Association of periodontitis stages with glycemic control in adults with and without type 2 diabetes mellitus: a cross-sectional study

Abstract

Objective:  To investigate associations among periodontal parameters, glycated hemoglobin (HbA1c), and metabolic parameters in adults with and without type 2 diabetes mellitus (T2D).

Methodology:  A cross-sectional study included 74 adults diagnosed with periodontitis according to the current periodontal classification of 2018. Participants underwent a full-mouth periodontal examination, laboratory assessment, and Body Mass Index (BMI). Periodontitis was categorized into Stages I/II and Stages III/IV. HbA1c, lipid profile, high-sensitivity C-reactive protein (CRP), and insulin resistance (HOMA-IR) were assessed. Periodontal inflammatory burden was quantified using the Periodontal Inflamed Surface Area (PISA). Non-parametric tests and Spearman correlation analyses were performed, stratified by diabetes status (α=5%).

Results:  Individuals with advanced periodontitis (Stages III/IV) had significantly higher HbA1c levels (6.8% vs. 5.8%; p=0.007), higher triglyceride concentrations (142.0 vs. 100.5 mg/dL; p=0.016), and lower HDL-cholesterol levels (46.0 vs. 52.0 mg/dL; p=0.012) than those in Stages I/II. Poor glycemic control (HbA1c >8.5%) and T2D duration ≥10 years were significantly associated with advanced stages (p<0.05). No significant differences were observed for BMI, LDL, total cholesterol (TC), CRP, or HOMA-IR between groups. In adults with T2D, PISA correlated positively with TC and LDL-cholesterol, whereas in non-diabetic individuals, PISA was associated primarily with triglycerides.

Conclusions:  Advanced periodontitis was associated with poorer glycemic control and a more atherogenic lipid profile, particularly characterized by elevated triglycerides and reduced HDL-cholesterol. The findings support periodontitis as a potential marker of systemic metabolic dysregulation and reinforce the importance of integrating periodontal care into cardiometabolic risk management strategies.

Keywords:
Periodontitis; Diabetes mellitus; Glycated hemoglobin; Dyslipidemia

Introduction

Diabetes mellitus is a chronic metabolic disorder characterized by persistent hyperglycemia resulting from impaired insulin secretion and/or insulin action, with Type 2 diabetes mellitus (T2D) accounting for nearly 90% of all cases worldwide.¹ Glycated hemoglobin (HbA1c) remains the gold-standard biomarker for the diagnosis and long-term monitoring of glycemic control.²,³ In addition to hyperglycemia, insulin resistance constitutes a central pathophysiological mechanism underlying T2D and is commonly estimated using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR).⁴

Accumulating evidence has consistently demonstrated a bidirectional relationship between diabetes and periodontitis.⁵–⁷ Periodontitis is a chronic multifactorial inflammatory disease initiated by dysbiotic oral biofilms and characterized by the progressive destruction of tooth-supporting tissues, ultimately contributing to a persistent systemic inflammatory burden.⁸ Although high-sensitivity C-reactive protein (CRP) has traditionally been employed as a marker of low-grade systemic inflammation, growing evidence suggests that alterations in lipid metabolism may represent a more relevant mechanistic pathway linking periodontal inflammation to metabolic dysfunction and cardiovascular risk.²

Meta-analytic evidence indicates that chronic periodontitis is significantly associated with an unfavorable lipid profile, including elevated triglycerides and low-density lipoprotein (LDL) cholesterol levels, accompanied by reduced high-density lipoprotein (HDL) cholesterol concentrations.⁹ Longitudinal cohort studies further support these findings, demonstrating that periodontal parameters are associated with higher follow-up levels of total cholesterol (TC), TG, and LDL.²,³ Together, these findings support the concept that periodontal inflammation may contribute to systemic lipid dysregulation and heightened cardiometabolic risk.²

In this context, alterations in individual lipid fractions have been recognized as sensitive indicators of the metabolic impact of chronic inflammation. Systematic evidence suggests that the inflammatory burden imposed by periodontitis may interfere with lipid homeostasis, contributing to a pro-atherogenic profile even before overt changes in TC occur.²,⁹ This metabolic imbalance is biologically plausible, as pro-inflammatory cytokines chronically elevated in periodontitis, such as TNF-α and IL-6, can stimulate hepatic triglyceride synthesis and simultaneously impair the maturation and protective function of HDL particles.¹⁰ Furthermore, longitudinal studies have demonstrated that periodontal destruction is independently associated with these specific lipid alterations, which may amplify the systemic pro-inflammatory environment characteristic of T2D.²,¹¹

The current 2018 periodontal classification system incorporates staging and grading to characterize disease severity and progression based on clinical attachment loss (CAL), radiographic bone loss, and complexity factors.¹² Staging is primarily based on the severity and extent of cumulative past tissue destruction, measured by CAL, bone loss, and tooth loss, while grading reflects the rate of disease progression and the influence of systemic risk modifiers, such as smoking and HbA1c levels. Although this categorical system is essential for clinical diagnosis, it does not provide a direct, continuous quantitative measure of the total active inflammatory burden currently present in the periodontium. In this context, the Periodontal Inflamed Surface Area (PISA) index, developed by Nesse, et al.¹³ (2008), serves as a valuable complementary tool. The rationale for including PISA in this study is its ability to quantify the total inflamed periodontal surface area as a single continuous variable.¹³ This allows for a more detailed assessment of how the active inflammatory load, rather than just past attachment loss, relates to systemic metabolic parameters—like insulin resistance, HbA1c levels, CRP, and lipid profile.¹⁴

Despite the well-established association between periodontitis and diabetes, important gaps remain regarding how contemporary periodontal staging relates to metabolic and lipid alterations, particularly in individuals with and without T2D. Therefore, our study aimed to investigate the association between periodontal parameters, HbA1c levels, and lipid parameters (TG, HDL, LDL, and TC) in adults with and without T2D. We hypothesized that advanced periodontitis stages (Stages III and IV) would be associated with poorer glycemic control and a more atherogenic lipid profile.

Methodology

Study Design and Ethical Aspects

This cross-sectional study was funded by the National Council for Scientific and Technological Development (CNPq) and the Brazilian Hospital Services Company (EBSERH) under grant number 408020/2021-0. The study protocol was approved by the Human Research Ethics Committee at the Faculty of Health Sciences, University of Brasília (approval number 87962818.4.0000.0030), and all participants provided written informed consent before enrollment, in accordance with the Declaration of Helsinki.

Recruitment

Participants were recruited from March to December 2023 at the dental clinic of the University Hospital of Brasília (HUB/EBSERH) in response to spontaneous demand for dental treatment. The study sample comprised a subset of a larger project conducted at the same institution. The flowchart is shown in Figure 1.

Figure 1
Flowchart.

Eligibility Criteria

Adults aged 30 years or older were eligible for inclusion, regardless of self-reported T2D status. Participants with or without T2D were included.

Exclusion criteria included: type 1 diabetes mellitus, pregnancy or postpartum status, periodontal treatment within the past 12 months, immunocompromised conditions, transplant recipients, epilepsy, Sjögren's syndrome, lupus, Crohn's disease, HIV infection, celiac disease, and a history of head and neck radiotherapy or chemotherapy within the past three months.

After screening, participants were evaluated through periodontal clinical examination and panoramic radiography. Only participants with a diagnosis of Periodontitis, according to the current periodontal classification, were included.¹²

Sample Size

This study used a convenience sample drawn from a larger project, whose original sample size calculation was based on a different primary outcome. Therefore, a post-hoc power analysis was conducted using the observed effect size for HbA1c levels across periodontitis stages.

With a final sample of 74 adults (n=24 for Stages I/II and n=50 for Stages III/IV) and an observed effect size of Cohen's d=0.716 for HbA1c levels, the study achieved 81.2% power at a 5% significance level.

Data Collection

Data collection included sociodemographic, behavioral, anthropometric, medical, laboratory, and periodontal assessments.

Sociodemographic and medical history information were obtained through a structured conversational interview based on the Adult Oral Health Standard Set.¹⁵ Smoking status was categorized according to Tomar and Asma.¹⁶ Individuals who had never smoked or had quit smoking more than five years before the interview were considered non-smokers.

Anthropometric measurements included body weight and height. Weight was measured with a calibrated digital scale, and height with a stadiometer. Body Mass Index (BMI) was calculated as weight (kg) divided by height squared (m²).

Peripheral venous blood samples were collected after a 12-hour overnight fast and analyzed by the hospital laboratory team. Laboratory analyses included fasting glucose, fasting insulin, glycated hemoglobin (HbA1c), high-sensitivity C-reactive protein (CRP), and lipid profile parameters.

HbA1c levels were measured by high-performance liquid chromatography (HPLC-A1C). Serum hs-CRP levels were determined by the immunoturbidimetric method. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), and triglycerides were analyzed by enzymatic-colorimetric methods.

Insulin resistance was estimated using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), calculated according to the standard formula: HOMA-IR = Fasting insulin (U/ml) × fasting glucose/405.⁴

Periodontal Examination

A full-mouth periodontal examination was performed at six sites per tooth on all present teeth using a Williams-marked Michigan O periodontal probe (Hu-Friedy, Chicago, IL, USA). The following periodontal parameters were measured:

• Probing depth (PD): the distance from the gingival margin to the base of the periodontal pocket or sulcus;

• Gingival recession (REC): the distance from the cementoenamel junction (CEJ) to the gingival margin;

• Clinical attachment loss (CAL): measured from the CEJ to the base of the pocket or sulcus;

• Bleeding on probing (BOP): recorded as present or absent.

Panoramic, bitewing, and periapical radiographs were obtained to classify periodontal condition according to the current periodontal classification criteria for staging and grading.¹²

Participants with HbA1c < 7.0% were classified as Grade B when bone loss criteria were met, whereas individuals with HbA1c ≥ 7.0% were classified as Grade C according to the established grading criteria.

Clinical examinations were conducted by five calibrated examiners following standardized protocols. Inter- and intra-examiner reliability for probing depth (PD) and clinical attachment loss (CAL) was assessed using weighted Kappa coefficients (linear weighting) to account for the magnitude of disagreement.¹⁷ Only examiners with coefficients above 0.70 were authorized for data collection. Because initial probing can induce bleeding and interfere with subsequent measurements, bleeding on probing (BOP) was excluded from the reliability assessment.

Periodontal Inflamed Surface Area (PISA)

The Periodontal Inflamed Surface Area (PISA) was calculated according to the method proposed by Nesse, et al.¹³ (2008). CAL, REC, PD, and BOP measurements obtained at six sites per tooth were used to estimate the inflamed periodontal epithelial surface area.

Only bleeding sites were included in the calculations. The total inflamed periodontal surface area was calculated in square millimeters (mm²) by summing the inflamed sites across the dentition. The PISA index served as a continuous measure of active periodontal inflammatory burden.

Statistical Analyses

Data were entered into Microsoft Excel spreadsheets and analyzed using JAMOVI (version 2.3.28).

The distribution of continuous variables was assessed using the Shapiro-Wilk test. Because most variables were not normally distributed (p<0.05), non-parametric statistical methods were used.

Descriptive analyses included absolute and relative frequencies for categorical variables and medians, along with minimum and maximum values, for continuous variables.

Participants were categorized by periodontitis stage into:

• Stages I/II (initial/moderate periodontitis)

• Stages III/IV (advanced periodontitis)

Comparisons between two groups were performed using the Mann-Whitney U test for continuous variables and the Chi-square test for categorical variables. Comparisons involving more than two groups were conducted using the Kruskal-Wallis test. When those analyses identified statistically significant differences, post-hoc pairwise comparisons were conducted using the Dwass-Steel-Critchlow-Fligner (DSCF) test with multiple-comparison adjustment.

Spearman correlation coefficients were calculated to assess associations among periodontal parameters, glycemic markers, inflammatory biomarkers, anthropometric variables, and lipid profile parameters. Correlation analyses were also stratified by self-reported T2D status to determine whether diabetes modified the relationship between periodontal inflammation and systemic metabolic markers. Correlation analyses were considered exploratory and aimed to assess potential effect modification by T2D status.

All analyses were conducted at a 5% significance level (p<0.05).

Results

Analyses were performed using available data for each variable, as indicated in Table 1. The final sample comprised 74 adults, all diagnosed with periodontitis according to the current periodontal classification (2018).¹² Participants were predominantly female (62.2%). Participants in the advanced stages group (Stages III/IV) had a significantly higher median age than those in the early stages group (Stages I/II) (57 vs. 45 years, p<0.001). Among the participants, 43 adults (58.1%) had T2D, while 31 adults (41.9%) did not (Table 1).

Table 1
Characteristics of the study population by periodontitis stage.

Characteristics	Periodontitis	Stage I/II n= 24	Stage III/IV n= 50	p-value
Sex n (%)				0.037 *
Male	28 (37.9%)	5 (6.8 %)	23 (31.1 %)
Female	46 (62.2%)	19 (25.7 %)	27 (36.5 %)
Total	74	24	50
Age (years), median (min–max)	54 (34-86)	45 (34-68)	57(34-86)	<0.001 *
BMI kg/m2 median (min-max)	27.3 (18.1-46.7)	26.6 (20.5-35.3)	27.9 (18.1-46.7)	0.319
BMI Categories, n (%)
Up to 24.9	18 (24.3%)	7 (9.4%)	11 (14.9%)	0.661
25.0 to 30.0	30 (40.5%)	10 (13.5%)	20 (27.0%)
Above 30.0	24 (32.4%)	6 (8.1%)	18 (24.3%)
Total	72	23	49
Smoking n (%)				0.131
Never	50 (67.5%)	20 (27.0 %)	30 (40.5%)
Current	5 (6.8 %)	1 (1.4%)	4 (5.4%)
Former smoker	19 (25.7%)	3 (4.1%)	16 (21.6 %)
Total	74	24	50
Education level n (%)
No education	1 (1.4%)	0 (0.0%)	1 (1.4%)	0.123
Elementary school	19 (25.7%)	4 (5.4%)	15 (20.3%)
High school	28 (38.0%)	6 (8.2%)	22 (29.8%)
Higher education	26 (35.1%)	14 (18.9 %)	12 (16.2 %)
Total	74	24	50
HbA1c % median (min–max)	6.2 (4.60-12.3)	5.8 (4.6-10.0)	6.8 (5.0-12.3)	0.007 *
Categories HbA1c n (%)
up to 6.4%	40 (54.1%)	20 (27.0 %) a	20 (27.0 %) a	0.003 *
6.5% to 7.5%	12 (16.2 %)	2 (2.7%) ab	10 (13.5 %) ab
7.6% to 8.5%	4 (5.4%)	0 (0.0%) ab	4 (5.4%) ab
above 8.5%	14 (18.9 %)	2 (2.7%) b	12 (16.2 %)b
Total	70	24	46
HOMA-IR median (min-max)	3.69 (0.12-43.47)	3.13 (0.78-15.62)	4.20 (0.12-43.47)	0.458
Diabetes, n (%)				0.013 *
with T2D	43 (58.1%)	9 (12.2 %)	34 (45.9 %)
Without T2D	31 (41.9%)	15 (20.3 %)	16 (21.6 %)
Total	74	24	50
Years since T2D diagnosis, n (%)				0.046 *
No T2D	31 (41.9%)	15 (20.3 %) a	16 (21.6 %) a
Up to 1 year	2 (2.7%)	0 (0.0%) ab	2 (2.7%) ab
2 to 9 years	15 (20.3%)	5 (6.8 %) ab	10 (13.5 %) ab
10 years or more	26 (35.1%)	4 (5.4 %) b	22 (29.7 %) b
Total	74	24	50
CRP mg/dL median (min–max)	0.25 (0.01-2.85)	0.320 (0.01-1.55)	0.230 (0.02-2.85)	0.627
Triglycerides mg/dL median (min–max)	133 (30-428)	100.5 (30-297)	142.0 (61-428)	0.016 *
Total cholesterol mg/dL median (min–max)	197 (115-287)	197.5 (115-287)	194.0 (115-281)	0.253
HDL cholesterol mg/dL median (min–max)	48.5 (32-91)	52.0 (35-91)	46.0 (32-69)	0.012 *
LDL cholesterol mg/dL median (min–max)	114.8 (43.2-198)	121.2 (63-188)	110.6 (43.2-198)	0.183

• BMI: Body Mass Index; HbA1c: Glycated hemoglobin; HOMA-IR: Homeostatic Model Assessment for Insulin Resistance; CRP: C-reactive protein. HDL: High-density lipoprotein LDL: Low-density lipoprotein.
• ^*
  p<0.05 indicates statistical significance between Stage I/ II and Stage III / IV groups (Mann-Whitney U or Chi-square test).
• Different superscript letters (a, b) indicate significant pairwise differences (p<0.05) between categories of ‘HbA1c levels’ and ‘Years since T2D diagnosis’ based on the Dwass-Steel-Critchlow-Fligner (DSCF) post-hoc test following a significant Kruskal-Wallis test.
• Categories sharing the same letter (or the ‘ab’ notation) do not differ significantly from each other.
• ^†
  Missing data: HbA1c results = 70 (4 missing), BMI results=72 (2 missing), HOMA-IR results=72 (2 missing), CRP results = 71 (3 missing) and LDL cholesterol results = 72 (2 missing).

Regarding the metabolic profile, HbA1c levels (n=70) were significantly higher in individuals with advanced periodontitis (median 6.8% vs. 5.8%; p=0.007). Significant differences were also observed in the lipid profile between groups; individuals in advanced stages presented higher triglyceride levels (142.0 vs. 100.5 mg/dL; p=0.016) and significantly lower HDL cholesterol levels (46.0 vs. 52.0 mg/dL; p=0.012). No significant differences were observed in BMI, TC, LDL, or CRP levels between the periodontal stage groups in the descriptive analysis (p>0.05) (Table 1).

Categorical analysis revealed an uneven distribution, where the proportion of individuals with poor glycemic control (> 8.5%) (n=70) was significantly higher in Stages III/IV (p=0.003). Furthermore, a T2D diagnosis duration of ≥10 years was significantly associated with periodontal severity (p=0.046). Regarding the lipid profile, individuals in advanced stages had higher triglyceride levels (p=0.012) and lower HDL levels (p=0.012). No significant differences were observed for BMI or CRP between the groups (Table 1).

Periodontal clinical parameters distinguished between the study groups (Table 2). There was a strong association between staging and periodontitis grade (p<0.001; Cramer's V=0.733), with most patients in Stages III/IV being classified as Grade C (62%), while Grade A was observed exclusively in Stages I/II.

Table 2
Periodontal clinical parameters of the study population by periodontitis stage.

Periodontal parameters	Stage I / II	Stage III / IV	p-value
	n= 24	n= 50
Periodontitis grade n (%)
A	14 (58.3%) a	0 (0%) b	<0.001*
B	8 (33.3%) a	19 (38%) a
C	2 (8.3%) b	31 (62%) a
Number of teeth in the mouth (including 3rd molars), median (min–max)	27 (10-32)	21 (4-29)	<0.001*
Probing Depth mm Mean±SD	2.23±0.29	2.29±0.66	0.557
Clinical Attachment Loss mm Mean±SD	0.71±0.57	1.64±1.81	0.013*
Bleeding on probing % Mean±SD	30.6±19.6	45.5±10.3	0.720
PISA mm2 Mean±SD	137.85±148.2	226.46±419.7	0.796
median (min-max)	85.38 (0.0-477)	69.27(0.0-2405)

• SD: Standard Deviation. PISA: Periodontal Inflamed Surface Area.
• ^*
  p < 0.05 indicates statistical significance between Stage I & II and Stage III & IV groups (Mann-Whitney U or Chi-square test). Different superscript letters in the same row indicate a statistically significant difference between stage groups (p < 0.05) based on Pearson's Chi-square test with adjusted standardized residuals analysis. Cramer's V = 0.733.

Tooth loss was significantly more pronounced in advanced stages, with a median of 21 teeth present compared to 27 in the early stages group (p<0.001). As expected, CAL was significantly higher in the Stages III/IV group (p=0.013). Interestingly, the inflammatory burden (PISA) and PD did not differ statistically between stage groups in this sample (Table 2).

Spearman correlation analyses, stratified by diabetes status, were conducted using available-case data for each variable (Table 3). In both groups (with and without T2D), periodontitis stages were positively associated with disease grade and strongly associated with the number of teeth and age (p<0.05).

Table 3
Spearman correlation matrix (rho) between periodontal and systemic variables stratified by T2D status.

Variable 1	Variable 2	Spearman's rho	p-value
Part A. Patients with T2D (n=43)
Periodontal Stage	Age	0.319	0.037 *
Periodontal Stage	Number of Teeth	-0.464	0.002 **
Periodontal Stage	LDL Cholesterol	0.316	0.042 *
PISA (mm2)	Total Cholesterol	0.421	0.005 **
PISA (mm2)	LDL Cholesterol	0.450	0.003 **
Periodontal Grade	BMI	0.413	0.007 **
Part B. Patients without T2D (n=31)
Periodontal Stage	Age	0.405	0.024 *
Periodontal Stage	Number of Teeth	-0.583	<0.001 ***
PISA (mm2)	Triglycerides	-0.402	0.025 *
Periodontal Grade	BMI	0.452	0.014 *

• Spearman's rho correlation coefficient. BMI: Body Mass Index; PISA: Periodontal Inflamed Surface Area; LDL: Low-density lipoprotein.
• ^a
  Significant associations are indicated by:
• ^*
  p<0.05,
• ^**
  p<0.01,
• ^***
  p<0.001.

Specifically, in the T2D group, a positive association was observed between periodontitis stage and LDL-cholesterol levels (rho=0.316; p=0.042). Additionally, the PISA index correlated positively with TC and LDL (p<0.01) only in individuals with diabetes. In the group without diabetes, BMI showed a positive association with CRP levels (rho=0.617; p<0.001) and a negative association with PISA (p=0.014). In both groups (T2D and without T2D), the metabolic markers HbA1c and HOMA-IR correlated significantly with each other but showed no direct linear association with clinical periodontitis stages when analyzed separately (p>0.05) (Table 3).

Discussion

The primary objective of this study was to investigate the association between periodontitis severity, as defined by the 2018 classification, and central markers of glucose metabolism and metabolic parameters.¹² These findings demonstrate that advanced periodontitis (Stages III/IV) is associated not only with worse clinical oral indicators (fewer teeth, greater attachment loss, fast progression – grade C) but also with a more adverse metabolic profile, characterized by higher HbA1c levels, elevated triglycerides, lower HDL, and longer diabetes duration (in adults with T2D). The extent of periodontal inflammation, measured by PISA, related differently to systemic markers depending on self-reported T2D status. Among adults diagnosed with T2D, a significant correlation was demonstrated between PISA and both TC and LDL cholesterol. In contrast, for those without T2D, PISA was significantly associated only with Triglyceride levels (Tables 1, 2, 3).

These results align with the well-established bidirectional relationship between periodontitis and diabetes mellitus, as well as the growing evidence linking periodontitis to metabolic dysfunction in individuals without diabetes.⁷,¹⁸,¹⁹ Diabetes, particularly when poorly controlled, significantly increases the risk, severity, and progression of periodontitis through multiple biological mechanisms, including oral microbial dysbiosis, increased inflammation, epithelial barrier dysfunction, impaired neutrophil and macrophage function, and altered bone metabolism.⁷ Conversely, periodontitis is strongly linked to poor glycemic control in diabetic patients, with clinical studies and meta-analyses reporting consistent positive associations.⁵,⁷,²⁰ The finding that adults with T2D and a longer time since diagnosis were more likely to present with advanced periodontitis stages (Table 1) is consistent with the concept of a cumulative, time-dependent effect of hyperglycemia on periodontal tissue destruction. The role of disease duration in this association is biologically plausible, as prolonged hyperglycemia leads to progressive accumulation of advanced glycation end-products (AGEs) in periodontal tissues. These accumulated AGEs interact with their receptor (RAGE), triggering NF-κB activation, oxidative stress, and the sustained release of proinflammatory cytokines (TNF-α, IL-1β, IL-6) and matrix metalloproteinases, collectively promoting collagen degradation, impairing tissue repair, and stimulating osteoclastogenesis.⁶,²¹

The association between advanced periodontitis and elevated HbA1c observed in this study is supported by substantial evidence in both diabetic and non-diabetic populations. A study of 135 normoglycemic patients found that most periodontitis patients were in the undiagnosed prediabetes group (47% of stages I and II, and 44% of stages III and IV), with higher average HbA1c levels across stages of periodontitis (p<0.01). Therefore, in individuals without diabetes, periodontitis has been found to be significantly associated with elevated HbA1c levels, being more pronounced in patients with stage III and IV periodontitis.¹⁸ Furthermore, comprehensive periodontitis case definitions, such as the current periodontal classification (2018), better detect the association between periodontal disease and HbA1c across populations.¹²,¹⁹ For the stage III/IV periodontitis period, the adjusted odds ratios for prediabetes and diabetes HbA1c were 1.19 and 1.76, respectively.¹⁹ A cross-sectional study demonstrated that patients with chronic periodontitis and undiagnosed diabetes had significantly higher serum HbA1c levels than periodontally healthy controls, with HbA1c levels positively correlated with the severity of periodontitis before diabetes onset.²²

Longitudinal evidence from the Study of Health in Pomerania (SHIP) demonstrated that periodontal disease was associated with 5-year HbA1c progression in participants without T2D, with an approximately fivefold increase in HbA1c between the highest and lowest periodontal disease categories, and results were markedly stronger among participants with CRP ≥1.0 mg/L.²³ Taken together, these studies reinforce the notion that periodontitis may contribute to glycemic dysregulation, even in the absence of a diagnosis of diabetes.

Another important aspect of our findings is the absence of a direct linear association between clinical periodontitis stages and HOMA-IR after stratification by diabetes status (Table 3). Although HbA1c and HOMA-IR remained significantly correlated, advanced periodontal stages were more consistently associated with long-term glycemic control than with insulin resistance itself. One possible explanation is that HbA1c reflects cumulative metabolic exposure over the preceding months, whereas HOMA-IR may be more sensitive to short-term metabolic fluctuations and obesity-related pathways. In addition, insulin resistance is strongly influenced by adiposity and hepatic metabolism.

The relationship between BMI, CRP, and periodontal parameters also warrants attention (Table 3). In the non-diabetic subgroup, BMI was positively associated with CRP levels, supporting the well-established role of obesity as a major driver of systemic low-grade inflammation. According to Abu-Shawish, et al.²⁴ (2022), obesity increases systemic inflammatory burden, which in turn increases susceptibility to the onset and progression of periodontal disease. Despite the high prevalence of overweight and obesity in the present sample, BMI did not differ significantly across periodontal stages (Table 1). This suggests that the metabolic alterations associated with advanced periodontitis may not be explained exclusively by obesity, but rather by the interaction between chronic periodontal inflammation and systemic metabolic pathways. Furthermore, the lack of significant differences in CRP levels between periodontal groups in our study (Table 1) may be explained by the pre-existing chronic inflammatory state inherent in severe obesity, which can "mask" the specific systemic inflammatory burden typically induced by periodontitis.²⁵

In the Mann-Whitney comparisons according to periodontitis stage (Table 1), adults with more advanced stages of periodontitis exhibited significantly higher triglyceride and lower HDL-cholesterol levels, whereas no significant differences were observed for TC, LDL-cholesterol, or CRP. While these findings partially diverge from some meta-analyses that reported significant elevations in TC and LDL in periodontitis patients, they are notably consistent with the meta-analysis by Nepomuceno, et al.⁹ (2017), which, after restricting the analysis to non-smoking individuals not using lipid-lowering agents, found that TC was higher in the periodontitis group but without reaching statistical significance, whereas triglycerides and HDL remained significantly altered.⁹,²⁶ This pattern would suggest that triglycerides and HDL may be more sensitive markers of the metabolic impact of periodontal inflammation than TC or LDL. From a mechanistic standpoint, proinflammatory cytokines, chronically elevated in periodontitis (particularly TNF-α and IL-6), stimulate hepatic triglyceride synthesis via increased LDL production, while simultaneously impairing HDL function.²⁷ In contrast, TC and LDL levels are more strongly influenced by dietary intake, genetic factors, and hepatic LDL receptor activity, thereby diluting the relatively modest inflammatory signal from periodontitis. The longitudinal cohort study by Song et al.³, involving 65,078 individuals, further supports this selective lipid alteration: periodontitis was independently associated with decreased HDL and tooth loss with increased triglycerides, whereas there were no significant longitudinal changes in TC or LDL.

Regarding the absence of a significant association with CRP in the stage-based comparison (Table 1), this finding aligns with the recent meta-analysis by Gupta, et al.²⁸ (2026), which pooled cardiovascular biomarkers in periodontitis and found that HDL was significantly reduced and the oxidative stress index, significantly elevated, whereas CRP, IL-1β, IL-6, and other inflammatory markers showed no significant differences. The relationship between periodontitis and CRP appears to be context-dependent. Singer, et al.²⁹ (2015) showed that this association is modified by systemic oxidative stress, with periodontitis being associated with elevated CRP only in the highest quartile of oxidative stress. Sample size, the cross-sectional design, and unmeasured confounders, such as physical activity and dietary patterns, may also have contributed to the lack of significant findings for these specific markers.

The absence of significant differences in PISA across periodontal stage groups warrants careful interpretation. Although patients with stages III/IV showed greater cumulative tissue destruction, tooth loss, and CAL, the active inflammatory burden, as measured by PISA, did not differ significantly between groups (Table 1). This finding likely reflects an important conceptual distinction between cumulative periodontal destruction and current inflammatory activity. The staging system primarily captures historical tissue loss accumulated over time, whereas PISA estimates the actively inflamed periodontal surface at the time of examination. Consequently, individuals with fewer remaining teeth and extensive past destruction may not necessarily exhibit proportionally larger inflamed periodontal surfaces. This interpretation is biologically plausible and reinforces the complementary role of PISA as a dynamic inflammatory marker rather than a measure of cumulative disease severity.¹²,¹³

Importantly, when the analysis was stratified by diabetes status (Table 3), a differential pattern of lipid alterations emerged. In diabetic patients, the advanced periodontitis stage was correlated with older age, fewer remaining teeth, and higher LDL-cholesterol, while PISA in this subgroup was associated with TC and LDL-cholesterol. Conversely, in non-diabetic patients, the advanced stage was associated with older age and fewer remaining teeth, whereas PISA was associated with triglycerides rather than LDL or TC. These divergent patterns suggest that diabetes acts as an effect modifier in the relationship between periodontal inflammation and lipid metabolism, channeling the dyslipidemic impact toward different lipid fractions depending on the underlying metabolic milieu.³⁰

The association between PISA and LDL-cholesterol specifically in diabetic patients is biologically plausible. Insulin resistance and hyperinsulinemia can promote hepatic overproduction of apolipoprotein B-containing lipoproteins, particularly small dense LDL particles.³⁰ The superimposed chronic inflammatory burden from periodontitis may synergistically amplify this pathway, as proinflammatory cytokines further impair LDL receptor expression and reduce LDL clearance.⁹ This is consistent with the findings of Zhang, et al.³¹ (2022), who demonstrated that in patients with T2D nephropathy and periodontitis, the number of remaining teeth was negatively correlated with LDL levels, and that periodontal inflammation was independently associated with a 2.3-fold higher risk of dyslipidemia. Furthermore, Graves, et al.⁷ (2026) highlighted that the bidirectional relationship between diabetes and periodontitis involves oral microbial dysbiosis, epithelial barrier dysfunction, and cytokine imbalance, which collectively may preferentially affect LDL metabolism in the diabetic state.

In contrast, the association of PISA with triglycerides in non-diabetic patients aligns with the predominant inflammatory pathway described in the literature. In the absence of metabolic derangements associated with diabetes, the systemic inflammatory response to periodontal infection primarily stimulates hepatic triglyceride synthesis by increasing VLDL production.³² Miki et al.³³ (2021), in a cross-sectional study of medically healthy individuals, similarly demonstrated that PISA was inversely associated with HDL-cholesterol and that this association was partly mediated by elevated serum CRP, reinforcing the inflammation-driven triglyceride/HDL pathway in the absence of diabetes.

These findings collectively suggest that the metabolic context modulates which lipid fractions are most susceptible to the inflammatory burden of periodontitis. As emphasized by the 2025 AHA Scientific Statement¹⁰ periodontitis is associated with cardiometabolic disease, including dyslipidemia and T2D, and the additive risk of the proinflammatory state attributable to periodontal disease is difficult to quantify in isolation against the backdrop of other exposures, underscoring the importance of controlling for confounding in studies examining the correlation between periodontal disease and systemic biomarkers.¹⁰

Notably, the interpretation of the lipid and inflammatory alterations described above must also consider the role of tobacco smoking, which represents a critical shared risk factor for both periodontitis and dyslipidemia.¹⁰,³⁴ The low prevalence of current smokers (6.8%) in our sample likely minimized the confounding effect of smoking on the observed associations. This is consistent with evidence suggesting that in populations with low smoking rates, the metabolic interplay between diabetes and periodontitis can be observed more directly.³⁵

Finally, these findings reinforce the importance of interpreting periodontitis within a broader systemic and cardiometabolic framework. Growing evidence suggests that periodontitis may affect not only glycemic control but also lipid metabolism, inflammatory homeostasis, and lipoprotein composition. Thouvenot, et al.²⁵ (2026) recently demonstrated that periodontitis in obese individuals is associated with dysbiosis of the gut microbiota and functional alterations in visceral adipose tissue. The combined observation of higher HbA1c, elevated triglycerides, lower HDL levels, and altered PISA-lipid associations in advanced stages of periodontitis supports the concept that periodontal disease acts as a chronic systemic inflammatory stressor. These findings further underscore the importance of integrating periodontal evaluation into multidisciplinary strategies aimed at managing diabetes and cardiovascular risk, particularly in metabolically vulnerable populations.²⁵

This study has some limitations. First, the cross-sectional design precludes establishing causal or temporal relationships between HbA1c levels and the stages of periodontitis. Consequently, it remains unclear whether sustained hyperglycemia contributed to the progression of periodontal destruction or, conversely, whether the systemic inflammatory burden imposed by advanced periodontitis adversely affected glycemic control.⁵,⁶ Second, the use of a convenience sample limits the external validity of the findings, as participants may not be representative of the broader population in terms of sociodemographic characteristics, disease severity, or healthcare-seeking behavior. Third, several behavioral and clinical variables known to influence both periodontal status and metabolic parameters, including medications, oral hygiene practices, dietary habits, and physical activity, were not included in the analysis and may have served as unmeasured confounders. As emphasized by the 2025 AHA Scientific Statement, the additive risk of the proinflammatory state attributable to periodontal disease is difficult to quantify in isolation, given other exposures, and residual confounding remains a concern in observational studies examining the relationship between periodontal disease and systemic biomarkers.¹⁰

Conclusion

In conclusion, the study demonstrates that advanced periodontitis stages, according to the 2018 periodontal classification, are associated with poorer long-term glycemic control and a more atherogenic lipid profile, characterized by higher triglyceride levels and reduced HDL-cholesterol concentrations. Individuals with longer T2D duration were more likely to present with advanced periodontitis, reinforcing the cumulative impact of chronic metabolic dysregulation on periodontal tissue destruction. Although no significant differences were observed in CRP or HOMA-IR across periodontal stages, the inflammatory burden measured by PISA showed distinct associations with lipid parameters by diabetes status, correlating with TC and LDL-cholesterol in adults with T2D and with triglycerides in non-diabetic individuals.

These findings suggest that advanced periodontitis serves as a clinical indicator of metabolic risk, underscoring the need for an integrated therapeutic approach that includes periodontal health as an essential component of systemic management for patients with glycemic and lipid imbalances.

Acknowledgements

This research was funded by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and the Empresa Brasileira de Serviços Hospitalares (Ebserh), grant number 408020/2021-0..

Data availability statement

All data generated or analyzed during this study are included in this published article.

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Edited by

• Editor:
  Linda Wang

• Associate Editor:
  Karin Hermana Neppelenbroek

Publication Dates

• Publication in this collection
  07 Aug 2026
• Date of issue
  2026

History

• Received
  05 Mar 2026
• Reviewed
  11 June 2026
• Accepted
  24 June 2026