Association of temporomandibular disorders and other jaw anomalies in chewing gum users—a systematic review

2.1 Eligibility criteria

This systematic review was conducted following a structured PECO (Population, Exposure, Comparator, Outcome) protocol and adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, as documented in the Supplementary material (PRISMA 2020 Checklist) [30]. This review was registered under the provisional PROSPERO number CRD42024553227.

2.2 PECO protocol

• Population (P): The review targeted individuals of all ages who were habitual users of chewing gum.

• Exposure (E): The primary exposure of interest was the habitual act of chewing gum.

• Comparator (C): The comparator group consisted of individuals who did not chew gum or chewed it infrequently, but was not deemed to be mandatory.

• Outcomes (O): The outcomes of interest were the presence of TMD and associated aspects pertaining to TMJ pain, clicking symptoms and discomfort.

2.3 Database search protocol

For this review, the database search protocol involved the incorporation of Boolean operators and MeSH (Medical Subject Headings) terms (Table 1). The search strategy was adapted for each database to accommodate the respective syntax and functionalities. The databases searched included PubMed, EMBASE, Cochrane Library, Web of Science, Scopus and PsycINFO. No limitation was placed in terms of the search period of the included articles. Each database search was conducted using a combination of keywords and standardized indexing terms, tailored to the specific database’s interface and indexing system as shown in Table 2.

2.4 Variable extraction protocol

A standardised data extraction protocol was devised for this review and tested it on a few studies to make sure it worked well for gathering the necessary information. The aim was to collect a range of information, including study details, methods used, information about the participants, what they were exposed to, how they were compared, what outcomes were measured, what the results were, and what the authors concluded. Two reviewers independently went through the studies and filled out a form with the required information. In cases where the two reviewers did not agree, they talked it over to find a solution or, if needed, they asked for another opinion from a third reviewer.

The Cohen’s kappa statistic was used to check how well the two reviewers agreed on what studies to include and the information they gathered. The results showed that they mostly agreed on which studies to include from the titles and abstracts (κ = 0.85) and which full texts were eligible (κ = 0.80). They had very high agreement when it came to pulling out key information like study design, who was in the study, and the main results (κ = 0.90). These kappa values suggested that the data extraction process was consistent and reliable. The review included these numbers to show the careful approach of the study and to let readers know that the results were not likely to be affected by the reviewers’ personal judgments.

2.5 Bias assessment protocol

We implemented a bias assessment protocol to critically evaluate the risk of bias in the included studies which involved the usage of Cochrane Risk of Bias 2.0 (RoB 2.0) tool for randomized control trials (RCTs) [31], while the Risk of Bias in Non-randomized Studies of Exposures (ROBINS-E) tool [32] was applied to non-randomized studies.

2.6 Assessment of certainty bias

Upon completing the bias assessment using the Cochrane RoB 2.0 [31] and ROBINS-E [32] tools, the research team proceeded with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach [33] to evaluate the overall certainty of the evidence included in this review. The GRADE framework provided a systematic method for considering factors such as study limitations, consistency of effect, imprecision, indirectness and publication bias, which collectively determined the quality of the evidence for each outcome.

2.7 Groups and parameters assessed

Al Sayegh et al. [34] assessed the impact of chewing tasks of differing durations (40 minutes and 60 minutes) on psychosocial variables, clinical examination of TMD (Diagnostic Criteria (DC)/TMD-Axis I), perceived exertion (RPE), and pain intensity (NRS). The psychosocial variables included assessments for the Generalized Anxiety Disorder-7 (GAD-7), the Patient Health Questionnaire-9 (PHQ-9), the Patient Health Questionnaire-15 (PHQ-15), the Perceived Stress Scale-10 (PSS-10), and the Pain Catastrophizing Scale-13 (PCS-13). This comprehensive approach allowed for a multidimensional analysis of the psychological and physical responses to prolonged chewing tasks. Christensen et al. [35] assessed the electromyographic (EMG) activity of the masseter muscles in healthy adults during three functional states: rest (idling), unilateral chewing, and maximum voluntary contraction (MVC). This study provided insights into the muscle activity patterns associated with various functional states of the masseter muscle, which is relevant to understanding masticatory muscle behavior in TMD.

Correia et al. [36] differentiated groups based on gum chewing habits and the presence of parafunctional habits. They measured the frequency and duration of gum chewing, the presence of TMD symptoms such as arthralgia and myofascial pain, and the extent of masseter hypertrophy. By comparing these variables across different groups, the study aimed to elucidate the relationship between gum chewing habits and TMD symptomatology. Farella et al. [37] examined the effects of chewing tasks (using hard gum, soft gum and empty chewing) on perceived muscle pain and masticatory fatigue. They used the Visual Analog Scale (VAS) to evaluate subjective pain experiences and measured pressure pain thresholds (PPTs) in the masseter and anterior temporalis muscles in women without TMD. This approach helped quantify subjective pain experience and objective muscle sensitivity.

Matsuda et al. [38] investigated the EMG activities of the masseter during different gum chewing tasks. The study measured the normalized root mean square (n-RMS) values of rhythmic masticatory muscle activity (RMMA) phasic bursts, along with burst duration and cycle time. This provided a detailed examination of masseter muscle function during mastication. Olchowy et al. [39] used shear wave elastography to measure the stiffness of the masseter and temporalis muscles before and after intensive gum chewing, as well as after relaxation. They also assessed the correlation between the stiffness of these two muscles. This study contributed to the understanding of muscle elasticity changes due to masticatory activity.

Watemberg et al. [40] examined the daily duration of gum-chewing in different groups and its association with a family history of migraine, findings from neuroimaging studies, and funduscopic examinations. By correlating these variables, the study sought to explore the potential link between gum chewing and neurological conditions. Yashiro et al. [41] compared healthy adults and TMD patients in terms of the kinematics of gum-chewing cycles using a non-invasive kinesiograph. They measured positional errors during opening/closing movements, skewness of the velocity profile, and ultraviolet (UV) for these movements. The comparison aimed to identify distinctive kinematic patterns associated with TMD.

3.1 Study selection process

The initial identification of records yielded 417 items from various databases and none from registers (Fig. 1). Before screening commenced, several records were removed: 39 were duplicates, 55 were marked as ineligible by automation tools, and no records were removed for other reasons. This left 323 records to be screened. Upon further scrutiny, 41 records were excluded due to the unavailability of full-texts, which necessitated the retrieval of 282 reports. However, not all reports could be retrieved; 38 remained inaccessible due to restricted access to certain journals and databases that required specific subscriptions or institutional memberships that were not available to us. Consequently, 244 reports were assessed for their eligibility based on the review criteria. During the eligibility assessment, several reports were excluded for specific reasons: 37 did not respond to the PECO criteria set for the study, 46 were off-topic, 65 were individual case reports, 51 were animal studies, and 37 were scoping reviews. After applying these exclusion criteria, only 8 studies [34, 35, 36, 37, 38, 39, 40, 41] met the requirements and were included in the review.

Fig. 1.PRISMA flowchart for the review. PECO: Population, Exposure, Comparator, Outcomes.

3.2 Bias observed across selected papers

When comparing the two studies, Al Sayegh et al. [34] and Correia et al. [36], both were evaluated to have an overall low risk of bias, although they each encountered domain-specific concerns (Fig. 2, Ref. [34, 36]). Al Sayegh et al. [34] demonstrated a low risk of bias in most domains including the randomization process, adherence to intervention, and outcome measurement. Their concerns were primarily with missing outcome data and the selection of the reported result. Correia et al. [36], in contrast, had similar low risks in the randomization process, outcome measurement, and reported results, but their concerns were concentrated on deviations from the intended intervention, which is an aspect where Al Sayegh et al. [34] did not face the same level of concern. Despite these individual domain concerns, both studies were ultimately classified as having a low overall risk of bias, suggesting that their findings are relatively robust.

Fig. 2.Assessed bias across different domains using the RoB 2.0 tool.

As shown through Fig. 3 (Ref. [35, 37, 38, 39, 40, 41]), comparatively, the studies by Christensen et al. [35], Farella et al. [37], and Watemberg et al. [40] shared similar overall low risks of bias, although each encountered some concerns in different domains. Christensen et al. [35] faced issues with the measurement of exposure and missing data, while Farella et al. [37] had some concerns regarding bias due to post-exposure interventions. Watemberg et al. [40], on the other hand, also had concerns in the domain of post-exposure interventions but were consistent in all other domains. Matsuda et al. [38] and Yashiro et al. [41] both presented low risks of bias in the majority of domains, with their only concerns being in the measurement of outcomes. These singular concerns did not significantly impact their overall low risk assessments. Olchowy et al. [39], however, stood out slightly different with concerns in two key areas: the selection of participants and the selection of the reported result, leading to an overall conclusion of some concerns regarding bias.

Fig. 3.Assessed bias across different domains using the ROBINS-E tool.

3.3 GRADE assessment

As elucidated through Table 3, for the RCTs, represented by Al Sayegh et al. [34] and Correia et al. [36], the common finding was that chewing gum might increase TMD symptoms, but the effects appear to be temporary and may not be significant. The risk of bias was rated as “low to moderate” due to some concerns in specific domains, but this did not profoundly affect the overall findings. Inconsistency and indirectness were both deemed low, implying a consistent finding across studies and a direct applicability of the results. Imprecision was also rated as low, indicating that the results are precise enough to be considered reliable. No other factors influenced the certainty domain, which was determined to be low.

The observational studies, including Christensen et al. [35], Farella et al. [37], Matsuda et al. [38], Olchowy et al. [39], Watemberg et al. [40], and Yashiro et al. [41], consistently suggested that excessive gum chewing is linked to TMD symptoms, muscle stiffness, and altered muscle function, though recovery is generally quick after cessation of chewing. The risk of bias for these studies was assessed as low, with a consistent methodology across studies and no significant deviations that would undermine the validity of the findings. However, there was some moderate inconsistency and imprecision, which may be due to the variability in study design, population and outcomes measured. Despite these variances, the overall certainty of the evidence from observational studies was considered low.

3.4 Population-associated characteristics

The synthesis of findings from Table 4 (Ref. [34, 35, 36, 37, 38, 39, 40, 41]) reveals the diverse array of research designs and population characteristics, conducted between 1996 [35] and 2021 [22]. RCTs were conducted in Sweden in 2020 [34] and Portugal in 2014 [36], with sample sizes of 31 and 50 participants, respectively, and mean ages of 26 and 23 years respectively. The male to female ratios in these trials were nearly balanced in the Swedish study and heavily skewed towards females in the Portuguese study. Observational studies formed the bulk of the research designs, with studies conducted in the USA in 1996 [35], Italy in 2001 [37], Japan in 2016 [38], and Poland in 2021 [39]. The sample sizes ranged from 8 in the USA study to 50 in the Italy study, indicating a variance in study power and potential impact on the reliability of the findings. The mean ages varied widely, from 27 years in the USA study [35] to 42.1 years in the Japan study [38], which suggests a broad age distribution across studies and potential variability in age-related outcomes. The gender distribution was also varied, from all-female participants in the Italy study [37] to a nearly balanced ratio in the Poland study [39].

One cross-sectional study was identified from Israel, conducted in 2014 with a sample size of 30 and a mean age of 12.8 years [40], which is notably younger than the other studies reviewed. The gender ratio here was also skewed towards females. The second study from Japan, conducted in 2005 with a sample size of 20, reported a mean age of 26.6 years and an equal distribution of males and females [41]. This provides a contrast to the earlier Japanese observational study with almost the same sample size but with older participants [38]. The global regions represented include both Western and Eastern societies, as well as European and Middle Eastern countries, allowing for potential cross-cultural comparisons. However, the overall sample sizes are relatively small, with only two studies having 50 participants [36, 37].

3.5 Chewing gum effect observed

In the study conducted by Al Sayegh et al. [34], the researchers observed a higher incidence of arthralgia following a chewing task, with symptoms decreasing at the 2-hour follow-up mark (Table 5, Ref. [34, 35, 36, 37, 38, 39, 40, 41]). Notably, there was a higher prevalence of myalgia and arthralgia after a 60-minute duration of chewing compared to a 40-minute duration. This suggests that prolonged chewing tasks may exacerbate TMJ symptoms, although there appears to be a recovery or adaptation period post-chewing. Christensen et al. [35] reported that the majority of participants experienced weak jaw muscle fatigue during unilateral gum chewing, but they did not report jaw muscle pain. This could imply that while prolonged chewing might induce muscle fatigue, it does not necessarily result in pain, potentially due to the sensitization of muscle nociceptors over time.

Correia et al. [36] found that a significant proportion of individuals with frequent gum chewing habits (Groups A–D) reported symptoms of arthralgia and myofascial pain, with the highest reports coming from Group D (63%) for arthralgia and Group A (83%) for myofascial pain. Additionally, all individuals in Group E reported masseter hypertrophy, indicating a potential link between gum chewing habits and the development of musculoskeletal alterations and pain syndromes. In the research by Farella et al. [37], it was observed that VAS scores for pain and fatigue increased during the chewing of hard gum but returned to baseline after 10 minutes of recovery. There were no significant changes in PPTs after any of the chewing tasks, which suggests that short-term masticatory exertion does not alter muscle pain sensitivity.

Matsuda et al. [38] documented that RMMA during sleep showed smaller n-RMS values of phasic bursts when compared to those during gum chewing. Additionally, the burst duration and cycle time of RMMA were significantly longer than during gum chewing, indicating a distinct pattern of muscle activity in TMD-related muscle actions versus normal chewing. Olchowy et al. [39] reported a significant increase in muscle stiffness after intense gum chewing, which significantly decreased after a period of relaxation. Furthermore, the temporalis muscle exhibited significantly lower stiffness compared to the masseter muscle, suggesting that the masticatory muscles respond differently to mechanical stress and recover at different rates.

Watemberg et al. [40] found no significant differences in temporomandibular symptoms among the groups based on the duration of gum-chewing. Interestingly, the discontinuation of gum-chewing led to complete resolution of symptoms in 19 out of 30 patients and some improvement in 7 patients, which could indicate that gum chewing may be a reversible risk factor for some individuals with TMD. Yashiro et al. [41] identified that patients with TMD had higher average UV during gum-chewing compared to controls. This suggests that individuals with TMD exhibit greater abnormalities in chewing movements, which may be indicative of underlying motor control dysfunction.

4.1 Limitations

The investigations into the association between gum chewing and TMDs encountered several limitations that warrant consideration when interpreting the findings. One prominent limitation was the inherent heterogeneity among study designs, including variations in sample size, population characteristics, and methodological approaches. This diversity among studies introduced challenges in synthesizing data and generating a cohesive understanding of the relationship between gum chewing and TMDs. Furthermore, the duration of the studies was generally short-term, which may not accurately capture the long-term effects of gum chewing on the temporomandibular joint and associated musculature. Consequently, the potential for reverse causation or the presence of confounding factors that might influence the onset or progression of TMD symptoms was not thoroughly examined. This is particularly relevant for observational studies where the control for external variables is inherently limited, and causality cannot be definitively established. In addition, the studies predominantly focused on the mechanical aspects of gum chewing, with less attention given to the biochemical or molecular mechanisms that may contribute to TMD pathogenesis. This omission suggests that the studies may not have captured the full spectrum of factors that influence TMDs, which could be critical to understanding the disorder’s multifactorial nature.

4.2 Clinical recommendations and implications for future research

Our results imply numerous suggestions depending on the material given. First of all, extended chewing activities—such as gum chewing—should be done carefully since they could aggravate TMJ problems and muscle tiredness. To reduce possible detrimental consequences, people should thus be aware of the length of their chewing activities. Also, considering the consequences of gum chewing, one must choose a customised method. Gum chewing can have different effects on different people; some may get musculoskeletal changes, pain syndromes, or muscle hypertrophy. Consequently, advice on gum chewing should be customised to the particular demand and situation of every person.

Furthermore, advised is consistent observation of symptoms and their reaction to gum chewing or other masticatory action. This enables people to spot any changes in the degree or length of symptoms after chewing activities, therefore enabling the identification of possible triggers and the application of suitable treatment techniques. Moreover, it is important to admit that extended chewing activities could cause muscle tiredness. People should be conscious of their degree of muscle tiredness and provide top priority to enough rest and recovery so that the chewing-related muscles could heal.

Future research should standardize methodologies to assess the impact of gum chewing on TMD, including consistent chewing durations and types. Longitudinal studies are needed to examine the long-term effects of habitual gum chewing on TMD development and recovery periods. Specific symptoms like arthralgia, myofascial pain and muscle fatigue should be differentiated to understand their underlying mechanisms. Research should also explore the interaction between psychological factors and physical symptoms. Detailed investigations into muscle activity, stiffness, and kinematics during chewing tasks can provide insights into the biomechanical and neuromuscular aspects of TMD. The potential reversibility of symptoms with the cessation of gum chewing and identifying susceptible subgroups could inform preventive and therapeutic strategies.