Bruxism assessment combining fractal analysis, clinical evaluation, and self-reports: a case-control study

Abstract

Objective

The aim of this study was to investigate the effects of bruxism using a combined method of fractal bone analysis, clinical testing, and patient-reported outcomes.

Methods

Thirty-five bruxism patients and 35 controls underwent: (I) Validated questionnaires assessing both sleep and awake bruxism, (II) Clinical examinations including: tooth wear, masticatory muscle pain on palpation (masseter, temporal, and lateral pterygoid muscles), soft tissue impressions (buccal/lingual), percussion and cold test sensitivity, and periodontal parameters (pocket depth, gingival and plaque indexes), (III) Radiographic analyses: panoramic radiographs for structural evaluation and fractal dimension analysis of mandibular first molars using ImageJ software, focusing on periapical mesial/distal regions, interdental areas, and alveolar crest on periapical radiographs. Statistical analyses included independent t-tests and Mann-Whitney U tests (α = 0.05).

Results

The bruxism group showed significantly higher female prevalence (p < 0.05), lower education (p < 0.05), and more systemic diseases (p < 0.05). Patients reported greater awareness of grinding/clenching (p < 0.001), with 60% experiencing temporal pain, 65.7% morning headaches, and 77.1% morning fatigue. Clinical findings included higher tooth wear (p < 0.001), buccal/lingual impressions (p < 0.001), masseter hypertrophy (p < 0.001), percussion sensitivity (p < 0.001) and cold sensitivity (p < 0.001). Muscle palpation revealed pain in masseter (91.4%), temporal (54.3%), and lateral pterygoid (57.1%) muscles (all p < 0.001 vs. controls). Radiographically, bruxism patients exhibited more periodontal ligament widening, bone loss, and lamina dura changes (all p < 0.001). Periodontal analysis showed deeper pockets (p < 0.05) and higher gingival indices (p < 0.05), but lower plaque indices (p < 0.05). Fractal analysis demonstrated increased fractal dimension value in interdental areas (p < 0.05) but no differences in other regions (p > 0.05).

Conclusion

Bruxism correlates with distinct trabecular bone changes detectable via fractal analysis, alongside characteristic clinical and self-reported markers.

Introduction

Bruxism is a condition characterized by the rhythmic or non-rhythmic activity of the masticatory muscles during sleep or wakefulness, leading to teeth clenching/grinding and jaw muscle contractions [1]. In adults, sleep bruxism is observed in approximately 10% of the population, while awake bruxism is reported in around 30%, with a higher prevalence noted among women [2, 3]. It is estimated that one in four individuals is affected by bruxism, highlighting its widespread nature [4]. Diagnostic approaches for bruxism include self-assessment, clinical examination, and polysomnography. This condition can result in various symptoms such as dental wear, cervical dentin hypersensitivity, tooth sensitivity, restoration fractures, muscle pain, temporomandibular joint (TMJ) pain, and TMJ sounds [5]. In severe cases, bruxism can cause significant damage to teeth and dental restorations, leading to morning jaw pain, temporal headaches, and TMJ dysfunction. Furthermore, bruxism is recognized as a risk factor for several clinical outcomes [3, 6].

The etiological factors of bruxism include alcohol, smoking, caffeine, various substances, and medications [5, 7, 8]. Associated factors encompass poor nutrition, sleep disorders (apnea, snoring) [9, 10], lifestyle, stress [11, 12], anxiety [10, 13], depression, and genetic predisposition [5]. The etiology of bruxism can be categorized into biological, extrinsic, and psychosocial factors. Symptoms associated with bruxism are complex and varied, necessitating a multifaceted and multidisciplinary approach to treatment. Therapeutic interventions may include pharmacological treatments, intraoral appliances, physical therapy, and dental or psychosocial therapies [14, 15].

Typically, a clinical method combining patient self-reports, clinical testing, and information from sleep partners is used to diagnose bruxism [1]. While these reports offer insights into the frequency of the activity, they do not provide detailed information about its intensity or duration. Approximately 50% of individuals who grind their teeth during sleep, report daytime symptoms such as facial muscle discomfort [16]. Polysomnography is typically utilized when comorbid sleep disorders are suspected. While EMG recordings can aid in diagnosing both awake and sleep bruxism, their reliability is limited when used in isolation. Rhythmic masticatory muscle activity represents the most frequently observed EMG pattern in sleep bruxism. To diagnose sleep bruxism, recurrent jaw muscle activity, such as teeth grinding or clenching during sleep, must be present alongside at least one additional symptom, such as abnormal tooth wear, transient morning jaw muscle pain or fatigue, or temporal headaches [17]. For awake bruxism, a practical evaluation that captures personal observations of muscle activity can serve as supplementary evidence [1].

The diagnosis of bruxism is categorized into “possible bruxism,” “probable bruxism,” and “definite bruxism.” A definitive diagnosis of bruxism is achieved by combining self-reported data (questionnaires, anamnesis records), findings from clinical examinations (dentist evaluations), and polysomnographic recordings (instrumental and technological assessments) [18]. In recent years, the STAB (Standardized Tool for the Assessment of Bruxism) system, which integrates medical history, clinical examination, and supplementary diagnostic data, has emerged as a crucial tool for the accurate diagnosis and management of bruxism [19, 20]. Bruxism is not categorized as a disease or disorder but is acknowledged as multifactorial motor behavior [1].

The necessity of treating bruxism is determined by its adverse effects on oral structures and its association with neurological and sleep-related conditions, such as tooth sensitivity and fractures, restoration failures, muscle tenderness, temporomandibular joint (TMJ) pain and dysfunction, and headaches [21, 22]. Treatment aims to prevent dental damage and alleviate associated symptoms. Bruxism can be considered harmless behavior, a risk factor linked to certain health issues (e.g., tooth wear, TMJ disorders), or a protective factor associated with conditions like obstructive sleep apnea, gastroesophageal reflux, and dry mouth [1, 23–25]. While debates continue regarding whether bruxism is a behavioral trait or a pathological condition, some authors have reported that such motor activities may lead to damage in hard and soft tissues [26–28].

The mechanical and biochemical interaction between bone and muscle may lead to bone remodeling in patients with bruxism. Excessive loading not only induces bone remodeling but also influences muscle mass through the release of factors regulating muscle development [29]. Studies focusing on bone changes in bruxism patients have demonstrated significant alterations in trabecular bone structure [27, 30]. A recent study utilizing fractal dimension analysis on panoramic radiographs identified differences in trabecular structure in the condylar region, concluding that mechanical stress may cause morphological changes in the condyle [31].

The definition, prevalence, and effects of bruxism vary significantly due to differences in diagnostic criteria and assessment methods across studies. Concerns have been raised regarding the generalizability of findings based on self-reporting methods [32]. This study employed a combination of questionnaires, clinical examinations, and radiographic assessments to diagnose bruxism. The primary objective was to explore the effects of bruxism on dental, pulpal, and periodontal tissues, as well as its association with dentin hypersensitivity. Additionally, the study aimed to evaluate the impact of bruxism on trabecular bone structure through fractal analysis conducted on periapical radiographs. The null hypothesis proposed that no significant differences exist in dental, periodontal, or radiographic parameters between individuals with bruxism and those without the condition.

Materials and methods

The ethical approval was taken from the Clinical Researchs Ethical Committee of Faculty of Medicine of Ankara Yildirim Beyazit University (#26379996/15, Decision date and number: 22.06.2022-11). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The participant consent was obtained from the patients for this study. Sample numbers were determined as a result of the power analysis performed with the G-Power program (effect size = 0.80, ɑ= 0.05 power = 0.95). Thirty-five individuals with bruxism and 35 individuals without bruxism were included in the study. Every patient was assigned a number for identification, which was also used for radiography. The patients included in the study were recorded for information on age, gender, marital status, education level, systemic disease, and smoking.

Patients who had received periodontal treatment within the last six months used analgesics/ dental anesthesia within the last 24 h were excluded from the study. It was ensured that the included patients had at least 24 teeth and had no missing teeth that would disrupt the closure in the posterior occlusion. Patients with significant systemic diseases affecting periodontal tissues, individuals under the age of 18 and pregnant women were also excluded from the study. The interview was recorded with the help of a proforma prepared for the collection of data and an intraoral examination was performed. To avoid inter-observer bias, the periodontal examination of the patients was performed by a single, well-calibrated periodontologist (M.A.T.), and the cold test and air test were performed by an endodontist (E.S.).

Bruxism Diagnosis-Inclusion end extrusion criterias

Bruxism was diagnosed using a dual-method approach, aligning with the 2018 International Consensus on Bruxism [1] and the Standardized Tool for the Assessment of Bruxism (STAB) [19]. The diagnosis required a 5-item questionnaire (Bruxism Questionnaire-1) [33] and a 7-item tool assessing sleep clenching (Bruxism Questionnaire-2) [34]. A single “yes” response to the questions indicated probable bruxism.

To minimize confounding factors, individuals having the following criterias were excluded:

• Recent (< 6 months) periodontal therapy.

• Use of analgesics/anesthesia within 24 h.

• Systemic diseases affecting periodontal health (e.g., uncontrolled diabetes).

• Pregnancy or age < 18 years.

The diagnosis of bruxism was established using the questions outlined in Table 1, which were integrated into the patient’s medical history. The diagnostic process adhered to the criteria set by the American Academy of Sleep Medicine, encompassing two primary approaches: (I) question-and-answer [33, 34] and (II) clinical examination [35]. The questions posed to patients and the non-invasive diagnostic methods employed were documented in the anamnesis form. The first questionnaire [33], comprises five items to be answered with ‘yes,’ ‘no,’ or ‘don’t know’ (Bruxism Questionnaire-1). According to Paesani et al., a ‘yes’ response to any of the items indicates the presence of bruxism. The second questionnaire, designed by Raphael et al. [34], is a seven-item tool aimed at evaluating sleep clenching (Bruxism Questionnaire-2). Raphael et al. suggest that bruxism is present if any of the items receive a ‘yes’ response. In this study, self-reported bruxism was categorized as ‘yes’ or ‘no’ based on consistent results from both questionnaires [35].

Table 1.

Comparison of sociodemographic features between the groups (Chi-square and t tests)

		Groups				p
		Control		Bruxism
		n	%	n	%
Gender	Female	19	54.3	28	80.0	0.042*
	Male	16	45.7	7	20.0
Marital status	Married	24	68.6	23	65.7	0.999
	Single	11	31.4	12	34.3
Educational status	Primary school and Secondary school	2	5.7	9	25.7	0.046*
	High school	17	48.6	11	31.4
	University and doctorate	16	45.7	15	42.9
Systemic diseases	No	31	88.6	19	54.3	0.004*
	Yes	4	11.4	16	45.7
Smoking	No	27	77.1	27	77.1	0.999
	Yes	8	22.9	8	22.9
		Min-Max(M)	Mean ± SD	Min-Max(M)	Mean ± SD
Aget		18–60 (35)	33.69 ± 10.4	15–64 (36)	37.2 ± 13.01	0.216

SD: Standard deviation, Min: minimum, Max: Maximum. Different letters mean statistically significant difference between the groups

A 4-item questionnaire was conducted under the title of ‘Patient’s Complaints Questionnaire’. The answers to the questions were recorded as ‘yes’ or ‘no’ in both groups.

Clinical examination

The presence or absence of the following four criteria for the clinical diagnosis of bruxism in the subjects included in the study was evaluated as ‘yes’ or ‘no’: (I) Abnormal tooth wear, (II) Tooth impressions on the buccal area, (III) Tooth impressions on the tongue, (IV) Masseter muscle hypertrophy. A “yes” response to one of these four questions was regarded as indicating the presence of clinical bruxism [35]. One question for pain of the muscles on palpation (masseter, temporal and lateral pterygoid muscles) was also included [36].

In the present study, the teeth numbered 16, 21, 24, 36, 41, and 44 were evaluated. Teeth that had experienced acute trauma, exhibited cracks, caries, or had undergone root canal treatment were excluded from the study. The teeth were then subjected to cold spray test for evaluating dentin sensitivity. The teeth were evaluated in terms of percussion sensitivity, sensitivity to probing in the cervical area and tooth wear. Following this, a periodontal examination was performed.

Cold spray application

It was ensured that the air and cold tests applied to the same tooth were at least 5 min apart. After the relevant teeth were isolated with cotton pellets and dried with the help of air spray, cold spray (Roeko Endo Frost; Coltene Group, Altstatten, Switzerland) was applied to the relevant tooth surface [37].

The pain felt by the patient after cold spray application was measured using the Heft-Parker visual analogue scale (VAS) with a 170 mm straight line scale [38]. The scale was divided into 4 categories: no pain (0 mm), mild pain (0.1–54 mm), moderate pain (54.1–113.9 mm) and severe pain (114 mm).

Evaluation of tooth wear

The occlusal/incisal, palatal/lingual, buccal/labial and cervical surfaces of teeth 16, 21, 24, 36, 41, 44 of the patients were scored between 0 and 4 according to the index proposed by Smith and Knight [39]:

0- No wear.

1. Wear at enamel level, minimal contour reduction in cervical areas.

2. Loss of enamel, abrasion of more than 1/3 of buccal, lingual and occlusal dentin; loss of enamel only on the incisal surface where dentin is exposed, loss up to 1 mm on the cervical.

3. Loss of enamel, extensive loss of buccal, lingual and occlusal dentin; loss of enamel and dentin on the incisal surface; 1–2 mm loss on the cervical surface.

4. Pulp or secondary dentin exposure; cervical loss more than 2 mm.

Periodontal examination

• (I)Silness and Loe Plaque Index was scored in the range of 0–3 [40].
• (II)Supragingival/subgingival calculus detection was scored with a simplified calculus index of 0–3 [40].
• (III)The severity of gingival inflammation was assessed using the Loe and Silness gingival index [40].
• (IV)The presence and amount of gingival recession, periodontal pocket depth and clinical attachment loss were measured separately for 6 surfaces around the teeth (mesiobuccal, mid-buccal, distobuccal, distobuccal, mid-lingual, mesiolingual) with a periodontal probe and recorded as mm [41].
• (V)Tooth mobility was recorded using Miller’s mobility index between 0 and 3 [42].
• (VI)bleeding on probing was recorded as present/absent [43].

To evaluate measurement consistency, intra-observer reliability testing was conducted prior to the main study. A calibration exercise was performed where the same examiner assessed seven periodontal parameters (probing depth, gingival recession, clinical attachment loss, bleeding on probing, gingival index, plaque index, and calculus index) in 10 patients who were not included in the main study cohort. Each parameter was measured twice with a 1-hour interval between examinations to minimize recall bias while ensuring clinical conditions remained stable.

The clinical (e.g., fractal analysis, tooth wear scoring, muscle palpation) and radiographic parameters were evaluated through a consensus-based methodology. Two calibrated examiners independently reviewed all ambiguous cases and jointly determined the final scores to minimize subjectivity.

Radiographic evaluation

Radiographic examinations were evaluated if the patients had existing periapical or panoramic films, otherwise standard periapical radiographs of the relevant teeth were taken only in suspicious cases. Periodontal ligament space widening [44], thickening of the lamina dura [45], presence of periapical pathology, interdental triangulation [46] and radiographic bone loss [47], if any, were recorded on these films.

Fractal analysis

The fractal analysis was performed on the periapical radiographs of teeth number 36 of all individuals using a predetermined method [48] by using a software program (ImageJ v1.48 for Windows; National Institute of Health, Bethesda, MD, USA). Periapical radiographs were taken by using a paralleling technique with intraoral phosphor sensor plates (Durr Dental, Bietigheim-Bissingen, Germany) and a dental X-ray unit (Castellini, Bologna, Italy). Exposure parameters were 70kVp, 7 mA, 400 ms. All periapical radiographs in the JPEG format were converted to tagged image file format (TIFF). The sizes of the images were 1044 × 806 pixels. The analysis was performed between the periapical of teeth numbered 35–36 and the region closest to the alveolar crest, the mesial and distal periapical of tooth number 36 and the bifurcation region (Fig. 1).

Fig. 1.

ROI areas selected from mesial periapical (A), distal periapical (B), bifurcation (C) of #36; and alveolar crest (D) and interdental area (E) of between 35–36

A standardized image resolution was selected ‘region of interest’ area (at 30 × 30 pixels size) was clipped and copied (Fig. 2A). The ‘Gaussian Blur’ filter (sigma = 35 pixels) was then used to blur the brightness due to changes in soft tissue and bone thickness (Fig. 2B). The blurred image was then extracted from the original image (Fig. 2C). To separate the bone marrow from the trabecular structure, 128 Gy was added to each pixel position (Fig. 2D). The image was then converted to a black and white format using the ‘Binary’ option (Fig. 2E). The noise was reduced with the ‘Erode’ option and then, with the ‘Dilate’ option (Fig. 2F), existing areas were expanded to make them more distinctive with ‘Convert to mask’ option (Fig. 2G). The ‘Invert’ option was then utilized to reveal the boundaries of the trabecular bone by converting the white areas to black and the black areas to white on the image (Fig. 2H). Following the application of the ‘Skeletonize’ option, the trabecular image was converted into the skeletal structure format (Fig. 2I). The fractal dimensions were then calculated using the ‘Fractal Box Counter’ option.

Fig. 2.

Fractal analysis steps: (A) Selection and duplication of ROI from the image. (B) Gaussian blur (C) Subtract blurred ROI from the original ROI. (D) Addition of a grey value of 128 to each pixel location. (E) Binarization (F) Erosion and Dilatation (G) Convert to mask option (H) Inversion. (I) Skeletonization

Statistical analysis

Statistical analyses were performed using software SPSS version 27 (SPSS Inc., St. Louis, MO) for Windows. The Skewness and Kurtosis values were calculated to evaluate the normal distribution of continuous variables. When the Skewness and Kurtosis values obtained from the measurements were between + 3 and − 3, it was accepted that they showed a normal distribution. For qualitative variables, frequency (n) and percentage (%); for quantitative variables, mean, standard deviation, minimum, maximum and median values were given. To compare the differences between two independent groups, t test was used for normally distributed data, and Mann Whitney U test was used for non-normally distributed data. Chi-square test was used for categorical variables. P < 0.05 was determined as statistically significant.

Intra-observer reliability was evaluated using Intraclass Correlation Coefficient (ICC) (two-way mixed model, absolute agreement), with ICC values and 95% CIs reported. ICC values of 0.75–0.90 indicate good agreement, while > 0.90 indicates excellent agreement.

To assess the independent effects of risk factors on bruxism while adjusting for confounders, logistic regression analysis was performed. A two-stage modeling approach was employed. In univariate model, variables showing significant associations in preliminary analyses (e.g., clinical signs, self-reports) were individually tested. In multivariate model, significant variables from the univariate analysis were combined to evaluate their independent contributions, expressed as adjusted odds ratios (OR) with 95% confidence intervals (CI). Confounding variables such as age, gender, and systemic diseases were included in the final model. Statistical significance was set at p < 0.05.

To evaluate the effects of gender and systemic diseases on fractal analysis in bruxism and control group a linear regression model was used to control for confounding factors. For data analysis, the independent samples t-test, Mann-Whitney U test and Two-way ANOVA were employed. Effect sizes were calculated using Cohen’s d (0.2: small, 0.5: medium, ≥ 0.8: large effect) and eta-squared (η²) to interpret the clinical significance of the findings.

Results

Sociodemographic evaluation

There was a statistically significant relationship between the groups for gender (p < 0.05), education status (p < 0.05) and systemic disease status (p < 0.05) (Table-1). In the bruxism group, the female rate (80.0%), primary school & secondary school rate (25.7%), and systemic disease incidence rate (45.7%) were higher than the control group. There was no statistically significant difference for marital status (p > 0.05), smoking (p > 0.05) and age (p > 0.05).

Bruxism questionnaire

The bruxism group responded “yes” to all questions on the Bruxism Questionnaire-1 and Bruxism Questionnaire-2 at a statistically significant level as compared to the control group (p < 0.05) (Table-2). In the four-item ‘Patient Complaints Questionnaire’, the bruxism group reported “yes” to the first three questions more than the control group, at a statistically significant level (p < 0.05) (Table-2). The incidence of occlusal splint use was similar for both groups (p > 0.05) (Table-2). Noone in the control group and 14.3% of the bruxism group used occlusal splint for bruxism.

Table 2.

Comparison of the groups regarding the questions posed to individuals to diagnose bruxism (Chi-square test)

			Groups				p
			Control		Bruxism
			n	%	n	%
Bruxism Questionnaire − 1	Are you aware that you grind your teeth during sleep?	No	35	100.0	7	20.6	0.000*
		Yes	0	0.0	27	79.4
	Has anyone ever told you that you grind your teeth during sleep?	No	35	100.0	19	54.3	0.000*
		Yes	0	0.0	16	45.7
	Tooth clenching substance to sleep: When you wake up in the morning or wake up at night, are your jaws thrust or braced?	No	33	94.3	8	22.9	0.000*
		Yes	2	5.7	27	77.1
	Do you clench your teeth when you are awake?	No	35	100.0	5	14.3	0.000*
		Yes	0	0.0	30	85.7
	Do you grind your teeth when you are awake?	No	35	100.0	19	54.3	0.000*
		Yes	0	0.0	16	45.7
Bruxism questionnaire-2	Has anyone told you that you clench your teeth during sleep?	No	35	100.0	14	40.0	0.000*
		Yes	0	0.0	21	60.0
	If yes, please mark the person who told you this:
	a) Dentist		0		22	62.85
	b) Another healthcare professional		0		0	0
	c) Sleep partner		0		14	37.15
	Have you noticed that you clench your teeth during sleep in the last 2 weeks?	No	35	100.0	5	14.7	0.000*
		Yes	0	0.0	29	85.3
	Has anyone told you that you grind your teeth during sleep?	No	35	100.0	18	51.4	0.000*
		Yes	0	0.0	17	48.6
	If yes, please mark the person who told you this:
	a) Dentist		0		22	62.85
	b) Another healthcare professional		0		0	0
	c) Sleep partner		0		14	37.15
	Have you noticed that you grind your teeth during sleep in the last 2 weeks?	No	35	100.0	16	45.7	0.000*
		Yes	0	0.0	19	54.3
	I clench/grind my teeth when I do tasks that require concentration.	No	31	88.6	12	34.3	0.000*
		Yes	4	11.4	23	65.7
Patient’s Complaints Questionnaire	I feel pain in my temples when I wake up in the morning.	No	34	97.1	14	40.0	0.000*
		Yes	1	2.9	21	60.0
	I have a headache when I wake up in the morning.	No	32	91.4	12	34.3	0.000*
		Yes	3	8.6	23	65.7
	I wake up tired.	No	25	71.4	8	22.9	0.000*
		Yes	10	28.6	27	77.1
	I use an occlusal splint because of my habit of clenching/grinding my teeth.	No	35	100.0	30	85.7	0.054
		Yes	0	0.0	5	14.3

Clinical examination

The prevalence of abnormal tooth wear (p < 0.05), tooth impressions on the buccal area (p < 0.05), and on the tongue (p < 0.05), masseter muscle hypertrophy (p < 0.05), and pain on palpation of masseter muscle (p < 0.05), temporal muscle (p < 0.05) and lateral pterygoid muscle (p < 0.05), were found to be statistically significantly higher in the bruxism group than in the control group (Table-3).

Table 3.

Comparison of the groups in terms of clinical examination (Chi-square test)

			Groups				p
			Control		Bruxism
			n	%	n	%
Abnormal tooth wear		No	35	100.0	18	51.4	0.000*
		Yes	0	0.0	17	48.6
Tooth impressions on buccal area		No	31	88.6	15	42.9	0.000*
		Yes	4	11.4	20	57.1
Tooth impressions on the tongue		No	32	91.4	7	20.0	0.000*
		Yes	3	8.6	28	80.0
Masseter muscle hypertrophy		No	35	100.0	3	8.6	0.000*
		Yes	0	0.0	32	91.4
Pain on palpation of the muscles	Masseter	No	35	100.0	3	8.6	0.000*
		Yes	0	0.0	32	91.4
	Temporal	No	35	100.0	16	45.7	0.000*
		Yes	0	0.0	19	54.3
	Lateral pterygoid	No	35	100.0	15	42.9	0.000*
		Yes	0	0.0	20	57.1

In the bruxism group, statistically significant higher sensitivity was observed in probing the cervical area (p < 0.05) and percussion test (p < 0.05) compared to control group (Table-4). There was a statistically significant difference between control and bruxism groups for cold test (p < 0.001) between no pain and moderate pain, no pain and severe pain, and mild pain and severe pain (Table-4). In terms of tooth wear level statistically significantly difference was found between 0 and 1, 0 and 2, and 0 and 3 (p < 0.001) (Table-4).

Table 4.

Comparison of the control and bruxism groups for dental and radiographic examinations (Chi-square)

		Control		Bruxism		p
Dental examination		n	%	n	%
Sensitivity in cold test	No pain (a)	105	50.0	85	40.5	0.001* a-c a-d b-d
	Mild pain (b)	93	44.3	89	42.4
	Moderate pain (c)	10	4.8	24	11.4
	Severe pain (d)	2	1.0	12	5.7
Percussion sensitivity	No	206	98.1	184	87.6	0.000*
	Yes	4	1.9	26	12.4
Tooth wear level	0(a)	204	97.1	130	61.9	0.000* a-b a-c a-d
	1(b)	6	2.9	41	19.5
	2(c)	0	0.0	24	11.4
	3(d)	0	0.0	14	6.7
	4(e)	0	0.0	1	0.5
Sensitivity to probing the cervical area	No	194	92.4	178	84.8	0.021*
	Yes	16	7.6	32	15.2
Radiographic examination
Periodontal ligament space widening	No	208	99.0	155	73.8	0.000*
	Yes	2	1.0	55	26.2
Bone loss	No	171	81.4	131	62.4	0.000*
	Yes	39	18.6	79	37.6
Changes in lamina dura	No (a)	209	99.5	106	50.5	0.000* a-b a-c
	Loss (b)	1	0.5	63	30.0
	Thickening (c)	0	0.0	41	19.5
Triangulation	No	193	91.9	177	84.3	0.016*
	Yes	17	8.1	33	15.7
Periapical lesion	No	210	100.0	203	96.7	0.015*
	Yes	0	0.0	7	3.3

Each level was symbolized with a letter for levels of sensitivity in cold test, tooth wear and changes in lamina dura. Significant difference was shown between the letters given after the p-value

Radiographic examination

The prevalence of periodontal ligament space widening (p < 0.001), bone loss (p < 0.001), changes in lamina dura (p < 0.001), triangulation (p < 0.05) and periapical lesion (p < 0.05) were statistically significantly higher in bruxism group compared to control group (Table-4). In terms of changes in lamina dura level, there was a statistically significant difference between no change and loss groups, and no change and thickening groups for these two groups.

Periodontal examination

There was a statistically significant difference between the control group and the bruxism group in terms of periodontal pocket depth (p < 0.05), gingival index (p < 0.05), plaque index (p < 0.05) measurements (Table-5). While periodontal pocket depth and gingival index measurements were higher in the bruxism group, plaque index measurement was lower. The difference in other measurements (gingival recession, clinical attachment loss, bleeding on probing and calculus index) were not statistically significant (p > 0.05). In mobility test 210 of the tested teeth in control group and 209 of the bruxism group showed no mobility. The data could not be statistically tested for mobility.

Table 5.

Periodontal examination of control and bruxism groups

	Control		Bruxism		p
	Min-Max (Median)	Mean ± SD	Min-Max (Median)	Mean ± SD
Periodontal pocket depth MW	1–3,6 (1,58)	1,62 ± 0,5	0–3,5 (1,77)	1,77 ± 0,56	0,036*
Gingival recession MW	0–0,58 (0,1)	0,11 ± 0,12	0–0,86 (0,03)	0,17 ± 0,26	0,688
Clinical attachment loss MW	0–1,6 (0,1)	0,22 ± 0,32	0–3,1 (0,3)	0,59 ± 0,87	0,170
Bleeding on probing (%) t	0-100 (29,16)	30,67 ± 24,52	0-100 (8,33)	20,52 ± 27,45	0,107
Gingival IndexMW	0–2,08 (0,5)	0,68 ± 0,5	0–33,3 (0,33)	1,43 ± 5,58	0,012*
Plaque Index MW	0–2,16 (0,42)	0,72 ± 0,61	0–8,33 (0,25)	0,62 ± 1,44	0,008*
Calculus index (%) t	0-100 (16,6)	25,02 ± 22,39	0–83,3 (8,33)	17,35 ± 22,89	0,161

t / MW: t test / Mann Whitney U tests

The intra-observer reliability analysis demonstrated excellent measurement consistency across all periodontal parameters (Table 6). Both the gingival index and calculus index showed perfect agreement (ICC = 1.00, 95% CI: 0.99-1.00, p < 0.001), while bleeding on probing (ICC = 0.98, 95% CI: 0.94–0.99) and gingival recession (ICC = 0.91, 95% CI: 0.75–0.97) achieved near-perfect reliability (both p < 0.001). Good agreement was observed for periodontal pocket depth (ICC = 0.82, 95% CI: 0.51–0.94) and plaque index (ICC = 0.87, 95% CI: 0.63–0.96) (both p < 0.001), with clinical attachment loss showing slightly lower but still good consistency (ICC = 0.79, 95% CI: 0.46–0.93, p < 0.05). All ICC values exceeded the 0.75 threshold for good reliability, though the marginally lower values for millimeter-scale measurements (periodontal pocket depth and attachment loss) likely reflect the inherent challenges of precise clinical measurements at this scale.

Table 6.

Intra-observer reliability of periodontal measurements

	ICC	95% CI	p-value	Interpretation
Periodontal pocket depth	0.82	[0.51, 0.94]	0.001	Good
Gingival recession	0.91	[0.75, 0.97]	< 0.001	Excellent
Clinical attachment loss	0.79	[0.46, 0.93]	0.003	Good
Bleeding on probing	0.98	[0.94, 0.99]	< 0.001	Excellent
Gingival Index	1.00	[0.99, 1.00]	< 0.001	Excellent
Plaque Index	0.87	[0.63, 0.96]	< 0.001	Good
Calculus index	1.00	[0.99, 1.00]	< 0.001	Excellent

Fractal analysis

The mean and median fractal dimension values of the bruxism and control groups were shown on Table 7. In the interdental area, the bruxism group exhibited a significantly higher fractal dimension value compared to the control group (p < 0.05, Z = 2.578). For the periapical mesial area and bifurcation region, no statistically significant differences were found between the bruxism and control groups (p > 0.05). In the periapical distal area, the results were not statistically conclusive between the groups (p > 0.05, Z = 1.797). There was no statistically significant difference between bruxism and control groups for the fractal dimension value in the alveolar crest ridge (p > 0.05, t = 1.868).

Table 7.

Comparison of fractal dimensions between bruxism and control group (A: t test, B: Z value)

Measuring area	Groups	Mean ± SD	Median/IQR	Min-Max	Test	P value
Periapical- mesial area	Control	1.2876 ± 0.0868	1.2876/0.1122	1.0475–1.4465	1.187 A	0.239
	Bruxism	1.3109 ± 0.0778	1.3130/0.1178	1.1379–1.4646
Periapical- distal area	Control	1.2780 ± 0.0900	1.2891/0.1450	1.0767–1.4265	1.797 B	0.072
	Bruxism	1.3119 ± 0.0917	1.340/0.1173	1.0778–1.4131
Bifurcation region	Control	1.2359 ± 0.0916	1.2502/0.1403	1.0327–1.3924	1.642 A	0.105
	Bruxism	1.2704 ± 0.0838	1.2961/0.1338	1.1042–1.4136
Alveolar crest ridge	Control	1.2436 ± 0.0947	1.2571/0.1655	1.0287–1.3971	1.868 A	0.066
	Bruxism	1.2838 ± 0.0852	1.2985/0.1258	1.1070–1.4262
Interdental area	Control	1.2605 ± 0.0888	1.2842/0.1095	1.0418–1.3982	2.578 B	0.010*
	Bruxism	1.3133 ± 0.0590	1.3285/0.0974	1.2082–1.4238

Logistic regression analysis

The univariate logistic regression analysis (Table 8) identified several statistically significant factors associated with bruxism development, including female gender (p < 0.05), presence of systemic diseases (p < 0.05), morning jaw tension (p < 0.001), teeth clenching/grinding during concentration-demanding tasks (p < 0.001), morning headaches (p < 0.001), waking up tired (p < 0.001), presence of tooth marks on buccal mucosa (p < 0.001), positive percussion test (p < 0.05), and positive triangulation test (p < 0.05), with odds ratios showing substantially increased risks: 55.69× for morning jaw tension, 14.85× for concentration-related clenching, 20.44× for morning headaches, 8.44× for tired waking, 10.33× for buccal tooth marks, 4.89× for positive percussion test, and 2.88× for positive triangulation test, along with 3.37× higher risk in females and 6.52× greater risk in those with systemic diseases; however, education level (p > 0.05), gingival index (p > 0.05), plaque index (p > 0.05), positive cold test (p > 0.05), probe sensitivity (p > 0.05), and pocket depth (p > 0.05) showed no significant associations. The multivariate analysis, after controlling for confounding factors, revealed that only morning jaw tension (OR = 80.54, p < 0.05), concentration-related teeth clenching (OR = 31.02, p < 0.05), and morning headaches (OR = 22.70, p < 0.05) remained as independent risk factors, while gender (p > 0.05), systemic diseases (p > 0.05), tired waking (p > 0.05), buccal tooth marks (p > 0.05), percussion test positivity (p > 0.05), and triangulation test positivity (p > 0.05) lost statistical significance, indicating these three factors as the strongest clinical predictors of bruxism when other variables are accounted for.

Table 8.

Univariate and multivariate logistic regression analysis of risk factors associated with bruxism: clinical and self-reported predictors

Risk factors (Bruxism = 1 Control = 0)	Univariate model						Multivariate model
	B	sh	p	OR	95% OR		B	sh	p	OR	95% OR
					Lower	Upper					Lower	Upper
Gender (female))	1,214	0,542	0,025*	3,368	1,164	9,744	1,399	1,183	0,237	4,050	0,398	41,171
Education level			0,084				x	x	x	x	x	x
Education level (primary-secondary)	1,569	0,860	0,068	4,800	0,889	25,919	x	x	x	x	x	x
Education level (University and higher)	-0,371	0,528	0,483	0,690	0,245	1,943	x	x	x	x	x	x
Systemic diseases (positive)	1,876	0,630	0,003*	6,526	1,897	22,452	0,521	1,376	0,705	1,683	0,113	24,971
Morning/Night Jaw Tension (Yes)	4,020	0,832	0,000*	55,687	10,902	284,457	4,389	1,427	0,002*	80,538	4,910	1321,172
Teeth Clenching/Grinding During Concentration (Yes)	2,698	0,640	0,000*	14,854	4,241	52,031	3,434	1,280	0,007*	31,015	2,524	381,144
Morning headache (Yes)	3,018	0,701	0,000*	20,444	5,175	80,773	3,122	1,584	0,049*	22,699	1,017	506,590
Wake up tired (Yes)	2,133	0,550	0,000*	8,437	2,874	24,775	-2,341	1,837	0,203	0,096	0,003	3,525
Tooth impressions on buccal area (positive)	2,335	0,632	0,000*	10,333	2,997	35,634	0,982	1,307	0,452	2,671	0,206	34,634
Periodontal pocket depth	0,571	0,487	0,241	1,770	0,681	4,597	x	x	x	x	x	x
Gingival Index	0,065	0,096	0,498	1,067	0,885	1,287	x	x	x	x	x	x
Plaque Index	-0,084	0,227	0,711	0,919	0,589	1,435	x	x	x	x	x	x
Cold test (pain present)	0,436	0,543	0,422	1,547	0,534	4,482	x	x	x	x	x	x
Perkussion test (positive)	1,587	0,705	0,024*	4,889	1,228	19,471	0,938	1,396	0,501	2,556	0,166	39,404
Triangulation (positive)	1,056	0,496	0,033*	2,875	1,088	7,598	0,422	1,130	0,709	1,525	0,167	13,965
Sensitivity to probing the cervical area (positive)	0,136	0,522	0,794	1,146	0,412	3,188	x	x	x	x	x	x

*p < 0.05 significant effect, p > 0.05 no significant effect; Logistic regression analysis

The statistical analysis revealed significant differences in fractal analysis between bruxism and control groups, particularly influenced by gender and systemic diseases (Table 9). Female bruxism patients exhibited a higher interdental FD compared to controls, with a statistically significant difference (p < 0.05) and a large effect size (Cohen’s d = 0.82). No significant difference was observed in alveolar crest FD (p < 0.05), though a moderate effect size (0.45) suggested a trend. Systemic diseases further amplified FD differences; bruxism patients with systemic conditions showed significantly higher interdental FD than controls (p < 0.05, Cohen’s d = 1.12). Similarly, bifurcation FD was elevated in the bruxism group with systemic diseases (p < 0.05). A two-way ANOVA identified a significant interaction between gender and systemic disease (F(1,66) = 8.42, p < 0.05, η²=0.11), with female bruxism patients having systemic diseases displaying the highest FD values (p = 0.001). These findings underscore the combined impact of gender and systemic diseases on bone morphology in bruxism, highlighting the need to account for these factors in clinical assessments.

Table 9.

Evaluation of gender and systemic diseases on fractal analysis in bruxism and control groups

Parameter	Control Group (n = 35)	Bruxism Group (n = 35)	p-value	Effect Size (Cohen’s d)	Interpretation
Gender (Female)
Interdental FD (Mean ± SD)	1.25 ± 0.08	1.31 ± 0.06	0.018*	0.82	Higher FD in females with bruxism
Alveolar Crest FD	1.24 ± 0.09	1.28 ± 0.09	0.112	0.45	Non-significant
Systemic Disease (Yes)
Interdental FD (Mean ± SD)	1.26 ± 0.07 (n = 4)	1.33 ± 0.05 (n = 16)	0.003*	1.12	Systemic disease increases FD
Bifurcation FD	1.23 ± 0.08	1.30 ± 0.07	0.021*	0.91	Altered bone density
Gender × Systemic Disease Interaction
Female + Disease FD	1.27 ± 0.06 (n = 2)	1.34 ± 0.04 (n = 13)	0.001*	1.35	Strongest FD increase

Discussion

This study, incorporating self-reported data along with clinical and radiographic examinations, demonstrated that adults with probable bruxism exhibited significantly higher prevalence rates of female gender (80%), primary education levels (25.7%), systemic diseases (45.7%), periodontal pockets, gingival index scores, masticatory muscle symptoms (masseter: 91.4%, temporal: 54.3%, lateral pterygoid: 57.1%), tooth wear (48.6%), dental impressions (buccal: 57.1%, tongue: 80%), cervical hypersensitivity (15%), percussion sensitivity (12.4%), positive cold test responses (59%), periodontal ligament widening (26.2%), lamina dura changes (49.5%), triangulation (15.7%), bone loss (37.6%), and periapical lesions (3.3%) compared to non-bruxers. In the interdental regions of bruxism patients (between second mandibular premolar and first mandibular molar) fractal dimension values on periapical radiographs were higher compared to the control group.

In contrast, no significant differences were observed in marital status, age, smoking habits (22.9%), or certain periodontal parameters (gingival recession, clinical attachment loss, bleeding on probing, calculus, mobility) among probable bruxism patients. Notably, plaque index values were found to be lower in this group. Comprehensive evaluation combining both clinical and radiographic examinations represents a key strength of this study.

The Bruxism Questionnaire-1, adapted from a previous study, has demonstrated high sensitivity in correlating self-reported bruxism with clinical findings [33], while the Bruxism Questionnaire-2) was validated against polysomnography, showing strong agreement for sleep bruxism detection [34]. These tools were selected for their established reliability in prior studies and alignment with the American Academy of Sleep Medicine criteria. Self-reports are widely used in bruxism diagnosis due to their cost-effectiveness and accessibility [1]. Findings of our study align with STAB guidelines, which classify ‘ probable bruxism’ via questionnaires  +   clinical signs [24].

Common consequences of bruxism include tooth wear, orofacial pain, and headaches [49]. In this study, 77.1% of bruxism patients reported waking up fatigued, while 60% experienced temporal pain and 65.7% reported morning headaches - findings consistent with previous research [50]. While self-reporting provides valuable diagnostic information, it should be supplemented with clinical assessments for optimal accuracy [33]. For instance, in our study, 85.7% of participants reported being aware of clenching their teeth while awake, whereas only 45.7% noticed grinding. This highlights the sensitivity limitations of non-instrumental methods (questionnaires/clinical examinations). According to the STAB criteria, instrumental methods such as polysomnography or EMG are required for a definitive diagnosis of sleep bruxism [19]. However, due to cost and practical challenges, a combination of questionnaires and clinical examinations is commonly used in clinical practice. Previous studies have compared questionnaire and clinical examination findings with polysomnography [51, 52] and electromyography [51, 53], confirming their high sensitivity in diagnosing sleep bruxism [6].

The literature reports that the chronic effects of bruxism may lead to both adaptive and degenerative changes in bone morphology [27, 31]. In our current study, fractal analysis performed using periapical radiographs revealed statistically significant higher fractal dimension values in the interdental regions of bruxism patients compared to the control group. This finding suggests that mechanical loading associated with bruxism induces trabecular bone reorganization and alterations in bone density in the alveolar bone. Studies in the literature present conflicting results regarding the effects of bruxism on bone structure. While some studies report lower fractal dimension values in the mandibular condyle [31], others describe higher fractal dimension values in the angle region in pediatric populations [54]. These contradictory findings indicate that factors such as bruxism type (awake/sleep), severity, and duration may lead to different adaptive responses in bone tissue. Panoramic radiographic analyses have demonstrated that fractal dimension values in the angle region are significantly higher than those in the condyle and corpus regions in bruxism patients [55]. Additionally, morphological changes such as osseous exostosis formation and increased bone apposition in the gonial region [56–58] provide further evidence supporting the biomechanical effects of chronic bruxism on bone. The pathophysiology of alterations in fractal dimension values is multifactorial, and the conflicting findings in the current literature indicate that the underlying mechanisms have been incompletely understood. Future studies incorporating parameters such as bruxism type, severity, and duration will contribute to a better understanding of bone adaptation mechanisms.

This study revealed significantly higher FD values in interdental regions of bruxism patients, indicative of trabecular reorganization under chronic loading. Direct comparisons with interdental-focused studies are limited. The interdental region’s heightened FD values may correlate with radiographic markers of occlusal trauma (e.g., periodontal ligament widening, triangulation), as noted in our study. This aligns with Dewake et al., who linked mechanical stress to PDL space alterations [45]. Similarly, a study by Padmaja Satheeswarakumar et al. observed trabecular reorganization in load-bearing areas, supporting our observation of interdental changes [27]. The absence of significant FD differences in other regions (e.g., alveolar crest) suggests localized rather than generalized bone adaptation, emphasizing the multifactorial nature of bruxism’s biomechanical effects.

While tooth wear represents a significant clinical finding in bruxism diagnosis, it cannot serve as a standalone diagnostic criterion. Dental wear exhibits multifactorial etiology and may be influenced by various factors including dietary habits and oral hygiene status [59]. Epidemiological studies typically combine questionnaire data with clinical examination findings to establish bruxism diagnosis [11, 60].

In this study, tooth wear was detected in 48.6% of bruxism patients, while dental impressions on the tongue (80%) and buccal mucosa (57%) showed higher prevalence rates. The high prevalence of lingual/buccal dental impressions in bruxism patients supports the dominance of clenching (sustained, isometric jaw contraction) over grinding (rhythmic movement). Mechanically, clenching generates prolonged pressure on oral soft tissues, leading to indentations on the tongue (lingual scalloping) and buccal mucosa (linea alba); and grinding, in contrast, typically causes occlusal wear facets, but fewer soft-tissue marks. This aligns with EMG studies showing that > 70% of bruxism episodes involve clenching, particularly during wakefulness [2]. Notably, the patients’ self-reports corroborated this: 85.7% acknowledged awake clenching, while only 45.7% reported sleep grinding. Lingual scalloping was referred as a pathognomonic sign of clenching [53], and linea alba (buccal impressions) reflects chronic cheek biting during parafunctional activity [3]. Our findings also align with current literature indicating that clenching rather than grinding constitutes the most prevalent parafunctional behavior in bruxism [2, 6].

From a muscular symptom perspective, our analysis revealed symptom prevalence rates of 91.4% in the masseter muscle, 54.3% in the temporal muscle, and 57.1% in the lateral pterygoid muscle. Current literature includes studies reporting no significant differences in EMG-recorded temporal muscle activity between individuals with and without dental wear [61]. These findings collectively demonstrate that comprehensive clinical evaluation of bruxism necessitates a multidisciplinary diagnostic approach.

Bruxism and other occlusal traumas can cause significant damage to the periodontium, though diagnosis requires careful evaluation of multiple clinical and radiographic indicators [45]. Key signs of occlusal trauma include tooth mobility, facet wear, fractures, thermal sensitivity, root resorption, widened PDL space, and alveolar bone loss [62, 63]. Research shows that even early-stage excessive forces can lead to cementum/alveolar bone resorption and PDL widening in cervical/apical regions, regardless of periodontal health status [64]. While some studies link excessive forces to periodontitis [45, 65], our findings in bruxism patients revealed higher rates of cervical sensitivity (15%), percussion sensitivity (12.4%), cold test positivity (59%), widened PDL (26.2%), lamina dura changes (49.5%), triangulation (15.7%), bone loss (37.6%), and periapical lesions (3.3%), but no significant differences in gingival recession, mobility, clinical attachment loss, or bleeding on probing, compared to controls. Current evidence suggests that while occlusal forces may exacerbate existing periodontal disease, bruxism alone doesn’t appear to directly cause periodontal damage [66], though it significantly contributes to biomechanical complications in implants and prostheses [66]. These findings highlight the need for comprehensive, multidisciplinary assessment when evaluating occlusal trauma cases.

In this study, sleep and awake bruxism were not distinguished; however, current literature indicates that this distinction involves methodological challenges and clear diagnostic criterias have yet to be established [67]. Although the 2018 STAB consensus provides an important framework for the clinical assessment of bruxism, it emphasizes the difficulty of making definitive diagnostic distinctions, particularly in secondary bruxism cases, due to the complexity of etiological factors [67, 68]. Given the limitations of observational studies in determining causal relationships, future research requires standardized criteria supported by longitudinal cohort studies. In this regard, elucidating the integration of STAB data into therapeutic decision-making algorithms would be a major advancement in the treatment of bruxism.

The presence of splint use in controls suggests potential undetected bruxism, warranting future studies with objective diagnostics (e.g., polysomnography). The absence of objective diagnostic methods, such as polysomnography, in case selection was a key limitation for this study. However, this reflects real-world clinical practice constraints. Additionally, the cross-sectional design precludes definitive conclusions about causality between bruxism and observed bone changes. Future longitudinal studies are needed to incorporate objective diagnostic tools like polysomnography or EMG to validate self-reported and clinical findings, ensuring greater diagnostic precision. Longitudinal studies could clarify the causal relationship between bruxism and observed bone changes, particularly trabecular reorganization detected via fractal analysis. Additionally, differentiating between sleep and awake bruxism subtypes may reveal distinct clinical and radiographic patterns, enabling more tailored treatments. Broader demographic sampling and interdisciplinary collaborations-integrating dentistry, sleep medicine, and neurology-would enhance the generalizability of findings and improve holistic management strategies.

Conclusion

This study investigated the clinical and structural effects of bruxism through multiple assessment methods, revealing significant associations between bruxism and various orofacial manifestations. The findings demonstrated that bruxism patients exhibited characteristic muscular pain patterns along with measurable dental wear and distinct alterations in both periodontal tissues and bone microstructure.

Abbreviations

STAB

Standardized tool for the assessment of bruxism

TMJ

Temporomandibular joint

Author contributions

E.S. and M.A.T. designed the research concept, collected and assemblied the data, E.S. analyzed the data, E.S and M.A.T. wrote the main manuscript and approved the final version of the article.

Funding

The authors received no specific funding for this work.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The ethical approval was taken from the Clinical Researchs Ethical Committee of Faculty of Medicine of Ankara Yildirim Beyazit University (#26379996/15, Decision date and number: 22.06.2022-11). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The participant consent was obtained from the patients for this study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.