting a comparative assessment of HOMA-IR and TyG-related indices, thereby providing a more comprehensive view of the underlying metabolic associations.

Our study revealed that HOMA-IR score and TyG-WHtR were superior than the other indices in predicting periodontitis. HOMA-IR requires the measurement of endogenous insulin, which is not involved in basic and routine blood tests. WHtR is an easily usable marker of generalized and abdominal obesity. Another study shows that WHtR is a more accurate indicator of cardiometabolic risk factors, particularly when detecting abdominal fat accumulation, than WC and BMI (Iliodromiti et al., 2018).

Our study provides novel information showing that HOMA-IR score and TyG-WHtR index can be early biomonitoring markers of periodontitis in susceptible populations. This study had several limitations: First, the results of the current study might have been influenced by selection bias, and cohort studies could provide more robust evidence. Second, this study had a relatively small sample size as some individuals had missing data. Therefore, the generalizability of the TyG-related indicators in larger populations should be cautiously evaluated.

HOMA-IR score and TyG-WHtR are optimal indicators of IR, which is a parameter used to assess the risk of periodontitis. We believe that these indices will be reliable and practical tools for primary prevention in individuals with a high prevalence of periodontitis.

Ethics approval and consent to participate

The study was conducted by the Declaration of Helsinki and was approved by the Institutional Review Board of the National Centre for Health Statistics. All participants provided informed consent before enrollment.

Consent for publication

Not applicable.

Availability of data and materials

Publicly available datasets were analyzed in this study. This data can be accessed at: The National Health and Nutrition Examination Survey https://www.cdc.gov/nchs/nhanes/index.htm

Competing interests

The authors declare no potential conflict of interest.

Funding

This study was supported by a grant from the Science and Technology Department of Jiangsu Province (Grant.BE2020707).

Authors' contributions

Yiyuan Lang designed the study, conducted data analysis, and drafted the manuscript. Xin Song conducted data analysis and drafted the manuscript. Yan Chen, Han Mei and Chengyu Wu have contributed to the production of charts and data processing. Changao Xue and Rui Zhang reviewed the article. All authors read and approved the final manuscript.

Acknowledgements

The authors sincerely thank the National Health and Nutrition Examination Survey (NHANES) database for providing data. We would also like to thank Haifeng Lang for helpful discussions.

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No competing interests reported.

Association between the indicators of insulin resistance and periodontitis: A study using data from the National Health and Nutrition Examination Survey 2009–2014

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Abstract

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1. Introduction

2. Methods

3. Results

4. Discussion

5. Conclusion

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