Background
Periodontitis is a chronic inflammatory disease caused by plaque that arises in periodontal supporting tissue. Several factors can influence the onset and progression of periodontitis; these are known as the risk factors. The purpose of this study was to assess the risk factors of periodontitis patients with different severity of clinical attachment loss (CAL) and different dental regions.
Methods
A total of 15,904 sites of 3976 teeth from 142 patients with periodontitis were recruited in this retrospective observational study. The teeth were categorized into three groups according to interdental CAL values: 1 mm ≤ CAL ≤ 2 mm group, 3 mm ≤ CAL ≤ 4 mm group and CAL ≥ 5 mm group. The multilevel regression analysis was carried out to find out the risk factors of the severity of CAL in anterior teeth, maxillary teeth and mandibular teeth, respectively.
Results
In anterior teeth, significant correlations were observed with increasing CAL values for the following factors: current smoking (2.21, 95%CI: [1.27–3.83]), drinking (0.65, 95%CI: [0.44–0.98]), probing depth (PD) (1.19, 95%CI: [1.02–1.38]) and alveolar bone defect (ABD) (1.33, 95%CI: [1.10–1.62]) (P < 0.05). For maxillary teeth, the factors showing significant correlations were ABD in both premolars (0.87, 95%CI: [0.78–0.98]; 0.77, 95%CI: [0.66–0.90] and 1.46, 95%CI: [1.03–2.06]) and molars (1.50, 95%CI: [1.30–1.73]; 1.74, 95%CI: [1.40–2.17] and 2.72, 95%CI: [1.52–5.13]), as well as root concavities (1.36, 95%CI: [1.26–1.46]; 1.48, 95%CI: [1.32–2.66] and 1.17, 95%CI: [1.05–1.61]) across different CAL groups (P < 0.05). As for mandibular teeth, ABD in premolars (0.89, 95% CI: [0.79–1.01]; 0.87, 95%CI: [0.74–1.02] and 1.51, 95%CI: [1.12–2.04]) and molars (1.58, 95%CI: [1.35–1.85]; 2.16, 95%CI: [1.71–2.72] and 1.92, 95%CI: [1.10–3.57]) demonstrated significant correlations across different CAL groups (P < 0.05).
Conclusions
The severity of CAL in periodontitis is associated with a variety of risk factors, and the effects of these factors are varied in different dental regions.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12903-026-07668-1.
Keywords: Clinical attachment loss, Periodontitis, Retrospective observational study, Risk factors
Plain Language summary
Periodontitis is an inflammatory disease caused by microbial infection, leading to the destruction of supporting tissues. The risk factors of periodontitis encompass local, systemic, demographic, and behavioral host conditions, which are of great significance for assessing the extent of pathological alterations and anticipating prognosis. In this study, we evaluated epidemiological characteristics and clinical parameters of periodontitis patients, aimed at identifying the factors that influenced the varying degrees of CAL in anterior teeth, maxillary posterior teeth and mandibular posterior teeth, respectively. The results of this retrospective observational study indicated that the risk factors could differ depending on the specific dental region and the severity of periodontitis present. Therefore, dentists should pay more attention to patients presenting these aforementioned factors when diagnosing and advising treatment plans. The findings of this study will be beneficial in clinical diagnosis and treatment planning for periodontitis, facilitating more targeted and effective care.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12903-026-07668-1.
Key findings
The risk factors varied with dental regions and the severity of CAL in periodontitis patients.
Introduction
Periodontitis is an inflammatory disease caused by microbial infection, leading to the destruction of supporting tissues [1, 2]. According to the 2018 classification of Periodontal and Peri-implant Diseases and Conditions, periodontitis was outlined in three dimensions: severity and complexity (stage), extent (localized, generalized, molar-incisor pattern), and rate of progression (grade) [3–5]. Some clinical parameters, such as clinical attachment loss (CAL), bone resorption, probing depth (PD), class of furcation involvement (FI), tooth loss due to periodontal reasons, can reflect the stage and extent of periodontitis [6]. Additionally, radiographic bone loss (BL) and interdental CAL provide valuable insights into the overall destruction caused by periodontitis.
Among the clinical parameters utilized to assess periodontal condition, CAL is the most commonly employed and reliable indicator for supervising periodontal status in affected individual and denoting patterns of periodontal destruction [7]. As periodontal disease progresses, CAL manifests through the destruction of periodontal ligament and its adjacent alveolar bone, resulting in the gingival recession and pathologic periodontal probing [8]. Furthermore, unlike PD measures, CAL embodies an individual’s cumulative periodontal history and is anchored to a consistent landmark, commonly the cementoenamel junction [9], rendering it the gold standard [7].
In addition to plaque, increasing attention is being paid to the recognition of risk factors that impact the onset and progression of periodontitis [10]. These risk factors encompass local, systemic, demographic, and behavioral host conditions [11–15]. The comprehension of such risk factors is of great significance for assessing the extent of pathological alterations and anticipating prognosis. Previous studies have demonstrated that age, gender, plaque and bleeding indices serve as risk factors for periodontitis [16, 17]. Additionally, these risk factors may differ depending on the degree of CAL [18] and the specific dental positions [19]. Nevertheless, there is few research examining the risk factors associated with the severity of CAL in various dental positions.
Therefore, this study aimed to evaluate and compare the different risk factors contributing to the severity of CAL in periodontitis patients across different dental regions (anterior teeth, maxillary and mandibular posterior teeth) through a retrospective observation study, in order to provide the basis for precise risk assessment and personalized treatment of periodontitis.
Materials and methods
Participant selection
This retrospective study was conducted in patients with periodontitis from the Department of Periodontics at the School of Stomatology, China Medical University, Shenyang, China between September 2019 and July 2023. The methods and protocols were implemented in accordance with the principles of the Declaration of Helsinki for research involving human subjects. The study was approved by the Institutional Ethics Committee of China Medical University and all the participants were provided written informed consent (no. 2012-02).
Inclusion/exclusion criteria
The eligibility criteria included [20]: (i) over 18 years old; (ii) systemically healthy; (iii) at least 20 natural teeth remained (excluding the third molar); and (iv) the diagnosis of periodontitis according to the current classification [4]. In order to mitigate potential confounding variables, participants were excluded based on the following criteria: (i) the presence of advanced cerebrovascular disease; (ii) the utilization of systemic anticoagulation or antiplatelet agents; (iii) pregnancy; (iv) breastfeeding; (v) the existence of malignant diseases; and (vi) previous periodontal therapy or periodontal surgery < 6months before enrollment into the study [21, 22].
Study outcomes
The primary outcome of this study was sites with 1 mm ≤ CAL ≤ 2 mm, 3 mm ≤ CAL ≤ 4 mm, and CAL ≥ 5 mm in anterior teeth, maxillary posterior teeth and mandibular posterior teeth, respectively. The sample size was determined using a calculation statistical software (Power Analysis and Sample Size, Version 11, Kaysville, Utah, USA) with a two-sided significance level of 0.05, a power of 0.8 (1-β), and 3020 teeth was considered necessary.
Data collection
Demographic assessment
In this study, all the participants were interviewed to obtain demographic information, followed by a comprehensive periodontal examination. The demographic information included socio-demographics (age, gender) and behavior (dental brushing behavior, tobacco and alcohol consumption). Smoking status of the patients were categorized as non-smokers (patients who never smoked), former smokers (patients who quitted smoking 15 years ago or more) [23], and current smokers (patients who reported smoking for 1 year or more) [24]. Similarly, never alcohol consumption and current alcohol consumption (including occasional drinking and regular drinking) were evaluated by considering the amount consumed or the frequency per day [1].
Periodontal examination
We categorized periodontal disease in alignment with the criteria specified in the 2017 WWP [5]. All the enrolled teeth underwent a thorough examination, which entailed segmenting them into three distinct regions: anterior teeth, maxillary posterior teeth, and mandibular posterior teeth. This assessment incorporated both clinical periodontal parameters and radiographic data. To ensure accuracy and consistency, clinical periodontal parameters were measured by two seasoned examiners at six designated sites (mesio-buccal, mesio-lingual, disto-buccal, disto-lingual, mid-buccal and mid-lingual) for each tooth across four quadrants (excluding the third molars) using an automated disk probe (FP32, Florida Probe, Gainesville, FL, USA). These parameters included CAL, PD, plaque index (PLI) (scored from 0 to 3) and gingival index (GI) (scored from 0 to 3) [25]. Furthermore, based on the CAL values, the tooth sites underwent further stratification into three distinct groups: 1 mm ≤ CAL ≤ 2 mm group; 3 mm ≤ CAL ≤ 4 mm group; CAL ≥ 5 mm group [18].
Imaging diagnosis by CBCT
Cone-beam computed tomography (CBCT) images of the maxillae and mandibles were obtained using NEWTOM VG CBCT (QR-NIM s.r.l.; Verona, Italy) with the following protocol: voxel size 160 μm, acquisition time 26.9 s, tube voltage 110 kV, filament current 5 mA, and field of view 20 × 25 cm. CBCT scans were performed with an NNT unit, and all original CBCT data were introduced into NNT software (QR-NIM s.r.l.; Verona, Italy) for further assessments. The following measurements were performed on CBCT images.
Alveolar bone defect (ABD): Measurement was established as the distance between the CEJ and the alveolar bone crest. The levels of ABD of central incisor, the first premolar and the first molar were measured in the interproximal area in millimeters. The maximal percentage of bone loss, which was used to describe the severity of alveolar bone loss, was calculated as percentage of bone loss=(d1–2 mm)/(d2–2 mm) × 100% [26, 27] (shown in Fig. 1A).
Root concavities: The root concavities were measured and divided into five types according to Ong’s classification [28]. Type I represented without concavity; type II represented root concavities from enamel position to start; type III represented concavities that had originated at the cemento-enamel junction; type IV represented concavities had originated below the cemento-enamel junction but above the one-third part of the root; and type V represented concavities initiated at the middle and apical parts of the root (shown in Fig. 1B).
Fig. 1.
The detailed measurements were performed on CBCT images. A Definition of alveolar bone absorbing height of molar measurements. B The different types of root concavity: (a) First premolar with no concavity on the root (type I); (b) The narrow concavity on first premolar starting at the enamel (type II); (c) The narrow concavity on first premolar starting at the cementoenamel junction (type III); (d) The wide concavity on first premolar starting at the cervical third first premolar (type IV); (e) The first premolar with a narrow concavity starting at the apical third (type V)
The clinical periodontal parameters and CBCT analysis were evaluated by two experienced clinicians. Calibration training was performed on continuous days. The recording of clinical examinations was calibrated after the intraclass and interclass kappa (κ) values were 0.85.
Statistical analysis
Continuous numerical variables were described using the mean and standard deviation statistical description, while level variables and classification variables were described using statistical description of n (%). To determine the factors associated with the severity of CAL in the three regions, a multilevel Poisson regression analysis was conducted, incorporating associations from both the individual and teeth sites levels. The odds ratio and 95% confidence interval were estimated. Variability values at individual level and teeth sites level were presented in the model as random coefficients.
All statistical analysis was performed using the SPSS software program (version 20.0; SPSS, Chicago, IL, USA).
Results
Descriptive epidemiological characteristics of patients with periodontitis
In this study, a total of 23,628 sites of 3938 teeth (1689 anterior teeth, 1130 premolars and 1119 molars) from 142 patients who met the inclusion criteria were registered. (shown in Supplementary Fig. 1). The epidemiological characteristics of the included patients and sites were summarized in Table 1. The mean age of the patients included was 52.40 ± 9.77 years. Among the included individuals, a similar frequency of males (42.96%) and females (57.04%) was observed. Approximately nearly 75% patients had never smoked. People who did not drink alcohol accounted for 78.87% of the sample. Within the enrolled sites, 61.26% sites presented with 1 mm ≤ CAL ≤ 2 mm, 30.93% sites with 3 mm ≤ CAL ≤ 4 mm, whereas 7.82% sites with CAL ≥ 5 mm. In anterior teeth, the proportion of subjects with different levels of ABD is 45.07%, 33.80% and 21.13%. In premolars, the proportion is 84.51%, 9.86% and 5.63%. And the proportion in molars is 29.58%, 41.55% and 28.87%.
Table 1.
Demographic characters of patients with periodontitis
| Variables | N (%) |
|---|---|
| Gender | |
| Male | 61 (42.96%) |
| Female | 81 (57.04%) |
| Age | 52.40 ± 9.77 |
| Cigarette smoking | |
| Current | 21 (14.79%) |
| Former | 15 (10.56%) |
| Never | 106 (74.65%) |
| Alcohol drinking | |
| Current | 30 (21.12%) |
| Never | 112 (78.87%) |
| Number of interior teeth | 1689 (42.89%) |
| Number of premolars | 1130 (28.69%) |
| Number of molars | 1119 (28.42%) |
| Number of sites with | |
| 1 mm ≤ CAL ≤ 2 mm | 14,474 (61.26%) |
| 3 mm ≤ CAL ≤ 4 mm | 7307 (30.93%) |
| CAL ≥ 5 mm | 1847 (7.82%) |
| Subjects with levels of ABD in anterior teeth | |
| 1 | 64 (45.07%) |
| 2 | 48 (33.80%) |
| 3 | 30 (21.13%) |
| Subjects with levels of ABD in premolars | |
| 1 | 120 (84.51%) |
| 2 | 14 (9.86%) |
| 3 | 8 (5.63%) |
| Subjects with levels of ABD in molars | |
| 1 | 42 (29.58%) |
| 2 | 59 (41.55%) |
| 3 | 41 (28.87%) |
Multilevel regression analysis
In order to investigate the influence of various factors on CAL in the anterior teeth, maxillary posterior teeth and mandibular posterior teeth, we categorized the enrolled tooth sites into three groups according to the CAL values: 1 mm ≤ CAL ≤ 2 mm group, 3 mm ≤ CAL ≤ 4 mm group, and CAL ≥ 5 mm group, and multilevel regression analysis was used to assess the risk factors associated with different degrees of CAL in each of these three regions.
The results of Multilevel Regression analysis conducted for varying degrees of CAL in anterior teeth were shown in Table 2. Notably, PLI (1.63 (95% CI [1.44–1.86]), p < 0.01), PD (1.18 (95% CI [1.01–1.08], p < 0.05), and ABD (1.27 (95% CI [1.09–1.21]), p < 0.05) showed a significant correlation with the 1 mm ≤ CAL ≤ 2 mm group. For 3 mm ≤ CAL ≤ 4 mm group, current drinking (0.80 (95% CI [0.64–0.99]), p < 0.05), PD values (1.19 (95% CI [1.02–1.38]), p < 0.05), current smoking (1.56 (95% CI [0.76–1.40]), p < 0.05) and ABD (1.33 (95% CI [1.10–1.62]), p < 0.01) were significant. In the CAL > 5 mm group, current smoking (2.21 (95% CI [1.27–3.83]), p < 0.01) and current drinking (0.65 (95% CI [0.44–0.98]), p < 0.05), and had higher PD values (1.56 (95% CI [1.08–2.28]), p < 0.05) and ABD (4.09 (95% CI [2.47–6.95]), p < 0.01) remained significant.
Table 2.
Multilevel Poisson rogression analysis in anterior teeth
| Variable | 1 mm ≤ CAL ≤ 2 mm | 3 mm ≤ CAL ≤ 4 mm | CAL ≥ 5 mm | ||||
|---|---|---|---|---|---|---|---|
| OR (95%CI) | p-value | OR (95%CI) | p-value | OR (95%CI) | p-value | ||
| Level 1- individual | |||||||
| Age | |||||||
| Gender | |||||||
| Male | 1 | 1 | 1 | ||||
| Female | 1.065 (0.91–1.25) | 0.43 | 1.04 (0.82–1.32) | 0.74 | 0.83 (0.80–1.38) | 0.46 | |
| Smoking | |||||||
| Never | 1 | 1 | 1 | ||||
| Current | 0.95 (0.76–1.18) | 0.64 | 1.56 (0.76–1.40) | 0.01* | 2.21 (1.27–3.83) | 0.00# | |
| Past | 0.94 (0.77–1.16) | 0.57 | 1.05 (0.79–1.39) | 0.75 | 1.56 (0.90–2.64) | 0.11 | |
| Alcohol consumption | |||||||
| Never | 1 | 1 | 1 | ||||
| Current | 0.88 (0.75–1.03) | 0.11 | 0.80 (0.64–0.99) | 0.04* | 0.65 (0.44–0.98) | 0.04* | |
| Level 2 - tooth site | |||||||
| PD | 1.18 (1.01–1.08) | 0.02* | 1.19 (1.02–1.38) | 0.02* | 1.56 (1.08–2.28) | 0.02* | |
| GBI | 0.97 (0.88–1.07) | 0.52 | 0.92 (0.80–1.06) | 0.26 | 1.00 (0.76–1.34) | 1.00 | |
| PLI | 1.63 (1.44–1.86) | 0.00# | 1.21 (0.98–1.48) | 0.07 | 0.76 (0.48–1.23) | 0.25 | |
| ABD | 1.27 (1.09–1.21) | 0.01* | 1.33 (1.10–1.62) | 0.00# | 4.09 (2.47–6.95) | 0.00# | |
| Root concavities | 1.10 (1.03–1.18) | 0.00 | 1.09 (0.99–1.21) | 0.08 | 0.89 (0.71–1.12.71.12) | 0.32 | |
* P < 0.05; # P < 0.01
Table 3 presented the results of maxillary posterior teeth. ABD in premolars (0.87 (95% CI [0.78–0.98]), p < 0.05) and molars (1.50 (95% CI [1.30–1.73]), p < 0.01), and root concavities (1.36 (95% CI [1.26–1.46]), p < 0.01) were significant in the 1 mm ≤ CAL ≤ 2 mm group. For 3 mm ≤ CAL ≤ 4 mm group, current drinking (0.76 (95% CI [0.59–0.97]), p < 0.05), as well as PD (1.24 (95% CI [1.04–1.48]), p < 0.05), ABD in premolars (0.77 (95% CI [[0.66–0.90]), p < 0.01) and molars (1.74 (95% CI [1.40–2.17]), p < 0.01), and root concavities (1.48 (95% CI [1.32–2.66]), p < 0.01) were significant. In the CAL > 5 mm group, PLI (2.03 (95% CI [1.06–2.40]), p < 0.05), ABD in premolar (1.46 (95% CI [1.03–2.06]), p < 0.05) and molar (2.72 (95% CI [1.52–5.13]), p < 0.01), and root concavities (1.17 (95% CI [1.05–1.61]), p < 0.05) showed significantly correlations.
Table 3.
Multilevel Poisson progression analysis in maxillary posterior teeth
| Variable | 1 mm ≤ CAL ≤ 2 mm | 3 mm ≤ CAL ≤ 4 mm | CAL ≥ 5 mm | |||
|---|---|---|---|---|---|---|
| OR (95%CI) | p-value | OR (95%CI) | p-value | OR (95%CI) | p-value | |
| Level 1- individual | ||||||
| Age | ||||||
| Gender | ||||||
| Male | 1 | 1 | 1 | |||
| Female | 1.12 (0.94–1.35) | 0.22 | 1.78 (0.90–1.55) | 0.23 | 1.05 (0.53–2.15) | 0.88 |
| Smoking | ||||||
| Never | 1 | 1 | 1 | |||
| Current | 0.88 (0.68–1.14) | 0.34 | 0.96 (0.66–1.37) | 0.82 | 1.44 (0.67–3.02) | 0.34 |
| Past | 0.97 (0.77–1.22) | 0.81 | 1.06 (0.77–1.45) | 0.74 | 1.00 (0.47–2.09) | 0.99 |
| Alcohol consumption | ||||||
| Current | 1 | 1 | 1 | |||
| Never | 0.87 (0.73–1.04) | 0.12 | 0.76 (0.59–0.97) | 0.03* | 0.59 (0.34–1.03) | 0.06 |
| Level 2 - tooth site | ||||||
| PD | 1.01 (0.90–1.13) | 0.84 | 1.24 (1.04–1.48) | 0.02* | 1.28 (0.80–2.09) | 0.31 |
| GBI | 1.10 (0.99–1.23) | 0.08 | 0.99 (0.85–1.16) | 0.93 | 0.85 (0.61–1.22) | 0.85 |
| PLI | 1.12 (0.97–1.29) | 0.11 | 1.00 (0.81–1.25) | 0.99 | 2.03 (1.06–4.20) | 0.04* |
| ABD in premolar | 0.87 (0.78–0.98) | 0.02* | 0.77 (0.66–0.90) | 0.00# | 1.46 (1.03–2.06) | 0.03* |
| ABD in molar | 1.50 (1.30–1.73) | 0.00# | 1.74 (1.40–2.17) | 0.00# | 2.72 (1.52–5.13) | 0.00# |
| Root concavities | 1.36 (1.26–1.46) | 0.00# | 1.48 (1.32–1.66) | 0.00# | 1.17 (1.05–1.61) | 0.04* |
* P < 0.05; # P < 0.01
Table 4 showed the results of mandibular posterior teeth. ABD in premolars (0.89 (95% CI [0.79–1.01]), p < 0.05) and molars (1.58 (95% CI [1.35–1.85]), p < 0.01) were significant in the 1 mm ≤ CAL ≤ 2 mm group. For 3 mm ≤ CAL ≤ 4 mm group, current drinking (0.71 (95% CI [0.56–0.91]), p < 0.01), as well as PD (1.34 (95% CI [1.13–1.59]), p < 0.01), PLI (0.78 (95% CI [0.63–0.98]), p < 0.05), and ABD in premolar (0.87 (95% CI [0.74–1.02]), p < 0.05) and molar (2.16 (95% CI [1.71–2.72]), p < 0.01) were significant. In the CAL > 5 mm group, ABD in premolar (1.51 (95% CI [1.12–2.04]), p < 0.01) and molar (1.92 (95% CI [1.10–3.57]), p < 0.05) remained significant.
Table 4.
Multilevel poison progression analysis in mandibular posterior teeth
| Variable | 1 mm ≤ CAL ≤ 2 mm | 3 mm ≤ CAL ≤ 4 mm | CAL ≥ 5 mm | |||
|---|---|---|---|---|---|---|
| OR (95%CI) | p-value | OR (95%CI) | p-value | OR (95%CI) | p-value | |
| Level 1- individual | ||||||
| Age | ||||||
| Gender | ||||||
| Male | 1 | 1 | 1 | |||
| Female | 0.84 (0.69–1.02) | 0.07 | 0.92 (0.71–1.20) | 0.53 | 0.59 (0.31–1.12) | 0.11 |
| Smoking | ||||||
| Never | 1 | 1 | 1 | |||
| Current | 1.05 (0.80–1.37) | 0.75 | 1.56 (1.12–2.17) | 0.11 | 1.72 (0.84–3.46) | 0.13 |
| Past | 1.16 (0.91–1.48) | 0.23 | 1.34 (0.97–1.84) | 0.07 | 1.76 (0.94–3.26) | 0.07 |
| Alcohol consumption | ||||||
| Current | 1 | 1 | 1 | |||
| Never | 0.88 (0.73–1.07) | 0.19 | 0.71 (0.56–0.91) | 0.01# | 0.79 (0.47–1.33) | 0.38 |
| Level 2 - tooth site | ||||||
| PD | 1.01 (0.89–1.15) | 0.84 | 1.34 (1.13–1.59) | 0.00# | 1.01 (0.64–1.62) | 0.95 |
| GBI | 0.95 (0.84–1.07) | 0.40 | 0.78 (0.94–1.33) | 0.22 | 1.19 (0.83–1.77) | 0.36 |
| PLI | 1.00 (0.86–1.16) | 1.00 | 0.78 (0.63–0.98) | 0.04* | 0.82 (0.45–1.53) | 0.53 |
| ABD in premolar | 0.89 (0.79–1.01) | 0.03* | 0.87 (0.74–1.02) | 0.04* | 1.51 (1.12–2.04) | 0.00# |
| ABD in molar | 1.58 (1.35–1.85) | 0.00# | 2.16 (1.71–2.72) | 0.00# | 1.92 (1.10–3.57) | 0.03* |
| Root concavities | 1.07 (0.99–1.17) | 0.09 | 1.04 (0.93–1.67) | 0.47 | 1.18 (0.88–1.59) | 0.29 |
* P < 0.05; # P < 0.01
Discussion
Periodontitis is a multifactorial infectious disease which is characterized by progressive loss of attachment and destruction of alveolar bone due to inflammatory process [29]. The risk factors of periodontitis include environmental, acquired and genetic conditions, which can alter the manifestation of the disease and influence its onset or progression [5]. However, the influence of periodontal-related parameters on the severity of CAL in different dental regions was still unclear. In this study, we used multilevel regression to evaluate the risk factors for the severity of CAL in the anterior teeth, maxillary posterior teeth and mandibular posterior teeth. We found that as the CAL values increased, current smoking, drinking, PD and ABD showed significant correlation in anterior teeth. In maxillary posterior teeth, root-concavities and ABD in both premolars and molars were significantly correlated with CAL of different severity, and drinking and PD, PLI was significantly correlated with 3 mm ≤ CAL ≤ 4 mm sites and CAL ≥ 5 mm sites respectively. In mandibular posterior teeth, ABD in both premolars and molars was significantly correlated with CAL of different severity, drinking and PD were significantly correlated with 3 mm ≤ CAL ≤ 4 mm sites (shown in Fig. 2).
Fig. 2.
The risk factors of anterior teeth, maxillary posterior teeth and mandibular posterior teeth
Our results clearly indicated that current smoking primarily affected the CAL of interior teeth in comparison to other regions. Previous studies have suggested a localized effect of smoking on maxillary teeth, particularly in the anterior region [30–32], and had strong interactive effect on alcohol consumption [33]. And smokers tended to exhibit greater prevalence of deeper periodontal pockets and greater mean periodontal probing depth [34]. The underlying reasons were that the smoke initially contacted with the anterior teeth, and nicotine in cigarette could potentially impair immune modulators, increase cytokine production leading to increased collagen destruction and bone resorption, and inhibit gingival fibroblast growth, collagen production [35–37] and fibronectin of the gingival extracellular matrix [36]. This could possibly explain the reason that the drinking and PD showed the significant correlation as CAL values increased in anterior teeth in our results.
Root concavities is a distinctive feature of the root surface [38], and is thought to promote the accumulation of plaque and to accelerate the onset of periodontitis [39]. We also found a notable correlation between the severity of CAL in maxillary posterior teeth and the presence of root concavities. However, this correlation was not observed in other regions. This difference could potentially be attributed to the frequency of root concavities occurring in conjunction with the anatomical characteristics of the root surface. Zhao et al. [38] found that the occurrence of root concavities was notably higher in maxillary first premolars compared to those in the mandibular region. Furthermore, these concavities usually presented as a deeper-V-shaped morphology in maxillary premolars [40], leading to plaque accumulation and posing challenges in its removal. These observations could potentially elucidate our research outcomes.
ABD provides a good estimate of the overall attachment loss of the supporting structures [41]. The most frequent radiographs to identify the defect in alveolar bone included periapical, bitewing and panoramic radiographs [42], which failed to assess the thickness, absorbing height and position of alveolar bone as 2-dimensional radiographic images [43]. To avoid these disadvantages, we used CBCT which provided highly detailed 2-dimensional to measure the ABD more accurately. Our findings revealed a significant association between ABD in both premolars and molars with the severity of CAL. This outcome aligns with previous studies that utilized CAL and radiographically evaluated alveolar bone height as indicators of periodontal tissue support loss in periodontitis, demonstrating a correlation between the two [4, 6, 44].
It is noteworthy that a significantly higher number of risk factors were found to be correlated with 3 mm ≤ CAL ≤ 4 mm sites, compared to CAL ≥ 5 mm sites which were considered more serious. Based on this observation, we hypothesized that systemic factors might have a more pronounced impact than other factors in patients with severe periodontitis. While we excluded patients with systemic diseases, it remained a possibility that certain patients might have concealed their medical history. Furthermore, there existed several contributing factors, such as education level, socioeconomic status, occlusion, pulp status and oral habit, that could potentially influence the severity of periodontitis; however, these were not included in our study. Hence, there are several limitations should be considered in this study, and it is imperative to evaluate a broader range of indicators in subsequent research.
Conclusion
The results of this retrospective observational study indicated that the risk factors could differ depending on the specific dental region and the severity of periodontitis present. In anterior teeth, the risk factors were predominantly associated with behavior, whereas those in posterior teeth were primarily associated to anatomical factors. Therefore, dentists should pay more attention to patients presenting these aforementioned factors, which can enhance the precision of periodontal diagnosis, improve risk prediction models, and ultimately guide the development of more personalized and effective treatment and maintenance protocols for patients with periodontitis.
Supplementary Information
Acknowledgements
Not applicable.
Authors’ contributions
All authors have made substantial contribution to conception and design of the study. Xue Yang has been involved in data interpretation and drafting the manuscript. Dongmei Zhang has been involved in revising the work. Shuo Liu and Yaping Pan have been involved in revising the work critically and have given the final approval of the version to be published.
Funding
This study was supported by the Natural Foundation of Liaoning Province (grant number 20180550403 to Shuo Liu). The authors report no conflicts of interest related to this study.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
All of the patients had provided written informed consent prior to treatment, and the study protocol was approved by the ethics committee of China Medical University. The Clinical trial number: not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Yaping Pan, Email: yppan@cmu.edu.cn.
Shuo Liu, Email: lexie0925@163.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.