Periodontal disease and sports performance: a systematic review and meta-analysis

ABSTRACT

This systematic review and meta-analysis aimed to assess the association between athletic performance and periodontal disease (PD). Observational studies published up to April 2022 were searched in online databases (PubMed, Scopus, Web of Science, The Cochrane Library, LILACS, OpenGrey, and Google Scholar). PECO statement focused on studies with professional athletes (Participants) with PD (Exposition) compared to those with healthy periodontium (Comparison) and its effects on sports performance (outcome). Searches were conducted according to the PRISMA guidelines (registration protocol: 10.17605/OSF.IO/7ADH6) and risk of bias evaluation according to the Joanna Briggs Institute checklist. A total of 793 references were retrieved, of which eight were considered eligible. Two studies did not show an association between clinical PD parameters and performance. A meta-analysis with 396 participants suggested a relationship between PD and self-reported reduction in sports performance (odds ratio [OR] = 1.55; 95% confidence interval [CI] 1.04–2.31; p = 0.03; I2 = 0%) with moderate quality of evidence accordingly GRADE analysis. Despite the differences in performance evaluations between studies, PD was associated with reduced self-reported sports performance. Additional studies assessing confounding factors and objective assessment of PD and performance are needed to clarify the real effect of both conditions.

KEYWORDS:

• periodontal disease
• periodontitis
• athletic performance
• systematic review
• meta-analysis

Introduction

Athletic performance refers to the efforts made by athletes to achieve specific performance goals. Skill, strength, endurance, and recovery are four significant sports performance dimensions (Handelsman, 2016). A particular combination of these features may result in maximum performance at different exercises. Many diseases, such as oral diseases, may affect an athlete’s physiological, psychological, and functional abilities, resulting in a lower quality of life and, consequently, a lower level of performance (Ashley et al., 2015). Continuing healthcare assistance is, therefore, one of many methods to manage athletes’ health and ensure that these dimensions are balanced to achieve better performance, especially during competitive seasons (Needleman et al., 2014).

Periodontal disease is a multifactorial inflammatory disease of the dental supporting tissues (gingiva, periodontal ligament, cement, and alveolar bone) and one of the most prevalent oral diseases in the worldwide population (Oppermann et al., 2015). Despite its widespread occurrence, healthcare providers often overlook the impact of periodontal disease on overall health. In fact, mild signs of periodontal diseases, such as bleeding during flossing and swelling, affect approximately half of the adults aged 30 and older (Genco & Sanz, 2020). In contrast, severe signs such as dental mobility and tooth loss are common among individuals aged 65 and older (Oppermann et al., 2015). Addressing the prevention and management of periodontal disease is essential for maintaining oral and overall health, yet it is often overlooked. The high prevalence of periodontal disease may be related to its low symptomatic status because, in most cases, there is no pain in the dental supporting tissues (Genco & Sanz, 2020). Thus, mild or moderate conditions may be neglected or masked by smoking or conditions such as diabetes (Genco & Sanz, 2020). Due to its multifactorial nature, periodontal disease is influenced by variables intrinsic to individuals and environmental and behavioural factors such as smoking, self-care, and hygiene (Meyle & Chapple, 2015).

In periodontal disease, dysbiotic dental biofilm triggers a host immune response and may be a potential cause of inflammation leading to possible systemic alterations (Ferreira et al., 2019; Zhao et al., 2018; Ferreira de Brito Silva et al., 2019). Without regular debridement, plaque accumulation can elevate the risk of periodontal damage and increase proinflammatory mediators, such as IL-1B, IL-6, C-reactive protein, and TNF-a (Ebersole et al., 2017). Some of these biomarkers are related to muscle fatigue, risk of sports injuries, and persistent inflammation status in high-intensity exercise practitioners (Lee et al., 2017). Therefore, it begs the question: could periodontal inflammation contribute to increased exercise-induced inflammation and the risk of injuries? Studies show that athletes with signs and symptoms of periodontal disease are more likely to experience recurrent injuries (Ford et al., 2017), a significant concern for athletes and technical staff (Solleveld et al., 2015). Poor oral hygiene is common among athletes, and many struggle to access preventive care, leading to a high prevalence of the periodontal disease among sports practitioners (Gallagher et al., 2020; Needleman et al., 2014). These findings underscore the importance of oral hygiene and regular dental care for athletes to reduce the risk of injury and maximize performance.

To maintain a high level of performance, athletes must manage small physiological and psychological changes that can impair their abilities. This necessitates careful health management, including monitoring signs and symptoms of easily preventable diseases such as periodontal disease (Gallagher et al., 2019). Since periodontal disease significantly influences systemic health, we hypothesized that it might affect athletes’ performance variables related to skills, strength, endurance, or recovery. This systematic review investigated the association between periodontal disease and athletic performance.

Materials and methods

Registration protocol and study design

This systematic review was conducted according to The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines (Page et al., 2021) (S1). The PRISMA criteria were followed after obtaining a registration code from Open Science Framework (10.17605/OSF.IO/7ADH6).

Eligibility criteria, search strategy, and data extraction

After developing a PECO statement that focused on comparisons between professional athletes (participants) with periodontal disease (exposure) and those with a healthy periodontium (comparison) and the effects of periodontal disease on sports performance (outcome), observational studies published until April 2022 were searched for in online databases. This study defined sports performance as any factor affecting an athlete’s skills, strength, endurance, or recovery (Handelsman, 2016). No restrictions were placed on the type of sports. Cross-sectional, case-control and cohort studies were included in the search.

Regarding performance definition, several qualitative and quantitative variables can assess sports performance by analysing an athlete’s health state, psychological status, training level, nutrition, as well as a sport technique and genetic heritage (D’Isanto et al., 2019). Body composition measurements (body mass index, skinfold measurements, bioelectrical impedance, etc.), blood and muscle biomarkers (CRP, creatine kinase, IL-1) (Lee et al., 2017), and categorical outcomes (win/loss, quality of life, presence/absence of self-reported issues or injuries) (Houston et al., 2016; Lochbaum et al., 2022) were considered for this review. To assess periodontal health, variables considered in this review were: gingival index > 30% of teeth, bleeding on probing (BOP >25% of sites), probing pocket depth, and plaque index (Papapanou et al., 2018). Secondary variables of periodontal health were the basic periodontal examination index, community periodontal index (CPI), community periodontal index of treatment needs (CPITN), and self-report periodontal issues, such as bleeding while flossing/brushing or gum swelling (Gallagher et al., 2017).

A search was conducted in the databases of PubMed, Scopus, Web of Science, Cochrane Library, and LILACS. Gray literature was also evaluated using OpenGrey and Google Scholar. Combined searches with “athletes” or “exercise” and “periodontitis” or “periodontal disease” or “gingivitis” and “sports performance” employed a combination of controlled pre-defined MeSH (Medical Subject Headings) and free terms linked to athletes, periodontal disease, and sports performance. Supplementary File 2 shows the search strategy for the selected databases. Differences in database syntax rules were accounted for when executing a combination of pre-defined phrases.

We employed a reference manager (EndNote, x9 version, Thomson Reuters) to save the retrieved citations in all databases. Duplicate results were eliminated, and only one citation for each article was considered. Opinion papers, technical articles, guidelines, and animal experiments were excluded because their titles and abstracts did not meet the eligibility criteria. The full texts of the remaining papers were evaluated to select the relevant articles. Citations from the reference lists of previously selected articles were also assessed using full-text analysis. All database searches were completed by two examiners (ROF and DRF). In disagreement, the articles were examined by a third examiner (RRL).

Data extraction was performed for the selected publications. Table 1 shows the publication year, study design, participant characteristics (source and sample size), age, periodontal assessment, sports performance assessment, and outcomes. An attempt was made to contact the authors via email if the lack of information affected data extraction or the risk of bias evaluation. The attempt consisted of sending a weekly email for up to 5 consecutive weeks.

Table 1. Data extracted from the selected studies.

Authors	Participants	Age	Periodontal disease evaluation	Sports performance evaluation	Outcomes
Alshail et al. (2016) Cross-sectional#	n=27 male=27 Soccer players	Group 1: BOP and PPD > 4mm and < 30% sites (n=14) − 18.2 ± 2.3 years (Mean ± SD) Group 2: BOP and PPD > 4mm and > 30% sites (n=13) 19.1± 0.6 years (Mean ± SD)	PPD, BOP and BOP	Serum CK	Levels of CK were significantly higher among individuals in Group 2 (292.7 U/L) when compared to those in Group 1 (52.3 U/L) (P < 0.01).
Botelho et al. (2021) # Cross-sectional	N=22 Male Soccer players	27.7± 5.4 (Mean±SD)	PI, PPD, CAL, PISA and PESA	Body mass index, Adipose folds, Muscle mass index, Fat mass, Waist-hip index, self-reported presence of muscular and/or articular injuries up to 6 months,	Periodontal disease (PD) was correlated with the percentage of fat mass, muscle mass, muscle mass index and total adipose folds. However, no association of periodontal disease and muscle and articular injuries was found.
Gallagher et al. (2018) # Cross-sectional	N=344 Olympic athletes	25 years (median) Range 18–39	BPE	OIDP questionnaire (Locker & Quinonez, 2011 with modifications)	Bleeding when cleaning teeth had an association with athlete-reported impacts on well-being and daily activity - OR 1.649 (1.023–2.657; 95% CI; p=0.04), but not with sport performance – OR 1.369 (0.820–2.287; 95% CI; p=0.230)
Gay-Scoda, (2011) # Cross-sectional	N=30Soccer players Soccer players	21±1.6 years Mean ± SD	Quigley & Hein Plaque index, Löe and Silness Gingival index, PPD	Physical extrinsic and intrinsic injuries – Medical records	PI (p=0.22; r=0.418) and PPD (p=0.032; r=0.392) showed a correlation with muscle injuries (p<0.05)
Kragt et al. (2019) Cross-sectional	N=116 40 men 76 women Olympic athletes	25.84 ± 5.82 (Mean ± SD)	DPSI	OHIP-14 questionnaire	Dutch elite athletes DPSI-score was 1.71 ± 0.73 and not significantly related to quality of life or reduction of sports hours per week (p>0.05).
Needleman et al. (2013) Cross-sectional	N=278; Olympic athletes	25.7 years (median) Range 16–47	CPITN	OIDP questionnaire (Locker & Quinonez, 2011 with modifications)	Periodontal disease (gingivitis: 76% athletes; periodontitis: 15% athletes). However, BPE was not associated with performance (p=0.122)
Needleman et al. (2016) Cross-sectional	N=187; Professional soccer players	24 years (median) Range 18–39 years	BPE	OIDP questionnaire (Locker & Quinonez, 2011 with modifications)	Gingivitis (BPE codes 1–2) was the worst finding and present in more than 8/10 of footballers with irreversible periodontitis (BPE codes 3–4) in 5% of players. However, no statisticaly significance was found related to quality of life.
Solleveld et al. (2015) # Cross-sectional	N=184 Soccer players	Range 16–31 years	Self-report of gum problems (bleeding, swelling or recession)	Self-report questionnaire about REAMC,MTR and MR.	Association with 2 or more oral health problems such as periodontal disease was related to reinjury variables. Adjusted OR - REAMC - OR 3.33 (1.11–9.96; 95% CI; p<0.05) MTR – OR 2.48 (1.01–6.09; 95% CI; p<0.05) MR – OR 3.40 (1.35–8.59; 95% CI; p<0,01)

Legend: BPE - Basic Periodontal Examination; CAL - Clinical Attachment Loss; CK - Serum creatine kinase levels; CPITN - Community Index of Periodontal Treatment Need; DPSI - Dutch Periodontal Screening Index; MTR - Muscle or Tendon Reinjury; MR - Multiple Types of Reinjury; OIPD - Oral Impacts on Daily Performance questionnaire; OHIP-14 - Oral Health Impact Profile-14; OHRQOL - Oral health-related quality of life questionnaire; PESA – periodontal epithelial surface area; PI – Plaque index; PISA - periodontal inflamed surface area; PPD – Probing Pocket Depth; REAMC - Repeated Exercise-Associated Muscle Cramps.

Quality assessment analysis and risk of bias

The Joanna Briggs Institute’s checklist for prevalence studies was used to evaluate the methodological quality and risk of bias. The study samples, measurement quality, confounding factor identification, outcome analysis, and statistical analysis were all part of the analysis (Moola et al., 2017). The response “No” was assigned to significant issues related to the assessed criteria or to criteria without a description. When there was no clear description of a criterion in the study, the response “unclear” was used. If there were no problems with the criterion, the response “yes” was used. Analyses that were not applicable owing to the study’s design was also checked, but with the notation “NA.” Table 2 lists all the assessment criteria.

Table 2. Quality assessment of methods and risk of bias for selected studies.

QUALITY	Alshail et al. (2016)	Botelho et al. (2021)	Gallagher et al. (2018)	Gay-Scoda, 2012	Kragt et al. (2019)	Needleman et al. (2013)	Needleman et al. (2016)	Solleveld et al. (2015)
Were the criteria for inclusion in the sample clearly defined?	No	Yes	Yes	Unclear	Yes	Unclear	Yes	Unclear
Were the study subjects and the setting described in detail?	No	Yes	Yes	Unclear	Yes	Yes	Yes	Yes
Was the exposure measured in a valid and reliable way?	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Unclear
Were objective, standard criteria used for measurement of the condition?	Unclear	Unclear	Yes	Unclear	Yes	Yes	Yes	Unclear
Were confounding factors identified?	No	Yes	Yes	Unclear	Yes	Yes	Yes	Yes
Were strategies to deal with confounding factors stated?	No	Yes	Yes	Unclear	Unclear	Yes	Yes	Yes
Were the outcomes measured in a valid and reliable way?	Unclear	Unclear	Yes	Unclear	Yes	Yes	Yes	Yes
Was appropriate statistical analysis used?	Unclear	Yes	Yes	Unclear	Unclear	Yes	Yes	Yes
	Alshail et al. (2016)	Botelho et al. (2021)	Gallagher et al. (2018)	Gay-Scoda, 2012	Kragt et al. (2019)	Needleman et al. (2013)	Needleman et al. (2016)	Solleveld et al. (2015)
Overall evaluation	High risk of bias	Some concerns	Some concerns	Some concerns	Some concerns	Some concerns	Some concerns	Some concerns

After analysing the checklist domains, an overall statement adapted for this review was written. If “yes” was selected for all domains, the study was labelled as having a “low risk of bias.” If one or two criteria were marked as “unclear,” the study was labelled as showing “some concerns.” The study was labelled as having a “high risk of bias” if “no” was applied to at least one domain or if “unclear” statements were used to multiple parts in a way that resulted in a low-confidence result in the outcome.

Quantitative synthesis

RevMan software (Review Manager, version 5.3, The Cochrane Collaboration; Copenhagen, Denmark) was used to analyse the extracted data to determine the relationship between periodontal disease and self-perceived sports performance measured by the oral impact on daily performance (OIDP) questionnaires. The presence of periodontal disease (events) was investigated in a meta-analysis, and the total number of participants in the case (performance effect) and control (no performance effect) groups were included in determining the odds ratio (OR) with the 95% confidence interval (CI). Random-effects models would be used if the studies were not methodologically equivalent (Borenstein et al., 2021). The meta-analysis aimed to generalize the findings, and heterogeneity was assessed using the I² index. If the heterogeneity was high or considerable, implicating many differences among studies’ methodologies, participants, risk of bias, or outcomes measurements (Chang et al., 2022); sensitivity analyses were performed to assess and validate the influence of individual studies or groups of studies on the pooled results (50%–100%) (Higgins et al., 2016). A funnel plot was created, if appropriate, to indicate a possible publication bias. Only papers with a “low risk of bias” or “some concerns” were considered in the quantitative analysis. If any selected papers had omitted part of the information needed for the meta-analysis, the authors were contacted and asked to provide missing data.

Quality of evidence assessment

The quality of the evidence (certainty in the estimates of effect) for the outcome “periodontal disease impact on performance” was determined using the GRADE approach (Ryan & Hill, 2016), in which observational studies begin with moderate quality of evidence and the quality of, or certainty in, the body of evidence decreases to low or very low quality if serious or very serious issues, such as risk of bias, inconsistency, or indirectness, are identified. Furthermore, if the magnitude of the effect is high or very large, or if the effect of all conceivable confounding factors is to lower the effect or suggest a spurious effect, the quality of the evidence can be improved. Consequently, the quality of evidence can range from very low to high.

Results

Study selection and characteristics

Of the 793 references identified in the database searches, 258 duplicates were removed. After reading the titles and abstracts, 521 of the remaining 535 references were excluded based on the eligibility criteria; thus, 14 references were selected for full-text appraisal. Subsequently, one study was excluded since it evaluated police officers (Hoppe et al., 2017), three were excluded since they did not include periodontal evaluations (Mendes et al., 2012; Solleveld et al., 2018; Suzuki & Toyoda, 2015); and two were excluded since they performed an assessment of Olympic athletes without a performance evaluation (Opazo-García et al., 2021; Oredugba & Perlman, 2010) (See Supplementary file 3). Finally, eight articles were eligible for qualitative evaluation (Figure 1).

Figure 1. PRISMA flow chart of study selection.

Results of individual studies

Eight cross-sectional studies were included in this meta-analysis. The relationship between periodontal disease and sports performance was demonstrated in six studies (Alshail et al., 2016; Botelho et al., 2021; Gallagher et al., 2018; Gay-Escoda et al., 2011; Needleman et al., 2016; Solleveld et al., 2015). However, two studies found no association between periodontal disease parameters and sports performance or injuries (Kragt et al., 2019; Needleman et al., 2013). The participants’ ages ranged from 16 to 47 years. Three studies analysed national athletes before or during competitions in various sports, including track and field, boxing, hockey, swimming, water polo, judo, volleyball, shooting, football, weightlifting, fencing, archery, handball, beach volleyball, taekwondo, wrestling, cycling, basketball, canoeing, gymnastics, equestrian, sailing, table tennis, rowing, and badminton (Kragt et al., 2019; Needleman et al., 2013).

One study evaluated practitioners of athletics, track and field, gymnastics, cycling, swimming, rowing, sailing, football, rugby/sevens, and hockey (Gallagher et al., 2018). Finally, five studies only evaluated soccer athletes (Alshail et al., 2016; Botelho et al., 2021; Gay-Escoda et al., 2011; Needleman et al., 2016; Solleveld et al., 2015).

The clinical and oral health/periodontal parameters reported in the selected studies were: probing pocket depth (PPD), bleeding on probing (BOP), Löe and Silness gingival index (GI), community periodontal index and treatment needs (CPITN), basic periodontal examination (BPE), and self-reported gum problems. Primary features of periodontal assessment are bleeding on probing (BOP) and clinical attachment loss (CAL). Then, only one study did not evaluate periodontal disease with more precision since its used self-report gum problems (Solleveld et al., 2018). All indexes reported have the evaluation of CAL and BOP. For sports performance assessment, studies focused in two major features: 1 - physiological variables such as serum levels of creatine kinase (CK) and medical records of extrinsic and intrinsic injuries, and 2- Questionnaire instruments to highlight how oral health problems affects performance and quality of life (OIDP questionnaire) and also self-reported questionnaire scores about repeated exercise-associated muscle cramps (REAMC), muscle or tendon reinjury (MTR), and other multiple types of injuries.

For performance analysis, the studies investigated serum CK levels, muscle and articular injuries, increased risk for damages, and a range of self-reported OIDP questionnaires. Therefore, some studies demonstrated that periodontal disease is associated with higher levels of serum CK (Alshail et al., 2016), muscle injuries (Gay-Escoda et al., 2011), self-reported sports performance impact (Gallagher et al., 2018), and risk of injuries (Solleveld et al., 2015). Regarding the type of sport, soccer showed relationships with periodontal disease possibly because it was the major sport evaluated (Alshail et al., 2016; Botelho et al., 2021; Gay-Escoda et al., 2011; Needleman et al., 2016; Solleveld et al., 2015). Olympic sports did not show such associations, but the authors reported limitations related to the low response rate of participants and participant sampling for medical assistance care (Kragt et al., 2019; Needleman et al., 2013).

Methodological quality of studies

Six of the eight studies identified a relationship between periodontal disease and athletic performance (Alshail et al., 2016; Botelho et al., 2021; Gallagher et al., 2018; Gay-Escoda et al., 2011; Needleman et al., 2016; Solleveld et al., 2015). Most problems among studies were related to sampling methods, clear description of eligibility criteria, clear description of study participants, the validity of condition measurements, and cofounding factor management. Regarding sampling methods, one study selected participants who needed dental healthcare during competitions (Needleman et al., 2013). Four studies recruited participants through questionnaires sent to sports organizations (Gallagher et al., 2018; Kragt et al., 2019; Needleman et al., 2016; Solleveld et al., 2015). Two studies selected a sample from a single sports organization (Botelho et al., 2021; Gay-Escoda et al., 2011). Additionally, one study did not describe the sampling method (Alshail et al., 2016).

In terms of eligibility criteria, the major problem was the lack of additional criteria and being an athlete (Alshail et al., 2016; Gay-Escoda et al., 2011; Needleman et al., 2013; Solleveld et al., 2015). No clear description of the participant’s demographic characteristics was provided in the two studies (Alshail et al., 2016; Gay-Escoda et al., 2011). One study raised concerns about the periodontal condition and performance measurement due to considering only self-reported data without clinical evaluation (Solleveld et al., 2015). Performance measurement concerns were related to a few outcome measurements without properly identifying confounding factors (Alshail et al., 2016; Gay-Escoda et al., 2011). A low response rate was verified in one study (Kragt et al., 2019).

Risk of bias

The quality of the measurements reported in each study is presented in Table 2. One study was considered to have an increased risk of bias (Alshail et al., 2016). As mentioned above, some issues related to sampling methods, clear description of eligibility criteria, clear description of study subjects, validity of condition measurements, and cofounding factor management reduced the quality of the generated evidence. The other seven included studies were classified as having some concerns.

Quantitative analysis of studies

Three studies concerning the overall evaluation were included for quantitative synthesis (Gallagher et al., 2018; Needleman et al., 2013, 2016). The other five studies were excluded because they used different performance evaluations. The same group published two studies (Needleman et al., 2013, 2016). However, they were considered eligible because different athlete populations were evaluated. Thus, the sample overlap hypothesis was discarded. The majority of athletes presented a BPE score 1 and 2 ranging 50% to 83% of the research samples(gingivitis and mild periodotitis). Needleman et al. (2013) reported 74.0% (97/131) of athletes with BPE score 1 or 2 without effects on performance and 77.1% (101/131) of athletes with BPE score 1 or 2 with effects on performance. The study of Needleman et al. (2016), 80.9% (72/89) of athletes with BPE score 1 or 2 without effects on performance and 83.0% (73/88) of athletes with BPE score 1 or 2 with effects on performance.

Gallagher et al. (2018) showed that 50% (134/268) of athletes with BPE score 1 or 2 have impact on performance.

The meta-analysis showed reduced heterogeneity (I² = 0%) and no statistical significance (p = 0.55); thus, no sensitivity analysis was conducted. A negative self-report of athletic performance (participation, experience of pain, training volume/quality reduction) was identified in 72.5% of athletes with periodontal disease (240 out of 331) in comparison with 60.1% of those (238/396) without periodontal disease. Therefore, a positive association was observed among the analysed factors (OR = 1.55; 95% CI 1.04–2.31; p = 0.03; I2 = 0%). Periodontal disease status was significantly associated with increased odds of negative effects on sports performance (Figure 2). This evidence was considered moderate (Table 3).

Figure 2. Forest plot reporting the association of periodontal disease with self-perceived reduction of sports performance according to the OIDP questionnaire.

Table 3. Summary of findings for the influence of periodontal disease on athletic daily performance.

Certainty assessment							№ of patients		Effect		Certainty	Importance
№ of studies	Study design	Risk of bias	Inconsistency	Indirectness	Imprecision	Other considerations	Effect on performance	No Effect on performance	Relative (95% CI)	Absolute (95% CI)
Periodontal disease impact on athletic daily performance (assessed with: Oral Impacts on Daily Performance (OIDP) questionnaire)
3	observational studies	not serious	not serious	not serious	not serious	all plausible residual confounding would reduce the demonstrated effect	240/331 (72.5%)	238/396 (60.1%)	OR 1.55 (1.04 to 2.31)	99 more per 1.000 (from 9 more to 176 more)	⊕⊕⊕◯ Moderate	4 -IMPORTANT

CI: Confidence interval.

Summary of findings and level of evidence

Findings derived from the meta-analysis of self-perceived performance reduction associated with periodontal disease in athletes (Table 3). The low heterogeneity among the studies (I² = 0%) indicated low inconsistency in the GRADE analysis. The absolute and relative effects of performance analysis, absence of possible publication bias, absence of serious problems among evaluation domains, and reduced influence of distortions yielded moderate evidence for the outcomes. However, the presence of potentially confounding factors may lead to a reduction in estimated effects.

Discussion

This review analysed the relationship between periodontal disease and sports performance, and the findings suggest an association between them, particularly in terms of self-perceived reductions in performance during training and competitions. The hypothesis under study relates to the fact that periodontal disease elicits a systemic inflammatory status, which could affect sports performance. Nevertheless, it needs to be highlighted that good standards of oral hygiene and periodontal health are rare (up to 70% in some studies), and six of the eight articles showed an association between periodontal disease and sports performance (Alshail et al., 2016; Botelho et al., 2021; Gallagher et al., 2018; Gay-Escoda et al., 2011; Needleman et al., 2016; Solleveld et al., 2015). Performance reduction dimensions included difficulty participating in routine training, reduction of training volume, and pain experience according to the OIDP questionnaires applied in three studies (Gallagher et al., 2018; Needleman et al., 2013, 2016). At least one of these dimensions was linked to periodontal disease.

Performance analysis comprehends an area of sport science concerned with actual sports performance in training and competitions, but also evaluates technical, physical and psychological aspects gathered in athlete’s capacities (O’Donoghue, 2009). The nature of performance analysis is complex due to the diversity of sports and their implications on athletes' health. Many measurements entail different impacts in performance dimensions. Fatigue variables may negative impact motor skills but also muscle recovery (Landers-Ramos et al., 2022; Mougios, 2007). Thus, due to the diversity of variables involving high-performance physical training and the multifactorial aspect of periodontal disease (Hecksteden et al., 2018; Meyle & Chapple, 2015), other associations should be carefully evaluated. These include changes in biochemical markers of muscle injury (CK) (Alshail et al., 2016; Gay-Escoda et al., 2011), increase in fat mass, reduction in muscle mass (Botelho et al., 2021), and prevalence of recurrent injuries (Solleveld et al., 2015). These associations should be taken into consideration, as they could also have an impact on athletic performance.

The relationship between physical activity and exercise and periodontal disease has been studied, and moderate physical activity has been associated with a reduction in the prevalence of periodontal disease (Ferreira et al., 2019). Individuals who engage in moderate physical activity or exercise for 30 to 150 min per week have a decreased risk of periodontal disease occurrence (Ferreira et al., 2019). The potential causes of this link could be related to inflammatory mediator regulation (IL-1b, IL-6, TNF-α, IL-10) or the behavioural changes related to self-care that promote a healthier lifestyle (e.g., adequate oral hygiene) (Al-Zahrani et al., 2005). However, athletes differ from the general population because of their high physical and psychological function levels and perceived health (Swann et al., 2015). Because athletes frequently engage in high-intensity training, periodontal disease may play a different role in triggering deficits in sports performance, such as an increased risk of injuries (Solleveld et al., 2015). Thus, a two-way relationship may exist between periodontal disease and sports performance.

Periodontal disease is a multifactorial condition characterized by a significant inflammatory profile of periodontal tissues, which is caused by the interaction of bacterial pathogens, host response, genetic factors, environmental factors, and personal health habits (Chapple et al., 2018). Multiple potential molecular processes involving cytokines, such as IL-1b, IL-6, IL-8, and TNF-α, are involved in periodontal disease. Increased levels of Il-6 and IL-8 play pivotal roles in matrix metalloproteinase-2 (MMP-2) activation by fibroblasts, leading to the degradation of gingival fibres and periodontal ligaments in periodontal disease (Cekici et al., 2014; Chapple & Matthews, 2007; Hajishengallis et al., 2020).

These cytokine functions result from the fight against the primary periodontal pathogens in an attempt to overcome bacterial challenges, but they are also related to high-intensity exercise (Cerqueira et al., 2020). Increased IL-6 and IL-8 levels were observed after moderate exercise. The concentration of IL-6 ranged from 1 to 4 times and from 1.5 to 26.79 in high-intensity exercises immediately after training execution, while IL-8 concentrations may vary from 1.37 to 2.77 times after high-intensity exercise compared to baseline levels (Cerqueira et al., 2020). Chronically increased levels of IL-6 and IL-8 are reported to be associated with fatigue (Silva et al., 2018), which is a severe risk factor for muscle injuries and leakage of CK (Ament & Verkerke, 2009).

Other important cytokines with similar roles in exercise and PD are IL-1β and TNF-α. Increased levels of these cytokines were found in intense exercise with predominant eccentric movements but not after moderate exercise (Cerqueira et al., 2020). IL-1β and TNF-α are potent proinflammatory cytokines that influence adhesion molecules and chemokines and are possibly related to leukocyte migration and function, especially osteoclast bone resorption in PD (Cekici et al., 2014; Meyle & Chapple, 2015). Thus, the inflammatory mediators shared by PD and high-intensity exercise could be related to an increased risk of fatigue, repeated muscle injuries, and potential aggravation of both PD and muscle function, consequently causing plasma leakage of CK (Alshail et al., 2016; Gay-Escoda et al., 2011; Silva et al., 2018; Solleveld et al., 2015).

CK is a protein involved in muscle metabolism (Baumert et al., 2016). The CK content is commonly used as a stress indicator and is regarded as a semi-quantitative indicator of muscle fibre injury (Baumert et al., 2016). Reference intervals of CK in athletes was previously published (Mougios, 2007) establishing parameters to identify normal values in sports practicing. Nevertheless, intervals of CK may differ considering the sport type and also the level of inflammation (Landers-Ramos et al., 2022). Thus, the upper limits of CK in a specific sport should be evaluated since their might increase risk for overexertion or injury (Mougios, 2007).

Although one of the studies showed a correlation between CK content and periodontal evaluation parameters such as BOP and PPD in soccer players’ dental evaluation (Alshail et al., 2016), serum CK levels can vary based on demographic factors such as age, sex, race, habits, and exercise style. Therefore, multivariate analysis is recommended to assay the actual effect of PD on CK levels. We also noted that the type of sport, such as soccer, may serve as another cofounding factor since eccentric exercise produces more significant muscle injury than concentric exercise, even at the same intensity (Baumert et al., 2016). Despite the biological mechanisms and other associations between PD and muscle injuries, further studies are needed to establish evidence of a real relationship between these events.

An important consideration while evaluating these findings is that observational studies cannot clarify causality. However, with plausible mechanisms, associations between exposure and outcomes should receive attention from the scientific community. Periodontal diseases are chronic noncommunicable diseases (Papapanou et al., 2018). These diseases share risk factors and indicators; therefore, common risk approaches are recommended (Meyle & Chapple, 2015). A healthy lifestyle should include good standards of oral hygiene, which will eventually influence the impacts of periodontal disease occurrence and severity (Al-Zahrani et al., 2005; Julie; Gallagher et al., 2019).

A quantitative synthesis of three studies showed that self-perceived reduction in performance analysed by the OIDP questionnaire was associated with PD (p = 0.03). Little heterogeneity (I2 = 0%) and non-serious issues of inconsistency, indirectness, risk of bias, and imprecision after the GRADE assessment of evidence led to a 1.5-fold increased risk of sports performance decline in athletes (Ryan & Hill, 2016). However, caution is needed when interpreting the pooled results, as dichotomous variables require more events to establish a relationship (Ryan & Hill, 2016). Furthermore, despite the relationship of self-reported decreased performance and periodontal disease, the univariate models only depict a possible effect between conditions among several other influences on the athlete’s routine and the pathogenesis of the periodontal disease (McKay & Verhagen, 2016; Meyle & Chapple, 2015). Poor periodontal health can affect athletes’ ability to compete, so the evidence is considered moderate and relevant (Ryan & Hill, 2016). Any changes in training volume, absences, or painful experiences can harm athletes, their teams, and investors (McKay & Verhagen, 2016).

Based on the review’s findings, athletes with periodontal disease should maintain good oral hygiene, seek treatment, be aware of potential performance reductions, and evaluate other possible associations. Those athletes should include regular brushing and flossing, as well as regular visits to the dentist. Besides, they should be aware of potential performance reductions, such as difficulty participating in routine training, reduction of training volume, and pain experience. These reductions could be linked to periodontal disease and impact overall sports performance. To support this, several studies have emphasized the importance of maintaining good oral hygiene and seeking treatment for periodontal diseases, such as Needleman et al. (2016), who discovered a link between periodontal disease and sports performance, and Alshail et al. (2016) who found that periodontal disease can alter biochemical markers of muscle injury. Additionally, Ferreira et al. (2019) found that moderate physical activity can reduce the prevalence of the periodontal disease.

A significant limitation of this review was that only observational studies were included in the search strategy. Thus, the selected studies did not employ random allocation and group-matching methods to reduce bias. Furthermore, even though six studies showed a relationship between PD and decreased performance and another three found a link between the two conditions, several limitations of these studies require consideration. Most studies did not examine the prevalent confounding factors for PD (e.g., smoking, and glycaemic status) by using multivariate analyses. Also, one study used self-report of gum problems to establish periodontal status instead of bleeding on probing (BOP) and clinical attachment loss (CAL), some of primary features of periodontal evaluation (Chapple et al., 2018; Papapanou et al., 2018). Health research involving athletes should consider a specific definition when recruiting participants that may represent this population (Handelsman, 2016; Hecksteden et al., 2018). Discrepant results in evaluating the effects of risk factors or implemented treatments can be avoided by implementing defined eligibility criteria, which can generate fewer indirect results (Hecksteden et al., 2018; Schisterman et al., 2009). However, considering different aspects of sports practice, the great variability in sports results in different physiologies related to the athlete’s biotype and oxygen consumption (Baumert et al., 2016). Thus, the influence of aerobic, anaerobic, strength, and endurance sports implies an increase in variables that can influence the evaluation of the results (Powers et al., 2016).

In addition to the significant variability across different types of sports, the use of self-reported questionnaires for periodontal evaluation and assessment of sports performance may have influenced the survey results because many studies used questionnaires with weak reliability and validity (Gallagher et al., 2017). Thus, epidemiological studies on the relationship between PD and sports performance require an accurate assessment of both conditions (Schisterman et al., 2009). Nevertheless, an important point to consider is that research linking sports practice and periodontal evaluation is inherently challenging (Hecksteden et al., 2018; Oppermann et al., 2015), with the following aspects being particularly notable: difficulties in obtaining participants who meet specific eligibility criteria (Hecksteden et al., 2018), yielding reduced sample sizes; the cost and time constraints associated with the large-scale application of methods used in sports or periodontal evaluation (McKay & Verhagen, 2016), such as VO₂max measurements and complete periodontal assessments (Oppermann et al., 2015), which are impractical in certain situations; and finally, athlete and technical team compliance and adherence to activities outside the training routine (McKay & Verhagen, 2016). As a result, there is uncertainty about the available evidence, necessitating additional studies using robust methodologies to reduce biases.

Conclusions

Within the limitations of this review, the findings revealed an association between PD and a self-perceived decrease in sports performance in elite athletes. We highlight the importance of preventive dental care, including engagement of athletes in oral health behavioural changes and developing periodontal treatment programmes to reduce the possible risks associated with athlete health. Further studies with larger sample sizes, assessment of confounding factors, and objective evaluations of PD and sports performance are needed to clarify the actual effect of both conditions. Considering the evidence of an association, randomized clinical trials to assess this two-way relationship are warranted.

Acknowledgements

The authors would like to thank the Federal University of Pará, Federal University of Rio de Janeiro, University of Alberta and Federal University of Rio Grande do Sul for technical and scientific support.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15438627.2023.2235048

Additional information

Funding

We are thankful for the partial financial support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) and Pro Rectory of Post-graduation and Research of UFPA (PROPESP-UFPA). RRL is a researcher from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and received grant under number - 312275/2021-8. The funders had no role in study design, decision to publish or manuscript elaboration.